rafmacalaba/data-use-mentions-extended huggingface dataset:
five years before transference the presence of civilian targeting is similar in protected areas that will be transferred to AP and in those that will not be (Figure S13a). As in our tourism analysis, we prefer binary measures of conflict in order to reduce potential measurement error stemming from reporting bias (SI A.6 and Figure S15). However, it is important to note that we do not find an effect of AP management on the number of civilian targeting events (Figure S16). We also find no clear evidence that AP changes the probability of any battles occurring within 25 km of the protected areas it manages, nor does AP appear to affect the probability of any protests and riots within 25 km of the protected areas it manages (Figure 3, Rows 7-8).

# **2.5 Mechanisms**

Which aspects of AP management might explain its capacity to improve wildlife conservation and tourism but exacerbate one form of conflict? We utilize survey data on management practices recorded with the Management Effectiveness Tracking Tool (METT) [74]. METT is a standardized questionnaire that is typically filled out as a group exercise among protected area managers and other stakeholders [75, 76]. It is designed to characterize the management and governance of protected areas by quantifying aspects such as planning, resource levels, law enforcement, and stakeholder involvement. These data are self-reported and only available for some protected areas and years; nonetheless, they represent the best opportunity to quantitatively understand the ways in which AP management differs from government management of protected areas.

Following previous research, we group responses to the METT’s 30 questions into four distinct categories [53, 76]:

**Design and Planning:** This category captures the legal framework of the protected area and whether its strategic design and planning promote effective operations [77]. AP management increases this dimension by 0.683 standard deviations, reflecting AP’s proactive and robust planning approach, although this effect is not statistically significant due to the limited
|19%|15%|Oils|60%|24%|16%|
|Meat||42%|18%|29%|Meat|38%|10%|20%|
|Sugar||78%|19%|12%|Sugar|53%|13%|12%|
|Food||53%|100%|100%|Food|48%|100%|100%|

_<mark>Source</mark>_ <mark>: Calculations using USDA data collected by C</mark> ristina Savescu. Note: „Oil exporters‟ denotes the developing oil exporters.

The impact on the import bill of these price increases in the MENA region is estimated at 0.6 percent of GDP, and 1.4 percent of international reserves, with grains making the largest contribution, followed by edible oils, sugar, and meat (Table 2). Oil importers are hardest hit by the increase in food prices. The increase in the import bill is estimated to be 1.2 percent of GDP, with half of the increase attributed to the impact of higher grain prices. This is consistent with the high share of grains in the import basket (Table 1B).

The expected increase in the import bill of the developing oil exporters as a result of higher food prices is estimated at 0.8 percent of GDP and 2.3 percent of international reserves. Increases in prices of edible oils and sugar account for more than half of the increase in the import bill. Dependency on imported edible oils and sugar is high; therefore, despite smaller shares in the import basket, these two groups have a large effect on the import bill.

The GCC countries are expected to be least impacted by the higher food prices at the macro level as they have small populations and high per capita incomes. The overall impact on the GCC is estimated to be 0.3 percent of GDP and 0.5
, and P.J. McEwan. (2009). “Preschool and Maternal Labor Market Outcomes: Evidence from a Regression Discontinuity Design.” _Economic Development and Cultural Change_ , 59(2), pp. 313–344.

- Berniell, M.I., and C. Sánchez-Páramo. (2011). “Overview of Time Use Data Used for the Analysis of Gender Differences in Time Use Patterns.” Background paper for the WDR 2012.

- Bertola, G., F.D. Blau and L.M. Kahn. (2002). “Labor Market Institutions and Demographic Employment Patterns.” Working Paper Series 9403, National Bureau of Economic Research, Cambridge, MA.

- Boone, C., P. Glick, and D. E. Sahn. (2011). “Household Water Supply Choice and Time Allocated to Water Collection: Evidence from Madagascar.” _Journal of Development Studies_ , 47(12), pp. 1826–1850.

