rafmacalaba/data-use-mentions-extended huggingface dataset:
tionable things when they are just doing what an authority figure told them to do". It’s worth noting, however, that for all items a significant majority of all respondents do not agree with the statements. Overall, politicians score on average 0.32 standard deviation lower than bureaucrats on the aggregate Integrity Index.

Panels B and C present results on personality traits. Politicians do fare better than bureaucrats in other non-cognitive dimensions. They score 0.12 s.d. higher on average in the Big-Five Index, though their advantage is restricted to two domains in which we would indeed expect politicians to perform better: Extraversion and Agreeableness. When we consider other measures of non-cognitive ability, bureaucrats fare better on Grit, Decision Making and Hostility Bias, such that we find no distinction between the two groups when pooling all dimensions above in a Non-Cognitive Index. We find no significant difference between politicians and bureaucrats in the Public Sector Motivation Index: bureaucrats report higher Compassion but score lower on Civic Duty and Self-Sacrifice; in other dimensions we observe no gap.<sup>15</sup> .

Finally, Panel D presents results on cognitive traits and measured attitudes of altruism and risk preferences. Consistent with large differences in educational attainment, politicians fare significantly worse in both cognitive measures: on average they can recall 0.3 fewer numbers than bureaucrats, and are also 3 p.p. more likely to choose a dominated option on a simple risk game (choosing a UGX 1 million reward instead of a gamble of equal probability between UGX 1 million and UGX 2 million)<sup>16</sup> . Regarding altruism, politicians donate a slightly larger fraction of a hypothetical prize on average, and also make less risky choices in lottery games.<sup>17</sup>

> 15One advantage of using the same modules as other surveys in the literature is comparing the results obtained in Uganda with other settings. This paper uses the same modules for measurement of PSM and Big-Five as Dal Bo
with firm _×_ product _×_ year fixed effects (columns 5 to 8). The number of observations is much lower than previously due to the incomplete availability of NTMs AVEs.<sup>30</sup> In spite of the reduced sample size and the attenuation bias due to the fact that AVEs are themselves econometric estimates, the results confirm the hypothesis of non-discrimination-cum-reduced competition. NTM reinforce the market power of non-exiting firms, domestic and foreign exporters alike, and thus their incentive to engage in PTM. As a result, PTM is significantly stronger quantitatively in markets with high levels of NTMs. Specifically, the coefficients on the exchange rate and its interaction with the NTM variable in column (1) suggest that moving from zero to a 10 percent ad valorem equivalent raises the price elasticity to exchange rate by a third from 0.5 percent to 0.7 percent. In columns (2) and (3), splitting the sample according to the level of NTMs yields similar results: The exchange rate coefficients is sixty percent larger in countries and sectors belonging to the top quartile of NTMs (column 3) than in those in the first quartile (column 2). Although the coefficients lose in precision and magnitude, the positive impact of NTMs on pricing-to-market

> 28Whereas applied tariffs are specific to origin-destination dyads, most non-tariff measures, in particular SPS and TBT regulations, are imposed on an “MFN” basis, i.e. specific to a destination and not a dyad. For instance, a maximum residual level of pesticides in horticulture products applies to _all_ imports, not just to imports from a particular country, and, unlike a tariff, will not be relaxed in the presence of a preferential trade agreement.

> 29An additional reason for doing this is that tariff data contain many missing values; using average values allows maximizing the number of observations. We however provide robustness exercises using time-varying tariffs.

> 30We confirmed that our main results of incomplete pass-through still hold despite the lower number of
120|4|2|5|5|116|41|677|41|
|**Low income**|120|5|1|1|1|117|39|613|58|
|**MENA**|116|3|3|5|7|115|44|664|24|
|**developing**<br>**countries**|89|5|3|10|18|99|39|638|33|

Source: Doing Business Report 2011, The World Bank Getting Credit: the legal rights of borrowers and lenders with respect to secured transactions through one set of indicators and the sharing of credit information through another. The strength of legal rights index measures the degree to which collateral and bankruptcy laws protect the rights of borrowers and lenders and thus facilitate lending. The depth of credit information index measures rules and practices affecting the coverage, scope and accessibility of credit information available through either a public credit registry or a private credit bureau. The public credit registry coverage indicator reports the number of individuals and firms listed in a public credit registry with information on their borrowing history from the past 5 years. The private credit bureau coverage indicator reports the number of individuals and firms listed by a private credit bureau with information on their borrowing history from the past 5 years.

