rafmacalaba/data-use-mentions-extended huggingface dataset:
and were effective tools in encouraging safe sex while providing sex workers with access to free condoms, they can be potentially used to identify the compensating differential for condom use. We can posit the existence of an equation determining whether a sex worker always uses condoms:

# C=C(X, _S) (2)_

where C is a binary variable denoting condom use, X is the vector of sex worker characteristics, and S is a dummy indicating if the sex worker has seen the flip chart. We will estimate (2) and (1) simultaneously using instrumental variables to get unbiased and consistent estimates of the impact of condom use on income. In particular, it helps deal with an important type of unobserved heterogeneity in this market - the sex worker's physical attractiveness which will bias the estimate of the impact of condom use on income if condom use is not instrumented. Physical attractiveness is perhaps the most important attribute in determining earnings from sex work and is also very difficult to measure. Since it is not measured, estimates of the impact of condom use on sex worker wages can be seriously biased because sex workers who are relatively attractive and consequently have a high demand for their services may also be more willing to "purchase" safe sex by using condoms. However, their earnings would remain high relative to the rest of the population. This would cause condom use to show a positive correlation with the average rate per act, which is a problem similar to the bias caused by unobserved productivity on estimates of compensating differentials in other labor markets (Hwang, Reed and Hubbard, 1992). While any such unobserved heterogeneity is a potential problem in OLS estimates of prices, so long as the excluded variable - contact with a peer educator - is not correlated with the source of unobserved heterogeneity, condom use can be instrumented to correct for the bias.

As explained above the data for this analysis are from a random sample of 612 sex workers in Sonagachi from a survey conducted in 1993. The sex
With these results at hand, we investigate the reasons behind the inefficiency in the allocation of production inputs. We obtain total factor productivity (TFP) estimates applying standard modern econometric procedures and compare the resulting TFP measures across different types of firms. Simple mean comparison tests unambiguously reveal that state-owned enterprises produce less efficiently and, more importantly, exhibit lower growth rates of TFP. In a final step, we are interested in unveiling the sources of these observed productivity differences. We estimate TFP convergence models and apply matching estimators in order to assess whether labor hoarding and/or inefficient over-investment in physical capital are able to explain low levels and growth rates in TFP in state-owned companies. Our results indicate that the inefficiencies in state-owned enterprises are at least partly related to the use of input factors which makes them less competitive than their private counterparts.

The paper is organized as follows. Section two gives a descriptive view of firm growth dynamics in the Belarusian machine building industry. Section three estimates panel data models in the framework of Gibrat's law specifications. The estimates of such models allow us to assess differences in the firm growth process between state-owned enterprises and private firms. Section four focuses on the estimation of TFP at the firm level for the machine building industry. The sources of differences in TFP dynamics between state-owned and private firms are studied in section five. Section six analyzes resource misallocation in more detail using matching techniques and section seven concludes.

# **2. Firm growth in Belarus: Descriptive evidence from the machine building industry**

This section provides empirical evidence on the growth process of manufacturing firms active in the machine building industry in Belarus. It relies on a balanced panel dataset spanning the years 2005 to 2010. Machine building has been historically one of the specialization sectors of the Belarusian economy and is quantitatively one of the most relevant industrial sectors in terms of employment and production, accounting for approximately 22% of total industrial 3
or working age adults not in the labor force. By contrast, men in households with more children are more likely to

> 21 Moreover, in the high frequency baseline, the mean absolute deviation across workers is not statistically different between wage and self-employed for either men or women, and while it does differ in the 2013 GHUPS, the differences are statistically significant but relatively small in magnitude (3.3 hours for men and 1.4 hours for women).

28
, _export taxes_ and _anti-dumping_ and _countervailing measures_ , _trade related intellectual property (TRIPs) and trade related investment measures (TRIMs)_ , _movement of capital, state owned enterprises_ , _state aid_ , _competition policies_ , _intellectual property rights (IPR)_ , _investment_ , _public procurement_ and _services_ .

5 Service activities tend not to be adversely affected by labor and environmental disciplines, likely because of the high-skill intensity and intangibility of such activities.

6 Using sectoral data on value added trade, (Laget, Osnago, Rocha, & Ruta, 2018) find that deep PTAs matter more for GVC trade in services and have a larger impact for trade in intermediates between developed and developing countries.

4
hence whether impediments to changes in the mixture of banks and markets hamper economic development (Beck and Levine, 2002; Demirguc-Kunt and Maksimovic, 2002; Levine, 2002).

