rafmacalaba/data-use-mentions-extended huggingface dataset:
for the assortative matching by gender we observe in our data.

We also run our main specifications on a data set which only includes customers transacting at matched agents (i.e., those for whom registration and transaction data could be matched). We do this to ensure that our results hold when we limit observations to transactions with agents that are largely similar. We create two different data sets: one with only transactions at matched agents and another that includes all transactions of customers who transacted at least once with a matched agent. The results are reported in Columns 9 and 10 of Table 4, respectively. Columns 9 and 10 report odds ratios of 2.098 and 1.825, respectively (both p-values are 0.000) and indicate an even stronger association between agent and customer gender with the restricted data set than in our preferred specification in Column 4 of Table 4 (odds ratio = 1.518, p-value = 0.000). Columns 9 and 10 of Table 6 also confirm the findings of Column 4, Table 6 that females transact larger amounts at female agents. Since matched male and female agents are comparable (Table 1), these robustness checks suggest that our results are not driven by unobservable factors.

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Policy Research Working Paper 10194

# **Abstract**

This paper examines the influence of gender inequality on poverty among Syrian refugees in Jordan between 2013 and 2018. Two waves of Home-Visit surveys, collected by the United Nations High Commissioner for Refugees, are analyzed to track the evolution of poverty among Syrian refugees in Jordan. To compare changes in poverty between female- and male-headed households, the paper uses relative comparisons of deciles in the expenditure distribution and quantile regressions. The analysis adjusts the poverty measure for economies of scale as the cost per person of maintaining a given standard of living may fall as household size rises. The findings show that the spending distribution has shifted over time, negatively affecting female-headed households. In 2013, female-headed households below the median had lower expenditure than male-headed households. In 2018, this pattern occurs in all deciles. The findings also show small differences between poverty rates of female- and male-headed households whether the poverty measure is adjusted for economies of scale or not. Regardless of the poverty measure, the poverty gender gap has increased over time, with female-headed households experiencing poverty more intensely. Female single caregivers remain at the most risk of falling into poverty when compared with other types of households and over time. This approach can help policy makers design more effective programs of assistance that respond to gender-based differences in vulnerability to poverty and find durable solutions for displaced populations.

This paper is a product of the Gender 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://www.worldbank.org/prwp. The authors may be contacted at lhanmer@worldbank.org and erubiano@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
br>Poverty Rate Poverty Rate<br><!-- End of picture text --> _Source_ : World Bank staff calculations, based on WDI and CBS data

# 5 Triangulating poverty projections with available evidence

As discussed in Section 3, the HNAP 2022 survey could provide a reasonably good assessment of the current extent of monetary poverty in Syria. While the consumption aggregate based on the HNAP 2022 survey is not comparable with the comprehensive recording of consumption from pre-conflict official household budget surveys, it is most likely providing a more accurate characterization of monetary poverty in Syria compared to projections based on a distribution neutral nowcasting approach, including on the subnational profile of monetary poverty. Using the nominal consumption aggregate obtained from the HNAP 2022, monetary poverty in Syria is the highest in northeastern governorates (Figure 8). Can this evidence be corroborated?

Similarly, as discussed in Section 4, distribution neutral approaches could lead to very different dynamics of the temporal evolution of poverty, depending on the underlying NA aggregate used to project growth in average household consumption. Based on the assessment of the likely quality of each aggregate, estimates of growth based on per capita GDP in current prices deflated using the CPI should be preferred over the default nowcasting estimates obtained using constant prices per capita GDP. As shown in Figure 11 and Figure 12, poverty trends based on per capita GDP in constant prices would lead to a monotonic poverty increase over the conflict period, whereas estimates using per capita GDP in current prices deflated with the CPI would lead to an increase in poverty over the period 2011-2016, followed by a poverty decline between 2016 and 2019, and again an increase thereafter. Can these trend dynamics be corroborated?
pansion of international bandwidth and a similar drop in mobile broadband price. In Tunisia, the arrival of a submarine cable in 2014 (Didon) was associated with a percentage drop in the price of mobile broadband.

