rafmacalaba/datause-encoder-data huggingface dataset:
Heterogenous Teacher Effects of Two Incentive Schemes: Evidence from a Low-Income Country<sup>_∗_</sup> Felipe Barrera-Osorio<sup>_†_</sup> , Jacobus Cilliers<sup>_‡_</sup> , Marie-H ́el`ene Cloutier<sup>_§_</sup> Deon Filmer<sup>_§_</sup> _Keywords:_ Student achievement; Teacher incentives; Learning outcomes; Recognition rewards _JEL Codes_ : I21; I28; J33; J45; O15

> _∗_ Acknowledgements: We thank a number of colleagues and institutions that have assisted at various stages of the evaluation. Nathalie Lahire, Karine Angles, and Assane Dieng who played an instrumental in support the preparation and implementation of the evaluation. Adama Tiendrebeogo who provide both essential in-country field work coordination and research assistance throughout. Diwakar Kishore, Youn Park, and Ana Alvarez who provided critical research assistance to the project. Faya Fran ̧cois Bourouno and Abdoul Aziz Diallo who supported in-country field work and supervision of data collection. This work would not have been possible without the impressive commitment from the Ministry of Pre-University and Civic Education (MEPU-EC), especially the teams of the Inspection G ́en ́erale de l’Education (IGE) and the<sup> ́</sup> Cellule Nationale d’Evaluation<sup> ́</sup> du Syst`eme Educatif<sup> ́</sup> (CNESE). We acknowledge funding from the Strategic Impact Evaluation Fund (SIEF) and the Research Support Budget (RSB) of the Development Economics unit (DEC). All findings and interpretations in this paper are those of the authors, and do not necessarily represent the views of their respective institutions or the Government of Guinea.

> _†_ Vanderbilt University

> _‡_ Georgetown University. ejc93@georgetown.edu

> _§_ World Bank
5 efforts. We conclude with a discussion section including possible interventions and lessons for policy.

# 2. Data and Methods

## **2.1 Data Sources**

### **2.1.1 Social Norms Sample**

We primarily present findings from a recently completed survey in KRI in 2018, that systematically measures social norms and cultural beliefs, and refer to this as the “social norms sample” in the rest of the paper. A random sample was drawn from the sample frame of the SWIFT survey implemented by the Poverty and Equity Global Practice at the World Bank. Districts from all three governorates of Erbil, Sulaymaniyah, and Dohuk were included, except for districts with a population of less than 30,000. The instrument we use was specifically developed to measure social norms in an urban context, and we, therefore, exclude rural areas. The number of clusters sampled from the remaining districts was in proportion to the population. Finally, the required number of households was randomly sampled from the list of households in each cluster in a given district, along with a replacement list of households.<sup>6</sup> Both a female and male counterpart in each household was included, restricting to spouses, father-daughter, and brother-sister relationships, in order to compare perceptions of the counterpart’s beliefs, with actual beliefs held by the counterpart. We oversampled households with working women, to assess if social norms and beliefs were different for the women and men in these households, and set a target to survey 33% working women (out of all the women we interviewed). Randomly drawn households were called initially to screen whether there was a male-female counterpart as described above, and to meet the target on surveying working women.<sup>7</sup> Given that we restricted household selection to those with women between the ages of 20-55 and with a male counterpart with the relationships described above and oversampled households with working women, we cannot calculate labor force participation rates or unemployment rates from this sample. However, our results are representative of both nonworking and working women within this age range (and their male counterparts), and of urban areas in all the three governorates in KRI.

In collaboration with Kurdistan Regional Statistics Office (KRSO), we partnered with a local survey firm, Sheekar Research Company, to implement the survey in August and September 2018. The instrument was initially translated into both Kurdish and Arabic, digitized, pilot-tested and administered on tablets.

> 6 However, households where the SWIFT survey had already been conducted were excluded.

