rafmacalaba/data-use-mentions-extended huggingface dataset:
<!-- Start of picture text --> Figure 4: Government education spending has grown rapidly in East Asia and the Pacific but has<br>not kept pace with economic growth in the Middle East and North Africa<br>a. Public education spending b. Public education spending as a percentage of<br>(Billions, constant 2015 PPP $) GDP<br>8<br>60 EAP<br>1998–2001 2002–05 2006–09<br>2010–13 2014–17<br>6<br>40<br>SAR<br>ECA<br>4<br>20 LCR<br>MNA<br>2<br>AFR<br>0<br>0<br>AFR ECA LCR SAR EAP MNA<br>1998– 2001 2002–05 2006–09 2010–13 2014–17<br><!-- End of picture text --> _Source:_ World Bank calculations using UIS and IMF online databases. _Note:_ Statistics on public education spending are averages for countries in each region that have data available for at least one year in the four-year period. World Bank regional classifications are used to group countries as follows: AFR = Africa, ECA = Europe and Central Asia, LCR = Latin America and Caribbean, EAP = East Asia and the Pacific, MNA = Middle East and North Africa, and SAR = South Asia.

Even as all regions have registered growth in government spending on education, the share of GDP they **–** have allocated to education has varied widely. In 1998 2001, Africa and South Asia devoted a similar share **–** of GDP to public education spending. However, by 2014 17, the percentage for Africa exceeded that for South Asia by 0.6 percentage point. Latin America and the Caribbean has also increased considerably the share of GDP used for public education spending since the late 1990s (Figure
although exports fell sharply (by 9.1%), imports fell even more (by 12.6%), so the current account played a strong role in moderating the drop in GDP.

Real government spending _on goods and services_ rose by 0.9% in 2009, but Figure 1 shows that the contribution to economic growth was rather modest, despite the stimulus programs of 2009 and 2010. However, this understates the potential role of government in maintaining GDP, since it also transfers resources to households directly, thereby helping to maintain private consumption spending.

<!-- Start of picture text --> 10%<br>8%<br>6%<br>4%<br>2%<br>0%<br>-2%<br>-4%<br>-6%<br>-8%<br>2006 2007 2008 2009 2010 2011<br>C I G X-IM GDP World GDP<br>% change p.a. (lines) or decomposition (bars)<br><!-- End of picture text -->

**Figure 1.  Decomposition of GDP growth into its macroeconomic components** Source: Data reported by Bank of Thailand; IMF (2012).  Note: C = consumer spending; I = investment spending; G = government spending on goods and services; X-IM = net exports.

The annual data that are summarized in Figure 1 are not fine-grained enough to allow us to date the onset of recession very accurately. Figure 2 presents quarterly data on real GDP growth (at annualized rates). GDP growth was negative for four quarters, starting in the last quarter of 2008. Compared to the crisis of 1997-1998, this recent downturn was substantially smaller and shorter.

One of the ways in which the global economic slowdown was transmitted to Thailand was through a dramatic reduction in the dollar value of merchandise exports, which dropped from US$170 billion in 2008 to
the primary source of energy for most households and the demand for cereals is expected to grow in the coming decades (OECD, 2016).

Table 1 provides descriptive statistics for the GAEZ dataset, showing that despite the average harvested area of rain-fed croplands being higher than that of irrigated croplands (100 hectares per grid cell versus 20 hectares per grid cell), the mean production and yield of irrigated croplands are relatively higher. This finding suggests production and productivity gains are possible through irrigation, which is also reflected in larger production gaps for rain-fed croplands than for irrigated croplands.

> 3Aquifer productivity, measured in liters per second, refers to the ability of an aquifer to sustain a certain level of groundwater extraction through a well or a bore. It can be thought of as the water yielded from a well or bore that sits on a certain aquifer.

> 4Note the irrigation landscapes of 2000 and 2010 are very similar for SSA, and thus, we opt to work with cross-sectional data for the latest year, which has a slightly higher rate of irrigation.

