rafmacalaba/data-use-mentions-extended huggingface dataset:
, while others are affected by multiple issues equally. In Sub-Saharan Africa, our results suggest that the absolute priority should be food security, and to a lesser extent health. In South Asia, on the other hand, the impact of food prices, disasters, and health shocks are almost equal, suggesting the need for a multi-prong approach.

# **3.4 Socioeconomic development and climate vulnerability**

We now look at how different assumptions regarding socioeconomic development (i.e., the baselines) affect climate change vulnerability in terms of people pushed into extreme poverty.

To do so, we select — in each country — two sets of scenarios from the 1000 baseline scenarios (i.e., scenarios of socioeconomic and demographic changes, but without climate change). The first set of scenarios is termed the _pessimistic_ baselines. Here, we select the 100 baseline scenarios with the highest poverty rates. These baseline scenarios have global poverty rates between 14% and 15.5%. The second set of scenarios, the _optimistic_ baselines, consists of the 100 scenarios with the lowest poverty rates. The _optimistic_ baseline has global poverty rates in the 2.8% and 3.8% range. The _optimistic_ baseline can be seen as a future with rapid and inclusive socioeconomic development, which can be achieved among others through pro-poor policies (they are aligned with the World Bank objective of reducing extreme poverty below 3% of the global population by 2030).

Climate change vulnerability in terms of people falling into extreme poverty is recalculated for the two sets of baselines (see Figure 5). In the worst-case combination — with pessimistic baselines and high climate change impacts — climate change impacts make more than 130 million people fall in poverty by 2030.

Within the high climate change impact scenarios, rapid and inclusive development (i.e., the optimistic baseline) can reduce climate change vulnerability by almost 50% (from 131.5 million people on average to 67.7 million people on average).
rarer, apart from a few exceptions such as China’s hukou household registration system, in fact many governments do try to discourage rural to urban migration. Bundervoet (2018) reports on a 2013 United Nations survey, in which 148 out of 185 countries had government policies aimed at reducing migration from rural to urban areas, and only five had policies designed to speed up this form of internal migration. These policies tend not to be legal restrictions against internal migration, but rather policies that make it more costly or difficult for migrants to access various public services when they arrive. Bundervoet gives the example of Ethiopia, where internal migrants can struggle to access urban ID cards, access housing, or access subsidized food.

_The costs of moving are so large that they exceed the benefits._ Apart from explicit policy barriers, another potential reason for not migrating is that the other components of _C_ are large, so that even 12
Policy Research Working Paper 10651

# **Abstract**

Does it matter whether poverty reduction programs target the female or male spouse? A randomized controllled trial in Ethiopia is used to study the differential impacts of easing information and financial constraints on agricultural productivity and household welfare, using data from 1,214 households in two regions of Ethiopia. The program targeted the husband, the wife, or both in a married household. The results indicate that the targeted spouse determines the type and channel of impacts. Targeting both spouses increased agricultural productivity in the short run and the monetary value of small ruminants and poultry in the long run, with a marginal positive impact on nonfood expenditure. Targeting only the female spouse resulted in increased business income from businesses with female involvement. This consequently increased household use of formal savings devices. This is in line with female preferences outside agriculture and for off-farm activities, and it results in little impact on agricultural productivity, despite an increase in women’s access to extension services. Targeting only the male spouse has no impact on household savings or expenditure even though it increases men’s wage income. The results suggest that the sharing of knowledge about the intervention changed household decisions. This would explain the different outcomes when both spouses were targeted, rather than only one.

This paper is a product of the Gender Innovation Lab, Africa Region. 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 tketema@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.
6 Research indicates that young women in partnerships have generally less autonomy and are at greater risk for both physical and sexual violence than older women. In Nicaragua, for example, not only did women between 15-19 report more physical and sexual violence within the last 12 months than older women, but they also experienced more severe acts of violence (Rosales, et al., 1999).

International research within the last decade has revealed that sexual abuse of women and girls by non-partners is also much more common than previously thought. Between 8 and 26% of women and girls reported having been sexually abused, either as children or adults (World Health Organization 2002). These figures are likely to be under-estimates of the true prevalence of abuse, as many women are reluctant to disclose violence due to shame and fear of reprisals (Koss 1993).

One of the main challenges for addressing GBV stems from the lack of evidence on the magnitude and characteristics of violence in different settings. There are many inconsistencies in the methods used by different researchers that make comparisons difficult across countries or even among studies within a given country. These include the reference period used (lifetime prevalence, 12 month prevalence or ongoing violence), the number and wording of questions asked, the age cut-off for abuse (before and after 12 years, before and after 15).

