rafmacalaba/datause-encoder-data huggingface dataset:
Policy Research Working Paper 11055

# **Abstract**

The paper examines the early integration of Ukrainian refugee students into Italy’s education system following the Russia’s invasion of Ukraine in 2022. Using administrative and survey data, the study presents enrollment trends, academic performance, and barriers to educational integration. Findings from the analysis indicate that Ukrainian refugees face lower enrollment rates, higher absenteeism, and lower test scores than other students, particularly in subjects requiring language proficiency. Despite these challenges, teachers often recommend Ukrainian refugee students for advanced educational tracks, thus revealing their optimism about the potential of these students. Language barriers, mental health challenges, and uncertain futures are identified as major obstacles to integration. The study highlights the importance of tailored interventions, such as psychological support and more dedicated teaching time, to foster refugee students’ academic and social inclusion.

This paper is a product of the Development Data Group, Development Economics and the Social Protection and Labor 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 michela_carlana@hks.harvard.edu; pcastaing@worldbank.org; mtestaverde@worldbank.org; and mtiberti@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
boom generation. As long as this generation is effectively integrated into the labor force through increased investment in education and in fixed capital assets, an economy can reap the demographic dividend of higher growth as in East Asia during the 1970s through the 1980s (Bloom and Canning 2003; Bloom and Williamson 1998). However, using the cross-country differences in the timings of key medical inventions in the 20<sup>th</sup> century as instruments, Acemoglu and Johnson (2006) do not find any effect of an increase in life expectancy on per capita income growth nor on the overall size of the economy.<sup>37</sup> Such an effect can be seen only when the increase in population is also accompanied by a corresponding increase in capital accumulation, in line with neoclassical growth theory (Acemoglu and Johnson 2006).

# _Education_

Although the actual magnitudes and effects of education on income and growth also bear the taint of endogeneity (as does health), many consider it plausible that education influences the level of income and growth. In fact, Jamison, Lau, and Wang (2005) show that education affects both the income and the growth, although the effect seems to be small. There are a number of links between health and education. One such link runs from lower fertility typically to a higher level of investment in children’s education by parents. In addition, lower mortality will lead to an increase in investment in human capital because the investment can be recouped over a longer time-horizon (Bloom and Canning 2003; Morand 2005). Acemoglu and Johnson (2006) do not find any support for this claim but the effect of health on education is noted in other studies.<sup>38</sup> Healthy children are more likely to pay attention during the class, will attend schools more often, and they tend to fare better in school. Using a longitudinal survey from Guatemala, Behrman and others (2003) find that children receiving nutrition supplements given at an early age (6-24 months) tend to have superior educational

> 37 Acemoglu and Johnson (2006) estimate that a 1% increase in life expectancy leads to 1.5% increase in the population size.

> 38 Education is also a key determinant of an individual’s health.  A study of 22 European countries finds that people with low educational attainment tend to report lower self-reported health.  However, the inequality in health status arising from education attainment varies greatly among different countries, sex, and age groups (von dem Knesebeck, Verde, and Dragano 2006).

17
Policy Research Working Paper 6033

# **Abstract**

In recent years, world food prices have increased and fluctuated widely. This paper explores the impact of international food prices and domestic policies on Millennium Development Goal (MDG) and macro indicators for two archetype low-income countries, a net food exporter and a net food importer, using Maquette for MDG Simulations (MAMS), a Computable General Equilibrium model. The simulations, which cover the period 2011–2025, indicate that the size of positive (negative) effects on macro and MDG indicators of a food export (import) price increase depend on the initial gross domestic product share for food exports (imports), leaving countries that are heavily involved in international food trade more exposed to international shocks. Given relatively low elasticity estimates, the impact of changes in food prices on undernourishment are relatively marginal. Flexible responses (in terms of production shares, whether output is exported or sold at home, and whether domestic demanders buy imports or domestic output) enable countries to benefit from or be less hurt by price changes. The case for policy responses to higher import prices is stronger for the net food importer. An untargeted food subsidy, financed by taxes or spending cuts, reduces undernourishment at the cost of a slight deterioration for most other indicators. By contrast, aid-financed food subsidies neutralize the negative impact of higher import prices whereas financing via domestic borrowing is counterproductive, leading to a deterioration across all indicators. If administered at moderate costs, tax-financed targeted transfers more effectively reduce headcount poverty and inequality with macroeconomic repercussions similar to those of taxfinanced subsidies.

