rafmacalaba/data-use-mentions-extended huggingface dataset:
teacher ratio; they are more likely to have electricity (which is essential for the PSI-PMI program), a library, and a computer lab; and there is a higher ratio of students in program schools taking the WASSCE exam.

To construct a reliable control group, we used extensive administrative data from 2014,<sup>8</sup> in addition to detailed information on the selection process of program schools, to select a list of non-program schools that would have been ex-ante comparable to the program schools, through propensity score matching.

Although there were 135 senior secondary schools in The Gambia in 2014, only 71 of these schools comprise our sampling frame. This is because the other schools are religious schools or follow a nonstandard curriculum. As such, students in those schools do not take the grade 12 WASSCE exam, which is our main outcome variable. This means that the total number of senior secondary schools from which we could select our control schools was 55. Table 2 provides the average differences between the pilot schools and this universe of control schools.

After applying the propensity score to match schools based on the above pretreatment variables (using nearest neighbor matching), 16 control schools were selected. The descriptive statistics on these schools and how they compare with the pilot schools are presented in Table 3. The table shows that our matching produces a comparable control group at the school level. We also used the Kolmogorov-Smirnov test to check the equality of the distribution for each variable before and after matching. Figure 1 shows the effects of matching.

Although there is one set of 16 control schools, there are two different sets of control students as stated before. This is because even in the PSI-PMI pilot schools, some students were not exposed to the program due to budgetary constraints. As a result, there were within-school control students (unexposed students in pilot schools) and between-school control students (students in schools that were not part of the pilot program). The within-school control group

> 8 In spring 2014, all
# **Figure 2A: Quantile Regression Estimates of the Differences between Countries Depending on the Total Number of Weeks of Full and Partial School Closure (UNESCO Data), EU Countries Only**

<!-- Start of picture text --> 5<br>0<br>-5<br>-10<br>-15<br>-20<br>-25<br>-30<br>1 2 3 4 5 6 7 8 9<br>Reading achievement decile<br>10 weeks closure 25 weeks closure 50 weeks closure<br>Departure from achievement trend<br><!-- End of picture text --> 12
areas within Brazil that have more job opportunities - The federal government, along with UNHCR and other civil society have been implementing a program like this since 2018.

- Provision of language training may help children to enroll in school at the grade, commensurate with their age and also promote employability of Venezuelan adults.

- Development of labor intermediation services focusing on language training, Venezuelan community outreach and specialized counsellors, who know employers where language is less a factor or looking for particular skill sets as suggested in Mazza (2017).

- Increased capacity of schools through holding di↵erent shifts can reduce overcrowding.

- Stronger labor market activation programs to include job intermediation and skills and language training to help in overcoming search barriers and matching friction.

- Continue provision of information assistance for documents issuances and enrollment to education, health and social assistance services and benefits and inform Venezuelan refugees and migrants of their social rights and guarantee access.

It should be noted here that results reported in this paper do not provide evidence of causation rather it provides insights on correlations. Another challenge this paper faces is that the population data, used to estimate the school age and working age population, is not updated regularly, which may lead to overestimation of Venezuelan population in Roraima as it is the main gateway. However, further research is needed to study the impacts of the policy already in place, like the relocation programs. Research is also needed to study how language barrier and xenophobia are a↵ecting

> 31Fundamental level refers here to grades 6 to grade 9 and primary refers to grade 5 completed.

45
). The information on anemia prevalence rate among nonpregnant women is drawn from Demographic and Health Survey 2006/7 (Table 6, p.19, DHS report (2009)).<sup>11</sup> The area characteristics including rainfall, slope, area and land quality are drawn from various GIS data sources. Appendix Table A.1 provides summary statistics for all variable included in our analysis.

> 10Many researchers in Asia found that rainfall reduces malaria incidence/prevalence by washing out the breeding grounds of Anopheles mosquito (Wijesundera, 1988.)

> 11Anemia status was determined by haemoglobin level in blood. Anyone with haemoglobin level below 7.0g/dl is classified as severely anemic, and with haemoglobin level between 7.0-10.p g/dl classified as having moderate to mild anemia.