In this paper, we evaluate empirically the changing importance of banks and securities markets as economies develop. In particular, we focus on assessing whether economies increase their demand for the types of services provided by securities markets relative to the services provided by banks as countries grow. We do this by testing whether the economic development “returns” to improvements to both bank and securities market development change as economies grow. At a more exploratory level, we also examine whether each level of economic development is associated with an “optimal” financial structure, such that deviations from this optimum are associated with lower levels of economic activity. We use data on 72 countries, over the period from 1980 through 2008, and we aggregate the data in 5-year averages (data permitting), so that we have a maximum of six observations per country. We use several measures of bank and securities market development, including standard indicators such as bank credit to the private sector as a share of gross domestic product (GDP), the value of stock market transactions relative to GDP, and the capitalization of equity and private domestic bond markets relative to GDP.

The primary methodological contribution of this paper is using quantile regressions to assess how the sensitivities of economic activity to both bank and securities market development evolve as countries grow (Koenker and Basset, 1978). Ordinary least squares (OLS) regressions provide information on the association between, for example, economic development and bank development for the “average” country, the country at the average level of economic development. But, quantile regressions provide information on the relationship between economic activity and bank development at each percentile of the distribution of economic development. Thus, we assess how the associations between economic development and both bank and securities market development change during the process of economic development.

Besides confirming that both banks and securities markets become larger
of member states, which _de facto_ renders these agreements akin to bilateral ones. To resolve these competing considerations, we keep this set of agreements separate.

> 15Following the approach adopted in other papers that exploit the WB-DTA 2.0 data, we approximate vertical depth with the count of services related provisions, and group PTAs in quartiles of the resultant depth distribution.

> 16 Where appropriate we show results based upon individual provisions; generally, however, provisions tend to be correlated, and indeed are sometimes collinear. Hence, including many or all them comprehensively is not feasible whereas arbitrarily including only selected provisions is potentially liable to omitted variable bias.

21
# **<u>1. Introduction</u>**

Women’s bargaining power within the household is generally recognized as an important development outcome (Duflo 2012). It is commonly measured through survey questions on women’s participation in decision-making. However, research comparing the answers of husbands and wives to these survey questions has uncovered widespread and systematic discrepancies between their reports, raising concerns with this measurement approach (e.g., Anderson, Reynolds & Gugerty 2017; Annan et al 2021; Ghuman, Lee, & Smith 2006; Jejeebhoy 2002). Pinpointing the mechanisms underlying this discrepancy is crucial for understanding the relationship between self-reported decision-making and bargaining power and, consequently, the reliability of decision-making as a measure of bargaining power. However, very little quantitative work has been done to illuminate the reasons behind these disagreements.

Using data from a spousal survey of 421 farmer couples in the Philippines, this paper tests for the three potential mechanisms underlying spousal response discrepancy that have been advanced in the existing literature. First, we test for asymmetric interpretation: measurement error caused by men and women understanding survey questions in different ways. Spouses may provide diverging reports of household decision-making if they have different interpretations of what it means to make a decision, to be a decisionmaker, or what qualifies as a “major” decision, leading to diverging answers to questions on general decisionmaking. These interpretations are asymmetric if they systematically fall along gendered lines. Second, we test for asymmetric information: spouses may have different perceptions of the overall balance of decision-making within the couple because they may not be privy to decisions made in activities in which they do not participate. Third, and finally, we test for enumerator effects—specifically the effect of enumerator gender—on reports of decision-making.

Comparing spouses’ reports of agricultural decision-making, we find that discrepancies are widespread and systematic, echoing studies from a multitude of different regions and contexts. Overall, 50.2 percent of spouses disagree on who makes decisions in any given
productive sector to more productive sectors, and (ii) “organic” productivity increases in each sector because of technology and institutional effects.

Table 1. Sources and aspects of growth (1978-2004) (average annual increase, in percent)

||1978-93|1993-2004|
|---|---|---|
|GDP growth|9.7|9.0|
|Employment growth|2.5|1.1|
|Urban employment growth|5.2|2.9|
|Labor productivity growth|7.0|7.8|
|From TFP growth|3.7|2.7|
|From increasing K/L ratio|3.2|5.1|
|Memorandum item (in percent)|||
|Investment/GDP ratio|30.2|36.8|
|At end-period|||
|Share employment in agriculture|56.4|46.9|

_Source: NBS, and authors' estimates._ The economy-wide capital-labor ratio should increase along the way because labor moves from a less capital-intensive sector to more capital intensive ones, and the sectors themselves also become more capital intensive. As labor moves out of agriculture, productivity there increases, and the productivity gap between agriculture and the other sectors declines over time. Therefore, as the economy grows, the share of employment in agriculture declines. Using cross-country data, figure 1 confirms the strong association between economic development and the share of total employment in agriculture.

