rafmacalaba/data-use-mentions-extended huggingface dataset:
represent the percentage of firms out of the year‟s population that make it to the following period. We show results for the 2006 cohort, which offers three year-on-year transitions. This way of presenting the data would reveal the “learning” process, whereby firms that survive up to a certain date have a higher chance of hanging on in the future, so the yearly rates should increase towards 100 percent.

Learning is evident in all the six types of units, even though they have different starting points and slopes. FPDs have the lowest starting point, as they are at the finest level of detail in the export space, where churning is at its highest, but after three transitions their resilience rate almost doubles, from 32 to 63 percent. Destinations start very high and reach 100 percent by the third year, which seems to show that there is much less geographical exploration, and firms that make it to a foreign market will do their best to remain there.

**Figure 8:** Yearly survival rates for firms, products, destinations, firm-products, firm-destinations, destinationproducts and firm-product-destinations in Laos

<!-- Start of picture text --> 100%<br>80%<br>60%<br>40%<br>20%<br>0%<br>2007 2008 2009<br>firms products destinations firm-prod<br>firm-dest dest-prod FPD<br><!-- End of picture text --> _Source:_ Authors‟ calculation based on Lao PDR Customs data In order to put this phenomenon into perspective, we compare Lao rates with those available for Senegal, Tanzania, Mali and Malawi (comparable data is from Cadot et al. (2010)). Figure 9 presents the evolution of yearly survival rates for the five countries, synchronized despite the different years which the data represent (and thus ignoring any year-specific effects such as global recessions, etc.). Senegal and Tanzania have longer data spans – the Senegal data captures seven
_APPENDIX_ **_1._** _ENROLLMENTS AND EXPENDiTURES ON EDUCATION_

**Table 1. Enrollments by type of school, 1994**

|**Education level**|**Public**|**Private**|**Others**|**Total**|
|---|---|---|---|---|
|Primary|13,593,797|895,913|40,689|14,530,399|
|Lower Secondary|4,661,522|388,806|12,004|5,062,332|
|Upper Secondary|2,386,758|778,587|49,385|3,214,730|
|Tertiary|1,461,189|530,754|1,503|1,993,446|

Source: ENIGH 94

**Table 2. Enrollments by type of school, 1996**

||**Public**|**Private**|**Others**|**Total**|
|---|---|---|---|---|
|Primary|13,802,395|768,748|1,746|14,572,889|
|Lower Secondary|4,972,116|326,229|4,153|5,302,498|
|Upper Secondary|2,767,993|875,129|15,782|3,658,904|
|Tertiary|1,459,820|580,962|7,680|2,048,462|

Source: ENIGH 96

**Table 3. Federal Expenditure (Thousands of 1996 constant pesos)**

||**1994**|**1996**|
|---|---|---|
|Primary|32
(Ethiopia) and 80 percent (Malawi) of households engaged in crop farming. The first data points during the COVID-19 pandemic suggest there is a significant increase in the household-level incidence of crop farming, as pandemic lockdowns limited other income generating activities, of 5.2 points in Burkina Faso, 13.5 points in Ethiopia, 9.3 points in Malawi, and 8.4 points in Uganda (Figure 1).

The initial increase at the onset of the pandemic leveled off during the course of 2020 but remained above pre-COVID levels until 2023 in Ethiopia, Malawi, and Nigeria. In Malawi and

> 6 We do so to maximize longitudinal coverage as fertilizer prices as reported in the price module and as reported in the agriculture module were collected across distinct survey rounds. To lend confidence to this approach, we compared the most common fertilizer types, compound and nitrogen-based fertilizers, using the type-specific price data. The median difference in prices across the two types was approximately zero.

6
led some to threaten to call in sovereign guarantees, is likely to have played an important role in deterring the entry of more IPPs. The persistence of different governments in continuing to set the actual tariffs below those calculated by the regulator to consumers so as to limit price rises through the provision of subsidies, despite pressure from multilaterals to reform this aspect of the management of the power sector, made it clear that there could be substantial risks of entering the Pakistan power sector. As is demonstrated below, the DISCOs had been operating inefficiently for a long period, thus throwing more burden on the government which wished to hold tariffs below costs. This too, may have limited the enthusiasm of possible new entrants.