This paper is a product of the Prospects Group, Development Economics. Prospects Group, prepared as background to the forthcoming Global Monitoring Report 2012 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 author may be contacted at hlofgren@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
vector of scores for a particular activity. The first element corresponds to the score related to the occupation with the highest score within a specific activity, while the last element corresponds to the score related to the occupation with the lowest score within the same activity, such that: The components of the vector are then normalized as follows: We implement this procedure for each of the 41 activities. The normalization allows us to speak to the relative importance of such a skill among Brazilian workers. For instance, a score of 0.05 suggests that only 5% of employed workers supply this skill less intensively, whereas a score of 0.95 suggests that few workers supply the skill more intensively.

Our interest in this paper is in how technology impacts routine, manual skills as compared to non-routine, cognitive skills; that is, our interest is in broader skill groupings than those described in the raw O*NET database. Therefore, we next aggregate across activities within a “bundle” for each occupation. We consider the following activity bundles: routine versus non-routine activities. Routine activities are further disaggregated into manual, routine activities and cognitive, routine activities. Non-routine activities are also further disaggregated into manual and cognitive activities. We then also distinguish between nonroutine, cognitive activities that are analytical versus non-routine, cognitive activities that are interactive or communications-oriented. Table 3.1 displays our classification of the 41 O*NET activities into these six distinct bundles.

It is important to note that in contrast to some papers in the literature relying on O*NET data, we classify and make use of all O*NET activities, rather than hand-picking a select one or few. We believe this strengthens the value of our results. As evidence of a high-quality match, 14
1 The importance of fiscal policy in the developing countries has long been recognized. More and more economists have recently argued that fiscal policy plays a crucial role in the determination of overall economic performance In the LDCs. In fact, new empirical studies suggest that macroeconomic (and especially fiscal) stability nay indeed be **an** important element in explaining the difference in real performance between the East Asian and the Latin American countries.I However, in spite of important recent developments in theoretical, and to some extent empirical, aspects of the macroeconomics of fiscal policy, modern analyses have until now failed to address the key question of what determines a country's fiscal stance. In a phrase, the problem Is that economists most of the time treat fiscal policy as exogenous, and consider the policymaker to be like a machine that can be programmed. Very few studies ask questions like: 'Why do some countries rely heavily on the Inflation tax, while others use primarily direct taxation?" Or, "Why do some Central Banks (or monetary systems for that matter) allocate a high proportion of their credit to the public sector and others don't?"<sup>Even</sup> fewer studies have used modern economic analysis to ask what type of institutions or legal arrangements will help maintain fiscal discipline and sustain stabilization efforts. There **is** little hope that we will be able to provide lasting policy advice until we understand the forces underlying the Iin nost (but not all) Latin American countries we observe cycles that go from fiscal Indiscipline to real exchange rate overvaluation, to increased trade restrictions and exchange controls. There is wide agreement that this scenario Is translated Into poor economic performance. On the other hand, this typo of behavior has been largely absent in the East Asian nations. See, for example, the Wiorld Develonment ReaD= 1988 as well as the abundant literature on adjustment that has emanated in the last few yeari from the World Bank and the IMF.
Policy Research Working Paper 8886

# **Abstract**

Current measures of fiscal impoverishment and gains are not consistent with the law of diminishing returns. This paper proposes new measures of fiscal impoverishment and gains that are consistent with the law of diminishing returns, based on a methodology that gives more significance to greater income gaps, and more importance to the experience of the poorest individuals within the fiscal system. The new indicators are decomposable and cover the incidence, intensity, and severity of fiscal impoverishment and gains. An empirical illustration using the 2014 household consumption data reveals that, overall, in Niger the fiscal system is improving the welfare of the population: only 33.2 percent of the population has become poorer due to the fiscal system, while the remaining 66.8 percent has become richer because of it. Moreover, the mean relative fiscal loss (0.014), is 11 percent lower than the mean relative fiscal gain (0.126).

This paper is a product of the Poverty and Equity Global Practice. 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 mcoulibaly2@worldbank.org/asanoh@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
elderly women heading the sending households interviewed had various health ailments: one had high blood pressure and visited a clinic regularly for medicine, one reported falling ill and having to leave her job, and another was losing her eyesight due to sugar diabetes.

