rafmacalaba/datause-encoder-data huggingface dataset:
assesses laws that affect a woman’s pension. A complete list of the eight indicators and 35 topics is presented in Table A1.

Indicator‐level scores are obtained by calculating the unweighted average of the four or five binary questions within that indicator and scaling the result to 100. Overall scores are then calculated by taking an unweighted average of the eight indicators, with 100 representing the highest possible score. Take, for example, the legal environment in Afghanistan in 2019: this economy receives a score of 50 out of 100 for the _Going Places_ indicator because women face legal restrictions in two of the four legislative issues covered (women in Afghanistan cannot travel outside their home, nor can they choose where to live, in the same way as a man). In the _Getting Paid_ indicator, women face legal restrictions in only one of the four issues covered and, so, Afghanistan receives a score of 75 for this indicator. Overall, based on an unweighted average of the eight indicators, the WBL index score for Afghanistan is 38.13. A WBL index score of 100 would indicate that there are no legal inequalities between men and women in the areas covered by the database.<sup>2</sup>

# **3. Existing Literature**

There is a growing body of evidence that suggests that the types of legal inequalities measured under the WBL index matter for women’s economic outcomes.<sup>3</sup> Take, for instance, laws that impact women’s mobility. Demirguc‐Kunt, Klapper and Singer (2013) document a relationship between legal mobility restrictions and women’s access to finance; Islam, Muzi and Amin (2019) find that travel restrictions placed on women are associated with lower levels of female business ownership; and Htun, Jensenius and Nelson‐Nuñez (2019) find that such restrictions may reduce women’s labor supply. Laws that impact women’s decisions to work and their salaries, should they do so, have also been shown to be impactful. According to research by Zabalza and Tzannatos (1985), UK legislation forbidding discrimination based on gender is associated with increased employment and earnings of women. Hallward‐Driemeier and Gajigo (2015) show that, in Ethiopia, lifting constraints on women’s right to work outside the home is associated with increased engagement of women in the formal labor market. Amin and Islam (2015) document a link between laws mandating nondiscrimination based on gender and women’s employment. While laws mandating nondiscrimination in employment have generally been associated with positive outcomes for women, evidence from the United Kingdom links equal pay legislation with a decrease in female

> 2 A full description of the laws covered under the WBL and the methodology used to calculate the index can be found in World Bank (2019b).

> 3 A summary of this evidence is provided in World Bank (2019a) and a more complete overview in Roy (2019).

4
Table A1 Tobacco Clubs Survey

||Clubs<br>Surveyed|Villages<br>Visited|Total clubs<br>in district|
|---|---|---|---|
|_NORTHERN REGION_||||
|Chitipa|19|15|328|
|Mzimba|20|13|2,670|
|Rumphi|20|18|1,242|
|_CENTRAL REGION_||||
|Dedza|21|19|420|
|Dowa|21|18|3,977|
|Kasungu|20|13|2,442|
|Lilongwe|19|11|5,851|
|Mchinji|20|18|1,457|
|Ntcheu|21|8|669|
|Ntchiji|20|17|1,038|
|_SOUTHERN REGION_||||
|Mangochi|16|13|708|
|Zomba|21|17|956|
|Total|238|180|21,767|

Notes: The total number of clubs in each district corresponds to 2007 and was provided by the Tobacco Control Commission of Malawi.

39
With regard to the debt position, debt liabilities rose steeply in Egypt and Morocco in the past two decades. This uptrend, coupled with a downtrend in the portfolio liabilities position, represents a shift in foreign investors’ preference for holding sovereign debt rather than equities in both countries. Hence, investors are becoming more risk averse evidently during late 2000s.