However, the predictions for the next five years show the capacity deficit disappearing in 2018, and a substantial surplus of nearly 5GW appearing by 2021, and this is in the context of demand growing by around 5 percent per annum (equivalent to an increase of about 5GW). Since the government has not changed its policies towards the sector with respect to price setting or the management of the public-sector utilities, some other explanation must be sought. In April 2015 the China-Pakistan Economic Corridor (CPEC) initiative was announced. The original valuation of the infrastructure projects included was $46 billion, and the total has since risen to $62 billion.

> 28 Data for Pakistan are for 2013-2015, while data for other countries are based on the most recent year in which a survey was undertaken.

28
# **Appendix 3: Calculating the Full GEGI in the data in term of ratios (BER, emp/pop)**

Similarly, the Other Employment gender gap becomes the gender gap in other employment rates, relative to their sum: Note that h is the relative productivity of skilled to raw labor (which has productivity 1). For example, if h= 3 , then skilled labor (people in better employment) are three times as productive as raw labor. For the current generation, the Penn World Tables human capital measure is exactly this ratio. For the next generation, can be calculated from the World Bank Human Capital Index. However, this requires some adjustment, because the HCI is productivity relative to a theoretical maximum (“complete human capital”) not relative to raw labor. The lowest HCI score, of someone with no education and in poor health is H ≈0.1979 . Hence the productivity of better employment relative to raw labor is h= H . Hence, the full GEGI can be written as: EEM II II/H Full GEGI= IIEEM G G �× 100% <u>(H /H m m)(B</u> +B <u>)</u> �ωωBBEE GG + (1 −ωω)OOEE where GG (H m )(B +B HH HH RRMM RRFF ωω= HH/H HH mm RRMM RRFF)+OOBBRRMM+OOBBRRFF

> 47 B He also uses share of employment in better jobs (SEBJ)=better employment/total employment = . 48 In terms of aggregates, this share can also be written as <u>(h/hm m)</u> (h/hm SSB SS LL /LL 26 ωω= mm)SSB SS+(1−SSB SS)
EU Extra‐EU<br>Services<br>Goods<br>Services<br>Goods<br><!-- End of picture text --> We next look at the extent to which the UK economy is integrated in global value chains with the EU and other non‐EU partners. In a world of international production networks, gross trade statistics are inflated by the double‐counting of goods and services that cross borders multiple times. Wang et al. (2016) offer a decomposition of gross exports based on the work by Koopman et al. (2014). This decomposition allows 11
# **4. Robustness checks and validation**

# **4.1 Robustness to use of projected employment declines**

<mark>The results of the macro-micro simulation reported in the previous section used actual employment data, taken from the ILO, for 2020. In many settings, like at the outset of a crisis, employment data may not be available. In this robustness exercise we compare the poverty, vulnerability, and middle-class projections presented in Section 3.2 with another set of results obtained using the sectoral employment elasticities calculations of Section 2 to project the employment level of 2020. We perform this analysis for Brazil, the Philippines, Türkiye, and South Africa using the elasticity</mark> method with the best performance according to Table A2 in the Appendix.

<mark>As was previously discussed, the 2020 employment projections based on employment elasticity calculations tend to overestimate the actual employment level of 2020 and therefore underestimate the adverse impact of the crisis on employment. Although the overestimation of employment was on a reasonable range of 5% for some countries, for some others including Brazil and South Africa, it was above that level (see Figure 1). Depending on which part of the income distribution these “additional workers” are located, we could obtain different poverty projections with respect to the</mark> results presented before.

<mark>Figure 8 shows that when using employment levels based on elasticities projections, we obtain a similar pattern of income change across the entire distribution. The only exception is Türkiye where we obtain small income increases instead of small income declines. The magnitude of the income reductions, however, are smaller in comparison to using actual employment data. For instance, in Brazil our previous simulation results show a decline of 12% of the per capita income</mark> of the bottom quintile, while using elasticities the decline is 5%.

21
function. Then, ll a = ∑ + ∑ + ∑ a , (1) KK LL MM aa kk=1 kk kk ll=1 ll ll mm=1 mm mm aa where a denotes the error term. TT αα AA ππ PP γγ CC + εε aa εε To estimate model (1) using the APC method, we construct a panel of individuals by their APC identifiers. The EU-LFS collects age information in five-year intervals, and we combine survey years and cohorts to correspond to these five-year intervals to preserve the APC relationship. Thus, we have 11 age intervals, 5 survey-year intervals, and 15 age cohorts.