> 7 Given the low female labor force participation rates in KRI, it was particularly challenging to find households where women worked, and several samples had to be drawn to meet this target.
# **1. Introduction**

Structural reforms can raise incomes, but the costs of reforms might fall disproportionately on some population groups, increasing inequality and fueling arguments opposing change. The risk of losses for large segments of society could be a powerful shaping force of economic and social policies. Identifying who will likely lose out from reforms and managing people’s perceptions about their future welfare is crucial for consolidating political support for costly measures and moving countries to higher growth trajectories. It might be particularly important to understand the factors that shape support for structural reforms for the middle-income countries in Europe, Central Asia, and elsewhere that are facing challenges in accelerating economic growth and raising their populations’ standards of living.

This paper investigates whether support for education reforms is affected by expectations about future economic mobility. The focus on the subset of structural reforms related to education stems from the evidence that investments in human capital play a crucial role in driving economic growth (Hanushek and Woessmann 2008) and that education reforms are a powerful policy channel through which countries can improve the inclusiveness of growth by leveling the playing field and enhancing the upward economic mobility of disadvantaged groups (IMF 2019).

The analysis is based on data on 39 countries in Europe, Central Asia, and the Middle East and North Africa from the 2010, 2016, and 2023 rounds of the Life in Transition Survey (EBRD 2023). This sample of countries is analytically interesting because, despite progress made over the last several decades, these countries lag the high-income countries in educational achievement (World Bank 2018). Reforms aimed at improving the quality of education are also more costly and politically challenging than efforts to expand access to education, which helped countries move from low-income to middle-income status (Aiyar and others 2013). Profound education reforms that take years to achieve lasting effects require a strong, broad-based, durable coalition at all levels of society.

The paper finds that individuals who expect themselves or their children to be upwardly mobile are more likely to support tax-financed education reforms than individuals who do not. This relationship is robust to various formulations of mobility expectations and persists across several 2
Policy Research Working Paper 5338

# **Abstract**

This paper examines whether and to what extent amendments in inheritance legislation impact women’s physical and human capital investments, using disaggregated household level data from India. The authors use inheritance patterns over three generations of individuals to assess the impact of changes in the Hindu Succession Act that grant daughters equal coparcenary birth rights in joint family property that were denied to daughters in the past. The causal effect is isolated by exploiting the variation in the timing of father’s death to compare within household bequests of land given to sons and daughters in the states of Maharashtra and Karnataka. The analysis shows that the amendment significantly increased daughters’ likelihood to inherit land, but that even after the amendment substantial bias persists. The results also indicate a robust increase in educational attainment of daughters, suggesting an alternative channel of wealth transfer.

This paper—a product of the Agriculture and Rural Development Team, Development Research Group—is part of a larger effort in the department to explore the role of policy reforms promoting equity and poverty reduction for women in developing countries. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at agoyal3@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
11 In order to investigate the determinants of market efficiency, we would like to create a summary measure of efficiency that lumps together the two dimensions of liquidity: transaction costs and the informational quality of stock markets and then study the determinants of this “composite efficiency measure”. Figure 6 plots such a composite index. It is constructed from the transaction costs and synchronicity measures, first by standardizing each one (subtracting the mean and dividing by variance), and then averaging the two measures.

Figure 6. Composite measure of efficiency <!-- Start of picture text --> Standardized score<br>8<br>Mex<br>US<br>6<br>CHL<br>Esp UK<br>Kor<br>HKMys RF<br>Tur<br>4 Sgp<br>Jpn<br>Tha<br>Idn<br>2 Phl<br>Chn<br>0<br><!-- End of picture text --> However, the difficulty with this index is that its components move in opposite directions in many countries in our sample. That is, it would appear that there are a significant number of countries which have relatively low transactions costs as a result of good physical or market infrastructure but at the same time rank low in terms of the quality of information disclosure and the exercise of corporate governance, resulting in high price synchronicity. This point can be seen from Figure 7, which shows the distribution of the countries in our sample (by region) along the two dimensions of transactions costs and quality of information disclosure. A sizable number of countries rank well in terms of transactions costs but not synchronicity, but equally a number of countries rank well on synchronicity but not in terms of transactions costs. As can also be seen from the figure, about 75 percent of the EAP countries in our sample rank in the

