rafmacalaba/datause-encoder-data huggingface dataset:
# **Box 1. Financial inclusion in Turkey** : **Insights from the 2017 Global Findex Survey**

- 69 percent of adults in Turkey have an account, up from 57 percent in 2014.

- 83 percent of men but only 54 percent of women have an account, a gender gap that is roughly three times the average in developing economies.

- 64 percent of adults make or receive digital payments, up from 48 percent in 2014. Part of the increase may reflect the increased use of debit cards, which 39 percent of adults use, up from 24 percent in 2014.

- 23 percent of adults save at a formal financial institution, up from 9 percent in 2014. On average, men are 9 percentage points more likely than women to save.

- 19 percent of unbanked adults cite religious concerns as a reason for not having an account— the same percentage that cites high costs. Just 1 percent of adults report religious concerns as their sole reason for not having an account.

- 72 percent of unbanked women (and 51 percent of unbanked men) indicate that one reason they do not have an account is that one of their family members already has one. In the developing world overall, a quarter of the unbanked cite this reason, with no difference between men and women.

- 89 percent of unbanked women (and 65 percent of unbanked men) are out of the labor force.

- 5 percent of unbanked women are wage‐employed and 6 percent are self‐employed.

- Roughly 15 million unbanked adults in Turkey have mobile phones—including 88 percent of unbanked women—suggesting possible opportunities to increase financial inclusion by moving routine cash payments into accounts.

- About 1 in 10 unbanked women in Turkey—1.3 million women—send or receive domestic remittances in cash or through an over‐the‐counter service. Expanding the reach of mobile remittances could have benefits that go beyond convenience. Research shows that mobile transfers help people survive financial shocks by making it easier to collect money from faraway relatives when times are tough.

- Roughly one in six unbanked women in Turkey saves using semi‐formal methods. If those savings were moved into accounts, up to 2 million unbanked women could join the formal financial system.

- 30 percent of women who have an account still pay utility bills in cash, including 5 million women who have mobile phones. Getting these financially included adults to use their accounts more often would help expand access to financial services.

29
interval, in all possible scenarios, the welfare associated with reforms increases monotonically with �. Hence, without loss of generality, we only consider the case � = �. That is, denoting the reform scenario by tilde, we assume that if reforms crowd in private investments the associated returns are given by In such a case, the private sector ...nds it pro...table to invest if 1 + xi + �� � c, or Notice that, under assumption (4), private and total welfare<sup>7</sup> associated with reform induced private sector’s investments are exactly the same. This means that the private sector participation constraint, and the condition that insures that the private sector’s projects are welfare improving, coincide. This condition can be written as Notice that, when �= 1, by the sole use of reforms the government is able to induce the private sector to ...nance all welfare improving projects at no cost for the society as a whole. Moreover, if � > 1, reforms increase the set of welfare improving projects B. For smaller values of �, a set of valuable projects (those below <u>�</u> ~~R~~<sup>inFigure2a)thatarenot...nancedbytheprivatesector</sup> remains; in the special case of �= 0, no additional project is ...nanced. Figure 2a illustrates how the introduction of reforms changes the private sector’s incentives to invest for di¤erent values of � .

# 3.2 Public sector intervention: Subsidies and public investments

Let us now consider the situation in which the government is willing to use subsidies (guarantees) or public projects to ...ll the ...nancing gap. We start with the subsidies, si, that the government can o¤er to the private sector at a cost csi. Since the government looks at total welfare, and si is a pure transfer from the government to the private sector, the welfare cost of a subsidy si, is si(c � 1),which is equal to the government’s cost of funding. Under such a policy, the private sector ...nds it pro...table to invest if 1 + xi + si � c, or

> 7 Throughout the paper, we assume that the public sector maximizes total returns, that is, the pro...ts and externalities associated with the projects.

6
|**Table**|**17. Credit sou**|**rces**||
|---|---|---|---|
|**Looked for a loan from a:**|**Banked**|**Unbanked**|**Total**|
|**Department stores**|**26.7%**|**48.6%**|**38.5%**|
|**Other**|**16.7%**|**25.7%**|**21.5%**|
|**Commercial bank**|**38.3%**||**17.7%**|
|**Friend**|**3.3%**|**8.6%**|**6.2%**|
|**Credit card**|**8.3%**||**3.8%**|
|**Government**|**1.7%**|**5.7%**|**3.8%**|
|**SOFOL**|**1.7%**|**2.9%**|**2.3%**|
|**Credit union**|**3.3%**|**1.4%**|**2.3%**|
|**Savings bank**||**4.3%**|**2.3%**|
|**Worker funds**|**1.7%**|**1.4%**|**1.5%**|
|**Savings and loan association**||**1.4%**|**0.8%**|
|**NGOs**||**1.4%**|**0.8%**|
|**Moneylender**|**1.7%**||**0.8%**|
|**Source: ENDESFI**||||

