rafmacalaba/data-use-mentions-extended huggingface dataset:
//doi.org/10.1002/hec.3529</u>

Deaton, A., & Cartwright, N. (2018). Understanding and misunderstanding randomized controlled trials. _Social Science & Medicine (1982)_ , _210_ , 2–21. <u>https://doi.org/10.1016/j.socscimed.2017.12.005</u>

- Deininger, K., Squire, L., & Basu, S. (1998). Does Economic Analysis Improve the Quality of Foreign Assistance? _The World Bank Economic Review_ , _12_ (3), 385–418. <u>http://www.jstor.org/stable/3990181</u>

- Denizer, C., Kaufmann, D., & Kraay, A. (2013). Good countries or good projects? Macro and micro correlates of World Bank project performance. _Journal of Development Economics_ , _105_ , 288–302. <u>https://doi.org/10.1016/j.jdeveco.2013.06.003</u>

- Dreher, A., Nunnenkamp, P., & Thiele, R. (2008). Does Aid for Education Educate Children? Evidence from Panel Data. _The World Bank Economic Review_ , _22_ (2), 291–314. https://doi.org/10.1093/wber/lhn003

- Dreher, A., Klasen, S., Vreeland, J. R., & Werker, E. (2013). The Costs of Favoritism: Is Politically Driven Aid Less Effective? _Economic Development and Cultural Change_ , _62_ (1), 157–191. <u>https://doi.org/10.1086/671711</u>

- Feeny, S., & Vuong, V. (2017). Explaining Aid Project and Program Success: Findings from Asian Development Bank
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school teachers one or two years of leave, with payment of full salary and benefits, so that they :an upgrade their quaiifications.1D Total institutional costs per student differ widely for each level of VTE. They are lowest at the secondary level: 2,285,969 CFAF per - year ($7,620 at $1 300 CFAF). As a frame of reference, it can be pointed out that in 1984 the C8te d'Ivoire's GNP per capita was $610. Teacher training costs per student are 3,067,830 CFAF per year ($10,226) and post-secondary VTE costs are 7,319,315 CFAF ($24,398).

- Apart from the two factors already mentioned the high cost of expatriate teaching staff and the high level of scholarships - two further elements contribute to these elevated unit costs. First, almost all VTE facilities are currently underutilized. The economic recession in C8te d'Ivoire since 1982 has reduced the demand for VTE graduates. We referred earlier to the high percentage of VTE graduates among people without a job, and in response to that situation the government has reduced entrance quotas. This has drastically raised unit costs, since no matching lay-offs in teaching staff were made. For example, the annual cost per student in a vocational high school (the most expensive type of secondary institution)

- 19/ The amount of scholarship per student derived from institutional cost data norresponds with that derived from the CILSS for secondary level students (see Table 21). At the post-secondary level, the CILSS figures are much below those computed from institutional budgets, suggesting either underreporting of scholarships by survey respondents, or, more likely, that the CILSS sample of post-secondary VTE students was too small to be representative of the student body as a whole. For teacher training, the figures caa-;tot be compared because teachers on paid leave would have reported their salary as such and not as a scholarship.
Figure 4 replicates the results of the PSLM data analysis presented in Figure 2. There are some key differences in the results. Most notably, household electricity use is considerably lower according to the billing data. Around 30 percent of the poorest two deciles consumed less than 50 kWh/month (the lifeline slab) according to the billing data, compared to less than 10 percent in the PSLM data. Again, this may be due to reporting of other electricity expenses (such as batteries) in the household survey measure. Despite the generally lower consumption levels, however, the pattern across the welfare distribution is similar: electricity consumption rises gradually with welfare, but almost all households still consume less than 300 kWh/month and therefore benefit from subsidies. This graph also implies that the subsidy cuts in 2013 likely had a direct impact on only a small proportion of households, since the tariff increases were restricted to slabs above 200 kWh/month.