Telecom sector research and industrial organization theories suggest two main channels through which SMCs can affect Internet access prices in the short run. First, the deployment of SMCs can result in cost savings on international connectivity for telecom operators through (i) economies of scale brought by increased international Internet bandwidth; (ii) a drop in data (re)routing cost supported by greater connectedness enabled by new SMCs; and (iii) a drop in network maintenance cost due to stronger resilience induced by the duplication of SMCs routes. Depending on the intensity of competition along the local broadband (BB) value chain, part of these cost savings can be passed onto end-users in terms of reduced price. Second, deploying SMCs can reduce barriers to entry into broadband markets, especially when the new infrastructure is shared under an open and non-discriminatory basis among retail broadband operators. In both cases, regulation can enhance these effects. These effects pertain to the short term, i.e., assuming no change in the availability and quality of connectivity for end-users. In the long run, changes in availability and quality of connectivity stemming from investment in middle and last-mile infrastructure may exert upward pressure on price.

In this paper, we assembled a dataset on SMCs to investigate their impact on price and the role of competition and regulation, controlling for several confounding factors, including the availability and quality of connectivity and market size. In particular, we sought to assess the impact of SMCs on price; how it evolves; regional heterogeneity; the biggest drivers of the impact, especially the relative influence of cost savings versus competition; and how this depends on the regulatory environment.

Our dataset covers more than 150 countries across all regions over 12 years (2008-2020) and includes detailed information on the capacity of SMCs, measured by the amount of international
baseline models using the index computed over a 5-year estimation window (PIQ-Q). One advantage of the PIQ-Q index is that it allows us to use a panel with nonoverlapping periods (we can only do this for sovereign rating because the spreads data do not have sufficient time-variation). While PIQ-Q is based on a smaller number of projects, it produces results that are fully in line with our baseline (see Columns 1-4 of Table A4 and panels 1-4 of Figure A4). Columns 5 and 6 of Table A4 and the corresponding panels of Figure A4 show that our results are robust (in fact, they become stronger) when we use non-overlapping periods.

# **3.4. Implications for public debt sustainability**

As a final empirical exercise, we test whether public investment quality affects the relationship between public investment and the evolution of the public debt-to-GDP ratio. Specifically, we compute impulse responses through a local projections model estimated separately for high- and low-PIQ countries. Formally, we estimate the following model: 20
- Brodmann, S., Pouget, Y., & Gatti, R. (2010). Labor Mobility in the Middle East and North Africa: Challenges and Opportunities. _World Bank, Washington, DC_ .

- Carletto, C., & Kilic, T. (2011). Moving up the ladder? The impact of migration experience on occupational mobility in Albania. _Journal of Development Studies_ , _47_ (6), 846–869.

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- De Bel-Air, F. (2016). Migration profile: Egypt.

- De Coulon, A., & Piracha, M. (2005). Self-selection and the performance of return migrants: the source country perspective. _Journal of Population Economics_ , _18_ (4), 779–807.

- Devillanova, C., Fasani, F., & Frattini, T. (2018). Employment of undocumented immigrants and the prospect of legal status: evidence from an amnesty program. _ILR Review_ , _71_ (4), 853–881.

- De Vreyer, P., Gubert, F., & Robilliard, A.-S. (2010). Are there returns to migration experience? An empirical analysis using data on return migrants and non-migrants in West Africa. _Annals of Economics and Statistics/Annales d’ ́economie et de statistique_ , 307–328.

- Dustmann, C., Fasani, F., & Speciale, B. (2017). Illegal migration and consumption behavior of immigrant households. _Journal
sample was drawn from a listing of households in randomly selected Grama Niladhari divisions. The SME survey of larger firm owners selected surveyed firms with between 5 and 250 workers (including the owner). This sample was drawn from a listing of visible enterprises conducted for other purposes by the Sri Lanka office of AC Nielsen. We surveyed owners first in April 2008, and resurveyed in April 2009 and April 2010. The questions from the wage worker and SME surveys that we used in the analysis for this paper are described in the text.

# **Appendix 5: Round by Round Survey Attrition Rate**

Appendix Figure 5 shows the attrition rate by round, in terms of whether we have information on whether the business is still open/the owner is self-employed, and in terms of whether we can measure whether the enterprise has paid workers. Starting in round 7 we added a module which collected information from relatives, friends, and neighboring businesses if the business was not able to be interviewed, resulting in a reduction in attrition at that time. The attrition rate averages 5.6 percent for data on whether the business is operating, and 9 percent for data on whether the business has paid workers. Attrition rates are balanced for treatment and control in most waves, and in the last round we have data on employment for all but 8 percent of firms.