Net debt as a share of GDP is consistent with the earlier results on non-oil-exporting countries’ maintenance of their net borrower position between 2007 and 2015. Egypt, Tunisia, Jordan, Lebanon, Morocco, and Mauritania ended up with larger net debt positions in 2015 than in 2007, indicating a higher propensity to borrow foreign currency. Saudi Arabia, Bahrain, and Oman extended more debt financing to international borrowers in 2015 than in 2007. Libya and Algeria closed 2015 as net lenders. Their lower net position than in 2007 reflects growing domestic financing needs. Almost all oil-exporting countries closed 2015 with a higher ratio of reserves to GDP than in 2007; exceptions were Algeria, Bahrain, and Iraq, which suffered slight declines (figure 8). Non-oil-exporting countries ended up with higher ratios of reserves to GDP than several oil-exporting countries (exceptions are Libya and Saudi Arabia). This pile-up of reserves in nonoil-exporting countries coupled with higher levels of total liabilities, including foreign borrowing, FDI liabilities, and excessive leveraging (figure 9). Reserve cumulation in non-oil-exporting countries is costly, given the sources financing it. As a consequence, the scale of financial integration in oil-exporting countries was greater in 2015 than in 2007 and significantly greater than in non-oil-exporting countries.

**Figure 8 Net debt as percent of GDP, by country, 2007 and 2015**

<!-- Start of picture text --> by country<br>2007 2015<br>AREBHRCOMDJIDZAEGYIRQJORKWTLBNLBYMARMRTOMNQATSAUSDNSYRTUNWBGYEM<br>1<br>0<br>-1<br>-2<br>-3<br>-4<br><!-- End of picture text --> _Source_ : Authors, based on Lane and Feretti 2015.

10
|Hansen<br>statistic<br>_J_|0.20|**5.13**<br>lts refer to the<br>er the average|the first stage<br>nstruments are|
|---|---|---|---|
|Partial<br>statistic<br>_F_|**555.49**|**260.97**<br>munism. Resu<br>) calculated ov|instruments in<br>is is that the i|
|es<br>SHI impact (%)|-0.021|**-0.363**<br>e country prior to com<br> _t_-tests. SHI impact (%|e subset of excluded<br>the joint null hypothes|
|M estimat<br>p-value|0.316|**0.001**<br>xisted in th<br>two-sided|ce test of th<br>ted, where|
|GM<br>SE<br>|1.90|**0.97**<br>hether SHI e<br>P-values from|insignifican<br>ns are repor<br>ation.|
|Coef|-1.95|**-3.92**<br>ndicator for w<br>icant at**5%**.|r to the joint<br>ying restrictio<br>the main equ|
|(%)||<br>d an i<br>Signif|) refe<br>entif<br>from|
|stimates<br>HI impact|-0.023|**-0.301**<br>dummy an<br>variable.|ster-robust<br>st of overid<br>y excluded|
|east squares e<br>p-value<br>S|0.284|**0.004**<br>lag of the SHI<br>he SHI dummy|_F_statistics (clu<br>stics for the te<br>nts are correctl|
|age l<br>E|95|**01**<br>first<br>d) of t|rtial<br>_J_stati<br>trume|
|o-st<br>S|1.|**1.**<br>the<br>ste|. Pa<br>n’s<br>ins|
|Tw<br>iable<br>Coef|nization rate<br>-2.13|(acute care)<br>**-3.25**<br>models, the excluded instruments are<br>f) and standard-error (SE, cluster-adju|corresponding estimating sub-sample<br>he last column, cluster-robust Hanse<br>h the error term and that the excluded|
|var|mu|tay<br>oth<br>Coe|he<br>In t<br>wit|
|Dependent|Measles im|Length of s<br>_Notes:_For b<br>coefficient (|outcome in t<br>regressions.<br>uncorrelated|
**Despite the growing number of developing countries investing in South Asia, the developed countries still lead in the value of FDI—and this edge has risen since the 2008 global economic crisis** . The value of developing country investments increased for much of the 2000s, hitting a peak of US$603 billion in 2008, or about 39 percent of total inflows. However, the developing countries’ share fell back to about 20 percent in 2010 (Figure 8). The global financial crisis’ relatively harsher impact on developed economies spurred greater FDI flows into developing countries (hence increasing developed country shares of FDI and lowering developing country shares), including South Asia. Estimates for 2012 suggest that the largest declines in the developing nations’ share of South Asia’s estimated FDI inflows were from 2009 to 2010.