- Botero, J., S. Djankov, R. La Porta, F. Lopez-de-Silanes and A. Shleifer. (2004). “The Regulation of Labor.” _Quarterly Journal of Economics_ , 119(4), pp. 1339–1382.

Boserup, E. (1970). _Woman’s Role in Economic Development._ London: Allen and Unwin.

- Budlender, D., N. Chonokoane, and Y. Mpetsheni. (2001). _A survey of time use. How South African women and men spend their time._ Resource Document. Pretoria: Statistics South Africa.

22
in Colombia encompasses a greater variety of institutions and yields a rich setting to investigate market dynamics. Colombia providers include public and (non-profit) private HEIs as well as SENA (National Learning Service). The latter is a decadesold public workforce training institution (not an HEI) with branches throughout the country, that only recently has begun providing SCPs. Since SENA’s decisions are made at the national level, outside the education domain, we focus on public and private HEIs’ supply, taking SENA’s offerings as given. Further, Colombia boasts rich higher education and labor market administrative data. We use data from the universe of SCPs and bachelor’s programs offered between 2003 and 2019, as well as individual-level data for all higher education graduates working in the formal sector between 2007 and 2013.<sup>4</sup> We study program entry and exit at the market level, defined as a combination of geographic location and field of study.<sup>5</sup> This definition captures entry and exit variation across locations and fields, and over time.

We show that SCPs have a high turnover rate—higher, in fact, than that of bachelor’s programs. In our sample, SCPs have a shorter average life than bachelor’s programs, as well as higher entry and exit rates. This leads to the question of whether the SCP “churn” might be in response to local labor market changes. Answering this question poses two problems. First, higher education indicators are typically reported by field of study whereas labor market indicators are reported by economic sector. Second, the correlation between the local SCP supply and the local demand for graduates might not be causal but rather driven by unobserved shocks to the local SCP market.

To bridge the gap between fields and economic sectors, we construct two measures of local labor demand by field of study. The first is a shift-share variable that measures local GDP by field. The underlying assumption is that aggregate, national shocks to
savings for investment (garment sector, construction and tourism). Of these four key drivers, agriculture had a relatively limited exposure to the crisis (Guimbert 2010). The next figure shows that after many years of high growth, the economy was strongly hit by the global financial crisis in 2008 with growth declining from 6.7% in 2008 to 0.1% in 2009. However, the negative shock was temporary as growth resumed quickly to 6.0% by 2010.

**Figure 1: Cambodia GDP growth (%) – total economy and key sectors**

<!-- Start of picture text --> 100.0<br>80.0<br>Agriculture<br>60.0<br>Garments and footwear<br>40.0 Construction and real<br>estate<br>20.0 Tourist arrivals<br>total GDP<br>0.0<br>-20.0<br>1995 1997 1999 2001 2003 2005 2007 2009 2011<br><!-- End of picture text --> Note: growth rates for GDP in 2000 constant prices, except ‘tourist arrivals’ (annual number of international visitors). Source: National Institute of Statistics, authors’ calculation.

In this paper, we look at the responses of individual firms to the large negative shock between 2008 and 2009. For this, we use two firm surveys that were implemented respectively in August 2007 - March 2008 (Investment Climate Survey, ICS 2007/2008) and in July-November 2009 (the Cambodia Rapid Business Survey, CRBS 2009). Both surveys randomly sampled firms in Phnom Penh and in four other main cities in Cambodia (Battambang, Kampong Cham, Siem Reap and Sihanouk Ville). The sample was limited to firms in the formal sector that were registered with the Ministry of Commerce and which had at least five employees. Because no full census of establishments was available at the time, a sampling frame was
# The Role of Importers and Exporters in the Determination of the U.S. Preferences Granted to Latin America<sup>∗</sup>