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# **4.5.6 Paid Family Leave: Impact on Living Standards**

The evidence reviewed on paid family leave shows, on one hand, that prolonged absences from the labor market might reduce labor market attachment; and on the other, that allowing workers to take time off a job (they can come back to) when they need it might reduce turnover and have beneficial effects both in terms of wages as well as employment levels.

**The impact of paid family leave on employment:** In a cross-country comparison, more generous family-friendly policies have been shown to lead to increased women’s employment, but they might do so via more part-time work and reduced access to high-level positions (Blau and Kahn, 2013).

However, more recent evidence for the United States, using more complex research designs and micro-data shows conflicting views. On the one hand, Byker (2016) finds that after the introduction of paid parental leave in California and New Jersey, women who otherwise would have exited the labor force temporarily in the months around a birth experienced an increase in labor force attachment, making them more inclined to continue participating in the labor force. On the other, Bailey et al. (2019) use administrative data to study the effects of California’s new paid leave on women’s careers and find no effects in the short run on women’s employment, earnings, or attachment to employers—but negative effects in the long run on employment and wages.

Rossin-Slater (2017) reviews the recent literature on maternity and family leave policies, not only in the US but also around the world, and finds are positive long-run effects on women’s employment outcomes in terms of job continuity and employment rates of less than 1-year-long leave; but that longer leaves can negatively affect women’s earnings, employment, and career advancement. Similarly, Sch ̈onberg and Ludsteck (2014), exploit Germany’s 5 major maternity leave expansions to find a very small negative
# Links to poverty, inequality, and human capital

In addition to evidence from specific interventions, policies, and programs showing the instrumental value of social sustainability and its key components, cross-country analysis also indicates that cohesion, inclusion, resilience, and process legitimacy are associated with macrolevel development objectives. There is a small but growing body of micro-level evidence, as well as the World Bank’s new Social Sustainability Global Database (SSGD), which finds that these four components are all correlated with poverty reduction, human capital, human development, and inequality.<sup>xi</sup> (See Annex A for illustrations of these correlations and Annex B for a full list of each index’s indicators and details on their construction.) Several of these correlations are strong—namely, inclusion and process legitimacy with poverty reduction and human capital as well as process legitimacy with inequality. Indeed, process legitimacy is among the most strongly correlated indexes, underscoring the importance of factors like the rule of law, fairness, justice, and government effectiveness for the broader development agenda. However, some correlations are weaker. This variation likely reflects data shortcomings and measurement challenges (including the need to refine SSGD indicators) as well as the inherent methodological difficulty of unpacking complex social relationships that are often affected by long-standing structural factors. Long-term country-specific time series data (as well as continued improvements in the core data) would improve analytical tools like the SSGD. Likewise, additional causal analyses – leveraging impact evaluations as well as experimental and quasi-experimental analyses – would help confirm the correlations presented here.

Beyond data considerations, weak correlations may also underscore that there are multiple ways to make progress on such high-level development goals, some of which are more 38
the country’s population. However, this principle does not always hold in practice and consequently the lower houses in many countries are malapportioned.

The paper first provides a political economy rationale for the emergence and persistence of legislative malapportionment. We base this rationale on the argument that, at the time of transition to democracy, groups that held political power during the preceding dictatorship<sup>2</sup> may have strong incentives to manipulate the newly established political institutions in order to protect their political and economic interests.<sup>3</sup> We claim that legislative malapportionment provides these groups with a way of enhancing their _de jure_ power in democracies by overrepresenting certain geographic areas and by favoring certain political parties versus others. This skewed political representation survives in equilibrium as long as it makes democratic consolidation more likely. At the same time, it is associated with lower political competition and distorts public policies, which also helps to preserve the power of the pre-democratic elite.

We then test this theoretical argument using data from Latin America<sup>4</sup> . In contrast to other features of political institutions, such as patronage, corruption or lobbying, malapportionment is clearly defined and measurable, allowing us to test the predictions of our argument empirically. We first rely on within country data to examine the political tendencies of electoral districts that are overrepresented in the sense that they have a higher share of representatives in the lower house than their population share. Consistent with our theoretical argument, we show that in the first election after transition to democracy, overrepresented districts are more likely to vote for parties that are close to pre-democracy ruling groups. As an additional check, we also provide evidence showing that overrepresented districts were more likely to support dictatorships in elections held in pre-democratic times.