Figure 1. China and other countries: agricultural employment share and GDP per capita, (2001, unless otherwise specified) <!-- Start of picture text --> 80<br>Y axis: Agricultural employment, as share of total<br>70<br>60<br>50 China (2003) Thailand<br>Indonesia<br>Malaysia (1980)<br>40<br>Phillipines<br>30<br>Malaysia
# Global Dataset on Education Quality: A Review and Update (2000-2017)

## Harry Anthony Patrinos

Noam Angrist<sup>1</sup> Key words: Quality, Human Capital, Education, International, Achievement, Database JEL Classification: C8, I2, N3, J24, O15 1 We are grateful to Syedah Aroob Iqbal and Husein Abdul-Hamid who were essential contributors to this work. This work builds on co-authored work with Nadir Altinok. Particular thanks to Aart Kraay for detailed comments and contributions to the methodology and paper. Valuable comments were provided by Eva L. Baker, Eduardo Cascallar, Stefan Dercon, Deon Filmer, Roberta Gatti, Rachel Glennerster, Daniel Koretz, Silvia Montoya, George Psacharopoulos, Heiner Rindermann, Halsey Rogers, Jaime Saavedra, Shwetlena Sabarwal, Justin Sandefur, and Eduardo Velez. This paper benefited from multiple workshops held at the World Bank, World Congress of Cliometrics, American Economic Association, IDB, Oxford, USAID and FHI360. A great number of individuals and organizations supplied us with data. A special thanks to Rebecca Rhodes for access to many EGRAs. In the future, the database will be developed as part of a World Bank and UNESCO Institute for Statistics (UIS) partnership. Support from the World Bank’s Research Support Budget is gratefully acknowledged. The views expressed here are those of the authors and should not be attributed to the World Bank Group.
.052|0.033|-0.007|-0.019|
|2*Cov(sector-occupation, experience-education)|0.040|0.053|0.043|0.013|-0.009|
|Residual|0.358|0.415|0.337|0.058|-0.078|
|El Salvador||||||
|Total Variance|0.446|0.633|0.411|0.188|-0.222|
|Variance in sector-occupation|0.092|0.154|0.082|0.062|-0.072|
|Variance in skill-groups|0.064|0.028|0.023|-0.035|-0.005|
|2*Cov(sector-occupation, experience-education)<br>Residual|0.058<br>0.232|0.036<br>0.414|0.037<br>0.269|-0.021<br>0.182|0.001<br>-0.146|

_Source_ : Authors’ calculations based on data from the Socioeconomic Database for Latin America and the Caribbean, World Bank and Center for Distributive, Labor and Social Studies of the Universidad Nacional de La Plata (CEDLAS) (http://sedlac.econo.unlp.edu.ar/eng). _Note:_ Total wage variance is the variance of the log hourly wage in the household surveys data set. Variance in skill-groups is the variance of the log real hourly wage that is explained by a full set of gender, education, and experience dummies, and their interaction. The variance in sector-occupation is the variance of the log real hourly wage that is explained by a full set of sector-occupation dummies. AKM = Abowd, Kramarz, and Margolis (1999).

60
rules, i.e. not restricting trade unnecessarily.

We focus on two types of NTMs to tease out such heterogeneity. The first is _antipest treatment requirements_ (APT), which we use as an example of “virtuous NTM”. Most countries apply this type of measure to eliminate a potential negative externality in agricultural products, i.e. the presence of plant and animal pests or disease-causing organisms. The second type of NTM is _pre-shipment inspections_ (PSI), which we deem an example of “protectionist NTM”. This measure requires the goods to be inspected at the port of departure. Only a handful of mostly low-income countries applies PSI, typically to ensure that the import declaration lists the correct classification of the goods to be imported as a way of detecting improper importing activities. Unlike APT, PSI appear redundant in a country like Indonesia, where the customs agency applies a risk management system aiming to detect suspicious shipment at the border.<sup>4</sup> In the absence of clear benefits, the bulk of the effect of this measure is likely to be the increased compliance costs for imports.

The analysis leverages the unusual richness of Indonesia’s manufacturing data to decompose firms’ revenue-total factor productivity (TFPR) into quantity-total factor productivity (TFPQ) and markup. The results of the analysis are in line with our priors linked to the different features of these NTMs. The introduction of APT on a plant’s inputs results in an increase in both the plant’s technical efficiency and its markup, consistently with an increase in the quality of imported inputs. On the other hand, the application of PSI on inputs reduces the markup and the TFPR of the plant. When applied on the same product produced by the plant, the PSI increases the markup, in line with the increased protection for domestic producers.