<u>Figure 3</u> shows the age effects associated with both estimation methods. Panel a presents the changes in average tenure along the life cycle of workers estimated by the ME method (Browning, <u>Crawford, and. Knoef 2012). Panel b shows the result of the Deaton-Paxon (DP) (1994)</u> decomposition. As expected, tenure increases with age almost linearly, with a sign of stabilization after 55. The ME decomposition estimates that, on average, a 30-year-old worker has 3 years more

> 11 The least squares estimator proposed by Deaton and Paxson (1994) remains popular and widely used in economic analysis, despite its deficiencies.<sup>12</sup> Ten years is about the average job tenure for the workers in our sample. Gregg and <u>Wadsworth (2002) used similar tenure categories in analyzing the evolution of job tenure in Great Britain between</u> 1975 and 2000.

12
However, as noted, the sample size is substantially smaller, so these results also need to be interpreted with more care.

Taken together, these findings call for future work to better understand the country determinants of the policy response. Further, the global database can support policy makers and researchers in evaluating policies in terms of their effectiveness and potential unintended consequences. For certain measures, authorities should continue to balance the relevant trade-offs between keeping temporary measures in place to support the real sector and maintaining prudent credit risk and liquidity management standards. As discussed in Section 2, some countries, particularly low- and middle-income EMDEs, have resorted to policy measures (e.g., lowering certain risk weights without adequate public guarantees, relaxing the classification and treatment of non-performing loans) that are not consistent with the principles that underpin international financial standards and recent guidance by standard-setting bodies and the IMF and the World Bank (see for example IMF and World Bank (2020)). These countries have adopted such measures perhaps because they have fewer options at their disposal due to limited policy buffers, less diversified financial systems, weaker implementation capacity, and less sophisticated regulatory and supervisory frameworks (e.g., countercyclical capital buffer frameworks are typically not in place). This may have created some respite in the short term but may also generate new risks since such policies may weaken bank buffers, reduce bank balance sheet transparency, induce moral hazard, and contribute to market fragmentation. These risks could undermine the medium-term resilience and stability of the financial system and compound the economic impact of the pandemic. Furthermore, some of these measures may jeopardize hard-won gains in upgrading regulatory and supervisory frameworks to align them with global standards and longer-term policy credibility. Such risks should be weighed against the development of the global health crisis and the pace of the economic recovery, particularly if a timely economic rebound does not materialize and insolvency pressures surge.

27
**Table 8. Results on Science test-scores in higher-order items according to teacher experience**

|_Independent variable_|(1)|(2)|(3)|
|---|---|---|---|
|Sequence vs. Control|0.434***|||
||(0.130)|||
|Low experience|-0.240|-0.034|-0.618***|
||(0.188)|(0.223)|(0.155)|
|(Sequence vs. Control)* Low<br>experience|-0.253<br>(0.253)|||
|Coaches vs. Control||0.537***<br>(0.167)||
|(Coaches vs. Control)* Low experience||0.317<br>(0.299)||
|Coaches vs. Sequence|||-0.051<br>(0.142)|
|(Coaches vs. Sequence)* Low<br>experience|||0.752**<br>(0.301)|
|Observations|1042|1072|1102|

_Source:_ Author's analysis based on experimental data generated for this study.

_Note:_ ** significant at 5 percent; *** significant at 1 percent. Robust standard errors in parentheses clustered at school level. Controls: (a) students’ characteristics (gender, age, nationality, parent’s education, if the student missed, at most, one class per month, if the student has internet in his/her home), (ii) teacher characteristics (gender, age, general teaching experience [in years], if she/he has postgraduate certificates), and (iii) school characteristics (school size, seventh grade size
(0.201)|_−_0.096<br>(0.236)|
|Observations|6,118|6,118|6,118|6,118|6,118|6,118|6,118|
|R<sup>2</sup>|0.562|0.579|0.408|0.485|0.661|0.645|0.566|
|Mean(ODP tons)|-821|-218|-3|-472|-19|-128|10|

FE triple-difference regressions on a stacked country-level panel with a _±_ 3 year event window around RTA entry into force. All outcomes are the inverse hyperbolic sine of the difference between ODS emissions and emissions targets under the Montreal Protocol. All models include country-event fixed effects. Robust standard errors are (two-way) clustered at the country-event and country-year levels. We report the mean deviation from target across the entire sample in tons of ozone depletion potential (ODP). Statistical significance from two-sided _t_ tests are denoted by _∗_ p _<_ 0.1; _∗∗_ p _<_ 0.05; _∗∗∗_ p _<_ 0.01.

iv
female labor supply is endogenous, not exogenous.<sup>7</sup> The GEGI calculation also assumes that human capital is the same across males and females—an accurate assumption based on the World Bank Human Capital Index (see Appendix Figure 3)—and that males and females are otherwise equally productive.