13
is that sampling frames were different in different regions (Table 3 shows information on the sampling frames in each country). In particular, surveys in SSA countries focused on household heads. We do a number of things to deal with this concern. First our weights are to some extent able to make our sample more representative at the individual level. Second, and more importantly, in Section 4.3 we showed that stopping work measures are consistent with household-level income loss measures. The subsequent panels of Figure 8 also demonstrate that these broader measures of income are related to the WEO change in the same way as stopping work in the LAC region, but also do not show a strong relationship with the WEO change in the SSA region.

Panels (c)-(h) show the same relationship between different income components (farming, non-farming, and wage income) and suggest a similar pattern of consistent relationships in the LAC region but weak and inconsistently signed relationships in the SSA region. This suggests that HFPS-data may be picking up economic impacts that are not typically incorporated into macroeconomic projections. However, the non-representative nature of the sample in SSA may also influence the comparison between the rate of work stoppage and the WEO GDP growth projections, meaning that further investigation is needed.

One piece of additional evidence comes from firm surveys that were fielded by the World Bank, which show that firm survey measures of labor demand also do not line up well with macroeconomic projections of GDP growth. To assess labor demand from the firm side, we draw on aggregate country estimates of the share of firms that laid off workers and the share of firms that reduced wages, hours, or granted leave to employees from a recent policy research working paper (Apedo-Amah et al 2020). Figure 9 shows that these measures of labor demand are not associated with changes in the WEO’s GDP projections for 2020. This suggests that labor market impacts and ultimately other measures of household welfare during the pandemic are not fully captured by GDP projections in the
- 32 -

# (e) Bank exposure, profitability and internal bank strategy

As suggested earlier, some banks will be in a stronger position to provision than others. Broadly speaking, the more profitable is the bank and the greater its ability to foster and develop other lines of business, the more inclined it will be to set aside relatively large provisions. Indeed, it will be the banks with the smallest exposure in developing countries that will be inclined to set aside the largest proportionate provisions against these loans because the absolute size of the provisions will be small in relation to those of other banks that are more heavily exposed. 18/ In addition to this, however, some banks may be in a stronger position to exploit the opportunity for debt-equity swaps, which, as will be seen later, is facilitated by provisioning. A bank with a relatively wide network of branches and with good information about investment opportunities in developing countries may be more enthusiastic about the scope for such swaps and may therefore be more anxious to prepare the ground for them. A bank with a less sanguine attitude to swaps may be expected to be less anxious to engage in provisioning.

# (f) Tax and regulatory environment

As was noted earlier in the report, perhaps the most noticeable characteristic amongst differences between International banks in their approaches to provisioning is their national identity. To some extent this is explained by the factors already listed. German banks, for example, with 18. This is confirmed by the data given in Section I.
.25|0.41|0.43|0.51|0.51|0.50|0.54|
|Household Characteristics||X|X|X|X|X|X|X|X|
|Urban/Rural|||X|||||||
|Survey Blocks||||X|||||X|
|Food Products|||||X|||||
|COICOP 2-dig||||||X||||
|COICOP 3-dig|||||||X|||
|COICOP 4-dig||||||||X|X|

This table shows the (negative) average slope of the Informality Engel Curves across countries for different specifications. In column 1, we report the slopes that are estimated from the following regression: _Share In f ormalip_ = _β_ 0 + _β_ 1 _ln_ ( _expenditurei_ ) + _εip_ where _Share In f ormalip_ is the share of household _i_ ’s informal expenditure on product _p_ . We weigh each observation using household survey weights and the expenditure share of the product. Average of lower and upper bound of 95% confidence intervals in brackets, from robust standard errors. In column 2, we augment this regression with controls for household characteristics (household size, age, gender, education of head). In column 3 (4), we instead add fixed effects for urban/rural (survey enumeration blocks). In column 5, we instead add fixed effects for food versus non-food products. In column 6/7/8, we instead add fixed effects for product codes at 2nd/3rd/4th level of the COICOP classification. In column 9, we add household characteristics, as well as fixed effects for survey blocks and COICOP-4.