We are able to explore in detail the mechanism behind the negative effects of input PSI on plants’ performance. This enables the paper to provide a third contribution by unveiling
(USD 1.90$ International Poverty Line) <!-- Start of picture text --> Chronic Poverty Status by Geographic Region - (USD 1.90$ International Poverty Line)<br>90%<br>80%<br>70%<br>60%<br>50%<br>40%<br>30%<br>20%<br>10%<br>0%<br> NC urban NC rural NE urban NE rural NW urban NW rural SE urban SE rural SS urban SS rural SW urban SW rural<br>never poor transitory poor chronic(always) poor<br><!-- End of picture text --> Source: Authors’ estimates based on GHS Waves 1-3 53
# **8 Conclusions**

Severe climate and environmental related natural disasters can have long-lasting negative effects on bank asset quality. Using a large panel dataset and the local projection method, this paper presents a comprehensive analysis on the effects of disaster events on NPLs and other important banking sector variables, and also discusses policies to monitor and mitigate these adverse effects. Severe disaster episodes are estimated to increase system-wide NPLs by between 0.5 and 0.6 percentage points after two to three years. The estimated effects are found for multiple regions across the developing world and for most income groups and four different types of disasters, although cross-country results are less significant for climate related disasters than for environmental ones. To partially address important caveats of the cross-country results, including data quality and granularity, we also look at a country-specific example of the effect of typhoons on NPLs in the Philippines and find the same relationship holds, but the estimated effects are much larger. In addition, we also present tentative evidence that climate change and environmental related disasters could reduce bank intermediation efficiency, lower system-wide liquidity relative to deposits and increase the regulatory capital ratio, although they may not necessarily reduce the overall volume of lending to the private sector. While we do not identify any specific transmission channel, our results point to multiple channels from physical risks to financial stability at work, including through credit risks, operational risks and liquidity risks.

Future extensions using more granular data would be promising. To arrive at a generic estimate using the largest possible sample, we have chosen to work with data at the country-year level. This has very likely biased us against finding stronger results, as disasters tend to affect a specific geographical area within a country disproportionately, and financial institutions serving specific areas. In general, stronger results are likely found at the more granular geographical level. While we try to mitigate this concern with the case study of the Philippines, a global sample using balance-sheet-level loan data and geographical NPL data would potentially improve the results while allowing us to explore
**Financial (Dis-)Information: Evidence from a Multi-Country Audit Study**<sup></sup>

Xavier Giné World Bank Rafael Keenan Mazer World Bank Keywords: financial information, audit study. JEL codes: D14, G18, G21, O16.

>  Giné: xgine@worldbank.org. Mazer: rmazer@worldbank.org. We thank CONDUSEF in Mexico, the Superintendencia de Banca y Seguros (SBS)  in Peru and in particular Juan Carlos Chong Chong, Jesus Chavez Ugalde, Maria Fernanda Saldivar Cortes, Mariela Zaldivar Chauca for their constant encouragement and support. We also thank the team at IPSOS for data collection and to Cristina Martínez, Adrià Llach and Ildrim Valley for superb research assistance. We are grateful to Sumit Agarwal, Santosh Anagol, Matthew Bird, Eva Gutiérrez, María Soledad Martínez-Peria, David Medine, José Luís Negrín, Claudia Ruiz, Enrique Seira and Bilal Zia for helpful comments and to the Russian Trust Fund, Knowledge for Change Program and the Strategic Research Program of the World Bank for funding.
training provider data collected during the matching meetings in 2013, and the endline applicant data collected from mid-2017 through May 2018. On average the endline data were collected about four years after the start of training. Since apprenticeships typically last three years, the endline data would capture short-run returns to training. The endline data focus primarily on labor market outcomes, but they also measure training history and include a trade-specific skills test designed in collaboration with local Ghanaian industry experts. Focusing only on the set of applicants that were randomized into the treatment and control groups, we find that the randomization was balanced across both groups. Typically, evaluations of training programs in developing countries are plagued by high attrition (McKenzie, 2017). In this study, sample attrition was relatively low (10 percent) and balanced across the treatment and control groups. This provides some assurance about the validity of our experiment. Our data show that the offered under the NAP was the same as that in the traditional training essentially apprenticeships available in the market. Given the geographic scope of our evaluation, our results provide insights into the effectiveness of the traditional apprenticeship system in Ghana.

We report three main findings. First, we find that access to the program led to modest increases in the probability of starting an apprenticeship, the probability of completing training, and the duration of training. Youth offered training under the NAP were 13 percentage points more likely to commence training, and 10 percentage points more likely to complete training, than the control group. Because the training completion rate among the control group was relatively low (25 percent) compared with its starting rate (63 percent), this suggests that the program was relatively more effective at encouraging the completion of training than it was the start of training. In addition, the treatment group completed four more months of training than the control group. The data suggest that female participants in cosmetology were the most responsive to the program offer, while male participants in construction were the least responsive (in terms of completion)