rafmacalaba/datause-encoder-data huggingface dataset:
1998), the authors could not find a significant link between foreign direct investment by nonfinancial firms and foreign bank activities in those countries.

Relative to the “follow the clients” motivation, there is consistent evidence for the importance of local market opportunities in driving foreign bank participation. Using data on the location choices of 143 banks with at least one shareholding abroad across 28 countries (including 6 developing countries: Czech Republic, Hungary, Korea, Poland and Turkey), Focarelli and Pozzolo (2001) find greater foreign bank entry in countries where the expected rate of economic growth is higher. Analyzing 2,300 international bank mergers that took place between 1978 and 2000 in developed and developing countries, Buch and DeLong (2004) find that foreign banks tend to go to larger yet less developed economies, where there is the prospect for economies of scale and future growth opportunities. Similarly, looking into the foreign direct investments of German banks across 190 countries during the second half of the 1990s, Buch and Lipponer (2004) find that, other things equal, German banks are attracted to larger markets (in terms of GDP).

Many studies have also documented the importance of regulatory barriers as obstacles to foreign bank entry. In their study of international bank mergers, Buch and De Long (2004) find that banks operating in more regulated environments are less likely to be the targets of international bank mergers. Similarly, Focarelli and Pozzolo (2001) find that foreign banks prefer to invest in countries with fewer regulatory restrictions on bank activities. Looking at the foreign asset holdings between 1983 and 1999 of international banks that report data to the Bank for International Settlements, Buch (2003) finds that regulations are important in influencing the international asset choice of banks. Finally, focusing on the specific case of German banks’ foreign assets holdings across countries, Buch and Lipponer (2004) find that if countries impose controls on cross-border financial credits, they receive less foreign direct investment from German banks and banks also perform fewer cross-border financial services in those countries.

The evidence on the importance of geographical proximity and economic and cultural similarities in driving foreign bank participation is quite overwhelming. Studies such as Buch and De Long (2004), Buch (2003), Galindo, Micco, and Serra (2003), Buch and Lipponer (2004), Claessens and Van Horen (2006) have shown that bilateral distance, sharing a border, speaking a common language, having common colonial ties are all factors that influence foreign bank entry. There is also some evidence that similarities in the legal, regulatory and institutional 8
**Table 3:** Drivers of hidden debt revelations

||Dep|. variable: Hid|den debt revelations, 1975-2020|
|---|---|---|---|
||(1)|(2)|(3)<br>(4)|
|Real GDP growth (WDI)|-0.03**<br>(0.01)||-0.03**<br>(0.01)|
|External sov. default||0.14***<br>(0.05)|0.12**<br>(0.05)|
|IMF program|||0.13***<br>0.12**<br>(0.04)<br>(0.05)|
|Observations|3,914|4,069|4,069<br>3,892|
|R-squared|0.049|0.047|0.048<br>0.053|
|Country FE|✓|✓|✓<br>✓|
|Vintage FE|✓|✓|✓<br>✓|

_Notes:_ This table shows regression results from a fixed effects panel regression of hidden debt revelations on real GDP growth, the occurrence of a sovereign default, and IMF programs. The dependent variable is the sum of all previously unreported loan commitments of a country as revealed by a new vintage (see Section 3.2 and equation (2) for details). Real GDP growth is detrended and winsorized at the 1<sup>st</sup> and 99<sup>th</sup> percentiles. Trends were computed using the Hodrick-Prescott filter with a smoothing parameter of 100. To account for outliers and to facilitate interpretation, real GDP growth and the dependent variable are standardized. IMF program measures the first year of a program and is from Horn et al. (2020). External sovereign defaults data is from Asonuma and Trebesch (2016) and refers to all years in which a country is in default. All regressions include country and vintage fixed effects. In regression (4) we additionally control for the creditor composition of external borrowing. Robust standard errors are shown in parentheses.

# **4.3 Hidden debt is associated with larger creditor losses and longer default spells**

The previous subsection showed that revelations of hidden debt are particularly common during external sovereign default episodes. In this context, international market creditors are often concerned about the existence of hidden debt that may dilute the recovery value of their claims. In several recent debt distress episodes, uncertainty over the true level of indebtedness has been a key obstacle to distress resolution that delayed the restructuring process and exacerbated the coordination issues among creditors (see Section 2 for anecdotal evidence).

Our newly collected data allows to empirically test, whether high hidden debts (as measured by subsequent upward revisions) are systematically correlated with longer and costlier debt restructuring processes. To test this hypothesis, we merge our hidden debt measures with the datasets on external sovereign defaults and restructurings compiled by Cruces and Trebesch (2013), Asonuma and Trebesch (2016) and Asonuma et al. (2023). Their combined data captures sovereign debt restructurings with external, private creditors between 1970 and 2020 and measures both net present value creditor losses (“haircuts”) and the length of each default episode (defined by the time between the initial missed payment and the resolution through a debt restructuring). This data allows to test whether high hidden debts at the onset of a default episode are associated with (i) larger haircuts and (ii) longer resolution processes.

