rafmacalaba/datause-encoder-data huggingface dataset:
moderate-income households. A simple way to begin is to promote the use of payroll cards as a way to make people comfortable with non-cash means of making payments and maintaining short-term savings. In addition, the government might consider implementing a variation on the Community Reinvestment Act (CRA), the U.S. legislation that puts mild pressure on banks to serve moderate-income communities. The entry into the Mexican banking system of _Banco Azteca_ , with it focus on middle- and moderate-income households, is also a positive development. The government should encourage other investors to compete with _Banco Azteca_ in this market, while ensuring that they maintain sound banking controls and balance sheets. Finally, the effort to strengthen the oversight and financial stability of the popular banks, while also aiding their outreach, could bring many benefits.

The growth and stabilization of the popular banking sector can bring two major benefits to the Mexican financial system. First, it provides more competition for the large commercial banks which could lower their fees. Second, the popular banks, which mainly serve moderateincome consumers and small businesses, can operate much more informally than traditional banks. In simple terms, they do not need lobbies made of marble. This means that they can be financially and culturally accessible to moderate-income households. If their offices have a similar appearance to other businesses or non-profit organizations that serve moderate-income households, then their target clientele will feel comfortable in this setting. In addition, by having a secure but informal setting, their operating costs will be lower which will allow them to serve moderate-income communities profitably. While we support the growth of popular banks, we do not do so at the cost of the stability of the financial system. But we do not believe that this tradeoff is necessary. The U.S. experience with community development banking has demonstrated the stability and profitability of “popular banking.” It has also proved a source of investment for traditional commercial banks.

As in the U.S., future Mexican policy would benefit from more research. The ENDESFI survey was invaluable in providing a baseline survey of the use of financial services by households in Mexico City. Additional research should develop this further and also focus on the business models of financial institutions, both banks and non-banks that currently serve moderate-income households. This will provide policy makers and private sector institutions a better understanding of how moderate-income households obtain financial services, what they pay form then, and what might be done to lower the cost or improve the quality of these services.

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# **TABLE A3. Heterogeneous effects of Maternal Mental Health on Children Vocabulary at Age 5 by Gender**

# **_Dependent variable: Standardized PPVT_**

||(1)|(2)|(3)|(4)|(5)|(6)|
|---|---|---|---|---|---|---|
||<br>IV<br>_E_<br>|<br>with PDS-s<br>_ffects on gir_<br>|<br>elected vari<br>_ls_<br>|<br>ables and fu<br>_E_<br>|<br>ll regressor<br>_ffects on boy_<br>|<br>set<br>_s_<br>|
||MHI-1|MHI-2|MHI-3|MHI-1|MHI-2|MHI-3|
|Maternal Mental Health (-)|-1.783*|-0.889*|-0.981*|-0.501|-0.238|-0.249|
||(0.982)|(0.495)|(0.558)|(0.700)|(0.328)|(0.342)|
|Constant|0.413|0.411|0.400|1.435***|1.436***|1.437***|
||(0.669)|(0.676)|(0.692)|(0.399)|(0.396)|(0.395)|
|Observations|544|544|544|551|551|551|
|Mother controls|Yes|Yes|Yes|Yes|Yes|Yes|
|Child controls|Yes|Yes|Yes|Yes|Yes|Yes|
|Household controls|Yes|Yes|Yes|Yes|Yes|Yes|

<mark>Table A3 presents estimated effects of maternal mental health on child vocabulary at age 5, separated by child</mark> gender. We estimate the model selected from LASSO procedure. Selected control regressor set includes mother's age, wealth index, living in urban area, child's age, consumption of durable goods index, household size, number of children younger than 5 years in the household, and Height for age Z-score. Sample is restricted to children with available information on maternal mental health in 2002 and PPVT scores in 2006 and 2009. * and ** indicate statistical significance at 10% and 5%, respectively. Robust standard errors in parentheses.
# **A. Context**