Figure 5 shows that the distribution of subsidies is disproportionately in favor of the richest households, with the top 20 percent of households receiving about 24 percent of the total subsidy. It can also be seen that the 50‐100 and 100‐200 kWh/month slabs account for the majority of subsidies: any substantial cuts to subsidies will need to be focused on these slabs, and this would adversely impact the majority of lower and middle‐income households.

The current subsidy system does not take into account natural intra‐year variation in electricity consumption. Given Pakistan’s warm summer climate and cool winters, electricity expenditures vary widely by season (Figure 6). Even poor households that qualify for the lifeline in the winter (Q3) move into higher slabs during the summer (Q1 & Q4). In the winter, around 13 percent of rich households qualify for the lifeline subsidy. These findings indicate that a static subsidy scheme throughout the year is failing to protect the poor, and provides an unnecessary benefit to the richest households in the winter months, when electricity affordability
>4.1. Backcasting</u>_

For the backcasting exercise, we start with the full consumption vector in the 2018/19 NLSS then construct the consumption vector in each previous year by “rolling back” consumption for each household using sectoral real GDP growth rates and population growth rates. The sectoral GDP data are already in real terms, having been adjusted using the GDP deflator: we therefore do not conduct any additional price adjustments to deflate the consumption vector in each year. Real sectoral GDP growth rates are converted to per capita terms by applying population growth “flat” to each sector: our approach does not, therefore, allow for sectoral switching. However, given the slow pace of structural transformation in Nigeria, this may be a tenable assumption over the period of interest.<sup>12</sup> We use the household head’s employment

> 11 Detailed documentation on the GHS survey can be found in the World Bank Microdata Library, see <u>https://microdata.worldbank.org/index.php/catalog/1002.</u>

> 12 - See Jenq, Lain, and Vishwanath (2021) https://pubdocs.worldbank.org/en/511161631652256763/pdf/Good <u>Jobs-for-a-New-Generation-Delivering-Quality-Jobs-for-Young-Nigerians-After-COVID-19.pdf.</u>

8
>work. Other controls include district fxed effects, year fxed effects, and a vector of year-child-age fxed effects.<br>The standard errors in square brackets are clustered at the district level. All regressions include district, year, age,<br>and sex fxed effects. SGRY: Sampoorna Grameen Rozgar Yojana. NREGA: National Rural Employment Guaran-<br>tee Act.<br>_∗p <_0_._10_,∗∗p <_0_._05_,∗∗∗p <_0_._01.|
|---|
used in the U.S. (Danielson, 2007). The observer evaluated the teachers’ effective use of 21 different activities over the course of a full 45-minute lesson. Based on these observations and a detailed rubric, the observer provided a subjective score, on a scale from zero to three, of four components of the lesson: communication of lesson objectives, delivery of material, use of assessment, and student engagement. The teacher’s incentivized score, as well the measure of pedagogy used in our analysis, is defined as the average of these ratings across the four domains.

## **3.5 Balance**

We use the baseline data described in this section to check whether the second-tier randomization produced an appropriately ‘balanced’ experienced treatment assignment. Table 2 confirms that across a wide range of school, teacher, and student characteristics there are no statistically significant differences in means between the experienced P4P and FW treatment arms.<sup>25</sup>

# **4 Results**

Our two-tiered experiment allows us to estimate impacts of pay-for-performance on the type of individuals applying to, and being placed in, primary teaching posts (the compositional margin), and on the activities undertaken by these new recruits (the effort margin). We report these results in Sections 4.1 and 4.2 respectively. Of course, the long-run effects of pay-for-performance will depend not only on selectionin, but also selection- _out_ , as well as the dynamics of the behavioral response on the part of teachers who stay. We address dynamic issues in Section 4.3, and postpone a substantive discussion of results until Section 5. All statistical tests are conducted via randomization inference with 2,000 permutations of the experienced treatment.

