ai4data/datause-dataset-rechunked huggingface dataset:
Power shortage data are reported annually by distribution companies (DISCO) to NEPRA and are published in the DISCO Performance Evaluation Report. The latest evaluation report includes shortage data at the DISCO level from year 2010-2011 to year 2014-2015.

Source: DISCO Performance Evaluation Report 2014-2015 by NEPRA.
Notes: SAIFI is the average number of interruptions that a customer experiences in a year.
Specifically, SPAIFI is calculated as the total annual number of consumer supply
interruptions divided by the total number of consumers that the distribution company
serves in any a given year. For the purposes of illustration, the index has been
transformed using the inverse hyperbolic sine.

The second measure, the System Average Interruption Duration Index (SAIDI), captures the outage duration (in minutes) that an average customer experiences in a year.

- (2016). Enterprise Surveys. Available http://www.enterprisesurveys.org,
Accessed June 10, 2017.


13



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### **Figures**

**Figure 1 Power outages and their impact**

Source: World Bank Enterprise Survey for Pakistan (2013)
Beneficiary assessments conducted in the southern provinces highlighted that women-headed households faced compounded barriers to accessing project services due to mobility constraints related to caregiving responsibilities and social norms discouraging women from attending mixed-gender community meetings. In response, the project's operational manual specifies that beneficiary assessments in subsequent years must include separate consultation sessions for women, held at times and locations identified as accessible by female community members themselves.
Markandya and Pedroso-Galinato (2007) dealt with cross-sectional data of 208 countries for 2000. The underlying production function was assumed to take a nested CES form. The results indicated a relatively high elasticity of substitutability between different types of capital; for example, loss of natural capital could be made up relatively easily by increases in human and physical capital. In addition, the paper also showed that the efficiency of all capital is significantly influenced by changes in economic indicators (trade openness and private sector investment).

Data will be gathered for "household final consumption expenditure (current US$)" as an alternative.|World Bank- World Development Indicators (WDI) database| |Wages (10-45 years old)|Wages affect schooling outcomes but the direction of influence is uncertain.

Data for the following will be gathered: `o` Public spending on education, total (% of GDP) `o` Public spending on education, total (% of government expenditure)

|Determinants|Description|References|Notes|Data Source| |---|---|---|---|---| |Income from agriculture|This variable captures the importance of agriculture to the economy.|Turner, et al. (1993); Lopez and Galinato (2005a,b); Irwin (2006)|Agriculture, value added (% of GDP)|WDI| |Demographic factors|Major determinants of land use include demographic factors such as population size and density.|Major determinants of land use include demographic factors such as population size and density.|Data needed: `o` Total population `o` Population density (people per sq.

