rafmacalaba/datause-encoder-data huggingface dataset:
longitudinal data from Bolivia show that in addition to the effect stemming from better socioeconomic status, mothers with higher educational attainment are more willing to accept modern health care and have more health knowledge to improve the nutritional status of a child. The effect of additional education is strongest at lower levels of educational attainment (Soares 2007). A study on mothers’ literacy skills in Venezuela also finds that literate mothers can comprehend the public messages on health and can communicate more effectively to healthcare workers about their child’s health conditions compared to illiterate mothers (Schnell-Anzola, Rowe, and LeVine 2005). Similarly, Hatt and Waters (2006) note that in Latin America, income levels plus the educational attainment of mothers together contribute significantly to the well-being of their child. The evidence of positive effect stemming from maternal education is fairly universal. Basu and Stephenson (2005) find that even few years of schooling can prepare would-be mothers in India to seek medical assistance and corrective measures when a child becomes ill. More educated mothers are better able to use ORT and more easily persuaded of the advantages of breastfeeding (Medlin and others 2006).<sup>61</sup> Studies on immunization rates point to the large impact stemming from the mother’s education level (Parashar 2005; Xie and Dow 2005). Children with better educated mothers in Malawi suffer less from fever and diarrhea (Kandala, Magadi, and Madise 2006). A study based on the data from 42 Demographic and Health Surveys points to strong linkages between maternal education and children’s health, in addition to the importance of the level of income (Boyle and others 2006). In other words, the effects of better water and sanitation, especially on the health of children can, be most effectively reinforced by education programs which ensure gender balance.

# **A Health Safety Net**

Reducing health inequity and providing the essential minimum amount of primary and curative care to the urban population requires a public safety net. Many countries make do with a mix of public and private provision of care but this tends to leave large numbers of the urban poor to fend for themselves. In low income countries, out of pocket

> 61 This needs to be qualified because breastfeeding is to be avoided if the mother is HIV positive or has been exposed to chemicals/heavy metals.

32
EU countries. The survey collects detailed information on the labor market outcomes of interviewed individuals, and asks about the region of birth and duration of stay in the current country, which allows to identify migrants. Following a similar approach as for the US, we report the number of migrants who moved to EU countries between 2000 and 2004 and still live there in 2008, 2013 and 2018. We further disaggregate the migrant cohort by age, gender, education and region of origin.

The results of this descriptive examination are reported in Figure 2. The yellow, green and blue bars represent the number of migrants from a given group who migrated between the years of 2000 to 2004 and remain in the country after 5-9 years (in 2008), 10-14 years (in 2013) and 15-19 years (in 2018), respectively.<sup>4</sup> Migrants to the EU disproportionately move at a young age and the number of female migrants to the region is slightly larger than males (panel a). The number of immigrants from a given cohort decreases noticeably over time and to a greater extent than in the US. After 15-19 years of stay, the number of immigrants who moved to the EU in 2000-2004 has reduced by 30 percent compared to 10 years prior. This drop is quite large in relative terms for migrants who moved when they were 45 or older (panel a). This is likely to be driven by preferences for retirement in the origin country, as individuals who were 45-54 year old when they migrated in 2000-2004 are close or past retirement age by 2018. Return patterns are fairly similar between males and females as well as between low-skilled and high-skilled migrants (Panel b). When disaggregated by region of origin (panel c), immigrants from Latin America and other destinations - which mostly consist of other Western European countries and high-income OECD countries - return at a much higher rate than migrants from other regions. Returns to Eastern Europe and Africa are fairly rare, even 15-19 years after migration.

> 4In contrast with the ACS data for the United States, the exact duration of stay of foreign-born individuals is not reported in the EU LFS. Instead, the survey reports brackets of 5 years instead of a more precise duration of stay.

