rafmacalaba/data-use-mentions-extended huggingface dataset:
significant heterogeneity. The census includes data on demographics, labor market (including employment, industry and salary), and access to infrastructure, among other. Using cartographic data on communities and former homeland boundaries we identified which communities were located inside and outside the former homelands. In the next section we document the extent to which the data are consistent with the historical accounts of the apartheid.

The geographic community definitions changed from 1996 to 2011. We use official cartographic data to match communities over time. For the analysis presented in the paper, we match the 2011 data to the 1996 data by the nearest centroid.<sup>15</sup> We allow for multiple matches, and therefore there is not a one-to-one correspondence between local communities.<sup>16</sup> Our final sample is comprised of almost 16,000 communities, observed both in 1996 and 2011. Appendix Table A1 provides summary statistics on these data.

Our main variable of interest is the growth of income per capita at the community-level. This variable is defined as the difference in the natural logarithms of population-weighted income per capita between 2011 and 1996. Since data on income are grouped in categories (e.g. no income, 1 to 4800 rand a year, and so on), we take the mid-point of each category.<sup>17</sup> All income values are expressed in December 2012 prices (obtained from Statistics South Africa). To provide complementary evidence on the specific mechanisms we emphasize, we also use data from the 10% sample of the 1996 population census.

# **5 The legacy of apartheid: Size and evolution of local development gaps**

We document the evolution of development differentials across communities located justinside and just-outside the former homelands. Communities are grouped in one-kilometer bins with respect to the minimum linear distance to the former homeland border. Our aim is to verify the extent to which the data are consistent with numerous historical accounts pointing to a tragic legacy of apartheid through the various
13 per capita income (y) and consumption (x) adjusted for regional price differences. That is, x is the welfare ratio or per capita consumption divided by the poverty line, and y is the income ratio or per capita income divided by the poverty line (for details on the construction of the poverty lines, see Wodon, 1997). If a household has a welfare (income) ratio of one, his per capita consumption (income) is exactly at the level of his regional poverty line. If the ratio is less than one, the household is poor, and if it is more than one, the household is not poor4.

# _4.1. Unidimensional Decompositions_

Gini decompositions are sensitive to the number of mutually exclusive groups or categories defined along given dimensions (at the limit, if we were to define each household as being a group, the Gini will be equal to the between group component) . To avoid such sensitivity as much as can be, to ensure that groups defined according to a combination of characteristics have a reasonable sample size, and to facilitate the comparisons between the decompositions, five categories were defined for each of the three dimensions of interest. The definition of these categories and summary statistics by education, land ownership, and occupation are provided in Tables 1 and 2 for, respectively, income and consumption.

Tables 1 and 2 remind us that half of the population of Bangladesh as represented in the 1991-92 HES is illiterate. One fourth of the population is landless, and another fourth is near landless. In terms of occupations, agricultural laborers and tenant farmers represent together one sixth of the population. Land owners deriving their income from their own land parcels, be them small or large, make up one third of the population. Factory, industrial, and other blue collar workers account for another third of the population. White collar workers such as officials,
## **F Subjective Well-Being**

Before turning to mechanisms of impact, we present results on two measures of subjective wellbeing. Indeed, improvements in sales and profits do not necessarily imply greater satisfaction as they may have incurred other subjective costs. To address this concern, we included two endline questions from the World Values Survey to elicit subjective well-being: (1) “How satisfied are you with the financial situation of your household?” and (2) “How satisfied are you with your life at this point?” (see, Inglehart et al., 2014).<sup>23</sup> Table 10 shows results from regressing these two measures of subjective-wellbeing on treatment assignment. While we do not detect significant treatment effects for satisfaction with life, the results show a positive and statistically significant effect of being assigned to _All Three_ on satisfaction with finances. Specifically, these shop owners are 4.5 percentage points (7.1%) more satisfied with their finances than those assigned to the control group. Shop owners assigned to other groups show a slight increase in both measures of well-being, but the effects are not statistically significant.

# **V Mechanisms**

We now turn to the mechanisms behind the increase in sales and profits identified in the previous section. The experiment design of this paper implies a strong causal link between improved business practices and better performance outcomes. This link is especially merited given the handbook and its accompanying experiential learning add-ons are precisely based on the business practices for which we identify treatment effects. In this section, we delve more deeply into the details of these practices and how they relate to gains in efficiency rather than other mechanisms. We also study possible alternative explanations for the performance improvement.

## **A Efficiency Gains or Just Better Record-Keeping?**

In this subsection, we unpack the individual practices underlying the aggregate indices to shed light on the mechanisms of impact. This exercise also helps address the concern that the performance gains we identify
cost efficiency. An analysis of performance with respect to preference costs measured as is not possible since almost all roads are paved and an inventory of road quality is only conducted in only two out of the seven states.