**Figure 8: Developing Country Share of Inward FDI into South Asia**

<!-- Start of picture text --> 45<br>40<br>35<br>30<br>25<br>20<br>15<br>10<br>5<br>0<br>2003 2004 2005 2006 2007 2008 2009 2010<br>Source: UNCTAD statistics, fDiMarkets and World Bank staff calculations<br>percent<br><!-- End of picture text -->

**From 2003 to 2011, almost 70 percent of South Asia’s inward FDI was from developed countries, including 32 percent from the EU, 17 percent from the United States and 20 percent from other advanced economies.** Among developing countries investing in South Asia, the largest shares of inflows arrived from the Middle East and North Africa (MENA) and the East Asia and Pacific Regions (EAP). South Asia itself accounted for almost 4 percent of FDI within the region (Figure 9). Looking at specific developing countries, the United Arab Emirates contributed 8.5 percent and China (including Hong Kong SAR, Macau, Taiwan, and mainland China) supplied 6 percent.

14
**Figure 6. Personal exemption levels (multiples of GDP per capita)**

<!-- Start of picture text --> Chile<br>Mexico<br>Costa Rica<br>Panama<br>El Salvador<br>Argentina<br>Brazil<br>Dominican<br>LAC<br>Ecuador<br>Peru<br>Colombia<br>Honduras<br>Guatemala<br>Nicaragua<br>0 2 4 6 8<br><!-- End of picture text --> Source: Stotsky and WoldeMariam (2002).

The limited collection of income taxes has prompted some experimentation with alternative taxes – such as gross asset taxes and taxes on financial transactions. The former is essentially a minimum tax, typically applied at a rate of 1 percent. While easy to administer and potentially effective against evasion, it is not devoid of efficiency problems (Gómez-Sabaini, 2005). In turn, taxes on financial transactions were originally introduced in several countries as emergency collection devices, but they have proven hard to replace and have tended to persist given their low administration cost and high revenue collection capacity – in spite of their clear distorting potential in terms of promoting financial disintermediation.<sup>29</sup> If Latin America’s tax collection, low by international standards, effectively limits the room for fiscal redistribution, how much more effective could the state be in performing its redistributive role if tax revenues were more plentiful? We can illustrate the answer to this question using the conceptual framework outlined earlier to perform a counterfactual exercise in which we raise both overall tax collection and overall transfers by 2 percentage points of GDP, but maintain unaltered the incidence of taxes and transfers across the population – so as to isolate the distributive impact of additional fiscal resources.

Figure 7 reports the results of these simulations. The first striking aspect is the large degree of heterogeneity in the country responses. For example, in Peru an increase of taxes and transfers is accompanied by increases of inequality, a reflection of the regressivity of the transfer system (in the sense that transfers contribute to higher income inequality). At the other extreme are Mexico and Colombia, where tax-transfer volume increases lead to noticeable declines in the Gini coefficient of between .5 and 1.2 percentage points. In the other countries, tax-transfer volume increases not accompanied by interventions affecting their incidence have only modest distributional effects.

> 29 See Tanzi (2000).

14
infrastructure (water, sanitation, telecommunications, electricity, transport) as depicted in Table A1 in the Appendix, whereas the infrastructure quality gap has been widening across countries due to delays in structural and institutional reforms. In spite of significant public investment in infrastructure, most countries in the region have been unable to cope with pressing needs stemming from population growth, rapid urbanization and economic growth. A good illustration of the inability of governments in MENA to cope with growing demand for infrastructure services is given by the electricity sector whereby installed generation capacity is estimated to be 20 percent below the aggregate demand for electricity.