7
**_Energy demand models for policy_** **_<u>formulation</u>_**

Fig. 7: MAED Framework of analysis <!-- Start of picture text --> Breakdown of the economy by sector: transport, industry, households and service<br>Scenario assumptions<br>Socio-economic scenarios Technological evolution<br>Social needs Level of economic Technological<br>activity determinants<br>Non-substitutable Substitutable demand<br>demand<br>Useful energy demand<br>Fuel penetration level<br>Efficiency of appliances and processes<br>Final energy demand<br>Electricity demand Non-electricity demand<br><!-- End of picture text --> Source: IAEA (2006) The demand is first determined at the disaggregated level and then added up using a consistent accounting framework to arrive at the overall final demand. The model focuses only on the final demand and does not cover the energy used in the energy conversion sector. The general framework of analysis of the MAED model is presented in Fig. 7. The detailed list of principal equations used in the model is provided in IAEA (2006).

84
Policy Research Working Paper 6290

# **Abstract**

Financial inclusion—defined here as the use of formal accounts—can bring many welfare benefits to individuals. Yet the authors know very little about the factors underpinning financial inclusion across individuals and countries. Using data for 123 countries and over 124,000 individuals, this paper tries to understand the individual and country characteristics associated with the use of formal accounts and what policies are effective among those most likely to be excluded: the poor and rural residents. The authors find that greater ownership and use of accounts is associated with a better enabling environment for accessing financial services, such as lower account costs and greater proximity to financial intermediaries. Policies targeted to promote inclusion— such as requiring banks to offer basic or low-fee accounts, exempting some depositors from onerous documentation requirements, allowing correspondent banking, and using bank accounts to make government payments— may be especially effective among those most likely to be excluded. Finally, the study the factors associated with perceived barriers to account ownership among those who are financially excluded and find that these individuals report lower barriers in countries with lower costs of accounts and greater penetration of financial service providers. Overall, the results suggest that policies to reduce barriers to financial inclusion may expand the pool of eligible account users and encourage existing account holders to use their accounts with greater frequency and for the purpose of saving.

This paper is a product of the Finance and Private Sector Development Team, Development Research Group. 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 Ademirguckunt@worldbank.org, lklapper@worldbank.org, and Mmartinezperia@ 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
_Figure 5: Interest rate sensitivity of liabilities, 2002 to mid 2006_ <!-- Start of picture text --> DKK bn<br>140<br>120<br>2005<br>100<br>2004<br>80<br>2002<br>2006 (1st half)<br>60<br>2003<br>40<br>20<br>0<br>-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5<br>-20 2003<br>2006 (1st half)<br>-40<br>2004<br>2002<br>-60<br>2005<br>-80<br><!-- End of picture text --> _Table 10: Interest Rate Sensitivity of Liabilities_

|||InterestRa<br>|te Change<br>||10 Year government bond<br>|
|---|---|---|---|---|---|
||- 1%|-0.7%|+0.7%|+ 1%|yield(end ofperiod)|
|||_DK_|_Kbn_||Percent|
|2002|66.0|42.2|-22.3|-48.0|4.46|
|2003|52.0|31.9|-16.6|-20.5|4.47|
|2004|76.1|49.0|-32.2|-42.3|3.85|
|2005<br>|112.4|72.7|-50.5|-67.1|3.28|
|2006(1<sup>st</sup>half)|63.7|40.8|-24.9|-32.1|4.12|

Source: Danish FSA. Bloomberg (yields) Figure 5 and Table 10 above shows the interest rate sensitivity of aggregate liabilities and, for reference, the 10 Year government bond yield. Liabilities increase when interest rates go down (the net present value of future payments goes up) and fall when interest rates rise. The effect is not symmetric, however. When rates fall by 1 percentage point, liabilities increase more than they fall when rates rise by 1 percentage point. This asymmetric effect can be attributed to the issued interest rate guarantees that gain in value rapidly when rates fall, while they have no value when rates are increasing from levels well above the guaranteed levels. This effect is visible in all the years illustrated above (2002 to 2006), but it is, as expected, more pronounced the lower the level of market interest rates. In 2005 when rates were at their lowest (see figure 3) the negative impact of a further fall in interest rates was the highest, as many of the issued interest rate guarantees were close to or already in the money. In that year a percentage point drop in interest rates would result in an increase in liabilities of DKK 110 bn.