# Peri Silva<sup>†</sup>

## Abstract

This paper investigates the role played by domestic importers and foreign exporters in improving preferential access to the domestic market. To this end, the framework used in this paper extends the protection for sale analysis to explicitly model the role of domestic importers and foreign exporters in the determination of preferential trade treatment. The predictions of the model are tested using data on preferential trade between the United States and Latin American countries. The results suggest that Latin American exporters and U.S. importers’ lobbying efforts have a signi fi cant and important role in determining the extent of preferential access granted by the United States. More interestingly, these fi ndings also show that U.S. importers capture a very substantial share of the rents generated by tariff preferences. These results therefore shed a pessimistic view on preferential trade schemes as a reliable source of gains for developing countries.

JEL classi fi cation numbers: F10, F11, F13 Keywords: Trade, Political Economy, Latin America, United States.

World Bank Policy Research Working Paper 3518, February 2005 .

The Policy Research Working Paper Series disseminates the fi ndings of work in progress to encourage the exchange of ideas about development issues. An objective of the series

> ∗I am grateful to Giovanni Facchini, Earl L. Grinols, Marcelo Olarreaga, Werner Baer, George Deltas, Hadi Esfahani, and Mathias Polborn for helpful comments. Special thanks are due to Marcelo Olarreaga and Kishore Gawande for providing key parts of the data. Financial Support provided by the World Bank and the Hewlett Foundation is gratefully acknowledged as well.

> †Department of Economics, University of Illinois at Urbana-Champaign, Champaign, Illinois; Tel. (217)333-0120; Fax: (217)244-6678; e-mail: pasilva@uiuc.edu
impact of different cholera risk mitigation strategies to improve water and sanitation infrastructure, quality, and access, including their relative efficiency and potential to target the highest impact parts of the city. The fact that two Wards (Kanyama and Harry Nkumbula) were ranked as first and second highest impact for nearly all mitigation scenarios reflects the clear need to prioritize this region of the city. The potential for greatest impact here likely stems from the confluence of a number of factors: the very high concentration of cholera risk (meaning predicted incidence rates are high), the dense population (meaning larger numbers can potentially be averted), and the poor levels of access to water and sanitation at the time (meaning there was large scope to improve on current provision). All three factors, in turn, were driven by the nature of these neighborhoods which were characterized by high rates of poverty and informal settlements with inadequate infrastructure.

The approach developed here has a number of limitations. All analysis stemmed from a model that sought to explain the spatial variation in reported cases across the city. These case data were geolocated according to the home residence of the patient, but of more interest is the location at which the infection was acquired. In many cases, this may be in or close to the home, but in others the exposure may have occurred somewhere else entirely – for example at a workplace, when visiting another household in a different parts of the city, or in a public venue. In future analyses, it may be possible to obtain data representing patterns of human movement (for example as collected via mobile phone records) and include these in analysis of spatial risk patterns (Bengtsson et al. 2015). A second limitation concerns the counterfactual analysis. This relied on the necessary assumption that the empirical relationships captured in the modeling between cholera risk and each putative risk factor were causal rather than mere associative. For example, it was assumed that the observed relationship between poor sanitation and cholera meant that improving sanitation would reduce cholera risk
Such potential gains are very important for African countries in relation to their current taxation levels. They could stem from two pathways: First, from a direct effect linked to tax audits based on actual information received. In other words, from ‘catching’ fraudsters and evaders. A second stems from an indirect compliance effect, i.e. the fact that people will have less recourse to tax avoidance strategies due to the existence of exchanges in the first place (which imply an increase in the risk of being caught). Evidence of the latter effect is brought by the implementation of voluntary disclosure programs. In the case of South Africa, the said program, running from October 2016 to August 2017, unveiled USD 1.8 billion worth of foreign assets and revenue gains of USD 296 million, while Nigeria’s program helped collect an extra USD 162 million between July 2017 and June 2019 (OECD 2022).