20
adequate employment and 44% are employed informally. Last, average monthly earnings were $331 and average hourly wages stood at $2.6 (at current prices).

The table also reports our estimates of the number of Venezuelan migrants in each canton as of the summer of 2019. The average across _cantons_ is 2,312 individuals, with a wide range of variation. While it is estimated that some _cantons_ had zero Venezuelan migrants, in Quito the estimated count is 87,505 individuals. As a percent of the population in the canton, the average across _cantons_ is 3.8% but also displays large variability.<sup>22</sup> As a percent of the population in Ecuador, our mobile records data imply that Venezuelan migrants make up 2.8% of the overall population and 3.7% of the working-age population.

Our analysis relies on the comparison of the changes in labor market outcomes (for different socio-demographic groups) across _cantons_ that differ in the _density_ of Venezuelan migrants relative to the canton’s population. More specifically, we classify all _cantons_ into three groups: low density ( _<_ 2 _._ 5%), medium density (between 2.5% and 5%) and high density of Venezuelans ( _>_ 5%). Our regression analysis will compare the evolution of several labor market indicators in the medium and high density groups relative to the low-density group before and after 2016, which we take as the first year with important inflows of Venezuelan migrants.<sup>23</sup> The cantons of Quito and Guayaquil together make up 32% of the working-age population in Ecuador. The low-density group contains 96 cantons, the medium density group contains 51 cantons and the high density group contains 31 cantons. In terms of working-age population, the low, medium and high groups account for 33%, 53% and 14%, respectively.

# **6.2 Estimation Labor-Market**

Our main analysis is based on a difference-in-difference estimation approach, applied to canton-level labor market indicators defined for several groups of workers differing in their gender, age and educational attainment.

In all cases, our main specification is as follows:

> 22As seen in Table 3, the Venezuelan share in the population ranges from 0% to 78.3%. The latter figure corresponds to one of the _cantons_ with very low population. Since the ENEMDU is not representative for these _cantons_ , we exclude the canton-year cells with the lowest population from our estimation sample. For most years, our sample contains 200 of the total of 221 cantons in Ecuador.

> 23It is worth noting that the two _cantons_ with the largest numbers of Venezuelan migrants (Quito and Guayaquil) are in the medium-density group. We estimate the density of Venezuelan migrants in the working-age population of these two cantons at 4.3% (Table 1).

14
# **1. Introduction and background**

In the past decade, special attention has been paid to generating empirical evidence on child labor for developing countries. Edmonds (2009) illustrates the boom in studies on child labor and provides an overview of labor force participation rates across a large number of countries. Recognizing the importance of both the definition of child labor and its measurement, the International Labor Organization/IPEC’s Statistical Information and Monitoring Programme on Child Labour (SIMPOC) has focused on establishing standardized methods for survey design to measure children’s work (see ILO, 2008, and ILO, 2004). Despite these efforts, there is still substantial variation in how child labor is measured. Partly this reflects the practice of measuring child labor as part of a broader survey, a consequence of the limited capacity of statistical offices in low-income countries to field frequent stand-alone child labor surveys. In turn, there can be considerable inconsistency in statistics.

Guarcello et al. (2009) carefully document the apparent inconsistency of child labor statistics from large-scale national surveys for several countries. In Ghana, for instance, a comparison between the Core Welfare Indicator Survey (CWIQ) (2003) and the SIMPOC survey (2000) shows a decline in child labor of 27 percentage points from 34 percent of children working in the SIMPOC survey. In Kenya, the Multiple Indicator Cluster Survey 2 (MICS2 2000) and SIMPOC (1998/99) surveys report an increase in child labor of 36 percentage points from 8 percent in the SIMPOC survey. Changes in child labor force participation rates over time certainly could reflect real changes – such as rapid economic growth. In this case, we would likely expect to see similar changes in school enrollment, which Guarcello et al. (2009) do not observe. Other explanations for such large fluctuations between two independent surveys administered in close proximity are survey design and sample design. However, Guarcello et al. (2009) find that differences in survey design (including questionnaire type and fieldwork season) explain only some of the variation in child labor estimates across surveys and that samples look otherwise comparable (including age, sex, and urban composition). A sizeable portion of the variation in child labor statistics remains unexplained. There is scant evidence on the impact of survey design on child labor statistics, in contrast with adult labor, where there is more evidence, especially 2
(2007).<sup>2</sup> The GIDD generates a counterfactual global income distribution by taking into account the expected changes in the age and education structure of the population, worker migration from farming to non-farming activities, changes in skilled-to-unskilled and farming-to-non-farming wage premiums, as well as different income growth rates across countries. The latter give rise to the _convergence_ component of changes in global inequality, i.e. changes in global distribution due to changes in average incomes between countries while keeping within-country inequality constant. Other changes— demographic transition, internal migration, and the evolution of wage gaps— generate the _dispersion_ component, i.e. the expected changes in the income distribution within countries. Thus, GIDD-based analysis allows us to understand how changes in global income distribution are accounted for by changes in growth rates across countries and changes in income differences within countries. By estimating a global Macro-Micro model, this study represents a big leap in our understanding of global income inequality.