47
timates on firm-level control variables show expected signs. Sales, export, and import are positively associated with employment, while purchase is negatively associated with employment. Columns (4) through (6) repeat the same estimations as (1) - (3) with the PS matched sample and frequency-weighted regressions. All estimates do not change qualitatively.

Second, we apply an alternative definition of the non-MNC group. To the extent that labor market policy changes (such as an abrupt minimum wage hike) induce firms to conduct outward foreign direct investment (Fan et al., 2018), Korean firms without any foreign affiliates before the abrupt minimum wage announcement in 2017 may have decided to establish new foreign affiliates in response to rising labor costs (i.e., in 2017, 2018, and 2019). One could argue that classifying them as non-MNCs is problematic. To address this concern, we drop Korean firms that established new foreign affiliates after 2017 from the sample and redo the analysis. Column (1) of Table 6 presents the estimation result with the alternative definition of non-MNCs. Reassuringly, the core result is the same, which is not surprising given that non-MNCs account for much less than 5% Table 5: Additional Firm-Level Controls in Manufacturing, 2013~2019

|||Depend|ent Variable|: Logof Em|ployment||
|---|---|---|---|---|---|---|
|||Full Sample<br>||M<br>|atched Sam<br>|ple<br>|
||(1)|(2)|(3)|(4)|(5)|(6)|
|MNC_i ×_Post_t_|-0.0295***|-0.0159**|-0.0152**|-0.0507***|-0.0251***|-0.
inheritance and the consequences of the HIV/AIDS epidemic. But, the situation of everwidowed women of often young ages who have remarried and so are no longer identified as ―widows,‖ or have been in some other way absorbed into male headed households along with their dependent children has to my knowledge received scant attention.

This paper has used available data to examine the individual welfare of women who have experienced the shock of widowhood in Mali. The welfare of their dependent children has also been examined.

A review of the situation of women in Mali suggests that they may be generally more vulnerable and less able to mitigate and cope with downside risk than men. And women may be exceptionally vulnerable to the loss of a husband.

An analysis of household consumption data on female headed households indicates that allowing for their smaller household size ─ and hence, potential scale economies ─ they have lower living standards than male headed households in both rural and urban areas only before controlling for marital status. Households with female heads who are also widows are significantly poorer than all other households.

Finally, the paper turns to an examination of individual welfare indicators from the 2006 Mali DHS. I first investigate whether selection into widowhood ─ whereby widows are poorer prior to widowhood not because of it ─ is a concern in this setting. The tests do not suggest that selection bias is an issue. The analysis then confirms that widows who are not necessarily household heads experience lower levels of individual welfare indicators. It also reveals that relative to other women, the vulnerability and lower welfare of women previously widowed or divorced persists through remarriage. Furthermore, these detrimental effects are passed on to children ─ and possibly more so to daughters ─ suggesting an intergenerational transmission of poverty stemming from widowhood and (less so) divorces.

Yet a review of social safety nets implemented by government and donors reveals that there is little systematic attempt to reach widows or their dependent children. Although it may be tricky to target widows and it should be kept in mind that the same conditions that
by 5–10 percentage points in an election year, particularly in districts with high level of electoral contestation. This pattern is not found in nonelection years or in lending by private banks. Cole also shows that this capture is costly as elections affect negatively loan repayment, and electionyear credit booms do not increase agricultural output either. An explanation for why government-run lending institutions in India are more generous during elections comes from Cole, Healy and Werker (2009) who using rainfall, public relief, and election data examine the reaction of voters to the response of governments to adverse shocks. They find that voters only respond to government relief efforts during the year immediately preceding an election.<sup>5</sup> Unfortunately, the culture of subsidies and frequent government reliefs undermines the culture of repayment as borrowers take advantage of the lax enforcement of credit contracts. The data clearly show that farmers anticipated that, with probability close to 50 percent, a relief package that benefits PACS (but not MFIs or informal lenders) would be announced in case of a drought. Since farmers do not benefit from a relief package if they repay the loan before the announcement is made, all farmers have an incentive to wait (even after the loan due date) until the announcement (if any) is made.