> 60% of B, owns 90% of S, and has a majority in both boards of directors.  Company S wants to dispose of some assets and Mr. James proposes that company B buy them, at a price that is above market value.  The transaction is approved, and the mandated disclosures are made.  However, since the transaction is unfair, shareholders of B sue Mr. James and any other parties that approved the transaction.  Using this common framework, Doing Business then ask lawyers from each country a set of questions regarding what disclosures should have been obligatorily made, what is the specific liability that directors and managers face, and how easy it is for shareholders to sue those who were responsible.  A score is then computed for each of these categories.
Policy Research Working Paper 7471

# **Abstract**

Mexican wage inequality rose following Mexico’s accession to the General Agreement on Tariffs and Trade/World Trade Organization in 1986. Since the mid-1990s, however, wage inequality has been falling. Since most trade models suggest that output prices can affect factor prices, this paper explores the relationship between output prices and wage inequality. The rise of inequality can be explained by the evolution of the relative price of skill-intensive goods relative to unskilledintensive goods, but these prices flattened by 1999 and thus cannot explain the subsequent decline in wage inequality. An alternative trade model with firm heterogeneity driven by variations in the relative price of tradable relative to nontradable goods can explain the decline in wage inequality. The paper compares this model’s predictions with Mexican inequality statistics using data on output prices, census data, and quarterly household survey data. In spite of the model’s simplicity, the model’s predictions match Mexican variables reasonably well during the years when wage inequality fell.

This paper is a product of the Office of the Chief Economist, Latin America and the Caribbean Region. 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://econ.worldbank.org. The authors may be contacted at halliday@hawaii.edu, robertson@tamu.edu, or dlederman@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
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We make this characterization because it is likely important for making inferences about market access interests from directly observable trade data. For disputes challenging observable policy changes, there is arguably a period before the imposition of the policy during which the respondent was not violating its WTO commitments or obligations. For these types of disputes, examination of the trade data from prior to policy implementation may provide information on the level of a respondent country’s market access commitment, and the size of the trade at stake for the complainant and other potential exporting countries. However, disputes that challenge the failure to reform ‘old’ policies do not have such a period in which a WTO-consistent policy was in effect. In these disputes, examination of the trade data may only provide a lower bound for the market access commitment of the respondent, as well as the potential trade interests of the complainant.

# **2.2.3 Global versus partial policies and respondent’s treatment of non-complainant exporters**

A final characterization of the WTO data is based on whether the policy under dispute was applied by the respondent in such a way that can negatively affect all of its trading partners – defined here as a ‘global’ policy – versus a policy applied in such a way that negatively affects only selected trading partners – defined here as a ‘partial’ policy. Examples of global policies would be a WTO-inconsistent application of an internal tax, subsidy, or regulation imposed on an MFN-conforming basis. Examples of partial policies would be a WTO-inconsistent application of an antidumping or countervailing duty or trade preference scheme.

While this characterization has parallels to whether the main WTO issue is an alleged violation of national treatment (global policies) or MFN treatment (partial policies), we note that our subjective data characterization is based on only a judgment from policy information of how the respondent applied its allegedly WTO-inconsistent policy vis-à-vis non-complainant exporters. The characterization is not based, for example, on whether the complainant’s formal allegation arising in the dispute refers to a claim under GATT 1947 Article I (MFN Treatment) versus Article III (National Treatment).<sup>8</sup> Furthermore, our characterization also does not rely on an ex post empirical assessment of observed changes to the trade flow data arising from the import policy.

> 8 Such a reference would not be possible for all of the disputes in our sample given that not all of them move beyond the consultations stage to the formal Panel stage in which complainants must fully articulate their allegations of respondent misconduct. Furthermore, the two allegations are also not mutually exclusive. For a discussion of some of the key economic aspects of National Treatment in the GATT and WTO, see Horn (2006). For a discussion of the role of MFN Treatment, see Horn and Mavroidis (2001).

10
many of its effects on students are of course not measurable in test scores for college admission.

The OLS results, shown in Table II, show that Fe y Alegría students perform 0.05 and 0.06 standard deviations higher in Verbal Score and Math Score respectively, after correcting for observables. Especially interesting in these regressions are the coefficients on several of the control variables. As might be expected, younger students tend to do better, as do students with fewer siblings. Instead of linear influences, however, the effects of family income and house quality seem to be in an inverted-U shape. Wealthier students living in “luxurious” houses actually tend to do worse on the exams than poor students. This may be because they have secured university admission through other universityspecific tests and thus do not take the PAA seriously.

