rafmacalaba/data-use-mentions-extended huggingface dataset:
>_∗_</sup> _p < ._ 1 _∗∗ p < ._ 05 _∗∗∗ p < ._ 01 In terms of project-level variables, the controls include project length (in years), the log of total committed funds, a dummy for new projects (versus follow-ups), a dummy for investment projects, sector dummies, share in the largest sector, and the log of completion and preparation costs relative to total committed funds.

Table 7 presents estimates from six different variants of equation (2). In column 1 the regression does not include any controls, in column 2 it includes all controls except cost variables (which are not available for many projects), and in column 3 it includes the entire control set. Columns 4–6 replicate the same specifications but also include sector fixed effects. The coefficient on the fraction of locations in the vicinity of a mission is small, and its sign is not consistent across specifications. The standard errors are at least three times as large as the coefficient. In short, table 7 shows no evidence that mission presence is correlated with better (or worse) project performance, as measured by IEG ratings.

The results in table 7 should be interpreted with some caution: the sample size is relatively small, and the explanatory variable is subject to measurement error due to the need to keep the dataset at the project level. These factors imply low statistical power to reject the null hypothesis. Furthermore, the IEG rating is an imperfect measure of project performance. It measures performance with respect to a goal, which is not the same across sectors, and it is at least partly based on documentation produced by the team leader.

Bank, but these data for the period before 2005 could not be located for the present study.

27
and civil society organization_

There also appears to be a large shift in Africa in organization among citizens. Village-level group formation in Africa increased dramatically over the 1990s when participatory approaches were emphasized in international development paradigms, promoted through aid, and adopted deliberately by country governments to deliver projects to communities.<sup>10</sup> Bernard et al (2008), for example, show a rapid proliferation of village organizations (VOs) in a sample of

> 9 Working papers using the Afrobarometer data can be found at http://www.afrobarometer.org/index.php?option=com_docman&Itemid=39

> 10 Here, we focus on community organizations intended to solve failures in the delivery of local public goods; instead of marketed-oriented organizations that have existed primarily in agriculture (Bernard et al, 2008).
effect is especially pronounced for agricultural activities and, to a lesser extent, for casual labor. More than 75% of the population worked in agriculture in the past 12 months, but less than 40% did so in the last seven days. These results are similar for women and men. However, labor market statistics of young people are more sensitive to the choice of the reference period. Considering someone employed if he engaged in at least one activity, the employment rate of the population aged 15 to 24 increases from 50% to 82% if a long rather than a short reference period is used, compared to an increase from 74% to 95% for the population aged 25 to 64. The share of young people in agriculture is particularly sensitive to the reference period. Like in Uganda, this finding suggests that seasonality affects young people more than the rest of the population.

# 4.4. Self‐reports or response by proxy

Questions about employment can be asked directly to each household member or to a single informed household member, often the household head, who reports for all household members. Both approaches are common. The literature often recommends self‐reporting as best practice (Benes & Walsh, 2018a), mainly because self‐reports are believed to be more accurate. Indeed, proxy respondents may not be aware of all activities carried out by all family members, particularly in extended families, or may have an incentive to under‐ or overreport specific activities of certain household members (Blair et al., 2004). At the same time, interviewing each household member rather than a single respondent is burdensome for the enumerators and respondents, and may increase non‐response (Thomsen & Villund, 2011). In order to facilitate fieldwork, many surveys therefore aim to minimize the level of proxy reporting, but do not prohibit it. A comprehensive ILO review of LFS shows that in half of the LFS 30% to 50% of the responses are provided by proxy informants (ILO,
entire sample period 1970-2004, for 172 countries, graphed against the log-level of GDP per capita in 2000. From this figure it is apparent that countries with higher income are somewhat less likely to engage in “sovereign theft”. However, this relationship is not particularly strong. In fact, a somewhat surprising feature of the data is that both types of sovereign theft have at one time or another occurred in countries of nearly all income levels. And similarly, there are countries at nearly all income levels that have not chosen to engage in either form of sovereign theft.

**Table 1** provides a basic description of the joint distribution of the two types of sovereign theft events across countries.  The first panel distinguishes between countries that have never defaulted or expropriated over the entire sample period 1970-2004 and those that have defaulted or expropriated at least once over this period.  On the one hand, most countries have either never committed sovereign theft of any kind, or they have both defaulted and expropriated at least once (a total of 137 out of 191 countries fall in these two categories).  On the other hand, only a few countries have either only defaulted but never expropriated (20 of 191 countries), and somewhat more have expropriated but never defaulted (34 of 191 countries).  A simple chi-squared test of the null hypothesis that the two events (ever expropriating, or ever defaulting) are independent strongly rejects the null with a p-value of 0.00.  This basic feature of the data was first noted in Tomz and Wright (2010), Table 3.1, over the longer period since 1929 covered in their full dataset.

