rafmacalaba/data-use-mentions-extended huggingface dataset:
For countries with multiple data waves, a subset of firms is re-interviewed over time, producing a panel component. This study exploits this panel component for 57 economies<sup>1</sup> surveyed at least twice between 2006 and 2019, amounting to approximately 14,000 unique firms. The panel data allows for the empirical estimations to include firm-level fixed effects, thereby accounting for time-invariant firm-specific omitted variables. However, there are some limitations of the panel subset of firms. First, typically less than 50 percent of firms surveyed in the first round are followed between the two waves, and thus the selection of firms may not be random and consists of survivor firms. Second, there are also high rates of attrition between the two waves.

An important feature of the ES data is the breadth of coverage in terms of topics. The surveys cover a wide range of topics, including access to finance, corruption, infrastructure, crime, competition, labor, the business environment, and performance. This enables the analyses to explore various channels of the effects, allowing for the possibility to build on studies using datasets based on registration lists (Huang et al., 2018). The data have been widely used by several studies to explore the private sector in developing economies (Paunov, 2016; Besley and Mueller, 2018; Chauvet and Ehrhar, 2018; Hjort and Poulsen, 2019).

Firm-level investment is the main outcome, captured by two types of variables. The first is a binary variable that takes a value of 1 if the firm purchased any fixed assets such as machinery, vehicles, equipment, land, or buildings were purchased (new or used) in the previous fiscal year. The second variable is the amount of expenditure on the fixed assets. These variables can be further broken down into type of investment – (a) land and buildings and (b) equipment and machinery. Summary statistics can be found in Table 1.

The main variable of interest is central government debt as a percentage
|Arts, entertainment, and recreation|Arts, entertainment and recreation|
|---|---|
|Voluntary and representative organizations|Other services activities|
|Household services|Activities of households as employers, undifferentiated<br>goods and services, producing activities of households for<br>own use|
|Extraterritorial organizations|Activities of extraterritorial organizations and bodies|
|Taxation and budget|Administration of the State and the economic and social<br>policy of the community|
|Multisector laws|-|
|Non-economic laws|-|

## **3.4 Methods for Exploring Legislative Predictability**

Once all the relevant indicators are calculated, both for legislative predictability and contextual variables like sectors, we carry out a range of explorative and descriptive analyses. Combining variables on modifications with contextual variables allows us to measure regulatory predictability and its underlying drivers.

First, we explore legislative predictability across countries, comparing Jordan to a set of different countries. This offers crucial insights into cross-country variability and how different legislative systems operate. The analysis is based on the smoothed hazard risk of legislative modification. Such smooth hazard curves display how the risk of modification changes over time (i.e. months). Second, we deep dive into Jordanian legislative data, by looking at trends to track legislative predictability over two decades. This in-depth descriptive analysis disaggregates the data by year, sector, and initiator. The in-depth analysis starts with the distribution of laws and regulations passed in a given year which takes the absolute yearly count of laws and regulations. Next, the analysis moves to modifications by displaying modifications as percentage of all laws and regulations passed in a given year, followed by modifications as percentage of all laws and regulations passed within 24 months. We further disaggregate modification within 24 months by the providing the percentage share of economic sectors as well as the policy initiator for all laws and regulations that were modified within 24 months.

# 4. LEGISLATIVE PREDICTABILITY IN AN INTERNATIONAL CONTEXT

Uncertainty in policy making is
follow the JMP guidelines to the extent possible with the available data. Specifically, each of the three category tiers are coded as shown in Table 1.<sup>5</sup> Table 2 shows the number and proportion of CCs that fall under each tier.

Each of the three tiers are then scaled into an index between 0 and 1. The WASH score for each HCF is the aggregate of the three indices combined. And the WASH index is the mean of the HCF WASH scores at the upazila level, scaled between 0 and 1. The upazilas with WASH index below 0.5 are categorized as ranking “low” in WASH, whereas those with a score above 0.5

> 4 Mean probability of households being below $2.50/day using the Progress Out of Poverty Index (PPI) computed using survey data.