These effects are however subject to certain caveats, first of which is the capacity of tax authorities to process the data received via the exchanges. While digitization and tax administration capacity are accounted for in the analysis, it may not account for a sudden surge of information at a given time – especially as AEOI is usually done around a specific period (September).

A second caveat is the absence of political involvement blocking audits – considering that evaders are often part of a business/political establishment. Holding offshore accounts is typically a matter of high-net worth individuals. News stories over the past years regarding the extent of tax avoidance revealed by the Panama papers, Paradise papers or recently the Pandora papers suggest that avoidance is conducted by individuals close to power. Lobbying to escape audits should not be discounted.

From a policy perspective, it is clear that the digital maturity of public administration works in favor of joining the Global Forum and engaging in information exchange.<sup>11</sup> However, the risks associated with digitalization should be mitigated by adequate administrative and institutional capacity to take advantage of digital
paper focuses on global unit values, this would not be a problem if the average quality of traded goods across the world does not change signicantly. Although there is no evidence on this regard, the average quality of exported goods is more likely to be stable than the quality of individual country exports, as during the life-cycle of a good, production of the cheapest varieties shifts to poorer countries. The concerns about quality dierences are also reduced by using a highly disaggregated classication, which is the motivation for working with the lowest level of aggregation reported by Feenstra et al. (2005). Also, problems with the level of unit values should not aect this measure because this paper focuses on the correlation between the growth rate of these global unit value indexes and the growth of the nominal exchange rates of dierent countries. Dierences between the growth of this index and that of the actual price of goods exported by a country within an SITC class may arise from dierences in the growth of the quality of a country's exports relative to global exports. However, these dierences would only introduce measurement error that would make it less likely to nd any signicant result.

A more pragmatic reason to use uctuations in global unit values as proxies for price uctuations 13
<!-- Start of picture text --> 7.0<br>6.4 6.5 6.3 6.3 6.3<br>5.9 5.8 6.0 6.0 6.0 6.0 5.8<br>5.4 5.5<br>5.0 5.0 5.0<br>EU CE & BC WB SC CA Russia Turkey EE RoW<br>2010 2016<br>8<br>6<br>4<br>Tier 1 stringency ratio<br>2<br>0<br><!-- End of picture text --> Source: Bank Regulation and Supervision Survey conducted by the World Bank.

Note: **EU** stands for Western Europe, Southern Europe, Northern Europe; **CE & BC** for Central Europe & Baltic Countries; **WB** for Western Balkans; **SC** for South Caucasus; **CA** for Central Asia; **EE** for Eastern Europe; **ROW** for the rest of the world **.** Having made a distinction between regulatory and economic capital, we examine how these capital ratios have changed in the region over the past 10 years using bank-level information on over 20,000 banks. In the analyses that follow, regulatory capital (RC/RWA) is calculated as the sum of Tier 1 and Tier 2 capital divided by risk weighted assets. The equity ratio (Equity/TA), also referred to as the simple leverage ratio, is calculated as total common equity divided by total assets. We also examine how risk-weighted assets have changed over time by calculating risk-weighted assets as a percentage of total assets (RWA/TA).<sup>10</sup> Figure 8 shows the evolution of regulatory capital ratios in the ECA subregions. Because many countries are dominated by
preschool or in the associated primary school. Subsequently, the oldest child was interviewed and asked for the names and ages of her siblings<sup>24</sup> below the age of seven. The list of all families in a school, including the names of the parents, the names of the oldest child in school and the names and ages of all children below age 7 constitutes that school’s baseline survey. To minimize the school’s incentives to distort baseline information, all baseline surveys were collected prior to the announcement of the randomization results to the schools. In addition, the schools were informed that the baseline survey information would not be used in determining the amount of food they would receive in case they became a treatment school. Prior to the start of the program, the households and children in the baselines in treatment and comparison schools were similar on most dimensions (Table 2).

The results presented in this paper are internally valid for children belonging to the baseline.

