rafmacalaba/datause-encoder-data huggingface dataset:
by Hauk and Wacziarg (2009) indicate that the coefficients on growth determinants are heavily biased toward zero in fixed-effects growth regressions. I suspect that the problem of timevarying measurement errors in both growth rates and initial distribution is even greater in the present data set, possibly reflecting survey comparability problems over time.

The problem of noise in the changes in growth rates can be illustrated if we consider the relationship between the two measures of the mean used in this study, namely that from the surveys (  _it_ ) and that from the private consumption component of domestic absorption in the national accounts ( _Cit_ ). Using a log-log regression in the levels gives an elasticity of  _it_ to _Cit_ of 0.75 (R<sup>2</sup> =0.82) for the latest survey rounds. Using a country-fixed effects specification in the levels, the elasticity drops to 0.51 (R<sup>2</sup> =0.21). However, when one also includes fixed-effects in the growth rates in the mean (using the subsample with at least three surveys) the elasticity drops to 0.09 (R<sup>2</sup> =0.07), which must be considered an implausibly low figure, undoubtedly reflecting substantial attenuation bias due to measurement error in the changes in growth rates.

# **7. Initial poverty and the growth elasticity of poverty reduction**

We have seen that countries starting with a higher poverty rate tend to see slower growth at a given initial mean. Now I turn to the second channel—how the growth elasticity of poverty reduction depends on initial distribution. This can be thought of as the direct effect of the initial distribution on the pace of poverty reduction, as distinct from the indirect effect via the rate of growth in the mean. Again I focus on the $2 line, although the $1.25 line gives similar results.

Table 4 gives regressions of the annualized change in the log of the $2 a day poverty rate against both the annualized growth rate in the mean and its interaction with the initial poverty rate. Columns (1) and (2) give unrestricted estimates of an encompassing test: _gi_ ( _Hit_ )   0   1 ln _Hit_  2  (  0  1 _Hit_  2 ) _g_ (  _it_ )  _it_ (12) Results are given for both OLS and IVE; the IVE method uses the growth rate in private consumption per capita from the national accounts as the instrument for the growth rate in the survey mean; following Ravallion (2001), this allows for the possibility that a spurious negative correlation exists due to common measurement errors (given that the poverty measure and the mean are calculated from the same surveys).

The results in Table 4 indicate that the (absolute) growth elasticity of poverty reduction tends to be lower in countries with a higher initial poverty rate. There is no sign of conditional 19
- 11 -

43. Conclusions. Any fiscal adjustment effort would need to aim at reducing the growth of the non-interest expenditures of the Central Government. This goal can be achieved through a decrease in the wage bill and transfers to public sector enterprises, economizing on expenditures on goods and services, and introducing cost-effective programs. In terms of functional distribution, further growth in military expenditures needs to be restrained. Reductions in the wage bill will likely require retiring personnel and revising wage policy. Both actions are likely to prove to be politically difficult to carry out. But, these actions are indispensable for achieving fiscal austerity. In this respect, the authorities should continue to implement the wage freeze for public employees and extend the freeze also to teachers and medical personnel. Obviously, politically strong unions could counteract these policies.

44. A large part of Central Government spending goes to wages and salaries, averaging about 45% of current expenditures and 7.7Z of GDP during 1982-87. A significsnt share of wages and s. laries are incurred in the education sector, accounting for about one-third of the public wage bill in 1986. The total wage bill grew as public employment jumped from 67,000 in 1982 to about 72,000 in 1986. About one-third of public employees were teachers in 1986.

45. Transfers also constitute a major source of Government outlays (Tables 6 and 7). A large part of these transfers go to public sector enterprises, averaging about 171 of total Central Govern,ment outlays and about 42 of GDP a year during 1984-87. Transfers to National Electricity Company (ENEE), National Water and Sewerage Service Company (SANAM), and National Agrarian Institute (INA) comprised a large share of those transfers over the last couple of years. El Cajon was the major recipient of capital transfers, while current transfers went rostly to the universities and INA.