> 5 The survey includes whether there was arsenic testing done at the HCF, however, no further information on water treatment or quality was solicited. The survey also includes a question on when the pit latrine was last emptied. However, this information is not complete enough to make a proper assessment of the state of sanitary facilities beyond functionality. Therefore, we leave those out in constructing our index. See Annex‐Table 1 for questionnaire.

4
identify return migrants are national household surveys. In those surveys, return migrants are captured at the time they have returned home after completing their most recent migration spell overseas. Such surveys in origin countries are suitable to carry out nationally-representative comparisons of the characteristics and labor market outcomes of return migrants with those of nonmigrants, including participation in labor market activities, type of employment after return and labor earnings. The drawback, however, is that the number of return migrants captured can be small due to the relatively low incidence of recent return migrants in the total country population, combined with the fact that survey questions

> 3According to the sponsorship system that regulates migration to the GCC, labor migrants can only enter and stay in the country through a sponsor, a local employer, which takes on both legal and economic responsibility for the migrant worker.

> 4The termination of employment abroad is reported as the main reason for returning home by labor migrants from Bangladesh and Nepal, according to the 2018/2019 World Bank Bangladesh Return Migrant Survey (BRMS), and to 2017/2018 Labor Force Survey for Nepal

6
** , “Broadband Internet: An Information Superhighway to Sex Crime?,” _Review of Economic Studies_ , 2013, _80_ (4), 1237–1266.

- **Bloom, Mia, Hicham Tiflati, and John Horgan** , “Navigating ISIS’s Preferred Platform: Telegram,” _Terrorism and Political Violence_ , 2017, _31_ (6), 1242–1254.

- **Brockmeyer, Anne, Quy-Toan Do, Cl ́ement Joubert, Mohamed Abdel Jelil, and Kartika Bhatia** , “Transnational Terrorist Recruitment: Evidence from Daesh Personnel Records,” _The Review of Economics and Statistics_ , forthcoming.

18
Policy Research Working Paper 11041

# **Abstract**

This paper provides evidence on the nature of financial constraints faced by women entrepreneurs, especially in contexts of stringent social norms. Using micro-data from the World Bank Enterprise Surveys for 61 countries, the analysis shows that formal firms managed by women do not face credit constraints on the extensive margin. They are equally likely to apply for credit as their male counterparts and experience lower rates of credit rejection, with a higher likelihood of opening credit lines. However, on the intensive margin, firms managed by women receive lower credit amounts, indicating signs of credit constraints. This disparity in access to credit cannot be explained by gender differences in risk profiles, profitability, or productivity.

However, firms managed by women have lower sales per worker, suggesting challenges in accessing product and labor markets. The paper finds suggestive evidence of capital misallocation based on gender, particularly in countries with more restrictive gender and cultural norms. Firms managed by women demonstrate a 15 percent higher average return on capital compared to firms managed by men, indicating the potential benefits of increased access to credit for women-led businesses. These findings emphasize the importance of addressing gender-specific constraints to accessing finance and promoting gender-inclusive policies to enhance firm growth and reduce capital misallocation.

This paper is a product of the International Finance Corporation. 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 agrover1@ifc.org and mviollaz@cedlas.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
Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|

_Source_ : Author based on DHS 2005/2010/2015. _Note:_ Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Reference group for wealth quintile is poorest.

Turning to economic opportunities, Columns (2)-(5) in Table 4 show that displacement is associated with more traditional attitudes around women in the domestic sphere. Depending on the specification, displacement reduces the probability of disagreeing with the statement ‘a woman’s main role is family caregiving and cooking’ by 6-8 percentage points. This might be explained by the fact that social expectations that assign women to the domestic sphere can make them ‘protective’ of the unpaid care space, attaching value to their leadership of it and being resistant to 18
-8-

more pronounced when lending ratss are used as a basis for comparison (see Figure 1B). This is not surprising, since there is no arbitrage to narrow the gap between foreign and domestic lending rates. There is no competition between foreign and domestic banks in Turkey for business loans; domestic banks enjoy what amounts to a monopoly pos'tion.

