DECEMBER 2023

IDA RESULTS
MEASUREMENTSYSTEM
INDICATOR METHODOLOGY CODEBOOKINTERNATIONAL DEVELOPMENT ASSOCIATIONWORLD BANK GROUP

Contents
INTRODUCTION ........................................................................................................................................ 5
TIER 1 INDICATORS ................................................................................................................................. 6
Population living on less than $2.15 a day ............................................................................................ 7
Median growth rate of consumption/income per capita of the bottom 40 percent ........................... 9Countries with growth concentrated in the bottom 40 percent ........................................................ 11
Gini Index (median) .............................................................................................................................. 13
CO2 Emissions ....................................................................................................................................... 15Countries without wealth depletion..................................................................................................... 17Countries without natural capital wealth depletion .......................................................................... 20
Average annual deforestation change ................................................................................................. 22
Marine protected areas......................................................................................................................... 24
Legal changes that support gender equality ....................................................................................... 26
Ratio of female to male labor force participation rate ...................................................................... 29
Maternal mortality ratio ...................................................................................................................... 32
Proportion of births attended by skilled health personnel ................................................................ 34
Contraceptive prevalence by modern methods .................................................................................. 36
Adolescent fertility rate ........................................................................................................................ 38
Refugees by country or territory of asylum........................................................................................ 40
Internally displaced persons, total displaced by conflict and violence ............................................. 43
GDP per person employed ................................................................................................................... 46
Non-agriculture sectors, value added .................................................................................................. 48
Annual growth rate of real GDP per capita ....................................................................................... 50
Proportion of population with access to electricity ............................................................................ 53
Youth employment to population ratio (age 15-24) ........................................................................... 55
Women (%) ......................................................................................................................................... 55
Men (%) .............................................................................................................................................. 55
Proportion of adults (15 years and older) with an account at a bank or other financial institution
or with a mobile money service provided ........................................................................................... 58
Proportion of adults (15 years and older) with an account at a bank or other financial institution
or with a mobile money service provided, bottom 40% .................................................................... 60

1

Prevalence of stunting among children under 5 years of age............................................................ 63
Under-5 mortality rate ......................................................................................................................... 65
Incidence of HIV ................................................................................................................................... 67
Population of children who cannot read by end-of-primary-school age .......................................... 69
Lower secondary gross completion rate & Ratio of girls’ to boys’ completion rate ....................... 72
Lower secondary enrollment rate & Ratio of girls’ to boys’ enrollment rates ............................... 74
People using basic drinking water services......................................................................................... 76
People using basic sanitation services ................................................................................................. 78
IDA countries with low or moderate risk from unsustainable debt ................................................. 80
IDA countries with improved budget reliability, transparency of public finances, and control inbudget execution.................................................................................................................................... 82
Statistical Performance Indicators ...................................................................................................... 85
IDA countries with increased tax fairness and progressivity............................................................ 88
Unweighted average increase in tax-to-GDP ratio in at least those IDA countries with tax
revenues below 15 percent of their GDP for three consecutive years .............................................. 91
Individuals using the internet in IDA countries ................................................................................. 93
Prevalence of undernourishment in IDA countries ........................................................................... 95
TIER 2 INDICATORS ............................................................................................................................... 97
Generation capacity of renewable energy ........................................................................................... 98
Net GHG emissions ............................................................................................................................. 100
People provided with access to clean cooking .................................................................................. 102
IDA countries supported to implement and/or update their NBSAPs ........................................... 104
IDA countries with completed Country Climate Development Reports (CCDRs) ....................... 106
IDA-FCS supported in building capacity to use field-appropriate digital open-source tools forcollection and analysis of geo-tagged data, and apply this technology to enhance project
implementation and coordination...................................................................................................... 108
Farmers adopting improved agricultural technology ...................................................................... 111
Area provided with new/improved irrigation or drainage services ............................................... 114
People provided with new or improved electricity service .............................................................. 117
Beneficiaries reached with financial services supported by World Bank operations ................... 120
Persons that benefitted from financial services supported by World Bank operations ..................... 120
Businesses that benefitted from financial services supported by World Bank operations ................ 120
2

Beneficiaries in IDA countries of job-focused interventions ........................................................... 123
People with enhanced access to transportation services .................................................................. 125
People provided with improved urban living conditions................................................................. 128
Beneficiaries of social safety net programs ....................................................................................... 130
People who have received essential health, nutrition, and population services............................. 134
Children Immunized (million) .......................................................................................................... 134
Women and children who have received basic nutrition services (million) ..................................... 134
Deliveries attended by skilled health personnel (million)................................................................. 134
COVID-19 vaccine doses administered ............................................................................................. 137
Large-scale assessments completed at primary or secondary level ................................................ 139
People provided with access to improved water sources ................................................................. 142
People provided with access to improved sanitation services ......................................................... 145
IDA countries publishing annual and timely public debt reports .................................................. 148
IDA countries provided statistical capacity building support by the WBG for the implementationof household surveys ........................................................................................................................... 150
Countries collecting disability data with IDA support .................................................................... 152
People provided with enhanced access to broadband internet ....................................................... 154
Countries supported toward institutionalizing disaster risk reduction as a national priority with
IDA support ......................................................................................................................................... 157
Countries integrating adaptive social protection into national systems with IDA support ......... 159
Satisfactory outcomes of IDA Country Partnership Frameworks ................................................. 161
Satisfactory outcomes of IDA operations.......................................................................................... 163
As a share of commitments ............................................................................................................... 163
As a share of operations .................................................................................................................... 163
Advisory Services and Analytics (ASA) objectives accomplished .................................................. 166
Client feedback in IDA countries on WBG effectiveness and impact on results ........................... 168
Client feedback in IDA countries on WBG knowledge ................................................................... 170
TIER 3 INDICATORS ............................................................................................................................. 172
IDA Budget Anchor ............................................................................................................................ 173
Bank Budget to Portfolio Volume Ratio (per $ billion under supervision) ................................... 175
Average cost of IDA supervision projects (implementation support) ............................................ 177
Share of climate co-benefits over total commitments in IDA-supported operations .................... 179
3

Share of adaptation co-benefits over total climate co-benefits in IDA-supported operations ..... 182
Total private mobilization of WBG-supported operations/transactions in IDA countries .......... 185
Direct Mobilization ........................................................................................................................... 185
Indirect Mobilization ........................................................................................................................ 185
IDA countries with the lowest Human Capital Index supported to improve the sustainability ofhuman capital financing ..................................................................................................................... 187
IDA $ commitments with disaster risk management co-benefits ................................................... 190
Satisfactory Bank performance in IDA-financed operations.......................................................... 193
Overall............................................................................................................................................... 193
At entry ............................................................................................................................................. 193
During supervision ............................................................................................................................ 193
Quality of M&E in IDA-financed operations ................................................................................... 196
IDA20 projects with an AA Resilience Rating ................................................................................. 198
Percentage of IDA operations with substantial climate co-benefits including at least one climatechange indicator in the results framework ....................................................................................... 201
Percentage of IDA-supported projects that demonstrate a results chain by linking gender gaps
identified in analysis to specific actions that are tracked in the results framework ..................... 203
Disbursement ratio.............................................................................................................................. 205
Proactivity Index ................................................................................................................................. 207
IDA-supported operations that address and respond to gender-based violence (GBV) .............. 209
Country programs (SCDs and CPFs/CENs) informed by diagnostics on crisis preparedness .... 211
Facetime index in FCS ........................................................................................................................ 213
Share of IDA IPF operations that applied the concept of universal access at design ................... 215
Countries supported by IDA to take IFF-related actions................................................................ 217
Client feedback on WBG on responsiveness and staff accessibility ............................................... 220
Client feedback on WBG on collaboration with other donors ........................................................ 222
Projects with beneficiary feedback at design.................................................................................... 224

4

INTRODUCTION
The International Development Association (IDA) is one of the largest sources of assistance for theworld’s poorest countries. IDA currently consists of 75 countries, 39 of which are in Africa. Overseen
by 173 shareholder nations, IDA aims to reduce poverty by providing credits and grants for programs that
boost economic growth, reduce inequalities, and improve people’s living conditions.
The IDA Results Measurement System (IDA RMS) tracks results in countries supported by IDA.
The World Bank Group (WBG) introduced the RMS with the IDA13 Replenishment (July 2002). It was
the first multilateral development institution to develop a framework of quantitative indicators to monitor
aggregate results. The RMS serves as a key reporting and accountability tool for tracking progress andcommunicating results achieved by IDA during each replenishment cycle. It is an integral part of theWorld Bank’s efforts to improve the focus on results. The IDA RMS is updated on an annual basis andpublicly disclosed on IDA’s website and the Bank’s results page.
The current RMS uses a three-tiered development results framework with 95 indicators to track
results of IDA countries at an aggregate level. Tier 1 indicators report on long-term development
outcomes and the broader context of countries in which IDA operates. Progress in Tier 1 indicators is notdirectly attributed to IDA’s interventions; rather it is the outcome of collective efforts by countries andtheir development partners. Tier 2 indicators track development results in countries supported by IDA
operations. These largely draw on net progress values extracted from project-level Implementation Status
and Results Reports (ISRs) and Implementation Completion and Results Reports (ICRs) to assess WBG
contributions to major areas of intervention. Tier 3 indicators track IDA’s operational and organizational
effectiveness. This includes indicators tracking the performance of IDA’s portfolio, the quality andtimeliness of projects delivered to clients, the results orientation of the operations, client and beneficiary
feedback, financial sustainability, and the implementation of the five IDA Special Themes.
The IDA20 RMS is the most ambitious results framework in IDA’s history, tracking a broad arrayof both contextual and outcome-oriented indicators. The IDA20 RMS includes 15 new indicators in
key strategic areas, such as climate change and crisis preparedness. It also has higher performancestandards across indicators, compared to previous cycles. Additionally, for the first time, the RMS is
publishing a compiled codebook outlining indicator definitions, data sources, calculation methodologies,
and potential limitations. The codebook provides as a means of ensuring greater transparency andaccountability in reporting, serving as a living document that will be updated as methodologies anddefinitions are improved. This will ultimately improve the reliability of indicators and generate moreconsistent data related to IDA’s main areas of focus.

5

TIER 1 INDICATORS

6

Population living on less than $2.15 a day
A. Overview
Indicator namePopulation living on less than $2.15 a day (%)

Definition(as it should appear on thedigital IDA RMS card)

Percent of the population living on less than US$2.15 a day at 2017PPP dollars.
Aggregation is average, weighted by the total population. Data are reported for all IDA
eligible countries (including blend countries) in a reporting fiscal year.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG Indicator 1.1.1: Proportion of population below the international poverty line, by sex,age, employment status and geographical location (urban/rural)

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Percent of Population☒ FCS1☐ Females

Calculation method

NA

Typically, numbers are updated before spring meetings, but it could be another update
before annual meetings
1.
2.

3.
Data Calculation Method

4.

5.

A Reporting Year is selected. The reporting year is the calendar year minus 2.
Thus, in this incoming 2023, the Bank will report poverty estimations for 2021.
Per capita welfare aggregates are estimated for all countries for their latest
available surveys. The daily per capita welfare aggregates are estimated for thelates available survey for each country. Then, these aggregates are deflated to 2017
prices and then deflated again to PPP levels.
Per capita welfare aggregates are forecasted to the Reporting Year. Due to not
all countries have household surveys each yea, the daily per capita welfare
aggregate must be forecasted to the Reporting Year. To do so, the daily per capita
welfare aggregates at US@2107 PPP are forecasted by using the changes of the
GDP per capita from the survey year to the Reporting Year. This is called the“Line-up welfare aggregate”.
Next, an estimate the poverty rate for each country for the Reporting Year ismade. The poverty rate is estimated by comparing the Line-up Welfare aggregatewith the US$2.15 at 2017PPP line. Those below this line are considered poor.
Finally, the aggregation for IDA countries is created. To do so, the estimatedpoverty rates for each country at the reporting year are aggregated using population
projection to the Reporting Year published by UN.

1

FY23 List of Fragile and Conflict-affected Situations: https://thedocs.worldbank.org/en/doc/69b1d088e3c48ebe2cdf451e30284f040090082022/original/FCSList-FY23.pdf

7Note:
This indicator is estimated with about 60% of countries reported household surveys
in the last 5 years. The rest have a longer forecasted estimation.
Data Source(s)Estimation consistent with lineup poverty estimations used for the global a regional poverty
estimation by the Poverty and Inequality Platform.

C. Key counterparts
Contributing
PGs/GPs/Regions

Regional Stats Teams in Poverty Global Practice, Poverty and Inequality Platform

D. Additional information
Harmonization withother corporate reporting
mechanisms:

The WBG Corporate Scorecard

Limitations andExceptions

Lack of annual available data is still a challenge. This indicator is estimated with about 60%
of all IDA countries with available data in the last 5 years. The rest are forecasted for longer
periods.

Date methodology
agreed/updated

The estimations are consistent with the forecasted poverty estimation made by
POVCALNET to measure global and regional poverty estimations.

8Median growth rate of consumption/income per capita of the bottom 40 percent
A. Overview
Indicator nameMedian growth rate of consumption/income per capita of the bottom 40 percent (%)

Definition(as it should appear on thedigital IDA RMS card)

Median growth rates of average real per capita expenditure or income of the bottom 40% of
every country’s population. Aggregation is an unweighted average. Data reported
worldwide for all IDA countries with available data, which requires 2 comparable surveys
in the selected period. Countries without 2 comparable surveys in (roughly) 5 years spell are
not included in the estimation.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG Indicator 10.1: By 2030, progressively achieve and sustain income growth of thebottom 40 percent of the population at a rate higher than the national average.

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Percent☒ FCS☐ Females

Calculation methodNA

The indicator is updated every spring and every second fall in years when there is no
Poverty and Shared Prosperity Report (PSPR) launched.
1.

2.

Data Calculation Method
3.

Identify (or create) two comparable welfare aggregates within a roughly 5year spell. Data uses actual survey results which are typically 5 years apart (+/-2
years). If the welfare aggregate of those two data points is not comparable, theteam uses custom methods (depending on the survey questions) to make themcomparable.
Estimate the average annual growth of the bottom 40 percent and the overall
population. The annual growth is calculated by estimating a geometric mean
between the start year and end year within roughly a 5-year spell (+/-2 years). Thisis done for the bottom 40 percent of the population and for the overall population
separately.
Estimate the median growth of B40 for all countries. Using the bottom 40
growth of all countries where the indicator can be calculated, including countries
with negative growth rates, the median is taken.

Note:
Finding comparable welfare aggregate is a challenge for IDA countries. Barely
40% of the countries are included in this estimation.

9

Data Source(s)Comparable welfare aggregates from household survey in the Global Monitoring Database(GMD). GMD includes the raw survey data that is used to calculate indicators reported in
the Poverty and Inequality Platform (PIP).

C. Key counterparts
Contributing
PGs/GPs/Regions

The Poverty and Equity Global Practice Regional Statistics Teams

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

This estimation is prepared with an average of 40% of all IDA countries that havecomparable welfare aggregates based on actual survey results. Because estimates are notused to calculate welfare aggregates for countries without actual survey results, the data is
not fully representative of all IDA countries.

Date methodology
agreed/updated

2015

10

Countries with growth concentrated in the bottom 40 percent
A. Overview
Indicator nameDefinition(as it should appear on thedigital IDA RMS card)

Countries with growth concentrated in the bottom 40 percent (%)
Percent of countries for which growth in average (mean) real per capita income of thebottom 40% is positive and greater than growth in average (mean) real per capita income of
the total population.
Growth rates are annualized over a time interval of roughly five years. Data reported
worldwide for all IDA countries with 2 comparable surveys in the selected period. Countries
without 2 comparable surveys in (roughly) 5 years spell are not included in the estimation.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG Indicator 10.1: By 2030, progressively achieve and sustain income growth of thebottom 40 percent of the population at a rate higher than the national average.

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Percent☒ FCS☐ FemalesNA

The indicator is updated every spring and every second fall in years when there is no
Poverty and Shared Prosperity Report (PSPR) launched.
1.

2.

Data Calculation Method

Calculation method3.

4.

Identify (or create) two comparable welfare aggregates within a roughly 5year spell. Countries without two comparable household surveys in a 5-year spell(+/-2 years) are not included in the estimation.
Estimate the average annual growth of the bottom 40 percent and the overall
population. The annual growth is calculated by estimating a geometric mean
between the start year and end year within roughly a 5-year spell (+/-2 years). Thisis done for the bottom 40% of the population and the overall population separately.
Identify countries with growth concentrated in the bottom 40 percent. In order
to be considered as a country with growth concentrated in the bottom 40 percent, it
must meet two criteria: (i) the country has a positive growth for the bottom 40 of
the population, and (ii) the growth on the bottom 40 is greater than the annual
growth of the overall population.
Estimate the percent of IDA countries where growth is concentrated in thebottom 40 percent. The percentage is estimated considering the number of IDA
countries with growth concentrated in the bottom 40 percent and all IDA countries
with comparable welfare aggregates in a 5-year spell (+/-2 years).

11

Data Source(s)Comparable welfare aggregates from household survey in the Global Monitoring Database(GMD). GMD includes the raw survey data that is used to calculate indicators reported in
the Poverty and Inequality Platform (PIP).

C. Key counterparts
Contributing
PGs/GPs/Regions

The Poverty and Equity Global Practice Regional Statistics Teams

D. Additional information
Harmonization withother corporate reporting
mechanisms:

The WBG Corporate Scorecard

Limitations andExceptions

This estimation is prepared with an average of 40% of all IDA countries that havecomparable welfare aggregates based on actual survey results. Because estimates are notused to calculate welfare aggregates for countries without actual survey results, the data is
not fully representative of all IDA countries.

Date methodology
agreed/updated

The shared prosperity indicator methodology was established in 2015 and has been reported
since.

12

Gini Index (median)
A. Overview
Indicator nameDefinition(as it should appear on thedigital IDA RMS card)

Gini index (median)
The Gini index measures the extent to which the distribution of income or consumption
among individuals within an economy deviates from a perfectly equal distribution. A Gini
index of 0 represents perfect equality, while an index of 100 implies perfect inequality. The
median of the Gini will be calculated as an unweighted median for all available IDA
countries with available data circa the reporting year (+/- 3 years).
This indicator is a placeholder until the World Bank determines which inequality indicator
to use for the Corporate Scorecard. At that point, this indicator will be updated/replaced tocorrespond as the IDA-version of the Corporate Scorecard inequality indicator.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG Indicator 10: Reduce inequality within and among countries

IDA20 Expected
range/value

NA

Included in IDA19

No

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Data Calculation Method

Percent☒ FCS☐ Females

Calculation method

Unit of analysis is the number of countries.

The indicator is updated every spring and every second fall in years when there is no
Poverty and Shared Prosperity Report (PSPR) launched.
1) Data selection: The latest available household survey used for welfare and poverty
estimation, circa the reporting year (+/- 3 years), is selected for each country.
2) Calculating welfare aggregates: Using the selected household survey, the daily
household per capita welfare aggregates are estimated for each country. These
aggregates are then deflated to 2017 prices using national CPI data and thendeflated for comparability across countries using 2017 PPP exchange rates.
3) Estimating the Gini index: The Gini index is estimated based on the welfare
aggregates for the selected surveys. The Gini index measures the area between theLorenz curve and a hypothetical line of absolute equality, expressed as apercentage of the maximum area under the line. A Lorenz curve plots the
cumulative percentages of total income/consumption against the cumulative
population share, starting with the poorest individual.
4) Estimating the median Gini index for IDA countries: The final step iscalculating the unweighted median of the Gini indexes for all countries classified
as IDA, in the current FY, with available data circa the reporting year.

13Note:
1.
2.

Data Source(s)The indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries
The indicator should include all the projects that are only-IDA financier type,blend-financier type (including IDA-financing), and Trust-fund financier type(including IDA-financing)Household surveys used for poverty estimation. The results are reported also in:
https://pip.worldbank.org/home

C. Key counterparts
Contributing
PGs/GPs/Regions

The Poverty and Equity Global Practice Regional Statistics Teams

D. Additional information
Harmonization withother corporate reporting
mechanisms:

WBG Corporate Scorecard

Limitations andExceptions

As noted above, this will serve as a placeholder until the World Bank Scorecard updates its
results reporting indicator for inequality. At that point, the indicator will be updated or
replaced accordingly.

Date methodology
agreed/updated

Indicator will be updated in parallel with the World Bank Corporate Scorecard.

14

CO2 Emissions
A. Overview
Indicator name

CO2 emissions (metric tons per capita)

Definition(as it should appear on thedigital IDA RMS card)

Carbon dioxide emissions are those stemming from the burning of fossil fuels and the
manufacture of cement. They include carbon dioxide produced during consumption of solid,
liquid, and gas fuels and gas flaring. Aggregation is population-weighted average. Data arereported for all IDA eligible countries, including blend countries, in a reporting fiscal year

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG Indicator 9.4.1: CO2 emissions per unit of value added

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Metric tons per capita☒ FCS☐ Females

Calculation method

NA

Annually
The per capita CO2 emissions in metric tons are calculated by dividing CO2 emissions by
midyear population.
Emissions data are sourced from the International Energy Agency (IEA) and Global Carbon
Project (GCP), covering the energy and industry sectors but excluding the land use change
and forestry (LUCF) sector—which contributes to both ways as a carbon sink and a sourceof emissions. Emissions factors, representing the amount of emissions associated withspecific activities or fuel types, are based on internationally recognized ones, such as thosefrom the Intergovernmental Panel on Climate Change (IPCC) guidelines.

Data Calculation Method

Total population accounts for all residents regardless of legal status or citizenship in
midyear. The data are sourced from the United Nations Population Division’s World
Population Prospects, etc., as listed in the source section.
Review process: WDI data are annually reviewed by country and regional teams, GPs and
CCSAs, and Executive Director Offices during the Bank-wide review, in addition to routine
sanity checks every update.
Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should

15

include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)
World Development Indicators (WDI) at http://wdi.worldbank.org/.

Data Source(s)CO2 emissions data are sourced from the Climate Watch Historical GHG Emissions. 2022.
Washington, DC: World Resources Institute. Available online at:https://www.climatewatchdata.org/ghg-emissions. Population data are sourced from (1)United Nations Population Division. World Population Prospects: 2022 Revision. (2)Census reports and other statistical publications from national statistical offices, (3)Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and
Vital Statistics Report (various years), (5) U.S. Census Bureau: International Database, and(6) Secretariat of the Pacific Community: Statistics and Demography Programme.

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

NA

Date methodology
agreed/updated

There may be methodological changes according to anticipated data source change in the
future.

16

Countries without wealth depletion
A. Overview
Indicator nameDefinition(as it should appear on thedigital IDA RMS card)

Countries without wealth depletion (%)
Percentage of IDA (inclusive of Blend) countries with positive changes in wealth per capita,
based on the ‘total wealth’ indicator produced as part of the Changing Wealth of Nations
publication and published on the World Bank’s databank. Changes in total wealth per capita
is a leading indicator of sustainability and measures the changes in the sum of assets whichyield an economic benefit over time. The four main asset categories are produced capital(machinery, structures, equipment, and urban land), human capital (including theknowledge, skills, and experience embodied in the workforce), natural capital (agriculturalland, forests, mangroves, fisheries, fossil fuels and minerals) and net foreign assets(portfolio equity, debt securities, foreign direct investment, and other financial capital heldin other countries). Measuring these assets are an important measure of economic
sustainability, as it is these assets which underpin future income and welfare.
The indicator measures the proportion of countries where the changes in the sum of all theseassets over time in per capita terms is positive. The higher the indicator the greater the shareof countries likely to be on an economically sustainable development pathway. The lower
the indicator the lesser the share of countries likely to be on an economically sustainable
development pathway.
. Data is reported for IDA eligible countries, including blend countries in a reporting fiscal
year. If the change in the aggregated per capita value of these assets increases from one
year to the next a country contributes positively to the indicator.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 12: Ensure sustainable consumption and production patterns

IDA20 Expected
range/value

NA

Included in IDA19

Yes (with updated methodology)

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Data Calculation Method

Percent of countries☒ FCS☐ Females

Calculation method

NA

The data is updated approximately every 2-3 years with updates of the Changing Wealth of
Nations publication.
Change in wealth per capita is derived from estimates of national produced, human, andnatural capital based on the methodology in the Changing Wealth of Nations report. The full
methodology is found here. The methodology attempts to align with international statisticalstandard for valuing national assets within national accounting frameworks wherever
possible.
Natural capital includes renewable natural capital including agricultural land, protected17

areas, forests (timber and ecosystem services), mangroves, fisheries; and non-renewable
natural capital including fossil fuels and minerals. The valuation approach is that the value
should equal the discounted sum of the net economic benefits an asset is expected togenerate over its lifetime. For natural capital, the net benefits are the resource rents.
Produced capital, comprises of machinery, structures, equipment and urban land. The
primary source of data is the Penn World Tables 10.0.
Human capital including the knowledge, skills and experience embodied in the workforce isestimated using the lifetime earnings approach to human capital. The data sources for theestimates include the I2D2 database, ILO employment data, UN National Accounts on
employment compensation, Penn World Tables, UN World Population Prospects and the
Global Burden of Disease study for health metrics.
Net foreign assets comprises of portfolio equity, debt securities, foreign direct investment
and other financial capital held overseas. The main data source is the Balance of Payments
and International Investment Position Statistics (IMF), compiled by the report the ‘External
Wealth of Nations’ (Lane and Milesi-Ferretti).
Expressed as equations:∆ 𝑊𝑒𝑎𝑙𝑡ℎ 𝑝𝑒𝑟 𝑐𝑎𝑝𝑖𝑡𝑎𝑖,𝑡1 = (𝑝𝑘𝑖,𝑡1 + ℎ𝑘𝑖,𝑡1 + 𝑛𝑘𝑖,𝑡1 ) − (𝑝𝑘𝑖,𝑡0 + ℎ𝑘𝑖,𝑡0 + 𝑛𝑘𝑖,𝑡0 )Where 𝑝𝑘 is produced capital per capita, ℎ𝑘 is human capital per capita and 𝑛𝑘 is natural
capital per capita. The 𝑡 subscript is in years and 𝑖 denotes a given country.
The % of countries without wealth depletion is then defined as follows:% 𝑜𝑓 𝑐𝑜𝑢𝑛𝑡𝑟𝑖𝑒𝑠 𝑤𝑖𝑡ℎ𝑜𝑢𝑡 𝑤𝑒𝑎𝑙𝑡ℎ 𝑑𝑒𝑝𝑙𝑒𝑡𝑖𝑜𝑛 =(∑𝑛1 𝑖 | ∆𝑊𝑒𝑎𝑙𝑡ℎ 𝑝𝑒𝑟 𝑐𝑎𝑝𝑖𝑡𝑎𝑖,𝑡1 > 0)∑𝑛1 𝑖

By this definition, if a country’s change in wealth per capita s positive(∆𝑊𝑒𝑎𝑙𝑡ℎ 𝑝𝑒𝑟 𝑐𝑎𝑝𝑖𝑡𝑎 > 0), then the country counts positively towards the indicator score
The indicator is defined as the percentage of total countries where wealth per capita is
positive.
Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

World Bank DataBank - Wealth Accounts.

C. Key counterparts
Contributing
PGs/GPs/Regions

Environment, Natural Resources, and the Blue Economy Global Practice

D. Additional information

18

Harmonization withother corporate reporting
mechanisms:

This indicator is proposed as part of the next WBG Corporate Scorecards revision. It may
also be a submission as part of the Roadmap Evolution.
Data provision and frequency of updates are currently dependent on trust fund resources,
since “The Changing Wealth of Nations” report is funded in part by the Global Program on
Sustainability, see here.

Limitations andExceptions

Date methodology
agreed/updated

The Changing Wealth of Nations publication is an evolving and iterative project now into
its 5th version. Each flagship report aims to improve data quality and coverage and strive tobetter measure comprehensive wealth. These changes can have significant impacts oncomparability of the data series across editions (we advise users to only use the most recent
series). Sometimes new assets are added to natural capital and valuation approaches arerefined. For example, in the last report additional natural capital assets were added for
mangroves and the methodology for agricultural land was significantly updated. For
reporting on the IDA RMS and Corporate Scorecard the submission team would criticallyassess the advantages of using improved data sources against the drawbacks of lesscomparability, and provided an explanatory note, if needed.
Methodology last agreed and updated: January 2023.

19

Countries without natural capital wealth depletion
A. Overview
Indicator nameCountries without natural capital wealth depletion (%)

Definition(as it should appear on thedigital IDA RMS card)

Percentage of IDA (inclusive of Blend) countries with positive changes in renewable natural
capital per capita based on a subset of assets in the natural capital data series produced aspart of the Changing Wealth of Nations publication and published on the World
Development Indicators database. Renewable natural capital includes estimates of forest(that is accounting for timber, ecosystem services and the value of protected areas),mangroves, fisheries, cropland and pastureland. If the change in the aggregated per capita
value of these assets increases from one year to the next a country contributes positively tothe indicator.
Renewable natural capital is an indicator of sustainable natural resource management and iscorrelated with the state of nature, environment and services provided by natural assets topeople. Consistent declines in renewable natural capital wealth provide an early warningthat an economy is on an unsustainable development path with livelihoods dependent onenvironmental assets at risk.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 12: Ensure sustainable consumption and production patterns

IDA20 Expected
range/value

37-85% (based on historical range between 1995 and 2018)

Included in IDA19

No

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Percent of countries☒ FCS☐ Females

Calculation method

NA

The data is updated approximately every 2-3 years with updates of the Changing Wealth of
Nations publication.
Renewable natural capital accumulation is derived from a subset of components in thenatural capital data published on the World Bank’s wealth accounts. Natural capital includes
both renewable and non-renewable natural capital, however for this indicator only therenewable natural capital components are included. The full methodology behind theseestimates can be found here.

Data Calculation Method

Expressed as equations:
Renewable natural capital per capita = (forest (timber, ecosystem services and protectedareas) + mangroves + fisheries + cropland + pastureland) / population.
The indicator measures the change from the latest year from the previous year of recorded
data.

20

Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

World Bank Databank - Wealth Accounts.

C. Key counterparts
Contributing
PGs/GPs/Regions

Environment, Natural Resources, and the Blue Economy Global Practice

D. Additional information
Harmonization withother corporate reporting
mechanisms:

This indicator is proposed as part of the next WBG Corporate Scorecards revision. It may
also be a submission as part of the Roadmap Evolution.
Data provision and frequency of updates are currently dependent on trust fund resources,
since “The Changing Wealth of Nations” report is funded in part by the Global Program on
Sustainability, see here.

Limitations andExceptions

Date methodology
agreed/updated

The Changing Wealth of Nations publication is an evolving and iterative project now into
its 5th version. Each flagship report aims to improve data quality and coverage and strive tobetter measure comprehensive wealth. These changes can have significant impacts oncomparability of the data series across editions (we advise users to only use the most recent
series). Sometimes new assets are added to natural capital and valuation approaches arerefined. For example, in the last report additional natural capital assets were added for
mangroves and the methodology for agricultural land was significantly updated. For
reporting on the IDA RMS and Corporate Scorecard the submission team would criticallyassess the advantages of using improved data sources against the drawbacks of lesscomparability, and provided an explanatory note, if needed.
Methodology last agreed and updated: January 2023.

21

Average annual deforestation change
A. Overview
Indicator name

Average annual deforestation change (%)

Definition(as it should appear on thedigital IDA RMS card)

The forest area net change measures the combined effects of forest expansion (throughafforestation and natural growth) and deforestation. A negative value indicates a decrease in
a forested area. The definition of a forest includes land that spans over 0.5 hectares, contains
trees with a canopy cover of at least 10 percent, and is not primarily used for agriculture or
urban purposes. The trees within the defined forest area should be at least 5 meters tall or
have the potential to reach that height. Data are reported for all IDA eligible countries,
including blend countries, in a reporting fiscal year.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 15.2: End Deforestation and Restore Degraded Forests

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Percentage☒ FCS☐ Females

Calculation method

NA

AnnuallyCountries submit national data to the Food and Agriculture Organization (FAO) in astandardized format to ensure consistency between global and national statistics. The annual
net change rate is calculated with the forest area data by employing the geometric mean overa specific period (e.g., 2010-2020).
However, there are limitations due to incomplete data at the country level. The annual net
change also represents only a partial view of sustainable forest management.

Data Calculation Method

Review process: WDI data are annually reviewed by country and regional teams, GPs and
CCSAs, and Executive Director Offices during the Bank-wide review, in addition to routine
sanity checks every update.
Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDA-

22

financing)

Data Source(s)World Development Indicators (WDI) at
https://data.worldbank.org/indicator/AG.LND.FRST.K2
Forest land area is sourced from FAOSTAT https://www.fao.org/faostat/en/#data/RL

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

Data are available for all 74 IDA countries except Kosovo, which is not available in
FAOSTAT as of January 2023.

Date methodology
agreed/updated

In the last report, we proposed the SDG indicator: Annual forest area change rate (%), to
capture both forest expansion (afforestation and natural expansion) and deforestation rather
than only monitoring the latter.

23

Marine protected areas
A. Overview
Indicator nameMarine protected areas

Definition(as it should appear on thedigital IDA RMS card)

Percent of areas of intertidal or subtidal terrain—and underlying water and associated floraand fauna and historical and cultural features—that have been reserved by law or othereffective means to protect part or all of the enclosed environment. Aggregation is weighted
average.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 14.5: Conserve coastal and marine areas - By 2020, conserve at least 10 per cent ofcoastal and marine areas, consistent with national and international law and based on thebest available scientific information.

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Percent of territorial waters☒ FCS☐ Females

Calculation method

NA

Annually in December
This indicator is calculated using spatial data from different sources, including protectedareas from the World Database on Protected Areas (WDPA), other effective area-based
conservation measures (OECMs), and Key Biodiversity Areas (KBAs) for marine
environments. It is measured as “protected marine and coastal area” divided by “total
marine and coastal area”.
• Aggregates are constructed as weighted averages, excluding landlocked countries.

Data Calculation Method

Review process: WDI data are annually reviewed by country and regional teams, GPs and
CCSAs, and Executive Director Offices during the Bank-wide review, in addition to routine
sanity checks every update.
Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)24World Development Indicators (WDI) at http://wdi.worldbank.org/.
Data Source(s)UNEP-WCMC and IUCN (2023), Protected Planet: The World Database on Protected
Areas (WDPA) [Online], January 2023, Cambridge, UK: UNEP-WCMC and IUCN.
Available at: www.protectedplanet.net.

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

WBG Corporate Scorecard••
Limitations andExceptions

Date methodology
agreed/updated

The extent to which the land areas, including inland waters, and territorial watersof a country/territory are protected is useful for planning purpose to protect
biodiversity. However, it is neither an indication of how well managed theterrestrial and marine protected areas are, nor confirmation that protection
measures are effectively enforced. Further, the indicator does not provide
information on non-designated or internationally designated protected areas that
may also be important for conserving biodiversity.
There are known data and knowledge gaps for some countries/regions due todifficulties in reporting national protected area data to the WDPA and/or
determining whether a site conforms to the IUCN definition of a protected area.
Gaps and/or time lags in reporting national protected area data to the WDPA canhowever result in discrepancies, which are resolved in communication with data
providers. The World Conservation Monitoring Centre (WCMC) compiles data onprotected areas, numbers of certain species, and numbers of those species under
threat from various sources. Because of differences in definitions, reporting
practices, and reporting periods, cross-country comparability is limited. Due tovariations in consistency and methods of collection, data quality is highly variable
across countries. Some countries update their information more frequently thanothers, some have more accurate data on extent of coverage, and many underreport
the number or extent of protected areas. Most of the IDA countries with access tothe ocean have data. Exceptions include Somalia, Eritrea, and Benin.

The methodology review is expected as the SDG 14.5.1 has changed from the percentage of
Key Biodiversity Areas (KBA) covered by protected areas to the mean percentage of each
KBA covered by protected area.

25

Legal changes that support gender equality
A. Overview
Indicator name

Legal changes that support gender equality (number of legal changes)

Definition(as it should appear on thedigital IDA RMS card)

Number of legal changes supporting gender equality in all IDA countries (including blend)
over a one-year period. The indicator covers legal changes taking place in the following
eight indicators as measured by the Women, Business and the Law dataset: mobility;
workplace; pay; marriage; parenthood; entrepreneurship; assets; and pension. Aggregation
is sum. Data are reported worldwide for all IDA eligible countries, including blend
countries, in a reporting fiscal year.

Tier typeOne

IDA20 Cycle Timeline

FY23-25
SDG Indicator 5.1: End all forms of discrimination against all women and girls everywhere.

Relevant SDG

SDG 5.a Undertake reforms to give women equal rights to economic resources, as well as
access to ownership and control over land and other forms of property, financial services,
inheritance and natural resources, in accordance with national laws.

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Number of legal changes in IDA countries (including Blend), with disaggregate data at acountry-level also available.
☒ FCS☐ Females

Calculation method

NAInternal Data Update
Frequency

The data used to calculate the number of legal changes that support gender equality is
updated on an annual basis. The latest data in Women, Business and the Law 2023 arecurrent as of October 1, 2022 and were published on March 2, 2023.

Data Calculation Method

5) The number of legal changes that support gender equality is calculated as a simple sumof legal changes taking place in IDA countries (including Blend) in the following eightindicators, as measured by the Women, Business and the Law (WBL) team: mobility;
workplace; pay; marriage; parenthood; entrepreneurship; assets; and pension.
6) Each of the eight indicators is assigned a score on a scale from 0 to 100. Indicator-level
scores are obtained by calculating the simple average of the four or five binary
questions within that indicator. The binary questions are assigned a score of 1 if theanswer to the question is “Yes”, and 0 – if the answer to the question is “No”. If
legislative or regulatory changes occur that change the answer to a question from “No”
to “Yes”, this is then classified as the legal change that supports gender equality. Whensuch change occurs, the indicator-level score increases. The amount of the increase in
the overall indicator score depends on the number of questions for which the answer
changes from “No” to “Yes”. Each question within the eight indicators is either 1/4(25%) (if an indicator consists of 4 questions) or 1/5 (20%) (if an indicator consists of 5questions).
7) To illustrate as an example: in the reporting FY22 the WBL team reported the number26

of legal changes that occurred between Oct 2, 2020 - Oct 1, 2021 – a total of five. For
example, as a result of the undertaken legislative and regulatory changes over a oneyear period, the score on the Pay indicator increased for Benin by 25 points, Burundi by
25 points and Pakistan by 25 points in comparison with these countries’ respectivescores on this indicator in the reporting FY21. Similarly, the score on the Pension
indicator increased for Cambodia in the reporting FY22 in comparison with FY21; thescore on the Entrepreneurship indicator increased for Sierra Leone. So, a total of 5 legal
changes that support gender equality occurred over a one year.
8) The WBL data for all countries are reviewed by more than 2000 local respondents withexpertise in family, labor, and criminal law, including lawyers, judges, academics, andmembers of civil society organizations working locally on gender issues. These data arethen verified with the corresponding legal basis by the WBL team. The data undergo athorough review through the Bank-Wide Review (BWR) process every year before thepublication.
Note:
1.

2.

3.

Data Source(s)Women, Business and the Law data spans more than 50 years in 190 economies
across 35 aspects of the law across the eight indicators. The eight WBL indicators
are assigned scores on a scale from 0 to 100, with 100 representing the highest
possible score. For more detailed methodology on how indicator level scores arecomputed by the team, please visit: https://wbl.worldbank.org/en/methodology[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

Women, Business, and the Law database.

C. Key counterparts
The underlying data based on which indicators are calculated is collected by Development
Economics Vice Presidency’s Women, Business and the Law team (DECWL) on an annual
basis. Data for all economies are reviewed by more than 2000 local respondents withexpertise in family, labor, and criminal law, including lawyers, judges, academics, andmembers of civil society organizations working locally on gender issues. These data arethen verified with the corresponding legal basis by the Women, Business and the Law team.
Contributing
PGs/GPs/Regions

The data undergo a thorough review through the Bank-Wide Review (BWR) process every
year before the publication. During this process, all GPs and Regions have the opportunity
to comment and/or highlight any issues. This review can lead to corrections of data as aresult of new information obtained, clarifications of answers, or consistency checks.
The indicator on the number of legal changes that support gender equality is calculated by
Women, Business and the law team based on the annually published underlying data.

D. Additional information
Harmonization withother corporate reporting
mechanisms:

Corporate Scorecard: The WBG Corporate Scorecard (CSC) included the same Tier 1
indicator, “Number of legal changes that support gender equality”, but the number reported
is limited to IBRD and IDA (including Blend) economies. This indicator has the samedefinition.