At higher frequencies, however, the coincidence between the two types of events diminishes. The second panel of **Table 1** reports the same information, but focusing on a pooled sample of 1050 5-year periods for the same set of countries. At this quinquennial frequency, there are only 20 cases of countries that have engaged in both forms of sovereign theft within
policies and delivering services. Modules available from the literature to measure integrity, altruism, cognition, risk-aversion, personality traits, and public service motivation, were administered to 1,357 district bureaucrats and 770 district politicians. Administrative data available on the implementation of nationally mandated public health programs serve as a measure of productivity of the district organization. These data reveal that the integrity of politicians is a robust predictor of district productivity in delivering health services. The size of the correlation is substantively large: a 1 standard deviation higher average integrity among local politicians is associated with a 0.2 to 0.4 standard deviation higher measure of performance in health service delivery. In terms of concrete indicators of health coverage, an increase of 1 s.d. in the average integrity of politicians is correlated with a 4.4 percentage point increase in child delivery at government facilities (9% increase at the mean); a 4.7 p.p. increase in share of households with latrines (6.2% at the mean); a 3.8 p.p. increase in share of pregnant women preventively treated for malaria (6.7% at the mean) and a 2.8 p.p. increase in pregnant women having at least 4 antenatal care visits (8.2% at mean).

In contrast to the correlation with political quality, we find no significant correlation of service delivery with measures of electoral competition such as the concentration of vote shares of competing candidates and the margin of victory. At the same time, we find that political integrity tends to be higher in places where there is greater electoral competition. This is suggestive evidence that competition can play a role through improving selection (such as, by enabling the election of politicians of higher integrity) rather than through incentives alone. Our results are consistent with other research that incentives generated by electoral competition may play an ambiguous role in public service delivery.<sup>3</sup> Our evidence also brings into
# **4 Parameterization**

In this model, labor productivity is a function of the calendar, as well as two depreciation rates, _δr_ and _δm_ , and two intensity parameters, _αr_ and _αm_ . In this section, I narrow down the parameter space based on three criteria. First, the parameters must imply labor productivity that peaks during the workweek, consistent with the patterns of electricity usage documented below. Second, the variation in productivity over the workweek must be within the range of predicted variation in electricity usage per worker. Finally, the parameters must be such that a year of absence from work is associated with a reentry penalty, consistent with magnitudes estimated in the labor literature.

The first two criteria are based on predicted variation in electricity perworker over the workweek. Variation in electricity usage is informative of variation in the utilization rate of capital, which, in the context of the model, is proportional to variations in _Lt_ (equation 4). I use data on electricity loads from seven regional transmission organizations (RTOs): ERCOT, PJM, ISONE, CAISO, MISO, NYISO and SPP.<sup>11</sup> The aggregate generating capacity of these RTOs corresponds to roughly 60% of US totals, though coverage varies by RTO.<sup>12</sup> Observations range from January 1st, 2003 and February 15th, 2015. Data are available on an hourly frequency (and on a higher frequency for some RTOs) and are aggregated to a daily frequency. To remove long-run and seasonal trends, the data is de-trended using a weekly moving average.<sup>13</sup> To account for potential variation in the number of workers over the workweek, I use the American Time Use Survey (ATUS) for the years 2003-

> 11Data for PJM, ERCOT and SPP are taken from their websites. Data for ISO-NE, CAISO, MISO and NYISO are taken from energyonline.com.

> 12Unfortunately, load data for the remaining RTOs is not readily
_Fareed M. A. Hassan, ECSPE_ 18 return to high tax rates and more complex schedule **8.** Under the 1993 Personal Income Tax Law there were ten income tax brackets, an increase of three brackets with higher rates: 44, 48, and 52 percent. Such amendment would complicate -rather than simplify- and strain existing scarce administrative tax capabilities<sup>9</sup> . Under such circumstances, the revenue, redistributive, and developmental objectives of tax amendment may prove difficult to attain. Fortunately, the 1997 amendment of the tax law has moved the personal income tax system toward less nominal progressivity in its rate schedule. For instance, the top-bracket rate has been reduced from 52 percent to its 1992 level of 40 percent. Second, the number of tax brackets has been halved in comparison with its number in 1993. Finally, the threshold at which positive personal income tax payment must be made is increased by 20 percent, reducing the tax burdens on the poor.