## **A.1 Administrative Boundaries**

**Figure A.1:** Administrative Boundaries

<!-- Start of picture text --> 10 ° N 10 ° N<br>9.5 ° N Koinadugu 9.5 ° N<br>Bombali<br>Kambia<br>9 ° N 9 ° N<br>Port Loko Tonkolili Kono<br>8.5 ° N 8.5 ° N<br>8 ° N Moyamba Bo Kenema Kailahun 8 ° N<br>7.5 ° N Bonthe 7.5 ° N<br>Pujehun<br>7 ° N<br>7 ° N<br>13 ° W 12.5 ° W 12 ° W 11.5 ° W 11 ° W 10.5 ° W<br>13 ° W 12.5 ° W 12 ° W 11.5 ° W 11 ° W 10.5 ° W<br>(a) Districts (b) Chiefdoms<br>10 ° N<br>9.5 ° N<br>9 ° N<br>8.5 ° N<br>8 ° N<br>7.5 ° N<br>7 ° N<br>13 ° W 12.5 ° W 12 ° W 11.5 ° W 11 ° W 10.5 ° W<br>(c) Sections<br><!-- End of picture text --> Maps of Sierra Leone’s different administrative units are provided for reference. Sections (bottom) nest neatly in chiefdoms (top right), which nest neatly in districts (top left). The original randomized experiment was run in four districts: Bombali, Tonkolili, Bo, and Kenema.

A3
# Figure 16.  Full sample: Countries with and without fiscal rules

<!-- Start of picture text --> Less Fiscal Rules More Fiscal Rules<br>1.0<br>0.8<br>0.6<br>0.4<br>0.2<br>0.0<br>-0.2 Less Fiscal Rules = 0.42***<br>More Fiscal Rules = 0.19***<br>-0.4<br>-0.6<br>-0.8<br>Côte d'Ivoire<br>Azerbaijan<br>GreeceEcuadorUruguayLiberiaArgentina<br>CyprusRwandaCongo, Rep.Timor-Leste<br>Antigua and BarbudaBrazilNamibiaEquatorial GuineaNigerPakistanIndiaHungaryKenyaRomaniaSerbia<br>ParaguayBurundiBeninTurkmenistanMontenegroPanamaChadCambodiaColombiaTanzaniaCentral African RepublicCroatiaAndorraGabonIcelandMongoliaSenegalMaliLatviaBurkina Faso<br>TogoEstoniaMaltaSri LankaSt. Kitts and NevisSt. Vincent and the GrenadinesIran, Rep. of<br>Cabo VerdeGeorgiaUgandaGrenadaCameroonIndonesia<br>JamaicaPolandLithuaniaRussian Federation<br>ArmeniaMaldivesNigeriaPortugalIsraelPeruSouth SudanBulgariaCzech Republic<br>Slovak Republic<br>MexicoSt. LuciaKazakhstanGuinea-BissauCosta RicaBotswanaVietnam<br>Slovenia<br>ItalySpain<br>Chile<br>Mauritius<br>Japan DominicaThailandLuxembourg New Zealand<br>France<br>SwedenMalaysia NorwayBelgium GermanyNetherlandsThe Bahamas<br>IrelandAustria<br>Australia<br>Finland<br>Singapore<br>government spending and real GDP 1980-2020 Denmark United States United Kingdom<br>Correlation between cyclical components of real<br>Canada Switzerland<br>Hong Kong SAR, China<br><!-- End of picture text --> Notes: Each bar represents the correlation between the (HP) cyclical components of real GDP and real government spending for countries with and without fiscal rules. “With” fiscal rules indicates that at least one fiscal rule is being enforced; “without” means no fiscal rule is being enforced. The difference between the two averages is not significant. *, **, and *** denote significance at the 10, 5, and 1 percent level, respectively. Sources: Authors’ calculations based on Davoodi et _al_ . (2022) fiscal database and WEO (IMF) data.
**Table 8 Age Distribution of Researchers in Latvia, 2000**

|Age|<35|36-45<br>46-55|56-65|>65|
|---|---|---|---|---|
|%|3.1|17.4<br>32.4|36.5|10.6|
|_Source:_Dat|a of the Mi|nistry of Education and Sc|ience of Latv|ia|