27

Limitations andExceptions

The Women, Business and the Law score relies on a series of assumptions. This approachhas both strengths and limitations. For example, the woman in question is assumed to residein the main business city of her economy and to be employed in the formal sector. Thisapproach may not capture restrictions applicable to areas outside the main business city or
to informal workers. However, four of the eight indicators have direct relevance for women
who work in the informal sector—for example, laws affecting women’s freedom of
movement, their ability to own or inherit property, or protections against domestic violence.
Additionally, legal protections affecting the formal sector provide a foundation foreconomic inclusion and offer incentives for women to be employed in or start businesses in
the formal sector and to transition from the informal to the formal economy. Still, theinterplay of other factors, such as access to quality education, infrastructural andinstitutional capacity, and social and cultural norms may prevent women from entering theworkforce. This study recognizes these limitations. Although they may come at the expenseof specificity, they also ensure that the data are reliable and comparable.
Note: For more detailed methodology, please visit:https://wbl.worldbank.org/en/methodology

Date methodology
agreed/updated

The Women, Business and the Law’s methodology and indicators were refined in
September 1, 2019. The indicator set went from 50 questions examining legal differences
across 7 indicators to 35 questions across 8 indicators.

28

Ratio of female to male labor force participation rate
A. Overview
Indicator name

Ratio of female to male labor force participation rate (%)

Definition(as it should appear on thedigital IDA RMS card)

The percentage of female to male labor participation rate. Labor force participation rate is
the proportion of the population ages 15 and older that is economically active: all people
who supply labor for the production of goods and services during a specified period.
Aggregation is population-weighted average. Data are reported for all IDA eligible
countries, including blend countries, in a reporting fiscal year.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 8.5: By 2030, achieve full and productive employment and decent work for all womenand men, including for young people and persons with disabilities, and equal pay for workof equal value.

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Data Calculation Method

Percent☒ FCS☐ Females

Calculation method

Quarterly (July, September, December, and April)
Statistical concept and methodology: The labor force is the supply of labor available for
producing goods and services in an economy. It includes people who are currently
employed and people who are unemployed but seeking work as well as first-time jobseekers. Not everyone who works is included, however. Unpaid workers, family workers,
and students are often omitted, and some countries do not count members of the armed
forces. Labor force size tends to vary during the year as seasonal workers enter and leave.
The series is part of the "ILO modeled estimates database," including nationally reported
observations and imputed data for countries with missing data, primarily to capture regionaland global trends with consistent country coverage. Country-reported microdata is based
mainly on nationally representative labor force surveys, with other sources (e.g., household
surveys and population censuses) considering differences in the data source, the scope ofcoverage, methodology, and other country-specific factors. Country analysis requires
caution where limited nationally reported data are available. A series of models are also
applied to impute missing observations and make projections. However, imputed
observations are not based on national data, are subject to high uncertainty, and should not
be used for country comparisons or rankings. For more information:
https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/.
Ratio of female to male labor force participation rate is calculated by dividing female labor29

force participation rate by male labor force participation rate and multiplying by 100.
Review process: WDI data are annually reviewed by country and regional teams, GPs and
CCSAs, and Executive Director Offices during the Bank-wide review, in addition to routine
sanity checks every update.

Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

World Development Indicators (WDI) at http://wdi.worldbank.org/.
Data Source(s)Most country data are sourced from International Labour Organization. “ILO Modelled
Estimates and Projections database (ILOEST)” ILOSTAT. Accessed December 6, 2022.
https://ilostat.ilo.org/data/.

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

World Bank Annual Report (Regional snapshot) at
https://www.worldbank.org/en/about/annual-report
Estimates of women in the labor force and employment are generally lower than those ofmen and are not comparable internationally, reflecting that demographic, social, legal, andcultural trends and norms determine whether women's activities are regarded as economic.
In many low-income countries women often work on farms or in other family enterprises
without pay, and others work in or near their homes, mixing work and family activities
during the day. In many high-income economies, women have been increasingly acquiring
higher education that has led to better-compensated, longer-term careers rather than lowerskilled, shorter-term jobs. However, access to good- paying occupations for women remains
unequal in many occupations and countries around the world.

Limitations andExceptions

Data on the labor force are compiled by the ILO from labor force surveys, censuses, andestablishment censuses and surveys. For some countries a combination of these sources isused. Labor force surveys are the most comprehensive source for internationally comparable
labor force data. They can cover all non-institutionalized civilians, all branches and sectorsof the economy, and all categories of workers, including people holding multiple jobs. By
contrast, labor force data from population censuses are often based on a limited number ofquestions on the economic characteristics of individuals, with little scope to probe. The
resulting data often differ from labor force survey data and vary considerably by country,
depending on the census scope and coverage. Establishment censuses and surveys provide
data only on the employed population, not unemployed workers, workers in small
establishments, or workers in the informal sector. The reference period of a census or survey

30

is another important source of differences: in some countries data refer to people's status on
the day of the census or survey or during a specific period before the inquiry date, while inothers data are recorded without reference to any period. In countries, where the household
is the basic unit of production and all members contribute to output, but some at low
intensity or irregularly, the estimated labor force may be much smaller than the numbers
actually working. Differing definitions of employment age also affect comparability. For
most countries the working age is 15 and older, but in some countries children younger than
15 work full- or part-time and are included in the estimates. Similarly, some countries havean upper age limit. As a result, calculations may systematically over- or underestimate
actual rates.
Date methodology
agreed/updated

This ILO-modeled estimates follow the methodology at
https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/.

31

Maternal mortality ratio
A. Overview
Indicator name

Maternal mortality ratio (number of maternal deaths per 100,000 live births)

Definition(as it should appear on thedigital IDA RMS card)

Maternal mortality ratio is the number of women who die from pregnancy-related causes
while pregnant or within 42 days of pregnancy termination per 100,000 live births. The data
are estimated with a regression model using information on the proportion of maternal
deaths among non-AIDS deaths in women ages 15–49, fertility, birth attendants, and GDP.
Aggregation is weighted average. Data is reported for all IDA eligible countries, including
blend countries, in a reporting fiscal year.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG Indicator 3.1.1: Maternal mortality ratio

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Number of maternal deaths per 100,000 live births☒ FCS☐ Females

Calculation method

Every three years according to the data source’s update schedule (United Nations Maternal
Mortality Estimation Inter-Agency Group).
Reproductive health is a state of physical and mental well-being in relation to thereproductive system and its functions and processes. Means of achieving reproductive
health include education and services during pregnancy and childbirth, safe and effective
contraception, and prevention and treatment of sexually transmitted diseases. Complicationsof pregnancy and childbirth are the leading cause of death and disability among women of
reproductive age in developing countries.

Data Calculation Method

The estimates are based on an exercise by the Maternal Mortality Estimation Inter-Agency
Group (MMEIG) which consists of World Health Organization (WHO), United Nations
Children's Fund (UNICEF), World Bank, and United Nations Population Fund (UNFPA),
and include country-level time series data. For countries without complete registration data
but with other types of data and for countries with no data, maternal mortality is estimatedwith a regression model using available national maternal mortality data and socioeconomic
information.
Review process: WDI data are annually reviewed by country and regional teams, GPs and
CCSAs, and Executive Director Offices during the Bank-wide review, in addition to routine
sanity checks every update.

32

Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

World Development Indicators (WDI) at http://wdi.worldbank.org/.
Data Source(s)WHO, UNICEF, UNFPA, World Bank Group, and the United Nations Population Division.
C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

Limitations: The methodology differs from that used for previous estimates, so data should
not be compared historically. Maternal mortality is generally of unknown reliability, as aremany other cause-specific mortality indicators. Household surveys such as Demographicand Health Surveys attempt to measure maternal mortality by asking respondents about
survivorship of sisters. The main disadvantage of this method is that the estimates ofmaternal mortality that it produces pertain to any time within the past few years before thesurvey, making them unsuitable for monitoring recent changes or observing the impact ofinterventions. In addition, measurement of maternal mortality is subject to many types oferrors. Even in high-income countries with reliable vital registration systems,
misclassification of maternal deaths has been found to lead to serious underestimation.

Date methodology
agreed/updated

NA

33

Proportion of births attended by skilled health personnel
A. Overview
Indicator name

Proportion of births attended by skilled health personnel (%)

Definition(as it should appear on thedigital IDA RMS card)

Births attended by skilled health staff are the percentage of deliveries attended by personnel
trained to give the necessary supervision, care, and advice to women during pregnancy,
labor, and the postpartum period; to conduct deliveries on their own; and to care fornewborns. Aggregation is weighted average. Data are reported for all IDA eligible
countries, including blend countries, in a reporting fiscal year.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG Indicator 3.1.2: Proportion of births attended by skilled health personnel

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Percent☒ FCS☐ Females

Calculation method

Once a year according to the data source’s update schedule, typically in April (The United
Nations Children's Fund (UNICEF)).
This indicator measures how many births are attended by skilled health personnel among thetotal live births—the number of births attended by skilled health personnel divided by the
total number of live births, expressed as a percentage. Skilled health personnel generally
refer to doctors, nurses, midwives, and in some cases other health professionals who aretrained to provide childbirth care.

Data Calculation Method

Data are harmonized by UNICEF after collecting from (i) household surveys such as
Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS),
Reproductive Health Surveys (RHS), (ii) population-based surveys where childbirthservices are not utilized, and (iii) service/facility records where births usually occur inhealth facilities. For example, the country-specific categories or occupational titles areverified to capture the reality.
Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)34

World Development Indicators (WDI) at http://wdi.worldbank.org/.
Data Source(s)UNICEF at https://data.unicef.org/topic/maternal-health/delivery-care/.
Demographic and Health Surveys at https://www.statcompiler.com/en/.

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

For indicators that are from household surveys, the year refers to the survey year. For more
information, consult the original data sources. Births attended by skilled health personnel isan indicator of health care utilization. It is a measure of the health system’s functioning andpotential to provide adequate coverage for childbirth. On its own, however, this indicatordoes not provide insight into the availability or accessibility of services, for example incases where emergency care is needed. Neither does this indicator capture the quality ofcare received. Data collection and data interpretation in many countries is challenged bylack of guidelines, standardization of professional titles and functions of the health careprovider, and in some countries by task-shifting. In addition, many countries have foundthat there are large gaps between international standards and the competencies of existing
health care professionals providing childbirth care. Lack of training and an enabling
environment often hinder evidence-based management of common obstetric and neonatal
complications.

Date methodology
agreed/updated

NA

35

Contraceptive prevalence by modern methods
A. Overview
Indicator nameContraceptive prevalence by modern methods (% of women ages 15-49)
Updated Indicator – please note that the definition should be updated, as the IDA19
indicator only covered % of married women ages 15-49.

Definition(as it should appear on thedigital IDA RMS card)

Married/in-union: Contraceptive prevalence, any modern method is the percentage ofmarried/in-union women ages 15-49 who are practicing, or whose sexual partners arepracticing, at least one modern method of contraception. Modern methods of contraception
include female and male sterilization, oral hormonal pills, the intra-uterine device (IUD), themale condom, injectables, the implant (including Norplant), vaginal barrier methods, thefemale condom and emergency contraception.
All women: Contraceptive prevalence, any modern method is the percentage of all womenages 15-49 who are practicing, or whose sexual partners are practicing, at least one modern
method of contraception. Modern methods of contraception include female and malesterilization, oral hormonal pills, the intra-uterine device (IUD), the male condom,
injectables, the implant (including Norplant), vaginal barrier methods, the female condom
and emergency contraception.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG Indicator 3.7.1: Proportion of women of reproductive age (aged 15–49 years) who
have their need for family planning satisfied with modern methods

IDA20 Expected
range/value

NA

Included in IDA19

Modified

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)

Percentage of women ages 15-49☒ FCS☐ Females

Calculation method

Internal Data Update
Frequency

Once a year in April or July according to the data source’s update schedule (United Nations
Population Division).

Data Calculation Method

Statistical concept and methodology: Contraceptive prevalence rates are obtained mainly
from nationally representative household surveys, including Demographic and Health
Surveys; Multiple Indicator Cluster Surveys; Contraceptive Prevalence Surveys; Gender andGenerations Survey; Reproductive Health Surveys; and World Fertility Surveys. Additional
information was provided by other international survey programs and national surveys.
Review process: WDI data are annually reviewed by country and regional teams, GPs and
CCSAs, and Executive Director Offices during the Bank-wide review, in addition to routine
sanity checks every update.

36

Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

World Development Indicators (WDI) at http://wdi.worldbank.org/.
Data Source(s)Household surveys, including Demographic and Health Surveys and Multiple Indicator
Cluster Surveys. Largely compiled by United Nations Population Division athttps://www.un.org/development/desa/pd/data/world-contraceptive-use.

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

Limitations andExceptions

Date methodology
agreed/updated

NA
Limitations and notes: While the data availability on contraceptive use has increased, inmany countries the contraceptive use data are available only for married women.
The time frame used to assess contraceptive prevalence may vary. In many surveys, it is left
to the respondent to determine what is meant by “currently using” a method ofcontraception.
NA

37

Adolescent fertility rate
A. Overview
Indicator name

Adolescent fertility rate (number of births per 1,000 women ages 15-19)

Definition(as it should appear on thedigital IDA RMS card)

Adolescent fertility rate is the number of births per 1,000 women ages 15–19. Aggregation
is age-weighted average. Data are reported for all IDA eligible countries, including blend
countries, in a reporting fiscal year.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG Indicator 3.7.2: Adolescent birth rate (aged 10–14 years; aged 15–19 years) per 1,000
women in that age group

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Number of births per 1,000 women ages 15–19☒ FCS☐ Females

Calculation method

Once a year in April.
The estimates are calculated based on Bayesian hierarchical models. The data sources areregistered live births from vital registration systems or, in the absence of such systems, fromcensuses or sample surveys.
Review process: WDI data are annually reviewed by country and regional teams, GPs and
CCSAs, and Executive Director Offices during the Bank-wide review, in addition to routine
sanity checks every update.

Data Calculation Method

Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

World Development Indicators (WDI) at http://wdi.worldbank.org/.
Data Source(s)United Nations Population Division, World Population Prospects at
https://population.un.org/wpp/.

38

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

When data is unavailable or deemed unreliable, estimations for individual countries or areas
are derived through a range of approaches. These approaches encompass expert-based
opinion, analysis and evaluation of each observation, utilization of automated statisticalmethods, and the implementation of a bias-adjusted data model.

Date methodology
agreed/updated

The methodology follows the Methodology Report of the World Population Prospects 2022
at https://population.un.org/wpp/Publications/Files/WPP2022_Methodology.pdf.

39

Refugees by country or territory of asylum
A. Overview
Indicator name

Refugees by country or territory of asylum (million)

Definition(as it should appear on thedigital IDA RMS card)

Refugees are people who are recognized as refugees under the 1951 Convention Relating to
the Status of Refugees or its 1967 Protocol, the 1969 Organization of African Unity
Convention Governing the Specific Aspects of Refugee Problems in Africa, people
recognized as refugees in accordance with the United Nations High Commissioner for
Refugees statute, people granted refugee-like humanitarian status, and people provided
temporary protection. Asylum seekers—people who have applied for asylum or refugee
status and who have not yet received a decision or who are registered as asylum seekers—
are excluded. Palestinian refugees are people (and their descendants) whose residence was
Palestine between June 1946 and May 1948 and who lost their homes and means of
livelihood as a result of the 1948 Arab-Israeli conflict. Country of asylum is the country
where an asylum claim was filed and granted. Aggregation is sum. Data is reported for all
IDA eligible countries, including blend countries, in a reporting fiscal year.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

NA

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Million☒ FCS☐ Females

Calculation method

Once a year in July or September according to the data source’s update schedule (UNHCR).

Statistical concept and methodology: The United Nations High Commissioner for Refugees(UNHCR) and the United Nations Relief and Works Agency for Palestine Refugees in the
Near East (UNRWA) collect and maintains data on refugees under their mandate in their
Statistical Online Population Databases.

Data Calculation Method

Refugees are an important part of migrant stock. The refugee data refer to people who havecrossed an international border to find sanctuary and have been granted refugee or refugeelike status or temporary protection. There are three main providers of refugee data:
governmental agencies, UNHCR and UNRWA field offices and NGOs. Registrations,
together with other sources - including estimates and surveys - are the main sources ofrefugee data. In the absence of Government estimates, UNHCR has estimated the refugee
population in most industrialized countries, based on recognition of asylum-seekers.
Asylum seekers - people who have applied for asylum or refugee status and who have notyet received a decision or who are registered as asylum seekers - and internally displaced40

people - who are often confused with refugees - are not included in the data. Unlike
refugees, internally displaced people remain under the protection of their own government,even if their reason for fleeing was similar to that of refugees.
Palestinian refugees are people (and their descendants) whose residence was Palestine
between June 1946 and May 1948 and who lost their homes and means of livelihood as aresult of the 1948 Arab-Israeli conflict.
Development Relevance: Movement of people, most often through migration, is asignificant part of global integration. Migrants contribute to the economies of both their hostcountry and their country of origin. Yet reliable statistics on migration are difficult to collectand are often incomplete, making international comparisons a challenge.
Global migration patterns have become increasingly complex in modern times, involving
not just refugees, but also millions of economic migrants. But refugees and migrants, even if
they often travel in the same way, are fundamentally different, and for that reason aretreated very differently under modern international law. Migrants, especially economic
migrants, choose to move in order to improve the future prospects of themselves and theirfamilies. Refugees have to move if they are to save their lives or preserve their freedom.
They have no protection from their own state - indeed it is often their own government thatis threatening to persecute them. If other countries do not let them in, and do not help themonce they are in, then they may be condemning them to death - or to an intolerable life in
the shadows, without sustenance and without rights.
Review process: WDI data are annually reviewed by country and regional teams, GPs and
CCSAs, and Executive Director Offices during the Bank-wide review, in addition to routine
sanity checks every update.
Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

World Development Indicators (WDI) at http://wdi.worldbank.org/.
Data Source(s)Data are sourced from UNHCR and UNRWA. Accessed June 16, 2022.
https://www.unhcr.org/refugee-statistics/.

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA41

Limitations andExceptions

There are difficulties in collecting accurate statistics on refugees. Many refugees may not beaware of the need to register or may choose not to do so, and administrative records tend tooverestimate the number of refugees because it is easier to register than to de-register. In
addition, most industrialized countries lack a refugee register and are thus not in a position
to provide accurate information on the number of refugees residing in their country. Many
countries have registries that are only maintained at the local level, so the data is notcentralized.

Date methodology
agreed/updatedNA

42

Internally displaced persons, total displaced by conflict and violence
A. Overview
Indicator nameInternally displaced persons, total displaced by conflict and violence (million)

Definition(as it should appear on thedigital IDA RMS card)

Internally displaced persons are defined according to the 1998 Guiding Principles (internaldisplacement.org/ publications/1998/ocha-guiding-principles-on-internal-displacement) as
people or groups of people who have been forced or obliged to flee or to leave their homes
or places of habitual residence, in particular as a result of armed conflict, or to avoid theeffects of armed conflict, situations of generalized violence, violations of human rights, or
natural or human-made disasters and who have not crossed an international border. “People
displaced” refers to the number of people living in displacement as of the end of each year,
and reflects the stock of people displaced at the end of the previous year, plus inflows of
new cases arriving over the year as well as births over the year to those displaced, minus
outflows that may include returnees, those who settled elsewhere, those who integrated
locally, those who traveled over borders, and deaths).

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 16: Promote peaceful and inclusive societies for sustainable development, provide
access to justice for all and build effective, accountable and inclusive institutions at alllevels

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Data Calculation Method

Million☒ FCS☐ Females

Calculation method

Once a year in July according to the data source’s update schedule (Internal Displacement
Monitoring Centre).
Statistical concept and methodology: Internally displaced persons are "persons or groups of
persons who have been forced or obliged to flee or to leave their homes or places of habitualresidence, in particular as a result of or in order to avoid the effects of armed conflict,situations of generalized violence, violations of human rights or natural or human-madedisasters, and who have not crossed an internationally recognized state border." Internallydisplaced people are often confused with refugees. Unlike refugees, internally displaced
people remain under the protection of their own government, even if their reason for fleeing
was similar to that of refugees. Refugees are people who have crossed an international
border to find sanctuary and have been granted refugee or refugee-like status or temporary
protection. “People displaced” refers to the number of people living in displacement as ofthe end of each year, and reflects the stock of people displaced at the end of the previous
year, plus inflows of new cases arriving over the year as well as births over the year to those
displaced, minus outflows which may include returnees, those who settled elsewhere, those43

who integrated locally, those who travelled over borders, and deaths.
Development Relevance: Although all persons affected by conflict and/or human rights
violations suffer, displacement from one's place of residence may make the internallydisplaced particularly vulnerable. Following are some of the factors that are likely toincrease the need for protection:1) Internally displaced persons may be in transit from one place to another, may be in
hiding, may be forced toward unhealthy or inhospitable environments, or face othercircumstances that make them especially vulnerable.
2) The social organization of displaced communities may have been destroyed or damagedby the act of physical displacement; family groups may be separated or disrupted; women
may be forced to assume non-traditional roles or face particular vulnerabilities. Internallydisplaced populations, and especially groups like children, the elderly, or pregnant women,
may experience profound psychosocial distress related to displacement.
3) Removal from sources of income and livelihood may add to physical and psychosocial
vulnerability for displaced people.
4) Schooling for children and adolescents may be disrupted.
5) Internal displacement to areas where local inhabitants are of different groups or
inhospitable may increase risk to internally displaced communities; internally displaced
persons may face language barriers during displacement.
6) The condition of internal displacement may raise the suspicions of or lead to abuse byarmed combatants, or other parties to conflict.
7) Internally displaced persons may lack identity documents essential to receiving benefits
or legal recognition; in some cases, fearing persecution, displaced persons have sometimes
got rid of such documents.
8) According to the Internal Displacement Monitoring Centre (IDMC) tens of millions
people around the world are displaced every year within their countries by conflict, humanrights violations, natural disasters and climate change. Unlike refugees who cross national
borders and benefit from an established system of international protection and assistance,
those forcibly uprooted within their own countries, by armed conflict, large-scale
development projects, systematic violations of human rights, or natural disasters, lackpredictable structures of support. Internal displacement has become one of the morepressing humanitarian, human rights and security problems confronting affected countries
and the international community at large.
Review process: WDI data are annually reviewed by country and regional teams, GPs and
CCSAs, and Executive Director Offices during the Bank-wide review, in addition to routine
sanity checks every update.
Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)44

World Development Indicators (WDI) at http://wdi.worldbank.org/.
Data Source(s)Data are sourced from Internal Displacement Monitoring Centre (IDMC). Accessed June 2,
2022. http://www.internal-displacement.org/

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA
Please note that most of the figures are estimates. The definition highlights two issues:

Limitations andExceptions

1) The coercive or otherwise involuntary character of movement. The definition mentions
some of the most common causes of involuntary movements, such as armed conflict,violence, human rights violations and disasters. These causes have in common that they giveno choice to people but to leave their homes and deprive them of the most essential
protection mechanisms, such as community networks, access to services, livelihoods.
Displacement severely affects the physical, socio-economic and legal safety of people andshould be systematically regarded as an indicator of potential vulnerability.
2) The fact that such movement takes place within national borders. Unlike refugees, whohave been deprived of the protection of their state of origin, IDPs remain legally under theprotection of national authorities of their country of habitual residence. IDPs should
therefore enjoy the same rights as the rest of the population. The Guiding Principles on
Internal Displacement remind national authorities and other relevant actors of their
responsibility to ensure that IDPs' rights are respected and fulfilled, despite the vulnerability
generated by their displacement.

Date methodology
agreed/updated

NA

45

GDP per person employed
A. Overview
Indicator name

GDP per person employed (constant 2017 PPP $)Definition(as it should appear on thedigital IDA RMS card)

GDP per person employed is Gros Domestic Product (GDP) divided by total employment in
the economy. Purchasing power parity (PPP) GDP is GDP converted to 2017 constantinternational dollars using PPP rates. An international dollar has the same purchasing powerover GDP that a U.S. dollar has in the United States. Aggregation is population-weighted
average. Data is reported for all IDA eligible countries, including blend countries, in areporting fiscal year.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG Indicator 8.2.1: Annual growth rate of real GDP per employed person

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Data Calculation Method

Constant 2017 purchasing power parity (PPP) $☒ FCS☐ Females

Calculation method

Quarterly (July, September, December, and April)
Statistical concept and methodology: GDP per person employed represents laborproductivity—output per unit of labor input. To compare labor productivity levels acrosscountries, GDP is converted to international dollars using purchasing power parity rates
which take account of differences in relative prices between countries. Estimates are basedon employment, population, GDP, and PPP data obtained from International Labour
Organization, United Nations Population Division, Eurostat, OECD, and World Bank. The
employment rates are part of the "ILO modeled estimates database," including nationallyreported observations and imputed data for countries with missing data, primarily to capture
regional and global trends with consistent country coverage. Country-reported microdata isbased mainly on nationally representative labor force surveys, with other sources (e.g.,household surveys and population censuses) considering differences in the data source, thescope of coverage, methodology, and other country-specific factors. Country analysis
requires caution where limited nationally reported data are available. A series of models arealso applied to impute missing observations and make projections. However, imputed
observations are not based on national data, are subject to high uncertainty, and should not
be used for country comparisons or rankings. For more information:
https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/
GDP per person employed is a key measure to monitor whether a country is on track toachieve the Sustainable Development Goal of promoting sustained, inclusive and46

sustainable economic growth, full and productive employment and decent work for all.
[SDG Indicator 8.2.1]
Review process: WDI data are annually reviewed by country and regional teams, GPs and
CCSAs, and Executive Director Offices during the Bank-wide review, in addition to routine
sanity checks every update.
Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

World Development Indicators (WDI) at http://wdi.worldbank.org/.
Data Source(s)Estimates are based on employment, population, GDP, and PPP data obtained fromInternational Labour Organization, United Nations Population Division, Eurostat, OECD,and World Bank.

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

For comparability of individual sectors labor productivity is estimated according to national
accounts conventions. However, there are still significant limitations on the availability of
reliable data. Information on consistent series of output in both national currencies andpurchasing power parity dollars is not easily available, especially in developing countries,
because the definition, coverage, and methodology are not always consistent acrosscountries. For example, countries employ different methodologies for estimating themissing values for the nonmarket service sectors and use different definitions of theinformal sector.

Date methodology
agreed/updated

GDP is based on the internationally agreed standards, the System of National Accounts(SNA). ILO-modeled estimates of employment follow the methodology at
https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/.

47

Non-agriculture sectors, value added
A. Overview
Indicator nameNon-agriculture sectors, value added (as % of GDP)

Definition(as it should appear on thedigital IDA RMS card)

Value added of non-agriculture sectors as percentage of gross domestic product (GDP),
calculated as subtracting agriculture value added (as percentage of GDP) from 100. The
non-agriculture sectors refer to the industry and services sectors. Industry corresponds to theInternational Standard Industrial Classification, revision 4 (ISIC rev.4) divisions 05–43 andcomprises value added in mining, manufacturing, construction, and electricity and watersupply. Services correspond to ISIC divisions 45–98 and include value added in wholesale
and retail trade, hotels and restaurants, transport, communication, government, financial,professional, and personal services such as education, health care, and real estate services.
Calculation is based on data in US dollars. Aggregates are calculated as a weighted averageof country values. Data are reported for all IDA eligible countries, including blend
countries, in a reporting fiscal year.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

NA

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)

Percent of GDP☒ FCS☐ Females

Calculation method

Internal Data Update
Frequency

Data are updated twice a year: in July and January.

Data Calculation Method

Value added is the value of the gross output of producers less the value of intermediate
goods and services consumed in production before accounting for consumption of fixed
capital in production. It is calculated without making deductions for depletion anddegradation of natural resources. Gross domestic product (GDP) represents the sum of value
added by all its producers.
Data are collected by WB staff working in the field from national compiling agencies(generally the national Statistics Office, in some countries the Central Bank). Data arereviewed by DECDG colleagues for accuracy, plausibility, and consistency. Any issue isdiscussed before agreeing on final numbers. Comparison is also made with data
disseminated by other international organizations (e.g., IMF).
For comparison purposes across countries, data expressed in local currency units areconverted into $US using the official exchange rates. However, adjustments may be made to
the official exchange rate in countries where other exchange rates, significantly different
than the official one, are also used.
Review process: WDI data are annually reviewed by country and regional teams, GPs and
CCSAs, and Executive Director Offices during the Bank-wide review, in addition to routine

48

sanity checks every update.
Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

Value added/GDP data are provided by national statistical agencies/ central banks or, if notavailable, estimated by the World Bank.
Data Source(s)Data needed to calculate this indicator are available in the World Development Indicators
database.
C. Key counterparts
Contributing
PGs/GPs/Regions

MTI (Macroeconomics, Trade and Investment)
DECDG

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptionsFirst value added and GDP estimates are published by the World Bank six months after theend of the year. Final value added and GDP data are only available two to three years after
the end of the year. Some countries are not able to provide national accounts estimates forthe most recent year. In this case, WB growth estimates provided by the MTI
macroeconomic modelling unit are used.

Date methodology
agreed/updatedNA

49

Annual growth rate of real GDP per capita
A. Overview
Indicator name

Annual growth rate of real GDP per capita (%)

Definition(as it should appear on thedigital IDA RMS card)

The annual percentage growth rate of GDP per capita is the percentage change in the valueof the Gross Domestic Product measured in constant prices (in US dollars) divided by the
mid-year population. Aggregates are calculated as a weighted average of country values andare based on constant 2015 U.S. dollars. Data is reported for all IDA eligible countries,
including blend countries, in a reporting fiscal year

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG Indicator 8.1.1: Annual growth rate of real GDP per capita

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Percent☒ FCS☐ Females

Calculation method

Data are updated twice a year: in July and January.
Gross domestic product (GDP) represents the sum of value added by all its producers. Value
added is the value of the gross output of producers less the value of intermediate goods andservices consumed in production before accounting for consumption of fixed capital inproduction. It is calculated without making deductions for depletion and degradation ofnatural resources.

Data Calculation Method

Constant price U.S. dollar series are used to calculate regional and income group average
growth rates. Local currency series are converted to constant U.S. dollars using an exchange
rate in the common reference year.Population estimates are usually based on national
population censuses. Estimates for the years before and after the census are interpolations or
extrapolations based on demographic models.
Review process: WDI data are annually reviewed by country and regional teams, GPs and
CCSAs, and Executive Director Offices during the Bank-wide review, in addition to routine
sanity checks every update.
Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should

50

include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

Data Source(s)GDP data are provided by national statistical agencies/ central banks or, if not available,
estimated by the World Bank.
Population data are retrieved from: 1) United Nations Population Division. World
Population Prospects: 2022 Revision. (2) Census reports and other statistical publications
from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations
Statistical Division. Population and Vital Statistics Report (various years), (5) U.S. Census
Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and
Demography Programme.
All data are available in the World Data Indicators database.

C. Key counterparts
Contributing
PGs/GPs/Regions

MTI (Macroeconomics, Trade and Investment)
DECDG

D. Additional information
Harmonization withother corporate reporting
mechanisms:

The indicator is available in the WDI tables “WV1. Size of the Economy” (by country, byregion, and by income group).
First GDP estimates are published by the World Bank six months after the end of the year.
Final GDP data are only available two to three years after the end of the year.

Limitations andExceptions

Each industry's contribution to growth in the economy's output is measured by growth in theindustry's value added. In principle, value added in constant prices can be estimated bymeasuring the quantity of goods and services produced in a period, valuing them at anagreed set of base year prices, and subtracting the cost of intermediate inputs, also inconstant prices. This double-deflation method requires detailed information on the structureof prices of inputs and outputs. In many industries, however, value added is extrapolated
from the base year using single volume indexes of outputs or, less commonly, inputs.
Particularly in the services industries, including most of government, value added inconstant prices is often imputed from labor inputs, such as real wages or number of
employees. In the absence of well-defined measures of output, measuring the growth ofservices remains difficult. Moreover, technical progress can lead to improvements in
production processes and in the quality of goods and services that, if not properly accounted
for, can distort measures of value added and thus of growth. When inputs are used toestimate output, as for nonmarket services, unmeasured technical progress leads tounderestimates of the volume of output. Similarly, unmeasured improvements in quality
lead to underestimates of the value of output and value added. The result can beunderestimates of growth and productivity improvement and overestimates of inflation.
Informal economic activities pose a particular measurement problem, especially indeveloping countries, where much economic activity is unrecorded. A complete picture of
the economy requires estimating household outputs produced for home use, sales in
informal markets, barter exchanges, and illicit or deliberately unreported activities. The
consistency and completeness of such estimates depend on the skill and methods of thecompiling statisticians. Rebasing of national accounts can alter the measured growth rate ofan economy and lead to breaks in series that affect the consistency of data over time. Whencountries rebase their national accounts, they update the weights assigned to various
components to better reflect current patterns of production or uses of output. The new baseyear should represent normal operation of the economy - it should be a year without major

51

shocks or distortions. Some developing countries have not rebased their national accounts
for many years. Using an old base year can be misleading because implicit price and volume
weights become progressively less relevant and useful. To obtain comparable series of
constant price data for computing aggregates, the World Bank rescales GDP and value
added by industrial origin to a common reference year. Because rescaling changes theimplicit weights used in forming regional and income group aggregates, aggregate growth
rates are not comparable with those from earlier editions with different base years.
Rescaling may result in a discrepancy between the rescaled GDP and the sum of therescaled components. To avoid distortions in the growth rates, the discrepancy is left
unallocated. As a result, the weighted average of the growth rates of the components
generally does not equal the GDP growth rate.
Date methodology
agreed/updated

The method used to calculate the indicator, based on data provided by sources, has notchanged since its inception in the WDI in 2002.

52

Proportion of population with access to electricity
A. Overview
Indicator name

Proportion of population with access to electricity (%)

Definition(as it should appear on thedigital IDA RMS card)

The percentage of the population that has access to electricity. Electrification data arecollected from industry, national surveys and international sources. Aggregation is
population-weighted average. Data are reported for all IDA eligible countries, including
blend countries, in a reporting fiscal year.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG Indicator 7.1.1: Proportion of population with access to electricity

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Percent of population☒ FCS☐ Females

Calculation method

NA

Annually

Electrification information is collected primarily from nationally representative household
surveys such as Demographic and Health Surveys (DHS), Living Standards Measurement
Surveys (LSMS), Multi-Indicator Cluster Surveys (MICS), and other surveys by national
statistical agencies, and occasionally censuses.
The original survey data results remain for all available years, but missing values get filled
in using a multilevel nonparametric modeling approach; if no survey data exist for aparticular year, potential access improvements are assumed to be similar to regional trends.

Data Calculation Method

Aggregates are constructed as weighted averages using population totals from the World
Development Indicators (SP.POP.TOTL).
Review process: WDI data are annually reviewed by country and regional teams, GPs and
CCSAs, and Executive Director Offices during the Bank-wide review, in addition to routine
sanity checks every update.
Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type53

(including IDA-financing), and Trust-fund financier type (including IDAfinancing)
World Development Indicators (WDI) at http://wdi.worldbank.org/.
Data Source(s)Country data is shared by Energy GP. Also available at https://trackingsdg7.esmap.org/
C. Key counterparts
Contributing
PGs/GPs/Regions

Energy GP

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

Data coverage as of January 2023 is as follows:• The latest observations are for 2020.
• All 74 IDA countries have data, except for Kosovo with missing observations in
2011, 2018, and 2020.

Date methodology
agreed/updated

The UN Statistical Commission designated the World Bank as the custodian agency tomonitor SDG 7.1.1 Proportion of population with access to electricity with the International
Energy Agency (IEA) and UN-Energy. Since then, the overall methodology has remained
the same.

54Youth employment to population ratio (age 15-24)
Women (%)
Men (%)A. Overview
Youth employment to population ratio (age 15-24) (%)
Indicator name−−

Youth employment to population ratio (age 15-24), women (%)
Youth employment to population ratio (age 15-24), men (%)

Definition(as it should appear on thedigital IDA RMS card)

The youth employment-to-population ratio is the proportion of a country’s population ofages 15–24 that is employed. Employment is defined as persons of working age who, during
a short reference period, were engaged in any activity to produce goods or provide services
for pay or profit, whether at work during the reference period (i.e., who worked in a job forat least one hour) or not at work due to temporary absence from a job, or to working-timearrangements. Aggregation is population-weighted average. Data are reported for all IDA
eligible countries, including blend countries, in a reporting fiscal year.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 8.6: By 2020, substantially reduce the proportion of youth not in employment,
education or training

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure

Percent of population☒ FCS

Reporting Disaggregation(if relevant)☒ Females

Calculation method

Female employed ages 15-24 / Female
population ages 15-24 * 100

Internal Data Update
Frequency

Quarterly (July, September, December, and April)

Data Calculation Method

Statistical concept and methodology: The employment-to-population ratio indicates how
efficiently an economy provides jobs for people who want to work. A high ratio means thata large proportion of the population is employed. But a lower employment-to-population
ratio can be seen as a positive sign, especially for young people, if an increase in theireducation causes it. The series is part of the "ILO modeled estimates database," including
nationally reported observations and imputed data for countries with missing data, primarily
to capture regional and global trends with consistent country coverage. Country-reported
microdata are based mainly on nationally representative labor force surveys, with othersources (e.g., household surveys and population censuses) considering differences in thedata source, the scope of coverage, methodology, and other country-specific factors.
Country analysis requires caution where limited nationally reported data are available. A

55

series of models are also applied to impute missing observations and make projections.
However, imputed observations are not based on national data, are subject to highuncertainty, and should not be used for country comparisons or rankings. For more
information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelledestimates/.
Review process: data are annually reviewed by country and regional teams, GPs and
CCSAs, and Executive Director Offices during the Bank-wide review, in addition to routine
sanity checks every update.
Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

World Development Indicators (WDI) at http://wdi.worldbank.org/.
Data Source(s)Most country data are sourced from International Labour Organization. “ILO Modelled
Estimates and Projections database (ILOEST)” ILOSTAT. Accessed December 6, 2022.
https://ilostat.ilo.org/data/.

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

Limitations andExceptions

NA
Limitations and exceptions: Data on employment by status are drawn from labor force
surveys and household surveys, supplemented by official estimates and censuses for a small
group of countries. The labor force survey is the most comprehensive source forinternationally comparable employment, but there are still some limitations for comparing
data across countries and over time even within a country. Comparability of employment
ratios across countries is affected by variations in definitions of employment and population.
The biggest difference results from the age range used to define labor force activity. The
population base for employment ratios can also vary. Most countries use the resident, noninstitutionalized population of working age living in private households, which excludes
members of the armed forces and individuals residing in mental, penal, or other types of
institutions. But some countries include members of the armed forces in the population baseof their employment ratio while excluding them from employment data. The reference
period of a census or survey is another important source of differences: in some countries
data refer to people's status on the day of the census or survey or during a specific period
before the inquiry date, while in others data are recorded without reference to any period.
Employment ratios tend to vary during the year as seasonal workers enter and leave. This
indicator also has a gender bias because women who do not consider their work
employment or who are not perceived as working tend to be undercounted. This bias has

56different effects across countries and reflects demographic, social, legal, and cultural trends
and norms.
Date methodology
agreed/updated

This ILO-modeled estimates follow the methodology at
https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/.

57

Proportion of adults (15 years and older) with an account at a bank or other financial
institution or with a mobile money service provided
A. Overview
Indicator name

Proportion of adults (15 years and older) with an account at a bank or other financial
institution or with a mobile money service provided (%)

Definition(as it should appear on thedigital IDA RMS card)

Percentage of respondents (% age 15 and older) who report, having an account (bythemselves or together with someone else) at a bank or another type of financial institutionthat falls under prudential regulation by a government body such as a credit union,
microfinance institution, or post office; having a debit card in their own name; receiving
wages, government transfers, or payments for agricultural products into an account or
through a mobile phone at a financial institution in the past 12 months; paying utility bills or
school fees from an account at a financial institution in the past 12 months; receiving wages
or government transfers into a card in the past 12 months. It also includes respondents whoreport personally using a mobile money service to make payments, buy things, or to send or
receive money in the past 12 months; or report receiving wages, government transfers, apublic sector pension, or payments for agricultural products through a mobile phone in thepast 12 months. Aggregation is based on weighted averages. Data are reported worldwide
for World Bank Group-supported countries with available data.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG Indicator 8.10.2: Proportion of adults (15 years and older) with an account at a bank orother financial institution or with a mobile-money-service provider

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure

Percent☒ FCS

Reporting Disaggregation

Poststratification weights are applied using
economy-level population statistics ongender to create gender-based estimates.

(if relevant)☒ FemalesInternal Data Update
Frequency

The data are collected triennially. Data were most recently collected and disseminated in
2021.