One of the reasons why the proposecl tax systems surpassed the 1992 system in its revenue raisinlg and re-distributional effects lies in the fact that the underlying income distribution is not adequately taken into consideration in designing the 1992 tax rates and brackets. Table 5a shows the tax bracket income level relative to mean per capita income as obtained from the 1992 household budget suLrvey. This ratio shows several interesting characteristics of the 1992 tax brackets. The zero bracket (exemption level) is very narrow, extending from zero to less than half the mean per capita income. Positive income payments start at higher income level. However, it is only at incomes above 7 times mean per capita income that **the** marginal tax rate becomes substantial -- at 36 percent rate. The narrowness of higher tax brackets is evident. The top tax rate of 40 percent requires an income of 14.3 8/Bulgaria's 1993 personal income tax schedule is given in _Tax Notes International,_ Volume 6, No. 19,
reached a low in 2013 and has since increased by 16 percentage points; it has risen in 90 percent of LICs and, in one-third of them, by more than 20 percentage points. The composition of LIC debt has shifted toward nontraditional sources of funding, including international capital markets and non-Paris Club creditors (World Bank 2019b).<sup>17</sup> Debt has been increasingly financed by non-concessional and private sources, increasing LICs’ vulnerability to financial market disruptions. As a result, interest payments are absorbing an increasing share of government revenues. Separately, the average LIC current account deficit widened to 8.1 percent of GDP in 2018, from 3.1 percent of GDP in 2007.

> 14 Based on data for 16 EMDEs that have 2019Q1 data: Argentina, Brazil, Chile, China, Colombia, Hungary, India, Indonesia, Malaysia, Mexico, Poland, Russia, Saudi Arabia, South Africa, Thailand, and Turkey.

> 15 Based on a larger sample of 48 EMDEs with data for 2017 and 2016.

> 16 Average LIC debt was 51 percent of GDP in 2018, lower than the 59 percent of GDP in 2007. However, the mean is driven by a minority of LICs who have seen significant declines in debt as part of the Enhanced HIPC initiative of 2009/10.

> 17 By August 2019, 12 out 28 LICs were regarded as being in debt distress, or at high risk thereof, under the IMF-World Bank debt sustainability framework (two more than at end-2018). A country is considered to be in debt distress if it is experiencing difficulties in servicing its debt, as evidenced, for example, by the existence of arrears or ongoing or impending debt restructuring, or if there are indications that a future debt distress event is probable.
9 As the ban only applied to agrochemicals, one may ask if the decreased use of inorganic fertilizer was offset by an increased use of organic fertilizer. We show this offset was very limited by examining the use of manure, a typical organic fertilizer. The quantity of manure applied to the soil had been increasing steadily over the twenty years prior to the ban and, importantly, its increase in 2021 merely followed this long-run trend, without any visible “jump” that would occur if farmers resorted to increased organic fertilizer use as a key coping strategy to deal with the ban (Appendix Figure A3a). Moreover, manure’s share of total fertilizer use was not atypically high in 2021 compared to the previous six years and this share was never higher than 2.5% (Appendix Figure A3b). Trade data also confirms that the collapse of chemical fertilizer imports, which decreased to less than 40 million USD in 2021 from a pre-ban baseline of 100-250 million USD, was hardly compensated by organic fertilizer: while the organic share of fertilizer imports did increase after the ban, it was never higher than 4% (Appendix Table A3).

# **III Data**

Our reduced-form and model-driven analyses rely on a rich assortment of mostly novel data. Table I presents our main data sources and variables, grouping them into several categories: trade policy; trade flows; agricultural production, cultivated area, and yields; agricultural prices; fertilizer use and subsidies; potential agricultural yields; labor share in value added; wages, land ownership, occupation, and household characteristics; and night lights. Appendix A provides additional details on all data sources and variables used. Below, we briefly highlight a few important features of our data.

**Trade-related variables** . The list of products targeted by import bans and their time coverage are hand-coded from Sri Lanka’s Extraordinary Gazettes on Imports and Exports. The fertilizer import bans started in May 2021, with most bans lifted by July 2021 or by November 2021 at
the neoclassical theory based on Becker (1959) and according to which discrimination is costly. Hence, the increase of industry competitiveness due to trade participation reduces the incentives to discriminate against women especially in concentrated industries than in competitive ones. For instance, Boler et al. (2015) use matched employer-employee data from the Norwegian manufacturing sector and prove that trade participation has narrowed the gender wage gap in exporting firms relative to non-exporters. Similarly, Juhn et al. (2014) and Black and Brainerd (2004) reach the same conclusion using various datasets. Nevertheless, contradictory results have been proven in other studies. For instance, in a study based in India, Taiwan, and China, Berik et al. (2004) show that competition resulting from international trade increases wage discrimination against female workers, which does not go in line with the neoclassical theory. Moreover, using difference-in-difference estimation and data from the Demographic Census for 1991 and 2000 fielded by the Brazilian Census Bureau, Gaddis and Pieters (2017) show that trade liberalization decreased the male and female labor force participation rate. The effect is significantly larger on men, which means that liberalization reduced the gender gap in employment and participation rates. Nevertheless, the results show no evidence that women got any benefit from the competitive effects of liberalization as their employment and participation rate did not increase relative to those of men. The literature also shows that the limited or negative employment effect was due to other concomitant factors such as the effect of anti-sweatshop activism (Harrison and Scorse 2010) and the constitution of minimum wage for export tariff privileges (del Carpio et al 2015). By studying the opposite dimension of the subject, Karam and Zaki (2021) argue that female labor participation in the MENA region has a positive significant impact on both trade margins. Furthermore, their results show that female ownership positively affects the probability of exports of large firms.