- As the two charts below indicate, most university students (70%) prefer to study liberal arts, business and law rather than science and engineering (less than 15%). Therefore, the system is not generating enough new science and engineering students to renew the rapidly ageing existing cadre.  Furthermore, Latvia is generating new science and engineering graduates at a rate that is less than half of the rate of the EU as a whole and less than a third of the rate of Ireland and Finland.  This is not the least bit surprising.  Why study science and engineering if there is no demand in Latvia for these skills?<sup>36</sup> Nevertheless, these trends do not bode well for Latvia’s future scientific and innovative potential.

**Figure 28 New S&E Graduates in 2000**

<!-- Start of picture text --> Turkey<br>Slovenia<br>Poland<br>Latvia<br>Lithuania<br>Hungary New S&E graduates (‰ of 20 -<br>Estonia 29 years age class) in 2000 or the<br>Czech Rep. closest year<br>Bulgaria<br>EU<br>Ireland<br>Finland<br>Denmark<br>0,0 5,0 10,0 15,0 20,0 25,0<br><!-- End of picture text --> _Source_ : Eurostat, Trendchart S&T Indicators, 2003, available at <u>www.trendchart.org</u>

> 36  Although there may not be demand in Latvia for these skills, Latvians with high quality scientific and education skills will soon be able to work elsewhere in the EU.  In the first instance, this will help Latvians, although it will not necessarily generate any immediate benefits for the Latvian economy. However, over the longer run, this is where emigration and return migration can play a useful role. Latvians can obtain training inside and outside Latvia, work outside Latvia for a while, and return when and if demand arises with skills, knowledge, and contacts which they can use inside Latvia.  This process of outmigration and subsequent inmigration has proven to be enormously beneficial for the development of Korea, Taiwan, and India.  It is also important to note that Latvian firms do not have to fill their managerial ranks only with Latvian managers.  Indeed, in the EU context, Finnish or French managers might be preferable.

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# **Capital Market Financing and Firm Growth**

Tatiana Didier<sup>a</sup> Ross Levine<sup>b, c</sup> Ruth Llovet Montanes<sup>a</sup> Sergio L. Schmukler<sup>a,*</sup>

**JEL Classification Codes:** F65, G10, G31, G32, L25, O10, O16, O40

**Keywords** : bond markets, capital market development, capital raising, equity markets, financial structure, firm dynamics, firm financing, firm size

a World Bank, b University of California at Berkeley, c NBER

> * We are grateful to Juan Jose Cortina, Marta Guasch, Soha Ismail, Matias Moretti, and Lucas Núñez for outstanding research assistance at different stages of the project. We received very helpful comments from Jean-Louis Arcand, Eugenia Andreasen, Fernando Broner, Paco Buera, Charlie Calomiris, Eduardo Cavallo, Julian di Giovanni, Roberto Fattal-Jaef, Tomoo Kikuchi, Edith Liu, Eswar Prasad, Luis Serven, Nirvikar Singh, and participants at presentations held at the XVII Workshop on International Economics and Finance (Costa Rica), Columbia University, Cornell University, CREIUniversitat Pompeu Fabra, the Geneva Graduate Institute, the Hong Kong Institute for Monetary Research, the Indian National Institute of Public Finance and Policy, the LACEA-LAMES Annual Meeting (Brazil), Pontificia Universidad Javeriana, Ridge Forum (Argentina), Stanford University, and the World Bank. Research support came from the World Bank Chile Research and Development Center, Knowledge for Change Program (KCP), the Latin America and the Caribbean (LAC) Region’s Chief Economist Office, and the Strategic Research Program (SRP). The research presented in this paper builds on previous work that appeared as <u>HKIMR Working Paper 17/2015, NBER Working Paper 20336, and World Bank Policy Research Paper 7353.</u> Email addresses: <u>tdidier@worldbank.org, rosslevine@berkeley.edu, rllovetmontanes@worldbank.org,</u> and <u>sschmukler@worldbank.org.</u>
declined to under 2 percent of the population (24,000 households). Surprisingly, this low coverage persisted in 2020 despite the economic challenges posed by the COVID-19 pandemic on people's earnings. The MSA scheme had limited coverage, with only 4.9 percent of the poorest quintile covered in 2011 (World Bank, 2020) and 2 percent of the population (World Bank, 2021, p.76). The MSA scheme's generosity was particularly low in 2013/14, representing only 1.3 percent of total household income and 1.9 percent of household income in the poorest quintile. While targeting accuracy for social assistance schemes, including MSA, was good, it was mainly due to low coverage rather than effective beneficiary identification methodology (World Bank, 2020).