As long as domestic interest rates are not linked to foreign interest rates (i.e. foreign rates plus exchange rate depreciation) there is an additional degree of freedom in macroeconomic policy. Then ci' es in domestic real interest rates can resolve potential discrepancies between' fiscal deficits and external targets through their impact on the r.et private savings surplus.3 In the process, private investment and hence output growth will be affected. This is an important link between fiscal policy and output growth.

The mechanism of this link between fiscal policy and output growth is shown in Figure 2. Underlying this figure is the following identity, derived from the national accounts, but with behavioral content built into private savings and investment:

- (1) CAS - FS + NPS(r)

- FS + Spr(r) - Ipr(r)

- i/ Changes in deficits will only : '%aire changes in real interest rates to induce private savings surplus if private savings would not rise automatically in response to tax cuts. Such an automatic offset may take place if the private sector recognized that a cut in taxes without a matching cut in expenditure simply raises the taxes they will need to pay in the future. Then a tax cut would have no impact on private consumption. Thus deficits would have a one-for-one impact on private savings and no impact on either real interest rates or external balance. This is known as "debt neutrality" in the economic literature. Empirical tests strongly reject this assumption of "debt neutrality" for Turkey.

ChhibberDisk/chhibber-Turkey Paper/ac:07-28-88 lc
cost by about 30% (Jack 2013). PES also achieved temporary reductions in deforestation in Uganda (Jayachandran _et al._ 2016) that were economically viable at a cost of carbon of $39/t. If the size of incentives exceeds the opportunity cost of environmentally inferior uses and issues of collective action (Edwards _et al._ 2021) or political economy (Pailler 2018; Cisneros _et al._ 2021) can be resolved, competitively awarded PES based on clear rights could offer considerable potential.

Evidence from Brazil shows that even simplified ways of self-registration can be used to monitor land use but that associated incentive effects need to be considered carefully. Linking eligibility for subsidized credit to compliance with environmental regulation has been effective in reducing deforestation (Assunção _et al._ 2020). It also allowed to effectively monitor Command and control measures, by targeting a 'Priority List' of municipalities with more intense environmental monitoring and enforcement, were effective, reducing deforestation by 40% and cutting 39.5 million tons of carbon emissions, an amount that could be significantly increased by selection of ex post optimal municipalities (Assuncao _et al._ 2019).

To incentivize conservation of native vegetation on about 394 million ha of private land, the country established the rural environmental cadaster (CAR) as a tool for voluntary self-registration of rural properties whereby landowners geo-reference their property boundaries and remaining forests using satellite imagery at their own expense, possibly with NGOs support (Azevedo _et al._ 2017). Yet, to the extent that it allowed credit constrained small farms to access subsidized credit to establish pastures on previously 25
Champaign. Two treatment arms provided encouragement to major in economics. A “prosocial” treatment provided information emphasizing the wide variety of career options and personal benefits associated with the major, while an “earnings” treatment provided information on financial returns. We evaluate the effects of the two treatments on subsequent choices to take another economics course and declaration of the economics major by the end of the student’s junior year using student-level matched administrative data. In addition to examining the overall effects of these treatments, we examine whether treatment effects are mediated by the gap between introductory-course performance and expected grade and having a female teaching assistant (TA).

Our primary aim is to evaluate whether women can be “nudged” into a major with lowcost, theoretically grounded, encouragement/information interventions. In addition to contributing to the college major literature, our work speaks to the broader literature on gender differences in behavior, including whether women are more prosocially motivated than men and gender differences in responsiveness to small nudges and framing.