Data Calculation Method

The indicators in the 2021 Global Findex Database are drawn from survey data undertaken
by Gallup, Inc. as part of its Gallup World Poll. The data are collected every three years andGlobal Findex has since 2011, conducted surveys of approximately 1,000 people in each ofmore than 160 economies and in over 150 languages, using randomly selected, nationally
representative samples. The target population is the entire civilian, noninstitutionalized
population age 15 and above.
Surveys are conducted face-to-face in economies where telephone coverage represents less

Calculation method58

than 80 percent of the population or where in-person surveying is the customary
methodology. However, because of ongoing COVID-19–related mobility restrictions, faceto-face interviewing was not possible in some of these economies in 2021. Phone-based
surveys were therefore conducted in 67 economies that had been surveyed face-to-face in2017.
Data weighting is used to ensure a nationally representative sample for each economy. Finalweights consist of the base sampling weight, which corrects for unequal probability of
selection based on household size, and the poststratification weight, which corrects forsampling and nonresponse error. Poststratification weights use economy-level population
statistics on gender and age and, where reliable data are available, education orsocioeconomic status. Regional population weights are used to calculate regional
aggregates.
Full report, including methodology and interview procedures, data preparation, margin oferror and notes by country are all available in the Methodology note here.
Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

Collected by Gallup, Inc. through the Gallup World Poll and compiled by the World Bank.
Official citation: Global Findex Database 2021

C. Key counterparts
Contributing
PGs/GPs/Regions

Global Findex team within the Development Research Group (DECRG)

D. Additional information
Harmonization withother corporate reporting
mechanisms:

Indicator is used to update:Tier 1 CSC/IDA19 RMS Financial accounts data; United Nations Sustainable Development
Goal 8.10.2.

Limitations andExceptions

In 2021, due to ongoing COVID-19–related mobility restrictions, many economies
previously surveyed in person switched to phone surveys, However, phone surveys were nota viable option in 16 Findex economies due to low mobile phone ownership. Data for these
economies were collected in 2022 and released in 2023. For more detail, please see themethodology note here. No specific challenges are anticipated for the next data collection
round in 2024.

Date methodology
agreed/updated

April 2023

59

Proportion of adults (15 years and older) with an account at a bank or other financial
institution or with a mobile money service provided, bottom 40%
A. Overview
Indicator name

Proportion of adults (15 years and older) with an account at a bank or other financial
institution or with a mobile money service provided, bottom 40% (%)

Definition(as it should appear on thedigital IDA RMS card)

Percentage of respondents in the poorest 40 percent of households (% age 15 and older) who
report, having an account (by themselves or together with someone else) at a bank oranother type of financial institution that falls under prudential regulation by a government
body such as a credit union, microfinance institution, or post office; having a debit card intheir own name; receiving wages, government transfers, or payments for agricultural
products into an account or through a mobile phone at a financial institution in the past 12
months; paying utility bills or school fees from an account at a financial institution in thepast 12 months; receiving wages or government transfers into a card in the past 12 months.
It also includes respondents who report personally using a mobile money service to makepayments, buy things, or to send or receive money in the past 12 months; or report receiving
wages, government transfers, a public sector pension, or payments for agricultural products
through a mobile phone in the past 12 months. Aggregation is based on weighted averages.
Data are reported worldwide for World Bank Group-supported countries with available
data.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG Target 8.10: Strengthen the capacity of domestic financial institutions to encourage
and expand access to banking, insurance and financial services for all

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure

Percent☒ FCS

Reporting Disaggregation

Poststratification weights are applied using
economy-level population statistics ongender to create gender-based estimates.

(if relevant)☒ FemalesInternal Data Update
Frequency

The data are collected triennially. Data were most recently collected and disseminated in
2021.

Data Calculation Method

The indicators in the 2021 Global Findex Database are drawn from survey data undertaken
by Gallup, Inc. as part of its Gallup World Poll. The data are collected every three years andGlobal Findex has since 2011, conducted surveys of approximately 1,000 people in each ofmore than 160 economies and in over 150 languages, using randomly selected, nationally
representative samples. The target population is the entire civilian, noninstitutionalized
population age 15 and above.

Calculation method

60

Surveys are conducted face-to-face in economies where telephone coverage represents lessthan 80 percent of the population or where in-person surveying is the customary
methodology. However, because of ongoing COVID-19–related mobility restrictions, faceto-face interviewing was not possible in some of these economies in 2021. Phone-based
surveys were therefore conducted in 67 economies that had been surveyed face-to-face in2017.
Data weighting is used to ensure a nationally representative sample for each economy. Finalweights consist of the base sampling weight, which corrects for unequal probability of
selection based on household size, and the poststratification weight, which corrects forsampling and nonresponse error. Poststratification weights use economy-level population
statistics on gender and age and, where reliable data are available, education orsocioeconomic status. Regional population weights are used to calculate regional
aggregates.
Adults in the poorest 40% of households are calculated relative to other adults in the
country. Per capita annual income of the country is used to divide respondents into fivegroups of equal size. Adults with household income in the two lowest income quintiles(poorest 20 percent and 21 to 40 percent) constitute adults in the poorest 40 percent ofhouseholds.
Full report, including methodology and interview procedures, data preparation, margin oferror and notes by country are all available in the Methodology note here.
Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

Collected by Gallup, Inc. through the Gallup World Poll and compiled by the World Bank.
Official citation: Global Findex Database 2021

C. Key counterparts
Contributing
PGs/GPs/Regions

Global Findex team within the Development Research Group (DECRG)

D. Additional information
Harmonization withother corporate reporting
mechanisms:

Limitations andExceptions

Indicator is used to update:Tier 1 CSC/IDA19 RMS Financial accounts data; United Nations Sustainable Development
Goal 8.10.2.
In 2021, due to ongoing COVID-19–related mobility restrictions, many economies
previously surveyed in person switched to phone surveys, However, phone surveys were nota viable option in 16 Findex economies due to low mobile phone ownership. Data for these
economies were collected in 2022 and released in 2023. For more detail, please see themethodology note here.

61

No specific challenges are anticipated for the next data collection round in 2024.

Date methodology
agreed/updated

April 2023

62

Prevalence of stunting among children under 5 years of age
A. Overview
Indicator name

Prevalence of stunting among children under 5 years of age (%)

Definition(as it should appear on thedigital IDA RMS card)

Prevalence of stunting is the percentage of children under age 5 whose height for age ismore than two standard deviations below the median for the international reference
population ages 0–59 months. For children up to two years old, height is measured byrecumbent length. For older children, height is measured by stature while standing. The data
are based on the WHO’s new child growth standards released in 2006. Aggregationis(under-five) population-weighted average. Data are reported for all IDA eligible countries,
including blend countries, in a reporting fiscal year.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG Indicator 2.2.1: Prevalence of stunting (height for age <-2 standard deviation from themedian of the World Health Organization (WHO) Child Growth Standards) among children
under 5 years of age

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Data Calculation Method

Percentage☒ FCS☐ Females

Calculation method

Every year (or every other year) in April or July according to the data source’s update
schedule (UNICEF, WHO, World Bank: Joint Malnutrition Estimates (JME)).
The data presented here are modeled estimates to create a trend line across national data
points using smoothing techniques and covariates (McLain et al. 2018). The underlying data
including anthropometric information are collected primarily from household surveys (e.g.,
Multiple Indicator Cluster Surveys (MICS), Demographic and Health Surveys (DHS),
Standardized Monitoring and Assessment of Relief and Transition (SMART) surveys, andLiving Standards Measurement Study (LSMS), following the Recommendations for datacollection, analysis and reporting on anthropometric indicators in children under 5 years ofage. The World Health Organization (WHO) Child Growth Standards serve as the standard
reference for the growth patterns of infants and children from diverse ethnic backgrounds.
Review process: WDI data are annually reviewed by country and regional teams, GPs and
CCSAs, and Executive Director Offices during the Bank-wide review, in addition to routine
sanity checks every update.
Note:
1.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only and

63

2.

blend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

World Development Indicators (WDI) at http://wdi.worldbank.org/.
Data Source(s)Data are sourced from UNICEF, WHO, World Bank: Joint Malnutrition Estimates (JME).
Accessed June 6, 2022. https://data.unicef.org/topic/nutrition/malnutrition/.

C. Key counterparts
Contributing
PGs/GPs/Regions

No

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

Modeled estimates are designed to address national data sparsity. Uncertainty intervals areavailable at the country level to address the caution level; a survey may affect the modeled
estimates, especially in countries with sparse data.

Date methodology
agreed/updated

The methodology is based on a technical consultation with experts, country representativesof National Statistics Offices, and IAEG-SDGs Members in 2019.

64

Under-5 mortality rate
A. Overview
Indicator name

Under-5 mortality rate (per 1,000 live births)

Definition(as it should appear on thedigital IDA RMS card)

The probability of a child born in a specific year or period dying before reaching the age of
5 years, if subject to age-specific mortality rates of that period, expressed per 1,000 live
births. Aggregation is weighted average. Data is reported for all IDA eligible countries,
including blend countries, in a reporting fiscal year.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG Indicator 3.2.1: Under‐5 mortality rate

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure

Number of under-5 deaths per 1,000 live births☒ FCS

Reporting Disaggregation(if relevant)☒ FemalesInternal Data Update
Frequency

Once a year according to the data source’s update schedule (the UN Inter-agency Group forChild Mortality Estimation).

Calculation method

The probability per 1,000 that a newborn
female baby will die before reaching age
five.

Statistical concept and methodology: The main sources of mortality data are vitalregistration systems and direct or indirect estimates based on sample surveys or censuses. A"complete" vital registration system - covering at least 90 percent of vital events in the
population - is the best source of age-specific mortality data.

Data Calculation Method

Estimates of neonatal, infant, and child mortality tend to vary by source and method for agiven time and place. Years for available estimates also vary by country, making
comparisons across countries and over time difficult. To make neonatal, infant, and childmortality estimates comparable and to ensure consistency across estimates by different
agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UNIGME), which comprises the United Nations Children's Fund (UNICEF), the World HealthOrganization (WHO), the World Bank, the United Nations Population Division, and otheruniversities and research institutes, developed and adopted a statistical method that uses all
available information to reconcile differences. The method uses statistical models to obtaina best estimate trend line by fitting a country-specific regression model of mortality rates
against their reference dates.
Review process: WDI data are annually reviewed by country and regional teams, GPs and
CCSAs, and Executive Director Offices during the Bank-wide review, in addition to routine65sanity checks every update.
Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

World Development Indicators (WDI) at http://wdi.worldbank.org/.
Data Source(s)UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN
DESA Population Division) at www.childmortality.org.

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

Complete vital registration systems are fairly uncommon in developing countries. Thus
estimates must be obtained from sample surveys or derived by applying indirect estimation
techniques to registration, census, or survey data. Survey data are subject to recall error, andsurveys estimating infant/child deaths require large samples because households in which abirth has occurred during a given year cannot ordinarily be preselected for sampling.
Indirect estimates rely on model life tables that may be inappropriate for the population
concerned. Extrapolations based on outdated surveys may not be reliable for monitoringchanges in health status or for comparative analytical work.

Date methodology
agreed/updated

NA

66

Incidence of HIV
A. Overview
Indicator name

Incidence of HIV (per 1,000 uninfected population ages 15-49)

Definition(as it should appear on thedigital IDA RMS card)

Number of new HIV infections among uninfected populations ages 15-49 expressed per
1,000 uninfected population in the year before the period. Aggregation is weighted average.
Data are reported for all IDA eligible countries, including blend countries, in a reporting
fiscal year.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG Indicator 3.3.1: Number of new HIV infections per 1,000 uninfected population, by
sex, age, and key populations

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure

Percentage of uninfected population ages 15–49☒ FCS
Number of new HIV infections among
uninfected female population ages 15-49 /Number of uninfected female population
ages 15-49* 1000

Reporting Disaggregation(if relevant)☒ FemalesInternal Data Update
Frequency

Once a year in September/October according to the data source’s update schedule(UNAIDS).

Data Calculation Method

Calculation method

Statistical concept and methodology: Data on incidence of HIV are from the Joint United
Nations Programme on HIV/AIDS. The numerator is number of new HIV infections, andthe denominator is the uninfected population (total population minus people living withHIV). Because of challenges in collecting direct measures of HIV incidence, modelled
estimates are used (the Spectrum software). The models incorporate data on HIV prevalencefrom surveys of the general population, antenatal clinic attendees, and populations atincreased risk of contracting HIV (such as sex workers, men who have sex with men, andpeople who inject drugs) and on the number of people receiving antiretroviral therapy,
which will increase the prevalence of HIV because people living with HIV now survive
longer. In countries with high-quality health information systems the models are also
informed by case reporting and vital registration data.
Note:
1.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only and

67

2.

blend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

World Development Indicators (WDI) at http://wdi.worldbank.org/.
Data Source(s)UNAIDS at https://aidsinfo.unaids.org/
C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA
Countries with high HIV prevalence generally have robust surveillance systems, withhousehold surveys contributing to the information needed to estimate incidence. However,surveillance systems for these populations are often incomparable over time due to changing
survey and sampling methods, resulting in over or underestimation of HIV incidence.

Limitations andExceptions

The data is also collected from routine antenatal clinic testing in many countries. However,this method might result in being biased when women who are known to be HIV positive
are not included in prevalence calculations, or when women who are initially tested negative
may be retested later in pregnancy. The uncertainty caused by these biases is difficult toquantify and therefore not accounted for.
In addition, although HIV prevalence and incidence among children appear reasonably
robust in generalized epidemics, estimating the pediatric HIV epidemic remains challenging
because no strong fertility measures exist among populations living with HIV.
Lastly, UNAIDS, the data source, supports the development of HIV estimates only incountries with populations greater than 250,000.

Date methodology
agreed/updated

NA

68

Population of children who cannot read by end-of-primary-school age
A. Overview
Indicator namePopulation of children who cannot read by end-of-primary-school age (%)

Definition(as it should appear on thedigital IDA RMS card)

This indicator measures the proportion of end-of-primary-school-age children who are notable to read and understand a short story of age-appropriate material. The material could befiction or non-fiction. The percentage of children not meeting the minimum proficiency
level of reading (as defined for SDG reporting) is adjusted by the share of out-of-school
children to motivate countries to have children in school and learning, also in alignment
with the SDGs. The final indicator is a population of reference weighted average for all IDA
eligible countries, including blend countries, in a reporting fiscal year. Missing country data
are imputed using regional values.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 4.1: By 2030, ensure that all girls and boys complete free, equitable and quality
primary and secondary education leading to relevant and effective learning outcomes.

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure

Percent☐ FCS

Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Data Calculation Method☒ Females

Calculation method

It is a count – we check what is available inthe microdata of the assessments used,
whether that is available for M/F
disaggregation.

For the learning poverty indicator, the process for changing country-level estimates isdecoupled from the process for changing global/regional estimates, as they have different
protocols and timelines. Country-level updates or revisions can be updated on an ongoingbasis for any country, usually once a year in February. This depends on several factors
including: whether new schooling or school deprivation data is available, and whether newassessment data is available from the country. Global or regional updates are done every 23 years depending on data availability as well. Global and Regional Learning Poverty
numbers trigger an update when there is sufficient new assessment data available.
The Learning Poverty (LP) indicator combines the share of primary-aged children out-ofschool who are Schooling Deprived (SD) and the share of pupils below a minimum
proficiency in reading, who are Learning Deprived (LD). By combining schooling andlearning, the indicator brings into focus both “more schooling”, which by itself serves avariety of critical functions, as well as “better learning” which is important to ensure thattime spent in school translates into acquisition of skills and capabilities.
𝑳𝑷 = 𝑺𝑫 + [(𝟏 − 𝑺𝑫) ∗ 𝑳𝑫]
where LP is Learning Poverty; LD, Learning Deprivation, is the share of children at the endof primary below minimum proficiency, as defined by the Global Alliance to Monitor
Learning (GAML) in the context of the SDG 4.1.1b monitoring; SD, Schooling Deprivation,69

is the share of primary-aged children who are out-of-school, and is linked to SDG 4.1.4.
The choice of a union approach to aggregate the deprivation dimensions of this measure
implies that all schooling-deprived children are regarded as being learning-deprived, or
below the minimum proficiency level for reading.
In case a country has multiple assessments, the following hierarchy is used for LD:
1. International Assessment in reading (For example, global assessments such as
PIRLS, or regional assessments such as LLECE, PASEC, or SEA-PLM withreading results.
2. International Assessment in reading that allows linking with historical regional or
national assessments (For example, AMPL-b results for reading)
3. International assessment in a subject other than reading (For example, TIMSS
science)
4. National Learning Assessment (interim reporting, validated by country teams)
The inclusion of AMPL-b is a new addition to the hierarchy of assessments used to reporton Learning Poverty, which is developed by UNESCO UIS to measure proficiency. AMPLb is first reported in the 2022 June update. Methodology remains the same otherwise.
National assessments (interim SDG reporting): For some larger-population countries thathave not participated in any of the assessments listed above, we used interim data from
National Assessments, as per the UIS SDG 4.1.1 reporting protocol. As with the regional
assessments, this required deciding on the appropriate level of proficiency to map to theglobal benchmark. We made these judgments by: (1) drawing on the proficiency-leveldescriptors within each national assessment to select the level that most closely matched theglobal description of reading proficiency; and then (2) consulting UIS and World Bank
country experts and triangulating with other data sources (such as PISA or citizen-led
assessments) to determine whether any adjustment was necessary.
The out-of-school adjustment in Learning Poverty relies on enrollment data. Our preferreddefinition is the adjusted net primary enrollment as reported by the UNESCO Institute for
Statistics (UIS). This data relies both on the population census (UNPD population estimatesfor school-age population) and administrative records (Education Management Information
System, school registers, or school censuses). We use the same year of school participation
as the preferred learning assessment for each country, depending on availability, whichmeans enrollment data for countries with new assessments may be updated in thecalculation of their Learning Poverty estimate. We follow a general hierarchy for choosing
enrollment data, depending on the following enrollment definitions (in order of priority):• Adjusted Net Enrollment Rate (ANER)• Total Net Enrollment Rate (TNER)• Net Enrollment Rate (NER)• Gross Enrollment Rate (GER): If the gross enrollment rate is higher than 100%, it
is adjusted to be 100%
Countries used to compute regional and global aggregates depend on the year of assessment.
To be included an assessment must fall within the reporting window of +4 years of thedefined anchor year.
There are substantial data gaps, and those gaps are not uniformly distributed across regions
or income levels. To overcome this limitation, and following the practice used for other
SDG indicators, we aggregate our global number as a population-weighted average of theregional learning poverty rates. Implicitly, this is equivalent to imputing the relevant
regional weighted average to all countries that lack the necessary data.
Hence, the learning poverty rate for each region is the population-weighted aggregate (10-70

to 14-year-olds) for the countries from that region for which there are assessment and outof-school data that meet the criteria explained above. Global and regional figures arereported only if at least 40% of the region’s population of reference is covered by actual
data. This protocol is aligned with those of other global indicators under the SDGs, such as
the International Poverty line, which also uses a 40% regional-population coverage
threshold for reporting regional and global aggregates.
Keywords/Topics:
Education, Learning, Poverty, Learning Assessment
Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

World Bank-UNESCO Global Learning Assessment Database; UNESCO Institute for
Statistics (UIS) database

C. Key counterparts
Contributing
PGs/GPs/Regions

Education GP only

D. Additional information
Harmonization withother corporate reporting
mechanisms:

Used for internal Education GP updates frequently. This data is sometimes produced aspart of our flagship ASAs

Limitations andExceptions

NA

Date methodology
agreed/updated

This was the latest information agreed up on June 2022.

71

Lower secondary gross completion rate & Ratio of girls’ to boys’ completion rate
A. Overview
Indicator nameDefinition(as it should appear on thedigital IDA RMS card)−−

Lower secondary gross completion rate (%)
Ratio of girls’ to boys’ completion rate

The lower secondary gross completion rate is measured as the gross intake ratio to last gradeof lower secondary education. This is calculated as the number of new entrants in the last
grade of lower secondary education, regardless of age, divided by the population at theentrance age for the last grade of lower secondary education. Data limitations preclude
adjusting for students who drop out during the final year of lower secondary education.
Aggregation is population-weighted average. Data are reported for all IDA eligible
countries, including blend countries, in a reporting fiscal year.
Ratio of girls’ to boys’ completion rate is defined as the ratio of the female gross completion
ratio to the male gross completion ratio in lower secondary education.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 4.1: By 2030, ensure that all girls and boys complete free, equitable and quality
primary and secondary education leading to relevant and effective learning outcomes.

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure

Percent☒ FCS
Number of female new entrants (enrollment
minus repeaters) in the last grade of lower
secondary education regardless of age /Female population at the entrance age forthe last grade of lower secondary education* 100

Reporting Disaggregation(if relevant)☒ FemalesInternal Data Update
Frequency

Once a year in September/October according to the data source’s update schedule(UNESCO Institute for Statistics).

Data Calculation Method

Statistical concept and methodology: Lower secondary completion rate is calculated as
the number of new entrants (enrollment minus repeaters) in the last grade of lower
secondary education, regardless of age, divided by the population at the entrance age for thelast grade of lower secondary education. Data on education are collected by the UNESCO
Institute for Statistics from official responses to its annual education survey. All the data aremapped to the International Standard Classification of Education (ISCED) to ensure thecomparability of education programs at the international level. The current version wasformally adopted by UNESCO Member States in 2011. Population data are drawn from theUnited Nations Population Division. Using a single source for population data standardizes

Calculation method72definitions, estimations, and interpolation methods, ensuring a consistent methodology
across countries and minimizing potential enumeration problems in national censuses. The
reference years reflect the school year for which the data are presented. In some countries
the school year spans two calendar years (for example, from September 2010 to June 2011);
in these cases the reference year refers to the year in which the school year ended (2011 in
the example).
Note UIS populates the population-weighted aggregates, gap-filling country-level data.
Review process: WDI data are annually reviewed by country and regional teams, GPs and
CCSAs, and Executive Director Offices during the Bank-wide review, in addition to routine
sanity checks every update.
Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

World Development Indicators (WDI) at http://wdi.worldbank.org/.
Data Source(s)Most country data are sourced from the UNESCO Institute for Statistics (UIS). UIS.Stat
Bulk Data Download Service. Accessed October 24, 2022.
https://apiportal.uis.unesco.org/bdds.

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

Limitations and exceptions: Data limitations preclude adjusting for students who drop out
during the final year of lower secondary education. Thus this rate is a proxy that should betaken as an upper estimate of the actual lower secondary completion rate. There are manyreasons why the rate can exceed 100 percent. The numerator may include late entrants andoverage children who have repeated one or more grades of lower secondary education as
well as children who entered school early, while the denominator is the number of children
at the entrance age for the last grade of lower secondary education.

Date methodology
agreed/updated

This traditional indicator is based on UIS guidelines for country data reporting. According
to the standard framework, ISCED, education levels and types are defined.

73

Lower secondary enrollment rate & Ratio of girls’ to boys’ enrollment rates
A. Overview
Indicator nameDefinition(as it should appear on thedigital IDA RMS card)−−

Lower secondary enrollment rate (%)
Ratio of girls’ to boys’ enrollment rates (%)

Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of
the age group that officially corresponds to the level of education shown. Lower secondary
education completes the provision of basic education that began at the primary level andaims at laying the foundations for lifelong learning and human development, by offering
more subject- or skill-oriented instruction using more specialized teachers. Aggregation is
population-weighted average. Data is reported for all IDA-eligible countries, including
blend countries, in a reporting fiscal year.
Ratio of girls’ to boys’ enrollment rate is defined as the ratio of the female gross enrollment
ratio to the male gross enrollment ratio in secondary education.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 4.1: By 2030, ensure that all girls and boys complete free, equitable and quality
primary and secondary education leading to relevant and effective learning outcomes.

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure

Percent☒ FCS
Number of female students enrolled insecondary education regardless of age /Female population of the age group which
officially corresponds to secondary
education * 100

Reporting Disaggregation(if relevant)☒ FemalesInternal Data Update
Frequency

Once a year in September/October according to the data source’s update schedule(UNESCO Institute for Statistics).

Data Calculation Method

Statistical concept and methodology: Gross enrollment ratio for secondary school iscalculated by dividing the number of students enrolled in secondary education regardless ofage by the population of the age group which officially corresponds to secondary educationand multiplying by 100. Data on education are collected by the UNESCO Institute for
Statistics from official responses to its annual education survey. All the data are mapped to
the International Standard Classification of Education (ISCED) to ensure the comparabilityof education programs at the international level. The current version was formally adopted
by UNESCO Member States in 2011. Population data are drawn from the United Nations
Population Division. Using a single source for population data standardizes definitions,estimations, and interpolation methods, ensuring a consistent methodology across countries
and minimizing potential enumeration problems in national censuses. The reference years

Calculation method74reflect the school year for which the data are presented. In some countries the school year
spans two calendar years (for example, from September 2010 to June 2011); in these cases,
the reference year refers to the year in which the school year ended (2011 in the example).
Note UIS populates the population-weighted aggregates, gap-filling country-level data.
Development relevance: Gross enrollment ratios indicate the capacity of each level of theeducation system, but a high ratio may reflect a substantial number of overage children
enrolled in each grade because of repetition or late entry rather than a successful education
system. The net enrollment rate excludes overage and underage students and moreaccurately captures the system's coverage and internal efficiency. Differences between the
gross enrollment ratio and the net enrollment rate show the incidence of overage andunderage enrollment.
Review process: WDI data are annually reviewed by country and regional teams, GPs and
CCSAs, and Executive Director Offices during the Bank-wide review, in addition to routine
sanity checks every update.
Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

World Development Indicators (WDI) at http://wdi.worldbank.org/. Most country data aresourced from the UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download
Service. Accessed October 24, 2022. https://apiportal.uis.unesco.org/bdds.

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

Limitations and exceptions: Enrollment indicators are based on annual school surveys, but
do not necessarily reflect actual attendance or dropout rates during the year. Length ofeducation differs across countries and can influence enrollment rates. International Standard
Classification of Education tries to minimize the difference. A shorter duration for primaryeducation tends to increase the rate; longer ones decrease it (in part because older children
are more at risk of dropping out). Age at enrollment may be inaccurately estimated or
misstated, especially in communities where registration of births is not strictly enforced.

Date methodology
agreed/updated

This traditional indicator is based on UIS guidelines for country data reporting. According
to the standard framework, ISCED, education levels and types are defined.

75

People using basic drinking water services
A. Overview
Indicator namePeople using basic drinking water services (% of population)

Definition(as it should appear on thedigital IDA RMS card)

People using basic drinking water services refers to the percentage of people using at leastbasic water services. This indicator contains people using basic water services as well as
safely managed water services. Basic drinking water services means drinking water from an
improved source, provided collection time is not more than 30 minutes for a round trip andsafely managed drinking water services means drinking water from an improved source thatis accessible on premises, available when needed and free from fecal and priority chemical
contamination. Improved water sources include piped water, boreholes or tube wells,
protected dug wells, protected springs, and packaged or delivered water. Aggregation isweighted average. Data are reported for all IDA eligible countries, including blend
countries, in a reporting fiscal year.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 6.1: By 2030, achieve universal and equitable access to safe and affordable drinking
water for all.

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Percent of population☒ FCS☐ Females

Calculation method

Every other year in September/October according to the data source’s update schedule(WHO/UNICEF Joint Monitoring Programme (JMP)).

Statistical concept and methodology: The Joint Monitoring Programme of the World HealthOrganization (WHO) and United Nations Children's Fund (UNICEF) develops estimates foreach country by fitting regression lines to the collected data inputs, using data from 2000
onwards, based on administrative sources, national censuses and nationally representative
household surveys.
Data Calculation Method

For countries lacking recent data or having only a small number of data points available, thefollowing methods are taken. If a country has only one data point or two data points lessthan five years apart, the JMP creates estimates using a simple average, which is extended
for four years beyond the most recent data point. If there are two or more data points,
covering a span of at least five years, the JMP applies linear regression with extrapolation
for up to two years forwards and backwards from the last data point, and extends estimatesfor up to four more years.
Review process: WDI data are annually reviewed by country and regional teams, GPs and76

CCSAs, and Executive Director Offices during the Bank-wide review, in addition to routine
sanity checks every update.
Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

World Development Indicators (WDI) at http://wdi.worldbank.org/.
Data Source(s)WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply, Sanitation andHygiene at washdata.org.

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA
National, regional and income group estimates are made when data are available for at least
50 percent of the population. (WHO Global Health Observatory).

Limitations andExceptions

The most recent household survey or census available for most countries was typicallyconducted two to six years ago. The JMP extrapolates regressions for two years beyond thelast available data point. Beyond this point the estimates remain unchanged for up to four
years unless coverage is below 0.5 per cent or above 99.5 per cent, in which case the line isextended indefinitely.

Date methodology
agreed/updated

77

People using basic sanitation services
A. Overview
Indicator namePeople using basic sanitation services (% of population)

Definition(as it should appear on thedigital IDA RMS card)

People using basic sanitation services refers to the percentage of people using at least basic
sanitation services, that is, improved sanitation facilities that are not shared with otherhouseholds. This indicator contains people using basic sanitation services as well as safely
managed sanitation services (improved sanitation facilities that are not shared with otherhouseholds and where excreta are safely disposed of in situ or transported and treatedoffsite). Improved sanitation facilities include flush/pour flush to piped sewer systems,
septic tanks or pit latrines; improved ventilated pit latrines, compositing toilets or pit latrines
with slabs. Aggregation is weighted average. Data is reported for all IDA eligible countries,
including blend countries, in a reporting fiscal year

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 6.2: By 2030, achieve access to adequate and equitable sanitation and hygiene for all
and end open defecation, paying special attention to the needs of women and girls and thosein vulnerable situations

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Percent of population☒ FCS☐ Females

Calculation method

Every other year in September/October according to the data source’s update schedule(WHO/UNICEF Joint Monitoring Programme (JMP)).
Statistical concept and methodology: The Joint Monitoring Programme of the World HealthOrganization (WHO) and United Nations Children's Fund (UNICEF) develops estimates foreach country by fitting regression lines to the collected data inputs, using data from 2000
onwards, based on administrative sources, national censuses and nationally representative
household surveys.

Data Calculation Method

For countries lacking recent data or having only a small number of data points available, thefollowing methods are taken. If a country has only one data point or two data points lessthan five years apart, the JMP creates estimates using a simple average, which is extended
for four years beyond the most recent data point. If there are two or more data points,
covering a span of at least five years, the JMP applies linear regression with extrapolation
for up to two years forwards and backwards from the last data point, and extends estimatesfor up to four more years.
Review process: WDI data are annually reviewed by country and regional teams, GPs and
CCSAs, and Executive Director Offices during the Bank-wide review, in addition to routine78sanity checks every update.
Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

World Development Indicators (WDI) at http://wdi.worldbank.org/.
Data Source(s)WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply, Sanitation andHygiene at washdata.org.

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA
National, regional and income group estimates are made when data are available for at least
50 percent of the population (WHO Global Health Observatory).

Limitations andExceptions

Date methodology
agreed/updated

The most recent household survey or census available for most countries was typicallyconducted two to six years ago. The JMP extrapolates regressions for two years beyond thelast available data point. Beyond this point the estimates remain unchanged for up to four
years unless coverage is below 0.5 per cent or above 99.5 per cent, in which case the line isextended indefinitely.
NA

79

IDA countries with low or moderate risk from unsustainable debt
A. Overview
Indicator name

IDA countries with low or moderate risk from unsustainable debt (number)Definition(as it should appear on thedigital IDA RMS card)

Number of IDA countries rated 4.0 and above on a scale of 1-6 on question 3.a of theCountry Policy and Institutional Assessment (CPIA). The indicator rating is based on debt
policy criteria and assesses whether a country’s debt management policy is conducive toensure medium-term debt sustainability and minimize budgetary risk. The criteria cover theextent to which external and domestic debt is contracted, with a view toachieving/maintaining debt sustainability. The CPIA rates countries against a set of 16
criteria grouped in four clusters: (i) economic management; (ii) structural policies; (iii)
policies for social inclusion and equity; and (iv) public sector management and institutions.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 17.4: Assist developing countries in attaining long-term debt sustainability throughcoordinated policies aimed at fostering debt financing, debt relief and debt restructuring, as
appropriate, and address the external debt of highly indebted poor countries to reduce debt
distress.

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation

Number of countries☒ FCS(if relevant)☐ FemalesInternal Data Update
Frequency

CPIA is updated annually.

Calculation method

NA

The CPIA is prepared every year for each IDA-eligible country. Country teams propose
ratings (from 1 to 6) for each criterion accompanied by written justifications. The proposals
and the write-ups are vetted by the Regional Chief Economists and then reviewed by the
GPs/GTs. Country teams’ submissions and Bank-wide comments are anchored in the CPIA
Criteria and use available external indicators and other relevant supporting documentation(which may include analysis that was developed outside the Bank).
Data Calculation Method

The particular indicator is based on question 3.a of the CPIA, which is related to the extent
to which external and domestic debt is contracted with a view to achieving/maintaining debt
sustainability. To calculate the indicator, we count the number of IDA countries rated 4.0 or
above as countries with this score face a moderate risk of external and/or domestic debt
distress (or better in the case of higher scores).
••

Data are based on the last CPIA rating available. If data for a country were notcollected in that particular year, we used the latest information available.
IDA classification is based on country eligibility in the FY in which the CPIA

80

•

exercise took place. Blend countries are considered IDA-eligible.
For FCV disaggregation, we use the FCV list for the FY in which the CPIA
exercise took place.

Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

CPIA Platform

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

The CPIA score for a given year may be missing for some countries. If that is the case, thelatest CPIA scores for those countries will be considered.

Date methodology
agreed/updated

NA

81

IDA countries with improved budget reliability, transparency of public finances, andcontrol in budget execution
A. Overview
Indicator name

IDA countries with improved budget reliability, transparency of public finances, andcontrol in budget execution (number)This indicator was created to measure the three important elements of public financial
management performance using three dimensions from three different pillars and indicatorsof the PEFA 2016 methodology: (https://www.pefa.org/resources/pefa-2016-framework)(1.1)

Definition(As it should appear on thedigital IDA RMS card)

Aggregate expenditure outturn; (9.1) Public access to fiscal information; (24.2)
Procurement methods

The three dimensions selected represent: budget reliability; transparency of public finances;and predictability and control in budget execution. The baseline score was set for eachcountry with the most recent PEFA 2016 Assessment by the numerated value of the averagescores of the three dimensions. The scoring is according PEFA 2016 methodology: A=4,
B=3, C=2, D=1 and NU=0. The detailed data calculation method is described below.
In order to measure the progress, a comparison with previous assessments will be doneusing PEFA 2016 methodology, except for the cases when the previous assessments wereusing PEFA 2011 methodology. There is a special Comparison table used to compare bothmethodologies. https://www.pefa.org/resources/pefa-indicator-comparison-table-2011-vs2016-and-2016-vs-2011-glance

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 16.6: Develop effective, accountable and transparent institutions at all levels.

IDA20 Expected
range/value

For IDA20: FY23-25
Total number of countries:- The total number of countries reporting on PEFA indicators are expected to be 40;- 40% of all countries to be with improved scores
IDA countries:- The expected number of IDA countries from the total is 30- 40% of IDA countries to be with improved scores
FCV countries:- Of the 30 IDA countries, 6 are expected to be FCV- 33% of FCV countries to be improving(As a reference, FY21-FY22 cumulative: The total number of countries was 18 withimproved scores for 60 % of the countries; from them the number of IDA countries 12 withimproved scores for 42% of the countries.)

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Number of countries☒ FCS☐ Females

Calculation method

82

Not ApplicableInternal Data Update
Frequency

The data are collected once - at the end of the FY, when IDA Reporting takes place
The main method of calculating the indicator includes:
Step 1. Identification of PEFA final reports for the FY and calculation of the indicator- identify how many PEFA reports were finalized at the end of the FY.
- identify how many of the countries of the reports are IDA, BLEND or FCS countries.
- for all of them compare the three dimensions with the previous report, calculating how
many have significant improvement (2), improvement (1) or no-improvement (0) (negativechange) using the described below methodology.
Methodology for calculation:
The three dimensions selected represent: budget reliability; transparency of public finances;and predictability and control in budget execution. The baseline score was set for eachcountry with the most recent PEFA 2016 Assessment by the numerated value of the averagescores of the three dimensions. The scoring is according PEFA 2016 methodology: A=4,
B=3, C=2, D=1, NR=1 and NU=0. Annual calculation of the progress would be calculated
as follows:Significant improvement for the country = 2 points.
At least 2 of the 3 dimensions show improvement in scores; orAt least 2 of the 3 dimensions keeps the same score “A” or “B”; orAt least 1 of the dimensions keeps the scores “A” or “B” plus at least 1 of theindicators improves

Data Calculation Method

Improvement for the country = 1 point
At least one of the dimensions improves or keeps the same score “A” or “B” and theothers do not change.
No improvement, negative movement, and no change in D or C scores = 0 points
Negative change; or
All other options except the mentioned above under significant improvement andimprovement
Step 2. Summary of data for the FY and commutatively
Based on the calculations the following numbers are considered for the FY:-

Total number of countries for the FY with improvement of scores
FCS countries for the FY with improvement of scores
IDA number of countries for the FY with improvement of scores
IDA FCS number of countries for the FY with improvement of scores

The same is calculated cumulatively for the assigned period. Every country could beconsidered only once. In case of countries with duplicated/repeated PEFA Assessments forthe assigned period of time, those with the highest improvement to be considered.
Step 3. Entering data into CSC and IDA
Data to enter in CSC:-

Total number of countries for the whole period with improvement of scores
FCS countries for whole period with improvement of scores

Data to enter in IDA:-

IDA number of countries for the whole period with improvement of scores

83-

IDA FCS number of countries for the whole period with improvement of scores

Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

All PEFA Final Public assessments and scores for the dimensions are available on PEFA
Website Assessments portal: https://www.pefa.org/assessments

C. Key counterparts
Contributing
PGs/GPs/Regions

Governance Global Practice (PEFA Secretariat Team)D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

NA
The methodology was agreed in 2017 and is used until present.

Date methodology
agreed/updated

PEFA methodologies that are used are PEFA2016 and PEFA2011 depending on the current
finalized PEFA Assessment and the previous one used for comparison. Since 2018 until
now the dimensions were compared mainly using PEFA 2011 methodology, from now onmore assessments will use PEFA 2016 methodology for comparison. A comparison tablebetween the two methodologies is available on PEFA website:
https://www.pefa.org/resources/pefa-indicator-comparison-table-2011-vs-2016-and-2016vs-2011-glance84

Statistical Performance Indicators
A. Overview
Indicator name

Statistical Performance Indicators (score from 0 to 100)

Definition(as it should appear on thedigital IDA RMS card)

The SPI overall score is a composite score measuring country performance across fivepillars: data use, data services, data products, data sources, and data infrastructure. A higherscore indicates a higher level of performance. Aggregation of the SPI overall score is aweighted average of the underlying 51 indicators.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 17.18: By 2020, enhance capacity-building support to developing countries, including
for least developed countries and small island developing States, to increase significantly
the availability of high-quality, timely and reliable data disaggregated by income, gender,
age, race, ethnicity, migratory status, disability, geographic location and othercharacteristics relevant in national contexts.
SDG 17.19: By 2030, build on existing initiatives to develop measurements of progress on
sustainable development that complement gross domestic product, and support statistical
capacity-building in developing countries.

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Data Calculation Method

Scale from 0 to 100☒ FCS☐ Females

Calculation method

Data are updated annually in June of each year.
The SPI overall score is a composite score measuring country performance across fivepillars: data use, data services, data products, data sources, and data infrastructure. The new
Statistical Performance Indicators (SPI) has replaced the Statistical Capacity Index (SCI),
which the World Bank has regularly published since 2004. Although the goals are the same,
to offer a better tool to measure the statistical systems of countries, the new SPI frameworkhas expanded into new areas including in the areas of data use, administrative data,
geospatial data, data services, and data infrastructure. The SPI provides a framework that
can help countries measure where they stand in several dimensions and offers an ambitious
measurement agenda for the international community. Weighted average of all statistical
performance indicators. Scores range from 0-100 with 100 representing the best score.
Full details on the data calculation methodology are available in the SPI Technical Note:https://documents.worldbank.org/en/publication/documentsreports/documentdetail/815721616086786412

85Review process: WDI data are annually reviewed by country and regional teams, GPs and
CCSAs, and Executive Director Offices during the Bank-wide review, in addition to routine
sanity checks every update.
Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

The SPI draws on a variety of data sources to create the indicators. A guiding principle isthat the SPI rely on openly available data from credible sources, such as internationalorganizations and NSO websites. The SPI team used web scraping, accessed publicly
available databases, or in some cases visited NSO websites to acquire the information.
While greater detail for each specific indicator can be found in the technical documentation
describing each indicator.
Full details on the data sources used are available in the SPI Technical Note:https://documents.worldbank.org/en/publication/documentsreports/documentdetail/815721616086786412
The SPI overall score is also available the World Development Indicators:
wdi.worldbank.org.