We already have data for the following indicators of governance: `o` Government effectiveness - perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies
`o` Government effectiveness - perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies.
market access Level two 0.2065*** (0.0607) Level three 0.2358** (0.0788) Level four 0.3559*** (0.0769) Distance to Zone city (Km) 0.0022*** (0.0006) Market accessibility indicator -0.0792* (0.0330) Observations 742 737 742 Chi-square test 0.0000 0.0000 0.0000 R2 0.2517 0.2435 0.2128 Source: World Bank Staff based on SESRE 2023. Standard errors in parentheses. All estimates are controlled for regions. +p<0.10, * p<0.05, ** p<0.01, *** p<0.001 Annexes 120 Table D.17: Proximity and market accessibility effects on engagement in service sector: logit model Variables Proximity Market access Model I Model II Individual feature Male -0.2151*** -0.2199*** -0.2153*** (0.0309) (0.0304) (0.0312) Age 0.0368*** 0.0331*** 0.0340*** (0.0089) (0.0089) (0.0096) Age squared -0.0005*** -0.0004*** -0.0004*** (0.0001) (0.0001) (0.0001) Some primary 0.1561*** 0.1636*** 0.1683*** (0.0333) (0.0334) (0.0344) Household feature HH size: member age [15,29] 0.0217+ 0.0226+ 0.0248* (0.0121) (0.0117) (0.0119) HH size: member age (30,44] -0.0664*** -0.0657**
0.0217+ 0.0226+ 0.0248* (0.0121) (0.0117) (0.0119) HH size: member age (30,44] -0.0664*** -0.0657*** -0.0553** (0.0197) (0.0195) (0.0205) HH size: member age (45,64] -0.0146 -0.0232 -0.0248 (0.0246) (0.0258) (0.0269) HH access electricity -0.0637 -0.0571 -0.1051+ (0.0489) (0.0499) (0.0559) Proximity and market access Level two -0.3000*** (0.0713) Level three -0.3988*** (0.0821) Level four -0.4862*** (0.0832) Distance to Zone city (Km) -0.002* (0.0008) Market accessibility indicator 0.0897** (0.0307) Observations 787 782 787 Chi-square test 0.0000 0.0000
UNHCR regularly publishes statistical reports, including “ Global Trends ”, “ Mid-Year Trends ”, “ Asylum Trends ” and “ Statistical Yearbook ”. Additionally, UNHCR hosts interagency information sharing portals for significant emergencies. 87 These portals provide data on populations of concern at regional and country levels, including time series data, demographics, location and accommodation information. 88 Eurostat compiles and publishes data on asylum (applications and decisions) and managed migration in European Union member countries. Countries and national and international NGOs also publish these statistics, based on sources of various completeness, quality and timeliness (UNSD 2014). There are sometimes substantial inconsistencies between the numbers published by different organizations for the same country, including high-income countries with good statistical systems, usually due to differences in definitions, times and statistical methods, including the mixing of data on flows and stocks (UNSD 2014). There are several challenges associated with the compilation of data on asylum-seekers and refugees.
(24 percent) with higher livestock ownership relative to other domains. Somalis are also more likely to work for private households, including household services, construction, and agricultural work. 0 10 20 30 40 50 60 70 80 90 100 Camp Hosts Camp Refugees Employed Unemployed, searching Unemployed, not searching Inactive not in school Inactive in school Percent Figure 3.2: Work status Source: World Bank Staff based on SESRE 2023. Table 3.1: Labor force statistics Camp- Hosts Camp- Refugees Labor force participation rate (strict) 52% 31% Unemployment rate (strict) 7% 21% Labor force participation rate (relaxed) 57% 43% Unemployment (relaxed) 15% 43% Employment-to-population ratio 48% 25% Source: World Bank Staff based on SESRE 2023. Note: Labor force participation ratio is the share of working-age people who are engaged in the labor market, either employed or unemployed. Unemployment is the share of people participating in the labor force who are not employed. The “relaxed” definition of labor force participation includes anyone who is available to work. The “strict” definition of labor force participation includes only those who are available to work and also actively searching for work. Employment-to- population ratio is the share of working-age people who are employed. 41 In Ethiopia, in-camp
The assumption of perfect implementation, however, is quite strong as interviewers have shown a preference for selecting respondents willing to participate in the survey (Alt, 1991), and a number of other studies found that data collected with random walk designs exhibit differences from known population statistics on gender, age, education, household size, and marital status (Bien et al. 1997, Hoffmeyer ‐ Zlotnick 2003, Blohm 2006, Eckman & Koch 2016). Probabilities of selection inherently cannot be calculated in a random walk sample design as no information is collected on how many structures are in the camp, or how likely it was that a given structure was the xth structure along any path. Random walk must then assume all structures have the same selection probability, implying constant sampling weights. Therefore, the only component of the weights for the random walk is the sub-sampling of households within a selected structure: 𝑤𝑤𝑖𝑖 ′ = 𝑁𝑁𝑗𝑗𝑗𝑗 𝑖𝑖. 2. 6. Comparison of Methods As mentioned above, stratified cluster samples with the canvassing of selected clusters is the most common sample design used to collect official socioeconomic statistics in the developing world, but in
**Component 2 Update: Infrastructure Works**