6
in Business Services.** Our

estimates of the ad valorem equivalents of discriminatory barriers against foreign providers of services in the services sectors are taken from Jafari and Tarr (2015) and shown in table 3. The Jafari and Tarr estimates are based on the World Bank database of discriminatory regulatory barriers in 11 services sectors in 103 countries; that database is described in Borchert, Gootiiz and Mattoo (2014). Borchert _et al_ . produced “Services Trade Restrictiveness Indices,” but did not transform their indices of the regulatory regimes into ad valorem equivalents. The Jafari and Tarr methodology uses the World Bank database for an assessment of the regulatory regimes, but builds on a series of studies, supported by the Australian Productivity Commission, to convert assessments of services regulatory regimes into ad valorem equivalents for all 11 sectors in 103 countries. Most of the Australian studies are published in Findlay and Warren (2000). Jafari and Tarr define mappings from the World Bank database to the scoring matrices of the Australian 22
# **2.3 Data**

Data collection began in November 2012 and lasted until September 2015 (Table 1). For each phase, three rounds of data were collected: baseline data at the start of the school year; midline data in the middle; and endline data at the end of the school year. Phase 1 baseline data were collected in November 2012February 2013, midline in August-September 2013, and endline in November 2013. Phase 2 data were collected at corresponding times in 2014. At baseline and endline, students were tested and teachers and head-teachers were surveyed. At midline, attendance data were collected for both students and teachers during unannounced visits. Teachers were observed teaching a class during the midline visits and their behaviors recorded along a number of dimensions using an instrument with 21 items across the following domains: how teachers interact with students; the materials they used during instruction; use of the blackboard; and assignment and review of homework.<sup>19</sup> After phase 2, post-endline data were collected in August-September 2015 during which the phase 2 cohort of students was re-tested only in math. Test scores used in our empirical analysis are all normalized to have a mean of 0 and a standard deviation of 1 for the control group in the relevant phase.

Around 83 percent of the schools in our sample are public schools; 92 percent are O Level only (go up to Grade 11). At time of the Phase 1 baseline (2013), around 36 percent of schools had electricity and almost all schools (99 percent) collected school fees. Around 56 percent of the schools in our sample have less than 10 permanent teachers; 11 percent have more than 20 permanent teachers. The majority of headteachers (85 percent) and teachers (79 percent) are male. Nearly 83 percent of teachers have more than secondary education and 90 percent have received some type of formal teacher training.

# **2.4 Estimation strategy**

We divide our empirical investigation into four
the private consumption component of the National Accounts Statistics (NAS), which have been diverging since the early 1990s (the 2010 to 2012 period is an exception). In levels, aggregate household consumption implied by the NSS is less than half that of the household component of the NAS. Such a gap is unusually large by international standards. The extent of bias in poverty, shared prosperity and inequality estimates depends on how much of the discrepancy is attributed to the NSS or the NAS. It is notable that changes in recall period for collecting consumption data – from URP to MRP and now MMRP – have helped close the gap between the NSS and NAS consumption aggregates.<sup>15</sup> However, some of the gap in consumption is due to errors in NAS consumption (which is determined residually in India). Choosing between the NSS and NAS is not easy 13 Using IHDS data, Gini of household income per‐capita in India is estimated to be 45.3 for 2005 and 45.9 for 2012. The income Ginis for South Africa, Brazil and Colombia are 63.4 (2011), 52.9 and 52.5 (2013), respectively. Countries with income Ginis close to India’s include Peru and Ecuador, while Russia, Turkey and United States had income Ginis between 40 and 42 (2012 or 2013) (all figures other than India’s are from the WDI database, accessed March 21, 2016).

14 See Banerjee & Piketty (2005), who find that the shares of the top 0.01 percent, 0.1 percent, and 1 percent in total income shrank substantially from the 1950s to the early to mid‐1980s but then rose again, with some impact on the overall income distribution. The estimated impact is also large enough to explain 20‐40 percent of the gap observed during the 1990s between average consumption growth in NSS data and national accounts data.

15 URP, or uniform reference period, is collected
Ethiopian Rural Sociological Survey (ERSS). This survey was also implemented by the Central Statistical Agency (CSA) of Ethiopia. However the consumption (and some other) indicators were deemed to be incomparable for the purpose of the exercise. The survey was conducted over a full year period, revisiting households three times during the year. See Central Statistical Agency and The World Bank (2013) for further details. The main three differences pertinent to this study are first, the much smaller sample size (3500 observations). Second, that the consumption module has slightly different recall periods for food consumption (7 days as opposed to 3 days in HICES) and non‐food consumption (a less detailed short‐term component, with 3 and 12 month recall). Finally, the data are not nationally representative.

