rafmacalaba/data-use-mentions-extended huggingface dataset:
enterprises carried out by the Government of India. Our primary manufacturing data are taken from surveys conducted in fiscal years 2005-06; the services sector data come from 2001-02. Even though these surveys were undertaken over two fiscal years, for simplicity we refer below to the initial year only. This section describes some key features of these data for our study, and our unpublished data appendix (available upon request) provides greater details. Appendix Table 1 provides a complete list of data sources and years employed. Nataraj (2009), Kathuria et al. (2010), Hasan and Jandoc (2010), Dehejia and Panagariya (2010), and Fernandes and Pakes (2010) provide detailed overviews of similarly constructed databases.

It is important to first define and characterize the distinction between the organized and unorganized sectors in the Indian economy, which our estimations consider separately. These

> 4 Our definition of entrepreneurship places this study in a well-established literature examining the locational decisions of plants, primarily studied in developed countries. Examples include Due (1961), Oakland (1978), Schmenner (1982), Carlton (1983), Bartik (1995), and McConnell and Schwab (1990).

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|-1.386***|
||[0.013]|[0.052]|[0.030]|[0.010]|[0.039]|
|Other Foods|9.753***|2.870***|8.923***|10.154***|7.429***|
||[0.111]|[0.043]|[0.168]|[0.223]|[0.231]|
|Observations|21,239|6,766|4,785|5,743|3,945|

Standard errors in brackets, 100 bootstrap replications *** p<0.01, ** p<0.05, * p<0.1 Source: 2012 1-2-3 Survey, DRC Table 5 shows expenditure elasticities for the aggregate commodities. Expenditure elasticities are computed in a two-step approach. First, they are computed for each household; then sample mean and standard error are calculated using bootstrap. Elasticities are statistically different from zero for all commodities in each area, showing that a linear demand system would provide inadequate estimates of welfare losses.

From these results, aggregate commodities display different expenditure elasticities depending on the analysis group. Among the non-poor (in rural and urban areas), cereals are inferior goods. Animal proteins (meats and fish) are normal goods. They are luxury goods in rural areas, whereas they are necessity goods in urban areas for both the poor and the non-poor. For all the analysis groups, tubers and plantains are inferior goods. An important fact from this table is that a price change is bound to have an income effect for most commodities; the size of the demand response to the price change will then depend on both income and substitution effects; the latter is captured by compensated elasticities.

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# **1. Introduction**

The COVID-19 pandemic has led to severe economic disruptions in the operations of businesses around the world. A prior work of the World Bank documents the impact of COVID-19 on firms in developing countries using the first wave of the Business Pulse Surveys (BPS) data collected during May-August 2020 in 51 countries covering more than 100,000 firms (Apedo-Amah et al., 2020). The analysis of this data found that the COVID-19 pandemic generated an average 49% drop in sales relative to 2019. This decline in sales was not only large but also persistent, as the drop in sales continued to be more than 40% even 4 months after the peak of the crisis (defined as the sharpest drop in mobility). During the May-August 2020 period, firms had been mostly holding on to workers, with only about a fifth of businesses resorting to lay-offs. However, most businesses (64%) made some adjustments to their payroll primarily by reducing hours, wages, or granting leave to workers. Financial risks driven by defaults and bankruptcies were large, with more than 55% of micro, small, and medium enterprises falling into arrears or expecting to be in arrears within the next 6 months from the time of the first wave of BPS. With the physical distancing norms in place, firms were found to be increasing the use of digital technology. About 34% of businesses started to use or increased the use of digital platforms and 16.5% increased their investment in digital solutions (Apedo-Amah et al., 2020).

The public health measures (e.g., physical distancing, strict lockdown of non-essential businesses) that dampened business operations in the first wave were largely retracted by October 2020 - March 2021, allowing activity to recover. Although business is not as usual yet and we are still in the midst of the crisis with more transmissible and virulent strains of the virus spreading (World Bank, 2021), this paper attempts to uncover the possible patterns of
using very granular barcode level price data, and show that local prices increase in winning counties a year after the MDP establishment is announced. The reason we go down to looking at the barcode-level prices rather than using off-the-shelf regional price indexes is described succinctly in Handbury and Weinstein (2015). They point out that even though the variation in prices across locations is central in economic geography, regional price indexes are plagued with problems such as product heterogeneity bias (consumers can purchase different varieties within a product category across locations), retailer heterogeneity bias (consumers can shop in systematically different stores with different amenities), and purchaser heterogeneity bias (purchase prices may reflect different shopping intensities of consumers). Regional price indexes typically do not correct for these biases because without barcode data it is difficult to find the identical good in two different locations. By comparing the same UPC variety sold in the same store and by looking at the intensity of shopping time changes before and after the MDP establishment in winner compared to loser counties, we are able to address these biases pointed out by Handbury and Weinstein (2015).