We then use panel data for eleven Latin American countries, covering the late XIX century to the present, to show that higher legislative malapportionment makes democratic

> 2 In this paper we use the term dictatorship to refer to any non-democratic regime
.2 million people in poverty. Most of the rural poor live in more dispersed rural areas, as 2.8 million were poor in semi-urban areas and 10.4 million poor in dispersed rural areas (information on population in rural areas in Appendix A).

Geographic factors are important when analyzing poverty in Mexico. Living in a poor area can make a profound difference to well-being and life prospects. There are large differences in income poverty between different regions, with a generalized gradient from North to South (Figure 3.2 and Table 3.1).<sup>5</sup> In 2002, the headcount poverty rate in rural areas in the North region with less than 15,000 inhabitants reached 14 percent, a third of that in the South region where 48 percent were poor.

> 5 ENIGH is not designed to be fully representative at regional level, but differences between regions are statistically significant (also Word Bank 2004).

9
worker employed by each of the establishments in the census to repeat the estimation, controlling for establishment by time fixed effects. Hence, we are effectively comparing workers employed in the same firm and year to identify the effect of covariates on the incidence of each type of rigidity. This should take care of the possibility that some of our results may be driven by worker selection into different types of firms, depending on the degree of wage rigidity operating. The results, reported in table 8, are qualitatively similar to those previously discussed, which suggests that the differences across workers highlighted here are not driven by worker sorting and firm heterogeneity.

# 6 Conclusions

Emerging countries have moved from high inflation regimes in the 1980s to relatively low and stable inflation rates since the second half of the 1990s. This paper assesses how this disinflation process has shaped wage setting in two of these emerging economies: Brazil and Uruguay. This investigation is important from a policy perspective. The natural response of wage setters to high inflation regimes is wage indexation. This form of wage rigidity is likely to translate into inefficient allocations, as relative wages are not allowed to adjust to firms’ productivity developments. These efficiency losses are, in turn, likely to result in lower levels of welfare and higher unemployment. Hence, from both a macro and labor economics perspective, it is important to know how downward real wage rigidities have evolved as inflation has fallen.

Measuring downward wage rigidities at the individual level imposes serious data requirements. In this paper, we have measured the incidence and nature of wage rigidities in Brazil and Uruguay using high quality administrative data, but it is still possible that measurement error might result in an underestimation of downward wage rigidities. Our model helps to deal with this possible bias by jointly estimating the parameters governing measurement error and the different types of rigidities we are considering. The model contrasts the individual wage changes observed in the data with a notional wage change, which is the wage change that would have prevailed in the absence of wage rigidities.
research is needed to use disability focused datasets, such as the Model Disability Survey developed by the World Bank and the World Health Organization. This work is needed notably to highlight the structural factors (e.g. social norms, attitudes, physical environment) that persons with disabilities may face in the workplace or in school settings for instance. In addition, information is lacking considerably, and more data are needed on health conditions that may lead to functional difficulties and/or socioeconomic deprivations. Data collection efforts that collect information on health conditions such as the Study of global AGEing and adult health (SAGE) are steps in this direction.

Despite the limitations of the data sets under use, this study has several implications for further research and data collection and monitoring. A measure of functional difficulties such as the WGSS should be included as a standard correlate in studies of inequalities. As it would be inconceivable _not_ to include age or gender as correlates, applied researchers should at least include a measure of disability based on the WGSS or similar questions as a potential correlate of socioeconomic outcomes.

Social protection programs were found to disproportionately reach persons with functional difficulties in some countries and yet they do not do away with inequalities. Policies and programs that some LMICs have adopted after ratifying the CRPD need to be assessed with 37
classification models for predicting whether a location is a landslide or a non-landslide location. To this end, we used the data sampled in the fourth step to train a Random Forest Classification model in each iteration. The model target (i.e., dependent variable) is to predict a binary value (zero or one) representing whether a location is a landslide or a non-landslide location. The model features (i.e., independent variables) are the score values of the factors identified in the first step. A random forest model is an ensemble of decision trees; each tree is created based on a random selection from the training data and the available features (Svetnik et al., 2003). During model training, each tree in the forest is designed by selecting leaf nodes and splits to maximize prediction quality. The prediction of a random forest model is made by aggregating the predictions of individual trees in the forest based on the majority vote (i.e., the mean) (Breiman, 2001). In this study, we used the Gini criterion to measure the 15