Enforcing contracts: the efficiency of the judicial system in resolving a commercial dispute. The list of procedural steps compiled for each economy traces the chronology of a commercial dispute before the relevant court. Time is recorded in calendar days, counted from the moment the plaintiff decides to file the lawsuit in court until payment. Cost is recorded as a percentage of the claim, assumed to be equivalent to 200% of income per capita.

53
away from heavier fractions to white products (gasoline, kerosene, and diesel) have resulted in economies of scale being critically important. In response, deregulated and competitive markets have seen consolidation and closure of small refineries (World Bank 2008a and 2008b). The trend in the United States is informative. In 1982, the _Oil and Gas Journal_ ’s “Worldwide Refining Survey” found 301 refineries in the country; by January 2013, the number had declined to 125, with an average size of 145,100 barrels per day (bpd). In the intervening years, 176 refineries—more than half of the refineries that existed in 1982—had been shut down and replaced by fewer, much larger refineries through expansion of existing refineries. Globally, the average size of refineries had increased to 135,800 bpd by 2013.

Against this backdrop, to give just two examples, Tunisia and the Dominican Republic have one refinery each of 34,000 bpd with the simplest configuration needed to produce gasoline and other petroleum products. Neither country is landlocked; both are close to major refining centers. If the current policy of strict price control were to be discontinued, exposing both refineries to open competition, it is far from clear that these refineries would be able to continue to operate. In the meantime, the high cost of operating these refineries is ultimately being borne by the government (Tunisia) or consumers (Dominican Republic). Many refineries in SubSaharan Africa and other regions are also uncompetitive and high-cost. Essentially all of these refineries have plans to increase capacity and modernize for this reason, but these plans are suffering from years, if not decades, of delay because they cannot attract investment, nor is it clear that it would make sense for refineries with chronic operational inefficiencies to expand.

One consequence of uncompetitive refineries is that fuel quality lags behind the EU or U.S. standards, or even the country’s own fuel specifications. For example, in Russia, the inability to meet Euro-3-compliant fuel quality
# 6 Education Financing and Impact on Learning

## 6.1 Officials in the EAP region overestimate public funding for education.

Overall, respondents from EAP countries believe that education financing levels are higher than they actually are, see Figure 16. This overestimation of education financing in EAP contrasts with other regions, where officials tend to underestimate education spending relative to actual spending levels. This finding remains consistent even when the education budget figure is taken into account instead of actual spending (World Bank, 2023). When asked about their preferred percentage of the total government budget to be spent on education, EAP respondents consistently provided estimates that exceeded their own perceptions of the current spending share allocated to education.