The forward-looking scenario in this study draws attention to several important developments that are likely to shape the evolution of the global income distribution over the next 25 years. Convergence of average incomes of developing countries to highincome levels is likely to offset worsening within-country distributions in many nations and lead to a significant decline in global inequality. Furthermore, inequalities around the world are likely to converge as countries with high initial inequality experience a narrowing of income gaps while countries with low initial inequality are likely to see their distributions widen. Finally, these trends are likely to result in the emergence of a large global middle class, composed mostly of developing country nationals. These future trends have important political economy implications with the increase in the global middle class increasing the support for further liberalizing reforms while the rise in within-country inequality counter-balancing this effect. This tradeoff could be eliminated if trade liberalization and other market-friendly reforms are complemented with income redistribution policies.

> 2   A new dataset was assembled as part of the GIDD project. A summarized version of the new dataset containing income information by quintiles as well as a paper documenting the steps followed to construct it is available from the authors upon request.

3
# Tax Morale and Compliance: Review of Evidence and Case Studies for Europe<sup>1</sup>

by Benno Torgler<sup></sup> _JEL Classification_ : H26 , H73, D70, K42 _Keywords:_ Tax Morale, tax compliance, Europe, accountability, governance, trust 1 This paper—a product of the Human Development Economics Unit, Europe and Central Asia Region—is part of an effort to understand the underlying factors that determine the size of informal employment in the shadow economy, providing background technical analysis for a forthcoming World Bank regional study ―In from the Shadow: Integrating Europe's Informal Labor‖. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted as follows:

>  The School of Economics and Finance, Queensland University of Technology, GPO Box 2434, Brisbane, QLD 4001, Australia, e-mail: benno.torgler@qut.edu.au. He is also a research fellows of CREMA – Center for Research in Economics, Management and the Arts, Switzerland and associated with CESifo in Germany.
Table A.16: Dynamics of the effects using 2018 data. Estimating the effect of migrants’ legal status on wages after return, unconditional on return

||(1)<br>Migrate|(2)<br>Illegal|(3)<br>Return|(4)<br>Log of<br>hourly wage|
|---|---|---|---|---|
|Age|-0.001|-0.048|0.008|-0.003|
||(0.001)|(0.044)|(0.011)|(0.006)|
|Age squared|0.000**|0.000|-0.000|0.000|
||(0.000)|(0.001)|(0.000)|(0.000)|
|No education|0.001|0.412***|0.138***|-0.334***|
||(0.003)|(0.158)|(0.040)|(0.031)|
|Primary or preparatory|0.002|0.175|0.124***|-0.329***|
||(0.003)|(0.184)|(0.044)|(0.031)|
|Secondary|0.000|0.267**|0.091***|-0.222***|
||(0.002)|(0.135)|(0.032)|(0.024)|
|Rural|0.003|-0.013|-0.059**|-0.007|
||(0.002)|(0.115)|(0.029)|(0.018)|
|Oil prices|0.004***<br>(0.000)||||
|Diplomatic exchange||-0.759***<br>(0.248)|||
|Confict|||0.258***<br>(0.054)||
|Illegal status||||-0.552***<br>(0.087)|
|Legal status||||0.169***<br>(0.056)|
|Observations|10,636|1,517|1,453|6,108|
|Parental controls|Yes|Yes|Yes|Yes|
|Decades of migration dummies|Yes|Yes|Yes|No|
|Labor market controls in Egypt|No|No|No|Yes|
|Predicted log wage: Non-mig.=2.|283; Illegal mig|.=1.739; Legal|mig.=2.441||

Robust standard errors in parentheses. *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1 _Notes_ : Data comes from the 2018 ELMPS survey. Our analysis is restricted to individuals who were also interviewed in 2012. Equation 1 is the probability of temporary migration. Equation 2 is the probability of undocumented migration. Equation 3 is the probability of return migration. Equation 4 models the logarithm of hourly wages upon return. For identification of equation (1), we use the inflation adjusted historical oil prices (in US dollars). For identification of equation (2), we use diplomatic exchange between Egypt and the countries of destination of Egyptian migrants at time of migration. It is a dummy variable equal zero if there is no evidence of diplomatic exchange neither in Egypt, nor in the country of destination and is equal one if there is evidence of diplomatic exchange either in Egypt or in the country of destination at the level of charg ́e d’affaires, minister, ambassador or other. For identification of equation (3), we use the number of active armed conflicts that is both country and year specific from the Uppsala Conflict Data Project (UCDP). Equation (4) estimates the effect of illegality on the logarithm of hourly wages, unconditional on return migration. The predicted logarithm of hourly wages for non-migrants, illegal migrants and legal migrants are reported in the last row.