> 4 To see that Equations 1 and 2 are equivalent, substitute in the denominator of Equation (1) and then substitute and . Females and males have almost identical populations, , and so population MM FF cancels in the numerator and denominator, yielding Equation (2). LL= LL + LL 5 MM MM MM FF FF FF MM FF LL Note that in countries where male employment rates are low, parity of employment by gender is a less ambitious target. = EE × PPE LL = EE × PPE PPE = PPE 6 Appendix Figure 4 (reproduced from Jones 2016) shows that the US capital-to-output ratio has been broadly constant at about 3-3.5 since World War 2.

> 7 Across countries, female employment is high in both low and high income countries (Pennings 2020), but this is a correlation, not causation.

4
et al. (2012) note the possibility that treated individuals may _report_ doing certain behaviors (e.g. separating personal and business accounts) because the training told them this was important, rather than because they actually do this.

Measuring profits and revenues poses further problems. Owners of the smallest businesses typically do not keep written records of these items, and owners of larger firms who do keep records may be reluctant to share them (because of concerns about theft, or because of taxation issues). De Mel et al. (2009a) study several approaches to obtaining profits from microenterprises and conclude that, in their context at least, a simple direct question is more accurate and much less noisy than calculating profits from revenues and expenses. However, collecting profits has proved difficult for many studies, with several studies not collecting profit data at all (Valdivia, 2012; Giné and Mansuri 2011; Klinger and Schündeln, 2011), collecting it but not using it due to too much noise (Drexler et al, 2012), or collecting only profit margins on the main product, rather than overall profits (Karlan and Valdivia, 2011).<sup>7</sup> Most studies have collected revenue data (Bruhn and Zia, 2011 is an exception), but some have struggled with much lower response rates for revenues than for non-financial business questions (e.g. Drexler et al, 2012 have a 46 percent attrition rate on revenues compared to 13 percent for their questionnaire as a whole). Similarly, Bruhn and Zia (2011) note that about one-third of clients in their study did not provide profit data.

> 7 In addition profits are not examined in two studies which look at business start-up as outcomes – Field et al. (2010) and Premaud et al. (2012).

11
|||||||||
||High income:OECD|12<br>||2,320.2]|1,581.8]|1,945.7]|513.6 ||7,185.2]|3,933.9|
||High income: non-OECD|6 ||1,372.5]|878.1]|1,248.0]|121.8|| 3,561.8]|1,082.9|
||EastAsia& Pacific|7|668.6]|431.6]|630.3]|443|| 1,570.3]|799.3|
||Europe & Central Asia|13.|[1,047.8]|909.2]|811.2}|38.0|| 3,176.4]|1,645.5|
||LatinAmerica&Caribbean|7|873.6||667.2)|587.6]|329.4|| 2,015.2]|967.0|
||Middle East & North Africa|d|385.9]|343.3]|295.6]|77.4|873.0)|384.7|
||South Asia|5|506.7}|365.5]|429.7]|71.1<br>|| 1,130.0]|531.7|
||Sub-SaharanAfrica|22|261.0]|150.3}|294.5|2.4||1,132.0]|281.1|

Source: Global Financial Development Database, 2008-10 data. Note: OECD = Organisation for Economic Co-operation and Development. a. Weighted average by total adult population.
# level of employment, are distinguished here:

|**Range of**<br>**employment**|**Number of plants**<br>in**sample**|
|---|---|
|Small<br>1-20|2346|
|Medium 21-100|2143|
|Large<br>101+|1310|

Research on industrial emissions must consider some subset of pollutants, because factories discharge hundreds of waslte products which are potentially harmful to human health or ecosystems. In this paper, we focus on emissions of airborne suspended particulates from the Mexico data base. Environmental scientists generally agree that air pollution from fine particles (those with diameters less than 10 microns) has the greatest impact on morbidity and mortality. Although fine particulate emissions are not yet commonly measured in developing countries, they are known to be highly correlated with total particulate emissions on which the present study focuses.

