rafmacalaba/data-use-mentions-extended huggingface dataset:
–2117.

- and , “The economics of urban density,” _Journal of economic perspectives_ , 2020, _34_ (3), 3–26.

- and Matthew A. Turner, “The Fundamental Law of Road Congestion: Evidence from US Cities,” _American Economic_

- _Review_ , October 2011, _101_ (6), 2616–52.

- Emporis, _Emporis database_ , Emporis, 2022.

- Erba, Diego Alfonso and Mario Andres Piumetto, _Making Land Legible: Cadastres for Urban Planning and Development in Latin America_ , Lincoln Institute of Land Policy Cambridge, MA, USA, 2016.

- Esch, Thomas, Elisabeth Brzoska, Stefan Dech, Benjamin Leutner, Daniela Palacios-Lopez, Annekatrin Metz-Marconcini, Mattia Marconcini, Achim Roth, and Julian Zeidler, “World Settlement Footprint 3D-A first three-dimensional survey of the global building stock,” _Remote Sensing of Environment_ , 2022, _270_ , 112877.

- Fay, Marianne and Charlotte Opal, _Urbanization without growth: A not so uncommon phenomenon_ , Vol. 2412, World Bank Publications, 2000.

- Florczyk, AJ, Michele Melchiorri, Christina Corbane, Marcello Schiavina, M Maffenini, Martino Pesaresi, Panagiotis Politis, S Sabo, S Freire, Daniele Ehrlich et al., “Description of the GHS urban centre database 2015,” _Public release_ , 2019, _1_ , 1–75.

- Fox, Sean, “Urbanization as a global historical process: Theory and evidence from sub-Saharan Africa,” _Population and development review_ , 2012, _38_ (2), 285–310.

- , “The political economy of slums: Theory and evidence from Sub-Saharan Africa,” _World development_ , 2014, _54_ , 191– 203.

and Tom Goodfellow, _Cities and development_ , Routledge, 2016.

- Frolking, Steve, Richa Mahtta, Tom Milliman, and Karen C Seto, “Three decades of global trends in urban microwave backscatter, building volume and city GDP,” _Remote Sensing of Environment_ , 2022, _281_ , 113225.

- Gjerlow, Haakon and Carl
participate in the intervention after they have been treated and cured of the infection; learning is encouraged through positive reinforcement, and mistakes can be corrected and overcome.

In addition to these urine-based NAAT STI tests, we also measured syphilis and HSV2 using blood-based tests. Because of the low prevalence of syphilis, and because HSV2 detects whether the individual has ever contracted HSV2, we elected to only measure these blood-based STI‘s at baseline and 12 months, rather than at each 4-month interval.

Finally, we also measured HIV at baseline and one-year follow-up. We did not conditional reward payments on HIV status, in part due to ethical concerns about ―punishing‖ somebody at the very time when they learn that they have contracted a fatal disease. We were not powered to look at intervention arm effects on HIV, but for scientific purposes did want to measure baseline HIV to better characterize our population. Our HIV rates turned out to be lower (just under 4%) than anticipated based on regional Demographic and Health Survey data; given the reasonably high rates of HIV testing in the population it may be that HIV positive individuals selected themselves out of the sample. We decided to also test HIV at the 12-month endpoint due to the study population‘s strong interest in checking their results again. Although over half of the population had received a prior HIV test, study enrollees expressed concerns about confidentiality of testing at local clinics, and strong desire for retesting by RESPECT study personnel.

# **_Incentive Size and Frequency_**

A major design consideration is the size of the incentive. CCT programs focused on uptake have typically relied on formulas to compensate participants on the opportunity costs, or time requirements, of complying with programmatic requirements such as attending antenatal care visits or taking the child to the clinic for his or her regular checkups. However, in the case of CCT programs designed to encourage safer sexual practices and discourage risky ones, the purpose of the incentive is not primarily to compensate the individual for the opportunity costs of participating in
bution reduce imports and impose substantial welfare costs, the magnitude of which is similar to that caused by border trade barriers. As is stressed in other CGE papers that analyze the impact of services policies, the extent to which inflated margins reflect excess costs or are captured by domestic agents as rents is important. If it is assumed that half of the excess margin generates rents, the simulation generates an increase in real income (equivalent variation) of 1.7 percent across the sample.<sup>35</sup> Francois and Wooton (2001a) focus on a related issue, developing a theoretical structure where trade requires transport costs supplied by a shipping sector operating as an oligopoly. Working with both their theoretical model and numeric examples in a simple CGE model, they link shipping prices to the combination of supply and demand elasticities. Hummels, Lugovsky, and Skiba (2009) offer empirical support for such a framework, finding that shipping firms charge much higher freight rates when demand is relatively inelastic. In general, the message from this literature is that with intermediate service firms exercising market power on two price-cost margins (meaning they act collectively as both an oligopoly vis-a-vis final consumers and an oligopsony vis-a-vis producers), the gains from trade in goods hinge on the degree of competition in service sectors. As such, trade and FDI policy in services may impact directly and substantively on trade in goods. This issue is little explored in a CGE framework, in part due to data constraints.<sup>36</sup> In principle, the GTAP database includes estimates of bilateral shipping costs. These data are admittedly crude, and do not include information on market structure, per unit and per weight charges, and the variation in these charges by route. However, with new data sources emerging, this situation should improve.<sup>37</sup> International trade in services is dominated by a small number of large firms, and much of global trade takes place within these firms. For example,
(1997) makes the valid criticism that the poverty statistics by gender reported in the 1995 World Bank report were based on assumptions of equal household size and other assumptions that bias poverty findings downward for female headed households. We recalculated the poverty statistics using their criteria and find that the relative differences in poverty movement over time between male and female headed households are still the same as reported in the 1995 report. Our analysis is available upon request.