C. Key counterparts
Contributing
PGs/GPs/Regions

DECDG, POV GP

D. Additional information
Harmonization withother corporate reporting
mechanisms:

Limitations andExceptions

NA
Development of the SPI has revealed a significant number of data gaps. In many criticalareas of national statistical system performance, at present there is no available data toconstruct measures. This calls for a substantial research agenda, requiring a wide range ofcountries, international agencies and other organizations to work together to produce
globally comparable, comprehensive, consistent and transparent information about national
statistical systems. An area of particular concern is the pillar of data use. Currently, thedashboard only features indicators for one of the five dimensions of data use, which is data
use by international organizations. Indicators on whether statistical systems are providing
useful data to their national governments (legislature and executive branches), to civilsociety, and to academia are absent. Thus the dashboard does not yet assess if national
statistical systems are meeting the data needs of a large swathe of users.
In the data sources pillar, more information is needed in the areas of administrative data,
geospatial data, and private and citizen generated data. On administrative data, the picture isincomplete with no measures of whether countries have administrative data systems in place86

to measure health, education, labor, and social protection program statistics. For thegeospatial indicator, there is a proxy measure of whether the country can produce indicators
at the sub-national level, but as yet, no understanding of how countries are using geospatial
information in other ways, for instance using satellite data. Finally, several of the ‘soft’components of the data infrastructure pillar lack adequate data. This includes the areas ofskills and of partnerships between entities in the national statistical system. The dashboard
makes use of the PARIS21 led SDG indicator on whether the statistical legislations incountries met the standards of the UN Fundamental Principles of Statistics, but this was notincorporated into the overall SPI score, because of inadequate country coverage.
Date methodology
agreed/updated

Methodology last finalized in March 2021.

87

IDA countries with increased tax fairness and progressivity
A. Overview
Indicator name

IDA countries with increased tax fairness and progressivity (number)Definition(as it should appear on thedigital IDA RMS card)

A tax system is progressive and fair when its design allows for the average tax rate
(liability) to increase as income or other relevant welfare metric increases. Note that fortaxes that are regressive the average tax rate decreases as income increases, and for
proportional taxes the average tax rate is constant as income increases.

Tier typeOne

IDA20 Cycle Timeline

FY23-25
SDG 10: Reduce inequality within and among countries

Relevant SDG

SDG 17: Strengthen the means of implementation and revitalize the Global Partnership for
Sustainable Development

IDA20 Expected
range/value

NA

Included in IDA19

No

B. Methodology
Unit of Measure
Reporting Disaggregation

Number of Countries☒ FCS(if relevant)☐ FemalesInternal Data Update
Frequency

Annually

Calculation method

N/A

The calculation focuses on income tax revenue. Income taxes refer to all taxes on incomes,
profits, and capital gains (such as personal income taxes and corporate income taxes). We
calculate two ratios. First, income taxes (including social security contributions) as a shareof total tax revenue (including social security contributions); and second, income taxes(including social security contributions) as a share of GDP. See “Assessing tax progressivity
in IDA countries” (Thomas, 2023) for more information on the rationale.
A record of all domestic resource mobilization-related projects (ASA or Lending) is used toverify where the Bank is active. Only IDA countries with Lending (board approved FY2325) or ASAs delivered (approved FY23-25) are considered to be engaged.
Data Calculation Method

Each IDA country’s baseline ratios of income-taxes-to-total-tax-revenue and income-taxesto-GDP are calculated as an average for the three years before the IDA cycle (i.e., for
IDA20, 2019-2021).
Each IDA country’s ratios of income-taxes-to-total-tax-revenue and income-taxes-to-GDP
are then calculated starting in the first year of the IDA cycle through the current year or
most recently available year with data.
Each IDA country that sees a positive difference (an increase) between the current ratio andthe baseline ratio is considered to have improved the ratio. The first ratio (income-taxes-tototal-tax-revenue) is a stronger measure of progressivity, so increases in this ratio are
considered an improvement in tax fairness and progressivity. The second ratio better88measures redistributive impacts and is reported for context. The number of countries
improving the first ratio is then reported.

Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

IMF Government Finance Statistics (GFS) as a base, and the IMF World Revenue
Longitudinal Data (WoRLD) for supplementary data

C. Key counterparts
Contributing
PGs/GPs/Regions

EMFTX

D. Additional information
Harmonization withother corporate reporting
mechanisms:

IDA20 Policy Commitment: This indicator is fully aligned with the IDA20 Governance &Institutions policy commitment (#2) on bolstering DRM. The PC targets assisting 15 IDA
countries to improve their revenue collection through fair and equitable revenue policies
and/or innovative compliance measures to achieve a tax-to-GDP ratio of 15%.
The methodology for calculating fairness and equity is a simple metric due to the limited
data availability (including data frequency), which is a particular challenge in lower income
countries. See “Assessing tax progressivity in IDA countries” (Thomas, 2023) for more
information on the rationale.
Furthermore, sometimes an increase in indirect taxes may be a desirable outcome (e.g.,excise taxes on tobacco, which can be progressive, or green taxes on carbon-polluting
activities, which may be a development goal), so it is not necessarily a failure if the ratio of
direct-to-total taxes worsens or stays the same. (See, for example,
https://documents1.worldbank.org/curated/en/893811554737147697/pdf/Is-TobaccoTaxation-Regressive-Evidence-on-Public-Health-Domestic-Resource-Mobilization-andEquity-Improvements.pdf)

Limitations andExceptions

Data from all sources listed are often reported at a 1- to 2-year lag. In addition, somecountries, especially some FCV countries, will not have any data that can be used for thisanalysis. Thus, a few countries may not be possible to include in this IDA20 indicator.
Social security contributions are included in total tax revenue to align it with a standard
definition that is also used by other organizations such as EU and OECD. This inclusion
keeps the definition of total tax revenue consistent between IDA RMS and CSC indicators.
Finally, the reporting team may include new frontier analysis on personal income tax
progressivity for additional context. This analysis maps personal income tax data onto
income distribution data to provide an estimate of income tax incidence. Estimates overtime allow for a measurement of improvement. Personal income tax collection may not besignificantly large enough in IDA countries for this frontier analysis to represent overall tax

89

progressivity, and the team calculating this indicator may not be ready in time for annual
IDA20 reporting requirements. Thus, this indicator may not be considered in the final
analysis of which countries are improving their tax fairness and progressivity and will only
be provided for context if available.
Date methodology
agreed/updated

The Bank is reviewing potential approaches to assessing the progressivity of tax systems,
and proposing a set of progressivity metrics to be adopted over the next three years to assess
tax progressivity in IDA countries.

90Unweighted average increase in tax-to-GDP ratio in at least those IDA countries with tax
revenues below 15 percent of their GDP for three consecutive years
A. Overview
Indicator nameDefinition(as it should appear on thedigital IDA RMS card)

Unweighted average change in tax-to-GDP ratio in those IDA countries with tax
revenues below 15 percent of their GDP for three consecutive years (%)
This indicator is a key measure of Domestic Resource Mobilization (DRM) tracking thenumber of IDA countries with tax revenues persistently (i.e. average over a three-year
period) below 15% of their GDP. The indicator is associated with IDA20 policy
commitment no. 2 under the Governance and Institutions cross-cutting theme, focused on
implementation of country programs that support the efforts of those IDA countries with tax
revenues persistently below 15% of GDP to achieve an unweighted average increase in taxto-GDP ratios through fair and equitable revenue policies, and/or innovative compliancemeasures to achieve a tax-to-GDP ratio of 15%.

Tier typeOne

IDA20 Cycle Timeline

FY23-25 (July 1, 2022, to June 30, 2025)

Relevant SDG

SDG Target 17.1: Strengthen domestic resource mobilization, including throughinternational support to developing countries, to improve domestic capacity for tax andother revenue collection

IDA20 Expected
range/value

NA

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation

Percent☒ FCS(if relevant)☐ FemalesInternal Data Update
Frequency

Annually

Calculation method

The indicator measures the increase unweighted average tax-to-GDP ratio in IDA countries
that have been persistently (averaged over three consecutive years) below 15%. Tax data(including social security contributions) are retrieved from the IMF’s GFS andsupplemented with MPO data when missing. Using the last year before the IDA cycle, IDA
countries’ tax-to-GDP ratios are averaged flatly in the three years before (i.e., for IDA20,
2019-2021) to see whether each is persistently below 15% and which serves as a baseline tocheck for an improvement.
Data Calculation Method

A record of all domestic resource mobilization-related projects (ASA or Lending) is used toverify where the Bank is active. Only IDA countries persistently below 15% with Lending(board approved FY23-25) or ASAs delivered (approved FY23-25) are considered to be engaged.
The tax-to-GDP ratio of each IDA country with Bank engagement below the 15% thresholdas identified in the previous steps, is then compared between its current (using the mostrecently available data or projections to the current year) and its baseline tax-to-GDP ratio.
A flat average of the differences (current minus baseline) across qualifying countries is then91

taken and reported.
Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

IMF Government Finance Statistics (GFS) as a base, and Macro Poverty Outlook (MPO) for
supplementary data

C. Key counterparts
Contributing
PGs/GPs/Regions

EMFTX

D. Additional information
Harmonization withother corporate reporting
mechanisms:

IDA20 Policy Commitment: This indicator is fully aligned with the IDA20 Governance &Institutions policy commitment (#2) on bolstering DRM. The PC targets assisting 15 IDA
countries to improve their revenue collection through fair and equitable revenue policies,
and/or innovative compliance measures to achieve a tax-to-GDP ratio of 15%.
As the fallout from the COVID-19 pandemic winds down, many countries temporarily
reduced tax rates or collections which may lower the baseline year affecting performance.

Limitations andExceptions

Date methodology
agreed/updated

Data from GFS are often reported at a 1- to 2-year lag, meaning estimates from MacroPoverty Outlook (MPO) will be substituted. Some MPO figures include social security
contributions in the total tax figures (which should be included for this analysis), but not for
all countries and when it is included, it isn’t flagged. In addition, some countries, especiallysome FCV countries, will not have any data that can be used for this analysis. Thus, a few
countries may not be possible to include in this IDA20 indicator.
September 2023

92

Individuals using the internet in IDA countries
A. Overview
Indicator nameIndividuals using the internet (% of population in IDA countries)

Definition(as it should appear on thedigital IDA RMS card)

Internet users are individuals who have used the Internet (from any location) in the last 3
months. The Internet can be used via a computer, mobile phone, personal digital assistant,games machine, digital TV etc.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 9.C: Universal Access to Information and Communications Technology

IDA20 Expected
range/value

NA

Included in IDA19

No

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Percent of Population☒ FCS☐ Females

Calculation method

Twice a year.
Methodology at the country level: The proportion of individuals using the Internet isexpressed as a percentage and is calculated by dividing the total number of in-scopeindividuals using the Internet by the total number of in-scope individuals, and thenmultiplying the result by 100. (ITU)
Methodology at the aggregate level: Aggregation Method: Weighted average (WDI)

Data Calculation Method

Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

World Development Indicators (WDI) at http://wdi.worldbank.org/.
Data Source(s)Country data are sourced from the International Telecommunications Union (ITU).
C. Key counterparts

93

Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

World Bank Annual Report (Regional snapshot) at
https://www.worldbank.org/en/about/annual-report

Limitations andExceptions

NA

Date methodology
agreed/updated

NA

94

Prevalence of undernourishment in IDA countries
A. Overview
Indicator name

Prevalence of undernourishment (% of population)

Definition(as it should appear on thedigital IDA RMS card)

Prevalence of undernourishment is the percentage of the population whose habitual foodconsumption is insufficient to provide the dietary energy levels that are required to maintaina normal active and healthy life.

Tier typeOne

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG Target 2.2 | Malnutrition: End all forms of malnutrition, including achieving targets onstunting and wasting in children under 5 years of age, and address the nutritional needs ofadolescent girls, pregnant and lactating women and older persons

IDA20 Expected
range/value

NA

Included in IDA19

No

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Percent of Population☒ FCS☐ Females

Calculation method

Once a year in September/October according to the data source’s update schedule (Food andAgriculture Organization (FAO)).

Data on undernourishment are from the Food and Agriculture Organization (FAO) of theUnited Nations and measure food deprivation based on average food available for humanconsumption per person, the level of inequality in access to food, and the minimum calories
required for an average person. For the estimation, FAO relies on the following data
sources: UN Population Division’s World Population Prospects and FAO Food Balance
Sheets. Data are expressed as a percentage: showing as 2.5 may signify a prevalence ofundernourishment below 2.5%.

Data Calculation Method

Review process: WDI data are annually reviewed by country and regional teams, GPs and
CCSAs, and Executive Director Offices during the Bank-wide review, in addition to routine
sanity checks every update.
Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDA-

95

financing)

World Development Indicators (WDI) at http://wdi.worldbank.org/.
Data Source(s)Food and Agriculture Organization at http://www.fao.org/faostat/en/#home.
C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

Limitations andExceptions

NA
When no recent household survey data is available on food consumption, the estimation isachieved through a model-based approach. This approach considers the mean level of
dietary energy consumption from Food Balance Sheets, an indirect estimate of thecoefficient of variation based on indicators such as the country's GDP, Gini coefficient of
Income, an index of the relative price of food, or other indicators of development such as
the country's Under 5 Mortality Rate. The UN Population Division's World Population
Prospects data is also used to estimate the Minimum Dietary Energy Requirement.
However, the accuracy of these estimates is generally low due to the uncertain nature of theinference and the margins of error associated with the model's parameters. While theoretical
Margins of Error cannot be calculated for these estimates, they are expected to be greaterthan plus or minus 2.5% in most cases. As a result, FAO only publishes national-level
estimates when they exceed 2.5%.

Date methodology
agreed/updated

96

TIER 2 INDICATORS

97

Generation capacity of renewable energy
A. Overview
Indicator name

Generation capacity of renewable energy (GW)

Definition(as it should appear on thedigital IDA RMS card)

The indicator measures in gigawatts (GW) the generation capacity of renewable energy
facilities to be enabled with direct, indirect, and/or enabling policy support through theWorld Bank’s operations in IDA-eligible countries (including IDA-blend). Data is reported
based on target values or projected results for assumed successful project completion asreported at the time of project approval, covering Investment Project Financing,
Development Project Financing, Program-for-Results, and Guarantees.
Renewable energy refers to electricity or heat from renewable sources, namely: the sun(solar photovoltaic, concentrated solar, solar water heater), wind; water (hydropower, wave,
tidal); combustion of organic matter from sustainable sources (bioenergy); or thermal
potential of the earth (geothermal). This covers grid, off-grid, bulk, and distributed sources.

Tier type

Two

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 7.2 – By 2030, increase substantially the share of renewable energy in the global
energy mix

IDA20 Expected
range/value

10 GW

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Gigawatt (GW)☒ FCS☐ Females

Calculation method

The data for this indicator is collected and updated annually (during Q1 of the fiscal year
following the referenced fiscal year).
Definition. The definition of the indicator captures direct, indirect, and enabling policy
support for renewable energy (RE) generation capacity:▪
▪

Data Calculation Method▪

Direct support covers financing of direct investments in physical infrastructure(both greenfield and brownfield) for renewable energy generation.
Indirect support covers financing of enabling infrastructure and activities(transmission and distribution, grid integration), and financing to support private
sector investment in renewable energy markets (including some technicalassistance such as transaction advisory, and market development support).
Enabling policy support includes the development or reform of government
policies or laws (including regulations) that are expected to accelerate theexpansion of renewable energy generation capacity. This may include policy
lending prior actions or technical assistance activities within financing operations.

Data Operationalization
1) The indicator includes direct, indirect, and enabling support through lending andrecipient-executed trust fund activities in all IDA-eligible countries (including IDAblend countries).
2) The reporting for this indicator is based on target values or projected results that are98expected to be achieved through the World Bank’s operations (Investment Project
Financing, Development Project Financing, Program-for-Results, and Guarantees).
3) RE generation capacity additions could be counted toward this indicator if Project
Appraisal Documents, Program Appraisal Documents or Program Documents have an
explicit reference to GW values supported by the project in the description of projectcomponents and/or the results framework of the project.
4) Trust-funded and IBRD-only financed operations in IDA-eligible countries that enable
RE generation capacity additions could be considered if these operations are embedded
in a broader energy sector engagement implemented by the government with thesupport of IDA. Only RE generation capacity additions that are quantifiable, verifiable,
and attributable (would not have been possible without overall IDA engagement in theenergy sector) would be counted.
5) In case of additional financing, only incremental increase of RE generation capacity(over and above what the parent project committed to achieve) is counted. When the
additional financing provides funds to support the achievement of the original RE target
under the parent project, then the additional financing results are not counted to avoid
double-counting.

Data Source(s)The data sources for this indicator are Project Appraisal Documents (for Investment Project
Financing and Guarantees), Program Appraisal Documents (for Program-for-Results),
Program Documents (for Development Project Financing), and Project Papers (forAdditional Financing).

C. Key counterparts
Contributing
PGs/GPs/Regions

N/A

D. Additional information
Harmonization withother corporate reporting
mechanisms:
Limitations andExceptions
Date methodology
agreed/updated

This indicator has been aligned – in terms of definition and target – with the IDA Policy
Commitment 4 “Sustainable Energy for All” which is focused on providing direct, indirect,
and enabling policy support for at least 10 gigawatts (GW) of renewable energy (including
at least one GW in FCS). The support would cover on-grid, off-grid, and distributed
renewable energy.
N/A
October 2023

99

Net GHG emissions
A. Overview
Indicator name

Net Greenhouse gas (GHG) emissions (total CO2 equivalent/year)

Definition(as it should appear on thedigital IDA RMS card)

Project level net (also termed as relative) GHG emissions are typically calculated as anannual average of the difference between emissions expected to be generated by project
activities aggregated over the economic lifetime of the project and the emissions of abaseline (counterfactual) scenario aggregated over the same time horizon. The indicator
applies to operations that are subject to GHG accounting under the corporate mandate. This
includes IBRD/IDA investment lending in Sustainable Development and Infrastructure
Practice Groups covering key economic sectors (Energy and Extractives; Transport;
Environment, Natural Resources and Blue Economy; Urban, Resilience and Land; Water;and Agriculture and Food) where World Bank-approved GHG accounting methodologies
and tools exist. The indicator is based on an ex-ante estimation performed during project
preparation using Bank approved methodologies and tools. The indicator value is negative if
the project is reducing or sequestering emissions, and positive if the project is increasing
emissions. Net GHG emissions is calculated as an aggregate of the net emissions of projects
delivered in the FY. If the project undergoes major restructuring or is subject to additional
financing relevant to GHG accounting, the ex-ante estimation of project net emissions needs
to be recalculated at the time of restructuring or processing additional financing. Net GHG
emissions are reported for entire projects regardless of the share of IBRD or IDA financing.

Tier type

Two

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 9.4: By 2030, upgrade infrastructure and retrofit industries to make them sustainable,with increased resource-use efficiency and greater adoption of clean and environmentallysound technologies and industrial processes, with all countries acting in accordance with
their respective capabilities

IDA20 Expected
range/value

Monitored

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation

Total CO2 equivalent/year☒ FCS(if relevant)☐ FemalesInternal Data Update
Frequency

Aggregate net emissions results are generated annually, reflecting projects that have gone to
Board for the given FY.

Calculation method

NA

Net GHG emissions is calculated as an aggregate of the net emissions of projects deliveredin the FY.
Data Calculation Method

Project level net GHG emissions are calculated as an annual average of the difference
between emissions expected to generate by project aggregated over the economic lifetime ofthe project and the emissions of a baseline (counterfactual) scenario aggregated over the100same time horizon. The indicator applies to operations that are subject to GHG accounting
under the corporate mandate. This includes IBRD/IDA investment lending in Sustainable
Development and Infrastructure Practice Groups covering key economic sectors (Energy
and Extractives; Transport; Environment, Natural Resources and Blue Economy; Urban,
Resilience and Land; Water; and Agriculture and Food) where World Bank-approved GHG
accounting methodologies and tools exist. The indicator is based on an ex-ante estimation
performed during project preparation using the approved methodologies and tools.
GHG emissions accounting for Investment Project Financing (IPFs) has been a corporate
mandate of the World Bank since 2012 following the World Bank Group Environment
Strategy. The WBG Environment Strategy (2012-20) further codified this agreement
through a proposal for the WB to start undertaking GHG accounting of investment projects
starting in FY13. The methodologies/tools have been since developed and evolved overtime
across the practice groups.
Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

Emissions numbers generated by task teams. The final GHG numbers (net emissions andgross emissions) are reflected in Ops Portal.

C. Key counterparts
Contributing
PGs/GPs/Regions

Energy and Extractives; Transport; Environment, Natural Resources and Blue Economy;
Urban, Resilience and Land; Water; and Agriculture and Food
All regions.

D. Additional information
Harmonization withother corporate reporting
mechanisms:

The WBG Corporate Scorecard

Limitations andExceptions

NA

Date methodology
agreed/updated

NA

101

People provided with access to clean cooking
A. Overview
Indicator namePeople provided with access to clean cooking (million)

Definition(as it should appear on thedigital IDA RMS card)

This indicator measures the number of people who are expected to gain access to new andimproved cooking services through the World Bank’s operations in IDA-eligible countries(including IDA-blend). Data is reported based on target values or projected results forassumed successful project completion as reported at the time of project approval, covering
Investment Project Financing, Development Project Financing, Program-for-Results, andGuarantees.

Tier type

Two

IDA20 Cycle Timeline

FY23-25

Relevant SDG

NA

IDA20 Expected
range/value

20 million

Included in IDA19

No

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Number of people (millions)☒ FCS☐ Females

Calculation method

The data for this indicator is collected and updated annually (during Q1 of the fiscal year
following the referenced fiscal year).
Definition. The definition of the indicator captures direct connections and continued
adoption of new or improved clean cooking services with end users in mind. It includes
interventions to provide efficient and clean cooking fuels and technologies. The indicatordoes not count on upstream projects on clean cooking fuels (liquified petroleum gas,
electricity, ethanol, and natural gas) production and transportation/transmission, as well as
general management of forestry or land.
Data Operationalization•

Data Calculation Method•••

The indicator includes support to new or improved clean cooking services throughlending and recipient-executed trust fund activities in all IDA-eligible countries(including IDA-blend).
The reporting for this indicator is based on target values or projected results that are
expected to be achieved through the World Bank’s operations (Investment Project
Financing, Development Project Financing, Program-for-Results, and Guarantees).
Clean cooking access results could be counted toward this indicator Project Appraisal
Documents, Program Appraisal Documents, or Program Documents have an explicit
reference to the number of people with new or improved access to clean cooking in thedescription of project components and/or the results framework of the project.
Aggregation of values for this indicator is done by calculating cumulative totals
committed at the project approval. In case of additional financing, only incremental

102

increase (over and above what the parent project committed to achieve) is counted.
When the additional financing provides funds to support the achievement of the original
target under the parent project, then the additional financing results are not counted to
avoid double-counting.

Data Source(s)The data sources for this indicator are Project Appraisal Documents (for Investment Project
Financing and Guarantees), Program Appraisal Documents (for Program-for-Results),
Program Documents (for Development Project Financing), and Project Papers (forAdditional Financing).

C. Key counterparts
Contributing
PGs/GPs/Regions

ESMAP’s Clean Cooking Fund Team (IEEES Unit) contributes to data collection andreporting on this indicator.

D. Additional information
Harmonization withother corporate reporting
mechanisms:

Limitations andExceptions

Date methodology
agreed/updated

N/A
Clean cooking projects may include expected results with units of measurement other than
the number of people. For the purposes of IDA RMS reporting, the following principles will
apply to convert different measurement units to the number of people with access to clean
cooking:• Number of households with access to clean cooking: multiply the number ofhouseholds by the country’s household size using the UN’s database on household sizeand composition 2022.
• Number of public institutions (e.g., schools, prisons etc.) provided with access to clean
cooking: multiply the number of public institutions by the number of people in the
public institution using the project data available.
• Number of improved cookstoves distributed: multiply the number of stoves distributedby the country’s household size, assuming one stove distributed per household.
• Number of refugee and host population provided with clean cooking solutions: same asa number of people with access to clean cooking.
October 2023

103

IDA countries supported to implement and/or update their NBSAPs
A. Overview
Indicator name

IDA countries supported to implement and/or update their NBSAPs (number)Definition(as it should appear on thedigital IDA RMS card)

The indicator measures the number of IDA countries supported to implement and/or update
their National Biodiversity Strategies and Action Plans (NBSAPs). The NBSAPs are themain vehicle for implementation of the Convention on Biological Diversity, including therecently adopted Kunming-Montreal Global Biodiversity Framework containing the new setof global biodiversity targets for the period of 2022-2030. NBSAPs are comprised ofnational strategies that reflect how a country intends to fulfill the global biodiversity targets,considering national circumstances, and the related action plans that constitute the sequenceof steps to be taken to meet these targets. Data are reported for countries that receive support
through interventions of IDA-financed operations to implement and/or update their
NBSAPs.

Tier type

Two

IDA20 Cycle Timeline

FY23-25

Relevant SDGs

SDG 15 – Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably
manage forests, combat desertification, and halt and reverse land degradation and halt
biodiversity loss.
SDG 14 - Conserve and sustainably use the oceans, seas and marine resources

IDA20 Expected
range/value

20 countries

Included in IDA19

No

B. Methodology
Unit of Measure
Reporting Disaggregation

Number of countries☒ FCS(if relevant)☐ FemalesInternal Data Update
Frequency

YearlyCalculation methodNA

The indicator measures the number of IDA countries supported to implement and/or update
their NBSAPs. This is tracked through the following steps:-

Data Calculation Method

Using World Bank systems (Operations Portal and Standard Reports) generating
lists of active and pipeline operations (for example the standard report “ST4.1
Lending Projects Sector & Theme Details”) and filter for:o Approval dates: projects that are (expected to be) approved within the
IDA20 cycle (FY23-25)
o Financing source: project that (will) receive IDA-financing
o World Bank’s operations theme codes: projects that are tagged with the“Biodiversity” sub-theme and other relevant sub-themes under“Renewable Natural Resources Asset Management” theme.
o Qualifying operations: IPF, DPF/DPL, and PforR. Activities dedicated torisk mitigation under the Environmental and Social Framework (ESS6)

104

-

-

are not eligible.
Conduct a word search in the documents of the shortlisted projects (PCNs, PIDs,
PADs, ISRs, and Project Papers) to identify relevant components and activities.
The word search will be performed partly manually and partly assisted by a text
analytics tool. Words that will be searched for include: ‘national biodiversity
strategies and action plans’, ‘national strategy on biodiversity’, ‘NBSAPs’,‘conservation’, ‘restoration’, ‘ecosystem’, ‘sustainable land management’,‘biodiversity’, ‘ecosystem services’, ‘protected areas’, ‘nature-based solutions’,‘habitat’ among others. Eligible activities also include policy reform which enables
those activities or scale up financing for nature. Note that the text analysis andword search may result in direct hits on the support to implementation/updating
NBSAPs (or a ‘national strategy on biodiversity’), or that further qualitative
analysis may be needed to assess/confirm whether project activities are eligible tobe counted under the indicator. This further analysis may involve looking at thecountry’s NBSAP and assessing whether project activities are supporting its
implementation/updating.
Based upon the final project list, report the IDA countries where the World Bank
has approved IDA-financed projects that support the implementation/updating of
NBSAPs. Continue to monitor the relevant pipeline projects throughout the IDA20
cycle.

Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

World Bank Operations Portal, Standard Reports, PADs, PCNs, ISRs, Project Papers.
Website with NBSAPs: https://www.cbd.int/nbsap/

C. Key counterparts
Contributing
PGs/GPs/Regions

Environment, Natural Resources and Blue Economy Global Practice

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

NA

Date methodology
agreed/updated

October 16th 2023

105

IDA countries with completed Country Climate Development Reports (CCDRs)
A. Overview
Indicator name

IDA countries with completed Country Climate Development Reports (CCDRs)(number)Definition(as it should appear on thedigital IDA RMS card)

The indicator measures the number of IDA countries with a completed Country Climate
Development Report (CCDR). The CCDR is a new Bank Group core ASA, which captures
the interplay between climate and development (including poverty reduction, growth,inequality). CCDRs are designed specifically to identify and analyze the disconnects
between climate and development policies, identifying the highest-impact actions to reduce
GHG emissions and build resilience, while delivering broader development goals.

Tier type

Two

IDA20 Cycle Timeline

FY23-25 (July 1, 2022, to June 30, 2025)

Relevant SDG

13.1 Strengthen resilience and adaptive capacity to climate-related hazards and natural
disasters in all countries.
13.2 Integrate climate change measures into national policies, strategies, and planning

IDA20 Expected
range/value

30-40 IDA countries with completed and published CCDRs

Included in IDA19

No, new indicator

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Number of countries☒ FCS☐ Females

Calculation method

NA

Quarterly

The indicator measures the number of IDA countries with a completed Country Climate
Development Report (CCDR) in the current FY. Completed is defined as being publishedon the WB Open Knowledge Repository website.
This is tracked through the following steps:•
Data Calculation Method•

Monitor and assess using World Bank systems, including the Operations Portal andOpen Knowledge Repository and through consultation with the Regional CCDR
coordinators
All unique/new IDA countries covered in published CCDRs since the start of the
IDA20 cycle (July 1, 2022) are counted toward indicator progress. Multiple countries
may be covered in a single CCDR.

Bank instrument type: ASAs
Note:
1.

[For country-based indicators (e.g., Number of IDA countries supported)] The

106

indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries
2.

Data Source(s)[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)Operations Portal, Open Knowledge Repository (where CCDRs are published), Regional
CCDR coordinators

C. Key counterparts
Contributing
PGs/GPs/Regions

CCDR Regional Coordinators

D. Additional information

Harmonization withother corporate reporting
mechanisms:•

IDA20 Policy Commitment: This indicator is fully aligned with IDA20 Climate
Change policy commitment (PC) #2 on CCDRs. The target for PC2 on CCDRs is 30
IDA countries with completed and published CCDRs. The Mid-Term Review target forinternal monitoring is 11 IDA countries. The baseline is zero.

•

CCAP: The CCAP includes a target of up to 25 CCDRs started in FY21. This indicator
is consistent with IDA20 PC and supports measuring its progress.

Objective of IDA20 PC2: Throughout the IDA20 period, CCDRs will be conducted in atleast 30 countries with priority to those with higher carbon emissions and deeper climate
vulnerabilities.

Limitations andExceptions

Rationale for IDA20 PC2: Throughout the IDA20 period and the remainder of the CCAP
2021-2025 period, CCDRs will be prepared for countries, with the selection determined by anumber of factors, including carbon emissions levels, the depth of climate vulnerabilities,
and the country engagement cycle. The CCDR is expected to inform country-level dialogue
on climate and development policy reforms and investments, as well as helping inform the
Bank Group country engagement process, and hence IDA operations going forward.
Anticipated Challenges: CCDR completion may be delayed due to political circumstances.

Date methodology
agreed/updated

November 2022

107

IDA-FCS supported in building capacity to use field-appropriate digital open-source tools
for collection and analysis of geo-tagged data, and apply this technology to enhance project
implementation and coordination
A. Overview

Indicator name

IDA-FCS supported in building capacity to use field-appropriate digital open-source
tools for collection and analysis of geo-tagged data, and apply this technology toenhance project implementation and coordination (number of IDA-FCS)

Definition(as it should appear on thedigital IDA RMS card)

Indicator tracks progress on building capacity of IDA/FCS clients as well as partners, andWorld Bank teams on the ground, to leverage field-appropriate technology for digital datacollection and analysis for enhanced monitoring, supervision and accountability of World
Bank-funded projects and within government systems. This indicator considers capacitybuilding as a programmatic approach to enhance M&E and supervision across projects
through client-oriented methods such as the innovative Geo-Enabling initiative for
Monitoring and Supervision (GEMS) to systematically enhance monitoring and evaluation(M&E) as well as supervision in FCV settings.

Tier type

Two

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 17.8 –Fully operationalize the technology bank and science, technology, andinnovation capacity-building mechanism for least developed countries by 2017 and enhance
the use of enabling technology, in particular information and communications technology

IDA20 Expected
range/value

18 countries (cumulative)

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Data Calculation Method

Number of countries☒ FCS☐ Females

Calculation method

NA

The data are updated in a tracking document continuously, as soon as new countries havefulfilled the requirements, as described below.
The IDA-19 PC, as well as the ongoing Tier 2 program under IDA-20, have been
implemented by the GEMS team, housed in the FCV group, through a client-focused digital
capacity-building and support program. The goal of this indicator was set to achieve
capacity building in 18 FCS countries. To monitor the achievement of the goal, the GEMS
team uses a yearly counting methodology and a two-tier verification approach, where every
year the team takes stock of the number of countries that actively apply GEMS taught skills
and tools in at least 2 projects and 1 sector of a given country portfolio. Adopting the annual
stock taking model allows for capturing the dynamic nature of capacity building and the
evolving FCS landscape in which the World Bank Group operates.
To facilitate indicator tracking, the team is using a robust centralized tracking tool thatserves as a repository of all projects that have been supported by GEMS, with a broad rangeof underlying data, including P-Codes, respective countries, FCS denomination, GPs, TTLs,

108and qualitative feedback, etc. The centralized tracking tool is updated after each training isdelivered to clients with the P-codes of projects whose PIUs participated in the training. Pcodes are collected as part of the training sign-up process.
To track progress in each country, respective GEMS team members follow up with clientsin their geographic portfolio on the use and adoption of tools. If confirmation has been
received from a PIU member that they effectively use tools and methodologies taught by
GEMS, the project ID gets recorded in a centralized tracking tool. At the end of each year,
this tool is used by the team to analyze whether at least 2 projects from 1 sector haveconfirmed the use of GEMS in each IDA-FCS country and if confirmed, then that country is
counted toward the target in this indicator,
It is important to note that as a capacity-building program, GEMS is not intended togenerate data for its own purposes. Rather it empowers project Implementation Units (PIUs)
to create customized data platforms for their specific needs and generate their own data to
feed into project decision-making processes in a decentralized manner. Therefore, there is
no automatic recording of collected data or the application of the system by the GEMS teamand the team relies on feedback by projects. In turn, the calculation of how and by whichclients GEMS is being used relies on feedback from project stakeholders, particularly
clients.
To collect systematic feedback, the GEMS focal points for each project proactively reachout to PIU staff (and TTLs, where applicable) to enquire to which degree the GEMS tools
and skills have been used by the projects. The focal points record both, categorized
information (e.g. use for M&E, ESF, Citizen Engagement, Supervision, TPM, etc.) andqualitative summaries on use cases, incl. quotes.
This specific calculation method has not been changed throughout IDA-19 and IDA-20.
Also, the tracking does not rely on records in any documents (PADs, CPFs, etc,), as thelatter may not represent the latest state or details on the M&E systems used by clients.
Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)NA

C. Key counterparts

Contributing
PGs/GPs/Regions

The ones relevant for the PC, which include IDA-FCS are the following: AWCF1;
AWCW3; AWCC1; AECE2; AECC2; AECE3; AECS2; LCC8C; MNCYE.
Relevant GPs, which have been supported in IDA-FCS as part of the PC, include thefollowing: AGF; DDT; EDU; EEX; ENB; GOV; HNP; SPJ; SSI; URL; WTR,

D. Additional information
Harmonization withother corporate reporting
mechanisms:

The IDA-19/20-related indicator as such is not recorded elsewhere.

109

Limitations andExceptions

The main challenge in terms of tracking this indicator is related to that fact that the PC is
implemented through a client-focused capacity-building program. As stated above, this
implies that the program relies on feedback from the respectively benefitting project teams
on client site (PIUs). The PIUs frequently face significant staff fluctuation and capacity
constraints, which can impact responsiveness.

Date methodology
agreed/updated

The methodology was agreed upon before the launch of IDA-19, in June 2020. For FY23
reporting, the team will use FY23 FCS list.

110Farmers adopting improved agricultural technology
A. Overview
Indicator name

Farmers adopting improved agricultural technology (million)
This indicator measures the number of farmers of the project who have adopted an
improved agricultural technology promoted by operations funded by IDA. Data are reported
for Investment Project Financing, Development Project Financing, Program-for-Results, andGuarantees unless otherwise specified.

Definition(as it should appear on thedigital IDA RMS card)•

Farmers are people engaged in farming activities or members of a farming business(disaggregated by men and women) targeted by the project.

•

Adoption refers to a change of practice or change in use of a technology that was
introduced/promoted by the project.

•

Technology includes a change in practices compared to currently used practices ortechnologies (seed preparation, planting time, feeding schedule, feeding ingredients,
postharvest storage/processing, and so on). If the project introduces or promotes atechnology package in which the benefit depends on the application of the entire
package (such as, a combination of inputs such as a new variety and advice onagronomic practices such as soil preparation, changes in seeding time, fertilizer
schedule, plant protection, and so on), this counts as one technology.

Source: Bank Guidance on Corporate Results Indicators
Tier type

Two

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 2.4 – By 2030, ensure sustainable food production systems to implement resilient
agricultural practices that increase productivity and production, that help maintainecosystems, that strengthen capacity for adaptation to climate change, extreme weather,drought, flooding, and other disasters and that progressively improve land and soil quality.

IDA20 Expected
range/value

6.5 – 7.0 million

Included in IDA19

Yes

B. Methodology
Unit of Measure

Number of people (in millions)☒ FCS

Reporting Disaggregation(if relevant)Internal Data Update
Frequency☒ Females

Calculation method

Twice a year

111

We use the data disaggregated by gender(male and female) for this indicator.

This indicator measures the number of farmers of the project who have adopted an
improved agricultural technology promoted by operations funded by IDA.
Data are reported via archived ISRs/ICRs for Investment Project Financing, Development
Project Financing, Program-for-Results, and Guarantees, unless otherwise specified.
The following are examples of Custom Indicators that can be considered:-

Number of Farmers adopting improved agricultural technology
Farmers in GCAP intervention areas who have applied improved technologies ormanagement practices (disaggregated by technology)
Number of small and medium farmers who adopted an improved agricultural
technology promoted by the project
Clients who adopted an improved agricultural technology promoted by project
Targeted farmers adopting soil moisture conservation practices and crop
production technologies
Farmers adopting climate-smart agricultural technologies

To identify the list of relevant projects, a portfolio review focusing on results framework is
carried out for projects under Agriculture, Fishing and Forestry Sector (AX Sector Code).
This list includes active projects and closed projects with an ICR due in the same reporting
FY. The ISRs/ICRs, once archived, can be downloaded anytime from the Operations Portal
for review.
ISR/ICR Review is done as follows:
Data Calculation Method

1) Review ISRs data (latest one archived in the reporting FY) for active projects; andclosed projects which do not yet have ICRs.
2) Review ICRs data for closed projects with completed ICRs.
3) In cases where data from ISR shows zero or negative progress value, TTL’s inputs
will be sought for validation and confirmation.
Calculation Methodology:4) (Current FY’s ISR progress data) – (previous FY’s ISR progress data) for ongoingprojects and closed projects without ICRs
5) (Current FY’s ICR data) – (latest FY’s ISR progress data) for closed projects withICRs
6) (Current FY’s ISR progress data) – (project baseline data) for new projects
approved in the current FY
Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)Archived ISRs and ICRs data available on Operations Portal.

C. Key counterparts

112

Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

NA

Date methodology
agreed/updated

June 12, 2023

113

Area provided with new/improved irrigation or drainage services
A. Overview
Indicator nameArea provided with new/improved irrigation or drainage services (Ha)This Corporate Result Indicator (CRI) measures in hectares the total area of land provided
with new or improved irrigation or drainage services in operations funded by IDA. This
includes:(i)(ii)

The area provided with new irrigation or drainage services (hectare), andThe area provided with improved irrigation or drainage services (hectare)

Data are reported for Investment Project Financing, Development Project Financing,
Program-for-Results, and Guarantees, unless otherwise specified.
Definition(as it should appear on thedigital IDA RMS card)•

Irrigation or drainage services refers to the better delivery of water to, and drainage
of water from, arable land, including better timing, quantity, quality, and costeffectiveness for the water users.

•

New irrigation or drainage services refers to the provision of irrigation and drainage
services in an area that has not had these services before. The area is not necessarily
newly cropped or newly productive land, but is newly provided with irrigation anddrainage services, and may have been rain-fed land before.

•

Improved irrigation or drainage services refers to the upgrading, rehabilitation,
and/or modernization of irrigation or drainage services in an area with existing
irrigation and drainage services.

Source: Bank Guidance on Corporate Results Indicators
Tier type

Two

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 2.4 – By 2030, ensure sustainable food production systems to implement resilient
agricultural practices that increase productivity and production, that help maintainecosystems, that strengthen capacity for adaptation to climate change, extreme weather,drought, flooding, and other disasters and that progressively improve land and soil quality.