# **3.2 Brazil**

Although the Mexican data are very rich, no information on plant location is available. Thus it is not possible with these data to explore hypotheses relating to local levels of development. The Mexican data are therefore supplemented by a database of 156,000 factories in 5,000 Brazilian municipios, made available b! the Instituto Brasileiro de Geografia e Estatistica (LBGE). The factories in this database are categorized by 266 4-digit Classificacao Nacional de Atividades Economicas (CNAE) codes, employment size, and location. Of the 5000 municipios, 3455 report some industrial employment and these form the data base for the Brazilian analysis.

Information on total population for each municipio is drawn from the 1991 demographi **c** ensus. To separate Brazilian municipios into ten income classes, median wage of the head-of-household from the same source is used for each municipio. It should, however, be noted that the deciles are constructed from a ranking of municipios by this measure, regardless of population. As a result, the two highest deciles
The treatment assignment is by construction independent of the error term and potentially a valid exclusion restriction. We therefore estimate eq. (2) by instrumental variables (IV). The identifying assumption is that the treatment only affects the outcome by changing the hours of usage of the platform. In our context this assumption is likely to hold. First, unlike other settings (Muralidharan et al., 2019) students do not use the application in computer lab, and it is therefore unlikely that the intervention could affect the peer composition. Since the intervention was conducted during the school closing where most of the teaching was already being conducted online, it is unlikely that the intervention could differentially affect teaching practices in the treatment and control groups.

Results are reported in **Table 5** . One standard deviation increase in the number of hours of use of ALEKS increases test scores by 0.20sd and reduces the probability of having failed any subjects by 6 percentage points. In line with the ITT results, the impact on the probability of enrolling in the third semester is null.

## _6.4. Potential Mechanisms_

There are different ways through which ALEKS might improve learning outcomes. First, by improving student preparedness, it might make learning more efficient. Unfortunately, our data do not allow us to test this hypothesis. Besides increasing the quality of learning, ALEKS might have increased the number of hours devoted to it (quantity). Information collected through the online survey applied contextually to the math test supports this hypothesis. Results presented in columns 1 to 4 in **Table 6** suggest that students are, on average, studying mathematics autonomously for more hours without sacrificing other subjects (column 5). Students in the treatment group displayed a higher perceived ability of their math skills with ALEKS (column 6). Altogether, these results are suggestive that, either because they are better equipped to understand more complex concepts or because of the gamification of the learning method, students who are eligible to use ALEKS
_have the right to bequeath it, even if you need to obtain consent or permission from someone else?_ in the IHPS).<sup>15,16</sup> While the IHS4 allowed for specifying up to 4 household members and 2 non-household members as joint parcel owners/right holders in the answers to these questions, the IHPS identified joint parcel owners/right holders through subsequent questions that would be asked conditional on the respondent identifying himself/herself as a parcel owner/right holder and that would first establish the existence of other potential joint parcel owners/right holders and then identify up to 3 household members and 2 non-household members as joint owners/right holders.

Finally, another key difference between the surveys was about the land rights-related data collection. In the IHS4, following the prevailing practice, the parcel-level questions on rights to sell and bequeath were asked of the most knowledgeable household member irrespective of the answers given to the question on reported ownership of that parcel. Since the reported ownership question is phrased to refer to any individual, rather than the most knowledgeable respondent himself/herself, and is aimed at identifying all owners associated with a given parcel in one, seemingly open-ended question, it is virtually impossible to enable the later questions on the rights to sell and bequeath as a function of the answers given to the earlier, also seemingly open-ended question on reported ownership. Conversely, in the IHPS, the questions on rights to sell and bequeath were not asked of the respondent if he/she did not name himself/herself as a reported owner for a given parcel.

In terms of success of implementation, among the 2,508 IHPS households, 98.7 percent completed at least one individual interview.<sup>17</sup> While all (5,089) eligible adults were targeted for interviews, the non-response rate was 18 percent on the whole, 24 percent for adult men and 12 percent for adult women.<sup>18</sup> As discussed