> 6 Louat et al (1993), Rosenhouse (1989) among others.

10
dropped after the implementation of the sanction. Over 2007-2013, the enrollment rates in primary and secondary schools were always around 97% and 89%, respectively (Source: Statistical Centre of Iran, otherwise noted). At the same time, the population of first-year college students decreased by 11.5%. Moreover, over the years of sanctions, the investment in children’s education measured by household spending on education has decreased on average by 43% (Source: calculation by the author using HIES). This reduction in households’ education spending could be because young children do not attend school and/or parents cut spending on school expenditures, for instance, choosing free public school instead of private school.

# **2.3 Mechanisms behind Sanctions**

In this section, I explore the mechanisms by which economic sanctions may decrease investment in children’s education. The sanctions affect children’s education through changes in the demand side (labor income and relative prices) and the supply side of schooling (government budget).

One mechanism by which the sanctions affect children’s education is through labor income. As explained above, as a result of the sanctions, labor earnings decreased in the treated industries. The changes in labor income may affect investment in children’s education through two channels: family budget constraint and changes in returns to education.

First, labor income shocks may affect children’s education through family budget constraints. An influential work, Acemoglu and Pischke (2001) provide theoretical and empirical support for the idea that parental resources can affect education decisions through budget and credit constraints because education is not a pure investment and can be a consumption good too. Reduction in family income after the sanctions may have made it harder for children to attend school. However, as explained above, households might adjust this shock to mitigate the impact of sanctions on children. For example, they can draw down savings or sell off assets to smooth consumption in response to a negative income shock (Browning
20-32.

Aghion, Philippe, Robin Burgess, Stephen J. Redding, and Fabrizio Zilibotti (2008), “The Unequal Effects of Liberalization: Evidence from Dismantling the License Raj in India,” American Economic Review, 98(4): 1397-1412.

Aghion, Philippe and Peter Howitt (1992), “A Model of Growth through Creative Destruction,” Econometrica, 60: 323 - 351.

Almeida, Rita and Ana M. Fernandes (2008), “Openness and Technological Innovation in Developing Countries: Evidence from Firm-Level Surveys,” Journal of Developing Studies, 44(5): 701-727.

Alonso-Borrego, C., M. Arellano (1999), “Symmetrically Normalized Instrumental-Variable Estimation using Panel Data,” Journal of Business and Economic Statistics, 17 (1): 36–49.

Arellano, M., S. Bond (1991), “Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations,” Review of Economic Studies, 58 (2): 277–297.

Arellano, M., S. Bond (1998), “Dynamic Panel Data Estimation Using DPD98 for Gauss: a Guide for Users,” Mimeo. CEMFI. ftp://ftp.cemfi.es/pdf/papers/ma/dpd98.pdf.

17
income or consumption value for 2020 and we calculate the shares of poor, vulnerable, and middle class in each country.

<mark>We apply this model to five countries in five regions: Brazil, the Philippines, South Africa, Sri Lanka, and Türkiye.</mark><sup>13</sup> <mark>The model requires five main inputs. Country-specific household survey microdata for each country is based on the 2019 Pesquisa Nacional por Amostra de DomiciliosContinua for Brazil; the 2018 Household Income and Consumption Expenditures Survey for Türkiye; the 2018 Family Income and Expenditure Survey for Philippines; the 2016 Household Income and Expenditure Survey for Sri Lanka; and the 2019 General Household Survey for South</mark>

> 13 We select the countries according to the availability of labor force surveys (for the measurement of employment level in 2020) and a household survey (for poverty measurement in 2019) with data on income and remittances.