# 5. **Country Case Studies**

Empirical analysis of the optimal structure for decentralized provision of roads suggests that the impact of fiscal decentralization on road performance is partially driven by country specific factors (see a companion paper by Humplick and Moini-Araghi, 1995). But these country effects are generally fixed and unobservable. In this paper, we 13The Deutsche Strassenliga brings together professionals working in different areas on roads. Members come mainly from the private sector but the agency is in close cooperation with the state and federal governments. It promotes the development of roads in Germany.

11
yes|
|Sector Fixed effect|Yes|yes|yes|yes|yes|
|Sector-Year Fixed effect|No|no|no|no|yes|

_Source:_ authors’ calculations based in the Orbis dataset for Turkey _Notes:_ The regressions are estimated by GLS. TFP is total factor productivity, computed using the WooldridgeLevinsohn-Petrin methodology (WLP). FO is transformed as (FO _/_ 100) + 1. FO is the share of foreign-owned equity. ∆<sup>_k_</sup> indicates the change between year _t_ and year _t_ − _k_ where _k_ = 1 _,...,_ 4. Standard errors clustered at the firm level are in parenthesis. *** , **, *, denote significance at 1%, 5%, and 10% levels.

All these regressions are estimated by feasible Generalized Least Squares (GLS). There is a large difference in the variance of the error terms across firms, so GLS is more efficient. We do this in two steps: first OLS estimation, and then we use residuals from the OLS estimation to calculate firm-specific standard errors which we then use to weight observations in the second step.

In spite of the firm level heterogeneity, sectors are not that different in terms of delivering this result. All our regressions in Table 1 and Table 3 have sector fixed effects and the last columns have sector-year fixed effects (both at 2 and 4 digit sectors). It is clear that the results of last two columns in both tables are very similar. To test the sectoral heterogeneity hypothesis further, we interact FDI 9
, while input-output tables for Vietnam were sourced from the Asian Development Bank (ADB). Finally, fixed capital deflators were obtained from the Food and Agriculture Organization (FAO).

## Descriptive statistics

Table 1 displays summary statistics of various firm characteristics used for markup estimation and measures of markups and firm profitability. For firm _i_ in year _t_ , Outputi,s,t is defined as deflated revenue; Employmenti,s,t denotes total employees at the end of year; Capitali,s,t denotes deflated total assets at the beginning of year; Materialsi,s,t denotes deflated cost of goods sold (COGS); MNEi,s,t is a dummy variable equal to one if the firm is foreign-owned; SOEi,s,t is a dummy variable equal to one if the firm is state-owned; and Yi,s,t is markup defined as price divided by marginal cost. According to the legal information reported in the survey, a firm is considered foreign-owned when it is a joint venture between foreign owners and other private proprietors or is 100% foreign-owned.

Firm-year observations vary widely in terms of their size whether measured in terms of revenue, employees, capital, or materials cost. Average estimated markups are greater than one, signifying that

> 7 Negative markups are implausible as they require prices or marginal costs to be negative. The high-end cutoff of three was selected as it implies very high gross margins in excess of 75 percent that are seldom seen in practice at this level of aggregation. While this cutoff is somewhat arbitrary, we show in Section VI that our results are robust to different levels of cutoffs. Overall, such outliers account for 2 percent of markup estimates assuming a CobbDouglas production function and under 1 percent of estimates assuming a translog production function. Outliers correspond to 1 percent or fewer of all translog estimates, although they are somewhat more common for within individual sectors for Cobb-Douglas estimates, with a maximum of 11 percent for the leather goods sector.

7
are more likely to provoke a strong interest rate defense on the part of a "tough" monetary authority committed to maintaining the fixed exchange rate, one might expect to find large increases in interest rates during successful attacks, and conversely, small increases in interest rates during failed attacks. This endogeneity 3A second possible source of non-linearities is in the time dimension, if, for example, the signaling value of tight monetary policy becomes less credible over time. Since I will be relying on the relatively low-frequency monthly data available for this large sample of speculative attacks, there is unlikely to be enough time series variation in each episode to identify non-linearities over time in the effects of monetary policy.

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# **5.3 Results by worker characteristics**

While the international movement of skilled and highly educated workers is subject to less binding administrative regulations (many _ad hoc_ visas are currently available for highly skilled workers that want to move internationally), primary educated workers and/or those employed in unskilled-intensive occupations suffer more stringent administrative constraints to international mobility. We therefore expect that visa provisions in RTAs stimulate relatively more unskilled workers. To test such an heterogeneous effect of visa provision on migrants with different skills we use the OECD DIOC dataset,<sup>28</sup> and test the effect of visa provisions on skilled _vs_ unskilled immigrants. Based on the occupation of workers, we consider high-skilled those immigrant workers in ISCO occupation 1 (Managers, senior officials and legislators), 2 (Professionals) and 3 (Technicians and associate professionals). Conversely, workers in other occupations are classified as low-skilled (i.e. ISCO occupations 4-9). Results are reported in Table 7. In line with the intuition, the presence of visa provision in RTAs increases the bilateral stock of low-skilled migrants by 17.9%, and the stock of unskilled immigrants by 9%.