## **4.1 Compositional margin of pay-for-performance**

We study three types of compositional effect of pay-for-performance. These are impacts on: the quality of applicants; the observable skill and motivation of placed recruits on arrival; and the student learning induced
on the one originally proposed by Binswanger, Deininger and Feder (1995), and not dissimilar from the approach used by several others including, most recently, Barrett et al. (2010). We estimate the following function at the household level: _A_ where<sup>_Y_</sup> _i_ represents net agricultural revenues for each household _i_ , _i_ the total area operated, _X i_ denotes a vector of households‟ characteristics that influence production such as the availability of family labor, the gender, age and education of the household head, value of inputs used, and a set of land quality variables, R is the rounding effect when net revenues per acre of area cultivated are measured with land size as reported by farmers, and<sup>_u_</sup> _i_ is the error term. We estimate two versions of this relationship, one using GPS and the other one with the self-reported land measure, and compare the two to gauge the impact of differences in measurement on the IR, which is captured by the coefficient on the land size variable. A negative coefficient on the land area variable indicates the presence of the IR. The further below 0 the coefficient, the stronger the IR. As in the previous model, we also include PSU fixed effects to control for survey team and local environmental effects.

The left hand side term - net agriculture revenues per acre - is computed as the value of total crop production net of value of variable inputs (hired labor, seeds, organic and inorganic fertilizers, chemicals, and animals rented for plowing), divided by the amount of land cultivated. While we maintain this is the preferred way to calculate net revenues, some may argue that subtracting hired but not family labor may give an unfair advantage to small farmers who rely mainly on the latter. We therefore also tried running our estimates without subtracting hired labor costs from gross revenues and the results (not reported) did not change to any significant extent.

Regarding the terms on the right hand
# variations.<sup>18</sup> The ...ndings are largely similar.

# [Table 3 about here]

The vertical production linkage between foreign owned subsidiaries and parent ...rms also determines that the former should exhibit a greater advantage over local competitors when host countries experience a greater incidence of the crisis, in particular, a larger negative demand shock. MNC subsidiaries sharing an input-output relationship with their parent ...rms tend to engage in more intra-...rm trade, thereby less dependent on host-country domestic demand conditions. When the demand in host countries contracts, the intra-...rm demand will help absorb part of the shock, leaving the subsidiaries less a¤ected by the crisis. This advantage of vertical MNC subsidiaries is particularly important when the demand shocks in the host countries are relatively large.

The above mechanism conversely implies that the advantage of vertically linked MNC subsidiaries should be negatively associated with the incidence of the crisis in MNCs’home countries. A better demand condition at home will enhance the advantage of vertical subsidiaries abroad, while a worse incidence of the crisis in home markets adversely a¤ects those MNC subsidiaries’performance overseas.

We examine the above hypotheses in Table 4. The incidence of the crisis, in particular, the degree of the demand shock is proxied here by the average percentage decrease of sales in each host country and industry. The measure was constructed using either all establishments in the entire WorldBase dataset or the subset that excludes MNC subsidiaries and their local matches. The results were similar.<sup>19</sup> The estimates obtained with the latter measure are reported in Table 4.

# [Table 4 about here]

We ...nd that, ...rst, the e¤ect of vertical production linkages on MNC subsidiaries’ relative performance increases in the incidence of the crisis in host countries. Vertical MNC subsidiaries exhibited a greater advantage over local counterfactuals in countries with larger negative demand shocks.
and support services. The role of support services activities in exports, such as sales representatives or office clerks, magnifies especially for high-income countries, with their share exceeding that of production activities for the richest countries.

Several channels help explain the changing distribution of jobs in exports across occupational groups as countries develop. First, as countries become richer their comparative advantage and thus composition of their export basket changes. Second, GVC upgrading can foster a structural transformation of jobs (World Bank forthcoming). Once countries upgrade into more advanced segments of manufacturing and services GVCs, for instance, more non-production activities are embodied in a country’s exports relative to production activities, including managerial, engineering and especially other support services activities. Third, supply linkages between sectors also adjust, with the “servicification” of manufacturing exports gaining in importance as countries develop (Nayyar, Hallward-Driemeier, and Davies 2021). For instance, while food exports in low-income countries often consist of raw commodities or staples, food exports in middle- and high-income countries increasingly rely on sophisticated services embodied in those food exports beyond logistics, transportation and trade services, and include engineering, support and other services (e.g., health inspections).