Civil works under 12 of the 14 contracted sites are progressing on schedule. ESMF compliance audits conducted in March found that all sites met the LMP requirements for worker accommodation and wage payment, but two sites required corrective action on dust and noise management during construction. GIS-based photographic tracking of construction progress — using geotagged photos uploaded by site engineers — has been added to the activity monitoring dashboard, providing real-time visual verification of works completion to supplement the progress certificates issued by the supervising engineer.
12 One could think of Jordan ’ s growth of local supply of public basic and secondary schools as a progressive public investment in human capital that increases the human capital production for children of marginal parents in terms of income and educational attainment. Those are parents who would have chosen higher investment in the human capital of their offspring, but were constrained by the limited supply of schools in their subdistricts of residence and could not afford to send their children to more distant schools outside their jurisdiction or to provide them with homeschooling. However, the increase in public schools is expected to have less of an effect on richer or more educated parents, who are expected to provide education to their children regardless of the availability of schools in their subdistricts either by sending their children to distant schools or through homeschooling. On average, however, the increase in the local supply of public schools is expected to reduce the intergenerational correlation of educational attainment or enhance intergenerational educational mobility. III. DATA Two new and unique data sources are employed in the empirical analysis. First, the Jordan Labor Market Panel Survey of 2010, carried out by the Economic Research Forum in cooperation with the Jordanian Department of Statistics, is a rich source of information on all aspects of the Jordanian labor market (JLMPS 2010).
assemble annual observations as follows for each grid square: the first 40 from the CRU

scores). We do this for both future periods, as well as for the historical CRU data (here

of rainfall and temperature for the past (from the benchmark CRU series that we have

table presents average R [2] scores for the bivariate relationships between the CRU
**Appendix C: Robustness to DHS Cluster Geocoding Uncertainty**

The standard DHS jitter algorithm displaces cluster centroids by up to 5 km (urban) or 10 km (rural). To assess sensitivity of our results to this measurement error, we implement a simulation in which each DHS cluster centroid is displaced 1,000 times by a random draw from the DHS jitter distribution, and the treatment indicator is recomputed after each displacement. We report the median coefficient and the 5th and 95th percentile bounds across simulations. The simulated bounds are narrow relative to the estimated confidence intervals, indicating that DHS cluster geocoding uncertainty does not substantially bias our estimates.
0 10 20 30 40 50 60 70 80 90 100 Percent Worse Same Better Figure 5.8: Perceived changes in household living standards Source: World Bank Staff based on SESRE 2023. Note: The survey asks how the household living standard has changed compared to last year and the last five years. a. Last 5 years b. Last 1 year Refugees’ Aspirations 48 scale44 gap between refugees and hosts is higher for in-camp refugees, the gap is relatively narrower for Addis Ababa refugees. The average food insecurity scale for in-camp refugees is “8” and for their hosts it is “4” out of 10; that is, in- camp refugee households experienced about eight food insecurity events while host households experienced about 4 in the past year. Consistent with other welfare indicators discussed, food insecurity tends to be more severe among in-camp refugees than their hosts or OCP refugees. In-camp refugees have less diverse diets and poor food consumption status compared to their hosts. The average household dietary diversity score—the number of food groups consumed out of twelve—is 7.5 for hosts and 6.5 for refugees (Figure 5.10a). Overall, the average dietary diversity score is also lower for in-camp refugees than their hosts. The
The model includes ϐixed effects for grade, school, and language spoken. 14 The results are presented in Table 3. We then narrow our focus to foreign students who joined Italian schools after February 2022, speciϐically comparing Ukrainian refugees to other newly arrived foreign students. This approach allows us to examine how Ukrainian refugees compare to other foreign students who entered the education system around the same time. By restricting the sample to these two categories of students, we estimate the following regression: 𝑌𝑌𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 = 𝛽𝛽0 𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑒𝑒𝑖𝑖 + 𝐸𝐸𝐸𝐸𝐸𝐸𝑆𝑆𝑖𝑖 + 𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑟𝑟𝑖𝑖 + 𝑓𝑓𝑔𝑔 + 𝑓𝑓𝑠𝑠 + 𝑓𝑓𝑙𝑙 + 𝜖𝜖𝑖𝑖𝑖𝑖𝑖𝑖 (2), with variables as deϐined in (1), and results presented in Table 4. Our analysis also aims to explore potential mechanisms that could explain results derived from equations (1) and (2). Using the administrative data, we investigate whether being placed in a smaller class inϐluences school achievement in the sample of Ukrainian refugees. The results are presented in Table 5. We then draw on ϐindings from the survey data to unpack and analyze how Ukrainian refugees feel in Italy, the challenges they face, and their aspirations. 4. Results 4. 1. Integration challenges faced by Ukrainian refugees in Italy Low enrollment and substantial dropout rates At the end of the 2021-2022 school year, the enrollment rate of Ukrainian refugee children in Italian schools was low. In the months following Russia ’ s full-scale invasion of Ukraine in 2022, 3, 320 Ukrainian refugees were enrolled into Italian secondary schools. This ϐigure constitutes 24 % of the 14, 106 Ukrainian refugees aged between 11 and 18 years who sought temporary protection as of 14 This variable is included to account for the potentially greater ease of learning experienced by students who speak languages that are considered closer to Italian.
approximated by wealth measured by the EMDHS asset index; and e)mothers' education. Note that the alternative