We also show that wages only increased for skilled workers, and therefore rising local prices translate into a direct fall in real wages for unskilled workers. In terms of methods, we follow the literature that uses event study methods to study the effects of MDPs by comparing the outcomes in winning versus immediate runner up counties, such as in Bloom et al. (2019), Kim (2020), Greenstone et al. (2010), Patrick (2016), Patrick and Partridge (2019), Giroud et al. (2021), and Slattery and Zidar (2020).

Second, we micro-found this mechanism of rising local inflation due to the MDP establishment by introducing a new partial equilibrium model with non-homothetic consumer preferences over consumption and leisure, and retailers who respond to consumers’ falling price sensitivity to rising wages by increasing mark-up. This relates our work to the trade and macro literature that studies price and mark-up
section, we briefly discuss implications for policy and research. There, we highlight the scale of the problems facing policy makers and other stakeholders, discuss how the findings can help improve our understanding of the growing experimental literature on education in developing countries, and point to avenues for future research.

# **2. Measuring teacher effort, knowledge, and skills: The Service Delivery Indicators**

The Service Delivery Indicators (SDI)—an ongoing Africa-wide program with the aim of collecting informative and standardized measures of what primary teachers know, what they do, and what they have to work with—grew out of concern about poor learning outcomes observed in various student tests as well as evident shortcomings in fast-expanding systems of education. This policy failure is evident throughout the education service delivery chain, but it is most clearly (and perhaps most damagingly) manifested at the school level.

The delivery of education in many low-income countries is characterized by centralized, but typically weak, state control and often low-capacity, locally governed institutions for education provision. At the same time, the institutional incentives for performance are largely missing, with both career progression and financial rewards delinked from performance. Hiring, salaries, and promotions are largely determined by teachers’ seniority and initial educational qualifications, and are unrelated to effort or performance. In most settings, parents have little influence on how teachers are hired or schools are managed, and the various state and local authorities provide limited technical support or supervision.

Teacher salaries account for the largest single item in education expenditure, in countries at all income levels. In Sub-Saharan Africa, salaries for teachers and education officials account for more than 70 percent of the expenditure in education (UIS/ISU 2013) and approximately 12 percent of total government expenditure. Teachers in Sub-Saharan African countries earn on the order of 4 times average GDP per capita (UIS 2011) whereas in high-income countries the ratio is closer to 1.5 (Bruns and Luque 2014).

In Africa, the public sector is the dominant actor
# **3.4 Canada (CAN)**

Canada’s antidumping process has a two-track determination of injury and dumping. Dumping determinations are handled by the Anti-Dumping and Countervailing Directorate of the Canada Border Services Agency (CBSA), while injury determinations are made by the Canadian International Trade Tribunal (CITT). Both bodies initiate their own investigations, each followed by preliminary and final decisions. Note however that this system was not used prior to mid-2000. Prior to 2000 the CBSA was known as the CCRA (Canada Customs and Revenue Agency) and the CITT did not initiate a separate investigation in the preliminary phase. The CCRA would briefly discuss whether injury was evident if they found preliminary evidence of dumping. Then the CITT would begin a separate injury investigation only if the case proceeded to the final phase. Alternatively, if an interested party (such as a company named in the case) referred the preliminary issue of injury to the CITT, the tribunal would hold a preliminary investigation.

A number of data sources were used to collect the Canadian information. The primary resources were the websites of the CBSA and the CITT. If possible, any discrepancies in the data (such as a difference in a date listed in two separate sources) were decided in favor of the information found in the actual case files on these sites. However, for pre-1995 CCRA cases, hard copies were used because the site did not have coverage of that era. They were provided by the Anti-Dumping and Countervailing Directorate and only covered final determinations. Therefore, information on preliminary CCRA cases - before 1995 was gathered from three sources: the CBSA Historical Listing (http://www.cbsa <u>asfc.gc.ca/sima/historic-e.html), a list of CCRA decision dates provided by the Directorate, and the</u> _Canada Gazette_ microfiche collection at Harvard University. Similarly, CITT cases before 1988 were not available online, and information on these was gathered from the Canada Gazette microfiche.

