rafmacalaba/data-use-mentions-extended huggingface dataset:
with WTO accession negotiations. Our findings on TTBs also relate to a separate study on TTB use by the United States, in which Bown and Crowley (2013b) provide evidence that economic incentives at the sector level shape antidumping and safeguard use and thus US participation in cooperative, selfenforcing trade agreements such as the WTO, an idea first formalized theoretically by Bagwell and Staiger (1990).

The rest of the paper proceeds as follows. Section 2 summarizes the theoretical work regarding macroeconomic shocks and new import protection, and it characterizes the institutional environment facing emerging economies’ trade policies under the WTO during 1995-2010. Section 3 introduces our empirical model and describes our panel dataset. Section 4 presents our baseline results regarding the relationship between macroeconomic fluctuations and new import restrictions for emerging economies under the WTO covering the years 1995-2010. In Section 5, we extend the data set back to 1989 where possible and compare emerging economy TTB use under the WTO relative to the prior GATT regime. Finally, Section 6 concludes.

# **2 Theory, Institutional Environment, Empirical Model, and Data**

# **2.1 Theory**

An extensive empirical literature documents evidence of counter-cyclical trade policy in industrialized economies. Nevertheless, there are relatively few theoretical contributions that explicitly model the channels through which such import protection arises.<sup>8</sup> Political economy models face two empirical difficulties: first, changes in political parameters do not necessarily match the speed of economic fluctuations; second, there is little evidence that the government’s preference for the welfare of import-competing sectors relative to consumers or export-oriented sectors rises during recessions.

Greater success in matching some of the stylized facts on time-varying trade restrictions comes from terms-of-trade-driven models of import protection. Consider first the approach of Bagwell and Staiger (1990); they present a dynamic, repeated-game model of the trade policy choices of two large countries that participate in a trade agreement. While global welfare is higher in such a framework when countries pursue a cooperative agreement that involves more liberal trade
there is<br>enough information<br>`o`<br>Improve use of alternative tariff structure options<br>`o`<br>Introduce subsidy and guarantee budgets (better control)<br>`o`<br>Rely more effectively on tax‐related data or consumption surveys<br>to reduce the risk of omissions or undesired inclusion in subsidies<br>(improve information for targeting)<br>`o`<br>Introduce ordeal mechanisms as eligibilitycriteria for subsidies|**‐**<br>**‐**<br>**‐**<br>**?**<br>**‐**|**‐**<br>**‐**<br>**‐**<br>**?**<br>**‐**|**?**<br>**?**<br>**‐**<br>**?**<br>**‐**|**‐**<br>**‐**<br>**‐**<br>**‐**<br>**‐**|
|**Oversight**<br>**and**<br>**regulation**|`o`<br>Create a truly independent regulator (separation of powers)<br>`o`<br>Ensure transparent recruitment of regulators<br>`o`<br>Limit future employment opportunities in the sector for ex‐<br>regulators<br>`o`<br>Ensure independent financing of regulatory agencies<br>`o`<br>Adopt competitive wages for regulators and their staff<br>`o`<br>Match regulatory institutions to the general institutional capacity<br>`o`
and Mitchell, 2011b, for an overview of financial literacy data in eight countries and Christelis, Jappelli, and Padula, 2010, for an overview in eleven countries).

Of primary interest to this study is the association between financial literacy and financial outcomes. Table 1 indicates that there is a moderately positive association between financial literacy and having a bank account (also shown in the correlation matrix between financial literacy and bank account in Appendix Table B3). Individuals in the high literacy group are also significantly more likely to use formal bank credit. In addition, high literacy groups are significantly less likely to experience low spending capacity, both in terms of the binary and the ordinal spending capacity variable. In contrast, individuals with higher financial literacy are significantly more likely to experience having unspent income and with higher frequency.

# **5. Financial and Real Consequences of Financial Literacy**

The important question we aim to address in this paper is whether financial literacy matters. To do so, we consider the following set of outcomes that expand upon the previous literature. We first estimate a set of regressions in which the dependent variable is (a) having a bank account, (b) using formal bank credit, and (c) using informal credit. In addition to financial consequences we also look at real consequences. Our set of dependent variables is (a) level of spending capacity and (b) availability of unspent income. The sets of explanatory variables in our regressions include financial literacy, gender, single-person household, the logarithm of age, a dummy for a negative income shock during the last year, and dummy variables for education (4 dummies), occupation (8 dummies), family income quartiles, and federal region of residence (7 dummies).

18
main drivers of real exchange rate variability.