_Figure 15: Share of public funding for education of total public spending_ <!-- Start of picture text --> 40%<br>35%<br>30%<br>25%<br>20%<br>15%<br>10%<br>5%<br>0%<br>LAO PHL VNM IDN MNG Average Non-EAP<br>EAP<br>Estimated budget share Actual budget share Officials' preferred budget share<br>Share of public spending for education<br><!-- End of picture text --> Sources: CGD–World Bank survey, 2022. Survey respondents were asked two financing questions: (i) Now thinking about the overall government budget, roughly what percentage do you think is spent on education? and (ii) What percentage of the total - government budget do you think should be spent on education? Data on actual budget share from UNESCO for 2021 (http://sdg4 <u>data.uis.unesco.org/).</u> The magnitude of the misperceptions is larger in EAP than in other countries, and in a different direction. On average, the gap between the estimated share of the budget and the actual share of the budget is 4 percentage
||Source: World Development Indicators,<br>World Bank.|
|---|---|
|Region fixed effects|A set of dummy variables indicating the<br>region of the country. There are 6 dummy<br>variables one for each world region. The<br>regions are: Sub-Saharan Africa (SSA), Latin<br>America and Caribbean (LAC), Eastern<br>Europe and Central Asia (ECA), Middle East<br>and North Africa (MENA), East Asia and the<br>Pacific (EAP), and South Asia (SAR). These<br>regional groupings are based on World<br>Bank’s classification.<br>Source: Enterprise Surveys<br>(www.enterprisesurveys.org)and World<br>Development Indicators, World Bank.|
|City-size fixed effects|<br>Dummy variables indicating the size of the<br>city (sampling region) where the firm is<br>located. Based on total population, cities are<br>grouped into the following size categories:<br>more than 1 million population, between 1<br>million and 250,000 population, between<br>50,000 and 250,000 population, and less than<br>50,000 population.<br>Source: Enterprise Surveys.|
||wwwenterprisesurveysorg|
|Firm Purchased Fixed Assets Y:1 N:0|..<br>Dummy variable equal to 1 if the firm<br>purchased fixed assets during the last fiscal<br>year (prior the year ES was conducted) and 0<br>otherwise.<br>Source: Enterprise Surveys.<br>|
||www.enterprisesurveys.org|
|Foreign Ownership (proportion)|Proportion of the firm that is owned by<br>foreign individuals, companies or<br>organizations.<br>
# **References**

Alesina, A., & Weder, B. (1999). Do Corrupt Governments Receive Less Foreign Aid? National Bureau of Economic Research Working Paper No. 7108.

Amin, M. and Soh, Y. C. (2020). Does Greater Regulatory Burden Lead to More Corruption? Evidence Using Firm-Level Survey Data for Developing Countries. Forthcoming _World Bank Economic Review_ . <u><mark>https://doi.org/10.1093/wber/lhaa007</mark></u> <mark>Aterido, R., Hallward-Driemeier, M., & Pages, C. (2011). Big Constraints to Small Firms' Growth? Business Environment and Employment Growth Across Firms.</mark> _<mark>Economic Development and Cultural Change</mark>_ <mark>, 59 (3): 609 – 647.</mark> Athanasouli, D., & Goujard, A. (2015). Corruption and Management Practices: Firm level Evidence. _Journal of Comparative Economics_ , 43 (4): 1014 – 1034.

Ayyagari, Meghana, Asli Demirguc-Kunt, and Vojislav Maksimovic. (2011). Small vs. Young Firms Across the World. Policy Research Working Paper 5631, World Bank, Washington, DC. Beck, T., & Demirguc-Kunt, A. (2006). Small and Medium-size Enterprises: Access to Finance As A Growth Constraint. _Journal of Banking and Finance_ , 30: 2931 – 2943.

Bernard, A. B., & Jensen, J. B. (1999). Exceptional exporter performance: Cause, effect, or both? _Journal of International Economics, 47_ (1), 1-25. doi:10.1016/S0022-1996(98)00027-0 Bloom, N., & Van Reenen, J. (2007), “Measuring and Explaining Management Practices across Firms and Countries,” _Quarterly Journal of Economics_ 122 (4): 135 – 1408
2022).

The strategic expansion observed may also be driven by vertical integration, where major firms increasingly act as consumer-facing service providers. Our study offers initial insights, by documenting the evolution of a firm’s number of external customers and suppliers relative to its ownership-linked firms. This represents an aspect of the data that is particularly unique. We highlight a notable trend: since 2018, Fortune 500 firms in the United States have increasingly turned their focus inward, emphasizing ownershiplinked networks over external partnerships with customers and suppliers. This shift toward more centralized, integrated operations within these corporations suggests a strategic pivot that may however be more prevalent in the U.S. than elsewhere.

Further detailed examination of these patterns, especially whether they reflect strategic diversification or are driven by other determinants, is essential. Moreover, although our findings suggest that these patterns might extend to LMICs, offering a potential pathway to enhanced economic development and sectoral integration, specific investigations into different countries are necessary to confirm this hypothesis.