The asterisks indicate the significance level: *** p<0.01, ** p<0.05, * p<0.1. Standard errors in parentheses. Regressions take sample
design and household weights into account by using Stata's svy command. Data: EMDHS 2014.

2007 Census. The 2007 census has two formats - a long and a short format. The long format is richer in terms of

The Ethiopian census has both a short and a long form, and to increase model fit, the models use the long

observed in Ethiopia before, based on other data sets [30]. SAE results in addition to these variables are highly
The LMP appended to the ESMF specifies that all contractors must submit workforce management plans prior to mobilization, detailing recruitment procedures, wage payment schedules, and the mechanism through which workers may raise concerns without fear of retaliation. Contractors employing more than fifty workers are required to establish a worker accommodation standard compliant with IFC Performance Standard 2. Compliance with the LMP will be verified through quarterly site inspections conducted jointly by the PIU's E&S officer and a representative of the national labor inspectorate.
Management Information System (EMIS) (UNHCR, 2020), and a separate chapter on refugee education is included in the annual education statistics report of the MoE. The GoE included expanding primary and secondary education for refugees in the national five-year Education Sector Development Programme VI (ESDP), covering 2020 to 2025, but little progress has been made. Box 2.1: Education system for refugees in Ethiopia 0 20 40 60 Percent 80 100 Hosts Refugees Hosts Refugees Hosts Refugees In camp Addis Ababa Total No education Incomplete primary Complete primary Complete secondary Complete post-secondary Figure 2.7: Education level (18 years and above) Source: World Bank Staff based on SESRE 2023. 0 20 40 60 80 100 Hosts Refugees Hosts Refugees Hosts Refugees In camp Addis Ababa Total No education Incomplete primary Complete primary Complete secondary Complete post-secondary Percent Figure 2.8: Youth (15 to 24) education level Source: World Bank Staff based on SESRE 2023. Sociodemographic Profile 14 OCP refugees attended education outside of Ethiopia and have relatively better educational attainment. One reason why OCP refugees have higher educational attainment compared to other refugees (especially other Eritreans) could be related to being relatively better off in their countries of origin (qualification for OCP requires having
Protection monitoring data from the last four cycles indicate that freedom of movement restrictions remain the most frequently reported protection incident, accounting for 34 percent of cases. The Protection Monitoring Tool was updated in cycle 5 to include an additional question distinguishing between formal government-imposed restrictions and informal social barriers to movement, following a recommendation from the protection analysis technical advisor. This change improved the actionability of protection monitoring findings for both advocacy and programmatic response teams.
the World Bank's Poverty and Inequality Platform (PIP). PIP is managed jointly by the Data and

Research Groups in the World Bank's Development Economics Division. It reports both poverty

measures and inequality measures, including the Gini Index for 168 countries from 1968 to 2022. The

Gini index is based on primary household survey data obtained from government statistical agencies

alternative dataset that provides inequality measures. Specifically, we use the Standardized World

Income Inequality Database (SWIID). [5] The SWIID maximizes the comparability of available income

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Income Study database.