# VI. **Conclusions**

Based on the country-specific Generalized Variance Decompositions we found that during 1992-1998 output variability in most Latin American countries was associated with domestic factors. These results coincide with other work (Hausman-Gavin (1995), Hoffmaister-Roldos (1997) and Ahmed (1999). In four of the eight countries (Brazil, Chile, Colombia, Mexico) the joint effect of shocks to domestic factors (real interest rates and real exchange rates) on output variability was greater than the combined effect of shocks to external variables (terms of trade and external spreads). In Argentina, Brazil and Mexico, shocks to external spreads played a major role, while in Chile and Colombia real interest rates shocks were the principal sources of output variability. In the remaining three countries, Ecuador, Peru and Venezuela, terms of trade shocks were
played by public procurement in the empirical ndings they document. They suggest that an eective anti-corruption policy would be to improve governance and best practices in public procurement.<sup>26</sup>

# 5 Reforms and productivity growth

This section will discuss the literature that analyzes the eect on productivity of several reforms implemented since the 1990s. Several of them tried to reduce distortions that were discussed in the previous section and thus improve the eciency of factor allocation.

## 5.1 Trade liberalization

In the late 1980s Brazil started a process of trade liberalization that lasted until the mid1990s. This episode consisted of large, unilateral, import tari reductions. Average taris fell from 31 to 13 percent, and there was ample variation in the magnitude of tari cuts across sectors. After 1995, taris remained relatively constant. Using a panel of manufacturing rms, Ferreira and Rossi (2003) measure the impact of trade reform on productivity growth. The results show that the tari reduction had a substantial positive impact on the growth rates of TFP and output per worker. Moreover, this eect was widespread in the manufacturing sector, with most activities experiencing large productivity improvements. Lisboa et al. (2010) show that one important mechanism through which the tari reduction increased productivity was that it allowed national producers to have access to more technologically advanced equipment and components from abroad. Despite the evidence that the trade liberalization reform increased productivity at the rm level, there were not sizable aggregate eects in the 1990s. Menezes Filho and Muendler (2011) provide evidence that is informative about this issue. They nd that even though output shifted to highproductivity export-oriented rms, there was a labor ow away from these rms because their labor productivity increased faster than their production. The labor that was shed from these productive rms moved to low-productivity service activities, unemployment and out of the labor force. As a result, despite sizable gains at the rm level, the labor reallocation
<!-- Start of picture text --> Public Private<br>Agriculture<br>Mining<br>Manufacturing<br>Utility<br>Construction<br>Trade<br>Logistic<br>Finance<br>Social<br>-.05 -.025 0 .025 .05 .075<br><!-- End of picture text -->

# **Figure 8. Effect of preschools on mothers’ choice of industry**

Note: Sample is restricted to females aged 19-45 in at least two IFLS rounds. We infer preschool data in-between PODES years. Each dot represents the interaction coefficient of public/private preschool density in one’s district of residence and a dummy for having a preschool-eligible child on the probability of being employed in a certain industry, standardized in z-scores to allow visual comparison across industry categories. IFLS collects 1-digit industry codes (see Table 10 for a list of top-3 occupations per industry code). 95 percent confidence intervals are represented by horizontal lines. See Table 9 for non-standardized effect sizes and adjustments to multiple hypotheses testing.

41
# **Abstract**

While providing the most reliable method of evaluating social programs, randomized experiments in developing and developed countries alike are accompanied by political risks and ethical issues that jeopardize the chances of adopting them. In this paper we use a unique data set from rural Mexico collected for the purposes of evaluating the impact of the PROGRESA poverty alleviation program to examine the performance of a quasi-experimental estimator, the Regression Discontinuity Design (RDD). Using as a benchmark the impact estimates based on the experimental nature of the sample, we examine how estimates differ when we use the RDD as the estimator for evaluating program impact on two key indicators: child school attendance and child work.

Overall the performance of the RDD was remarkably good. The RDD estimates of program impact agreed with the experimental estimates in 10 out of the 12 possible cases. The two cases in which the RDD method failed to reveal any significant program impact on the school attendance of boys and girls were in the first year of the program (round 3). RDD estimates comparable to the experimental estimates were obtained when we used as a comparison group children from non-eligible households in the control localities.