In conclusion, this paper not only aligns with but also builds upon existing research, offering new insights into the dynamics within Global Value Chains in the agri-food sector. The suggested research directions can deepen our understanding and highlight critical areas for policy refinement and business strategy development, particularly in emerging markets where such insights are most urgently needed.

# **6 Conclusion**

This paper investigates the evolution and resilience of global value chains (GVCs) in the agri-food sector amid global disruptions such as trade wars, pandemics, and environmental crises. Utilizing unique data from the FactSet database and a comprehensive list of Fortune 500 firms, we analyze around 17,500 agri-food companies and over 150,000 31
relative to their pre-migration jobs. Accordingly, we restrict the sample to Venezuelan migrants (living in Ecuador) that report information on both their current job and their last job prior to migration.

The findings are collected in Table 9. Among Venezuelan migrants to Ecuador, the three most popular occupations _prior_ to migration were private-sector employment (about 116,000), government employment (about 30,000) and self-employment (21,000). In comparison, their shares of employment in Ecuador as self-employed, day laborers, domestic employees or outsourced employees have experienced large increases. In contrast, the shares of managers and government employees are sharply lower than prior to migration. More specifically, when we focus on Venezuelan migrants employed as day laborers in Ecuador, we find that their main occupations in Venezuela were private-sector and government employment. Both of these occupations are characterized by much higher wages than what day laborers typically earn and highlight the large occupational downgrading experienced by Venezuelan migrants.

# **6 Policy Simulations**

This section carries out a number of simple, yet informative policy simulations. We focus on two policy actions: legalization (in the sense of providing legal work and residence permits to all migrants) and measures aimed at improving the quality of employment for highly educated Venezuelan migrants.

## **6.1 The Effects of Legalization**

Based on the EPEC survey, approximately 90% of Venezuelan migrants in Ecuador lack legal status, in the sense that they are not authorized to work. This has important consequences for Venezuelan workers. As shown in Section 4.3, lack of legal status is associated with a higher likelihood of informal employment (column 5 in Table 7).

Inspired by Clemens et al. (2018), the goal of this section is to use the estimates of these effects to simulate the consequences of providing legal work permits to Venezuelans on the quality of their employment (measured by informality) and, through this channel, on their productivity (measured by wages).

The
Table 3: Sample actual and offered payments, acceptance rates

||Mean|sd|Max|min|
|---|---|---|---|---|
|a. Leaders|||||
|Approx. payment per ha|412|98|700|280|
|First offer in referendum|326|1678|770|80|
|Actual value - referendum value|86|163|590|-440|
|Voted yes to frst offer|0.72|0.45|1|0|
|Obs|862||||
|b. Households|||||
|Approx. payment per ha|412|98|700|280|
|First offer in referendum|329|171|770|80|
|Actual payment - referendum offer|84|165|590|-440|
|Voted yes to frst offer|0.79|0.41|1|0|
|Obs|8413||||

Values from leader (panel a.) and household (panel b.) survey.

of acceptance was somewhat lower for those leaders who were offered a contract at a value less than the one that they were supposed to receive; in these cases, 64% of the leaders voted yes, and 78% of households. This rate decreased to 59% among leaders of beneficiary communities, but remained high, at 76%, among beneficiary community households.

With regards to the second offer price, we did encounter switching consistent with a change in the level. For those who voted yes to the first contract price offered, and hence received a lower price for the second question, 27% said that they would not take the lower offer. On the other hand, among the 244 respondents in the leader survey who said no to the first offered price, 83% said yes to the second (see Appendix Tables A7 and A8).
After merging available precipitation data and dropping observations with missing data, the sample size in the 2000 IFLS3 for our analysis was reduced to 6,188 households from a total of 10,292. In our 2000 sample, 3,290 households were located in rural areas, and of these 2,159 were located on Java. Data from additional weather stations would benefit this analysis by improving the level of disaggregation of weather data, but these data could not be obtained.