|**Tabl-**<br>**6:**Contral Go<br>**the**Rot**of th**<br>**(mi**|vernment<br>Current**Transfe**<br>**e**Public Sector. 1984-86<br>**llions**<br>**of**t)|**r.**<br>to<br>|
|---|---|---|
||1984<br>1985|1996|
|Public Sector Enterprises|**89.8**<br>106.9|**128.5**|
|INA|(25.4)<br>(80.6)|**(81.9)**|
|**NIAN**|(48.1)<br>(67.9)|(7.56)|
|JNBS|**(9.1)**<br>(10.4)|(18.2)|
|**Municipalities**|_*.6_<br>**0.5**|**_0.6_**|
|**Others**|12.9<br>**86.8**|**81.2**|
|Total Public Sector|102.7<br>187.2|**166.2**|
|**Memorandum**<br>**Item**|||
|Total current**transfers**<br>**as**a<br>**of**GDP|**1.6**<br>**2.0**|**2.1**|

Source: Central Bonk **of** Honduras.
These are standard limitations of correspondence-based audit studies. But it does mean that the design cannot easily quantify the importance of firm-side information frictions relative to workseeker-side information frictions on the same outcome. Furthermore, we randomly match workseekers to vacancies in the audit study. This omits any role for search targeting, which the public and private certification results suggest may be important. We therefore view the audit study as less important evidence than the arms of the workseeker-facing experiments. It simply provides additional evidence that the difference between the public and private certification results can be explained by firm-side information frictions.

# **5 What Do Workseekers and Firms Learn from Skill**

The preceding two sections show that skill certification provides information that improves workseekers’ outcomes in the labor market. In this section, we explore what workseekers and firms learn from skill certification, what this implies for the effects of certification on different types of workseekers, and what this might imply for the effects of certification at scale. This section relies on smaller experiments and heterogeneity analysis of the main experiments, so we view these as secondary results.

## **5.1 Assessment Results Matter, Not Just Being Assessed**

The public certification and audit results above are consistent with three interpretations. First, our preferred interpretation is that firms and workseekers acquire information about workseekers’ skills from the assessment results. Second, firms may acquire information about workseekers’ tenacity or proactivity from their choice to get assessed, not their actual assessment results. Third, the assessment results may provide no useful information to firms but may be visually appealing or attention-grabbing because they are colorful, branded, and printed on high-quality paper. In this section, we discuss two smaller experiments whose results are consistent with the first, but not the second or third interpretations. The first interpretation is also consistent with the private certification results, while the second and third are not.

In the first experiment, we manipulate information about workseekers’ assessment results, holding constant the information that workseekers have been assessed and any visual appeal of the certificates. We randomly assign 254 candidates from our workseeker sample, assessed over 3 days, to a ‘placebo’ certification group. These candidates receive placebo certificates that are identical to the public certificates except that the actual assessment results are omitted (Figure F.1) and the psychologist’s briefing does not discuss the assessment results.

The placebo certification treatment has minimal effects on labor market outcomes (Table F.1). It increases an index of labor market outcomes by 0.03 standard deviation. This is not significantly different to zero and is significantly smaller than the public certification effect of 0.12 standard deviation. This index is an inverse covariance-weighted average of the five labor market outcomes 25
2

# **H. Different Measures of Capital Flight**

What is capital flight? Definitions are manv They can be broad, wovering all private outflows, or narrow, seeking to exclude some "normal" flows oi international transactions. for each definition, moreover, there are several different measures. And some measures are complementary; for example, trade misinvoicing can be added to one rneasure to create another. Finally, data sources differ, which give conflicting final figtlres and make comparisons among the various measures difficult. For instance, Erbe (1985) uses the same methodology as the World Bank (1985) but uses OECD (not Bank) debt data. Hardly surprising, then, that many measures of capital flight can be constructed. The four most common approaches are the residual measure (used by the World Bank, Morgan Guaranty and Cline); measuring the stock of unreported foreigrn assets (Dooley's method);<sup>3</sup> hot money measutl,s (Cuddington); and measuring trade misinvoicing. For each, there are variations which lead to (minor) differences. The starting point for all measures is balance-of-payment figures.

Balance of payments. Let us take a stylized balance-of-payments framework, using standard notaijon, but supplemented by World Bank debt data and based on the EMF's Balance of Payments Yearbook.<sup>4</sup> 3We will show below that in -ffect tne Dooley method is also a residual method. 4The presentation of items below follows that in Ciimby and Levich (1987), Chang and Cumby (1991) and Chang, Claessens and Cumby (1993). The Balance of Payments Yearbook line item numbers are those reported in the hard copy of the' BOP Year books. The corresponding codes are listed in Annex 3.
district’s employment in 2000 matters for the changes observed. Areas with a high concentration of local employment in this sector are observed to have 1989-2010 shifts toward specialization and away from diversity. In the upcoming growth analyses, we will control for the traits modeled in Table 9, so that we are measuring the impact of specialization and diversity in a district’s industrial base over-and-beyond these correlates. While this approach better isolates the role of specialization and diversity, we should not forget these two basic connections when using stricter econometric frameworks.