Keywords: Mexico, PROGRESA, Regression Discontinuity, Treatment effects JEL codes: I21, I28, I32, J13
||(0.064)|(0.053)|
|Confident storing inneighboring village|-O.047|0.004|
||(0.060)|(0.049)|
|Neighboring village memberwouldreturnwallet|-0.216%**|-0.178*#|
||(0.060)|(0.078)|
|Confidence in institutions index|-0.013|-0.006|
||(0.012)|(0.012)|
|Haraniagespecific|||
|# of bags to store iftakingpart inwarrantage|O.O0g***|O.008***|
||(0.003)|(0.002)|
|Scoreoffamiliaritywithwarrantage|0.021*|0.019%|
||(0.012)|(0.010)|
|Numberofloansaskedduringthepast12months|0.13274|0.051|
||(0.053)|(0.050)|
|Observations|245|245|
|Village FE|NO|YES|
|R-squared|O.217|0.168|

Notes: The sample is restricted te lottery winners who stored their crops. Dependent variable measured from the epdline survey. All other variables measured from the baseline survey. Standard errors are clustered by village and presented in parentheses. *, **, *** indicate significance at the 1, 5, and 10 percent respectively.
income ratio 10%<br>571% 5%<br>6.0 5% 4% 3% 2%<br>5.0<br>0%<br>4.0<br>Mega Large Medium Small Micro<br>3.0 220% -5%<br>2.0 84% 84% 96% -10%<br>1.0<br>- -15% -15%<br>Mega Large Medium Small Micro -20%<br>Source: own calculations based on FECUs<br><!-- End of picture text --> The low leverage of Chilean firms suggests that their access to debt financing may be constrained, while differences in financing structures across firms suggest these constraints may differ depending on firm sizes. The lower average leverage ratio of Chilean firms than that of their peers in other emerging or industrial countries may result from conservative financial management (see Figure 7). However, it could also signal that firms cannot get as much debt financing as they would want. Leveraging one’s balance sheet optimally creates indeed value added for shareholders (via the tax savings resulting from debt financing). Therefore, under-leveraging firm balance sheets as much as in Chile may not be optimal and
Policy Research Working Paper 9053

# **Abstract**

Why do some students learn more in some schools than others? One consideration receiving growing attention is school management. To study this, researchers need to be able to measure school management accurately and cheaply at scale, and also explain any observed relationship between school management and student learning. This paper introduces a new approach to measurement using existing public data, and applies it to build a management index covering 15,000 schools across 65 countries, and another index covering nearly all public schools in Brazil. Both indices show a strong, positive relationship between school management and student learning. The paper then develops a simple model that formalizes the intuition that strong management practices might be driving learning gains via incentive and selection effects among teachers, students and parents. The paper shows that the predictions of this model hold in public data for Latin America, and draws out implications for policy.

This paper is a product of the Education Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at rlemos@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
between a strong federal structure and lower per capita spending at the municipal level. However, spending per capita at the municipal level tends to go up with per capita income, with all countries with per capita income above 20,000 euros spending 1000 euros or more per capita at the local level. This one structural variable seems to predict to some extent local spending, even in widely differing systems. Overall, this table illustrates that there are many different ways to structure public finances to deliver good services at the local level

# **Table 2.1 Sub-National Government Spending Aggregates--Selected Countries of the European Union 2005 and India**

|**Sub National Govern**<br>**Country**|**ment Spending--**<br>**Municipal**<br>**Spending Euro**<br>**Per Capita**|**Selected Countri**<br>**Municipal % of**<br>**Subnational**|**es of the Europea**<br> <br>**Municipal**<br>**Spending as %**<br>**of GDP**|**n Union and Indi**<br>**Total**<br>**Government**<br>**Spending as a**<br>**Share of GDP**|**a**<br>**Municipal as %**<br>**of Total**<br>**Government**<br>**Spending**|**GDP Per**<br>**Capita**<br>**Euro 2005**|**GDP per**<br>**Capita US $**<br>**PPP 2008**|**% Urban**|
|-
Panel A in Table 1 reports results from simple regressions of potential yields of a number of ...eld crops on percentage of area under LDO leases and distance of an area from large urban centers. The potential yield data at sub-district level (i.e., DSD level) are derived from the IFPRI SPAM model for Sri Lanka. The potential yields are determined on the basis of soil quality, moisture level, rainfall and other land quality and climatic variables. The potential yields assume an ideal amount of labor to be applied irrespective of prevailing wages. The yield regressions also include a district level ...xed e¤ect to control for factors such as infrastructure, other services and demand conditions. As noted before, the district ...xed e¤ects also wipe o¤ any time invariant land or labor productivity di¤erences across districts. The results reported in Panel A of Table 1 show that, in a given district, yields are signi...cantly higher in DSDs with higher percentage of land under LDO restrictions for 11 out of 12 ...eld crops considered. For ‘other oilseeds’, the estimated coe¢ cient is positive but not estimated with precision. One might worry that the potential yield does not give us a complete picture regarding di¤erences in productivity as the LDO areas might have di¤erent levels of human capital (health and education), and as a result the actual (ex post) productivity of land might be systematically di¤erent. Panel B in Table 1 reports the estimates for actual yield which can be treated as a summary measure of all the di¤erent factors a¤ecting productivity including di¤erences in human capital and cultural norms regarding work across di¤erent DSDs. It is reassuring that the regression results for actual yield con...rm the conclusions based on potential yield in Panel A of Table 1. The evidence in Table 1 is thus very strong in favor of the conclusion that the LDO
blocks increases, this makes the VDT type converging towards the IBT type. In this paper, we focus only on the VDT type. This is justified by the fact that this structure is the most common type of tariff structure used in developing countries.