Propensity score matching gives qualitatively similar results. The probit regression used to generate the propensity scores is shown in Table III, confirming anecdotal evidence that poorer students tend to be selected into (graduation from) Fe y Alegría. Table IV shows the Average Treatment Effect for Verbal Score and Math Score are 0.11 and 0.08 standard deviations (although the effect on verbal scores is not significant).

Differences between parameter estimates in OLS and matching can be attributed to a heterogeneous treatment effect, as discussed in depth in Angrist (1998). Regression and matching estimators weight the underlying treatment effects differently: the weights applied in matching estimators are proportional to the probability of treatment, whereas the weights applied in OLS are proportional to the variance of treatment. The most basic test of a heterogeneous effect is to test the joint insignificance of the OLS parameters on the interaction between the treatment effect and the observables:
Table A2: Share of High Educated and Skilled Workers, by Country and Sector of Activity

||Manufacturing|Services|Agroindustry|Construction|Other|Total|
|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|
|Panel A. Share of H|igh Educated Workers||||||
|Cambodia|10.76|22.64|0.94|4.79|-|16.28|
|China|20.31|53.20|-|-|-|31.50|
|Indonesia|47.40|-|64.33|-|-|47.89|
|Malaysia|17.53|-|-|-|-|17.53|
|Philippines|27.24|-|-|-|-|27.24|
|SouthKorea|37.64|45.88|-|62.14|18.89|43.88|
|Thailand|24.06|-|-|-|-|24.06|
|Vietnam|11.41|32.00|-|28.33|80.00|14.43|
|Panel B: Share of S|killed Occupations||||||
|Cambodia|0.166|0.713|0.458|0.353|-|0.572|
|China|0.342|0.766|-|-|-|0.480|
|Indonesia|0.201|-|0.115|-|-|0.199|
|Malaysia|0.239|-|-|-|-|0.239|
|Philippines|0.258|-|-|-|-|0.258|
|SouthKorea|0.328|0.378|0.521|-|0.333|0.372|
|Thailand|0.182|-|-|-|-|0.182|
|Vietnam|0.217|0.634|0.358|-|1.000|0.274|

Source: Author's calculations are based on the _Enterprise Suveys_ (World Bank) Note: Panel A reports the mean of the share of high educated workers (more than the secondary education), by country and sector of activity. Panel B reports the mean share of skilled occupations (management, professionals and nonproduction workers), by country and sector of activity.
composition of top managers using cross-country comparable firm-level data across a wide spectrum of 87 developing countries is a rarity in the existing literature.

Presence of female top managers is not uncommon in our sample. Projecting to the private non-agricultural part of the economies that is targeted by the survey, 18.8 percent of the firms have a female top manager. Our exploration of the data confirms that the presence of female vs. male managers is significantly higher in the service sectors relative to manufacturing. However, this difference between service and manufacturing sectors is entirely due to firms in the retail sector with little contribution from the remaining service sectors such as wholesale, construction services and the residual category of other services. In other words, for gender composition of top managers, the retail sector is special not just vis-a-vis the manufacturing sector but also the rest of the service sectors. For example, our findings show that depending on the specification used, the likelihood of having a female manager is higher for a retail firm compared with a firm in the manufacturing sector by 4.5 to 8.1 percentage points. The difference is statistically significant and also economically large given that in the full sample only 18.8 percent of the firms have a female manager. We also find strong evidence that the proportion of female managers in the retail sector vis-à-vis manufacturing or the rest of the economy is particularly high among the relatively small firms and among firms located in the relatively small cities in our sample. Hence, use of firm-level or micro data is helpful in order to explore heterogeneity across data points within a sector – a possibility that is not available using macro or industry level data.

The findings from this study could be useful from the policy point of view. Given a greater presence of top female managers in the retail sector, policies aimed at improving the livelihood of females may find it attractive and optimal to expand the retail sector through 3