On top of physical limitations, these women tend to head large households with inconsistent and insufficient funds. Those that can, brew beer to sell locally, although this is not lucrative and one noted the risks involved and stopped brewing: “People would start fighting when they got drunk and I did not want any trouble because of that.” In many cases, the fathers of their migrant daughters’ children are absent: “[the fathers] are not around; some of them neglect their children. All they do is make children and pass by”. Interviewers were surprised by how little farming the rural households were engaged in, whether due to a lack of able bodies, climate change, or low agricultural productivity overall. A surprising number of households rely solely on migrants’ remittances and old‐age pensions of grandparents living in the family household.<sup>14</sup> Instead, most case studies were the main breadwinners of their family households. However, remittances are often inconsistent: “My daughters are the ones that buy me gas when they want to”; “They do it randomly, it all depends on who is able to send me money”. The grandmother of an unmarried domestic worker details the uncertainty: “What gets to me is my son’s [case study’s father] working in South Africa as a miner because he barely helps with the children and I have no one to seek help from. He knows very well the burden he has left me with of taking care of his children. He does not come home often and does not even send money regularly. He does not help much in the household necessities.” Further, remittances only cover education costs and basic needs: “I would die [if she stopped remitting], I depend on her alone, I would be really affected.” One sending household even reported being unable to feed children outside of breakfast: “I cannot afford [children’s lunch boxes]. They eat breakfast at home and that will be it. They will eat at school when every child is fed at lunch hour.”

> 14 According to HBS 2013/2014, Q3, while 15% of households receive an average of M503 per month in old age pensions from the government, only people older than 70 are eligible to receive them. Rural households receiving old‐age pensions are nevertheless less likely to report having a member move away over the past 12 months. Among rural households, 19% of those without any members who moved away recently report receiving old‐age pension, compared to only 16% of those with recent internal migrants. The HBS data do not enable us to identify longer‐term migrants however.

24
**Table 6: Motivations for Leaving Previous Job and Starting Business**

|Motivation|1|2|Cluster<br>3|4|5|6|
|---|---|---|---|---|---|---|
|_Why Did You Leave Your Last Job?_|||||||
|Laid off or business closed|13.7|26.7|19.5|9.9|19.8|13.3|
|Contract ended|3.3|4.6|6.3|5.7|6.4|6.0|
|Pay too low|25.6|18.2|31.8|17.4|25.6|25.4|
|To be independent|49.3|44.1|35.1|58.5|31.2|42.9|
|Retired|1.9|_1.5_|0.9|1.7|3.7|1.7|
|Illness or injury|1.9|1.2|2.7|0.9|7.8|4.5|
|Other'|4.1|3.8|3.7|5.9|5.4|6.2|
|No Response|17.7|14.9|22.0|30.3|14.5|24.7|
|Total|100|100|100|100|100|100|
|_WhyDid You Start This Business?_2|||||||
|Fired or laid off|2.8|7.4|3.5|0.6|5.1|1.5|
|No other work available|5.2|10.7|15.2|13.2|22.0|15.7|
|To be independent|52.5|41.0|41.8|59.2|42.9|44.6|
|Family tradition|12.7|8.4|9.9|14.4|3.6|13.3|
|Complement family Y|10.8|13.3|13.8|10.9|16.1|12.9|
|Higher pay than salaried|33.3|23.3|27.8|24.7|22.4|24.1|
|Flexible hours|1.7|2.3|3.7|2.9|3.5|_3.5_|
|Total Observations|640|309|1409|174|1092|802|
|%of sample|14.5|7.0|31.8|3.9|24.7|18.1|

' Includes family responsibilities or moving. 2 Multiple'responses possible.

Table7: **Main Business Problems (in percent)'**

|Problem|1|Cl<br>2|uster<br>3|4|5|6|Total|
|---|---|---|---|---|---|---|---|
|Lack of clients|53.6|48.2|63.7|56.9|62.3|61.7|60.2|
|Lack of credit|12.5|19.4|9.2|9.2|6.4|5.4|9.0|
|Lack of economic resources|18.4|22.7|21.2|13.2|23.9|17.1|20.5|
|Low earnings|40.9|42.7|43.6|47.7|49.0|47.8|45.4|
|Problems with authorities|7.2|19.7|6.7|16.1|5.6|4.4|7.4|
|Excessive competition|43.0|52.4|44.9|53.4|40.8|45.9|18.4|
|Problems with workers|2.0|2.3|0.6|2.3|0.7|1.1|1.2|
|Late payments|13.4|13.9|12.2|8.6|10.6|9.1|7.5|
|Raw materials problems|3.1|3.6|3.6|2.3|3.3|2.9|3.3|

'Multiple responses possible.