# **Estimation of consumed quantities**

With multiple pricing, the estimation of the quantities consumed by the household is also a little more complicated given that household surveys typically contain information on expenditure but not on quantities consumed of a good such as electricity. Households report expenditure as shown on the electricity bill but not the kWh consumed. However, the quantities consumed can be easily estimated.

Let _B_ = the number of tariff blocks with ; the upper kWh consumption within block and the upper expenditure threshold in block Then, consumption of electricity in kWh for each household belonging to each bracket can be calculated as follows: 24
Table 11: Average Job Quality between 2007-2021, by employment structure

|||Employment|Structure||
|---|---|---|---|---|
||(1)<br>Micro and Small Firms|(2)<br>Medium and Large|(3)<br>Self-employed|(4)<br>Employer|
|||Firms|||
|2007|0.25|0.74|0.38|0.54|
|2008|0.23|0.72|0.38|0.47|
|2009|0.24|0.71|0.39|0.51|
|2011|0.22|0.74|0.42|0.55|
|2012|0.26|0.75|0.40|0.51|
|2013|0.24|0.76|0.41|0.55|
|2014|0.22|0.75|0.40|0.49|
|2015|0.23|0.73|0.40|0.51|
|2016|0.23|0.77|0.41|0.50|
|2017|0.23|0.76|0.40|0.54|
|2018|0.22|0.77|0.40|0.54|
|2019|0.23|0.78|0.41|0.54|
|2020|0.22|0.79|0.43|0.58|
|2021|0.24|0.75|0.40|0.52|

_Notes:_ Based on data from EH 2007-2021. Estimation using a rescaled score from the first principal component of the PCA. Workers in micro and small firms are
equal to 1 if firm _i_ exported (or started exporting) product _p_ to country _j_ in year _t_ . STC (cnt) is the incidence of Specific Trade Concerns (STC) on product _p_ , normalized between 0 and 1, that has been raised in the WTO. Coefficients on spatial exporting controls are not reported for brevity. *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1

# **5.2 Alternative measure of regulation intensity: FDA prior notice**

Table 8 presents the results using an alternative proxy for the regulation intensity of products: prior notice requirements for FDA. This alternative measure captures different types of regulations compared to the STC data set, as it is concentrated mainly in food, drugs, and medical devices, imported or offered for import into the United States that require prior notice to the FDA. Using this measure, the results show that the third-country effect is weaker for FDA-regulated products in case of shallow RTAs,

> 28This frequency ranges from 1 to 30 in SPS STC and 1 to 46 in the TBT STC. The most frequently raised product in the SPS STC is 0201 meat of bovine animals (fresh or chilled), and in the TBT STC is 2204 wine of fresh grapes. SPS and TBT combined, the most frequently raised product is 0201 meat and bovine animals (fresh or chilled), raised in 68 STCs.

17
Notice that SOFES prefers low-risk students to safeguard repayment of the loans. Students whose parents own a real estate property and sign a collateral agreement are eligible for a higher loan amount than students without such a guarantee. The additional loan amount equals at maximum an additional a 10%-points of the tuition cost. Secondly, students from middle or higher-income families can receive a larger loan than students from low-income families. SOFES has to balance between its equity goal (access independent of family income), and its goal to operate as a financially viable institution. In addition, the credit level depends on the study field, categorized into three areas (Humanities and Social Sciences, Economics and Administration, and Engineering and Natural Sciences).<sup>4</sup> Finally, SOFES can recommend universities to give grants to students from relatively needy families (i.e. with an ENF lower than 0.15).<sup>5</sup> Students eligible for the SOFES loan reapply every semester. Renewal of the loan is contingent upon student performance: students only receive the renewal when they are promoted to the next term. Renewal is also contingent upon payment of interest: insolvent students do not receive the next part of the SOFES-loan.

Figure 1 shows the development of the number of SOFES recipients over time. The data for 2003 and 2004 are forecasts. Currently there are almost 20,000 students with a credit from SOFES. This is a relatively small number, compared to a total higher education enrollment of almost 2 million students. Although SOFES is only 7 years old, the student loan scheme clearly appears to be financially sustainable. As of October 2003, default rates are exceptionally low for a student loan scheme in a developing country, 7 percent. Additionally, operation costs amount to only 1 % of the value of the portfolio. The student loans carry a 2 % real interest rate, which is adjusted monthly with the rate of inflation.

**Figure 1: Growth in the number