During the last decade, however, there have been several efforts to improve the measurement of GBV. The World Health Organization has conducted a multi-country study on domestic violence and women’s health in 15 sites and 10 countries. This study has produced comprehensive set of research tools, including instruments, field manuals and data entry programs (Garcia Moreno, Watts et al. 2003). The United Nations Interregional Crime and Justice Research Institute (UNICRI) has also initiated surveys in several countries on violence against women. Both the Demographic and Health Surveys conducted by Macro International and the Centers for Disease Control’s Reproductive Health Surveys have begun to incorporate questions on violence in their surveys (
across various sectors of the economy. For instance, in the case of part-time employees, who more frequently earn the minimum wage exclusively, the proportion of women slightly surpasses that of men, with figures of 20.4% for women and 18.4% for men.

**Minimum wage earners are overrepresented in the construction sector.** Individuals who are taxpayers within the construction sector earn a higher minimum wage (3,000 RON). Consequently, the proportion of individuals earning the minimum wage within the construction sector exceeds that in other sectors of the economy by more than two-fold. Specifically, a substantial 54.6% of employees eligible for fiscal benefits within the construction industry fall into the category of minimum wage earners. In contrast, among employees not employed in the construction sector, the percentage of minimum wage earners stands at 25.1%. The generous tax incentives granted to the construction sector starting in 2019 could have contributed to reducing the informal economy. Still, ex-post analyses are needed to confirm this hypothesis, given the sector's high volatility and the growth recorded from 2019, which follows three years of decline.

> 22 This is based on total earnings from labor before tax deductions (gross labor income), based on individual tax records.

28
emotional regulation and self-control is wider at higher education levels. In general, these results are suggestive rather than definitive, as two important considerations arise in the measurement of each skill. First, self-reported measures may reflect gender-specific biases in assessments of skills. In complementary work, we are developing observation-based measures of skills, that will help address this issue. Second, this study is based on available data, and measures were not validated for this division of skills. In addition, larger efforts were spent on measuring intrapersonal skills (75% of socioemotional skills items) than interpersonal skills across studies. Thus, measures of interpersonal skills suffer 28
Both empirical research and the experience of WBG SIRM pilots depicted in Box 2 highlight the relevance of addressing questions of FDI retention and expansion within any broader discussion of investment facilitation. Doing so would require no changes to existing host country legislation on investment protection. On the contrary, this approach would entail only pragmatic solutions to ensure the effective implementation of norms and disciplines already in force and agreed to by governments applicable in their respective jurisdictions.

# **4.2.4 Regulatory heterogeneity**

Cross-country differences in how countries regulate the provision of the same service create additional costs for suppliers that need to adapt to new sets of rules in a multiplicity of markets. Addressing trade costs stemming from regulatory heterogeneity through strengthened international cooperation has taken center stage in the latest generation of preferential trade and investment agreements (Polanco-Lazo and Sauvé, 2017). This is so even as evidence of regulatory convergence, proxied as it can be by the conclusion of mutual recognition agreements, remains generally scant.

Regulatory cooperation makes doing business easier for exporters, and available research shows that it has a relatively large impact on trade conducted through a commercial presence. Based on an OECD data set of services trade policy heterogeneity, Nordås and Kox (2009) estimate that if all countries harmonized or recognized each other’s regulations to the extent that the heterogeneity index took its lowest bilateral value for all country pairs, total services trade through commercial presence could increase by between 13 and 30 percent depending on the country. Likewise, if the business environment became more similar among the countries in the sample, total services trade through commercial presence could increase by between 2 and 60 percent, with the largest gains in India, the Republic of Korea, Poland and China (WTO, 2019).

The OECD estimates that trade costs imposed by cross-country differences in regulation range from 20% to 80%. It further recalls that lifting existing discriminatory restrictions where they are still high should be a policy priority, as the gains from regulatory harmonization, convergence or approximation are far
Closing the gender labor force participation rate would increase GDP by 2.3 percent. Generally, women of working age (20-65) have high activity rates, with an average labor force participation rate of 77.8 percent, as compared to 88.6 percent for men.<sup>21</sup> Yet if we close the 10.7 percentage point difference, the workforce would grow from 1.90 million to 2.04 million (Figure 2). Ultimately, GDP would reach USD 4.14 billion and the contribution of women would rise to USD 1.13 billion from USD 1.08 billion. The influx of workers into the labor-market would not be equally absorbed, instead displacing female and male workers between sectors to differing degrees. The share of workers in the traditional sector would increase from 70.5 percent to 73.9 percent and the share of workers in the modern sector would decrease from 29.5 percent to 26 percent. Notably, the share of female in the modern sector would increase from 32.7 to 40 percent while its male share would decrease from 67.3 to 60 percent. Since the gender gap in labor force participation is similar in Liberia to those in Sub-Saharan Africa and the OECD, we do not present the results here.<sup>22</sup>