The
organization cannot be overruled by the central government. The relationship between central and district government agencies therefore accords closely to the theoretical literature’s notion of de facto ‘agent authority’. In contrast, within an organization a manager has the ability to overrule the agents she employs on business decisions. By contrasting the differences in information between principals (central tiers of government or managers) and agents (district governments or employees) under these two regimes allows us to assess the impact of the nature of authority on information acquisition.

We can also use the fact that different organizations in the Ethiopian context are managed differently (as will be shown below) to investigate the impact of environments that differ in terms of how they value the acquisition of information. As the culture of an organization becomes more empirical, we can interpret this as an increase in the individual rewards for information use. We can thus test the impact of mediating incentives on the likelihood of information acquisition. **2.2 Survey of Public Officials** The implementation of any of the three core tasks of public administration outlined above requires information on the characteristics and thus needs of the citizens they serve. To elicit an understanding of the information public officials have about their environment and to understand the incentive environments in which they operate, between June and September 2016 we held face-to-face interviews with 1,831 public administrators in 382 organizations across the three tiers of Ethiopia’s government. Table A1 lists the organizations included in our study, and Figure A1 provides a map of the district governments we sampled. Our analysis focuses on the agriculture, education, health, revenue, and trade sectors only. For each of these five sectors, we sample the main ministry, all the corresponding regional offices, and a geographically representative sample of corresponding district offices from across the country.<sup>7</sup> Within each organization, we interviewed senior managers and a representative sample of their staff. We limit our scope to the professional grades of technical and administrative officers
they benefitted from it. Once these establishments were randomly selected, the SSI staff then tracked all relevant variables for all time periods available in the database for that employer. In practice, though, information prior to 2004 was scattered and unreliable, and we decided to keep observations starting from 2004 only.

A source of duplication in the raw dataset can come from edits in declarations that the employers submit after the end of the month, such as editing the days worked or gross wages. We investigated and prepared the data meticulously together with the technical team of SSI in order to help them prepare and share the anonymized dataset with us for the purpose of this analysis. Finally, we reorganized the dataset we received from SSI to generate a dataset that can be readily analyzed.

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Poverty Gap (%)<br><!-- End of picture text --> _Note: Figure shows relative percent change from the baseline under the intermediate scenario._ Based on the results of the simulation, under the intermediate scenario, the Learning Poverty Gap will rise by 2.1 percentage points from 9.5% to 11.6% for low- and middle-income countries. The increase in Learning Poverty Gap is particularly high in in Europe and Central Asia and East Asia and the Pacific (Table D2). This means that moving forward, these countries will need to focus on children at the bottom, including those out of school (who are assumed not be learning) to ensure that they are not left behind.

While the Learning Poverty Gap measure shows how far students are behind the minimum proficiency level on average, it is not distribution-sensitive, and cannot distinguish between changes in the learning gap driven 11
# International Harmonization of Product Standards and Firm Heterogeneity in International Trade

Jos ́e-Daniel Reyes<sup>_∗†_</sup>

## **JEL Classification Numbers:** F12, F13.

**Keywords:** Firm heterogeneity, Productivity, Standards, Microdata.

> _∗_ International Trade Department (PRMTR), the World Bank, e-mail: _jreyes2@worldbank.org_

> _†_ I am deeply in debt with Rod Ludema and Brad Jensen for delightful discussions to previous versions of this work. I thank John Wilson for kindly sharing the World Bank EU electrotechnical product standards database with me. I also thank Andrew Bernard, Peter Schott, Francis Vella, Oliver Cadot, Justin Pierce, participants at the U.S. International Trade Commission Seminar and at the Latin American and Caribbean Economic Association 2010 meeting for helpful comments and discussions. The research in this paper was conducted while the author was a Special Sworn Status researcher of the U.S. Census Bureau at the Center of Economic Studies Research Data Center in Washington DC. Any opinions and conclusions expressed herein are those of the author and do not necessarily represent the views of the U.S. Census Bureau, the World Bank, its Board of Directors or the countries that they represent. All results have been reviewed to ensure that no confidential information is disclosed. All remaining errors are my responsibility.