**Table 2: Impact of Infrastructure Shortages on Firms**

|Region|Electricity<br>connection delay<br>(days)|Value lost to power<br>outages (% of sales)|Water connection<br>delay (days)|Mainline telephone<br>connection delay<br>(days)|
|---|---|---|---|---|
|East Asia & Pacific|21|2.6|18|16|
|Europe & Central Asia|15|3.0|9|16|
|Latin America &<br>Caribbean|34|4.1|35|36|
|Middle East & North<br>Africa|62|4.3|44|49|
|South Asia|49|7.4|29|50|
|Sub-Saharan Africa|38|5.9|42|54|
|OECD|10|2.3|—|9|

Source: The data are derived from World Bank Investment Climate Assessments, and reported at <u>www.enterprisesurveys.org</u> In addition, political and institutional factors (i.e. inefficiencies in government decisions and actions) also affect the level of infrastructure stock and quality in a given country. This is particularly acute in MENA countries which have yet to implement structural institutional reforms, including the implementation of market liberalization policies, effective regulation of service providers, and roll back subsidies distorting end users’ tariffs. In addition, lack of institutional reform and inefficient public investment policies contain the impact of infrastructure investment on growth. Mustapha Kamel Nabli & Marie-Ange Véganzonès-Varoudakis (2007) investigate the linkage between economic reforms, human capital, infrastructure and economic growth in MENA. Employing growth regressions that include composite indicators of infrastructure on panel data, they find that the contribution of infrastructure on growth in MENA has been substantial but has declined from 1.4 during between 1980 and 1989 to 1.0 between 1990 and 1999. In the same vein, Agenor et al. (2005) investigate the impact of public 3
**Chart 12**

<!-- Start of picture text --> Ratio of external to domestic debt<br>3.00<br>Emerging Markets Emerging Europe Asia Latin America<br>2.50<br>2.00<br>1.50<br>1.00<br>0.50<br>0.00<br>2000 2001 2002 2003 2004 2005 2006 2007 2008 2009<br>Note: USD‐linked domestic debt reallocated to external<br>Source: JP Morgan EM Debt and Fiscal Indicators (2009) and BIS Financial Stability and<br>local currency bond markets (2008)<br><!-- End of picture text -->

**The relatively swift adjustment in the structure of the debt stock was possible thanks to the implementation of a series of liability management operations that altered the structure of the existing debt stock.** In all regions debt managers prepaid international bonds and/or multilateral and bilateral debt through buy backs or exchanges. In addition, countries like Colombia, Brazil, Uruguay and Egypt issued, for the first time ever, global bonds denominated in local currencies in the international capital markets. Even, if the contribution of these securities to the transformation of the composition of the government debt portfolios was rather marginal (except for Uruguay), this led to questioning of the validity of the “original sin hypothesis”<sup>13</sup> and opened a new financing channel to debt managers. For Brazil, this channel allowed the government to issue fixed-rate securities in reais at longer maturities than those placed in local markets, creating a valuable reference for the gradual extension of the curve domestically (discussed in more detail in the next section).

# **These findings are also confirmed by the structure of outstanding securities issued by EMs reported**

**in the BIS’s quarterly statistics**<sup>14</sup> . According to the BIS, international outstanding bonds and notes issued by EM governments as a proportion of their total issuance dropped 20 percentage points from over 30% in 1998 to about 10% in 2009. It is worth noting the considerable variation in this ratio among regions. While in Asia securities issued in foreign markets have traditionally accounted for less than 7%

> 13 See Eichengreen, B., and Hausmann, R., (1999). "Exchange Rates and Financial Fragility", In New Challenges for Monetary Policy. Proceedings of a symposium sponsored by the Federal Reserve Bank of Kansas City.

> 14 BIS quarterly statistics on bonds and notes outstanding issued by governments of EMEs. The sample included in chart 13 tracks the same countries for domestic and international securities. These are the countries used by the BIS in the Securities statistics and Syndicated Loans Table 16A: Domestic debt securities, by sector and residence of issuer. See <u>http://www.bis.org/statistics/secstats.htm. The ratio of international to domestic securities slightly</u> overestimates the ratio of foreign to local currency because of the issuance of local currency bonds in the international capital markets.