**Figure 2. Selected macro-economic changes due to complete convergence in the LFPR gender gap (in USD, growth in %)**

<!-- Start of picture text --> $4,500 20%<br>4,142<br> $4,000 15%<br>15.2% 15.9%<br> $3,500<br>10%<br>10.0%<br> $3,000<br>5%<br> $2,500<br>3.5%<br>2.3% 0%<br>
The preferred destinations for those who migrate to work are Lower Egypt (56.6 percent), followed by Cairo (22.8 percent). Those who left Cairo for work reasons went largely to Lower Egypt (70.8 percent) or Upper Egypt (19.4 percent). Lower Egypt was also the prime destination for migrants from Upper Egypt (41.4 percent), followed by Cairo (30.5 percent).

Table 9- Direction of Migration (for work only) – Regions (classified according to origin)

||Current Region|||||
|---|---|---|---|---|---|
|Previous location|Cairo|Lower Egypt|Upper Egypt|Frontier|Total|
|Cairo|2.9|70.9|19.4|6.8|100|
|Lower Egypt|20.5|69.3|5.6|4.6|100|
|Upper Egypt|30.6|41.5|21.2|6.8|100|
|Frontier|14.8|14.8|11.1|59.3|100|
|Total|22.9|56.6|13.5|7.1|100|

Source: Authors’ calculations using Labor Force Survey The majority of those migrating to Cairo for work came from Upper Egypt (55.3 percent) and Lower Egypt (41.9 percent). Migrants from Lower and Upper Egypt tend to change localities within their home region.

Table 10- Direction of Migration (for work only) – Regions (classified according to destination)

||Current Region|||||
|---|---|---|---|---|---|
|Previous location|Cairo|Lower Egypt|Upper Egypt|Frontier|Total|
third establishment receives “0003”, and so on. Some of the companies are composed by a single establishment, which receives the 4-digit code “0001”.<sup>3</sup> The last two digits of the CNPJ correspond to the establishment economic sector, and they work more as a confirmation code. Therefore, we use the first 12 digits of the CNPJ to extract the establishment composition of each company.

To summarize, there are three reasons why the RAIS data set is particularly useful for the analysis. These are:

- (i) It identifies entry behavior each year, allowing us to build a panel of entry data that we use to control for spatial fixed effects.

- (ii) It provides spatial detail on entry decisions (necessary for discussion of policies to promote entry into lagging regions).

- (iii) It describes firm family structure (i.e., identifies parent or headquarters, which we find to be a particularly important determinant of entry).

To model spatial entry decisions, we had to select an appropriate geographic unit.

Using municipalities creates several problems: (i) there are a large number of municipalities (5,506 in the year 2000), which would significantly increase the computational burden in estimating the location decision model; (ii) many municipalities are very small (i.e., with fewer than 5,000 inhabitants) and/or in rural areas with very few establishments in the formal sector; (iii) because of the continuous creation of new municipalities in Brazil, it is necessary to coordinate different municipality maps across the

> 2  Refer to Table 5 for a list of the industries included in the analysis.

> 3 The establishment with digits “0001” in positions 9 to 12 is the initial headquarters of the company. However, should the headquarters be transferred to another municipality and the previous establishment be maintained, the new headquarters may receive a four-digit sequence different from “0001” while the previous establishment retains the “
which focused on rapid global growth in biofuel production under conventional conversion technologies, the price increase for major crops ranges between 30% and 76% by 2020. There is significant increase in malnutrition in many developing country regions with Sub-Saharan Africa being the hardest hit. Using the AGLINK and COSIMO models, the OECD predicts the impact of achieving the stated policy targets (as of 2006) for biofuels in several countries [42]. It finds that compared to a situation with unchanged biofuel quantities at their 2004 levels, crop prices could increase by between 2% in the case of oilseeds and almost 60% in the case of sugar by the year 2014.