IDA20 Expected
range/value

1.5 – 2.0 million

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Hectares (Ha)☒ FCS☐ Females

Calculation method

Twice a year

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This indicator measures in hectares the total area of land provided with new or improved
irrigation or drainage services in operations funded by IDA. This includes
(iii)
(iv)

The area provided with new irrigation or drainage services (hectare), andThe area provided with improved irrigation or drainage services (hectare)

Data are reported via archived ISRs/ICRs for Investment Project Financing, Development
Project Financing, Program-for-Results, and Guarantees, unless otherwise specified.
The following are examples of Custom Indicators that can be considered:-Area provided with improved irrigation investments
Area under irrigation through rehabilitated systems
Area with a request for improved irrigation technologies approved
Targeted irrigable land rehabilitated
Area with increased drainage capacity for a 10-year return period

To identify the list of relevant projects, a portfolio review focusing on results framework is
carried out for projects under Agriculture, Fishing and Forestry Sector (AX Sector Code).
This list includes active projects and closed projects with an ICR due in the same reporting
FY. The ISRs/ICRs, once archived, can be downloaded anytime from the Operations Portal
for review.
ISR/ICR Review is done as follows:
1) Review ISRs data (latest one archived in the reporting FY) for active projects; andclosed projects which do not yet have ICRs.
2) Review ICRs data for closed projects with completed ICRs.
3) In cases where data from ISR shows zero or negative progress value, TTL’s inputs
will be sought for validation and confirmation.

Data Calculation Method

Calculation Methodology:4) (Current FY’s ISR progress data) – (previous FY’s ISR progress data) for ongoingprojects and closed projects without ICRs
5) (Current FY’s ICR data) – (latest FY’s ISR progress data) for closed projects withICRs
6) (Current FY’s ISR progress data) – (project baseline data) for new projects
approved in the current FY
Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)Archived ISRs and ICRs data downloaded from Operations Portal.

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

115

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

NA

Date methodology
agreed/updated

June 12, 2023

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People provided with new or improved electricity service
A. Overview
Indicator namePeople provided with new or improved electricity service (million)
The indicator measures the number of people that have received new or improved electricity
service through the World Bank’s operations in IDA-eligible countries (including IDAblend). This includes estimates of direct access, inferred access, and improved service. Datais reported based on actual results achieved in a referenced fiscal year, covering Investment
Project Financing, Development Project Financing, Program-for-Results, and Guarantees.
The indicator is a composite of the following estimates:

Definition(as it should appear on thedigital IDA RMS card)

•

•

•

Direct access measures the number of people in households previously lacking
electricity service that benefited from the new grid or off-grid service. This measure isbased on operations’ results reports for household electricity access.
Inferred access measures the number of people in households previously lacking
electricity service that are likely to have benefited from new services made possible as
an indirect result of investments that increased the availability of electricity in the gridin the given country.
Improved service measures the number of people in households with pre-existing grid
service that are likely to have benefited from attaining a higher tier of electricity service
under the Multi-Tier Framework for Energy Access (mtfenergyaccess.esmap.org).

Tier type

Two

IDA20 Cycle Timeline

FY 23-25

Relevant SDG

SDG 7.1.1 – Proportion of the population with access to electricity

IDA20 Expected
range/value

35 – 50 million

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Number of people (in millions)☒ FCS☐ Females

Calculation method

The data for this indicator is collected and updated annually (during Q1 of the fiscal year
following the referenced fiscal year).
Data Operationalization•

Data Calculation Method•

The indicator of people provided with new or improved electricity service is acomposite of estimates of direct access, inferred access, and improved service
supported through lending and recipient-executed trust fund activities in all IDAeligible countries (including IDA-blend).
The reporting for this indicator is done based on actual results achieved in areferenced fiscal year through the World Bank’s operations (Investment Project
Financing, Development Project Financing, Program-for-Results, and Guarantees).

117

•

•

•

Direct access results are captured by the results frameworks of the projects andreported based on the Implementation Status and Results (ISR) and
Implementation Completion Results (ICR) Reports that capture the number ofpeople that have been provided new or improved electricity service as a direct
result of the Bank’s operation.
Inferred access and improved service results are estimated using a methodology of
the World Bank’s Energy and Extractives Global Practice based on operations’
results reports for increases in generation, transmission and distribution capacity,or other relevant indicators. The methodology for inferred access and improved
service applies only to projects that do not capture direct access results.
In case of additional financing, only incremental increase (over and above what theparent project committed to achieve) is counted. When the additional financing
provides funds to support the achievement of the original target under the parent
project, then the additional financing results are not counted to avoid doublecounting.

Calculating direct access results
The direct access results for the fiscal year are calculated as an increment to the previous
fiscal year’s results, for which the following formula is used:
𝒓𝒆𝒑𝒐𝒓𝒕𝒆𝒅𝑽𝒂𝒍𝒖𝒆𝒄𝒖𝒓𝒓𝒆𝒏𝒕𝑭𝒀 = 𝒓𝒆𝒔𝒖𝒍𝒕𝒄𝒖𝒓𝒓𝒆𝒏𝒕𝑭𝒀 − 𝒓𝒆𝒔𝒖𝒍𝒕𝒑𝒓𝒆𝒗𝒊𝒐𝒖𝒔𝑭𝒀
Calculating inferred access and improved access results
•

•
•

•

•

Data Source(s)Energy and Extractives Global Practice uses in-house model to calculate theinferred and improved access results. The model is based on the country-specificparameters, historical trends of residential electricity access for each country, andproject-specific results.
The model was constructed to capture the comprehensive energy sector parameters,
including data on electricity access levels, average household consumption,
household electrification growth, and other parameters.
The model establishes a relationship between additional available electricity andthe additional electricity consumption by newly connected households. The
model’s calculations allow for inference of the number of people expected toreceive new connections from a given project (inferred access), as well as thenumber of people expected to improve their tier of electricity service according to
the Multi-Tier Framework for Energy Access (improved access). By using countryspecific empirical data, this methodology improves the accuracy of conservatively
estimated progress on new or improved electricity services for each project.
The methodology captures new or improved electricity service results forgeneration, transmission and distribution projects, covering a full range ofinvestments in the energy sector value chain which result in increased availabilityof electricity for household (new or increased) consumption. Thereby themethodology provides a complete perspective of the ramifications of energy accessprojects on the provision of electricity service.
Following the update of parameters and the list of relevant generation andtransmission and distribution projects and project-specific results achieved in areferenced fiscal year, the model automatically updates the results for the numberof people with inferred and improved access.

The data sources for this indicator are Implementation Status and Results Reports (ISRs)and Implementation Completion Results Reports (ICRs).

C. Key counterparts

118

Contributing
PGs/GPs/Regions

ESMAP’s Access Team (IEEES Unit) contributes to data collection and reporting on thisindicator.

D. Additional information
Harmonization withother corporate reporting
mechanisms:

Aligned with CSC Indicator “Millions of people provided with access to electricity”.

•

The corporate results indicator (CRI) used most often to capture direct access results is“people provided with new or improved electricity service”. However, the project could
also include custom indicators with other units of measurement for direct access results.
If the results indicator captures the number of households/connections, results reported
by Implementation Status and Results Reports (ISRs) and Implementation Completion
Results Reports (ICRs) need to be converted to the number of people.
Direct access results indicators should report cumulative numbers. As some results
frameworks may include annual targets, the reporting team should pay attention to thetype of indicator reported in Implementation Status and Results Reports (ISRs) and
Implementation Completion Results Reports (ICRs). If the type of indicator is not clear,
the reporting team should check project documentation and/or confirm with the project
teams that the reported numbers are cumulative.

Limitations andExceptions•

Date methodology
agreed/updated

October 2023

119

Beneficiaries reached with financial services supported by World Bank operations
Persons that benefitted from financial services supported by World Bank operations
Businesses that benefitted from financial services supported by World Bank operations
A. Overview
Indicator name-

Persons that benefitted from financial services supported by World Bank
operations (million)
Businesses that benefitted from financial services supported by World Bank
operations (million)

The indicator measures the number of persons who benefitted from financial services inoperations supported by IDA, and the number of businesses that benefited from financial
services. Data is reported for Investment Project Financing, Development Project Financing,
Program-for-Results, and Guarantees unless otherwise specified.
•Definition(as it should appear on thedigital IDA RMS card)

Persons that benefited from financial services: Number of persons reached withfinancial services in operations supported by the World Bank. Financial services
include transaction accounts, deposit accounts, mobile money accounts, loans,insurance, housing finance, and so on. Note: Reports on financial services tomicroenterprises and individuals/people are not always well-separated since someindividuals take out personal loans for use in microenterprises. These numbers will bereported on as provided by the client.

•

Businesses that benefited from financial services: Number of businesses reachedwith financial services in operations supported by the World Bank. Beneficiaries
include microenterprises, small and medium enterprises, and large businesses. Financial
services include transaction accounts, deposit accounts, mobile money accounts, loans,insurance, pension, factoring, leasing, bonds, and so on. Note: Since large businesses
make up a minute number of beneficiaries in client countries and since they are very
difficult to separate and almost all countries don’t report on them separately, thisindicator will include all businesses. Reports on financial services to microenterprises
and individuals/people are not always well-separated since some individuals take out
personal loans for use in microenterprises. These numbers will be reported on asprovided by the client.

Tier type

Two

IDA20 Cycle Timeline

FY23-25 (inclusive)

Relevant SDG

SDG 8.10: Strengthen the capacity of domestic financial institutions to encourage andexpand access to banking, insurance, and financial services for all

IDA20 Expected
range/value• 4.75-6.175 million beneficiaries (persons/ individuals)• 0.25-0.325 million beneficiaries (businesses/ firms)
This represents a total of 5.0 – 6.5 million beneficiaries (of which 95% are individuals and
5% firms)

Included in IDA19

Yes

B. Methodology
Unit of Measure

Number of people/businesses (million)

Reporting Disaggregation☒ FCS(if relevant)☒ Females

Calculation method

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Including a gender component anddisaggregating data by sex within projects
has allowed for doing a simple count. For
projects where no breakdown is provided particularly projects contributing with highnumbers, beneficiaries are estimated using
the methodology found in Annex 1 -thismethodology has been used since 2016 toensure consistency.
Internal Data Update
Frequency

Annually, during Corporate Scorecard update
Several steps are taken to identify and verify relevant indicators:

Data Calculation Method

1) A list of identified projects and indicators expected to contribute to results(provided by FCI) is used as a preliminary reference list and serves as the basis of
the annual update (IDA projects targets list).
2) A manual search using keywords (e.g., financial services, account, loan, mortgage,
housing, finance, credit, insurance, cash, mobile money, beneficiaries, and so on) is
done directly in the data dump file (excel file) that is provided by OPCS every
year. This way, a preliminary list of projects with potentially relevant indicators is
obtained -while most relevant projects belong to FCI and are mostly identified(through the IDA projects targets list), there are projects from other GPs that
contribute to results and the manual search is helpful to identify them. In addition,
looking into every project and indicator from the entire FCI active and pipeline
portfolio is helpful in identifying those new projects that need to be tracked andavoiding missing any from the targets list or during the manual search in the data
dump file.
3) Each potential indicator is analyzed and verified to be relevant and attributable byconsulting context documents such as PADs, PIDs, and RES and with TTLs to
confirm (especially projects contributing with large numbers). This is especiallynecessary when it is difficult to determine relevance and attribution (e.g. genericindicators like “Project beneficiaries”).
4) Once the indicator is confirmed as relevant and beneficiaries as attributable under
the project/ intervention, it is added to the excel master file where progress istracked.
5) Data sources are generally ISRs for ongoing projects, and ICRs for closed projects.
Nonetheless, in many cases, other documents need to be consulted to understandthe project, any changes in the project or the indicator. Also, TTLs need to be
consulted, to confirm data and attribution of results, especially those that contributewith high numbers and/or show drastic changes (in some cases, mostly for projects
with a significant contribution, managerial approval is requested).
6) Finally, a flag for job-focused interventions is included for reference in the excel
master file. Reported results under the CRI for financial services is currently used
as a proxy for the Jobs CRI.
Calculation of results (net progress) during corresponding FY update•

Yearly reported results account for net progress achieved during the FY for which
the update is done. For instance, the net progress value for FY23 update will becalculated as follows:••(FY23 ISR progress data) – (FY22 ISR progress data) for ongoing projects
and closed projects without ICRs
(FY23 ICR data) – (latest FY22 ISR progress data) for closed projects with

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•

ICRs
(FY23 ISR progress data) – (project baseline data) for new projects

Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only
and blend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

OPCS data file (provided at the beginning of the Fiscal Year), Operations Portal, Standard
Reports, ICRs, ISRs, PADs, PIDs and RES. In some cases (mostly when there is an error in
any of these reports, we use the information provided by TTL and share TTL/ PM
confirmation email as supporting document).

C. Key counterparts
Contributing
PGs/GPs/Regions

All EFI regions. Finance, Competitiveness, and Innovation. Other contributing GPs include,
but are not limited to: AGR, SPLJ, ENR, and EEX.

D. Additional information
Harmonization withother corporate reporting
mechanisms:

WBG Corporate Scorecard
When setting targets, FCI has been asked to identify projects that will contribute to results.
This also provides a preliminary list of projects to track.
Using the CRI in projects must be encouraged across teams and GPs (especially within
FCI). A note next to the CRI could provide more context about who the beneficiaries are
and how they are being benefitted (e.g., using a customized indicator).

Limitations andExceptions

Current potential limitations of data include the lack of disaggregated data by sex
across several projects and that reports on financial services to microenterprises andindividuals/people are not always well-separated since some individuals take out
personal loans for use in microenterprises. To address these issues, and as indicatedbefore, female beneficiaries for those projects that do not provide such a breakdown, andparticularly projects contributing with high numbers, beneficiaries are estimated using themethodology found in Annex 1 -this methodology has been used since 2016 to ensure
consistency. Ideally, including a gender component and disaggregating data by sex withinprojects will allow for doing a simple count. Regarding separating microenterprises andindividuals/people, these numbers will be reported as provided by the client. Information
about beneficiaries is described in the PADs and/or other relevant project documents.
The exact date is not available. Circa 2013. Indicators were reviewed in 2018. In addition,
IDA cycles were revised from 3 years to 2 years in 2018.

Date methodology
agreed/updated

Methodology for estimating female beneficiaries: 09/30/2016 (This methodology was
initially developed to address the lack of disaggregated data by sex. As disaggregated data
becomes more widely available, this methodology could stop being used).

122

Beneficiaries in IDA countries of job-focused interventions
A. Overview
Indicator nameBeneficiaries in IDA countries of job-focused interventions (million)
The indicator measures the number of beneficiaries reached by interventions that contributeto the jobs agenda in operations funded by IDA. The indicator captures the cross-cutting
nature of the jobs agenda, as beneficiaries (disaggregated by gender) may be individuals,
workers, households, farmers, microenterprises, small and medium-sized enterprises (SME),
and other target groups that benefit from IDA-supported operations in different sectors andtypes of operations. Data is reported for Investment Project Financing, Development Project
Financing, Program-for-Results, and Guarantees, unless otherwise specified.

Definition(as it should appear on thedigital IDA RMS card)•

Jobs are defined as “activities that generate income, monetary or in kind, without
violating human rights” (Source: WDR on Jobs, 2013).

•

Jobs-focused interventions are those contributing to the jobs agenda that have an
explicitly stated and substantive link to creating more, better, and/or inclusive jobs•

Jobs agenda supports the creation of better-quality jobs for more people. The Jobs
agenda is broad and includes interventions on the supply and demand side, acrossvarious sectors and cross cutting themes. It includes (but not limited to) the following:

•
•
•
•
•
•

expanding employment or labor force participation
increasing employability of unemployedincreasing firm entry and employment
improving labor productivity, skills, earnings, or livelihood
improving working conditions or benefits
developing value chains to create more and better jobs downstream or greening jobs

Tier type

Two

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 8.5: By 2030, achieve full and productive employment and decent work for all womenand men, including for young people and persons with disabilities, and equal pay for workof equal value.

IDA20 Expected
range/value

Monitored

Included in IDA19

Yes

B. Methodology
Unit of Measure

Number of people (in millions)☒ FCS

Reporting Disaggregation(if relevant)Internal Data Update
Frequency☒ Females

Calculation method

The data on females is reported by the
projects, either as a share of total
beneficiaries or as numbers.

The data is updated annually as a part of IDA RMS exercise led by OPCS

123

The Jobs CRI is a composite indicator, and it aggregates data from the following indicators:
1.
2.
3.
4.
5.
6.

Data Calculation Method

direct project beneficiaries of jobs focused interventions (Jobs Group)
beneficiaries of labor market programs (SPJ GP)
farmers reached with agricultural assets and services (AGRI GP)
teachers recruited or trained (EDUC GP)
students benefitting from direct interventions to enhance learning (TVET & tertiary
learning only) (EDUC GP)
beneficiaries reached with financial services (FCI GP)

The first indicator captures jobs relevant indicators that are not included in GP estimates andis analyzed by the Jobs Group using indicator data shared by OPCS. The other indicators(nos. 2-6) are reported directly by respective GPs and we take the data verbatim. Before
aggregating the data, we ensure that indicators are not reported by multiple GPs andduplications are removed to improve accuracy. Indicator values are reported separately for
individual beneficiaries and firm beneficiaries. We also perform quality checks to ensure
indicator values are reflected accurately. For example, we double check indicators thatreport a value that is significantly higher (or lower) than the previous year or baseline; wereview indicators where the task team hasn’t reported any values to check if there was noprogress or information hasn’t been updated. We also compare indicator value to the unit ofmeasurement. For example, if the unit of measurement is percentage and the value reported
is expressed as a number, the indicator is further investigated. When a sub indicator ishigher than average, it is flagged for verification in a results brief or the IDA RMS report.
Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

Data source: Indicator values reported in Project ISRs and ICRs by Operational Task
Teams.

C. Key counterparts
Contributing
PGs/GPs/Regions

FCI GP, SPJ GP, Education GP, Agriculture and Food GP, Jobs GroupD. Additional information
Harmonization withother corporate reporting
mechanisms:

The update is shared with HD VPU and reported in Jobs Brief for Annual and Spring
meetings, on Jobs Group promotional materials and Jobs MDTF Annual Report for donors.

Limitations andExceptions

Anticipated Challenges: The indicator is dependent on GPs who are responsible forreporting aggregate numbers. This may lead to delay and there is risk associated with GPs
dropping an indicator during an IDA cycle.

Date methodology
agreed/updated

The indicator was designed in FY 18 and has since been estimated annually.

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People with enhanced access to transportation services
A. Overview
Indicator namePeople with enhanced access to transportation services (million)

Definition(as it should appear on thedigital IDA RMS card)

Number of direct and indirect beneficiaries that experience improved access to transport
infrastructure and services that have been built or rehabilitated through World Bankfinanced project (including highways, rural roads, urban and interurban roads, mass transit
systems, ports/waterways, railways and airports). Beneficiaries typically experience
reductions in cost and time to travel and/or improvements in safety, as well as increased
access to markets, job opportunities, and health and education services. In urban areas,
beneficiaries include the increase in the number of users of improved services. In rural
areas, beneficiaries include the increase in the number of people who live in proximity to
improved services. Data is reported for Investment Project Financing, Development Project
Financing, Program-for-Results, and Guarantees, unless otherwise specified.

Tier type

Two

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 9.1: Develop quality, reliable, sustainable, and resilient infrastructure, including
regional and transborder infrastructure, to support economic development and human wellbeing, with a focus on affordable and equitable access for all.

IDA20 Expected
range/value

90 – 105 million

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Data Calculation Method

Number of people (in millions)☒ FCS☐ Females

Calculation method

Every 6 months
First, the team identifies all IDA projects (IPF, P4R) from the Transport GP that were activeat any time of the reporting period (FY). Starting with the FY23 update, the search will also
include projects outside of the Transport GP coded with >40% core transport sub-sectors.
Then, the indicator is calculated by adding the actual value reported on beneficiaries intransport projects, taken from the last available ISR or ICR on the given fiscal year, andsubtracting it from the previous year’s figure to obtain the net progress increment. Since theindicator was introduced around January 2020, a number of equivalent indicators are taken
into account while projects retrofit or introduce the new indicator. The most found are:-Direct Project Beneficiaries
People provided with an all-season road
Number of direct and indirect beneficiaries having enhanced access to roadtransport services
Number of persons living within X km of an all-weather road

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-

People provided with an all-season road
Number of people provided with improved climate resilient road accessPopulation having access to roads with upgraded safety and climate resilience
Rural Accessibility Index (proportion of the rural population who live within 2 kmof an all-season road)
Daily bus/BRT/metro passenger ridership
Number of people with enhanced access to transportation services

For projects without a valid indicator (~40%), the GP will liaise with PMs and Task Teams
to identify an estimated baseline, target, and progress on beneficiaries while teams
restructure projects to formally include an indicator in the Results Framework.
Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

Last available ISR or ICRs before the end of the FY

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

WBG CSC and IDA RMS

Limitations andExceptions

Challenges: Our main problem still is the number of projects that don’t have a valid
indicator to measure these beneficiaries (more than one third) followed by the fact that mostprojects tend to only report on progress once the infrastructure is built and the project isalmost closed.
Mode of transport / subsector:
Roads/Highways
Number of direct and indirect beneficiaries having enhanced access to road transport
services as a result of interventions supported by the World Bank Group (including
highways, secondary roads, rural roads):
Direct beneficiaries typically include the current and new users (normal, diverted, andgenerated traffic) of the road who will benefit from reductions in cost and time to travel
and/or improvements in safety, quality, comfort. This would be reported as ADT, multipliedby an appropriate contextual occupancy factor per passenger car unit (PCU).
Indirect beneficiaries would include residents who live in the immediate hinterland of theroad (within 2 km using the improved RAI methodology) who will benefit from improved
safety along the road, higher environmental standards along the road, and the potential forincreased access to local markets, job opportunities, and health and education services.
Railways
Number of direct and indirect beneficiaries having enhanced access to railway transport
services as a result of interventions supported by the World Bank Group (including, rural,inter-urban, long-distance urban, and international passenger services):126Direct beneficiaries typically include the current and new users (normal, diverted, andgenerated traffic) of the railway service who would benefit from reductions in cost and timeto travel and/or improvements in safety, quality, comfort.
Indirect beneficiaries would include residents who live in the serviced hinterland (catchmentarea) of the railway service who will benefit from improved access to local markets, job
opportunities, and health and education services
Catchment area is defined as the geographic area served by the railway and it can becalculated by estimating the number of people living or working within x kilometers fromthe stations on the railway line. The catchment area radius will vary depending on the typeof service as higher speeds, quality, and frequencies tend to attract passengers from farther
away. Other factors influencing the size of the catchment area will depend on national
characteristics such as willingness of population to drive to train stations or access tomultimodal connection to and from the train station. For freight railways or services, theindicator would be the increased tons carried annually by the railway.
Urban Transport
Number of direct and indirect beneficiaries with enhanced access to urban transport services
as a result of interventions (including public transport, non-motorized transport, traffic
management and other systems, etc.) supported by the World Bank Group:
Direct beneficiaries include all regular users of the improved system who may benefit from
improved access to job opportunities, local markets, and health and education services, aswell as improved mobility, safety, security, and environmental conditions. For example, fora mass transit project (i.e. BRT or metro), direct beneficiaries would be the typical weekday
ridership on the main lines including feeder services.
Indirect beneficiaries include people living or working in the influence or catchment area ofthe project who may eventually benefit from improved accessibility, mobility, safety,
security, or environmental conditions even if they are not daily users of the system. The
influence area of the project will be defined by Task Team based on census data, theproject's urban accessibility analysis (if available) or other available data considering thecharacteristics of project, quality of services, and other factors such as local and national
travel characteristics.
IWT / Ferries
Number of direct and indirect beneficiaries having enhanced access to inland or maritime
transport services as a result of interventions supported by the World Bank Group(passenger, coastal, ferry, IWT vessel, etc.):
Direct beneficiaries typically include the current and new users (normal, diverted, andgenerated traffic) of the services who would benefit from reductions in cost and time totravel and/or improvements in safety, quality, comfort.
Indirect beneficiaries would include residents who live in the serviced hinterland (catchmentarea) of the passenger service who will benefit from improved access to local markets, job
opportunities, and health and education services
Catchment area is defined as the geographic area served by the inland or maritime transport
services, and is proposed to be estimated by multiplying the number of people living or
working within x kilometers from the calls/ports on the route of inland or maritime transport
services. The catchment area radius will vary depending on the type of service as higher
speeds, quality, and frequencies tend to attract passengers from farther away. Other factors
influencing the size of the catchment area will depend on national characteristics such as
willingness of population to drive to ports/ferry terminals etc.
For freight services, whether maritime or inland, the indicator would be the increased tons
carried annually by the ship/ferry/IWT vessel.
Aviation
Annual seat capacity offered by airlines in operation in the subject airport.
Date methodology
agreed/updated

January 2020

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People provided with improved urban living conditions
A. Overview
Indicator namePeople provided with improved urban living conditions (million)

Definition(as it should appear on thedigital IDA RMS card)

The indicator measures the cumulative number of people living in urban areas thathave been provided with access to improved services, housing, tenure,neighborhoods, public spaces, parks, resilience and/or urban environmental
conditions, through the direct interventions of operations financed by IDA. Data isreported for Investment Project Financing, Development Project Financing, Programfor-Results, and Guarantees, unless otherwise specified

Tier type

Two

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 9.1: By 2030, ensure access for all to adequate, safe and affordable housing andbasic services and upgrade slums.

IDA20 Expected
range/value

15 – 20 million

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation

Number of people (in millions)☒ FCS(if relevant)☐ FemalesInternal Data Update
Frequency

AnnualData Calculation Method

Calculation method

The indicator measures the cumulative number of people living in urban areas andonly the net progress value of the referenced FY is calculated. The required data is
obtained from ISRs and ICRs.
ISR data: ISRs by archived FY will be provided by ITS/OPCS. The focal pointcleans the ISR database to make sure the reported figures are sound and to determine
which projects and indicators should be used to calculate the data.
ICR data: ICRs by archived FY will be provided by ITS/OPCS. The focal pointcleans the ICR database to make sure the reported figures are sound and to determine
which projects and indicators should be used to calculate the data.
The net progress value is calculated through the following methodology:

128

Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)]
The indicator should include all countries that are IDA-eligible (both IDAonly and blend). See: https://ida.worldbank.org/en/about/borrowingcountries[For project-based indicators (e.g., People provided with…)] The indicator
should include all the projects that are only-IDA financier type, blendfinancier type (including IDA-financing), and Trust-fund financier type(including IDA-financing)

OPCS data-dump, Operations Portal, Standard Reports which extracts data from ISRsand ICRs, in addition to desk reviews of key PADs, ISRs, and ICRs

C. Key counterparts
Contributing
PGs/GPs/Regions

SURGP

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

The main challenge is that task teams do not always use the exact language of theindicator, and thus focal points need to search and track indicators through the use of
key words such as "urban"; "cities", "resilient cities", "slum upgrade", "improve
quality of water supply or sanitation", "sewerage", "sidewalks", "roads", "housing","park", "public space", "flood", "electricity" and "waste collection", "Solid Waste
Management" that are typical for urban projects.

Date methodology
agreed/updated

The current focal point joined in FY20 and the current methodology was already in
place

129

Beneficiaries of social safety net programs
A. Overview
Indicator nameBeneficiaries of social safety net programs (individuals, in million)

Definition(as it should appear on thedigital IDA RMS card)

This indicator measures the number of individuals benefiting from safety nets programs
supported by IDA. Safety nets programs are designed to provide social assistance to poorand vulnerable individuals or families by including them in cash transfers (conditional andunconditional), public works and workfare programs, fee waivers for services, and in-kindassistance to address critical needs (such as, food, medicine, shelter, and social services).
Data are reported for Investment Project Financing, Development Project Financing,
Program-for-Results, and Guarantees, unless otherwise specified.

Tier type

Two

IDA20 Cycle Timeline

FY23-25
SDG 1.2: By 2030, reduce at least by half the proportion of men, women and children of allages living in poverty in all its dimensions according to regional definitions.

Relevant SDG
SDG 1.3: Implement nationally appropriate social protection systems and measures for all,including floors, and by 2030 achieve substantial coverage of the poor and the vulnerable.
IDA20 Expected
range/value

75 – 375 million

Included in IDA19

Yes

B. Methodology
Unit of Measure

Number of people (millions)☒ FCS
The unit of measurement is the number ofindividuals, both total and female, inmillions, as provided in the ISRs.

☒ Females

Calculation method

Reporting Disaggregation(if relevant)☒ COVID
Beneficiaries

Calculation method

130

If the values are reported as households,
rather than individuals, the value ismultiplied by the average household size ofthe country. If the female beneficiaries’
values are reported as a percentage of total,
the calculation is made to establish thenumber of individuals. In case neither theindividual nor percentage value of female
beneficiaries are documented in the ISR, thevalues are calculated at 50% of total
individual beneficiaries.
Beneficiaries of COVID-19 programs are asubset of the total number of SSN
beneficiaries. The value is calculated using
only operations tagged for COVID-19.
Information on the COVID-19 tag isavailable in the Standard Reports as well as
the operations portal and can be used to
identify operations responding to the
COVID-19 crisis.
Internal Data Update
Frequency

While ISRs are completed every 6 months, the values may not change, as they are typically
updated on annual basis by the countries. The value reported is the latest ISR value
available.
Step 1: Delete any projects from prior year that has the ICR values reported.
Step 2: Highlight any project that closed in the past two years and has not yet had the ICR
values included in the tabulation. Calculate incremental value by subtracting prior progress
value and baseline values from final value and report this number. It is important to record
decision and rationale for any judgements that are made.
Step 3: For active projects, search for SSN CRI or similar indicator for existing projects on
the list, and for any project from the prior year that may have been excluded. If there areseveral indicators, select the indicator that 1) is most similar to the CRI and 2) is at the PDO
level over intermediate level Include values as reported in the ISR, doing calculations toconvert value to individuals, if necessary. Calculate incremental value by subtracting priorprogress value and baseline values from final value and report this number. It is importantto record decision and rationale for any judgements that are made (for instance, number of
average HH size for calculation and source of information).
Step 4: Add any projects that are new in the current FY that have the SSN CRI or similar
indicator. Include projects with values of zero (0) as the values since new projects often do
not have beneficiaries in the first few years. This ensures that projects are not missed insubsequent years and contributes to the value of the number of countries included in thereport.
Final value is the sum of values reported for Steps 2-4.

Data Calculation Method

1) Defining key terms that limit what is counted: Any project with an indicator thatmatches or is similar to the CRI for SSN beneficiaries. If there are several
indicators, select the indicator that 1) is most similar to the CRI and 2) is at
the PDO level over intermediate level.
2) Specifying formulas used: Exact number reported from latest ISR if given as
individuals in millions; calculate individuals from households if necessary;calculate %female beneficiaries from total if necessary; for any project that
does not provide count of female beneficiaries, calculate value at 50% female
beneficiaries.
3) Specifying instrument types included: Any IPFs, DPFs, P4Rs and TFs that are
funded by IDA.
4) Stating whether the value is actual or expected, cumulative or incremental: value isactual and incremental.
5) State whether additional financing results are also counted, or only parent projects:
total and disaggregate values are reported using line for the parent project,regardless of whether the project has AF.
6) Keywords or system tags used to identify relevant projects: any project withlanguage that matches or is similar to CRI, regardless of the responsible VPU;
Double-check for any SPJ project that is coded with the Level 3 Theme code
for Social Safety Nets for inclusion to minimize exclusion error.
7) Criteria applied in manual checks: Check that an indicator is not missed because
the values are reported as text; Check that any SPJ project is included that 1)131

is approved in the current and 1 year prior; 2) has a relevant indicator thatprovides the number of SSN beneficiaries. Check for any calculations toreflect individuals from household or percentage values.
8) Any differences in the methodology for calculating results from new projects vs.
projects continued from the previous FY. There is no difference in calculating
the number of beneficiaries based on the age of projects: Doublecheck
whether or not follow-on projects that are new have baseline values from theprior project that need to be subtracted to avoid double counting with ICR ofclosed prior project. Projects older than one fiscal year prior to the review arenever added to the universe of projects.
9) Any differences in methodology for calculating the data between the first year in
the IDA cycle compared to subsequent years (for example, to avoid double
counting results for “number of countries” indicators): No variation tomethodology for calculating data.
10) Any other relevant information: None.
Note:[For project-based indicators (e.g., People provided with…)] The indicator should include
all the projects that are only-IDA financier type, blend-financier type (including IDAfinancing), and Trust-fund financier type (including IDA-financing)

Data Source(s)ISRs are the only source of data for active projects. For projects that were previously
included, but closed in the past year, ICR values are used. In the event that a project closed
in the past year, but the ICR has not been completed, the latest ISR values are used in thecurrent CSC, and updated, if changed in the ICR, in the subsequent year.

C. Key counterparts
Contributing
PGs/GPs/Regions

Any project that uses the indicator for SSN beneficiaries is included in the count, regardlessof the responsible unit. No other unit is included in curating or calculating the data.

D. Additional information
Harmonization withother corporate reporting
mechanisms:

The SSN beneficiary indicator is often requested in ad-hoc high-level discussion, but nototherwise routinely included in other corporate reporting exercises.

Limitations andExceptions

Counties may prefer to report this indicator in number of households, rather than
individuals. In such cases, the project teams estimate the number of individuals in the ISRs,
by extrapolating from average HH size. In the event that the ISR include the HH value, theCSC team will do the calculation. The exact text of the CRIs is often not used as a projectindicator, which introduces the necessity of the CSC team to make judgement calls on
which indicator should be included. Training (approximately in early FY20) to regional
quality focal points provide information about the necessity of use of the CRI and forconsistency across the GP.

Date methodology
agreed/updated

The last change to the methodology of total and female beneficiaries occurred
approximately in 2017, due to a corporate change in the theme taxonomy in 2016. Prior to
2016, any project coded with the SSN theme above 20% was included. The taxonomy
change included a change to the assignment of percentage of theme, such that the total did
not need add up to 100%. Subsequent to coding change, the theme information was nolonger required to include a project in the universe. Any project with any indicator that
included SSN beneficiaries was included in the CSC count, regardless of the whether a132

project was coded with the SSN theme and regardless of what GP is responsible. No
noticeable change in the results were evident by the change of this methodology.
The COVID-19 tag for operations was introduced in the summer/fall of 2020 tosystematically track and report on Bank financing and operations that are part of thepandemic response. Operations were considered to be part of COVID-19 response if they
directly responded to the impacts of COVID-19 and would not have been undertaken in theabsence of COVID-19, or if they included significant components (IPF or PforR) or prioractions (DFP) that would not have been undertaken in the absence of COVID-19. In order tosecure the COVID-19 tag, project teams were required to submit country COVID-19
response plans – a two-page summary on the impact of COVID-19 in a country, thegovernment’s response and the WBG response. The project or program documentationneeded to include the country response plan and provide justification for the COVID-19
focus of the specific operation, such as in the storyline, PDO, results framework, and/or the
project or program activities, components, pillars, or prior actions. This applied to new
operations as well as to restructurings and additional financing.

133

People who have received essential health, nutrition, and population services
Children Immunized (million)
Women and children who have received basic nutrition services (million)
Deliveries attended by skilled health personnel (million)
A. Overview
People who have received essential health, nutrition, and population services (million)(Indicator reporting total from three sub-indicators)
Indicator name-Children Immunized (million)
Women and children who have received basic nutrition services (million)
Deliveries attended by skilled health personnel (million)

The indicator measures the sum of the number of children immunized, the number ofwomen and children who received basic nutrition services, and the number of deliveries
attended by skilled health personnel, through operations funded by IDA. Data are reported
for Investment Project Financing and Program-for-Results.
•

Number of children immunized: Refers to the number of children 5 years of age andyounger receiving vaccines purchased through an IDA- financed project, as well as thenumber of children immunized with vaccines purchased with other resources (that is,
GAVI or government funds) that are delivered through an IDA-supported program. It
captures the number of children immunized and not the number of vaccinations; that is,if the same child is immunized with multiple vaccines on the same day or has several
immunization visits in a given year, the child will be counted only once. Thus, simply
tallying the monthly totals of the number of vaccines delivered to children as recorded
in immunization registers or health management information systems, will lead to
double counting. Since contribution rather than attribution is to be measured, pro-ratingbased on proportion of IDA financing is not required.

•

Women and children who have received basic nutrition services: Refers to the total
beneficiaries reached by any of the following services: direct feeding programs(supplementary feeding for pregnant and lactating women and infants and young
children under age 5); programs promoting appropriate infant and young child feeding(such as promotion/support for exclusive breastfeeding, adequate and timely
introduction of complementary foods); nutrition programs for adolescent girls,
including nutrition education, micronutrient supplements, and so on, delivered throughschool health/nutrition programs or other programs reaching adolescent girls; provisionof micronutrient supplements to pregnant/lactating women and children under 5
including vitamin A, iodine, iron/iron folic acid, supplemental zinc, and multiple
micronutrient powders; food fortification (such as, iodized salt); deworming;monitoring of nutritional status; nutrition and food hygiene education; nutrition
components of early childhood development programs; home gardens and small
livestock production for improved dietary diversity; targeted emergency food aid andtreatment of severe acute and moderate acute malnutrition. Although the same
individuals could receive more than one of the above services, they should be counted
only once.

•

Number of deliveries attended by skilled health personnel: Refers to the number ofwomen who delivered a child with the assistance of a skilled health provider (specialist
or non-specialist doctor, midwife, nurse, or other health personnel with midwiferyskills), whether in health facilities or women’s homes. If World Bank-financed
activities are mainly at health facilities, the data for this indicator can be obtained fromdelivery records or health management information systems. If the IDA-financed
activities include supporting skilled health providers to provide home deliveries, efforts

Definition(as it should appear on thedigital IDA RMS card)134

should be made to accurately record such home deliveries in addition to the institutionaldeliveries.
Tier type

Two

IDA20 Cycle Timeline

FY23-25
SDG 3.8 – Achieve universal health coverage, including financial risk protection, access toquality essential health-care services and access to safe, effective, quality, and affordable
essential medicines and vaccines for all

Relevant SDG

SDG 2.2 – By 2030, end all forms of malnutrition, including achieving, by 2025, theinternationally agreed targets on stunting and wasting in children under 5 years of age, andaddress the nutritional needs of adolescent girls, pregnant and lactating women, and older
persons
SDG 3.1.2 – Proportion of Births Attended by Skilled Health Personnel
People who have received essential HNP services: 285 – 430 million

IDA20 Expected
range/value

Included in IDA19-

Children Immunized (105 – 200 million)-

Women and children who have received basic nutrition services (140 – 150 million)-

Deliveries attended by skilled health personnel (40 – 80 million)

Yes

B. Methodology
Unit of Measure

Number of people (in millions)☒ FCS-Children immunized (assumption is 50%
female)Reporting Disaggregation(if relevant)☒ Females

Calculation method-Women and children who received basic
nutrition services (assumption is 67%
female and children)-Deliveries attended by skilled healthpersonnel (assumption is 100% female)Internal Data Update
Frequency

Annually for the IDA RMS exercise.
The indicator aggregates three types of health, nutrition and population interventions
through IDA-financed interventions, based on updates provided by task team leaders in
regular implementation support reports. Quality teams at regional level are tasked with
monitoring the portfolio and can provide both training and oversight to ensure data validity.

Data Calculation Method
Note:
1.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries

135

2.

Data Source(s)[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

Sources: ISRs, ICRs.

C. Key counterparts
Contributing
PGs/GPs/Regions

Health, Nutrition, and Population Global Practice

D. Additional information
Harmonization withother corporate reporting
mechanisms:

WBG Corporate Scorecard
The indicator is an aggregate of three different indicators with potential over- and underreporting issues:

Limitations andExceptions

There are potential opportunities for counting beneficiaries multiple times, e.g., if theyreceive nutrition services and vaccinations or follow up doses in subsequent years. The
quality teams at regional level have issued guidance and provide training and oversight tomitigate this issue.
The indicator does not count the ‘completeness’ of a course of vaccinations. If a child turns
up for only one of a series of vaccines, the child is still counted.

Date methodology
agreed/updated

The methodology was developed in 2021. It is possible that the list of CRIs will need to be
expanded in line with new developments in the Corporate Scorecard.

136

COVID-19 vaccine doses administered
A. Overview
Indicator name

COVID-19 vaccine doses administered (million)

Definition(as it should appear on thedigital IDA RMS card)

Estimated number of COVID-19 vaccine doses purchased with Bank-financing and alreadyin people’s arms.

Tier type

Two

IDA20 Cycle Timeline

FY23-25

Relevant SDG

NA

IDA20 Expected
range/value

Monitored

Included in IDA19

No

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Number of doses (million)☐ FCS☐ Females

Calculation method

NA

WeeklyFor countries capable of providing data on administered doses by financier, data reported asprovided by Task Teams in the regions.