# C.  Why don’t the unbanked use banks?

Individuals in the survey who reported that they did not have a bank account were asked why they do not. Most (72%) responded that they had not tried to open an account. As shown in table 18, when these individuals were asked why they had not tried to open an account, 49% replied that they didn’t have enough money and another 11% stated that the minimum balance requirement was too high. Although a recent study has demonstrated that banks in Mexico City tend to locate in censal tracts with high income levels and up market commercial activity, are disproportionately represented in low income areas and practically absent from the “informal” neighborhoods<sup>16</sup> , only 3% of the respondents reported that bank location was a barrier. This is similar to what was found the U.S. Although bank offices have a far wider presence in the U.S. In both countries, _financial access_ to banks was perceived as a much larger barrier than physical access. Unlike in the U.S. where a large percentage of the unbanked say that they do not need a bank account because they don’t have any savings, only 7% of the unbanked in the Mexico City survey stated that they did not need an account. This difference could be due to the wording of the survey or could reflect the absence in Mexico City of institutions, such as check-cashing outlets, that provide convenient payment services for unbanked individuals. Another difference between the responses in Mexico and the U.S. is that almost 9% of Mexicans in the capital city said that they did not trust the banks, a response that was well under 1% in the U.S. Undoubtedly, this reflects the turbulent history of Mexican banks over the past 20 years.

> 16  Ruiz, as cited in Solo et. al, 2003

43
|Water<br>——|SACU|Botswana|Lesotho|Namibia|south<br>|<br>;<br>Africa|Swazlind|Upper<br> Midde<br>Income|Lower<br>Middle<br>Income|Low<br>Income|SeA|
|---|---|---|---|---|---|---|---|---|---|---|
|Access to Improved Water Sources<br>D<br>(% ofpopulation)|78|95|.<br>76|$0|$7|52|93|35|.<br>as|.<br>o4|
|Access to Improved Sanitation<br>;<br>(% ofpopulation)|45|41|a7|30|.<br>a7|5)|.<br>80|72|4]|37|
|Commercial Perception ofWater Service<br>-<br>I<br>(l=worst 7=hest)|59|57|.|.<br>62|57|.|50|48|40|43|
|Households UsingPiped or Well Water as Main Source of<br>a<br>DrinkingWater<br>("ofhouseholds)|s|t.|.|-|8|.|0|8|B|B|

Note: Data used isfront the latest observation available between 1997 and 2603, Source: Estache, Antonio and Anta Goicoechea (2005), “A ‘Research’ Database on Infrastructure Econontic Performance,” Policy Research Paper No. 3643, infrastructure Network, Office ofthe Vice President, June 2008,
- Hardy, Morgan and Gisella Kagy. 2018. “Mind The (Profit) Gap: Why Are Female Enterprise Owners Earning Less than Men?” _AEA Papers and Proceedings_ 108:252–55.

- Heath, Rachel and Seema Jayachandran. 2018. “The Causes and Consequences of Increased Female Education and Labor Force Participation in Developing Countries.” _Oxford Handbook of Women and the Economy_ .

- Hennekam, Sophie and Yuliya Shymko. 2020. “Breadwinner vs caretaker: the pandemic’s potential gender implications for families.” _Blog Entry, LSE Business Review_ .

- ILO. 2018. “Women and Men in the Informal Economy: A Statistical Picture.” _International Labour Organization Report_ .

- Jayachandran, Seema. 2021. “Social Norms as a Barrier to Women’s Employment in Developing Countries.” _IMF Econ Rev_ 69(5):576–595.

- Kugler, Maurice, Mariana Viollaz, Daniel Duque, Isis Gaddis, David Newhouse, Amparo Palacios-Lopez and Michael Weber. 2021. “How Did the COVID-19 Crisis Affect Different Types of Workers in the Developing World?” _World Bank Policy Working Paper_ .

- Liu, Yu, Siqi Wei and Jian Xu. 2021. “COVID-19 and Women-Led Businesses around the World.” _Finance Research Letters_ 43.

- Martinez, Sebastian, Sophie Naudeau and Vitor Pereira. 2017. “Preschool and Child Development under Extreme Poverty : Evidence from a Randomized Experiment in Rural Mozambique.” _World Bank Policy Research Working Paper_ .

- McKenzie, David and Anna Luisa Paffhausen. 2019. “Small firm death in developing countries.” _Review of Economics and Statistics_ 101(4):645–657.

- Morrissey, Taryn W. 2017. “Child care and parent labor force participation: a review of the research literature.” _Review of Economics of the Household_ 15(1):1–24.

- Mu ̃noz Boudet, Ana Mar ́ıa, Patti Petesch, Carolyn Turk and Ang ́elica Thumala. 2013. “On Norms and Agency: Conversations about Gender Equality with Women and Men in 20 Countries.” _World Bank Policy Research Working Paper_ .

- OECD. 2017. “Dare to Share: Germany’s Experience Promoting Equal Partnership in Families.” _OECD Publishing, Paris_ .