As a robustness check of previous results we use a sector-based definition of workers’ skills. Namely, we classify as primary educated migrants those employed in low-skill intensive sectors such as: (i) agricultural, fishery and related laborers (ISCO code 92), (ii) laborers in mining, construction, manufacturing and transport (ISCO code 93), and (iii) stationary-plant and related operators. Results, reported in Table 8, show that migration related provisions in RTAs favor in particular migrant workers in primary low-skill intensive sectors (see columns 1-2 in Table 8).<sup>29</sup>

## – Table 8 about here –

All in all, the results in Tables 7 and 8 confirm the intuition that visa provisions in RTAs are beneficial for international migration subject to more binding administrative regulations (i.
ment’s Covid-19 policies and improve how citizens perceive the state’s capacity to implement these policies. We focus on two types of information: _(i)_ information about past state success in managing crises, and _(ii)_ information about non-state actors’ support for state policy. Governments frequently deploy both strategies to spur citizens to support their policies or build citizens’ trust in the state.

All respondents received basic information about the government’s directives as part of the survey. We provided additional information to respondents assigned to a treatment group. Referring to truthful information about how the government successfully managed a large-scale dengue fever outbreak in 2011, the first treatment informs respondents that the government selected the right policies to address a public health emergency in the past, and that it possessed the capacity to successfully implement these policies.

The second treatment complements the first treatment. It emphasizes that, according to experts’ assessments, the government successfully tackled the dengue outbreak because, in addition to the government identifying and undertaking appropriate actions, citizens substantially cooperated with the government’s policies.

The third treatment represents an appeal to religious authority, a common strategy in Islamic countries’ politics. The treatment provides information that religious authorities support the government’s policy. We informed respondents about a fatwa issued by Al– Azhar University in Egypt considered one of the highest authorities on Sunni Islamic – thought by many Muslims permitting a ban on congregational prayers and urging citizens to hold confidence in their respective government’s Covid-19 policy.

Given concerns about potential experimenter demand effects in phone surveys, we include an additional treatment group that allows us to isolate experimenter demand effects from estimated treatment effects. This condition precludes misleading interpretations of estimated treatment We collected rich demographic data (e.g. on partisanship, belief in conspiracy theories, religiosity and economic exposure to the Covid-19 crisis) before sharing any information with the respondents. After providing respondents the respective informational treatments, we collected data on three sets of outcomes: support for the government
## 4.3 Summary of the findings

The simulation results presented above, which confirm and extend the findings of Drukker and Liu (2019), have important implications for our work.

Given that in our application we only have data on 282 trade agreements,<sup>20</sup> we cannot expect any of the methods considered to be able to precisely identify the set of provisions that matter for trade. The task of identifying the correct set of explanatory variables is particularly challenging in our application because many of the provisions have very strong correlations with others, and there are even cases of perfect collinearity. In this challenging context, the iceberg lasso and bootstrap lasso emerge as providing a good compromise between parsimony and the ability to identify the relevant variables. The iceberg lasso has the practical advantage of being easier to implement and not requiring the choice of additional parameters, such as the number of bootstrap samples. Consequently, the iceberg lasso is our preferred approach to select the relevant variables, but the bootstrap lasso is a credible alternative that can be used, at least, as a robustness check. Additionally, the bootstrap lasso is the only approach we have considered that can provide information about model uncertainty, but exploring that is beyond the scope of this paper.

If the objective of the researcher is to accurately predict the trade impact of a given PTA, the preferred approach is to compute the predictions using the post-lasso estimates obtained with the plug-in penalty. Indeed, this approach performs extremely well in all cases, and is only marginally outperformed by the adaptive lasso in the larger sample we considered.<sup>21</sup> However, the bootstrap lasso is also a credible alternative in this context and it can serve as a useful robustness check.

# 5 Empirical Results

In this section, we present the lasso results obtained using the methods described and studied in the previous sections. We first present results for the plug-in method before briefly discussing the results obtained using cross-validation. We then turn to the iceberg
**Can Wage Subsidies Boost Employment in the Wake of an Economic Crisis? Evidence from Mexico**

Miriam Bruhn<sup></sup> _JEL codes_ : J23, H32, L60 _Keywords_ : Wage subsidies, industrial policy, crisis mitigation, firm behavior

>  Development Research Group, The World Bank. mbruhn@worldbank.org. I thank David McKenzie and Will Wiseman for valuable comments and the Mexican Social Security Institute (IMSS) for sharing their data on employment in manufacturing industries. Nathaniel Russell, Christian Salas, and Lucía Juárez provided excellent research assistance.
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the raw data, including original measures of checks and balances and political stability.