17
mainstream consumption survey data—over time (Deaton and Kozel 2005). Similar concerns, albeit to a lesser extent, were raised about the dramatic poverty reduction between 2004 and 2012 as well. One main reason is that the questionnaire design of the consumption module in the 2011/12 (68th) round of the NSS is not comparable to that in the 2009/10 (66th) round (and 2004/05 or 61st round), which may result in inconsistently constructed and incomparable consumption data. Dang and Lanjouw (in press) apply imputation methods to provide checks on the poverty trend. They first build an imputation model using the 2004/05 round as the base survey to obtain poverty estimates for 2009/10, which are satisfactorily not different from the actual poverty rates. They subsequently employ the same model using the 2009/10 as the base survey to obtain poverty estimates for 2011/12. These estimates are close to the actual rates in this year, thus providing supportive evidence for the swift fall in poverty observed in the data.

A key assumption for survey-to-survey imputation is that the coefficients β estimated from the previous consumption survey can be combined with the variables in the more recent survey to obtain poverty estimates.<sup>15</sup> While concerns exist that this assumption is likely to be valid only under normal circumstances, rather than during periods of fast (economic growth and) poverty reduction, it has been shown to hold during a period of dramatic economic growth in China and Vietnam where poverty incidence was cut by around half (Christiaensen _et al._ , 2012). Furthermore, a weaker version of this assumption has been proposed and validated for data from various countries such as India, Jordan, and Vietnam (Dang _et al._ , 2017a; Dang _et al_ ., 2017b; Dang and Lanjouw, in press). Yet, we would like to note that the validity of this assumption can be contextspecific, and it can be useful to check it using at least two previous rounds of household consumption surveys wherever such data are available. Common sense also suggests that the

> 15 This is also commonly known as the constant parameter assumption.

16
Control Affects Labor Supply and Gender Norms,” NBER Working Papers 26294, National Bureau of Economic Research 2019.

- **Folke, Olle and Johanna Rickne** , “Sexual harassment and gender inequality in the labor market,” _Quarterly Journal of Economics_ , 2022, pp. 1–50.

- **Gibbons, Steve** , “The Costs of Urban Property Crime,” _The Economic Journal_ , 10 2004, _114_ (499), F441–F463.

- **Greenwald, Anthony G., Brian A. Nosek, and Mahzarin R. Banaji** , “Understanding and Using the Implicit Association Test: I. An Improved Scoring Algorithm,” _Journal of Personality and Social Psychology_ , 2003, _85_ (2), 197–216.

- **Guardian** , “Jeremy Corbyn faces backlash over women-only train carriages idea,” 2015.

- **Iyer, Lakshmi, Anandi Mani, Prachi Mishra, and Petia Topalova** , “The Power of Political Voice: Women’s Political Representation and Crime in India,” _American Economic Journal: Applied Economics_ , July 2012, _4_ (4), 165–93.

- **Jayachandran, Seema** , “The Roots of Gender Inequality in Developing Countries,” _Annual Review of Economics_ , 2015, (7), 63–88.

- , “Social Norms as a Barrier to Women’s Employment in Developing Countries,” Working Paper 27449, National Bureau of Economic Research June 2020.

- **Kondylis, Florence, Arianna Legovini, Kate Vyborny, Astrid Zwager, and Luiza Andrade** , “Survey Data for WP9269: Demand for “Safe Spaces”: Avoiding Harassment and Stigma 2015-2016,” https://microdatalib.worldbank.org/index.php/catalog/11600 2020.

- **Lee, Kenneth, Edward Miguel, and Catherine Wolfram** , “Experimental Evidence on the Demand for and Costs of Rural Electrification,” Working Paper 22292, National Bureau of Economic Research May 2016.
using the Probit host country fixed effects. In the first column, we only include a dummy indicating the presence of a restriction in setting up a branch and the maximum amount of capital that a foreign investor can hold when acquiring a domestic company. The positive and significant coefficient on the restriction to open a branch is likely to reflect some substitution among different forms of entry: firms engage more in M&A when they cannot enter a foreign market simply by setting up a branch.<sup>33</sup> Equity restrictions do not seem to be significantly correlated with the probability of a particular country receiving any cross-border M&A inflow in services.