We also asked farmers about their perceived probability of different events related to loan repayment, and their answers showed similar patterns. For example, farmers perceived that their loan with a PACS would be rescheduled in the event of a drought with a 70 percent chance, while this probability dropped to 55 percent for Commercial Banks and only 25 percent for MFIs. The same pattern occurs with the perceived probability of loan forgiveness. Besides, PACSs appeared more likely to issue loans in amounts lower than requested (the difference between PACS and MFIs exceeds 30 percentage points) and less likely to issue new loans even if the previous ones were fully repaid. PACS were less trustworthy of savings and more likely to have a share of the loan deducted
clearinghouse” function to connect employers with female jobseekers** . Such a function can allow women to share information about their skills, and for employers to share information about opportunities, and can help women build professional networks. For example, Malaysia built a database of women who wish to return to the labor force to connect them with potential employers (see Country Example 4).<sup>100</sup>

- **Public information or education campaigns to raise awareness and reduce bias** among firms and investors about women’s skills and abilities. Australia has a Workplace Gender Equality Agency that disseminates information to employers and the public laying out the business case for gender equality.<sup>101</sup>

- **Certification or qualification programs** that allow women to take advantage of standardized accreditation to signal to employers their competencies. In India, a network of government‐run vocational training programs has been established to provide skills‐based training and stimulate employment opportunities among women.<sup>102</sup>

> 98 Jaumotte, “Female Labour Force Participation: Past Trends and Main Determinants in OECD Countries.”

> 99 Elborgh‐Woytek et al., “Women, Work, and the Economy: Macroeconomic Gains From Gender Equity.” 100 “PM Announces New Measures To Optimise On Malaysian Graduate And Women Talent.”

> 101 _Workplace Gender Equality Agency (Australian Government), September 2016,_

> _https://www.wgea.gov.au/sites/default/files/wgea‐business‐case‐for‐gender‐equality.pdf._

> 102 “Overview: Directorate General of Training (DGT),” January 12, 2015, http://dget.nic.in/content/institute/overview‐wt.php.

31
mentioned, it has rarely been analyzed in depth.<sup>15</sup> To be sure, the natural resources curse story

> 13 Declining oil prices, shrinking demand for migrant labor, diminishing remittance flows, and increasing international competitive pressure are among the root causes of this crisis that have been put forward (Yousef, 2004). Moreover, failing to encourage private investment, the regulatory environment hindered the development of exportoriented industrial sectors, thus creating obstacles to the integration of the MENA region's economy into globalized markets (Shafik, 1998; Abed, 2003).

> 14 Despite the increase in human capital made up of a predominantly young population, the economic performance of the MENA region was generally weak, with almost no growth in physical capital and productivity (Yousef, 2004). 15 Using a 1960-2016 dataset on Algeria, Gasmi and Laourari (2017) examine whether this heavily oil-dependent country has suffered from the Dutch disease and find no clear evidence of the existence of this syndrome. They then suggest that the puzzle of the deindustrialization of this country could be better understood by examining the curse of natural resources through the lens of political economy, in particular, the quality of its institutions and the distribution process of the oil rent. Asking whether oil and gas resources are a curse or a blessing in MENA, Aoun (2009) concludes that this phenomenon creates economic and social distortions that impede economic development and impoverish the quality of institutions, in particular, by hindering democracy and encouraging corruption. Looney (2005) emphasizes integration in global markets as an objective for MENA and argues that governments in the region should put a higher priority on enhancing the quality of governance, in particular, by improving voice and accountability and fighting corruption, than on conducting further economic reforms. Abed (2003), Abed and Davoodi (2005), and Abed and Gupta (2002) convey a similar message. Finally, in a dataset concerning 36 oil-rich