We find that the average male student receiving either treatment is more likely to take at least one more economics course after the focal course, but there is little evidence of increased majoring. The average woman appears unresponsive to either treatment. We next consider mediating factors suggested by the prior literature, finding that the introductory course grade is an important mediator for women, while TA gender is an important mediator for men. Women with better-than-expected grades can be nudged to take another economics course, but there is no effect on majoring. Men with a female TA in the focal course are more likely to take another economics course in response to treatment, with no effect on majoring.

# **2. Experimental Design and Analysis**

# 2.1 Setting

The study took place at the University of Illinois at Urbana-Champaign, a large elite public university. The economics program is housed in the College of Liberal Arts and Sciences. When students register for courses, they sign up for both a lecture with a faculty instructor and
|_λt_<br>Mean|Diferent values<br>-0.834|Infrastructure stock, Brazil, 1970-2007|
|Average growth|0.0038||
|_ei_, _Am_1970, _fq_|1, 1, 0.1|Normalizations|

Output Tables, 2016 release. In 2007 the share of manufacturing in fixed capital formation was about 73%. Then, we assign the remaining 27% to services. Given this information, we choose _μm_ = 0 _._ 73 and _μs_ = 0 _._ 27. The elasticity of substitution between sectors in investmentgoods production is taken from Sposi (2012), who estimates a value of 0.18 for _ν_ using data from the Republic of Korea.

On the production side, we adopt the values of Restuccia and Rogerson (2008) in a similar setting for the shares of private inputs; in particular, _α_ = 0 _._ 283 and _γ_ = 0 _._ 567. Given that there are not available estimates of the impact of electricity access to output production at the sectoral level, we estimate them. Following the similar approach to the one explained in section 5.1, we perform an econometric analysis employing variation in electrification over the period 1970-1996 using Brazil municipality panel data on sectoral production, labor use 34
<!-- Start of picture text --> Figure 14: Sierra Leone Has Space to Expand Education Spending and Improve Outcomes<br>Potential Financing Pathways for Sierra Leone<br>a. Total education spending, b. Education spending per child, c. Learning-adjusted years of<br>$ constant PPP (millions) $ constant PPP schooling<br>650 250 5<br>2.3% 218 4.7<br>200 4.4<br>550<br>166 4 4.1<br>150<br>450 1.7%<br>100 126<br>3<br>350<br>50<br>1.6%<br>250 0 2<br>2015/16 2020/21 2015/16 2020/21 2015/16 2020/21<br>Average growth (median) Average growth (median) Average growth (median)<br>Ambitious growth (75th percentile) Ambitious growth (75th percentile) Ambitious growth (75th percentile)<br><!-- End of picture text --> _Source:_ World Bank calculations based on HCI, UIS, and IMF data. _Note:_ The data labels in panel (a) show education spending as a percentage of GDP.

In the Sierra Leone example, we have used high-spending and fast-spending-growth low-income countries as benchmarks for gauging the scope for increasing public education spending over five years. However, other benchmarks may be more relevant for specific countries and for more detailed analysis. For example, Sierra Leone has recently come out of a protracted civil war, so benchmarks associated with similar postconflict countries might be more appropriate in this case. The World Bank is currently developing a benchmarking tool that includes common comparison groups as well as the possibility for analysts to choose specific groups.

As countries run out of fiscal space or approach the efficiency frontier, the room for increasing funding for education will be limited. In the
proposes a practical microsimulation approach to assessing the distributional impact of enhancing market competition in key sectors of economic activity. The approach combines data from household budget surveys with the parameters of reform scenarios in selected markets to estimate the welfare gains among current and new consumers likely to benefit from enhancing competition. This novel approach is applied to the case of the mobile telecommunication market in Ethiopia, which has been dominated by a state-owned monopoly until recently. The results show that a reform scenario that reduces the market share of the monopoly to 45 percent would be associated with a 25.3 percent drop in the prices of mobile services and an increase in the number of new users by 4.6 million. The