In the second column, we include several restrictions concerning licensing: a difference in criteria for domestic versus international firms in applying for a license, transparency of criteria to obtain a license, the automatic nature of the license renewal, and transparency in obtaining reasons why a license is denied. We find a negative and statistically significant coefficient on the transparency about the reason for a license denial. Surprisingly, we find a positive and significant coefficient on the dummy for differential criteria for licensing for domestic and foreign firms. A way to interpret this result is that in the presence of discriminatory licensing, firms might prefer to acquire a local firm (rather than to establish a branch or a subsidiary), and thus be able to apply for licences as a “domestic” firm.

Among the restrictions affecting operations, we explore the role of nationality limits on employees and on the board of directors. We find a negative and significant coefficient on the nationality restrictions for the general employees, but not on the restrictions specific to the board of directors which, in practice, often does not add any new information that would not already be embodied in the variable capturing foreign equity participation limits.

Column (4) proposes a model where we include the key restrictions from each of the different types of measures, retaining only those measures that exhibit significant coefficients in the previous specifications. In this joint specification the restriction on setting up a branch, the lack of transparency on the reason for a license denial, and limits to the nationality of are limited by the fact that not all our individual policy variables are available for all the countries in our sample. This is the reason why estimations in Table 10 have fewer observations than in Tables 8 and 9. 33The difference between a branch and a subsidiary is that the former is legally still part of the parent firm, while the second is a separate legal entity.

25
# 4. Estimating a vulnerability map of Senegal

A vulnerability map is estimated at the commune level. To achieve this, the steps outlined in section 3 were followed, and an individual model was developed to predict household expenditures in each of the country's 14 regions. Appendix A, table A.1 compares the variables available in the census and the household survey, while regressions for each region are illustrated in appendix B, table B.1. The variables used for each of the regions vary, but present consistent coefficients, such as a negative relationship with household expenditure in the case of household size, the dependency ratio, and rural location, a positive correlation with higher educational attainment and asset ownership, and a positive relationship with dwelling conditions and better access to public services, such as piped water. Another measure of the model's performance is how closely poverty estimates in the census data match the poverty rates observed in the household survey. The difference between the observed and predicted poverty rates is less than 1 percent at the national level while in 10 of the 14 regions it is below 5 percent. Yet, all estimates fall within the survey’s poverty estimate 95 percent confidence interval (table 1).

**Table 1. The observed poverty rate and small area estimation predictions, by region**

|_Region_<br>|_Su_<br>|_rvey_<br>|_Cen_<br>|_sus_<br>|
|---|---|---|---|---|
|<br>_Pov_|_erty rate(observed)_|_Vulnerability (predicted)_|_Poverty rate(predicted)_|_Vulnerability (predicted)_|
|Dakar|9.0|11.0|9.4|16.0|
|Diourbel|43.9|60.6|44.7|61.4|
|Fatick|49.2|74.7|52.6|77.3|
|Kaffrine|53.0|78.0|54.5|74.0|
|Kedougou|61.9|82.5|69.0|82.0|
|Koalack|41.5|58.9|40.6|60.4|
|Kolda|56.6|83.3|57.2|82.0|
|Louga|43.4|66.1|45.0|67.0|
|Matam|47.7|88.1|44.6|89.0|
|Saint-Louis|40.1|56.0|41.5|55.3|
|Sedhiou|65.6|89.5|73.0|90.1|
|Tambacounda|61.9|84.0|60.6|79.4|
|Thies|34.1|45.7|33.2|51.0|
|Ziguinchor|51.1|83.0|55.0|72.0|
|National|37.8|55.9|38.2|55.7|

_Sources:_ Calculations using EHCVM (Enquête Harmonisée sur le Conditions de Vie des Ménages 2018–2019; Harmonized Survey on Household Living Standards 2018–2019), Living Standards Measurement Study, World Bank, Washington, DC, https://microdata.worldbank.org/index.php/catalog/4292; RGPHAE 2013 (2013 Recensement Général de la Population et de l'Habitat, de l'Agriculture et de l'Elevage; Population and Housing Census, 2013) (dashboard), National Agency of Statistics and Demography, Dakar, Senegal, https://www.ansd.sn/enquete-et-etude/recensement-general-de-la-population-et-de-lhabitat-delagriculture-et-de-lelevage.