Data Calculation Method

For countries unable to provide data on administered doses broken down by financier, i.e.
unable to identify if Bank-financed doses have been used, an estimate is calculated based on
the share of WB-financed doses delivered to a country as a percentage of the total numberof doses delivered and then applying that same percentage to the total number of doses
administered by a country. In this case, the data source for the total number of dosesdelivered and administered by a country is the WB-WHO-IMF-WTO Task Force tracker
available at https://data.covid19taskforce.com The data source for WB-financed delivered
doses are either UNICEF for AVAT and COVAX doses or else data provided by regional
Task Teams for all purchases made directly from a manufacturer.
Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)137

Data Source(s)WB-WHO-IMF-WTO Task Force tracker available at https://data.covid19taskforce.com

C. Key counterparts
Contributing
PGs/GPs/Regions

HNP Teams in all regions.

D. Additional information
Harmonization withother corporate reporting
mechanisms:

The WB-WHO-IMF-WTO Task Force

Limitations andExceptions

NA

Date methodology
agreed/updated

NA

138

Large-scale assessments completed at primary or secondary level
A. Overview
Indicator name

Large-scale assessments completed at primary or secondary level (number)Definition(as it should appear on thedigital IDA RMS card)

Number of IDA-supported completed large-scale assessment rounds in primary or
secondary level. “Large-scale assessment rounds” refers to rounds of a large-scaleassessment of student achievement (regardless of grade level), for which the results are
made publicly available within two years of the assessment administration; the assessment
round is counted as completed for the year in which the assessment learning data arereleased – not in the fiscal year that the assessment is conducted; if an assessment isadministered during a particular year that covers multiple grades and/or subjects, thatassessment is counted as one round in the year that the data are publicly released; “IDAsupported” refers to either IDA lending (via Investment Project Financing, Program-forResults, Recipient-Executed Trust Fund, and so on), which specifies support for thisparticular large-scale assessment in the project World Bank Project Appraisal Document.
The supported activities could include, among other things, capacity building, design,administration, analysis, reporting, use, publication, and dissemination of an assessment;“Large-scale assessment” includes both national large-scale assessments (those that measure
student performance with the aim of describing overall performance levels in the education
system as a whole at the sub-national or national levels) and international large-scaleassessments (those that measure student performance with the aim of comparing overall
performance levels across countries or education systems.)

Tier type

Two

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 4.1: By 2030, ensure that all girls and boys complete free, equitable and quality
primary and secondary education leading to relevant and effective learning outcomes

IDA20 Expected
range/value

25 – 35 assessments

Included in IDA19

Yes

B. Methodology
Unit of Measure

Number☒ FCS

Reporting Disaggregation(if relevant)☐ Females

Calculation method

No disaggregation, as it is the number oflearning assessments conducted.

Internal Data Update
Frequency

Annually.

Data Calculation Method

The indicator tracks the number of Bank-supported completed large-scale assessment
rounds at the primary or secondary levels. It includes both national (NLSA) or internationallarge-scale assessments (ILSA). This indicator is tracked in any operations that make use of
IPFs, DPFs, P4Rs lending instruments, and/or IDA grants. Additional Financing projects arealso counted for reporting on this indicator. ASAs are not included for Corporate Reporting
because they do not report data through ISRs and would require manual data collection.

139

Under this indicator, National Large-Scale Assessment (NLSA) are defined as measures ofstudent performance with the aim of describing overall performance levels in the education
system as a whole at the sub-national or national levels. International Large-Scale
Assessments (ILSA) are defined as measures of student performance with the aim ofcomparing overall performance levels across countries or education systems.
The baseline for this indicator should be 0 for a new lending project. For each completedassessment round that meets the guidelines below, add one to the baseline or previously
reported ISR actual (current) value. Over the course of the project, count the number ofcompleted learning assessments that meet the guidelines below and report a cumulative total
as the actual (current) value in each fiscal year over the course of the project.
•

•
•
•
•

Two-year deadline to publicly release results. Assessment results must be publicly
released within 2 years of the assessment administration to be counted in the actual(current) value. If data are not publicly released within 2 years of the assessment
administration, do not count the assessment in the actual (current) value.
Assessments should be added to the actual (current) value in the fiscal year that thedata are publicly released – not in the fiscal year that the assessment is conducted.
If an assessment covers multiple grades and/or subjects at the same time, it iscounted as one round in the year that the data are publicly released (see TIMSS
2019 example below).
Please include the assessment name, grade levels assessed, administration
month/year, and results release month/year as a comment on the actual (current)
value.
Indicator reporting is required for IDA20 baseline corresponding to FY20, FY21,
and FY22. The IDA20 cycle timeline includes FY23, FY24, and FY25. Indicator
data for each fiscal year will be aggregated in July/August based on the most recent
ISR values reported into the ISR system for each project. Comments are manuallyvalidated to check for duplicates and to ensure that all data were measured at thesame unit of analysis.

Notice that there are no differences in the methodology for calculating results from new
projects versus projects continued from the previous FY. Keywords or system tags used
to identify relevant projects are “assessment,” “assessments,” “NLSA,” “ILSA,”“NLA,” “LSA,” “Outcome,” “Learning Outcome,” “EGRA,” and/or “EGMA.”
For any other relevant information and examples, please review the guidance note
“Corporate Reporting Methodological Note” and contact the focal points from the EDU GP
global team.
Note:[For project-based indicators (e.g., People provided with…)] The indicator should include
all the projects that are only-IDA financier type, blend-financier type (including IDAfinancing), and Trust-fund financier type (including IDA-financing)
Data Source(s)We use the Enterprise Data Center (EDC) portal (this link), which includes data from all
ISRs and ICRs.

C. Key counterparts
Contributing
PGs/GPs/Regions

Education GP, all regions

D. Additional information

140

Harmonization withother corporate reporting
mechanisms:

Limitations andExceptions

Date methodology
agreed/updatedNA
We have an internal guidance note for EDU GP staff that helps with reporting on this andother CRIs.
ASAs are not included for Corporate Reporting because they do not report data through
ISRs and would require manual data collection.
January 2023.

141

People provided with access to improved water sources
A. Overview
Indicator nameDefinition(as it should appear on thedigital IDA RMS card)

People provided with access to improved water sources (millions)This indicator measures the cumulative number of people who benefited from improved
water supply services that have been constructed through operations supported by IDA. This
includes people newly provided with access to improved water sources and people
benefiting from rehabilitation works. Data are reported for Investment Project Financing,
Development Project Financing, Program-for-Results, and Guarantees, unless otherwise
specified.
•

Improved water sources include piped household connections (house or yardconnections) and community water points (public standpipes, boreholes, protected dug
wells, and protected spring and rainwater collection). It does not include water provided
through tanker trucks or vendors; unprotected wells or unprotected springs; surface
waters (such as rivers, ponds, dams, lakes, streams, and irrigation channels); or bottled
water. The definition of “improved water sources” follows the UNICEF-WHO Joint
Monitoring Program definition.

Tier type

Two

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG Indicator 6.1.1 “Proportion of population using safely managed drinking water
services”

IDA20 Expected
range/value

13 – 20 million

Included in IDA19

Yes

B. Methodology
Unit of Measure

Number of people (in millions)☒ FCS

Reporting Disaggregation(if relevant)☒ Females

Calculation method

142

Mixed. In some cases, it is a simple count(for projects that report this indicator alreadydisaggregated), in other cases it is apercentage of the overall results. The data
source for either of these values are the ISRs
or ICRs. For projects where a percentage
breakdown is not provided, we use the shareof the population female (%) based on
World Development Indicators (World Bank
staff estimates based on age/sex
distributions of United Nations Population
Division's World Population Prospects:
2022 Revision). These percentages areapplied to: i) People provided with access toimproved water source; and ii) People
provided with access to improved sanitation.

For countries with sub-nationally
representative data or project area specificdata on sex-ratio these percentages should
be used and the source provided as afootnote in the PAD.
Notes:

Internal Data Update
Frequency

1.

Improved water and sanitation areprovided at the household and/or
community level, wherein the sex
ratio of population gaining accessapproximates that of the broader
community, sub-national or
national context.

2.

Share of population, female (%)
ranges from 27.3 in Qatar to 55%
in Armenia, however differences
for the majority of countries are in
2 – 3% range

3.

WDI estimates for % population
female are published annually.

YearlyThe indicator measures the number of people that have been provided with improved water
sources in a given Fiscal Year. We look at every active and recently closed project from theWorld Bank portfolio that contains this indicator in their results framework. This includes,
IPFs, DPFs and P4R’s, including any additional financing of those projects. The progress ismeasured for each project using information from the Implementation Status and Results
Reports (ISR) or the Implementation Completion and Results Report (ICR). Since thisindicator is cumulative, we compare the latest available data in a given fiscal year and thelast data point reported under that indicator in the fiscal year immediately before. For
projects reporting results for the first time, we compare this value to the indicator’s baseline.

Data Calculation Method

There are 3 types of units of measurement used to report on this indicator: number ofpeople, number of households, and number of water points. We use a conversion factor toaggregate results using number of people as the unit of measurement. The conversion factor
is 5 in the case of households, and 200 in the case of water points. For example, if a project
reports 100 households gaining access to improved water sources, this would be equivalent
to 500 people gaining access.
Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)143

Data Source(s)ISRs and ICRs

C. Key counterparts
Contributing
PGs/GPs/Regions

We calculate this indicator for all World Bank projects that use this indicator. This includes
projects led by the Water GP and projects led by other GPs such as Urban, Agriculture,
Health, Environment, etc.

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

The conversion factor is an approximation and may be different than the factor of 5 in thecase of households and 200 in the case of water points. However, given that this is close to
the average, the difference should not be as significant.

Date methodology
agreed/updated

Last updated on June 13, 2023.

144

People provided with access to improved sanitation services
A. Overview
Indicator nameDefinition(as it should appear on thedigital IDA RMS card)

People provided with access to improved sanitation services (million)
The indicator measures the cumulative number of people who benefited from improved
sanitation facilities that have been constructed through operations funded by IDA. This
includes people newly provided with access to improved sanitation facilities and people
benefiting from rehabilitation works. Data are reported for Investment Project Financing,
Development Project Financing, Program-for-Results, and Guarantees, unless otherwise
specified.
•

Improved sanitation facilities include flush or pour-flush to a piped sewer system,
septic tank, or pit latrine; ventilated improved pit latrine; pit latrine with slab; andcomposting toilet. It does not include flush or pour-flush to elsewhere (that is, not to apiped sewer system, septic tank, or pit latrine); pit latrine without slab/open pit; bucket;
hanging toilet or hanging latrine; shared facilities of any type; or no facilities, bush, or
field. The definition of “improved sanitation facilities” follows that of the UNICEFWHO Joint Monitoring Program.

Tier type

Two

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG Indicator 6.2.1 “Proportion of population using (a) safely managed sanitation services
and (b) a hand-washing facility with soap and water”

IDA20 Expected
range/value

12 – 18 million

Included in IDA19

Yes

B. Methodology
Unit of Measure

Number of people (in millions)☒ FCS
Mixed. In some cases, it is a simple count(for projects that report this indicator alreadydisaggregated). In other cases it is apercentage of the overall results. The data
source for either of these values are the ISRs
or ICRs.

Reporting Disaggregation(if relevant)☒ Females

Calculation method145

For projects where a percentage breakdown
is not provided, we use the share of the
population female (%) based on World
Development Indicators (World Bank staff
estimates based on age/sex distributions ofUnited Nations Population Division's World
Population Prospects: 2022 Revision).
These percentages are applied to: i) People
provided with access to improved water
source; and ii) People provided with accessto improved sanitation. For countries with
sub-nationally representative data or project
area specific data on sex-ratio thesepercentages should be used, and the source
provided as a footnote in the PAD.
Notes:

Internal Data Update
Frequency

4.

Improved water and sanitation areprovided at the household and/or
community level, wherein the sex
ratio of population gaining accessapproximates that of the broader
community, sub-national or
national context.

5.

Share of population, female (%)
ranges from 27.3 in Qatar to 55%
in Armenia, however differences
for the majority of countries are in
2 – 3% range

6.

WDI estimates for % population
female are published annually.

YearlyThe indicator measures the number of people that have been provided with improved
sanitation in a given Fiscal Year. We look at every active and recently closed project fromthe World Bank portfolio that contains this indicator in their results framework. This
includes, IPFs, DPFs and P4R’s, including any additional financing of those projects. The
progress is measured for each project using information from the Implementation Status andResults Reports (ISR) or the Implementation Completion and Results Report (ICR). Since
this indicator is cumulative, we compare the latest available data in a given fiscal year andthe last data point reported under that indicator in the fiscal year immediately before. For
projects reporting results for the first time, we compare this value to the indicator’s baseline.

Data Calculation Method

There are 3 types of units of measurement used to report on this indicator: number ofpeople, number of households, and number of latrines. We use a conversion factor toaggregate results using number of people as the unit of measurement. The conversion factor
is 5 in the case of households, and 200 in the case of latrines. For example, if a project
reports 100 households gaining access to improved sanitation, this would be equivalent to
500 people gaining access.
Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)146

Data Source(s)ISRs and ICRs

C. Key counterparts
Contributing
PGs/GPs/Regions

We calculate this indicator for all World Bank projects that use this indicator. This includes
projects led by the Water GP and projects led by other GPs such as Urban, Agriculture,
Health, Environment, etc.

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

The conversion factor is an approximation and may be different than the factor of 5 in thecase of households and 5 in the case of latrines. However, given that this is close to theaverage, the difference should not be as significant.

Date methodology
agreed/updated

Last updated on June 14, 2023.

147

IDA countries publishing annual and timely public debt reports
A. Overview
Indicator name

IDA countries publishing annual and timely public debt reports

Definitions(as it should appear on thedigital IDA RMS card)

IDA countries that publish public debt reports at least on an annual basis providing
information on the outstanding external and domestic public sector debt portfolio and its
main cost and risk characteristics, with data that is not older than 6 months.

Tier type

Two

IDA20 Cycle Timeline

FY23-25 (July 1, 2022, to June 30, 2025)

Relevant SDG

SDG 17.1: Strengthen domestic resource mobilization, including through international
support to developing countries, to improve domestic capacity for tax and other revenue
collection.

IDA20 Expected
range/value

30 – 35 countries

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Number of countries☒ FCS☐ Females
Annually••

Data Calculation Method••2

Calculation method

Number of IDA countries that publish public debt reports at least on an annual basis
providing information on the outstanding external and domestic public sector debt
portfolio and its main cost and risk characteristics, with data that is not older than 6months.
Debt reports. In terms of the Debt Reporting Heat Map2 criteria. Debt reports with info
on external and domestic public sector debt corresponds to countries assessed with atleast a ‘partial’ debt coverage instrument (yellow and/or green indicator). Main costs
and risks characteristics are reported when there is a ‘Debt Management Strategy(DMS)’ described (when this indicator is not red). Data that is not older than 6 months
corresponds to a Time Lag indicator that is not red.
To sum up, the updates will count the number of countries in the Heatmap with: (i) ayellow and/or green rating in the ‘instrument coverage’ indicator; a non-red ‘DMS’
indicator; and (iii) a non-red ‘Time lag’ indicator.
The baseline is the 2021 Debt Heatmap report (with date of assessment: October 1,
2021.)

https://www.worldbank.org/en/topic/debt/publication/report-debt-transparency-in-developing-economies

148

Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

Debt transparency heatmap

C. Key counterparts
Contributing
PGs/GPs/Regions

Global Macro and Debt Analytics, in the Macroeconomics, Trade & Investment (MTI)
Global Practice (for Heatmap, DMF and LIC DSAs).

D. Additional information
Harmonization withother corporate reporting
mechanisms:

Alignment with Monitoring and Evaluation (M&E) of DMF III
Objective of debt IDA20 PC: IDA20 debt policy commitment has the objective tostrengthen the quality and coverage of PPG debt and fiscal risk reporting to support
countries address key debt vulnerabilities and risks.

Limitations andExceptions

Rationale for debt IDA20 PC: Debt transparency has surfaced as a particularly criticalpolicy challenge against the background of rising public debt vulnerabilities. Transparency
is important to ensure that governments and creditors take informed decisions and that debt
sustainability assessments are based on a comprehensive coverage of the entire public sector
debt burden. It is also critical for governments to be able to adequately monitor and mitigate
debt-related fiscal risks. The IDA20 commitment advances the quality of outcomes, shifting
the focus from publishing debt reports (IDA19) to enhancing their comprehensives by
including additional subsectors of the public sector, including SOEs, and by focusing oncomprehensive fiscal risk statements that help mitigate key risks.
Anticipated Challenges:•

Date methodology
agreed/updated

The debt reporting heatmap shows both improvements and deterioration from one year
to another. For instance, there are countries that had a full coverage in both instrument
and sectorial indicators in 2021 (green color) and became countries with an incomplete
coverage (red) in 2022 because the debt reporting was deemed lagging or incomplete.
In other cases, countries were downgraded because the debt data was pre-cutoff date,and so on. While almost 40 percent of IDA countries recorded an improvement inoverall debt reporting performance between 2021 and 2022, one-third of IDA countries
experienced a deterioration.

June 12, 2023

149

IDA countries provided statistical capacity building support by the WBG for the
implementation of household surveys
A. Overview
Indicator name

IDA countries provided statistical capacity building support by the WBG for the
implementation of household surveys (number)Definition(as it should appear on thedigital IDA RMS card)

Technical assistance activity provided to national statistical agencies related to household
surveys used for official welfare and/or poverty measurement (such as, sampling,questionnaire review, data collection, field logistics, data management, dissemination, andestimation of poverty-lines). Data are reported for IDA eligible countries, including blend
countries. Data is reported cumulatively, without double counting countries, starting fromthe first year of the IDA20 cycle.

Tier type

Two

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 17.19: By 2030, build on existing initiatives to develop measurements of progress on
sustainable development that complement gross domestic product, and support statistical
capacity-building in developing countries

IDA20 Expected
range/value

55 countries

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Number of countries☒ FCS☐ Females

Calculation method

The data are collected on an annual basis during Q3, no later than March 30 th. The results
are ready for publication by June 30.
The data for this indicator are collected through an annual Household Survey Scorecard
exercise conducted by the Poverty GP in Q3. The survey is managed by the Data for
Goals (D4G) Global Program. The survey scorecard is filled out by all Country Poverty
Economists. The information is collected at the country level and then aggregated at
total, IDA, and FCS country classifications levels.
The survey gathers information on any support provided under any type of financing.

Data Calculation Method

The data are collected, reviewed (taking into consideration previous FY results), andanalyzed by the D4G team, The results are published in Q4. The Household Survey
Scorecard questions are shown below.
Q1. During FYXX, did the World Bank provide any technical assistance (defined as
any activity related to the design, implementation, and dissemination of the household
survey used for official welfare and/or poverty measurement, such as sampling,questionnaire review, data collection, field logistics, data management anddissemination) to the National Statistical Office specifically related to the household

150

surveys used for official welfare and/or poverty measurement?
•

Answer options: Yes, No

Q2. If yes, under what bank instrument(s) was this technical assistance provided during
FYXX (check all that apply).
•

Answer options: EFO, trust fund or other type of grant (including RETF),
RAS, lending (IPF, P4R, PDO, etc), or BB (ASA, IO, etc).

From this data, the country list is constructed with the following criteria:••

IDA or IDA blend country
Relevant Bank instrument: All instruments and sources of financing (IDA, BB,
TF, EFO, et.)Other Notes••

This indicator is reported on a cumulative basis for the period of the IDA
cycle.
The indicator is disaggregated by FCS category, using the applicable FCV listof countries.

Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)Household Survey Scorecard executed by Poverty GP with the contributions of all Poverty
Economists.

C. Key counterparts
Contributing
PGs/GPs/Regions

Poverty GP

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

NA

Date methodology
agreed/updated

Jan 2019

151

Countries collecting disability data with IDA support
A. Overview
Indicator nameCountries collecting disability data with IDA support (number)Definition(as it should appear on thedigital IDA RMS card)

Number of countries conducting household surveys for IDA countries 3 collecting theWashington Group Short Set (WGSS) for disability questions in their survey used formeasuring welfare and poverty

Tier type

Two

IDA20 Cycle Timeline

FY23-25

Relevant SDG

NA

IDA20 Expected range/value

Monitored

Included in IDA19

No

B. Methodology
Unit of Measure

Number of countries☒ FCS
The unit of analysis forthis indicator is thenumber of surveys, notgenderReporting Disaggregation (ifrelevant)☐ FemalesInternal Data Update
Frequency

The data are collected on an annual basis during Q3. The results are ready for publication on
Q4.

Data Calculation Method

Calculation method

The data for this indicator are collected through an annual Household Survey
Scorecard exercise conducted by the Poverty GP in Q3. The survey is overseen by
the Data for Goals (D4G) Global Program. Once the survey is prepared for launch, it isdistributed to the regional Statistical Teams in all regions of the Bank to be completed.
The data collection process takes place at the country level, where information isgathered and recorded. Subsequently, this data is aggregated at various levels, including
the total, International Development Association (IDA), and Fragile and ConflictAffected Situations (FCS) country classification levels.
The data collected undergoes a thorough review process by the D4G team. This
review takes into account the results of previous fiscal year (FY). This review ensures
the accuracy and reliability of the data. The results of this analysis are published in the
fourth quarter (Q4) of the fiscal year. Statistics teams are required to respond if thequestions on disability within a survey correspond to the WGSS questions with three
options: (1) Yes, fully, (2) Yes, partially, and (3) No. The six questions on disability forcomparison are the following:3

https://www.washingtongroup-disability.com/fileadmin/uploads/wg/Washington_Group_Questionnaire__1__WG_Short_Set_on_Functioning__October_2022_.pdf

152

(i)
(ii)
(iii)
(iv)
(v)
(vi)

Do you have difficulty seeing, even if wearing glasses?
Do you have difficulty hearing, even if using a hearing aid?
Do you have difficulty walking or climbing steps?
Do you have difficulty remembering or concentrating?
Do you have difficulty (with self-care such as) washing all over or dressing?
Using your usual (customary) language, do you have difficultycommunicating, for example understanding or being understood?

Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

Poverty GP executes an annual survey (known as the Household Survey Scorecard) to all
the Regional Statistical Teams to gather this information with the help of poverty
economists.

C. Key counterparts
Contributing
PGs/GPs/Regions

Poverty and Equity Global Practice Regional Statistics Teams and poverty economists

D. Additional information
Harmonization with othercorporate reporting
mechanisms:

NA

Limitations and Exceptions

NA

Date methodology
agreed/updated

WGSS was adopted in 2019153

People provided with enhanced access to broadband internet
A. Overview
Indicator namePeople provided with enhanced access to broadband internet (million)
The indicator measures the number of people who have benefitted from new or enhanced
access to broadband internet service during the project implementation period.
•

Definition(as it should appear on thedigital IDA RMS card)•

New access is defined as the number of beneficiaries (people) that have gained newaccess to internet service.
Enhanced access is defined as the number of people that have benefitted from
improved Internet service. Enhanced access refers to improved download and upload
speeds, better quality through lower latency and jitter as well as lower prices for dataservices and internet-enabled devices.

Internet use can be through fixed or mobile broadband networks and can be at any locationof Internet access (such as, home, work, school, internet cafés, public places). Depending on
project focus, data on mobile and/or fixed subscribers is used to calculate internet users.
Tier type

Two

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 9.c: Significantly increase access to ICT and strive to provide universal and affordable
access to internet in LDCs by 2020

IDA20 Expected
range/value

80 – 88 million

Included in IDA19

Yes

B. Methodology
Unit of Measure

Number of people (in millions)☒ FCS

Reporting Disaggregation(if relevant)Internal Data Update
Frequency☒ Females

If the project includes a gender component
and disaggregates data by sex, a simple
count or an estimation of the number offemale beneficiaries is possible.
Calculation method
Otherwise, for projects without genderdisaggregated data, the number of female
beneficiaries is calculated according to themethodology in Annex 1.

Annually, during Corporate Scorecard update

154

The following steps are taken to identify and verify relevant indicators:
•

•
•

•
Data Calculation Method•

To identify projects that need to be tracked, an initial manual search in the OPCS
database for keywords that relate to connectivity is undertaken. Keywords include
connectivity, internet, broadband, telecommunications/telecom, mobile services,and telecom license.4 In addition, looking into every project and indicator from theentire DD active portfolio is helpful in identifying those new projects that need to
be tracked and avoid missing any during the initial manual search in the project
file. Instruments that are included in the search are IPFs, DPFs and P4Rs.
Only projects that have become effective, have disbursed, and where project
activities have an impact on the indicators are measured.
Each indicator relating to the above keywords is analyzed and verified to be
relevant for measuring progress in broadband internet access. Documents toanalyze for this step include PADs, ISRs and ICRs and TTLs can be consulted insituation where indicators are not clear. In addition, components related toconnectivity are identified to make sure that key word searches don’t overlook any
possible results on access.
It is important to note that the indicator looks at new and/or improved access anddoes not incorporate pre-project data.
To calculate the number of beneficiaries of new access, project tracking documents(ICRs/ISRs) are consulted. The relevant indicator is the incremental increase of thenumber of people with new access to the internet from the previous fiscal year.
When a project intervention is limited to a specific region of a country the targeted
population percentage as identified in the PAD is used. For the number ofbeneficiaries of enhanced access, global sources of internet access data can be
consulted in addition to project documents, such as ‘Unique mobile internet
subscribers”5 from GSMA (published quarterly) or equivalent data from ITU.
When reporting on this indicator, a contribution discount rate of 20% is applied to
all projects.

Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

OPCS data file (provided at the beginning of the Fiscal Year), Operations Portal, Standard
Reports, ICRs, ISRs, and PADs. In some cases (mostly when there is an error in any ofthese reports, we use the information provided by TTL and share TTL/ PM confirmation
email as supporting document).

4

The full list of keywords is: access, affordability, backbone, backhaul, bandwidth, broadband, cable, capacity,
competition, connectivity, coverage, datacenter, device, exchange, fiber, fixed, infrastructure, internet, IXP,
liberaliz, license, mobile, network, operator, privatiz, regulat, telecom
5
Defined as: “Total unique users who have used internet services on their mobile device(s) at the end of the period.
Mobile internet services are defined as any activity that consumes mobile data (i.e. excluding SMS, MMS andcellular voice calls). Subscribers differ from connections such that a unique user can have multiple connections.”
See GSMA (2020).

155

Information on inferred access, unless provided by teams, is obtained from regulatory
agencies for most up-to-date data, and GSMA Intelligence (unique mobile subscribers) orInternational Telecommunications Union where reliable data from the regulator is notavailable. To avoid double counting, data on mobile internet users should be used, unlessthe project has a clear focus on fixed broadband access only, in which data on fixed
broadband subscriptions should be used.
C. Key counterparts
Contributing
PGs/GPs/Regions

All DD regions, DD global units, Other contributing GPs include, but are not limited to:
FCI, Energy, Transport, Urban, Education, Health.

D. Additional information
Harmonization withother corporate reporting
mechanisms:

WBG Corporate Scorecard••
Limitations andExceptions•••

Date methodology
agreed/updated

Measuring inferred access is important for understanding the wider project impact,
especially impact created through policy and regulatory reforms that target the enabling
environment. While it is difficult to fully attribute growth in the number of people who
use the internet to policies implemented as part of the project, in theory all people who
use the internet benefit from these reforms.
Given mobile internet is used as the main indicator, there may be underestimation of
the project impact in cases where individuals have access to fixed but not to mobileinternet.
Data on internet users is estimated by GSMA and ITU, using information from
regulatory agencies in most cases. Sometimes, these organizations change themethodology for estimating internet users, which will impact the results indicators andneeds to be considered for results reporting.
Collection of data on “enhanced” broadband access was collected starting in 2023 andbackfilled for 2022 when the definition and methodology around “enhanced” wasfurther developed.
Definition and methodology are likely to be updated or revamped following approval of
the revamped WBG Corporate Scorecard.

November 1, 2023

156

Countries supported toward institutionalizing disaster risk reduction as a national priority
with IDA support
A. Overview
Indicator nameCountries supported toward institutionalizing disaster risk reduction as a national
priority with IDA support (number)Definition(as it should appear on thedigital IDA RMS card)

This indicator reports the number of IDA countries supported by active IDA-funded
operations that have contributed to the institutionalization of disaster risk management(DRM). A contribution-based approach is used to ascertain the World Bank’s support toinstitutionalizing DRM at the national and local levels, in line with the Sendai Frameworkfor Disaster Risk Reduction 2015–2030 priorities for action. These include: i)
Understanding disaster risk, ii) Strengthening disaster risk governance to manage disaster
risk, iii) Investing in disaster risk reduction for resilience and iv) Enhancing disaster
preparedness for effective response, and to “Build Back Better” in recovery, rehabilitation,and reconstruction.

Tier type

Two

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 13.2: Integrate climate change measures into national policies, strategies, and planning

IDA20 Expected
range/value

55 – 70 countries

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation

Number of countries☒ FCS(if relevant)☐ FemalesInternal Data Update
Frequency

Once a year (WBG IDA Corporate Scorecards annual exercise)

Calculation method

NA (unit of measure is number of countries)- The number of countries supported toward institutionalizing disaster risk reduction as anational priority with IDA support is calculated based on the information provided bydisaster risk management staff working in World Bank regions in the Global Practice for
Urban, Disaster Risk Management, Resilience and Land (GPURL).

Data Calculation Method- Key DRM staff in each region provides a list of the countries with IDA supported
programs that have contributed, during the last FY, to ensuring that disaster risk
management was a national priority with a strong institutional basis for implementation inalignment with the Sendai Framework. This information is collected once a year (usually atthe beginning of the FY).
- The focal point validates and aggregates the information received and reports the numberof countries. Each country is counted only once during the IDA cycle. This requires
comparing lists from the three years of the IDA cycle and removing any duplicates to avoid
double counting.

157

Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

Key DRM staff in each region in GPURL provides a list of the countries with IDA
supported programs that have contributed to institutionalizing disaster risk reduction during
last FY, in line with the Sendai Framework for Disaster Risk Reduction 2015–2030
priorities for action. Then the Focal Point validates the list using data available in the WB
Operations Portal (i.e. to ensure the DRR actions included are relevant, the IDA countries
are correctly identified based on the list of countries that are currently eligible to receive
IDA resources).

C. Key counterparts
Contributing
PGs/GPs/Regions

All Regions Global Practice for Urban, Disaster Risk Management, Resilience and Land
(GPURL)D. Additional information
Harmonization withother corporate reporting
mechanisms:
Limitations andExceptions
Date methodology
agreed/updated

NA
NA

2017

158

Countries integrating adaptive social protection into national systems with IDA support
A. Overview
Indicator nameCountries integrating adaptive social protection into national systems with IDA
support (number)Definition(as it should appear on thedigital IDA RMS card)

Adaptive Social Protection Systems are systems which build resilience to and can respondto covariate shocks such as climate shocks. Such systems can build the resilience ofhouseholds prior to a shock through the provision of cash transfers, productive inclusion
activities, employment schemes, etc. They can also provide support to households who are
negatively impacted by shocks to prevent them from falling into or deeper into poverty.
Adaptive systems require functioning institutional arrangements and government leadership,strong financial systems, adaptable and flexible programs, and significant data on shocks
but also households.

Tier type

Two

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 1.2 – By 2030, reduce at least by half the proportion of men, women and children of
all ages living in poverty in all its dimensions according to national definitions.
SDG 1.3 – Implement nationally appropriate social protection systems and measures for all,including floors, and by 2030 achieve substantial coverage of the poor and the vulnerable.

IDA20 Expected
range/value

Monitored

Included in IDA19

No

B. Methodology
Unit of Measure

Number of countries

Reporting Disaggregation(if relevant)☒ FCSInternal Data Update
Frequency

The data will be updated upon request in our unit.

Data Calculation Method

Step 1: Based on a keyword search, identify any project (IPF, DPO, PforR) in the IDA20
cycle that a) includes in their PDO elements of shock responsive social protection or
adaptive social protection, or b) supports adaptive social protection, with one of thefollowing criteria in their activities: (i) supporting conditional or unconditional cash transfer
programs with a focus on building shock resilience; (ii) economic inclusion programs with afocus on building shock resilience through sustainable and diversified livelihoods, (iii)
supporting the introduction and strengthening of cash transfers that can expand horizontallyor vertically in the case of shocks, (iv) investments in building social protection delivery
systems including social registries, identification systems, G2P payment systems, link toearly warning systems and disaster risk financing systems for ASP. Pilots should beconsidered and counted as the indicator is about the action of integrating rather than theoutcome of it being fully fledged and integrated.
The list of projects may include Additional Financing (AF) operations. If the AF operation
does not include IDA resources but the parent project includes them, then it should becounted.

159

Step 2: Count the number of IDA countries supported by the projects. Each country should
only be counted once. The values reported should be cumulative.
Step 3: Share the list of countries and operations with the operations team from each region
to confirm if there are any other operations on Adaptive social protection.
Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)Operations Portal (PADs).

C. Key counterparts
Contributing
PGs/GPs/Regions

SPJ GPD. Additional information
Harmonization withother corporate reporting
mechanisms:

IDA20 Human Capital Theme, Policy Commitment #4 on Adaptive Social Protection

Limitations andExceptions

NA

Date methodology
agreed/updated

This methodology note was prepared in January 2023.

160

Satisfactory outcomes of IDA Country Partnership Frameworks
A. Overview
Indicator nameSatisfactory outcomes of IDA Country Partnership Frameworks (%, IEG Rating, 4year rolling)

Definition(as it should appear on thedigital IDA RMS card)

Percentage of Country Partnership Framework (CPF) Completion Reports rated moderately
satisfactory, satisfactory, or highly satisfactory by Independent Evaluation Group (IEG).
Data is reported for CPFs of IDA eligible countries, including blend countries, during CPF
period.

Tier type

Two

IDA20 Cycle Timeline

FY23-25

Relevant SDG

NA

IDA20 Expected
range/value

70%

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency%, IEG rating, 4-year rolling☒ FCS☐ Females

Calculation method

NA

Data is updated annually.
The indicator is based on IEG Outcome ratings specified in the CLRR. This information is
manually collected from the documents.
A country is classified as an IBRD/IDA country according to its eligibility at the time the
CLR was presented to the Board. For example, for a CLR delivered in FY18, the FY18 list
was used; for a CLR delivered in FY19, the FY19 list was used, and so on.
Blend countries are considered as part of IDA

Data Calculation Method

A country is classified as FCV if it was considered as such at time the CLR was presented to
the Board. The lists of FCVs used are available:
https://www.worldbank.org/en/topic/fragilityconflictviolence/brief/harmonized-list-offragile-situations.
The Outcome rating is on a six-point rating scale: Highly Satisfactory, Satisfactory,
Moderately Satisfactory, Moderately Unsatisfactory, Unsatisfactory, and Highly
Unsatisfactory.
Once the list of CLRs and their ratings is available, the indicator is calculated considering
the total number of countries that had an outcome rating of Moderately Satisfactory or
above.
The indicator considers the list of CLRs delivered in the last four years. So the indicator

161

would be calculated as the sum of all countries with CLRs delivered in the last 4 FYs whichwere rated as Moderately Satisfactory or Above over the total number of countries with
CLRs delivered in the last 4 FYs.
Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

Outcome ratings extracted from the IEG CLR documents.

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

NA

Date methodology
agreed/updated

NA

162

Satisfactory outcomes of IDA operations
As a share of commitments
As a share of operations
A. Overview
Satisfactory outcomes of IDA operations
Indicator name-As a share of commitments (%, IEG ratings, 3-year rolling)
As share of operations (%, IEG ratings, 3-year rolling)

Definition(as it should appear on thedigital IDA RMS card)

Share of IDA operations and IDA commitments rated by the Independent Evaluation Group(IEG) as “moderately satisfactory” or higher on achievement of outcomes. Data are forprojects exiting in the three previous fiscal years for which at least 60% of the projects foreach fiscal year have been evaluated by IEG. The rating captures the extent to which a
project’s original or formally revised development objectives were achieved. The rating isbased on three criteria: (i) relevance of the objectives and design (relevance); (ii) extent towhich the objectives were achieved (efficacy); and (iii) extent to which the operationachieves a higher rate of return than the opportunity cost of capital or is able to provide asimilar economic justification (efficiency).

Tier type

Two

IDA20 Cycle Timeline

FY23-25

Relevant SDG

NA

IDA20 Expected
range/value-

As a share of commitments (%, IEG ratings, 3-year rolling): 80%-

As share of operations (%, IEG ratings, 3-year rolling): 75%

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Data Calculation Method

Percentage, IEG rating, 3-year rolling average☒ FCS☐ Females

Calculation method

Twice a year, for internal reports: Operations Update to the Board and QBRR, which
include charts on IBRD and IDA evaluations
The IEG ratings data is downloaded from AO report 4.a.1. “Key IEG Indicators”. We use
Agreement Type to separate IBRD and IDA projects. Please note that IBRD agreement typeincludes Blend projects, so IDA Agreement Type only includes purely IDA financed
projects. We also download the evaluation data from AO report 4.c.2 “Counts for ICR and
IEG Ratings” to check evaluation rates for recent closing FYs. Only FYs where at least 60
percent of projects are IEG evaluated are included.
The evaluation rate is calculated in % as number of evaluations divided by number of each
FY’s closed projects for all IBRD/IDA (PE product line) projects. Once the most recent FY
reaches 60%, we include it in the 3-year rolling average.
We check the IEG rating data from “Key IEG Indicators” report for any major

163

inconsistencies (closed and evaluated projects showing with a date in the future, forexample). If needed, we work with ITS to fix the underlying issues in our systems. Once thedata is checked, we add tags for FCV, based on AO country code and the FCV list specified
by the IDA RMS team; the FY21 list was used for the last update, and then create pivots forcalculating the 3-year rolling average for % Satisfactory. Please note:--

We only include projects in “Closed” project status.
AF projects are not included in the data.
We use Closing FY field, which is based on Revised Closing Data, and not Exit FY,
which is based on Deactivation Date and can result in incorrect values.
We use project Agreement Type to determine whether a project is IDA; blend projects
are reported under the IBRD Agreement Type and are therefore excluded from thisreporting.
All instruments are included (IPFs, DPFs and P4Rs).
Region field used is VPU, which cleanly separates the old AFR code into AFE and
AFW.
Unrated projects (blank value) are excluded.
3 year rolling average is calculated for the selected FY range, using count of project IDs
for share of operations and net commitments values for share of commitments

To calculate the value of share of operations we divide project count of all Satisfactoryrated projects (AO reports value of 100 in “Outcome % Satisfactory” field of the “Key IEG
Indicators” report) by project count of all rated projects in given FY. To calculate the valueof share of commitments we divide net commitment total of all Satisfactory-rated projects
by net commitment total of all rated projects in given FY. We then average last three FY forwhich we meet the 60 percent evaluated threshold.
Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

AO reports 4.a.1. “Key IEG Indicators” and 4.a.1. “Key IEG Indicators” for data; AO
report 4.c.2 “Counts for ICR and IEG Ratings” to determine time window.

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:
Limitations andExceptions

Regional Updates: IBRD and IDA charts
For the Q2 and Q4 Operations Update to the Board and the QBRR: IBRD and IDA charts
The reporting system overhaul and the upcoming full switch to Standard Reports will
require validation of the SR data against the AO reports; the upcoming transition to single
product line and viewing projects by type of financing will require redefining what iscounted as IDA projects (any projects with IDA financing) instead of using Agreement

164Type.

Date methodology
agreed/updated

Methodology agreed upon few years ago and confirmed during last update of the Scorecard
data, September 2022. The use of Agreement Type in particular was confirmed.

165

Advisory Services and Analytics (ASA) objectives accomplished
A. Overview
Indicator name

Advisory Services and Analytics (ASA) objectives accomplished (client rating, %)Definition(as it should appear on thedigital IDA RMS card)

Share of completed ASA activities for which clients strongly agree or agree with thefollowing statements: “Overall, this activity is likely to achieve its intended development
objectives” for ASA with completed Activity Completion Summary (ACS) during the fiscal
year.

Tier type

Three

IDA20 Cycle Timeline

FY23-25

Relevant SDG

NA

IDA20 Expected
range/value

80%

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Client rating, %☒ FCS☐ Females

Calculation method

Annually
The data for this indicator for IDA eligible countries are extracted from the Client Survey
database for the reporting year in question. The value (actual, annual) is calculated as thepercentage of ASAs with a survey response where the survey statement “Overall, thisactivity achieved is likely to achieve its intended development objectives” was rated either“strongly agree” or “agree”.

Data Calculation Method

Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

World Bank Client Satisfaction Survey

C. Key counterparts

166

Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:
Limitations andExceptions

The survey is being revamped to increase the response rate of clients.

Date methodology
agreed/updated

May 2017

167

Client feedback in IDA countries on WBG effectiveness and impact on results
A. Overview
Indicator name

Client feedback in IDA countries on WBG effectiveness and impact on results (averagerating scale: 1-10)

Definition(as it should appear on thedigital IDA RMS card)

Mean score for the answer provided by World Bank Group clients in IDA countries to thefollowing question from the annual World Bank Group Country Opinion Survey (COS)
Program: “How effective has the World Bank Group been in achieving development resultsin your country?” (Based on a 10-point scale with 1 being “not effective at all” and 10 being“very effective”). World Bank Group clients in IDA countries are defined as respondents
who report in the Country Opinion Survey that they collaborate with the World Bank (IDA).
The indicator reflects the current fiscal year ratings (FY23), that is, for about a third of all
World Bank Group client countries surveyed during each three-year cycle. Data are reported
for IDA eligible countries, including blend countries, in a reporting fiscal year.