In addition, changes in productivity trigger changes in relative wages across occupations which are reflected in incomes in exports (rather than jobs in exports) measures. Not surprisingly, managerial and engineering services activities account for a larger share in lower-income countries when using the income in exports measure as opposed to the jobs in exports measure (Figure 17, lower panels). This is because average incomes (and productivity levels) are higher for managers and engineers relative to workers in production and support services occupations in lower-income countries, as they are endowed with a larger relative supply of low-skilled workers (e.g., de Vries, Timmer, and de Vries 2015; McMillan, Rodrik, and Sepulveda 2017). However, such differences decline as countries get richer because relative wage gaps between these occupation categories fall.

20
12 4.7 million individuals. Our effective sample size in terms of UC impacts is, of course, much smaller because the program operates at the province level, and there are only 76 provinces. Offsetting this is the fact we have data for 74 periods: 12 quarters covering the period 1997-2000, the three months of 2001 up to the launch of UC in April, and then 57 months during and after UC implementation.<sup>4</sup> Our outcome of interest is whether the individual reports himself as being too ill to work. LFS respondents who said they were not available for work during the survey week were asked why there not available; the list of possible answers included “Illness, disability”. We use this to construct our self-reported health limitations measure.

Our UC “treatment” variable is constructed from the province of residence of the respondent, the timing of the UC implementation in the individual’s province, and the date (month and year) of the LFS. We construct variables corresponding to the numbers of months, quarters, half years, and years since implementation of UC in the individual’s province as of the LFS in question. From these we construct the dummy variables in eqn (1).

Our VF variable is constructed from the province of residence of the respondent, the timing of the arrival of the first VF funds, and the date (month and year) of the LFS. We define the VF variable analogously to the UC variable so if, for example, the UC variable is defined as years from UC implementation, the VF variable is also be defined as years from VF implementation<sup>5</sup> . In practice, pinning down the date of VF implementation was not

> 4 We have only the first and the third quarters of LFS 1997 and LFS 1998.

> 5 The value of this village fund variable would be equal to zero for municipal areas because villages are in non-municipal areas only.
Business Associations. Additional details on the survey methodology are offered in Apedo-Amah et al. (2020); Cirera et al. (021b); and Cirera et al. (021a). For the WBES COVID-19 follow-up surveys, see for example Muzi et al. (2022).

Our sample covers 68 _,_ 007 firm-level observations from 61 countries. The list of countries and the number of firms sampled in each country is presented in Appendix Table A1.2 Small, medium-sized, and large firms, respectively, account for 6%, 23%, and 11% of the sample. And 19 _._ 3 % of firms in the sample are exporters. The sectoral distribution is skewed towards the non-agricultural sector that comprises 94% of firms in the sample (32% in manufacturing, 8% in hospitality services, 32% in retail services, 3% in knowledge -intensive services, and 19% in other services) (see Appendix Table A2).

We measure the amenability for remote work by the fraction of occupations that can be performed remotely in the U.S. computed in Espitia et al. (2021) using the 2017 O*NET data. This measure of amenability is computed at the level of both 2-digit and 4-digit sectors in the International Standard Industrial Classification (ISIC). The WBES already includes the 2-digit and 4-digit sector identifiers for each firm in the sample. For the BPS, we use the 2-digit and 4-digit ISIC identifiers obtained by Constantinescu et al. (2022) using the description of the economic activity for each business collected by the enumerator.<sup>3</sup> At the 2-digit ISIC level, the amenability to remote work ranges from 14% in crop and animal production and 32% in the manufacture of wearing apparel to 71% in computer . programming services and 72% in financial services (see Appendix Table A3) We measure internet penetration at the country level by the fraction of the population using the internet as well as by
SYS-REVIEW/HI-LMIC found in the literature. Section 5 examines enrollment into health insurance schemes and its related impact. Section 6 concludes the paper.