By contrast, the absence of some correlations is striking. In the United States, larger cities tend to be less specialized and more diversified (e.g., Black and Henderson, 1998, Duranton and Puga, 2000). Duranton (2013b) also observes this for Colombia. For India, at least with respect to manufacturing, we do not see this pattern. These null patterns are also evident with population density.<sup>11</sup> It is also striking that infrastructure metrics and banking conditions tend to have limited correlation with the specialization and diversity metrics. Finally, overall urbanization levels of districts are not clearly linked.

# **4. Economic Productivity and Growth with Specialization and Diversity**

This section describes our empirical exercises regarding economic outcomes. We first consider production functions for manufacturing establishments that estimate how the specialization and diversity levels of the district in which a plant is located link to its productivity. We then consider whether the growth of a district’s manufacturing employment links to the district’s specialization or diversity.

## _Manufacturing Production Function Estimations_

Table 8 analyzes whether local specialization or diversity relates to the productivity of Indian manufacturing establishments. We use the 2000 survey for this exercise. We estimate a 11 Our framework does not yet allow us to compare fully to the United States and Colombia in this regard. For example, we have yet to include services in our framework, and the non-traded nature of services is one reason given for the size-specialization relationship. (It is worth noting, however, that most of the informal sector employment that defines our manufacturing metrics comes in effectively non-traded forms.) Big cities, where firm headquarters and service firms are often based, tend to specialize in business services. Henderson (1997) finds that medium cities have more mature manufacturing industries (but not newer technology-centric manufacturing).

17
and rule of law, even after controlling for potential reverse causality (Abdih, Chami, Dagher, and Montiel 2012).

A related literature explores whether temporary migration contributes to the transfer of cultural and social norms to the home country. Migrants can be a vector of cultural transmission, and empirical findings using the World Values Survey data indicate that this transmission occurs from host to home countries rather than the other way around (Rapoport, Sardoschau, and Silve 2020). The few country-specific empirical studies are consistent with this finding. Return migrants in Egypt have been found to adjust their fertility choices to the norms that prevail in their previous country of destination (Bertoli and Marchetta 2015). Return migration can also contribute to transfer of gender norms back home. In Jordan, controlling for both emigration and return migration selections, women with a family member who returned from more conservative Arab countries are more likely to bear traditional gender norms than women in households with no migration experience (Tuccio and Wahba 2018). In Mali, girls who live in villages with a higher share of returnees from other African countries, where female circumcision is uncommon, are significantly less likely to suffer from genital mutilation (Diabate and Mespl ́e-Somps 2019).

# **8 Conclusions and areas for further research**

This paper offers a summary and discussion of the multiple and complex linkages between temporary migration and economic development in origin countries. Despite a rapidly expanding literature, significant knowledge gaps remain. First, much of the existing literature focuses on high-skilled temporary migration. Evidence on the impacts of low-skilled migration is much sparser, despite the fact that temporary emigration from many developing countries is largely low-skilled. For instance, while high-skilled migration increases educational investment in origin countries in various settings, it remains unclear whether low-skilled emigration reduces incentives to invest in education. Similarly, while high-skilled migrants have been shown to accumulate human capital while they are overseas which ultimately benefits home labor markets, there is still limited evidence on whether low-skilled migrants experience human capital gains. Second, the vast majority of the literature has been treating temporary migration has a one-time event. Yet, the impacts of repeated/circular migration for the home country are much less understood. This is partly driven by data availability as one would need detailed historical data on all the migration episodes undertaken by workers and their outcomes to analyze repeat migration. Third, even though policy makers in migrant-sending countries are often concerned about the possible discouragement effect of past migration on economic participation in home labor markets, this question has 33
Policy Research Working Paper 8376

# **Abstract**

Despite the growing numbers of forcibly displaced persons worldwide, many people living under conflict _choose_ not to flee. Individuals face two lotteries—staying or leaving—characterized by two distributions of potential outcomes. This paper proposes to model the choice between these two lotteries using quantile maximization as opposed to expected utility theory. The paper posits that risk-averse individuals aim at minimizing losses by choosing the lottery with the best outcome at the lower end of the distribution, whereas risk-tolerant individuals aim at maximizing gains by choosing the lottery with the best outcome at the higher end of the distribution. Using a rich set of household and conflict panel data from Nigeria, the paper finds that risk-tolerant individuals have a significant preference for staying and risk-averse individuals have a significant preference for fleeing, in line with the predictions of the quantile maximization model. These findings are contrary to findings on economic migrants, and call for separate policies toward economic and forced migrants.