Tier type

Two

IDA20 Cycle Timeline

FY23-25

Relevant SDG

NA

IDA20 Expected
range/value

7

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Average rating scale: 1-10
☒ FCS
☐ Females

Calculation method

Annually
The indicator is calculated as follows:

Data Calculation Method

The data for respondents from IDA/Blend countries surveyed in the fiscal year isaggregated across all countries.
Only those respondents who answered Yes to the question, “Currently, do you
professionally collaborate/work with the World Bank Group (IBRD/IDA, IFC,
MIGA, ICSID) in your country?” AND answered, “World Bank (IDA)” to thequestion, “Which, if any, of the following agencies of the World Bank Group do
you primarily collaborate/work with in ____?” are selected for analysis.
For each respondent selected, the mean rating for the question, “How effective has
the World Bank Group been in achieving development results in your country?” isthen calculated (excluding any Don’t Know responses).
This mean rating provides the defined overall indicator.
For the FCS disaggregation, only those respondents selected in #2 that are also
from FCS-designated countries are selected for analysis. The mean rating for thequestion, “How effective has the World Bank Group been in achieving
development results in your country?” is then calculated (excluding any Don’t

168

Know responses). This mean rating provides the defined FCS-disaggregatedindicator.
Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)Country Opinion Surveys completed in the fiscal year in countries with IDA or Blend
financing.

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

Although the Country Opinion Survey program aims to survey a third of all World Bank
Group client countries each fiscal year, the deployment of the surveys is contingent upon
approval and cooperation of the region and the individual country team. The survey sample
is comprised of approximately 80% from country team databases of contacts andapproximately 20% from the independent fielding agency (which most often provides
supplemental contacts from outside the government). The response rate for Country Opinion
Surveys is approximately 50%.

Date methodology
agreed/updated

August 2023

169

Client feedback in IDA countries on WBG knowledge
A. Overview
Indicator name

Client feedback in IDA countries on WBG knowledge (average rating scale: 1-10)

Definition(as it should appear on thedigital IDA RMS card)

Mean score for the answer provided by World Bank Group clients in IDA countries to thequestion from the annual World Bank Group Country Opinion Survey (COS) Program:“How significant a contribution do you believe the World Bank Group’s knowledge workand activities make to development results in your country?” (based on a 10-point scale with
1 being “not significant at all”, and 10 being “very significant”). World Bank Group clientsin IDA countries are defined as respondents who report in the Country Opinion Survey thatthey collaborate with the World Bank (IDA). The indicator reflects the current fiscal year
ratings (FY23), that is, for about a third of all World Bank Group client countries surveyed
during each three-year cycle. Data are reported for IDA eligible countries, including blend
countries, in a reporting fiscal year.

Tier type

Two

IDA20 Cycle Timeline

FY23-25

Relevant SDG

NA

IDA20 Expected
range/value

7

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Average rating scale: 1-10
☒ FCS
☐ Females

Calculation method

Annually
The indicator is calculated as follows:1.
2.

Data Calculation Method
3.

4.

The data for respondents from IDA/Blend countries surveyed in the fiscal year isaggregated across all countries.
Only those respondents who answered Yes to the question, “Currently, do you
professionally collaborate/work with the World Bank Group (IBRD/IDA, IFC,
MIGA, ICSID) in your country?” AND answered “World Bank (IDA)” to thequestion, “Which, if any, of the following agencies of the World Bank Group do
you primarily collaborate/work with in ____?” are selected for analysis.
The mean rating for the question, “How significant a contribution do you believe
the World Bank Group’s knowledge work and activities make to development
results in your country?” is then calculated (excluding anyone who selected Don’t
Know as a response). This mean rating provides the defined overall indicator.
For the FCS disaggregation, only those respondents selected in #2 that are also
from FCS-designated countries are selected for analysis. The mean rating for thequestion, “How significant a contribution do you believe the World Bank Group’s
knowledge work and activities make to development results in your country?” is170

then calculated (excluding anyone who selected Don’t Know as a response). This
mean rating provides the defined FCS-disaggregated indicator.
Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)Country Opinion Surveys completed in the fiscal year in countries with IDA or Blend
financing.

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

Although the Country Opinion Survey program aims to survey a third of all World Bank
Group client countries each fiscal year, the deployment of the surveys is contingent upon
approval and cooperation of the region and the individual country team. The survey sample
is comprised of approximately 80% from country team databases of contacts andapproximately 20% from the independent fielding agency (which most often provides
supplemental contacts from outside the government). The response rate for Country Opinion
Surveys is approximately 50%.

Date methodology
agreed/updated

August 2023

171

TIER 3 INDICATORS

172

IDA Budget Anchor
A. Overview
Indicator name

IDA Budget Anchor (%)

Definition(as it should appear on thedigital IDA RMS card)

Administrative expenses as a share of IDA revenue.

Tier type

Three

IDA20 Cycle Timeline

FY23-25

Relevant SDG

NA

IDA20 Expected
range/valueLess than or equal to 100%

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Percentage☐ FCS☐ Females

Calculation method

Not Applicable

AnnualIDA’s goal is to have its net administrative expenses covered by its loan revenue (interest,
service charges, commitment fees, and guarantee fees). IDA Budget Anchor measures IDA
net administrative expenses* as a percentage of IDA loan revenue (a/b).
a) Net Administrative expenses for Budget Anchor are the total net non-interest
expenses on an Adjusted Net Income basis as taken from the IDA Financial
Statements.
b) Total Revenue for Budget Anchor is the total of Interest Revenue from Loans netof associated borrowing expenses, Commitment fee and Guarantee fee revenue,
and Gains (losses) on revenue-hedging forward currency contracts.

Data Calculation Method* IBRD and IDA's administrative budget is a single resource envelope that funds the
combined work programs of IBRD and IDA. The allocation of administrative expenses
between IBRD and IDA is based on an agreed cost and revenue sharing methodology
approved by their Boards. The allocation is primarily driven by the relative level ofactivities relating to lending, knowledge services and other services between the two
institutions.

Note:
1.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries

173

2.

Data Source(s)[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

Management’s Discussion and Analysis and IDA Financial Statements.
For reference, for Fiscal Year 2022 the IDA Budget Anchor was derived from Table 13:
Budget Anchor, on page 21 of June 2022’s ‘Management’s Discussion & Analysis andFinancial Statements (link:
https://financesapp.worldbank.org/summaryinfo/financialresults/)

C. Key counterparts
Contributing
PGs/GPs/Regions

WFAVP

D. Additional information
Harmonization withother corporate reporting
mechanisms:

Forward Look, Management’s Discussion and Analysis and IDA financial statements.

Limitations andExceptions

NA

Date methodology
agreed/updated

October 2016

174

Bank Budget to Portfolio Volume Ratio (per $ billion under supervision)
A. Overview
Indicator nameBank Budget to Portfolio Volume Ratio (per $ billion under supervision) ($ million)

Definition(as it should appear on thedigital IDA RMS card)

Total administrative budget expenses per US$ billion portfolio under supervision

Tier type

Three

IDA20 Cycle Timeline

FY23-25

Relevant SDG

NA

IDA20 Expected
range/value

Monitored

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency$ million☐ FCS☐ Females

Calculation method

Not applicable

Annually
The Bank Budget to Portfolio Volume measures the efficiency of IDA administrative
resource utilization. This measure is calculated by dividing the total IDA net Bank-budget
administrative expenses* by the IDA portfolio volume (a/b).
a)

The IDA net bank-budget administrative expense, measured in US$ millions, is theactual IDA Administrative Expenses less the actual IDA Reimbursable Revenue foradministrative activities.

b) The IDA portfolio volume, measured in US$ billions, is the total of IDA net
commitment amounts at the end of the reporting period, reported for active IBRD/IDA
projects.
Data Calculation Method* IBRD and IDA's administrative budget is a single resource envelope that funds the
combined work programs of IBRD and IDA. The allocation of administrative expenses
between IBRD and IDA is based on an agreed cost and revenue sharing methodology
approved by their Boards. The allocation is primarily driven by the relative level ofactivities relating to lending, knowledge services and other services between the two
institutions.
Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should

175

include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)
Data Source(s)World Bank Enterprise Resource Planning (SAP – Systems Applications and Products).

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

NA

Date methodology
agreed/updated

July 2018176

Average cost of IDA supervision projects (implementation support)
A. Overview
Indicator name

Average cost of IDA supervision projects (implementation support) ($ thousand)Definition(as it should appear on thedigital IDA RMS card)

These are supervision costs attributed directly to operational projects in the IDA portfolio
divided by the monthly average number of projects in the IDA portfolio, plus the 3-year
weighted average costs of fiduciary (financial management and procurement) andsafeguards (environmental and social safeguards) that are indirectly attributed to theportfolio.

Tier type

Three

IDA20 Cycle Timeline

FY23-25

Relevant SDG

NA

IDA20 Expected
range/value

Monitored

Included in IDA19

Yes

B. Methodology
Unit of Measure$ thousand☒ FCS

Reporting Disaggregation(if relevant)Internal Data Update
Frequency☐ Females

Calculation method

The average cost of IDA supervisionprojects indicator is disaggregated for FCS
countries. The calculation method applies
the same as for IDA projects, with theinformation filtered for countries in the
FCS-country list.

AnnualThe average cost of IDA supervision projects is the sum of (a) supervision costs charged
directly to IDA projects, including fiduciary (financial management and procurement) andsafeguards (environmental and social safeguards), (b) divided by the monthly average
number of projects in the IDA portfolio; plus (c) the 3-year weighted average costs offiduciary and safeguards shared services not charged to projects that are indirectly attributed
to the IDA portfolio.
(Average cost of IDA supervision projects = a/b + c)

Data Calculation Method• The project supervision (direct) cost is calculated as the total costs charged to IDA
projects, applied exclusively to IBRD/IDA projects and guarantees that are IDA financier
type; all business processes associated with project supervision; and cost funded by the
Bank’s budget.
• A portion of supervision cost for fiduciary and safeguards shared services are notcaptured under specific projects but collected through portfolio, sub-regional, or regionalbased cost objects dedicated to project supervision. These indirect costs are thenattributed to projects in the IDA portfolio on a weighted average basis over three years

177(i.e., the average of total fiduciary/safeguards supervision cost and the total number ofprojects in portfolio in the last three years, multiplied by the number of projects in the
IDA portfolio).
Note:
1.

2.

Data Source(s)1.

World Bank Enterprise Resource Planning System (SAP – Systems Applications andProducts).

Key counterparts

Contributing
PGs/GPs/Regions
2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

NA

Additional information

Harmonization withother corporate reporting
mechanisms:

NA
Caveats to the calculation methodology:
1.

The current methodology excludes from the costs and counts some projects that are
blend-financier type that include IDA financing. However, the number of such
instances is small, and the impact on the indicator is immaterial. Changing themethodology implies adding another layer of manual processes to the calculation,
which further increases the complexity and probability of errors.

2.

Direct costs charged to projects exclude overheads and global mobility benefits
received by staff.

3.

FCS countries are identified using the Bank’s FCS country list and these do notcount sub-regional or regional projects which may comprise one or more countries
from the FCS-country list.

Limitations andExceptions

Date methodology
agreed/updated

October 2017178

Share of climate co-benefits over total commitments in IDA-supported operations
A. Overview
Indicator nameShare of climate co-benefits over total commitments in IDA-supported operations (%)
The indicator measures the share of a project’s IDA lending commitment at Board Approvalthat is expected to contribute to climate change adaptation and/or mitigation.
Climate Co-Benefits refer to the share of World Bank financing dedicated to eligible climate
mitigation and adaptation activities. All IDA/IBRD lending operations (such as Investment
Project Financing [IPF], Development Policy lending [DPL], and Program-for-Results[PforR]) are assessed for Climate Co-Benefits. IPFs are assessed at the Component or SubComponent level for activities linked to eligible expenditures; DPFs are assessed at the Prior
Action level and all prior actions are assumed to have equal financing; and PforRs areassessed based on the Disbursement Linked Indicators and the component-level description
to identify specific activities that can be counted towards adaptation and or mitigation.

Definition(as it should appear on thedigital IDA RMS card)

Calculation of Co-Benefits is based on the joint Multilateral Development Bank (MDB)
methodologies for tracking climate change adaptation and mitigation finance, which isapplied to all IBRD/IDA lending operations. This methodology is also used by nine other
MDBs for tracking adaptation and mitigation finance.
Adaptation Co-Benefits are based on a context- and location-specific approach and captures
financing amounts directly linked to measures addressing climate change vulnerability inprojects. Mitigation Co-Benefits are based on a MDB agreed list of eligible activities thatare compatible with low emissions pathways and support long-term decarbonization goals.
The list includes a series of 11 tables that describe the eligible activities by sector. There areseveral activities in each of these sector categories. Only the listed activities are eligible tobe counted for mitigation Co-Benefits. This means that if the activity is not listed in theeligible activities list, but illustrates GHG reductions through GHG analysis, it still cannot
count toward mitigation Co-Benefits.

Tier type

Three

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 13.2: Integrate climate change measures into policy and planning

IDA20 Expected
range/value

35% over FY23-FY25

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Percentage (%)☐ FCS☐ Females

Calculation method

Quarterly

179

NAData Calculation Method

1) Climate Co-Benefits are calculated ex-ante based on the approved Board package(specifically based on climate information available in the PAD or equivalentproject document) for all IDA lending operations.
2) Final Climate Co-Benefits across all IDA projects are aggregated and recorded in
the WB-internal Climate Commitments Dashboard, on a monthly basis.
3) Along with the monthly Climate Commitments Dashboard update, CCG prepares amonthly Climate Commitments update for the SD VP. A similar fiscal year-end
report is also prepared.
4) The Climate Co-Benefits percentage (climate finance) refers to the original amountof IDA financing that was committed at Board approval stage (i.e., grosscommitments). These monthly and year-end reports will be used as a basis tomonitor and biannually report on this RMS indicator.
5) Exclude P178372, P176786, P176459, and P173312 from FY23 list
Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)Primary: WB-internal Climate Co-Benefits Dashboard;
Data Source(s)Secondary: CCG Monthly and Year-End Climate Co-Benefits Reports to SD VP.
C. Key counterparts
Contributing
PGs/GPs/Regions

All PGs/GPs across the WB are contributing to achievement of the objective and target.

D. Additional information
Monitoring and reporting of this RMS indicator will be aligned with that of the WBG
Climate Change Action Plan 2021-2025.
Harmonization withother corporate reporting
mechanisms:

Limitations andExceptions

Aggregate Climate Co-Benefits numbers are currently disclosed through four reporting
channels—Joint MDB Report on Tracking Climate Finance (WBG), IDA20 PC Reporting(IDA), and Capital Package Reporting (IBRD, IFC). In addition, project level Climate CoBenefits information financing has been disclosed for FY18, FY19, -FY20, FY21, andFY22 (IBRD/IDA).
The World Bank Group uses the joint MDB methodology for tracking climate finance in all
IBRD/IDA lending operations, jointly developed by the MDB in 2012. Both the mitigation
methodology and the adaptation methodology were recently updated 6 and approved for use
by all MDBs. Thus, this is not a methodology that the World Bank can independently

6

The adaptation methodology was updated in November 2022 and has officially been implemented at the WB
starting July 1, 2023 (FY24). The mitigation methodology was revised in early 2021 and has officially been
implemented at the WB starting July 1, 2021

180

change. Moreover, if used as the sole metric for tracking progress on climate action, CoBenefits have certain drawbacks. As an ex-ante, input-based metric, Co-Benefits captureand drive incremental climate action and are limited in their ability to measure the overall
climate impact of a project in a more holistic manner. This is because the metric is designed
to measure the amount of finance (input) that can be counted as “climate finance” (aka“Climate Co-Benefits”). Thus, Co-Benefits focus only on the climate-positive elements ofprojects, but not the overall impacts. Proposed reviews of the mitigation and adaptation CoBenefits methodologies are unlikely to change these core elements of the metric.
Date methodology
agreed/updated

181

Share of adaptation co-benefits over total climate co-benefits in IDA-supported operations
A. Overview
Indicator nameShare of adaptation co-benefits over total climate co-benefits in IDA-supported
operations (%)

Definition(as it should appear on thedigital IDA RMS card)

The indicator measures the share of adaptation co-benefits over total climate co-benefits ofproject’s IDA lending at Board Approval (i.e., IDA gross commitments). Climate change
adaptation refers to activities that are carried out in response to current or expected climatechange impacts. The joint Multilateral Development Bank (MDB) methodology for tracking
climate change adaptation and mitigation finance specifies that adaptation co-benefits must
be clearly linked to project activities that address the climate change vulnerabilities relevantto the project’s location and context. As per the methodology, adaptation co-benefits are
assigned to project activities when the project document: (i) sets out the climate change
vulnerability context of the project; (ii) makes and explicit statement of an intent to address
the identified climate vulnerabilities as part of the project; and (iii) articulates a clear anddirect link between specific project activities and the project’s objective to reduce
vulnerability to climate change. Through this three-step process, the methodology attempts
to capture the incremental cost of adaptation activities that are differentiated from the usualdevelopment finance in a project. If the incremental cost cannot be estimated, a proportional
approach is taken to determine the share of development activities that correspond toadaptation activities.

Tier type

Three

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 13.2 integrate climate change measures into national policies, strategies, and planning

IDA20 Expected
range/value>=50%

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Percentage (%)☐ FCS☐ Females

NA

Quarterly-

Data Calculation Method

Calculation method--

Adaptation Co-Benefits: The share of IDA lending commitment that contribute toclimate change adaptation. Adaptation Co-Benefits must be clearly linked toproject activities that address the climate change vulnerabilities relevant to theproject's location and context.
Climate Co-Benefits including Adaptation and Mitigation Co-Benefits arecalculated ex-ante based on the approved Board package (specifically based on
climate information available in the PAD or equivalent project document) for all
IDA lending operations.
Final Climate Co-Benefits across all IDA projects are aggregated and recorded in
the WB-internal Climate Commitments Dashboard, on a monthly basis.

182

-

-

-

Along with the monthly Climate Commitments Dashboard update, CCG prepares amonthly Climate Commitments update for the SD VP. A similar fiscal year-end
report is also prepared.
The Climate Co-Benefits percentage (climate finance) refers to the original amountof IDA financing that was committed at Board approval stage (i.e., grosscommitments). These monthly and year-end reports will be used as a basis tomonitor and biannually report on this RMS indicator.
Exclude P178372, P176786, P176459, and P173312 from FY23 list

Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)Primary: WB-internal Climate Co-Benefits Dashboard;
Data Source(s)Secondary: CCG Monthly and Year-End Climate Co-Benefits Reports to SD VP.
C. Key counterparts
Contributing
PGs/GPs/Regions

All PGs/GPs across the WB are contributing to achievement of the objective and target.

D. Additional information
Monitoring and reporting of this RMS indicator will be aligned with that of the WBG
Climate Change Action Plan 2021-2025.
Harmonization withother corporate reporting
mechanisms:

Limitations andExceptions

Aggregate Climate Co-Benefits numbers are currently disclosed through four reporting
channels—Joint MDB Report on Tracking Climate Finance (WBG), IDA20 PC Reporting(IDA), and Capital Package Reporting (IBRD, IFC). In addition, project level Climate CoBenefits information financing has been disclosed for FY18, FY19, -FY20, FY21, andFY22 (IBRD/IDA).
The World Bank Group uses the joint MDB methodology for tracking climate finance in all
IBRD/IDA lending operations, jointly developed by the MDB in 2012. Both the mitigation
methodology and the adaptation methodology were recently updated 7 and approved for use
by all MDBs. Thus, this is not a methodology that the World Bank can independently
change. Moreover, if used as the sole metric for tracking progress on climate action, CoBenefits have certain drawbacks. As an ex-ante, input-based metric, Co-Benefits captureand drive incremental climate action and are limited in their ability to measure the overall
climate impact of a project in a more holistic manner. This is because the metric is designed

7

The adaptation methodology was updated in November 2022 and was officially implemented at the WB starting
July 1, 2023 (FY24). The mitigation methodology was revised in early 2021 and was officially implemented at the
WB starting July 1, 2021

183

to measure the amount of finance (input) that can be counted as “climate finance” (aka“Climate Co-Benefits”). Thus, Co-Benefits focus only on the climate-positive elements ofprojects, but not the overall impacts. Proposed reviews of the mitigation and adaptation CoBenefits methodologies are unlikely to change these core elements of the metric.
Date methodology
agreed/updated

NA

184

Total private mobilization of WBG-supported operations/transactions in IDA countries
Direct Mobilization
Indirect Mobilization
A. Overview

Indicator name

Total private mobilization of WBG-supported operations/transactions in IDA
countries.
-

Direct mobilization ($ billion)
Indirect mobilization ($ billion)

Private Capital Mobilization (Private Co-financing) is the private financing mobilized by an
MDB in a project. Total activity financing of the project is the from all public and private
sources provided in connection with a specific activity for which the MDB is providing
financing. Total Activity Financing is composed of the following three components: 1MDB Commitment; 2- Private Co-financing (including private sponsor financing); 3- Public
Co financing.
Private Capital Mobilization (Private Co-financing) is the investment made by a private
entity, where “private entity” is defined as a legal entity that is: (i) carrying out or isestablished for business purposes; and (ii) financially and managerially autonomous fromnational or local government. Examples include registered commercial banks, insurancecompanies, sovereign wealth funds and other institutional investors investing primarily on acommercial basis.
Definition(as it should appear on thedigital IDA RMS card)

Private Capital Mobilization (Private Co-financing) includes Private Direct Mobilization
and Private Indirect Mobilization. Private Direct Mobilization is financing from a private
entity on commercial terms due to the active and direct involvement of an MDB leading to
the commitment. Evidence of active and direct involvement includes mandate letters, fees
linked to financial commitment or other validated or auditable evidence of an MDB’s active
and direct role leading to commitment of other private financiers. PDM does not include
sponsor financing. Private Indirect Mobilization is defined as financing from private entities
provided in connection with a specific activity for which the World Bank Group isproviding financing and is not playing an active or direct role that leads to the commitmentof the private entity’s finance. Private Indirect Mobilization includes sponsor financing if
the sponsor qualifies as a private entity.
More detail can be found in the MDB Methodology for Private Investment MobilizationReference Guide- June 2018. Methodology can be found under the “Other” section in thisdocument.
Data is reported for IDA eligible countries, including blend countries, in a reporting fiscal
year.

Tier type

Three

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 17.3: Mobilize additional financial resources for developing countries from multiple
sources

IDA20 Expected
range/value

Monitored

Included in IDA19

Yes

185

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency$ billion☒ FCS☐ Females

Calculation method

Yearly1) Key terms that limit what is counted: the private co-financing amounts being
reported at the time of board approval in board package data sheet.
2) Bank instruments include IPF, DPF with Guarantee, PforR, Guarantees
3) Value is expected, estimated at the time of Board approval
4) Keywords include “PCM” “Private Capital Mobilization” “Private Co-financing”“PPP” “Guarantees”; any amounts under unguaranteed commercial financing indata table5) PCM from Blend projects will be based on specific project component. If both
IBRD and IDA financed the project component PCM comes from, the PCM
amount is split between IBRD and IDA pro rata
6) Criteria applied in manual checks: Private entity definition according to the
Methodology (see under Others”);

Data Calculation Method

Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

Source of data include Region’s input, Task team inputs in Operations Portal and PAD,
Standard Report 11.5

C. Key counterparts
Contributing
PGs/GPs/Regions

All Regions

D. Additional information
Harmonization withother corporate reporting
mechanisms:
Limitations andExceptions
Date methodology
agreed/updated

NA

PCM Methodology
Reference Guidelines_Final.pdf

Please refer to the attached methodology reference guideline for more information.
Methodology was finalized in June 2018

186

IDA countries with the lowest Human Capital Index supported to improve thesustainability of human capital financing
A. Overview
Indicator name

IDA countries with the lowest Human Capital Index supported to improve thesustainability of human capital financing (number)Definition(as it should appear on thedigital IDA RMS card)

The indicator tracks progress of IDA20 policy commitment 8 under Human Capital Special
theme: To strengthen public finance for human capital investments, support IDA operationsin at least 20 IDA countries, of which eight are among those with the lowest HCI, throughpolicy or administrative reforms impacting (i) the availability of resources, and/or (ii) the
efficiency of expenditure management, and/or (iii) the results-orientation of human capital
investments. (HC8)Tier type

Three

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 17.1: Strengthen domestic resource mobilization, including through international
support to developing countries, to improve domestic capacity for tax and other revenue
collection.

IDA20 Expected
range/value

20

Included in IDA19

Yes, but IDA19 focused on the sustainability of human capital financing with a policy
commitment supporting mainly analytical work. Under IDA20 the focus will be to expand
and to also emphasize improved adequacy and efficiency with a policy commitment focusedon operations.

B. Methodology
Unit of Measure
Reporting Disaggregation

Number of countries☐ FCS(if relevant)☐ FemalesInternal Data Update
Frequency

Semi-annual

Calculation method

The indicator counts countries where there are projects supporting human capital financing
administrative and/or policy reforms.

Data Calculation Method“Lowest HCI countries” refer to the 30 IDA countries with the lowest Human Capital Index(HCI). The HCI is a summary measure of the amount of human capital that a child born
today can expect to acquire by age 18, given the risks of poor health and poor education thatprevail in the country where the child lives. It measures 5 dimensions of human capital - theprobability of survival to age 5, expected years of school, harmonized test scores, the adultsurvival rate from age 15 to 60 and the fraction of children under 5 not stunted. Using
estimates of the economic returns to education and health, these components are combined
into an index that captures the expected productivity of a child born today as a future
worker, relative to a benchmark of complete education and full health. As of September
2021, the lowest 30 HCI IDA countries (based on the HCI 2020 update) are: Afghanistan,
Benin, Burkina Faso, Burundi, Cameroon, Central African Republic, Chad, Comoros, Côte

187

d'Ivoire, Dem. Rep. of Congo, Ethiopia, Guinea, Lesotho, Liberia, Madagascar, Malawi,
Mali, Mauritania, Mozambique, Niger, Nigeria, Pakistan, Rwanda, Sierra Leone, South
Sudan, Sudan, Tanzania, Uganda, Yemen, Zambia. This list will be updated periodically. As
with IDA eligibility, a project will “count” if the country is on the list at the time of Board
approval.
Qualifying instruments:
Only financing operations (i.e., IPFs, PforRs, DPOs) approved by the Board under IDA20
within the IDA20 cycle (FY23—FY25) will count against the targets. ASAs and stand-alone
TF-funded operations are excluded.
Contributing global practices: It is expected that projects led by EDU, GOV, HNP, MTI
and SPJ will contribute to the achievement of this policy commitment.
To qualify, a country must have:
IDA operations with components or policy actions that meet one or more of the aspects ofthe policy commitment•
Qualifying administrative and policy reforms: improving budget reliability,transparency of public finances, or control in budget execution for human capital
investments in at least one HD sector.
•
Operations supporting country-based reforms that aim at improving government’s
capacity to better link human capital spending and related public investments withmeasurable outputs/outcomes for at least one (pilot) HD sector through reforms such as
results- or program-based budgeting - stronger policy coordination and management, andimproving the incentives, skills, and accountability of key service delivery personnel, suchas teachers and medical workers.
•
PforRs or IPFs that support increased efficiency or effectiveness of HC investments
through disbursement-linked indicators (DLIs) or performance-based conditions (PBCs)
linked to outputs/outcomes in at least one HD sector.
•
DPOs that support prior actions aimed at increasing expenditure efficiency (e.g.,more output with the same or less resources) or effectiveness (e.g., improved spending
outcomes) for HC investments. Reforms in areas that direct more resources toward HC
investments, such as energy subsidy reforms, would also count.
Methodology: qualitative review of PADs
Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

Data Source(s)C. Key counterparts
Contributing
PGs/GPs/Regions

EDU, GOV, HNP, MTI, and SPJ

188

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

Data are not disaggregated by FCS but rather according to “lowest HCI countries.”

Date methodology
agreed/updated

January 4, 2023

189

IDA $ commitments with disaster risk management co-benefits
A. Overview
Indicator name

IDA financing commitments with disaster risk management co-benefits ($ billion)

Definition(as it should appear on thedigital IDA RMS card)

This indicator measures an approximate dollar value of the sum approved by the Board in agiven fiscal year, to be extended to clients in loan, credit, or grant terms from IDA sources
identified as providing disaster risk management co-benefits.8 Disaster Risk Management(DRM) aims to avoid, lessen or transfer the adverse effects of natural hazards9 throughactivities and measures for prevention, mitigation and preparedness.

Tier type

Three

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 13.2: Integrate climate change measures into national policies, strategies and planning

IDA20 Expected
range/value$ 2 billion

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation$ billion☒ FCS(if relevant)☐ FemalesInternal Data Update
Frequency

Once a year-

Data Calculation Method

Calculation method

n/a (unit of measure is $ billion)

The World Bank’s Global Facility for Disaster Reduction and Recovery Unit calculates
ex-post DRM co-benefits (CB) based on the final assessment of climate adaptation cobenefits (CCB) of all IDA financed Investment Project Financing (IPFs), Development
Policy Financing (DPFs) and Program for Results (PfoRs) approved during the last FY(including any additional financing) considering the following criteria:• The calculation is based on the principle that DRM CBs and adaptation CCBs
are conceptually linked, and therefore two intersecting sets, with certain
aspects that do not overlap, as outlined below.
• We define DRM CBs equal to adaptation CCB (-) minus activities linked toclimate resilience that are not DRM-related as environmental conservation
activities, blue economy and ocean-related activities, agricultural activities
related to climate resilience of crops among others; (+) plus activities related
to the management of geological risks as earthquake, volcanoes, earthquake
induced tsunamis and landslides among others.
• For this FY, we consider all GPs’ IDA or blended IBRD/IDA projects having

8 Development activities provide DRM co-benefits when they contribute to DRM, even when this is not their main objective.
9 Weather and climate-related hazards (hydrometeorological) as well as geological hazards including earthquakes, earthquake-

induced tsunami and landslides, volcanic eruptions, among others.

190

•

•
•

DRM CBs and adaptation CCBs equal except for Environment, Natural
Resources, and Blue Economy, Governance and Agriculture GPs 10 For thesethree GPs an in-depth analysis of CCB detailed assessment using a subset of
FY23 projects have been done. Based on this analysis11, we calculate an
average percentage (%) of DRM CBs per GP based on the CCBs assessment.
Next FY, we will continue refining the methodology to expand the analysis
and include other GPs.
We assign all standalone IDA Cat DDOs as having 100% DRM CCBs. Hybrid
DPOs with a Cat DDO will be counted based on the number of DRM-related
prior actions supported under the program through an analysis of the Program
Document.
We assign all Food Security Projects responding to Ukraine crisis as having
0% DRM CCBs.12
We assign all COVID-19 related projects as having 0% DRM CCBs.13

Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

The revised DRM co-benefits methodology is grounded in the established principles anddetailed database from the Climate Change Co-Benefits assessment done for each project
after board approval (SCCOP database).
Data Source(s)DRM co-benefits are derived from the adaptation CCB with the subtraction of a set ofprimarily "environmental” activities and with the addition of benefits linked to “reduced
geo-hazards and impacts”, not captured under adaptation CCBs.
C. Key counterparts
Contributing
PGs/GPs/Regions

SCCOP

D. Additional information

10 For all GPs except for ENB, Agriculture and Governance GPs, we do not expect project financed activities will differentiate

between geological and hydro-meteorological hazards (Safer Schools, Resilient Transport and Energy networks, Adaptive Social
Protection) therefore we assume CCBs are equal to DRM CBs. The choice of the ENB, Agriculture and Governance GPs wasdone based on a technical analysis considering projects under these GPS could have high CCBs which include no DRM-related
activities as defined in point ii.
11 Total set of IDA projects in the FY20-23 subset with CCBs: 1,100. The sample size was 43 projects in the three selected GPs(Agriculture, Governance and ENB) for FY23. Confidence level 95% and margin of error 15%
12 & 7 For Ukraine and COVID-19 response/emergency projects we assume DRM CBs (as for CCBs) are very low since activities
were linked to respond to a specific non-natural hazard-related crisis. We therefore assign 0 DRM CBs to all the projects related
to the emergency response to these two events.

191

Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

We anticipate some challenges with this methodology since the team propose estimations
only for certain sectors/GPs which we expect having large CCB without DRM CCB.
Having a proxy methodology there is a potential risk of counting extra DRM CCBs. We
consider the proposed methodology to correspond to the upper bound of the DRM CCBs.
We anticipate the revised indicator to better align with the Climate Change Co-Benefit
ecosystem and therefore improve the consistency of the WBG's reporting on CC related
actions and impacts. We also anticipate that the increased transparency of the methodology
and its simplicity will be beneficial to its interpretation by donors and task teams alike.
Nonetheless, as a first step in aligning this indicator with CCBs, we anticipate fine-tuning
needs in the following Fiscal Years, consistent with the overarching principles outlined inthis document.

Date methodology
agreed/updated

The last update to the methodology was done on October 24, 2023.

192

Satisfactory Bank performance in IDA-financed operations
OverallAt entry
During supervision
A. Overview
Satisfactory Bank performance in IDA-financed operations (%, IEG Rating):
Indicator name-

OverallAt entry
During supervision

Definition(as it should appear on thedigital IDA RMS card)

This indicator measures percentage of the net-commitment amount of the closed IDA
projects reviewed by IEG that are rated Moderately Satisfactory, Satisfactory, or Highly
Satisfactory on overall bank’s performance, performance at entry and performance during
supervision, against the total net-commitment amount of the closed IDA projects reviewed
by IEG in a three-year rolling basis.

Tier type

Three

IDA20 Cycle Timeline

FY23-25

Relevant SDG

NA
Satisfactory Bank performance in IDA-financed operations:

IDA20 Expected
range/value

Included in IDA19-

Overall (%, IEG ratings, 3-year rolling): 80%-

At entry (%, IEG ratings, 3-year rolling): Monitored-

During supervision (%, IEG ratings, 3-year rolling): Monitored

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation

Percentage (%), IEG ratings, 3-year rolling☒ FCS(if relevant)☐ FemalesInternal Data Update
Frequency

We do not report on this data outside of IDA RMS

Data Calculation Method

Calculation method

The IEG ratings data is downloaded from AO report 4.a.1. “Key IEG Indicators”. We use
Agreement Type to separate IBRD and IDA projects. Please note that IBRD agreement typeincludes Blend projects, so IDA Agreement Type only includes purely IDA financed
projects. We also download the evaluation data from AO report 4.c.2 “Counts for ICR and
IEG Ratings” to check evaluation rates for recent closing FYs. Only FYs where at least 60
percent of projects are IEG evaluated are included.
The evaluation rate is calculated in % as number of evaluations divided by number of each
FY’s closed projects for all IBRD/IDA (PE product line) projects. Once the most recent FY
reaches 60%, we include it in the 3-year rolling average.

193

We check the IEG rating data from “Key IEG Indicators” report for any major
inconsistencies (closed and evaluated projects showing with a date in the future, forexample). If needed, we work with ITS to fix the underlying issues in our systems. Once thedata is checked, we add tags for FCV, based on AO country code and the FCV list specified
by the IDA RMS team; the FY21 list was used for the last update. We then then create
pivots for calculating the 3-year rolling average for % Satisfactory Bank Performance atentry, during supervision and overall. Please note:
1) We only include projects in “Closed” project status.
2) AF projects are not included in the data.
3) We use Closing FY field, which is based on Revised Closing Data, and not Exit
FY, which is based on Deactivation Date and can result in incorrect values.
4) We use project Agreement Type to determine whether a project is IDA; blend
projects are reported under the IBRD Agreement Type and are therefore excluded
from this reporting.
5) All instruments are included (IPFs, DPFs and P4Rs).
6) Region field used is VPU, which cleanly separates the old AFR code into AFE and
AFW.
7) Unrated projects (blank value) are excluded.
8) 3 year rolling average is calculated for the selected FY range, using net
commitments values for share of commitments
For Satisfactory rated projects, AO reports value of 100 in “Bank Performance at Entry %Sat”, “Bank Performance at Supervision % Sat” and “Bank Overall Performance % Sat”
fields of the “Key IEG Indicators” report. To calculate the Satisfactory Bank performancevalues, we divide Satisfactory-rated project net commitment total divided by net
commitment total of all rated projects in given FY. We then average last three FY for which
we meet the 60 percent evaluated threshold.
Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

AO reports 4.a.1. “Key IEG Indicators” and 4.a.1. “Key IEG Indicators” for data; AO
report 4.c.2 “Counts for ICR and IEG Ratings” to determine time window.

C. Key counterparts
Contributing
PGs/GPs/Regions

none

D. Additional information
Harmonization with othercorporate reporting
mechanisms:

NA

194

Limitations andExceptions

The reporting system overhaul and the upcoming full switch to Standard Reports will
require validation of the SR data against the AO reports; the upcoming transition to single
product line and viewing projects by type of financing will require redefining what iscounted as IDA projects (any projects with IDA financing) instead of using Agreement
Type.

Date methodology
agreed/updated

Methodology agreed upon few years ago and confirmed during last update of the Scorecard
data, September 2022.

195

Quality of M&E in IDA-financed operations
A. Overview
Indicator name

Quality of M&E in IDA-financed operations (%, IEG ratings, 3-year rolling)

Definition(as it should appear on thedigital IDA RMS card)

This indicator measures percentage of the net-commitment amount of the closed IDA
projects reviewed by IEG that are rated “Substantial” or “High” on quality of M&E, against
the total net-commitment amount of the closed IDA projects reviewed by IEG in a threeyear rolling basis.

Tier type

Three

IDA20 Cycle Timeline

FY23-25

Relevant SDG

NA

IDA20 Expected
range/value

60%

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency% IDA commitments, IEG ratings, 3-year rolling☒ FCS☐ Females

Calculation method

We do not report on this data outside of IDA RMS
The IEG ratings data is downloaded from AO report 4.a.1. “Key IEG Indicators”. We use
Agreement Type to separate IBRD and IDA projects. Please note that IBRD agreement typeincludes Blend projects, so IDA Agreement Type only includes purely IDA financed
projects. We also download the evaluation data from AO report 4.c.2 “Counts for ICR and
IEG Ratings” to check evaluation rates for recent closing FYs. Only FYs where at least 60
percent of projects are IEG evaluated are included.
The evaluation rate is calculated in % as number of evaluations divided by number of each
FY’s closed projects for all IBRD/IDA (PE product line) projects. Once the most recent FY
reaches 60%, we include it in the 3-year rolling average.

Data Calculation Method

We check the IEG rating data from “Key IEG Indicators” report for any major
inconsistencies (closed and evaluated projects showing with a date in the future, forexample). If needed, we work with ITS to fix the underlying issues in our systems. Once thedata is checked, we add tags for FCV, based on AO country code and the FCV list specified
by the IDA RMS team; the FY21 list was used for the last update. We then then create
pivots for calculating the 3-year rolling average for Quality of M&E in IDA-financed
operations. Please note:
1) We only include projects in “Closed” project status.
2) AF projects are not included in the data.
3) We use Closing FY field, which is based on Revised Closing Data, and not Exit

196

FY, which is based on Deactivation Date and can result in incorrect values.
4) We use project Agreement Type to determine whether a project is IDA; blend
projects are reported under the IBRD Agreement Type and are therefore excluded
from this reporting.
5) All instruments are included (IPFs, DPFs and P4Rs).
6) Region field used is VPU, which cleanly separates the old AFR code into AFE and
AFW.
7) Unrated projects (blank value or #) are excluded.
8) 3 year rolling average is calculated for the selected FY range, using net
commitments values for share of commitments
AO reports values of “Low”, “Negligible”, “Modest”, “Substantial”, “High”, “NonEvaluable, “Not applicable” and “#” (equivalent to blank), in “M&E Quality” field of the“Key IEG Indicators” report. To calculate the values for Quality of M&E, we divide Highand Substantial-rated project net commitment total divided by net commitment total of all
rated projects in given FY. The “#”, “Non-Evaluable” and “Not applicable” values are
excluded. We then average last three FY for which we meet the 60 percent evaluatedthreshold.
Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

AO reports 4.a.1. “Key IEG Indicators” and 4.a.1. “Key IEG Indicators” for data; AO
report 4.c.2 “Counts for ICR and IEG Ratings” to determine time window.

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

The reporting system overhaul and the upcoming full switch to Standard Reports will
require validation of the SR data against the AO reports; the upcoming transition to single
product line and viewing projects by type of financing will require redefining what iscounted as IDA projects (any projects with IDA financing) instead of using Agreement
Type.