Regarding the validation results overall, the full model with all interactions and a quadratic crop loss function is the preferred specification. We use this model to illustrate below for a simulation of CAT risk modelling outcomes, using the pooled 2005‐2011 model as the training data.

# **6. Application of the derived vulnerability relationships within a probabilistic catastrophe risk modelling framework**

The overall purpose of the exercise presented in this paper is to determine whether valid general form vulnerability functions for poverty outcomes can be applied within a probabilistic catastrophe risk modelling framework. Sections 3 to 5 above describe the outcome of the exercise. The purpose of this section is to demonstrate how the derived functions would be applied in practice, and to propose future work on the basis of the findings of the paper.

## a. **Outcomes for consumption simulation exercise**

In the absence of a probabilistic hazard model for rainfall variability in Ethiopia at the resolution required, and compatible with the LEAP protocol, we have produced illustrative examples based on the results from the regression model.

26
71|0.12|0.08|0.40|
|Size|159,224|55,580|39,825|464,960|11,588|34,815|108,933|80,534|
|Reference Period||2/2010<br>–|2012<sup>(3)</sup>|7/2011-|9/2009–|2010<sup>(6)</sup>|7/2010-|7/2012<br>–|
|(Survey)|4/2011-<br>8/2012<sup>(1)</sup>|1/2011<sup>(2)</sup>||6/2012<sup>(4)</sup>|9/2010<sup>(5)</sup>||6/2011<sup>(7)</sup>|6/2013<sup>(8)</sup>|

Source: Authors’ own estimates based on South Asia Harmonized Micro Dataset (SARMD).

<mark>(1)National Risk and Vulnerability Assessment 2011 - 2012, Afghanistan Living Conditions Survey Report. Helmand and Khost provinces were excluded from consumption information</mark> (2) Statistical Division of the Ministry of Planning (2011) Bangladesh Household Income and Expenditures Survey: Key Findings and Report. (3) Asian Development Bank (2013) Bhutan Living Standard Survey 2012 report.

Design and Estimation Procedure of NSS 68th Round) Expenditures Survey 2009/10. Findings (6) Central Bureau of Statistics (2011) Nepal Living Standard Survey – highlights (7) Statistic Division of the Government of Pakistan - PSLM report (8) Sri Lanka Department of Census and Statistics (2015) Household Income and Expenditures Survey (9) Atolls are considered rural areas.

(10) There is a further 5% in the Estate sector
8 online or broadcast learning compared to 70 percent of primary students and more than 80 percent of upper-secondary students (Nugroho et al., 2020).

# **Table 1**

_Countries are less likely to provide distance learning options for ECE across all media_

|Percentage<br>of<br>countries<br>offering distance learning by<br>medium and level|ECE|Primary|Lower<br>Secondary|Upper<br>Secondary|
|---|---|---|---|---|
|Radio|28|46|36|34|
|TV|42|61|66|65|
|Online|51|81|84|86|
|Paper-Based|40|59|55|53|

_Source_ : Authors’ calculations of UNESCO et al., 2020 data Unlike older students, young children typically cannot participate in distance learning without assistance from a parent or other caregiver (Gayatri, 2020). Equally concerning, less than half of the countries in the aforementioned survey reported providing guidance or materials to help parents and caregivers support young children’s learning at home during school closures (Nugroho et al., 2020). Countries are also less likely to report having a plan for nation-wide reopening of ECE compared to primary and secondary education (UNESCO et al., 2020a).