This paper is a product of the Fragility, Conflict and Violence Global Theme. 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 pverme@worldbank.org or Lidia.Ceriani@georgetown.edu.

_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
Still, we end this section on an optimistic note that more methods have recently been developed in an effort to provide more comparable wealth indexes over time. For example, a promising direction of research is offered by Rutstein and Staveteig (2014), who adjust, relative to a reference country, a country-specific wealth index using the country-level relationship between some “unsatisfied basic needs” and ownership of certain basic assets such as a car, a refrigerator, a landline telephone, and a television. This study builds on earlier studies that employ asset indexes to analyze poverty trends over time (e.g., Sahn and Stifel (2000)), but it does not use consumption data to validate its estimates based on the asset indexes.

# **IV. Partially Missing Consumption Data**

To further operationalize our estimation framework, we extend Equation (1) to a more general model where the error term ��� is now broken down into two components, one (���� a cluster random effects and the other (��� the idiosyncratic error term. Note that we also suppress the subscript that indexes households to make the notation less cluttered. Conditional on household characteristics, the cluster random effects and the error terms are usually assumed uncorrelated with each other � � and to follow a normal distribution such that ���|��~��0, ���� and ��|��~��0, ����. While the normal distribution assumption results in the standard linear random effects model that is more convenient for mathematical manipulations and computation, it is not necessary for this type of model. As can be seen later, we can remove this assumption and use the empirical distribution of the error terms instead, albeit at the cost of somewhat more computing time.

for all time periods, this bias would cancel out for estimates of the trends in consumption—or the relative growth of the mean. We provide more formal discussion of this result in the proof for Proposition 1.

18
# **5. Lessons learned from other ‘hard to survey’ populations**

Sexual orientation, gender identity and/or expression, are complex, deeply internal processes.<sup>61</sup> Surveys assume that the respondents ‘know’ the information that is being asked about and is willing to reveal it. For sexual orientation, gender identity and expression this will often not be the case. That said, there are other identities that are highly personal (e.g. faith) and in many contexts, these are also subject to stigma and discrimination and are therefore sensitive questions that could be potentially dangerous to disclose. Many of the above-described methodological problems in reaching LGBTI communities and comparing their experiences to those of the non-LGBTI population are familiar to researchers looking at other ‘hard to survey’ populations – such as victims of domestic violence, drug users or sex workers.

Past studies and surveys of sexual and gender minorities have built on experiences with other hard to reach populations. What is often needed is a set of culturally sensitive questions that allow respondents to articulate their own self-identification. This, of course, makes meaningful quantitative analysis more complicated. The most challenging part of data collection for any of these groups is defining the target population and sampling them. The Nepal and India surveys used a venue-based snowball convenience sampling method, in which key actors of the community distributed the surveys and each respondent was encouraged to do the same. This method has been used for communities where other standard probability sampling methods are problematic. Respondent-driven sampling,<sup>62</sup> another form of chain-referral sampling, takes into account the nature of the referrals and has been used in some cases to correct for bias in the overall network. Online surveys, such as the FRA, are another approach with its own challenges.

Surveys of vulnerable groups require a high amount of privacy and trust in order to overcome barriers to non-response, inaccuracy, and access. Many LGBTI people face violence as result of their sexual orientation, non-conforming gender identity and expression, and/or sex characteristics similar to many victims of gender-based-violence. Analogous to surveys on sexual and gender-based violence, protocols, and training programs need to be developed to ensure that respondents feel safe in answering surveys, are not put at the greater physical, emotional or psychological risk by doing so and can be appropriately referred to counseling and welfare services as needed. This will also lead to better data as people are more likely to disclose their true experiences when they feel safe.

> 61 In this sense, Intersex might be viewed differently since it is a relatively clear defined medical term and while Intersex people might face similar discrimination and exclusion they also have unique subset of challenges that LGBT people do not face.

> 62 Similar methodology to snowballing. A mathematical model of who recruitment process is than used to weight the sample. More information

18