8
**Policy Research Working Paper Series**

|**Title**|**Author**|**Date**|**Contact**<br>**for paper**|
|---|---|---|---|
|WPS2442 AFirms's-Eye View of Policy and<br>Fiscal Reforms in Cameroon|Bernard Gauthier<br>Isidro Soloaga<br>James Tybout|September 2000|L. Tabada<br>36896|
|WPS2443 The Politics of Economic Policy<br>Reform in Developing Countries|Richard H. Adams Jr.|September2000|M.Coleridge-Taylor<br>33704|
|WPS2444Seize the State, Seize the Day:<br>State Capture. Corruption, and<br>Influence in Transition|Joel S. Hellman<br>Geraint Jones<br>Daniel Kaufmann|September 2000|D. Billups<br>35818|
|WPS2445 Subsidies in Chilean Public Utilities|Pablo Serra|September 2000|G. Chenet-Smith<br>36370|
|WPS2446 Forecasting the Demand for<br>Privatized Transport: What Economic<br>Regulators Should Know, and Why|Lourdes Trujillo<br>Emile Quinet<br>Antonio Estache|September 2000|G. Chenet-Smith<br>36370|
|WPS2447 Attrition in Longitudinal Household<br>Survey Data: Some Tests for Three<br>Developing-Country<br>Samples|Harold Alderman<br>Jere R. Behrman<br>Hans-Peter Kohler<br>John A. Maluccio<br>Susan Cotts Watkins|September 2000|P. Sader<br>33902|
|WPS2448 On 'Good" Politicians and "Bad"<br>Policies: Social Cohesion,<br>Institutions, and Growth|Jo Ritzen<br>William Easterly<br>Michael Woolcock|September 2000|A. Kibutu<br>34047|
|WPS2449 Pricing Irrigation Water: A Literature<br>Survey|Robert C
the spot market rates—the fact which has not been explored in the trade literature. In practice, importers closely watch annual contract rates as they determine their trade volumes for the entire year.<sup>31</sup> Third, if annual-contract markets dominate containerized shipping, the within-route price dispersion should be detectable in the transaction-level datasets, conditional on them reporting freight rates. Two papers have recently conducted this type of analysis: Holmes and Singer (2018) and Ardelean and Lugovskyy (2021).

**Stylized Fact 20.** _There are two types of containerized shipping markets: long-term contract market and spot market. The rates may differ significantly between the two._

Both document rate and link it to the and papers pronounced freight dispersion firm shipment sizes: larger firms and larger shipments face lower freight rates. The papers use different datasets and provide different interpretations of these findings. Holmes and Singer (2018) use Bills of lading filed with the U.S. Department of Customs and Border Protection (CBP). They attribute the lower freight rates faced by larger trading firms to the container indivisibility and the ability of larger firms to pack shipments fuller than smaller companies.<sup>32</sup> Ardelean and Lugovskyy (2021) use Chilean Imports reported by Panjiva. They explicitly model price-discriminating carriers with trading firms getting quotes from carriers, where each quote is subject to a fixed cost of processing. Larger firms have greater bargaining power in this setting as they have greater incentives to obtain more quotes. This advantage disappears if the number of carriers is limited so that all firms, large and small, obtain the same number of quotes.

Empirically, they find that the 90<sup>_th_</sup> percentile importing firms pay up to 23% lower freight rates than the 10<sup>_th_</sup> percentile firms. In line with their theoretical predictions, they also find that price discrimination disappears in the thin markets—i.e., in markets
. Similarly, another recent study (OECD 2021) based on data from two large-scale international assessments showed that school discipline problems affect boys more negatively than girls. Combining data from the Teaching and Learning International Survey (TALIS) 2018 and PISA 2018, the study found that increases in teachers’ perceptions of classroom discipline problems are associated with an increase in the achievement gap between girls and boys (OECD 2021). The results also showed that other school

> 1 More formally, learning poverty is defined as “being unable to read and understand a simple text by age 10”, whether children are enrolled in school or not (World Bank 2019, 6).

> 2 The learning poverty rate is calculated using the results of international student assessments, adjusted for the share of out-of-school children. Overall, 59 percent of children in MENA are not able to read and understand an age-appropriate text by age 10. About two-thirds of boys in MENA (66 percent) lack basic skills in reading compared to 56 percent of girls, resulting in the largest gender gap in learning poverty among all regions.

2