Based on the imputed model in the census, the national vulnerability rate is 55.7 percent. This includes 38.2 percent of individuals who are vulnerable because of poverty (poverty-induced vulnerability) and 17.5 percent who are nonpoor but exhibit a high probability of falling into poverty (risk-induced vulnerability). Survey estimates of vulnerability are consistent with the small area estimates, with a 11
research with entrepreneurs. The best examples are the technology transfer models of Massachusetts Institute of Technology (MIT) in fostering Boston’s creative community and Stanford University in creating the Silicon Valley (Porter and Monitor Group 2001, Saxenian 1994, Walcott 2002). In addition, industrial associations can function as political lobby groups to advance collective interests. For instance, the ambitious Bay Area Multimedia Partnership is aggressively seeking to implement a regional development agenda for the multimedia industry in the Bay Area (Scott 2000).

Vital to the fashion cluster are the cultural intermediaries and their role in facilitating the image-building process. These intermediaries include runway shows, fashion magazines, and media fashion segments. Their target is primarily the consumer, even in the case of runway shows, as most high-end designers have already placed their orders with buyers by the time of their shows (Rantisi 2002). Cities like New York have a distinct advantage over other centers of fashion design because of the presence of such intermediaries. The Council of Fashion Designers has coordinated the designers’ shows in New York and the top ten fashion magazines are all based there.

# **Appropriate base of knowledge and skill**

Almost all creative centers are places with a high concentration of educated people and the ability to retain skills.<sup>17</sup> The best example is probably Washington DC, where 42 percent of the adult population has at least a bachelor’s degree and 19 percent has a graduate degree (McNally 2003). In the software industry, firms have essentially one tangible asset – the talented software developers and entrepreneurial thinkers (Sommers and Calson 2000). These key employees know that other firms are eager to hire them if compensation and local living conditions are not ideal. Attracting and retaining them are one of the highest priorities for software firms. Much the same is true for the publishing industry. A publishing firm has few assets other than its key personnel, which is highly mobile (Caves 2000). But the dependence of writers on a dense creative milieu and a large number of gatekeepers appear to tie the publishing industry more firmly to places than the software cluster. Similarly, the multimedia sector appears to flourish most likely in places where an existing and well-developed skill base of

> 17 Research has shown that increasing the average level of education in a metropolitan area by one grade increase total factor productivity by 2.8 percent (cited in Appleseed Inc 2003).

12
# **Figure 2.14: Despite structural transformation women’s employment remains concentrated while men diversify** Share in selected industries %, 2009-2019

# **a) All workers**

<!-- Start of picture text --> 100%<br>11.2 13.6<br>18.2<br>3.4<br>4.2 80%<br>11.2 4.6<br>11.3<br>3.5<br>5.8 6.7 14.5<br>60%<br>11.1 8.7<br>10.8<br>40%<br>58.1<br>46.6<br>37.2 20%<br>0%<br>2009 2014 2019<br>Agriculture and forestry Mining Food, beverage and tobacco<br>Textile and apparel Wood Construction<br>Sales Transport Public administration<br>Others<br><!-- End of picture text -->

# **b) Men**

<!-- Start of picture text --> 100%<br>11.4 14.2<br>18.8<br>4.5<br>5.0<br>6.3 7.8 5.2 80%<br>7.4<br>8.5<br>6.1 7.7<br>11.2 10.7 60%<br>14.8<br>40%<br>58.0<br>44.8 20%<br>34.6<br>0%<br>2009 2014 2019<br>Agriculture and forestry Mining Food, beverage and tobacco<br>Textile and apparel Wood Construction<br>Sales Transport Public administration<br>Others<br><!-- End of picture text --> 10 | P a g e