63
Policy Research Working Paper 11062

# **Abstract**

This paper presents the results from a novel field experiment that examined the impact of in- creasing the presence of revenue authority officers on tax compliance and tax morale among small and medium-size enterprises in a lower-income country. The experiment was embedded in the implementation of a representative, face-to-face survey of SMEs across mainland Tanzania. An independent survey firm was accompanied by Tanzania Revenue Authority officers, who observed the interviews in a randomly selected set of urban and peri-urban wards. This translated into a temporary increase in the presence of tax officers throughout parts of the country. The findings indicate that an increase in tax officer presence did not have a significant overall impact on tax compliance and tax morale among SMEs, as measured using a combination of administrative and survey data. However, there were short-term increases in compliance in the largest city and sustained increases in tax morale in the rest of the country. A follow-up survey suggests that these results were likely driven by an increase in the perceived credibility of enforcement rather than meaningful increases in perceptions of facilitation and trust.

This paper is a product of the Development Impact Group, Development Economics and the Poverty and Equity Global Department. 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 jkarver@worldbank.org. A verified reproducibility package for this paper is available at http://reproducibility.worldbank.org, click **here** for direct access.

<!-- Start of picture text --> TRANSPARENT<br>ANALYSIS<br>G<br>R E<br>N<br>S<br>I P<br>Y E<br>K A<br>C A<br>R P<br>LI R<br>O E<br>O C<br>W R<br>H<br>S<br>P<br><!-- End of picture text --> _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
# A Proxy Means Test for Targeted Social Protection Programs in Sudan

Alvin Etang, Paul Ervin, and Suleiman Namara<sup>1</sup> World Bank<sup>2</sup> Keywords : Proxy means test; poverty; consumption expenditure; welfare; targeting.

JEL : I32, I38, H53.

1 Alvin Etang is a Senior Economist in the Poverty and Equity Global Practice of the World Bank; Suleiman Namara is a Lead Social Protection Specialist in the Social Protection & Jobs Global Practice of the World Bank. Paul Ervin is a Hazard Risk Economist at North Carolina Emergency Management. This paper was prepared as part of the Sudan Poverty Analytics ASA (P174168) under the overall guidance of Pierella Paci (Practice Manager, EAEPV). The authors are grateful to Franck Adoho (Senior Economist, EAWPV) for feedback and suggestions on an earlier draft. All remaining errors and omissions are the responsibility of the authors. The authors may be contacted at aetangndip@worldbank.org, <u>paervin@gmail.com, and snamara@worldbank.org.</u> 2 On October 25, 2021 the World Bank paused disbursements in all of its existing operations in Sudan and stopped processing any new operations due to the developments in the country. These measures were adopted in accordance with the World Bank Operational Policy 7.30 “Dealing with De Facto Governments”’. The present paper is a Bank-financed product and was concluded before October 25, 2021. However, consultations with the client were not feasible due to the aforementioned pause.
# **1. Introduction**

One of the major difficulties in doing cost-benefit analyses of development projects is to estimate total values of the project benefits, which are usually multi-dimensional and include goods and services that are not traded in the market. Take a non-motorized transport (NMT) project for example. The major benefits may include improving travel convenience and safety, reducing congestion and saving time, improving environmental quality, and reducing driving costs. Most of the benefits, however, are nonmarket goods and cannot be easily valued<sup>2</sup> . Even if an economic value can be estimated for each of the project benefits, the final aggregation may still face a number of issues such as double counting. One potentially feasible solution to estimating the total value of a development project can be the contingent valuation (CV) method, with which a survey can be designed and implemented to collect preference information of the potential project beneficiaries and a total value of the project in monetary terms can be inferred. As the utility level of a respondent should be affected by the various aspects of the multidimensional benefits associated with a development project, a CV survey can be so designed that a respondent is required to consider a total value of the benefits of the project for his/her family.

After 50 years of research in the area of non-market valuation, the CV method has been developed from its initial controversial stage to a legitimate and most popular valuation approach, given that a number of survey design and execution requirements are satisfied. The CV method has been successfully developed and applied in the area of environmental economics, but has not been well tested in estimating the total value of a transport project. As a big part of the benefits of a transport project, such as time savings, improvements in environmental quality and public health, increased land value, etc., are not generally traded in the market, no such information on market demand or competitive market prices is readily available, especially in developing

> 2 Transport economists have developed sophisticated valuation models for time savings, but for other benefits there has been no much research.

2