The COVID-19 pandemic is expected to threaten education provision and financing, not only through the immediate effects of school closures, but also through the longer-term impacts of the pandemic-induced economic recession (World Bank, 2020b). During previous economic crises, governments responded to budget shortfalls by reducing per capita student spending. Donor assistance to education has only recently recovered from the last global recession. The World Bank warns of a triple shock to education financing driven by stagnating or declining contributions from national governments, households, and international donors (Al-Samarrai et al., 2020). One in five
MLT ESPITANZLISRKORJPNFRAFIN GBR BELTWNCANISLDNKDEUBHRAUSAUTSWEHKGNLDSAUKWTUSA NORCHEARESGPIRLLUX MAC QAT 105 ETH NPL SEN IRQ PERPAN URY POL FRA<br>-2 0<br>7 8 9 10 11 12 6 7 8 9 10 11<br>Log GDP per worker in PPP (2015) Log GDP per worker in PPP<br>Average Years of Schooling<br>Years of Schooling Difference: Men - Women (2015)<br><!-- End of picture text --> _Notes_ : The left panel plots the difference in the average years of schooling in the population above 25 between men and women against log GDP per worker (in PPP terms) in 2015. The right panel plots (for countries belonging to the first to tenth deciles of the income distribution, plus the United States) average years of schooling in the population above 25, across regions (grey dots) and for the whole country (black dots), against the country’s log GDP per worker (in PPP terms). Data on years of schooling by gender is taken from Barro and Lee (2013), years of schooling by region is from IPUMS International (, n.d.), while GDP per worker is taken from version 10.0 of the Penn World Tables (Feenstra et al., 2015).

> 3Evans et al. (2021) document that in most developing countries gender gaps in education have typically widened first (as boys started going to school) and then shrunk in a second phase (as educational expansions started involving girls as well).

8
fiscal measures. In 2009, the fiscal deficit was large, accounting for over 8 percent of the gross domestic product (GDP). But Cambodia progressively reduced its fiscal deficit through increased revenue collection and prudent spending. Since 2015, Cambodia was able to substantially reduce the fiscal deficit and maintain it at less than 3 percent of the GDP (Figure 1). The deficit is often financed by foreign aid grants or development partner financing of investment projects. In 2019, government savings rose to 20 percent of GDP (or KHR 22.2 trillion) after several years of accumulation. The overall fiscal deficit is estimated to have been limited at -0.7 percent of GDP in 2019.

Figure 1: Domestic revenue and expenditure in Cambodia (% of GDP), 2009-2019 <!-- Start of picture text --> 30<br>20<br>10<br>0<br>2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019<br>Direct taxes Indirect taxes (incl. trade taxes)<br>Other revenue Domestic revenue<br>Expenditure<br>Source: MEF.<br>Percent<br><!-- End of picture text --> Note: Other revenue includes non-tax revenue, capital revenue and provincial revenue.

Revenue collection increased because of improvements in tax administration and a broadening tax base. Between 2009 and 2019, tax revenue collection of the central government increased from 9.7 percent of GDP to 20 percent. Various tax administration reforms introduced by the General Department of Taxation (GDT) and the General Department of Customs and Excises (GDCE) supported this increase. Since 2008, the GDCE rolled out the Automated System for Custom Data (ASYCUDA) and enhanced anti-smuggling measures. In 2014, the GDT introduced a shift toward a real regime system of taxation for business profits (mainly of large, incorporated and/or commercial enterprises), improved taxpayer registration and services, and improved tax auditing capacity leading to better compliance
**9 Tables**

Table 1: Summary statistics

|Variable|Observations|Municipalities|Mean|Std. Dev.|
|---|---|---|---|---|
|_Panel A: All_|||||
|Minimum deviation|4311|976|71.07|83.09|
|Min deviation _<_ 0|4311|976|0.11|.32|
|% ha receiving payment|4311|976|0.04|0.16|
|∆log ha sowed|4311|976|-.01|.47|
|Log ha sowed|4311|976|7.50|1.36|
|Log yield|4311|976|0.99|0.55|
|Log income p.c.|5879|192|8.35|0.79|
|Log expenditure p.c.|5879|192|8.36|0.76|
|Remittances|5879|192|764.36|3050.78|
|Remittances _>_ 0|5879|192|0.12|0.33|
|_Panel B: Payment = 0_|||||
|Minimum deviation|3900|943|80.24|81.28|
|Min deviation _<_ 0|3900|943|0.04|0.20|
|% ha receiving payment|3900|943|0|0|
|_Panel C: Payment = 1_|||||
|Minimum deviation|411|267|-15.85|37.23|
|Min deviation _<_ 0|411|267|.77|0.42|
|% ha receiving payment|411|267|0.45|0.32|

Note. Rainfall and agricultural variables in panel A come from the agricultural panel, which has municipal-level observations and consists of policy
the World Bank Group provided record level support of US$26 billion financing for infrastructure.<sup>31</sup> But since the 2008-09 economic crisis affected several donor countries, it is not unreasonable to expect that infrastructure aid is likely to decline in the years to come. Using panel data from 1977 to 2007, Dang, Knack, and Rogers (2009) find that banking crises in donor countries are associated with a significant decline in aid flows by 20 to 25 percent, starting to increase again only about a decade after the start of the crisis. This decline went beyond any

> 31 The World Bank Group’s lending for infrastructure was even larger in 2010, but is projected to decline going forward.