14
| While accounting for a relatively minor share of electricity trade in most countries, power<br>exchanges offer an instrument for price discovery. Exchanges can also provide helpful hedging<br>instruments for generators and consumers to lock in electricity prices for future time periods<br>providing some protection from price volatility.|
|---|
|**Policy recommendations for implementing competitive retail markets**<br>Based on the global experience with this structure, several key insights can be discerned:<br> Product differentiation is key for retail supply companies to capture higher margins associated<br>with differentiated and a unique product in a segment that traditionally has slim margins.<br> The contestability of retail markets is necessary for the cost associated with setting up these<br>complex market structures to deliver expected efficiency results. In some emerging markets,<br>this constraint may justify long durations before a transition to full retail competition.<br> Transaction costs are typically lower for sales to larger industrial and commercial consumers.<br>In some markets, a phased approach to opening up the retail market first to these customer<br>groups and then extending it over time to households may be preferable.<br> The market power of incumbent energy companies can threaten effective competition and<br>market entry of new supply companies. Strong sector regulation is needed to limit and eliminate<br>uncompetitive behavior in the market.<br> Advents in disruptive digital technology hold promise to lower the cost barriers to independent<br>supply companies that do not have these legacy advantages. Retail companies can deploy<br>digital technologies to improve their competitiveness. For example, by utilizing advanced<br>analytics on pooled customer data on customers’ usage patterns, segmentation, and preferences,<br>they can identify target customer segments and potential opportunities to deploy new products<br>and services.<br> Technological advances are placing
Policy Research Working Paper 7676

# **Abstract**

This paper examines whether export participation matters for job training. The paper draws on longitudinal worker-firm data for Brazilian manufacturing, linked with detailed records on training activity from the main provider. The analysis uses industry-specific exchange rate movements to generate exogenous variation in export status at the firm-level. The findings indicate that export participation tends to increase the share of workers who receive technical upgrading. The results also reveal that technical upgrading has positive returns to trainees within exporting firms. These findings support the hypothesis that exporting requires skill upgrading, and suggest that this is partially achieved by training firms’ existing workforce.

This paper is a product of the Trade and International Integration Team, Development Research Group, and 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 pbastos@ worldbank.org, jsilva@worldbank.org, or rproenca@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
# **1. Introduction**

We use a unique data set for Peru that captures the elimination of subnational regulatory barriers to firm entry and competition across 1,800 municipalities. These were caused by legal reforms in 2013 and 2014 that strengthened the mandate of Peru’s competition authority over the implementation of business regulation by subnational government bodies. We match these data with establishment census panel data from 2008-15 to estimate the impact on changes in establishments’ productivity and markups. We find that the reforms have raised firm productivity. To the best of our knowledge, it is the first time that a positive impact of strengthening a country’s institutions to enforce the elimination of barriers to market entry and competition on firm productivity in that country has been established.

According to conventional wisdom, product market competition improves the allocative efficiency among firms and makes market structures more conducive to innovation and growth. Specifically, declining market entry costs are expected to level the playing field and encourage firms to increase their cost effectiveness to outperform their competitors.

But the empirical evidence linking competition to productivity growth has been relatively scant, except for reforms related to international trade liberalization, due to the lack of adequate data. Cross-country data do not seem adequate given the difficulty to identify exogenous regulatory changes across countries with unobservable institutional characteristics and given the limited low-frequency sample sizes relative to the seemingly open-ended list of growth correlates. Microeconomic data, on the other hand, often lack sufficient disaggregated variation needed to identify an appropriate control group (of firms) not affected by regulatory changes.

We argue that recent reforms expanding the legal mandate of Peru’s competition authority to enforce the elimination of subnational regulatory barriers to market entry and competition provide a unique quasi-experimental setting to identify the impact of strengthening the enforcement of competition, that is the elimination of regulatory barriers to market entry, within the controlled institutional environment of a single country. Specifically, Peru provides a unique setting for at least two reasons.

First, Peru has one of the most liberal international trade regimes in
number of products, or number of destinations (the extensive margin).<sup>39</sup> Naturally it is important to integrate such data with program data such as from the project monitoring database.

The trade and integration unit of the World Bank Development Research Group is involved in a major data collection exercise that may help the IE of trade-related interventions in the next few years. As described in Freund and Pierola (2011), the exercise consists of the collection and compilation of the first ever database on exporter-level customs transaction data across countries and over time. Data has been obtained for 20 countries in Africa, Asia, Eastern Europe, and Latin America, and negotiations are in progress to obtain data for 25 more countries. The database will include statistics on exporters’ characteristics and behavior by country, industry, and destination market. The purpose of the database is to provide policymakers, development agencies, researchers, and the public with a novel source of information to conduct analysis of export growth at the micro level and allow for the evaluation of programs and policies affecting that growth.