Data on natural disasters is from the EM-DAT database maintained by the Centre for Research
Individual characteristics Age, sex, education, language skill, years in exile SESRE Household characteristics Gender of household head, household size, head education level, access to electricity, productive asset ownership, food insecurity experience SESRE Community characteristics Community economic development status Predominant land cover in the community SESRE Local Factors Remoteness Distance to towns and cities, distance to the nearest international border Ethiopian shapefile and Refugee geospatial from ESS Local labor market LFPR, unemployment rate, the share of wage employment, the share of employment by economic sector LMS, 2021 Market access Market accessibility index Ethiopia transport network layer, 2020 (ERA) & gridded population (GPWv4) Notes: For logistic regression, we assume local factors are exogenous in the model as refugees do not select their location. Since refugees’ residential location is not self-selected, they do not choose their respective camps to maximize their utility. Instead, they come across the border and are either assigned to camps close to where they crossed or a new camp is established. Our model compares refugee employment status by local factors in the hosting Zones and community: where subscripts denote : individual and : camp. refers to local factors; represents personal and presents household characteristics; refers to the characteristics of
These may include skills on how to write a CV, prepare for job interviews, business and entrepreneurial skills to start a business, etc. In this regard, the mechanism for improving social cohesion values appears to have come from inter-community volunteering activities, rather than improvements in soft skills. (c) IMPACTS ON LABOR MARKET OUTCOMES While the NVSP was designed primarily to improve social cohesion values among participating Lebanese youth, it was also hoped that engaging them in volunteering activities, coupled with soft skills training, would enhance their employability and thus increase their chances of employment. At baseline, half of the selected and non-selected volunteers were active and searching for a job. Among them, 49 percent reported being unemployed, 31 percent wage employed, 13 percent employed in unpaid jobs, and 7 percent self-employed (see table 1). Those active volunteers were older in age than the rest of volunteers who reported being inactive in the study ’ s sample (with an average age of 21 and closer to labor market insertion). One year later, it appears that many of 19 Our interpretation that offered soft skills are likely too basic for this pool of volunteers is provided given the scale that we used in the questionnaire to test their knowledge on soft skills. We cannot rule out the possibility that had we used a different scale, we might have found an impact, either negative or positive.
decreased satisfaction. For example, using the German Socio-Economic Panel Survey (SOEP),

Two studies that use the German SOEP data (D'Ambrosio and Frick, 2007 and 2012) find that

using a set of European panel surveys concludes that absolute income is more important than

Current global counts rely on combining each country's total food balance with information on distribution patterns from household consumption expenditure surveys. Recent research has advocated for calculating hunger numbers directly from these same surveys.

details about how household surveys are designed and
how these data are then used. Using a survey experiment
in Tanzania, this study finds great fragility in hunger
counts stemming from alternative survey designs. As a
consequence, comparable and valid hunger numbers will
be lacking until more effort is made to either harmonize
survey designs or better understand the consequences of
survey design variation.
Nassar, R., J. Mastrogiacomo, W. Bateman-Hemphill et al. 2021. Advances in quantifying
power plant CO2 emissions with OCO-2. Remote Sensing of Environment. 264: 112579.

Nordhaus, W., A. Azam et al. 2006. The G-Econ Database on Gridded Output: Methods and
Data. Yale University.

Ye, X., T. Lauvaux, E. Kort, T. Oda, S. Feng, J. Lin, E. Yang and D. Wu. 2020. Constraining
fossil fuel CO2 emissions from urban area using OCO-2 observations of total column CO2. JGR
Atmospheres, 125(8).

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**Appendix: Mobilizing OCO-2 Data for the Stakeholder Community**

In this paper, we have shown that a relatively simple tracking model can provide useful information
about changes in local CO2 concentration anomalies for areas of interest. However, we recognize that
most stakeholders do not have the requisite hardware and software for mobilizing the OCO-2 data
directly. Accordingly, the World Bank's Development Economics Vice Presidency (DEC) has
established an open web facility with the following features. We believe that it will contribute to the
global effort to reduce CO2 emissions.