Partial models have several limitations, such as lack of acknowledgement of the finiteness of resources such as land, labor, and capital; no explicit budget constraint on households; and no check on conceptual and computation consistency of the model [30]. These limitations can be overcome by using a general equilibrium approach. Computable general equilibrium (CGE) modeling is a numerical technique that combines the theoretical framework of Walrasian general equilibrium formalized by Arrow and Debreu [6] with real world economic data to determine the levels of supply, demand, and price that support equilibrium across a specified set of markets [69]. These models, which were initially developed to analyze the impact of changes in trade policies and public finance, have subsequently found wide application in the analysis of relationship between energy and the macro economy, the impact of greenhouse gas policies, and most recently in the context of biofuel policies [10, 13, 31]. GTAP, LINKAGE, and USAGE are some prominent general equilibrium models that were used to analyze biofuels.<sup>4</sup> Dixon, Osborne, and Rimmer [18] use a dynamic CGE model called USAGE to quantify the economy wide effects of partial replacement of crude petroleum with biofuels in the United States. They forecast the impact of the current biofuel policies on the U.S. economy in 2020 [18]
24 J.C. Duque, N. Lozano-Gracia, J.E. Patino, P. Restrepo / LCR Flagship Report on Cities and Productivity use the digital elevation model from the NASA Shuttle Radar Topographic Mission (SRTM) version 4, with a resolution of 90 meters (Jarvis, Reuter, Nelson, & Guevara, 2008), to calculate slopes; and the Global MODIS Raster Water Mask (Carroll, Townshend, DiMiceli, Noojipady, & Sohlberg, 2009a, 2009b) to account for the presence of bodies of water. We implemented the process to define the potential urban extent in ArcGIS from the extracted urban extents for 1996, considered as the real urban extents. We first determine the “minimum-bounding circle” that contains the real urban extent and locate its centroid. Then we use the r��,� estimated from equations (5) and (6) with the buffer function to obtain the estimated circles for each date. In all cases we use the estimated radius for the first date (1996). This is because we observed contraction of the potential urban extents when using the minimum-bounding circle for the first date (1996) and the estimated ratio for the following two dates (2000 and 2010). Second, we defined the developable terrain. Initial tests with a 15% slope threshold proved to produce fragmented patches of developable land in many cities, resulting in potential urban extents that were extremely small compared to reality. While architectural development guidelines in developed countries typically use the 15% slope threshold as constraint threshold for urban development (Saiz, 2010), given that the Andean Mountain Range crosses many countries in Latin America, in the region, urban development guidelines have been more tolerant and cities have grown in areas with considerably steeper slopes. An analysis of the distribution of slope values in a sample of urban extents extracted for the year 1996 suggested that in fact the median slope in the areas considered is 21%; hence, in the analysis we use a threshold of 20% slope to
Economic Census (EcC), and the various waves of the Egypt Labor Market Panel Survey (ELMPS) – produce different rates of formality for our universe, they demonstrated similar relationships between formality and observable characteristics. Results on the relationship between formality and characteristics were comparable across firm size (number of workers), firm age, economic activity and region. In a subset of the data sets, measures of firm productivity and whether or not they hired outside workers also showed comparable results. Only the ELMPS data include firms that operate outside fixed establishments, which are predominantly informal. After establishing the highly informal nature of firms outside establishments, we restricted most of our analyses to firms operating within fixed establishments, which can be found across all our data sources.

We generally found that firm size and firm age are strong predictors of formality, with larger and older firms being more likely to be formal. Industry and region were, at best, inconsistent if not unreliable predictors of formality. Firms that hired wage workers, especially non-relatives, were more likely to be formal, as were the ones that had higher labor productivity or net revenue per worker. When owner characteristics were available, we found that owners with secondary education, but especially higher education were more likely to have formal firms and so were prime age and older owners compared to owners under the age of 30.

When we compared the distributions of formal and informal firms in terms of their predicted probabilities of being formal, we found that there was some overlap. This result suggests that some informal firms are similar to formal firms and thus may be amenable to formalization. The overlap was larger when only firms that operate in fixed establishments were compared and when there was a limited set of 72
questions on paid work in agriculture, and to a lesser extent on small/secondary jobs.</u> Source: Koolwal (2018), based on ILO LFS pilot study data accessed at ILO.

Careful attention to wording choice, adapted to local context, is therefore important in the framing of employment questions. A recent study by Comblon and Robilliard (2017) using data from more than 40 surveys and censuses conducted in Cameroon, Mali and Senegal between 1976 and 2012 also discusses how women’s reporting of employment is more sensitive to questionnaire wording and design, owing to the effects of social norms/interpretation of wording, and the specific types of work women in low-income contexts tend to be involved in. Most socioeconomic surveys also do not distinguish between running and supporting a family business in their labor modules — within the LSMS, the 2016-17 Malawi and 2013-14 Uganda surveys do ask separate questions on whether respondents “run a business of any size for 9