> 28 To calculate the money metric welfare of a price decrease, the expected expenditures of new entrants are assumed to be equal to that of the current user group. See the WELCOM user manual for more information; see WELCOM Stata Tool, Global Solutions Group on Markets and Institutions for Poverty Reduction and Shared Prosperity, Poverty and Equity Global Practice, World Bank, Washington, DC, http://dasp.ecn.ulaval.ca/webwel/welcom.html. The change in well-being is equal to the negative value of the product of the estimated change in the proportion of users, the average expected expenditures among new users of the good of interest, and the observed change in price. Average expected expenditures among new users are estimated by running a quantile regression model and random imputation of the residuals for those households with positive expenditures. mcema also provides the option to run a linear regression to estimate these expenditures. Please refer to Rodríguez-Castelán et al. 2021 for a detailed discussion.

15
Table A.5: Other studies considered

||Study|Intervention|Country|Reason for not inclusion|
|---|---|---|---|---|
||Adoho et al.(2014)|Job or business<br>training|Liberia|Positive effect of business training on self-employment but short-term hori-<br>zon (outcomes measured 7 months after intervention)|
||Attanasio et al.(2015)|Microcredit|Mongolia|Public use data does not include migration|
||Attanasio et al.(2017)|Vocational training|Colombia|10-years evaluation requires access to several administrative data sets with<br>focus on formal employment|
||Augsburg et al.(2012)|Microfnance|Bosnia and<br>Herzegovina|Positive impact on self-employment but short-term horizon (outcomes mea-<br>sured 14 months after intervention)|
||Bandiera et al.(2017)|Graduation program|Bangladesh|Public use data does not include migration|
||Bandiera et al.(2018)|Vocational training|Uganda|No attempt to track respondents who moved outside BRAC branch offce area|
|4|Banerjee et al.(2015);<br>Banerjee et al.(2016)|Graduation program|West Bengal|Public use data does not include migration|
|4|Berge et al.(2014)|Business training<br>and grant|Tanzania|No effect on business survival and short-term horizon (outcomes measured<br>4-7 months after intervention)|
||Blattman and Annan(2016)|Agricultural training +<br>in-kind grants of $125|Liberia|Short-term horizon (outcomes measured 14 months after intervention) and<br>no effect on self-employment|
||Blattman and Dercon(2018);<br>Blattman et al.(2019b)|Cash grants of $300<br>or job offer|Ethiopia
# **1. Introduction**

The COVID-19 pandemic is having a deeper impact on South Asia. The World Economic Outlook of the IMF predicts that in 2020 the world economy will contract by 4.4%, while real GDP in India is expected to decline by 10.3%. Afghanistan, Pakistan and Sri Lanka will enter into recessions while the region as a whole is expected to contract by 8.4% (IMF, 2020). Governments in the region have introduced a number of interventions, ranging from delays in payments on taxes and debt service to increasing liquidity (World Bank, 2020b). These interventions were done amid ongoing fiscal stress and socioeconomic challenges, including social inequality and lack of opportunities for certain groups. Along with other developing economies, countries in the region face greater risk of not only reversing advances in sustainable development (Schneider et al., 2021), but also deepening existing vulnerability problems if sound policies are not in place.

This paper explores the impact of COVID-19 on South Asia using a global database of over 100,000 firms collected by the World Bank. It uses the Business Pulse Surveys (BPS) in 30 countries, and the World Bank Enterprise survey data in 21 countries.<sup>1</sup> This paper is organized around the following three core questions. _First_ , how is COVID-19 impacting South Asian firms relative to those in other regions and countries? To this end, we examine in-depth the usual target groups of "vulnerable" firms, namely: (1) micro and small firms; (2) sectors, especially the hardest hit ones; (3) female-led firms; and (4) exporters. _Second_ , how are South Asian firms adjusting to the COVID-19 related economic disruptions? We look into adjustments on employment, digitization and the propensity to pivot product-mix. _Third_ , what is the role of policy in supporting South Asian firms during crisis and recovery? This paper argues that size and sector are imprecise targets for policies supporting