<mark>1</mark>
- (i) The list of consumption items included in the questionnaires is mostly consistent with major headings in COICOP classification (2 digit), with the sole omission of expenditure on “alcoholic beverages and tobacco” and “recreation and culture”.<sup>20</sup> However, in some cases the list of consumption items in the HNAP 2022 questionnaire includes items at lower levels of aggregation, including some coarse expenditure headings open to interpretation by respondents (for example: personal care, childcare, NFIs...).

- (ii) No information is available to properly account for housing costs. Information on expenditure on rent paid is available for market tenants, which only constitute 10 percent of households, a sample to small and geographically segregated to attempt estimating any model to impute for the value of housing services consumed by owners or other nonmarket tenants.

- (iii) No information is available on consumer durables possessed by the household.

Another important challenge that needs to be addressed to estimate monetary poverty, is to control for spatial price differences. Unfortunately, CBS does not produce any subnational CPI index and lacking detailed information on food and non-food consumption items, it is not possible to estimate one using HNAP survey data. A possible approach is to use a proxy food price index constructed using “standard food basket” price estimates at the governorate level produced by WFP (Table 6). In Syria, WFP standard food basket is set at a group of dry goods providing 2,060 kcal a day for a family of five during a month. The basket includes 37 kg bread, 19 kg rice, 19 kg lentils, 5 kg of sugar, and 7 liters of vegetable oil. WFP provides governorate level estimates on such basket in its monthly “market price watch bulletin”, building on market level price information it has been collecting in the country since 2011.

_Table 6: Spatial price deflator based on WFP Standard Food Basket (SFB)_

||Standard food basketprice(SYP)
Policy Research Working Paper 5874

# **Abstract**

Middle class values have long been perceived as drivers of social cohesion and growth. This paper investigates the relation between class (measured by position in the income distribution), values, and political orientations using comparable values surveys for six Latin American countries. The analysis finds that both a continuous measure of income and categorical measures of incomebased class are robustly associated with values. Both income and class tend to display a similar association to values and political orientations as education, although differences persist in some important dimensions.

Overall, there is no strong evidence of any “middle class particularism”: values appear to gradually shift with income, and middle class values are between the ones of poorer and richer classes. If any, the only peculiarity of middle class values is moderation. The analysis also finds changes in values across countries to be of much larger magnitude than the ones dictated by income, education, and individual characteristics, suggesting that individual values vary primarily within bounds dictated by each society.

This paper is a product of the Office of the Chief Economist, Latin America and 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 author may be contacted at jrigolini@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
# 1. Introduction

Over time, an increasing number of countries have been mandating maternity leave provisions that meet or exceed the standard of 14 weeks set by the International Labor Organization (ILO).<sup>2</sup> In tandem, more countries have introduced legislation to grant a certain amount of paid leave to fathers following the birth of a child. Policy movements in this area recognize the growing body of evidence that granting parents a period of leave following the birth of a child can be beneficial for both children and their parents. However, the consensus on the impact of maternity and paternity leave on women’s labor market outcomes remains equivocal and while the empirical evidence on the link has been growing in depth, it has not necessarily been growing in breadth. Indeed, much of the research has been based on data from a select set of mostly high-income economies. Through this research, we present a global overview of how family leave policies have evolved using a novel data set covering 190 countries over 52 years and consider the relationship between maternity and paternity leave and women’s labor market outcomes.

The literature on family leave policies and their effects considers different types of leave—maternity, paternity and parental; paid, partially-paid and unpaid—and a range of outcomes, including wages and employment for both parents, child development, and fertility rates. The pioneering study of Winegarden and Bracy (1995) shows that periods of paid maternity leave may be associated with several positive outcomes. Using data from 17 OECD countries, results from the authors’ structural estimation show that extending the duration of maternity leave is associated with lower infant mortality rates, higher rates of female labor force participation and increased fertility. Results from a reduced-form estimation, however, show that when the direct and indirect effects are combined, the positive association with fertility rates disappears, but the positive correlation between female labor participation and lower infant mortality remains significant. Ruhm (1998) considers the impact of parental leave on the gap between female and
Scussolini et al. 2015). For the national‐level analysis, flooded areas are defined as any area with inundation higher than 0. We have not yet explored the depth dimension, although the flood hazard maps developed for this study allow for this potential in future work.

For the HCMC analysis, the location of the slum areas in the PUMA data set are mainly restricted to the old town. Furthermore, slum areas are often difficult to define and the data we have likely does not capture all slum areas within HCMC. Finally, the urban expansion data set does not make a distinction between the urban expansion of residential areas or infrastructure (roads, etc.).

19