In contrast to other databases, these variables are nearly all objective and their construction is entirely transparent. They are also disaggregated, allowing researchers to get away from such useful but broad indicators of countries as whether they allow elections or ‘not, whether elections are “free”, or whether the executive is “constrained.” Instead, the DPI allows researchers to use precise and concrete institutional features of countries, and to combine them in ways appropriate to theories they are examining.

In this paper, we identify numerous and policy-relevant research directions where this data will be helpful. We also describe the different variables and demonstrate their utility in several applications. For example, we find that earlier results concerning the impact of divided government on public debt (Roubini and Sachs, 1989), and the impact of presidentialism vs. parliamentarism on democratic consolidation (Stepan and Skach, 1993), change considerably when their methodologies are replicated using the DPI’s variables on divided government, presidentialism and parliamentarisrn. The remainder of the paper, and the annexes, provide details on sources and collection methodology.

# The need for cross-country institutional data

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_A large and diverse array of inquiries into the political economy of economic development and the determinants of institutional change have been hindered by the absence of detailed cross-national objective data on the institutional and political characteristics of countries. A few of the areas of investigation to which the DPI can contribute are outlined here.

Political Business Cycles. Research on the existence and importance of a political business cycle has largely focused on a select group of developed countries. One reason for the narrow
# Picking the Poor: Indicators for Geographic Targeting in Peru

Norbert R. Schady World Bank* I thank particularly Christina Paxson for much helpful advice. I have also benefited from comments made by Greg Felker, Francisco Ferreira, Jesko Hentschel, John Waterbury, and participants at a seminar held at the World Bank. I am indebted to Marcos Robles for help obtaining the necessary data from INEI, and to Vajeera Dorabawila for help with the consumption aggregates for the 1994 and 1997 LSMS. Please address correspondence to Norbert R. Schady, The World Bank, 1818 H Street N.W., Washington, DC 20433 (nschady@worldbank.org).
in terms of shareholder-affiliate ownership links. Second, it differentiates those links as to be horizontal versus vertical (and then forward versus backward) in terms in the light of GVC data. Third, it identifies parameters and provides insights based on a very large panel data set covering all pairs among 209 countries and 38 sectors over a period of 9 years. The latter permits conditioning on a host of unobservable factors in a high-dimensional fixed-effects design. The latter ensures that the effects – of PTAs and their depth can be identified from the time variation in the data i.e., – the new membership in PTAs only.

The key insights from our study are the following. First, entering a PTA raises the number of new foreign ownership links. Second, the latter is completely driven by vertical links, i.e., ones in the forward or backward integration direction. The effects tend to be somewhat stronger in the forward than in the backward direction. The propensity of horizontal ownership links declines with the formation of PTAs. The effects of PTAs on vertical ownership links increase with a higher PTA depth. Finally, PTA effects on vertical investment are stronger, if the specificity of inputs 3
(Allen et al., 2005), but a firm-level survey suggests that bank financing has spurred firm growth (Ayyagari et al., 2010).<sup>11</sup> Evidence at the provincial level indicates that capital market depth is positively and significantly associated with provincial growth, though bank depth is usually not (Hasan et al., 2009). Our findings complement the existing papers and provide evidence on the positive association between the use of capital markets and firm performance.

Third, a separate strand of the literature studies the Gibrat’s law, which states that firm size and growth are independent and that the FSD is stable over time and approximately log-normal. This view has been challenged over time. Although the growth of large firms seems independent of their size, including smaller firms in the analysis typically introduces a negative relation between growth and firm size (Lotti and Santarelli, 2004, Coad, 2009). Moreover, the distribution of young firms is skewed to the right (most of the mass is on small firms) and the skewness tends to diminish monotonically as firms age and become larger (Cabral and Mata, 2003, Angelini and Generale, 2008). Our findings suggest that even among the publicly listed firms, which consist of the largest firms within a country, there is some heterogeneity: firms that use capital market financing are larger to begin with and grow faster than non-users. In fact, our results indicate that there is no convergence in firm size; if anything, the distributions seem to diverge. The results seem consistent with the rapid growth within large plants in India (Bollard et al., 2013). Moreover, a misallocation of capital in China and India (Hsieh and Klenow, 2009, 2012) might have kept large, highly productive firms artificially small, which might explain why they are the ones that grow the most when financing becomes available.

Fourth, a related strand of the literature studies financial constraints by analyzing whether measures of financial performance affect firm