Date methodology
agreed/updated

Methodology agreed upon few years ago and confirmed during last update of the Scorecard
data, September 2022.

197

IDA20 projects with an AA Resilience Rating
A. Overview
Indicator name

IDA20 projects with an AA Resilience Rating (number)
The indicator measures the number of IDA20 projects with an AA rating as measured by the
new Resilience Rating System (RRS). The RRS has been developed by the World Bank
Group with the aim to guide investment decisions and improve climate resilience in project
design and outcomes (World Bank, 2021), and has been piloted on 20+ IDA19 projects.

Definition(as it should appear on thedigital IDA RMS card)

The RRS provides guidance and specific criteria to assess resilience along twocomplementary dimensions of project design: (1) the resilience of the project rates theconfidence that expected investment outcomes will be achieved in spite of climate anddisaster risks, based on whether a project has considered these risks in its design,
incorporated adaptation measures, and demonstrated economic viability considering climate
risk uncertainty, and (2) the resilience through the project rates a project’s contribution to
the resilience of beneficiaries, communities and systems, based on the nature of theoutcomes (e.g., a new social protection will help a community deal with shocks; a new roadwill help them evacuate before a storm; a new building code that ensures buildings canwithstand higher winds from hurricanes).
With a rating from C to A+ in each dimension, the RRS offers a way to “label” projects andserve as a guide to reflect the extent to which adaptation and resilience considerations havebeen integrated into the design of projects and investments, to increase the attractiveness ofprojects that have been well designed, and guide investors and decision-makers so that they
can prioritize projects that are resilient and contribute to resilience building. These ratings
can also improve tracking of progress on adaptation and resilience, including the quality ofadaptation investments, as well as create incentives to engage in more and better adaptation.

Tier type

Three

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 13.1: Strengthen resilience and adaptive capacity to climate related hazards and natural
disasters in all countries.

IDA20 Expected
range/value

10 projects

Included in IDA19

No (new indicator in RMS, was piloted as PC in IDA19)

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Number of projects☒ FCS☐ Females

Calculation method

Yearly198

NA

The indicator measures the number of IDA20 projects with an AA rating as measured by the
new Resilience Rating System (RRS).
•
•

•

•
•
Data Calculation Method

•
•
•
•
•

IDA20 projects are defined as projects that are Board Approved between the
IDA20 cycle (FY23-25)
Projects (IPFs only) to apply RRS are nominated by Regional Directors. Suggested
sectors for IDA20 include Agriculture, Environment (Forestry), Urban, DRM, andWater; Energy, Transport, and Digital Development; Education, Health, and SPJ;
and FCI.
Climate Change Specialists in the RRS team in CCG work with Task Teams andprovide inputs on climate risk assessments and adaptation considerations for
project design. Climate Change Specialists also conduct climate and disaster risk
stress tests on project’s economic and financial analysis. screens the projects in theearly stage of project preparation to identify risks and to enhance the resilience of
project design.
As the RRS methodology is continuously updated, the latest version will beutilized to assess the projects (as confirmed by the RRS focal points in CCG)
The final RRS rating used to monitor and track the progress of this indicator willbe the one assessing the project’s Board-level document
The final RRS rating will be verified by the RRS focal points in CCG
Multiple projects may be from the same IDA country and will be counted as
unique entries if each achieves the AA rating
Projects from Blend countries and IDA-only countries are both eligible to be rated
and will count toward this indicator
Additional financing projects may also be rated
Bank instrument type: IPFs

Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

Board-Approved PADs, RRS template

C. Key counterparts
Contributing
PGs/GPs/Regions

Task Teams working on adaptation and resilience-building projects

D. Additional information

Harmonization withother corporate reporting
mechanisms:

Developed as part of the IDA19 policy commitments, which provides guidance and criteria
for assessing resilience, the RRS methodology brings together the World Bank Group’s
corporate commitments on adaptation—climate and disaster risk screening, climate
adaptation co-benefits, and climate (adaptation) indicators—under one umbrella.
Specifically, it builds on the World Bank’s climate and disaster risk screening commitment,
which mandates that all projects be screened for short- and long-term climate and disaster199

risks. It also offers guidance on conducting deeper risk assessments and providing
qualitative and quantitative estimates for levels of climate risk.
The RRS makes progress toward a corporate mandate to use new metrics to better capture
climate adaptation and resilience. As well as delivering at least 50 percent of climate financetoward adaptation (an input metric quantifying the share of World Bank lending
contributing to climate change), the World Bank has been making progress toward using
additional metrics to further incentivize effective climate adaptation actions and better
capture climate impacts. Developing resilience metrics (such as the RRS) that are designed
to increase incentives for more effective climate adaptation actions, and piloting them in 20
IDA19 operations, was a policy commitment under the IDA19 Replenishment Package. The
IDA20 Results Measurement System increases this ambition to encourage at least 10 IDA
operations to achieve an AA rating on the RRS scale. Furthermore, the World Bank Group
Climate Change Action Plan (CCAP) 2021–25 identifies the RRS as an important way ofmeasuring the resilience of operations to physical climate shocks.
•
Limitations andExceptions

Date methodology
agreed/updated•

Sector-specific methodologies to achieve an A rating in the ‘resilience of’dimension has not been developed for all sectors
Quality control by RRS focal point to review the final RRS ratings based on the
RRS methodology and the examples from IDA19 pilots is crucial to enforce
uniform application across sectors

NA

200

Percentage of IDA operations with substantial climate co-benefits including at least one
climate change indicator in the results framework
A. Overview
Indicator name

Percentage of IDA operations with substantial 14 climate co-benefits including at least
one climate change indicator in the results framework (%)

Definition(as it should appear on thedigital IDA RMS card)

Climate indicators are indicators in the results framework that track climate-related results.
All IDA operations with more than 20 percent Climate Co-Benefits15 will incorporate atleast one climate-related results indicator to increase the focus on climate outcomes.

Tier type

Three

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 13: Take urgent action to combat climate change and its impacts.

IDA20 Expected
range/value

95%

Included in IDA19

No

B. Methodology
Unit of Measure

Percentage☒ FCS
The Climate Commitments team encourages
and notes where task teams havedisaggregated indicators by gender. A
gender-element to the indicator, if present, isalso noted in the data records.

Reporting Disaggregation(if relevant)☐ FemalesInternal Data Update
Frequency

The review of operations requiring a climate indicator in the results framework is updated
monthly.

Data Calculation Method

The Climate Commitments (CC) team reviews projects with 20 percent climate co-benefits
at Decision meeting and at Approval stage to see if at least one climate indicator is present.
To be considered a climate indicator, the indicator must include the causal link to climate
action similarly to climate co-benefits assessment. In instances where there is no indicatoror causal link at Decision stage, the CC team alerts and advises the task team withrecommended action(s). The integrated CCG helpdesk (AskClimate Help Desk) facilitatesinquiries from task teams and engage their climate regional focal points as needed. The
climate indicator commitment is applicable to IPFs, DPFs, PforRs, additional financing andmulti-phase programs. Indicators are part of the Results Framework (for IPFs and PforRs)
and Policy Matrix (for DPFs).

Calculation method

14

Includes all operations with 20 percent or more climate co-benefits.
Climate co-benefits refer to the share of financing dedicated to climate change adaptation or mitigation in operations financed by the World
Bank, support climate action while also furthering development objectives.
15201

Note: Exclude P178372, P176786, P176459, and P173312 from FY23 list

Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

The PAD is reviewed for the project components. The results framework is the source ofappropriate climate indicators. The operations portal and standards reports are used for also
reviewing those operations with a climate tag.

C. Key counterparts
Contributing
PGs/GPs/Regions

All PGs/GPs/Regions

D. Additional information
Harmonization withother corporate reporting
mechanisms:

The climate indicators commitment is reported out as part of the CCAP 2021-2025
commitments

Limitations andExceptions

In certain cases, a project may receive less than 20% CCBs (and therefore may not include a
CI at the DM stage) but the final CCBs may increase to 20% or higher at Board Approval
due to changes in project design. In such situations, task teams may not have a chance toinclude a CI at Board Approval. Task teams receive a reminder at the DM stage to ensurecompliance with the CI requirement at the BA stage.

Date methodology
agreed/updated202

Percentage of IDA-supported projects that demonstrate a results chain by linking gender
gaps identified in analysis to specific actions that are tracked in the results framework
A. Overview

Indicator name

Percentage of IDA-supported projects that demonstrate a results chain by linking
gender gaps identified in analysis to specific actions that are tracked in the results
framework (%)

Definition(as it should appear on thedigital IDA RMS card)

Percentage of IDA-supported operations that identify specific gaps between women andmen, and/or boys and girls and link them to specific actions supported by the project, withindicator(s) in the results framework to track progress, out of the total IDA projects
approved in the reporting fiscal year.

Tier type

Three

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 5: Achieve gender equality and empower all women and girls.

IDA20 Expected
range/value

60%
Note: 60% is the corporate commitment

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Percentage (%)☒ FCS☐ Females

Calculation method

The data are updated on a monthly basis
The Gender Group reviews the Project Appraisal Document of all Board-approved projects
to assess whether the project meets the Gender Tag criteria, which are: i) the project
document provides a gender gap analysis or discussion relevant to the project scope; ii) the
project proposes specific interventions to address the identified gender gap(s); and iii) the
project document includes relevant indicators in the Results Framework to track progress ofthe proposed interventions. Projects must meet all three criteria to be Gender Tagged (Yesor No).

Data Calculation Method

The assessment applies to all IDA operations (as well as IBRD operations) across thefinancing instruments – IPFs, P4Rs, and DPOs – and to AFs and SFs.
Once the assessments are completed, the Gender Group submits the final data (% of the
projects that meet the Gender Tag out of the total number of approved projects in thereporting month) to OPCS every month. The final cumulative FY data is submitted to
OPCS in the context of the annual CSC reporting.
Note:
1.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only and

203

2.

Data Source(s)blend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

The data source is the Operations Portal. The Gender Portal(https://genderportal.worldbank.org) accesses the PADs on a continuing basis as they aresubmitted to SECPO for Board approval

C. Key counterparts
Contributing
PGs/GPs/Regions

The indicator covers all PGs, GPs, and Regions. The Regions and GPs as well as individual
project TTLs have an opportunity to review the Gender Tag assessment and to request a reassessment. The Gender Group maintains the Gender Tag data and is responsible forcalculating the indicator.

D. Additional information
Harmonization withother corporate reporting
mechanisms:

Limitations andExceptions

Date methodology
agreed/updated

The indicator is used in the CSC and IDA RMS reporting.
Monthly updates are used by OPCS for regular senior management briefings.
Data are shared with the Regions and GPs on a quarterly basis.
It is important to note that there is no Gender Tag “requirement” for individual projects as
the institution recognizes that not every investment operation can meaningfully address or
reduce a gender gap that is relevant to the PDO and project scope. This encourages
deliberate and targeted gender interventions where they are integral to the project’s intended
development outcomes and where the expected results can be tracked.
The application of WB’s Gender Tag methodology has helped enhance focus on gender in
its lending operations and has established an accountability mechanism to report on genderresults as evidenced by the steadily increasing share of the Gender Tagged operations in thepast years.
The Gender Tag methodology was instituted in FY17 as an M&E tool for monitoring theimplementation of the WBG Gender Strategy.

204

Disbursement ratio
A. Overview
Indicator name

Disbursement ratio (%)

Definition(as it should appear on thedigital IDA RMS card)

Ratio of disbursements during the fiscal year to the undisbursed balance at the beginning of
the fiscal year for IDA Investment Project Financing projects. There is no corporate target
for IDA disbursement ratio; instead, a corporate standard based on historical experience isused.

Tier type

Three

IDA20 Cycle Timeline

FY23-25

Relevant SDG

NA

IDA20 Expected
range/value

20%

Included in IDA19

Yes

B. Methodology
Unit of Measure

Percentage (%)☒ FCSReporting Disaggregation(if relevant)Internal Data Update
Frequency☐ Females

Calculation method

Please specify how females are counted(e.g., whether it’s a simple count OR if aformula is applied to arrive at the number offemales)

Annually
The indicator provides the amount of disbursement that took place in a fiscal year (FY)against the undisbursed balance amount in the beginning of the FY. The indicator is only
calculated for IPF instrument type.
Disbursement ratio = Disbursement in the FY/Undisbursed balance at the beginning of the
FY.
The value calculated is actual.

Data Calculation Method

Disbursement/Undisbursed amounts of Additional Financing operations are included in the
numerator and denominator of the ratio.
This indicator is only valid for a given FY, which means that a new ratio is calculated at theend of each fiscal year and the previous FYs disbursement and undisbursed figures don’t
factor in the new fiscal year.
Note:
1.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries

205

2.

Data Source(s)[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

One can find the disbursement ratio figures in Standard reports (P1.1), Analysis for Office(AO) (3a.12 – Disbursement Ratio by Year)

C. Key counterparts
Contributing
PGs/GPs/Regions

N/A

D. Additional information
IDA20 RMS: Tier 3 indicator.
Harmonization withother corporate reporting
mechanisms:

Limitations andExceptions

In the following corporate reports, the disbursement ratio is calculated for IBRD and IDA
together: Regional MOUs, Regional/PG Updates to the Board, Operations Update to theBoard
The reporting system overhaul to the upcoming full switch to Analysis in Excel (AE) from
AO will require validation of the AE data against the AO reports; the forthcoming transition
to the single product line and viewing projects by type of financing will require redefining
what is counted as IDA projects (any projects with IDA financing) instead of using
Agreement Type.

Date methodology
agreed/updated

206

Proactivity Index
A. Overview
Indicator name

Proactivity Index (%)

Definition(as it should appear on thedigital IDA RMS card)

The ratio of projects in “actual” problem status 12 months ago that have had a proactivity
action in the last 12 months divided by the total number of problem projects from 12 months
ago. After being downgraded to Moderately Unsatisfactory or lower for Development
Outcome and/or Implementation Progress rating in supervision reports, a project needs tohave one of the following actions taken within the next 12 months, otherwise it will beconsidered a proactivity problem. The actions are upgrade, close, cancel >=20%, suspend,or restructuring (both level 1 and level 2) (note: restructurings for extensions of closing
dates or reallocations are not counted as proactivity actions unless they are combined withother actions). Data of IDA-funded operations is reported.

Tier type

Three

IDA20 Cycle Timeline

FY23-25

Relevant SDG

NA

IDA20 Expected
range/value

80%

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Percentage☒ FCS☐ Females

Calculation method

Annually
This indicator provides information on the number of Proactive actions that have takenplace in the past 12 months for operations that were in problem status 12 months ago.
In AO (Analysis for Office) (3a.2): There is an indicator called Proactivity Index % thatgives the information. It can also be calculated using the following formula: Proactivity
Index % = Sum of Proactive Actions/Sum of Proact Proj

Data Calculation Method

In Standard Reports (P1.3): Proactivity Index (%) = No. of Proactivity Action taken last 12
months/ Problem Projects 12 months ago
The value calculated is actual.
The Proactivity Index % can be calculated for IPFs, DPFs, PforRs.
Only Parent projects are counted towards proactivity index %This indicator is only valid for a given FY, which means that the FY index is calculated at
the end of the fiscal year. A new set of proactive actions and problem project figures in the
new FY are used to calculate this indicator for the new fiscal year.

207

Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

One can find the Proactivity Index % figures in Standard reports (P1.3), Analysis for Office(AO) (3a.2 – Portfolio Status Indicator by Year)

C. Key counterparts
Contributing
PGs/GPs/Regions

N/A

D. Additional information
IDA20 RMS: Tier 3 indicator.
Harmonization withother corporate reporting
mechanisms:

In the following corporate reports, the Proactivity Index % is calculated for IBRD and IDA
together:
Regional MOU, Regional/PG Updates to the Board, QBBR, Operations Update to the Board

Limitations andExceptions

The reporting system overhaul to the upcoming full switch to Analysis in Excel (AE) from
AO will require validation of the AE data against the AO reports; the forthcoming transition
to the single product line and viewing projects by type of financing will require redefining
what is counted as IDA projects (any projects with IDA financing) instead of using
Agreement Type.

Date methodology
agreed/updated

208

IDA-supported operations that address and respond to gender-based violence (GBV)
A. Overview
Indicator name

IDA-supported operations that address and respond to gender-based violence (GBV)

Definition(as it should appear on thedigital IDA RMS card)

Number of operations that include actions to prevent and/or respond to GBV that go beyond
Sexual Exploitation and Abuse (SEA) and Sexual Harassment (SH) risk mitigation activities
as outlined in ESF related Good Practice Notes. Based on IDA-funded projects approved incurrent fiscal year.

Tier type

Three

IDA20 Cycle Timeline

FY23-25
SDG 5.1: End all forms of discrimination against all women and girls everywhere.

Relevant SDG

SDG 5.2: Eliminate all forms of violence against all women and girls in the public andprivate spheres, including trafficking and sexual and other types of exploitation.
SDG 5.3: Eliminate all harmful practices, such as child, early and forced marriage andfemale genital mutilation.

IDA20 Expected
range/value

Monitored

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Number of operations☒ FCS☐ Females

Calculation method

Semi-annually
The Gender Group’s reviewers monitor the indicator by reading the Project Appraisal
Document (PAD) or Project Document (PD) that are approved by the Board. Additional
financing are also reviewed separately from the parent project.
Step 1: The Gender Group’s gender tag reviewers review all board-approved
IDA/IBRD projects in a Fiscal Year. During their review, they mark those projects that
include any reference to GBV in the PAD/PD, and compile project details in a bespoke
database.

Data Calculation Method

Step 2: The Gender Group’s GBV team then reviews this bespoke database by gender tag
reviewers on projects with any reference to GBV to assess whether project activities arelimited to risk mitigation of Sexual Exploitation and Abuse (SEA) and Sexual
Harassment (SH) as per the ESF related Good Practice Notes or go further to focus on
GBV prevention and/or response.
The Gender Group GBV team considers that a project meets the indicator if it includes aclear description of actions that purposefully seek to prevent or respond to GBV.
Projects that include only SEA/SH risk mitigation measures (e.g. ensuring codes of conduct

209

signed by contractors, establishing GM for SEA/SH reporting, mapping service providers
for case referral, etc.) are not considered to meet the criteria as they are complying with ESF
standards. Projects that may potentially have an impact on GBV, but do not articulate
project activities to be geared towards addressing GBV are not included as meeting thecriteria.
All forms of GBV are considered. Example forms include: violence against women (VAW),
violence against women and girls (VAWG), physical violence, sexual violence, childmarriage, early marriage, forced marriage, domestic violence, intimate partner violence,
female genital mutilation, female genital cutting, forced prostitution, harmful traditional
practice, honor killing, trafficking, sexual violence, sexual harassment, sexual exploitation,
LGBTQI harassment, LGBTQI violence (non—exhaustive list).

Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

Source – Operations Portal
Data Source(s)Types – PADs/PDs

C. Key counterparts
Contributing
PGs/GPs/Regions

Gender GroupD. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

Assessments of operations in the Human Development Practice Group now benefit from the“Good Practice Note on Addressing Sexual Exploitation and Abuse and Sexual Harassment(SEA/SH) in Human Development Operations” which includes recommendations on thetypes of activities that are considered mitigation measures, and which reflect the ESF
principles and provisions. This note was launched early in FY23. For the past reporting
years, the GBV Team exercised its best judgment (based on the existing ESF Guidelinesthat apply to the INFRA operations) to identify HD operations that would meet theindicator, taking into consideration the individual project context, activities and relevant
potential GBV risks identified. As a result, there may be some adjustment in how GBVrelated activities in HD operations are assessed in the short term, thereby bringing down thenumber of HD operations that meet this indicator.

Date methodology
agreed/updated

NA

210

Country programs (SCDs and CPFs/CENs) informed by diagnostics on crisis preparedness
A. Overview
Indicator nameCountry programs (SCDs and CPFs/CENs) informed by diagnostics on crisis
preparedness (number)Definition(as it should appear on thedigital IDA RMS card)

Cumulative number of SCDs and CPFs/CENs delivered during IDA20 informed bycrisis preparedness assessments

Tier type

Three

IDA20 Cycle Timeline

FY23-25

Relevant SDG

NA

IDA20 Expected
range/value

Monitored

Included in IDA19

No

B. Methodology
Unit of Measure
Reporting Disaggregation

Number☒ FCS(if relevant)☐ FemalesInternal Data Update
Frequency

The indicator will be updated annuallyCalculation method

NA

SCDs and CPFs/CENs delivered within the Fiscal Year will be considered each year, but the
cumulative number during IDA20 cycle will be reported.
A word search for “Crisis Preparedness” as well as the main diagnostics16 will be performed
as a first step. If this term is found in the document, the following should be explored:•
Data Calculation Method••

If the text mentions that the SCD/CPF/CEN considered a Crisis Preparedness
diagnostic as an input; orIf it describes the results of such diagnostic; orIf the SCD/CPF/CEN identifies a knowledge gap in this area and if the CPF/CEN
explains the plans for addressing such knowledge gap.

Then, the SCD/CPF will be considered as informed by crisis preparedness assessment.
The total number of SCDs and CPFs will be reported separately to avoid double counting.

16 Some examples are: Crisis Preparedness Gap Analysis (CPGA) (FCV Group, multisectoral); Ready2Respond (R2R) (PURL/GFDRR);

Social Protection Stress Test (SPJ); Climate and Disaster Risk Finance diagnostics (FCI/DRF); Pandemic preparedness diagnostics (HNP); PostDisaster Financial Management Review and Engagement Framework (GOV). Other diagnostics, including those not prepared by the WBG will
also be considered.

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Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

The data will be collected from SCDs and CPFs/CENs approved within Fiscal Year.

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

Limitations andExceptions

Date methodology
agreed/updatedNA
It would be important to note that some of FY23 SCDs/CPFs/CENs have started preparation
before the commitments of IDA20, so it may take a while to reach a more consistent use ofcrisis preparedness analysis in Country Engagement Products.
A SCD/CPF/CEN will be considered as crisis informed even if it identifies a knowledge gap
in this area as long as the CPF/CEN mentions a plan to address this.
July 2023. The methodology may be refined during the preparation of the data.

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Facetime index in FCS
A. Overview
Indicator nameDefinition(as it should appear on thedigital IDA RMS card)

Facetime index in FCS
Staff presence on the ground in IDA-eligible FCS per year, measured as mission days incountry, resident staff days (assumed number of days per year x staff number) and local
consultant days worked.
Facetime (in days) = Total GE+ (staff at analyst level or higher) Mission Days in-country +resident GE+ staff days worked (assumed number of days per year [220] x staff number) +local consultant days worked. Annual fiscal year data is reported for all IDA-eligible
countries (+West Bank and Gaza) on the FY21 harmonized FCS list. To ensure consistency,
this list will remain the sample for IDA19 monitoring going forward.

Tier type

Three

IDA20 Cycle Timeline

FY23-25

Relevant SDG

NA

IDA20 Expected
range/value

Monitored

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Index/ Number of days
☒ FCS
☐ Females

Calculation method

NA

Annually
There are 3 data sources for calculation of Facetime:DS1 - Mission Data: GE + Staff & ETC Travel from Non-FCV to FCV countries or FCV
to Non-FCV countries
1. Derive the mission data for the Fiscal Year at the UPI & Trip level details
2. Filter the mission data with criteria as Source Country or Destination Country is an FCVCountry.

Data Calculation Method

3. Add Appt Type & Grade and filter it for GE+ Staff & ETCs
4. Use the mission days field to get the first part of Facetime
DS2 -Residency: GE + Staff in FCV Countries
1. Use the Monthly Snapshots on Staff on Board Report (in HR Dashboard) to get the No. of
GE+ Staffs & ETC in FCV Locations.
2. Multiply Each Month’s above staff count with 220/12 to get the Residency Number for
GE+ Staff in FCV Countries.

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DS3 - Residency: STC working in FCV Countries
1. Using STC Days Paid report in Contingent Workforce Dashboard (in HR Dashboard) get
the data of Days Paid by Plant Country with filters on HQ STC & Local STC.
2. Filter out the data for Plant Country as per the list of FCV Countries
3. Use the Total Days Paid as Residency Facetime for STCs
Facetime = DS1 + DS2 + DS3
Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

HR Dashboard

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

The methodology will be reviewed in an upcoming Working Group on FCV staffing mattersto assess any potential challenges.

Date methodology
agreed/updated

Last update: Sep 26, 2023.

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Share of IDA IPF operations that applied the concept of universal access at design
A. Overview
Indicator nameShare of IDA IPF operations that applied the concept of universal access at design (% ofapproved IDA IPF in FY)

Definition(as it should appear on
the digital IDA RMS
card)

The indicator measures the percentage of IDA IPF approved during a fiscal year applying theconcept of universal access at design. The indicator is aligned to the progressive realization of
disability inclusion within lending operations through the Environmental and Social
Framework. Universal access is defined as “unimpeded access for people of all ages andabilities in different situations and under various circumstances.”

Tier type

Three

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 10.2: By 2030 empower and promote the social, economic, and political inclusion of allirrespective of age, sex, disability, race, ethnicity, origin, religion or economic or other status

IDA20 Expected
range/value

Monitored

Included in IDA19

Yes

B. Methodology
Unit of Measure

Percentage of approved IDA IPF in FY (%)

Reporting
Disaggregation (ifrelevant)☐ FCS

Internal Data Update
Frequency☐ Females

Calculation method

Quarterly
The calculation uses data recorded on the Environmental and Social Standards (ESS) undereach IPF lending operation. Quarterly, a two-step process is used to conduct the analysis on
lending projects:••

Data Calculation
Method•The monitoring team filters IDA Investment Project Financing (IPF) operations within
the relevant time. This number is the denominator.
Out of these projects, the team selects projects that check “Yes” to “ESS 4: Is theconcept of universal access being applied?” This information is collected within aninternal monitoring database using the ESF documents prepared for each project. The
documents are available publicly. This number is the numerator.
A direct percentage calculation i.e., N/D * 100 is used to report the data for the RMS.

Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only and blend).
See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type215

(including IDA-financing), and Trust-fund financier type (including IDA-financing)

Data Source(s)IPF ESF summaries and management plans

C. Key counterparts
Contributing
PGs/GPs/Regions

Calculating Indicator:
SSI Global Unit

D. Additional information
Harmonization withother corporate
reportingmechanisms:
Limitations andExceptions
Date methodology
agreed/updated•••

ESF ISU (Implementation Support Unit) updates
SSI MoU Mid-Year Progress update
SSI MoU End-Year Progress update

The data used for this calculation are automatically extracted from project documents preparedby project task teams. While it is expected that all documents are accurate, any gaps in thesource data will also carry forward into this calculation.
January 2020216

Countries supported by IDA to take IFF-related actions
A. Overview
Indicator nameCountries supported by IDA to take IFF-related actions (number)Definition(as it should appear on thedigital IDA RMS card)

The indicator measures the number of IDA countries supported i) in the conduct ofcomprehensive Illicit Financial Flow (IFF) assessments including tax evasion issues and the
preparation of related action plans and; ii)in undertaking policy actions that tackle
corruption, money laundering, and/or tax evasion to reduce IFFs, such as strengthening
public accountability mechanisms, increasing access to and awareness of beneficial
ownership information, and/or adopting automatic exchange of information to reduce tax
evasion.
Indicator tracks progress under the IDA 20 Governance and Institutions policy commitment
number 5.

Tier type

Three

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 16.4: By 2030 significantly reduce illicit financial and arms flows, strengthen recovery
and return of stolen assets, and combat all forms of organized crime
SDG 16.5: Substantially reduce corruption and bribery in all their forms.

IDA20 Expected
range/value

Monitored

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Number of countries☒ FCS☐ Females

Calculation method

NA

Once a year
“IFF assessments” encompass the variety of tools the World Bank Group will use to help
IDA countries to monitor and measure IFFs. These include Tax Administration Diagnostic
Assessment Tools, AML-CFT National Risk Assessments, Tax evasion AML-CFT risk
assessment, the AML-CFT legal entities assessment and other approaches for assessing thedifferent dimensions of IFF.

Data Calculation Method

Activities supporting IFF policy actions are risk assessments, training of public officials,
workshops, legal and administrative reforms, reports, and assessments that contribute to thefight against corruption, money laundering, terrorist financing and tax evasion, including
activities to strengthen public accountability mechanisms, increase access beneficial
ownership information, and implementing exchange of information on request andautomatic exchange of information to reduce tax evasion.
Indicator is based on the number of IDA eligible countries having completed either acomprehensive assessment or supported to undertake a specific policy action.
Input data include ASAs, including TFs and EFOs, IPFs, DPFs, and P4Rs. The calculated

217

value is the total number of countries for July 2022 to June 2025 that satisfy the scopecondition with respect to having been supported with a comprehensive assessment or
supported to undertake a specific policy action. Data includes assessments and actions
supported through trust funds (and in some cases) operations without IDA funding.
A combination of approaches is used to take into account that the system does not havecodes sufficient to capture all support to countries in controlling IFFs. Relevant projects are
identified by a list of country projects including relevant IFF activities (National/Sectoral
IFF or AML risk assessments, exchange of information, Beneficial Ownershiptransparency/investigation, Legal persons beneficial ownership).
In addition, theme code Transparency, Accountability and Good Governance captures many
projects aimed at controlling corruption. As this will miss many projects and activities, it
may be supplemented by a keyword search. Keywords (including partial words) include:
Corrupt, Launder, Fraud, Arbitrary, Discretion, Asset declaration, Income declaration,
Assets declaration, Declarations of income, Declarations of asset, Bribe, Collusion, Conflictof interest, Conflict-of-interest, Conflicts of interests, Crime, Ethic, Ghost, Gift, Illicit,
Integrity, Misconduct, Mismanagement, Misuse, Nepotism, Patronage, Red flag, State
capture, Whistle Blowers, and Transparency may also be used, although they require
manual verification as they can lead to false positives.
For manual checks for the number of IDA countries supported in undertaking policy actions
that tackle corruption, money laundering, and/or tax evasion to reduce IFFs, the essential
criterion is that the support is aimed specifically at those causes. For example,
administrative simplification and civil service reform can be aimed in part at controlling
corruption, or may be wholly aimed at other purposes, such as business-friendly
environment and efficient public administration. For the purpose of tracking this IDA
commitment, the criterion is whether or not the supported policy reforms are aimed atcontrolling corruption.
The methodology for IDA 20 does not differ from IDA19.
Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

Reporting from TTLs corroborated by Operation portal, including progress reviews and TFs
annual reporting to donors.

C. Key counterparts
Contributing
PGs/GPs/Regions
D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

218

Limitations andExceptions

As previously indicated, data on completion may be underestimated when country activities
are included in a regional or global trust fund and do not have a specific code different fromthe main TF or EFO code. As a result, accuracy will result from data collection from theTTLs, including progress review documents.
In addition, as noted above, search by keywords and by themes will have false positives andfalse negatives. These will be addressed through manual verification of project documents.

Date methodology
agreed/updated

NA

219

Client feedback on WBG on responsiveness and staff accessibility
A. Overview
Indicator name

Client feedback on WBG on responsiveness and staff accessibility (average rating
scale: 1-10)

Definition(as it should appear on thedigital IDA RMS card)

Mean score for the answer provided by World Bank Group clients in IDA countries to thefollowing questions from the annual World Bank Group Country Opinion Survey (COS)
Program: “To what extent is the World Bank Group an effective development partner inyour country, in terms of (i) responsiveness to needs, and (ii) access to WBG staff andexperts?” (Based on a 10-point scale with 1 being “to no degree at all”, and 10 being “to avery significant degree”). World Bank Group clients in IDA countries are defined as
respondents who report in the COS that they collaborate with the World Bank (IDA). The
indicator reflects the current fiscal year ratings (FY23), that is, for about a third of all WorldBank Group client countries surveyed during each three-year cycle. Data are reported for
IDA eligible countries, including blend countries, in a reporting fiscal year.

Tier type

Three

IDA20 Cycle Timeline

FY23-25

Relevant SDG

NA

IDA20 Expected
range/value

7

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Average rating scale: 1-10
☒ FCS
☐ Females

Calculation method

Annually
The indicator is calculated as follows:1.
2.

Data Calculation Method
3.

4.

The data for respondents from IDA/Blend countries surveyed in the fiscal year isaggregated across all countries.
Only those respondents who answered Yes to the question, “Currently, do you
professionally collaborate/work with the World Bank Group (IBRD/IDA, IFC,
MIGA, ICSID) in your country?” AND answered “World Bank (IDA)” to thequestion, “Which, if any, of the following agencies of the World Bank Group do
you primarily collaborate/work with in ____?” are selected for analysis.
For each respondent selected, the mean rating for the questions, “To what extent is
the World Bank Group an effective development partner in your country, in termsof responsiveness to needs?” and “To what extent is the World Bank Group aneffective development partner in your country, in terms of access to WBG staff andexperts?” is then calculated (excluding any Don’t Know responses).
The mean rating across all selected respondents for this index of two questions isthen calculated. This mean rating provides the defined overall indicator.

220

5.

For the FCS disaggregation, only those respondents selected in #2 that are also
from FCS-designated countries are selected for analysis. The mean rating acrossthese selected respondents for this index of two questions (from #3) is thencalculated. This mean rating provides the defined FCS-disaggregated indicator.

Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)Country Opinion Surveys completed in the fiscal year in countries with IDA or Blend
financing.

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

Although the Country Opinion Survey program aims to survey a third of all World Bank
Group client countries each fiscal year, the deployment of the surveys is contingent upon
approval and cooperation of the region and the individual country team. The survey sample
is comprised of approximately 80% from country team databases of contacts andapproximately 20% from the independent fielding agency (which most often provides
supplemental contacts from outside the government). The response rate for Country Opinion
Surveys is approximately 50%.

Date methodology
agreed/updated

August 2023

221

Client feedback on WBG on collaboration with other donors
A. Overview
Indicator name

Client feedback on WBG on collaboration with other donors (average rating scale: 110)

Definition(as it should appear on thedigital IDA RMS card)

Mean score for the answer provided by World Bank Group clients in IDA countries to thequestion from the annual World Bank Group Country Opinion Survey (COS) Program: “To
what extent is the World Bank Group an effective development partner in your country, interms of collaboration with other donors and development partners?” (Based on a 10-point
scale with 1 being “to no degree at all”, and 10 being “to a very significant degree”). WorldBank Group clients in IDA countries are defined as respondents who report in the COS thatthey collaborate with the World Bank (IDA). The indicator reflects the current fiscal year
ratings (FY23), that is, for about a third of all World Bank Group client countries surveyed
during each three-year cycle. Data are reported for IDA eligible countries, including blend
countries, in a reporting fiscal year.

Tier type

Three

IDA20 Cycle Timeline

FY23-25

Relevant SDG

SDG 17.16: Enhance the global partnership for sustainable development, complemented bymulti-stakeholder partnerships that mobilize and share knowledge, expertise, technology,
and financial resources, to support the achievement of the sustainable development goals inall countries, in particular developing countries.

IDA20 Expected
range/value

8

Included in IDA19

Yes

B. Methodology
Unit of Measure
Reporting Disaggregation(if relevant)Internal Data Update
Frequency

Average rating scale: 1-10
☒ FCS
☐ Females

Calculation method

Annually
The indicator is calculated as follows:1.
2.

Data Calculation Method

3.

The data for respondents from IDA/Blend countries surveyed in the fiscal year isaggregated across all countries.
Only those respondents who answered Yes to the question, “Currently, do you
professionally collaborate/work with the World Bank Group (IBRD/IDA, IFC,
MIGA, ICSID) in your country?” AND answered “World Bank (IDA)” to thequestion, “Which, if any, of the following agencies of the World Bank Group do
you primarily collaborate/work with in ____?” are selected for analysis.
The mean rating for the question, “To what extent is the World Bank Group aneffective development partner in your country, in terms of collaboration with other
donors and development partners?” is then calculated (excluding anyone who
selected Don’t Know as a response). This mean rating provides the defined overall

222

4.

indicator.
For the FCS disaggregation, only those respondents selected in #2 that are also
from FCS-designated countries are selected for analysis. The mean rating for thequestion, “To what extent is the World Bank Group an effective development
partner in your country, in terms of collaboration with other donors anddevelopment partners?” is then calculated (excluding anyone who selected Don’t
Know as a response). This mean rating provides the defined FCS-disaggregatedindicator.

Note:
1.

2.

Data Source(s)[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)Country Opinion Surveys completed in the fiscal year in countries with IDA or Blend
financing.

C. Key counterparts
Contributing
PGs/GPs/Regions

NA

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

Although the Country Opinion Survey program aims to survey a third of all World Bank
Group client countries each fiscal year, the deployment of the surveys is contingent upon
approval and cooperation of the region and the individual country team. The survey sample
is comprised of approximately 80% from country team databases of contacts andapproximately 20% from the independent fielding agency (which most often provides
supplemental contacts from outside the government). The response rate for Country Opinion
Surveys is approximately 50%.

Date methodology
agreed/updated

August 2023

223

Projects with beneficiary feedback at design
A. Overview
Indicator name

Projects with beneficiary feedback at design (%)

Definition(as it should appear on thedigital IDA RMS card)

Share of IDA Investment Project Financing operations for which at least one citizen
engagement indicator is included in the results framework of the World Bank Project
Appraisal Document.

Tier type

Three

IDA20 Cycle Timeline

FY23-25

Relevant SDG

NA

IDA20 Expected
range/value

100%

Included in IDA19

Yes

B. Methodology
Unit of Measure

Percentage (%)☒ FCS(Number of IDA IPF operations with at least
one citizen engagement indicator—i.e.,
Beneficiary Feedback Indicator—in the
results framework of the World Bank Project
Appraisal Document) / (Active IDA IPF
operations) * 100

Reporting Disaggregation(if relevant)☐ FemalesInternal Data Update
Frequency

Internally the indicator is monitored and reported quarterly with the support of Regional CE
Focal Points and OPCS verification.

Data Calculation Method17

Calculation method

1) Only monitor and report on IDA IPFs that are currently “active” in the Operations
Portal (excluding projects that are closed, dropped, or on hold17)2) According to the CE Strategic Framework and the Environmental Stakeholder
Framework (ESF), the definitions of the three terms are as follows:
Citizens: ultimate client of government, development institutions, and private
sector interventions in a country. The term citizen is understood in the broad
sense of referring to all people in a society or country in an inclusive and nondiscriminatory way.
Beneficiaries: the subset of citizens directly targeted by and expected tobenefit from a WB-supported project or program. They can include
individuals, groups, associations, or organizations, and may (or may not)belong to the public or private sectors, and may represent a variety of interests.
Stakeholders: people who will be informed and consulted about the project
including individuals, groups, or communities that (i) are affected or likely to

Regional CE Focal Points can reach out to CESA GSG to request exemption from CE assessment for projects forwhich implementation is on hold (e.g. often due to political factors).

224

be affected by the project (project-affected parties) and (ii) may have aninterest in the project (other interested parties).
3) The following criteria help determine whether an indicator is considered abeneficiary feedback indicator:- The indicator clearly captures feedback from citizens or monitors the degree of
involvement in decision-making that citizens have in the design,
implementation, or oversight of projects. An indicator that captures feedback
from beneficiaries should report whether/what actions (if any) were taken
based on that feedback – this is called closing the feedback loop.
- The indicator reports on feedback from (or the engagement of) ultimate
beneficiaries (i.e., citizens, civil society organizations, private sector).
4) Additional Financings are also counted.
5) In the Operations Portal, the “CE tag” is available, among the cross-cutting theme
tags, to mark indicators project teams designated for meeting the corporate
commitment for citizen engagement.
Note:
1.

2.

[For country-based indicators (e.g., Number of IDA countries supported)] The
indicator should include all countries that are IDA-eligible (both IDA-only andblend). See: https://ida.worldbank.org/en/about/borrowing-countries[For project-based indicators (e.g., People provided with…)] The indicator should
include all the projects that are only-IDA financier type, blend-financier type(including IDA-financing), and Trust-fund financier type (including IDAfinancing)

Citizen Engagement Database (FURL: CEDB)
Data Source(s)For reference purposes, Operations Portal
C. Key counterparts

Contributing
PGs/GPs/Regions

All regions have Regional CE Focal Points (who actively participate in updating the statusof projects and agree/disagreeing with the CE compliance assessments conducted by CESA
GSG.
Not all but most GPs have GP CE focal Points who do not actively participate in theverification process but do provide advice on matters that require GP expertise whenrequested by regional FPs, project teams, or the CESA GSG. List of Regional and GP
Citizen Engagement Focal Points are available on the internal website of CESA GSG.

D. Additional information
Harmonization withother corporate reporting
mechanisms:

NA

Limitations andExceptions

NA

Date methodology
agreed/updated

The Strategic Framework for Mainstreaming Citizen Engagement in World Bank GroupOperations, which is the governing document of the Bank’s monitoring and reporting on
citizen engagement, was published in 2014 and the monitoring and reporting began in
FY15, with FY14 data being the baseline.

225