Data on firm characteristics (covariates), used to control for selection bias, is typically hard to obtain. If an industrial survey is available in the country where the trade intervention is taking place, it can provide the required variables (e.g., location, age of the firm, education of its head, number of employees, foreign ownership). However this requires that customs and industrial census data be merged, which raises confidentiality concerns and may require active collaboration by busy officials in local institutions. When data is not available, an alternative is to conduct a ―retrospective survey‖ — although this method may be biased. In its evaluation of Tunisia’s export-promotion agency, Gourdon et al. (2011) use a combination of data from a survey and from national sources (the customs agency and national statistics institute). Yet another alternative is to include questions on program participation and details in ongoing surveys
conceptualize remoteness and dispersion relative to a nation’s capital. For each case-study PIC, we calculate alternative indicators of remoteness as communities’ distance from the national capital—either directly, or via local regional hubs. The associated dispersion indicators follow, as the populationweighted average community-level remoteness. These alternative measures of remoteness (and relatedly dispersion) are less sensitive to changes in settlement patterns, but potentially more transparent.

The benchmark remoteness, dispersion and sparsity indicators we focus on in this paper have many appealing intuitive characteristics. In particular, they are highly sensitive to variation in population settlement patterns. Variation in these measures across different geographical settings broadly aligns with intuition around what it means for a community to be remote in a country-context, or for a population to be highly dispersed. For example, a greater level of dispersion will be recorded in a setting with less population clustering, e.g. where two inhabited islands are further apart, all else being equal.

Another appealing characteristic of our new measures is that there is a natural link between the microlevel geographic indicator (local-area remoteness) and macro measures of population dispersion and 26
participation rates and market power, consistent with our results on heterogeneity.

First, this paper contributes to an extensive literature that evaluates the impacts of SNAP. Recent papers regarding SNAP (Hoynes and Schanzenbach, 2009; Almond et al., 2010; Hoynes et al., 2016) exploit the county-level rollout of the program in the 1970s as a quasi-experiment to evaluate the impact of SNAP on consumption, birth weights, and long-run measures of human development. Furthermore, a growing number of studies have estimated the MPCF out of SNAP benefits. Hastings and Shapiro (2018) (hereafter HS) use transaction-level data from a large US grocery retailer’s operations in five states to estimate an MPCF out of SNAP of 0.5 to 0.6 but an MPCF out of cash of 0.1. Based on these estimates and other evidence, they reject the fungibility of SNAP benefits.<sup>7</sup> Hoynes and Schanzenbach (2016) provide a review of the literature.

The supply-side responses of retailers have received less attention. A number of recent papers have investigated cross-state variation in within-month issuance schedules to investigate how quickly consumers exhaust their benefits upon receipt, and whether retail stores take advantage of these predictable expenditure phases (Hastings and Washington 2010; Goldin et al. 2022). Jaravel (2018) studies relationships between SNAP take-up rates, prices, and product variety using consumer scanner data.<sup>8</sup> We utilize a novel source of variation to study the incidence of a persistent increase in SNAP benefits.

Second, this paper contributes to a literature studying the incidence of social programs through their impacts on prices. Cunha et al. (2019) study a village-level randomized experiment in Mexico and find that in-kind transfers of food decrease prices due to increases in supply, whereas equivalently valued cash transfers have a negligible impact on prices. Filmer et al. (2018) analyze a randomized evaluation of a Philippine cash transfer program and show prices of perishable protein-rich foods rose as a
changes in distribution, we should expect a change in poverty rates between 0.62*8.58 = 5.32 and 0.68*8.58 = 5.83 percentage points if one uses a deflator reflecting the food share of the bottom 30 percent of the population to define real expenditure changes.

Table 3: Sensitivity of Headcount Poverty to the Poverty Line

||Usin|g 1996 Suse|nas Data|Using|1999 Suse|nas Data|
|---|---|---|---|---|---|---|
|Percentage<br>increase in<br>poverty<br>line over<br>lowest<br>level|If poverty<br>line is<br>(Rp/person<br>/month)|Then<br>headcount<br>poverty is<br>(percent)|Elasticity<br>(percent point<br>change in<br>poverty/<br>percentage<br>change in<br>expenditures)|If poverty<br>line is<br>(Rp/person<br>/month)<br>|Then<br>headcount<br>poverty is<br>(percent)|Elasticity<br>(percent<br>point change<br>in poverty/<br>percentage<br>change in<br>expenditures)|
|0|28,516|9.75|-|62,877|9.75||
|_5_|29,942|12.01|0.45|66,021|12.10|0.47|
|10|31,368|14.39|0.50|69,165|14.55|0.51|
|15|32,793|16.93|0.56|72,309|17