10
### **Table 1: Parameters used in the built environment audits**

|**Parameter**|**Description**|**Lowest Value**|**Highest Value**|
|---|---|---|---|
|**1 Lighting**|Availability of lighting<br>infrastructure (surveyed at<br>nighttime)|None|Bright|
|**2 Walking path**|Presence of sidewalks|None|Good|
|**3 Openness**|Ability to see and move in all<br>direction|Not open|Completely open|
|**4 Visibility**|Presence of vendors, shops,<br>building entrances, windows<br>and balconies from where<br>you can be seen|Out of sight of<br>others|Completely<br>visible|
|**5 Security**|Presence of police or security<br>guards|None|High|
|**6 People**|Number of people around<br>you|Deserted|Crowded|
|**7 Gender usage**|Presence of women near you|None|Majority of<br>women|

_Note: Each parameter was assigned a score between 0 (lowest value) and 3 (higher value), therefore allowing for two additional intermediate scores (1 and 2). These scores will then be rescaled and combined to create an overall safety index between 0 and 100% (see section 3.1.c).._

# **_2.2. Household survey_**

## _a. Design and sampling methodology_

The household surveys in all three cities were conducted from May to September 2022.<sup>15</sup> The surveys include socio-economic and demographic characteristics, transport mode choices, as well as employment choices. The original sample included 6,088 households, of which 176 were excluded because of data quality and missing information. The final sample of 5,912 households consists of working age women and men (working age is defined as between 18 and 50 years old). In Amman, the sample includes 1,995 households (998 men and 997 women); in Beirut: 2,000 households (1,000 men and 1,000 women); and in Cairo: 1,917 households (953 men and 964 women).<sup>16</sup> Figure 2 presents the location of surveyed households in the city.

The sampling of the households was done to be geographically representative by selecting locations proportionally to population density and building density. Among selected

> 15 In Amman: from July to September 2022; in Beirut: from June to August 2022; in Cairo: from May to June 2022.

> 16 Note that the sample size does not need to be proportional to the underlying population sizes. Therefore, although the cities have overall different size populations, our samples are similar in size.

10
determining both occupational choice and firm size (Evans and Jovanovic 1989, Blanchflower and Oswald 1998?, Banerjee and Duflo 2005). Hurst and Lusardi (2004) suggest that some of the evidence on capital constraints might instead be interpreted as reflecting the fact that aversion to risk falls with wealth. There is also the fact that an entrepreneur may not know his ability level before beginning the business. Jovanovic (1982) develops a model in which learning is important. Cabral and Mata (2003) are among those finding a relationship between firm size and firm age consistent with learning after entry.

Most of the empirical literature we have referenced uses data from high-income countries. There are reasons to believe that entrepreneurship differs in developing and developed countries for several reasons that may affect which factors differentiate entrepreneurs from wage workers. First, risk is likely to play a larger role and innovation a commensurately smaller role. The instability of the political and economic environment increases uncertainty of outcomes. Fewer firms operate at the cutting edge technologically. Technologies are likely to be adopted rather than invented in developing countries. Second, agency problems are arguably greater in developing countries. The difficulty of using courts and the scarcity of formal information systems makes delegation of authority within enterprises more problematic. This makes both arms length contracting across firms and separation of ownership and management within firms more difficult. We might expect the local social and political connections to matter more in more hostile institutional environments.

Third, agency issues and lower levels of formal schooling in the labor force make management of workers more challenging. Labor regulations which raise hiring and firing costs also contribute to making labor management more challenging. Combined with the difficulty of separating ownership and management, this implies that entrepreneurial outcomes will depend on managerial ability to a greater extent than is the case in developed countries.

Fourth, the market for business services is likely to be thinner in developing than developed countries. This implies that entrepreneurs must possess a greater range of skills themselves. Note that even in developed countries, entrepreneurs have been found to be jacks-of-all-trades, less specialized than managers (Lazear 2005; Wagner 2003). We