**Figure 2: Variation in monsoon onset and post-onset rainfall**

<!-- Start of picture text --> 1996/1997 1999/2000 1996/1997 1999/2000<br>N. SumatraW. SumatraS. SumatraLampungJakartaW. JavaC. JavaYogyakartaE. JavaS. KalimantanBali N. SumatraW. SumatraS. SumatraLampungJakartaW. JavaC. JavaYogyakartaE. JavaS. KalimantanBali N. SumatraW. SumatraS. SumatraLampungJakartaW. JavaC. JavaYogyakartaE. JavaS. KalimantanBaliN. SumatraW. SumatraS. SumatraLampungJakartaW. JavaC. JavaYogyakartaE. JavaS. KalimantanBali<br>2<br>1<br>0<br>-1<br>-2<br>10<br>5<br>0<br>-5<br><!-- End of picture text --> Figure 2 shows variation by province in monsoon onset and post-onset rainfall. With respect to delays in monsoon onset, only provinces in Java experienced a delay greater than one standard deviation from the 25 year mean in 1999/2000. As for the amount of rainfall during the 90 day post-onset period, the data indicate that only provinces in Java experienced rainfall below two standard deviations from the 25 year mean in 1999/2000.

The summary statistics of household expenditures, household characteristics, and rainfall shock exposure in rural Java are shown in Table 1. The majority of household heads were married males who did not have more than an elementary education. The vast majority of households utilized electricity. Half of the households owned farmland, and 44% were engaged in
Although urban concentration in China is well below that of comparative countries and the world average – the Gini coefficient is 0.43 against 0.56 for the world in 2000 (see Table 3) (Henderson 2004) - just 10 major municipalities account for almost a quarter of China’s GDP and possibly a third of its growth rate (see Table 4). It is in these urban crucibles that China’s new industrial economy is being nurtured.

**Table 3: Urban Gini Coefficients of Selected Countries**

|Brazil|Japan|Indonesia|UK|Mexico|Nigeria|France|India|Germany|USA|Spain|
|---|---|---|---|---|---|---|---|---|---|---|
|0.6|5<br>0.65|0.61|0.60|0.60|0.60|0.59|0.58|0.56|0.54|0.52|

_Source_ : Henderson (2004)

**Table 4: Large cities’ share of GDP**

|Rankby GDP|City|Share ofcity GDPtonational(%)|
|---|---|---|
|1|Shanghai|5.2%|
|2|Beijing|3.1%|
|3|Guangzhou|2.9%|
|4|Shenzhen|2.2%|
|5|Tianjin|2.0%|
|6|Chongqing|1.9%|
|7|Hangzhou|1.7%|
|8|Chengdu|1.6%|
|9|Qingdao|1.4%|
|10|Ningbo|1.4%|

_Source_ : China Statistical Yearbook (2003) However, the perspectives we gain from analyzing organizational changes in the urban
Policy Research Working Paper 8836

# **Abstract**

Business survey outcomes for micro and small firms are notoriously noisy, with multiple sources of measurement and recall error. This paper introduces a new survey methodology that combines automatic consistency checks of electronic data collection with triangulation and dynamic adjustment to arrive at more precise estimates of business performance. The methodology uses insights from behavioral science to lower the cognitive cost of initial recall and establishes salient and relevant anchors to allow for dynamic triangulation and adjustment toward a final estimate. The validity of this method is field tested against traditional performance measures as well as administrative data across three emerging markets: Ghana, Rwanda, and Uganda. The results show significant upward adjustment from traditional measures for both sales and profits, a lower coefficient of variation in the cross-section, and higher autocorrelation in panel data. Comparisons with administrative data further confirm a higher correlation and closer magnitude relative to traditional measures. This research reconciles recommendations for increased attention to survey design with a method to leverage electronic survey technology beyond consistency checks.

This paper is a product of the Development Research Group, Development Economics. 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://www.worldbank.org/prwp. The authors may be contacted at bzia@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