23
nature of migration is imposed by the laws in the destination countries in the Persian Gulf and East Asia where acquisition of citizenship or permanent residency is effectively impossible, irrespective of migrants’ occupation, education, nationality, or duration of stay (Wahba 2015; Fargues 2011; Fargues and De Bel-Air 2015). Valid employment contracts are typically for a fixed duration of time and tied to a specific employer who can extend the contract (Das et al. 2019). Yet, because stay inside the country is conditional on holding an employment contract, migrants cannot retire in the destination country, even if they have stayed for decades. Furthermore, low-skilled

> 4Emigration from Bangladesh is largely male-dominated. According from administrative data from the Bangladesh, Bureau of Manpower Employment and Training (BMET), women represent only 4 percent of temporary migrants from Bangladesh. Data from the World Bank Return Migrant Survey (BRMS) for Bangladesh show similar patterns. The prevalence of male labor migration is driven by the low labor-force participation of women in Bangladesh (Rahman and R. Islam 2013), combined with concentration of foreign labor demand in brawn-based occupations. In addition, there is social pressure on women to stay behind as they bear household responsibilities, and low-skilled temporary migrants are not allowed to take their families with them (Ahmed and Bossavie 2021).

6
inflows that is not reflected in balance of payments statistics.

There are particular reasons that explain why many of the surveyed countries fail to cover in their statistics the remittance transactions conducted by money transfer companies. First, in those countries money transfer companies are neither regulated nor supervised by the central bank or any other financial sector authority, as explained in Section 3. In fact, in those countries, money transfer companies are not established as “financial institutions”, but as commercial firms. As a result, they are not subject to regulatory or oversight requirements applicable to financial institutions. Although in some countries, due to recent anti-money laundering legislation, money transfer companies have been required to register themselves

> 5 According to authorities in Brazil, money transfer companies can only pay remittances through commercial banks. In Venezuela, money transfer companies are allowed to pay remittances, but most of them do it through local commercial banks, which act as agents of these companies.

8
similar firms either in the region or in other regions, and whether consumers have access to that information.

In Ethiopian markets, like most of Africa, information asymmetries are widespread. Both consumers and firms must incur search costs, and sometimes other transaction costs, to access reliable information about prices, buyers, sellers, quality of products and quantities supplied or demanded. This introduces inefficiency through costs of bargaining, time and money costs of supervision and enforcement in dealing with prices. The more widespread access to price information changes customer behavior and induces manufacturing suppliers to face intensified competition. As such, their incentives are affected in a way that reduces markups and price dispersion, while also boosting productivity as well as wages and employment. The higher TFP can be a source of faster formal job creation.

The period following the rollout of 3G broadband networks coincides with a more robust growth in Ethiopia, often putting the country among the fastest growing economies in the world. Though, the adoption of broadband technologies itself could be an outcome of this fast growth, it has also played a significant role in facilitating the growth of industries and reinforcing market competition, hence productivity, particularly in the manufacturing sector. This paper examines the impact of access to 3G broadband networks on firm productivity in Ethiopia through its impact in closing gaps and information asymmetries about market prices.

# **3. Description of Information Sources and Data**

This study uses two different sources of data in estimating the effect of expanded mobile communication access in local markets on firm performance in Ethiopia: Large and Medium Manufacturing Industries (LMMI) and Household Consumption and Expenditure Surveys (HCES). LMMI is a firm-level census panel data collected by the Ethiopian Central Statistical Agency (CSA) from 2000 to 2014. The census covers all public and private manufacturing firms that have more than 10 employees and use electricity for production. The data set provides detailed information on sales, production, wages and benefits, number of employees, cost and quantity of raw materials, types of ownership,