**The coverage of the MSA program dropped to less than 2 percent of the population (24,000 households) in 2019 and remained the same in 2020 despite COVID-19's impacts on earnings (World Bank, 2021); the limited coverage and generosity of means-tested social assistance programs have led to a limited impact of the program on poverty reduction.** The direct beneficiaries of the scheme peaked in 2014-2015 (around 52,000) but gradually contracted to close to 20,000 beneficiaries in 2021-2022. In 2018, meanstested benefits represented 20 percent of benefits for the poorest 20 percent of beneficiaries' disposable incomes, down from 24 percent in 2016. As a result of the combined decline in coverage and adequacy, means-tested programs reduced the poverty gap by only 25 percent and the Gini coefficient by only 1.3 percentage points after considering all other social protection transfers (World Bank, 2021). Recent evidence (Almeida et al., 2022) has documented very low generosity of the minimum income scheme in Bulgaria compared to other EU countries when using the 40% poverty line as a criterion and even more with the 60% poverty line. This is also the case when comparing benefits with the median disposable income in a sample of OECD countries (Figure 4).

**A significant limitation to higher coverage of the MSA scheme in Bulgaria arose from strict eligibility criteria, including income-related conditions and other limiting factors** . Only a small fraction of the poor population qualified for MSA because of the low threshold for available income as an eligibility criterion. The program's design was restrictive and conservative, and systematic indexation was not applied, making it challenging to adapt to macroeconomic environment changes during different economic cycle phases. There were also no clear rules for setting the GMI level and percentage system or methods for regularly updating them for various beneficiary types. Consequently, the coverage was low and decreasing (European Commission, 2018; World Bank, 2021). Therefore, there was a need for reforms to improve the coverage, adequacy, and impact of the program on poverty reduction in Bulgaria (European Commission, 2018; Vaughn & Cabrera, 2022; World Bank, 2020; World Bank, 2021).

**Figure 4. Adequacy of minimum income benefits (% of median disposable income), 2022**

10
**<u>Table 5.3: Estimated Annual Health Impacts of Indoor Air Pollution (Thousands)</u>**

||**Estimat**<br>**Case**|**ed Annual**<br>**s(000)**|**Estimat**<br>**DALY**|**ed Annual**<br>**s(000)**|
|---|---|---|---|---|
||Urban|Rural|Urban|Rural|
|**_Acute Respiratory Illness(ARI): _**|||||
|Children(under the age of 5years)– increased mortality|19.5|166.4|662|5,660|
|Children(under the age of 5years)– increased morbidity|7,570|47,925|12.5|79|
|Females(30years and older)– increased morbidity|9,401|47,384|65.8|331.7|
|**_Chronic obstructive pulmonary disease (COPD):_**|||||
|Adult females – increased mortality|7.5|53.4|74|363|
|Adult females – increased morbidity|39,000|202.5|127.7|455.6|
|Total Disability Adjusted Life Years (DALYs)-mortality<br>and morbidity|||942.4|6,889.3|

_Source:_ Staff estimates.