2
## **Place-based policies**

For the second set of policies, I study whether place-based policies that reallocate formal firms in the city can effectively increase welfare and reduce informality rates. The intervention consists of increasing the commercial floor space employed by formal firms in different parts of the city. I consider two sets of policies; the first one consists of increasing the commercial floor space in the center of the city, and the second one in the outskirts. Figure 9 plots the locations in which the Government implements the policy; in total, there around 250 treated census-tracts in both parts of the city. The goal is to compare policies that reallocate formal firms to the outskirts vs. transit shocks that connect informal workers with formal jobs.

Figure 10 plots the results of the intervention. In panel A, the Government increases commercial floor space in the central locations, and in panel B in the remote areas. The results suggest that it is more effective to intervene in the central locations than in the outskirts. For instance, if the Government increases the commercial floor space by around 40% in the central areas, the policy generates similar welfare gains to the transit shock that I studied. On the other hand, as shown in panel B, it is very ineffective to reallocate firms to the outskirts. Even if the Government increases the commercial floor space by a substantial proportion, 60%, it only increases welfare by 0.18%, which is significantly lower than the one obtained by the new subway line that connected informal workers with formal jobs. Moreover, in the latter case, the allocative efficiency margin and the externality component explain a very small fraction of the total gains.

There are two main explanations for this result. The first one is that since most of the formal firms locate in the CBD, the agglomeration forces are minimal in the outskirts. The second one is that these locations are very unproductive in terms of the productivity scale parameters, especially for formal firms. Hence, reallocating firms to
# **<mark>Table A6.1: Management Data availability by measure and time period</mark>**

|||# Fi<br>|rms with Data<br>Treatment<br>|by<br>||
|---|---|---|---|---|---|
|**Measure**|**Period**|**Control**|**Individual**|**Group**|**Data source**|
|Anexo K management score|2013|52|51|53|Anexo K collected by CNP|
||2014|42|46|0|Anexo K collected by CNP|
||2015|26|40|35|Anexo K collected by CNP|
||2016|0|0|36|Anexo K collected by CNP|
|WMS management score|2013|26|24|27|WMS collected by LSE|
||2016|20|19|31|WMS collected by IPA|
|MOPS management data|2012|28|33|34|Collected retrospectively by IPA|
||2017|28|33|34|Collected byIPA|

Figure A6.1 compares the distribution of baseline management practice data for firms which attrit and do not have endline (2015 for the control and individual treatment, 2016 for the group treatment) Anexo K data. We see that the distributions of those with and without follow-up management data are similar, both for the full sample, and when we split by treatment status. We cannot reject equality of distributions between attritors and non-attritors using a KolmogorovSmirnov test of equality of distributions. This shows that attrition is not selective on initial management practices.

58
13 cumulative consumption growth in the survey data, the simulated year-by-year changes in mean consumption will not be equal to the year-by-year GDP per capita changes. In Tanzania, the cumulative GDP per capita growth (6.1%) is close to growth in consumption per adult equivalent in the survey (6.5%). As a result, the difference between the GDP per capita changes and simulated mean consumption changes in each year is small.

In general, use of a large number of quantiles will cause the simulated distribution in the final year to more closely match that in the final survey year data. However, when using weighted data, complications may arise that force the use of a smaller number of quantiles. The simulation requires that at least one household be associated uniquely with each quantile. Because the quantiles are calculated by individual, with weighted data a household may be classified as being in two adjacent quantiles, even though the number of households exceeds the number of quantiles. If this is the case, a smaller number of quantiles should be used. For the analysis in this paper, 50 quantiles are used.

# **4.3 Reconciling National Accounts and Household Survey Data**

The approach taken in this paper is to apply per capita GDP growth rates from the national accounts data to unit-record household survey data to simulate changes in household per capita consumption. This approach assumes some correspondence between the micro-level household data and the macro national accounts data. Because the two sets of data are drawn from entirely different sources and are designed to capture different phenomena, it is to be expected that the match-up between the two sources of data is rough at best.

In general, it is often difficult or impossible to reconcile differences between the national accounts and household survey data. As Ravallion (2003) says in a review of comparisons between national accounts (NAS) and survey data, “It is evident that when the levels or growth rates from these two data sources differ, there can be no presumption that