> 22 Preschool and primary school children in rural Busia and Teso go to school on foot. Bicycles are used by teachers and secondary school children. Cars or busses are not used as a mode of transportation in this context.

> 23 The Kenyan system of ...nancing school buildings and teachers provided strong incentives for building many schools. For a discussion of primary school ...nance, see Kremer, Moulin and Namunyu (2001). For a discussion of pupil sorting between schools, see Miguel and Gugerty (2002).

> 24 In the remainder of this paper, children living in the same compound will be called siblings, even though they are not necessarily biological brothers and sisters. During ...eld work, the older children were asked for the names of all children ”eating from the same kitchen”, which is a common expression in Kenya and avoids the di¢ culties involved in identifying parents in polygamous households.

13
Figure 3. Wealth Index Distribution <!-- Start of picture text --> (a) Wealth Index - Total (b) Adequate Housing Materials (% of Total)<br>-5 0 5 10 15 0 .2 .4 .6 .8 1<br>Wealth Index Average - Dwelling Material<br>Colombian Venezuelan Colombian Venezuelan<br>Venezuelan: Before migrating Venezuelan: Before migrating<br>(c) Asset Ownership (# Total) (d) Access to Services (% of Total)<br>0 10 20 30 40 0 .2 .4 .6 .8 1<br>Total Assets Average - Access to Services<br>Colombian Venezuelan Colombian Venezuelan<br>Venezuelan: Before migrating Venezuelan: Before migrating<br>4<br>.25<br>.2 3<br>.15<br>2<br>k-Density k-Density<br>.1<br>1<br>.05<br>0 0<br>.15 3<br>.1 2<br>k-Density k-Density<br>.05 1<br>0 0<br><!-- End of picture text --> _Notes:_ Panel (a) presents the distribution of the wealth index for Colombian and Venezuelan households in our sample in 2022 and pre-migration. Wealth Index is an index measure of the household’s cumulative living standard constructed following The Demographic and Health Surveys (DHS) methodology. It includes the following variables: i) dwelling materials is the average of dichotomous variables that take the value of one if the materials of the floors and walls are of adequate quality (including block, brick, stone, polished wood, and cement); ii) asset ownership is a set of count variables for 15 consumer items (telephones, cellphones, TVs, computers, tablets, microwave, washing machine, fridge, blenders, water heater, radio/recorder, cars
interventions includes smaller loans or grants covering several areas (such as a $2m investment grant covering 8 areas), large and focused ($100m investment loan addressing 2 areas), as well as medium-large and diverse ($49m for an investment loan addressing 14 areas). Some of these differences are related to the countries‘ size, but they also represent considerable diversity as to the financial ̳firepower‘ brought to bear relative to the number of issues covered and the degree of challenge presented by these.

Overall, current practice of Bank support for public sector reforms is spread widely across countries and across issues. Most operations tend to be moderately or significantly complex and virtually all touch on some sensitive aspects which require substantial political commitment to succeed. These indications of limited selectivity imply that an important share of public sector operations would be expected to encounter political economy challenges in implementation. The following section explores the actual success rate of operations according to IEG outcome ratings, the patterns in the distribution of more and less successful operations across countries, and the type of challenges encountered.

# **III.2 Frequency and Types of Political Economy Problems: Patterns across Countries and Operations**

To explore the frequency of political economy problems in public sector reform support provided by the World Bank, this section examines what share of recently closed World Bank operations was rated less well, whether poor performance has been related to political economy challenges, and if so to what type of political economy problems.

**Graph 1: Distribution of outcome ratings – all public sector operations, ILs and DPLs**

<!-- Start of picture text --> Outcome rating distribution in Outcome rating distribution Outcome rating distribution<br>%, all public sector operations in % for DPLs only in % for ILs only<br>45.0 41.0 50.0 46.1 40.0 36.2<br>45.0 34.5<br>40.0 35.0<br>