# **<<A>>Methodology**

The methodology aims to critically examine the evidence on whether health insurance schemes, once implemented, (1) are adopted, (2) provide greater access, (3) provide financial protection, and (4) improve health status among the intended beneficiaries. The last three points describe welfare impact. We summarize the methodology by defining the types of insurance that are of interest.

# **<<B>>** _Types of Insurance_

If universal health care coverage is to be financed through prepayment for insurance, health insurance should have the following characteristics: (1) compulsory contributions to the risk pool (otherwise, the rich and healthy will opt out); (2) large numbers of people in the risk pool because pools with a small number of people cannot spread risk sufficiently and are too small to handle large health costs; and (3) pooled funds that are generally subsidized from government revenue (WHO 2010) due to the large numbers of poor people. The standard SHI schemes in developed countries mandate enrollment for people who are fully employed by imposing a mixture of tax on the employer and direct payment of insurance premiums. This effort is accompanied by requiring enrollment from people who are self-employed or unemployed, with varying degrees of revenue funding and cross-subsidies (OECD 2004).

3
farming (Panel A). These positive effects are robust to the choice of the decay function in the construction of the IV.<sup>17</sup> This effect is compatible with households mainly relying on subsistence farming prior to the arrival of refugees (see descriptive statistics) and potentially responding to an increasing demand for some agricultural products from refugee settlements. Market expansion induced by refugees would allow subsistence farmers to sell some of their home production and diversify their sources of livelihood. Alix-Garcia and Saah (2009) similarly find that, compared to urban households, rural households closer to refugee camps experience a positive wealth effect which could be resulting from production and supply of non-aid food products in response to the upward price shifts. We could not find any significant effect on those initially involved in commercial farming, wage employment and nonagricultural employment. But the reduction of sample sizes and the weakness of the first-stage regressions do not allow us to draw any firm conclusion.

Table 6: Second stage: Effects of refugee presence on household welfare disaggregated by initial main source of income, - <u>with analysis at cluster level and the distance weighted refugee index at 50km from the clusters (Panel 2009 2012)</u>

||Log of welf<br>|are (consumpti<br>equival<br>|on aggregate p<br>ent)<br>|er adult<br>|
|---|---|---|---|---|
||(1)|(2)|(3)|(4)|
||Pa|nel A (Subsiste|nce farming)||
|Log of refugees (50km)|0.08035|0.08138|0.09170*|0.08407*|
||(0.05125)|(0.05133)|(0.04793)|(0.04368)|
|Observations|2,850|2
developing countries, although they account for most of world trade in value added, which is generated by high income countries. Because they comprise only high income or large middle income countries, these databases tend to have great levels of accuracy. On the other hand, the Eora database has the widest country coverage, with 187 countries in total, but only 25 sectors. However, the data at this stage do not ensure consistency in terms of aggregation and reconciliation of trade flows. This can generate problems of imbalances in the data, which can be particularly relevant for smaller developing countries.<sup>6</sup> GTAP data strike a balance between the accuracy of the data (including a rigorous submission process for national IO tables), the global consistency of the national account and trade data across countries, and the relatively wide coverage of developing countries. GTAP uses various data sources and estimates missing data. The GTAP IO data also include social accounting matrices that cover additional countries where no official IO tables are available. While the global coverage is smaller than Eora (120 versus 187 countries), the countries covered in the GTAP data account for over 90% of developing countries’ population.<sup>7</sup> In addition, GTAP disaggregates the factors of production into skilled and unskilled labor.

There are also certain drawbacks in using GTAP to compute such data, which should be acknowledged upfront. The quality of the data critically hinges on the underlying IO tables and social accounting matrices that each country produces autonomously. While GTAP researchers check and validate these data before using it, their quality cannot be fully observed. That can be a problem especially for certain sectors in specific countries. A second problem relates to the frequency of the data. As the production of GTAP data is complex (it needs global consistency and requires multiple data inputs and iterations), its frequency is not regular and the data suffer from non-negligible time lags. For example, the latest data currently available are from 2011. For