Table 5.3 also gives the DALYs lost to indoor air pollution. An estimated 8 million DALYs are lost each year. About 70-80 percent are from mortality and 20-30 percent are from morbidity.

The central estimated costs associated with the impacts identified above are given in Table 5.4. Briefly, the cost of mortality is based on the value of statistical life (VSL) estimated for India as a higher bound and HCA as a lower bound for adults and on HCA for children under 5. The cost of morbidity includes the cost of illness (medical treatment, value of lost time, etc) and value of DALYs estimated in GDP per capita.

To summarize, the total annual cost of indoor air pollution is estimated at Rs. 305-1425 billion, with a mean estimate of about Rs.865 billion (Table 5.4) or 1.3 percent of GDP in 2009. About 68 percent of this cost is associated with COPD, and 32 percent with ARI.<sup>14</sup> COPD and ARI mortality represents about 90 percent of the total cost, and morbidity about 10 percent (Figure 5.1).

# **Table** **<u>5.4: Estimated Annual Cost of Indoor Air Pollution</u>**

||**Estimated A**<br>**(Billio**<br>|**nnual Cost**<br>**n Rs)**<br>|
|---|---|---|
||Urban|Rural|
|**_Acute Respiratory Illness(ARI): _**|||
|Children(under the age of 5years)– increased mortality|20|190|
|Children(under the age of 5years)– increased morbidity|5|15|
|Adult females – increased morbidity|10|20|
|**_Chronic obstructivepulmonary disease(COPD): _**|||
|Adult females – increased mortality|99|485|
|Adult females – increased morbidity|6|15|
|**TOTAL**|140|725|

_Source:_ Staff estimate.

> 14 Based on the mean estimated annual cost.

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_genitalium_ , syphilis and HSV2. Each had unique considerations: Chlamydia and gonorrhea were well known among the target population, thus although they ended up having relatively low prevalence overall, they were useful to include due to their salience in the target population. Trichomonas has the merit of fairly high prevalence (and presumed incidence), although additional complications are introduced by the fact that it is biologically more common among women than men. Mycoplasma genitalium is also a high prevalence STI, but has the drawbacks that it is not well known (many clinicians in this setting are unaware of it), there are no rapid tests for it, and treatment failure rates are not well understood; for these reasons we opted not to condition rewards on this STI, but still measured it for the purposes of increasing statistical analysis power.

For highly reliable measurement of these first four STIs, every four months we collected urine samples from men and vaginal swabs from women (performed by a local nurse after careful explanation and consent—acceptability of swabs did not turn out to be problematic), and conducted assays using nucleic acid amplification tests (NAAT) at the Ifakara Health Institute microbiology lab. The NAAT tests were chosen because of their high sensitivity, but they are also expensive and thus would not normally be possible to do if scaling up the intervention; a more feasible design for scale would be to focus just on a subset of STIs with reliable rapid tests. Use of laboratory-based NAAT testing also required a two to three week period in order to process all of the tests, thus we had to ask participants to return to their village study station to pick-up the tests. Over 90% of participants came back to collect their results three weeks later, even in the Control group; this is likely due to a combination of the fact that this is a population accustomed to research studies, as well as the high level of interest people had in ―knowing their status‖ and rechecking it regularly (for both HIV and STIs). This also had the added benefit that we had another contact with study participants to remind them of the study and also provide individual post-test counseling (pre-test counseling was provided to all at the time of specimen collection). Individuals who tested positive were provided vouchers for themselves and up to five partners for free treatment at the local health clinic, and a system was put into place to ensure that the first and second line medicines were always available in those clinics. A critical point is that each of these four urinebased STIs is curable. Thus enrollees who test positive for an STI can continue to 17
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