29
Table A24: Robustness of impact on economic outcomes index to differential attrition

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|---|---|---|---|---|---|---|---|
||Main|Trimming|treated|Im|puting cont|rol|IPW|
||spec.|Bottom<br>UB|Top<br>LB|95th pc.|75th pc.|50th pc.||
|T1 (Safe Spaces)|0.05|0.07|0.01|0.04|0.04|0.05|0.06|
||(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|
|T1+Leaders|0.02|0.15|-0.20**|-0.05|-0.01|0.03|0.03|
||(0.11)|(0.11)|(0.10)|(0.11)|(0.11)|(0.11)|(0.11)|
|T2 (Safe Spaces + IGA)|0.18**|0.25***|0.05|0.13|0.15*|0.19**|0.18*|
||(0.09)|(0.09)|(0.10)|(0.09)|(0.09)|(0.09)|(0.09)|
|T2+Leaders|0.24***|0.41***|0.02|0.16*|0.20**|0.23***|0.24***|
||(0.09)|(0.10)|(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|
|T3 (Safe Spaces + Husbands Clubs)|0.29***<br>(0.08)|0.47***<br>(0.09)|0.09<br>(0.08)|0.19**<br>(0.08)|0.23***<br>(0.08)|0.28***<br>(0.08)|0.30***<br>(0.08)|
|T3+Leaders|0.27**|0.31***|0.21*|0.25**|0.26**|0.27**|0.27**|
||(0.12)|(0.11)|(0.11)|(0.12)|(0.12)|(0.12)|(0.12)|
|T4 (control spillover)|0.07|0.08|0.07|0.07|0.07|0.07|0.07|
||(0.07)|(0.07)|(0.07)|(0.07)|(0.07)|(0.07)|(0.07)|
|N|3003|3002|3002|3004|3004|3004|3003|
|Control Mean|0|0|0|.002|.001|0|0|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. Column (1) replicates the main results presented in tables 3, 4 and 5. Columns (2)-(3) present results equivalent to Lee bounds: we re-run the estimations after dropping _K_ observations from the top/bottom of the distribution in the treatment group to calculate the lower/upper bound, where _K_ is the difference between the number of attriters in the treatment groups and the control group. Columns (4)-(6) present similar results, but instead of dropping _K_ observations in the treatment group, we impute the outcomes of _K_ attriters in the control group using the 5th, 25th and 50th percentiles of the observed distribution of the treatment group. Column (7) presents the Inverse Probability Weighting (IPW) estimates.

56
Policy Research Working Paper 6784

# **Abstract**

Negative attitudes toward groups in society are widespread and underpin systematic processes of social exclusion that marginalize people and deny them opportunities and dignity. This paper looks at the processes underlying social exclusion. It uses data covering Eastern Europe and Central Asia to study the responses to a simple hypothetical survey question about which specific groups respondents would not like to have as neighbors. Unwelcoming attitudes toward groups such as immigrants, ethnic minorities, the poor, HIV+ individuals, and others are surprisingly common. These attitudes fall into three distinct clusters: intolerance for the poor and for different lifecycle stages; intolerance toward stigmatized attributes and behaviors; and intolerance toward specific identity groups. An empirical analysis of the determinants of attitudes shows that country-specific factors are far more important than socio-economic characteristics. These findings could have important implications for theories about exclusion and for the design of appropriate social inclusion policies. The authors argue that strategies to address social exclusion need to consider ways to change social norms, attitudes, and behaviors toward disadvantaged groups. The paper explores potential entry points for change within formal and informal institutions.

This paper is a product of the Social Development Unit, Sustainable Development Network. 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 SLakhani@worldbank.org, ASacks@worldbank.org, and RHeltberg@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
**To Impute or Not to Impute? A Review of Alternative Poverty Estimation Methods in the Context of Unavailable Consumption Data**

Hai-Anh H. Dang<sup>*</sup> Key words: poverty, imputation, consumption, wealth index, synthetic panels, household survey JEL: C15, I32, O15

> * Dang (hdang@worldbank.org) is an economist in the Survey Unit, Development Data Group, World Bank, a nonresident research scholar with School of Public and Environmental Affairs, Indiana University, and a non-resident senior research fellow with Vietnam’s Academy of Social Sciences. We would like to thank Gero Carletto, Dean Jolliffe, and Peter Lanjouw for helpful discussions on related work. We are grateful to the UK Department of International Development for funding assistance through its Strategic Research Program (SRP) and Knowledge for Change (KCP) program.