- Oreffice, Sonia and Climent Quintana-Domeque. 2021. “Gender inequality in COVID19 times: evidence from UK prolific participants.” _Journal of Demographic Economics_ 87(2):261–287.

- Pettit, Becky and Jennifer Hook. 2005. “The structure of women’s employment in comparative perspective.” _Social Forces_ 84(2):779–801.

- Pierotti, Rachael, Milli Lake and Chlo ́e Lewis. 2018. “Equality on His Terms: Doing and Undoing Gender in Men’s Discussion Groups.” _Gender and Society_ 32(4):540–62.

34
The multilateral development banks also have a comparative advantage in data access— providing a public good function of collecting national data and presenting them with consistent definitions and standards across countries. Open data is a vital tool to democratize access to the information that forms the building block for economic research. The World Bank, and other multilateral development agencies, can work to facilitate knowledge generation in the south through open data, open tools and other such initiatives.

Finally, the World Bank Group and other multilateral development agencies can use their convening power to bring together researchers and policy makers from the developing world to exchange ideas and experiences. This convening power is one important tool in promoting ―south-south‖ learning among countries of the developing world.

# <u>Bibliography</u>

- Acemoglu, Daron, 2003, ―Labor- and Capital-Augmenting Technical Change,‖ _Journal of European Economic Association_ , Vol. 1, pp. 1-37.

- Adams-Kane, J. and J. J. Lim. 2011. ―Growth Poles and Multipolarity,‖ World Bank Policy Research Working Paper Number 5712.  June 2011.

- Aghion, Philippe and P. Howitt, 1992, ―A Model of Growth through Creative Destruction,‖ _Econometrica,_ 60(2): 323-351.

- Aghion, Philippe and Jean Tirole, 1994, "The Management of Innovation", _The Quarterly Journal of Economics_ , vol. 109, n. 4, pp. 1185-1209.

- Amin, Samir (1976), ―Unequal Development: An Essay on the Social Formations of Peripheral Capitalism‖, New York: Monthly Review Press.

- Antunes, António, Tiago Cavalcanti and Anne Villamil, 2007, ―The effect of financial repression and enforcement on entrepreneurship and economic development,‖ _Journal of Monetary Economics_ , Vol. 55, pp. 278-297.

- Azariadis, Costas and John Stachurski, 2005, ―Poverty Traps,‖ in Aghion, Phillipe and Steven Durlauf, eds., _The Handbook of Economic Growth_ , Elsevier.

- Bannerjee, Abhijit V. and Esther Duflo, 2001, _Poor Economics: A Radical Rethinking of the Way to Fight Global Poverty_ , PublicAffairs (Perseus): New York.

- Bourguignon, François and C. Morrisson, 2002, ―Inequality among world citizens,‖ _American Economic Review_ , Vol. 92(4), pp. 727-44.

- Brada, J. C., 1996,  ̳Privatization Is Transition, Or Is It?‘. _Journal of Economic Perspectives_ , 10, (2), 67– 86.

- Bruton, Henry J., 1998, ―A Reconsideration of Import Substitution,‖ _Journal of Economic Literature_ , Vol. 36, June, pp. 903-936.

47
-27-

ratio between domestic and foreign prices (of competing goods). This relation is embodied in the equation: (1) Log(RER) - aM0 + D + /P) .Log(P with the notation PX . price index for exports, PM . price index for imports, P , domestic price level (CPI or GDP deflator),

# RER -P/PM

D , a variable that represents exogenous shocks of demand.

The presumption is that the signs of a and P are positive.

The exogenous shocks to demand D, can originate in the private or the public sector. It is interesting in view of this to examine whether the shocks of the public sector have a greater effect on the domestic price level than rhose of the private sector. A simple method is to check this is to introduce an additional variable in the previous equation which measures the differential effect of the public sector on prices: where G is a variable that measures public expenditures.

A standard measure for the exogenous to total demand is the ratio between domestic expenditures and income (the absorption), which by the National Incnme Accounts is equal to one minus the ratio between the trade surplus and
- 23 -

the arrears and the rescheduling variables<sup>as exogeneous, while these</sup> variables obviously depend upon debt and perhaps upon<sup>the price itself. In</sup> order to overcome these two difficulties (to which one should also add a more technical one which is that the price being smaller<sup>than one hundred, log p</sup> cannot be normally distributad), we have estimated a reduced form equation in which the dependent variable has the logistic form log (p<sup>/100-p), so as to</sup> let the elasticity depend upon the level of<sup>the price. The result comes as</sup> follows:

-0.048 X growth - 0.583 Dummy 87.12

(0.024) (0.288)

*2 u 0.389; pooled equation for 1986.12 and 1987.12<sup>data;</sup> 60 degrees of freedom; X growth: rate of growth of

exports.

According to this equation the elasticity of<sup>the pricw with respect</sup> - to debt (100 p) is 1.509 (with a standard error of<sup>0.305). This indicates</sup> that the debt overhang problem could not be rejected<sup>at the 95 percent level</sup> degree of confidence for these countries in the sample for which the price was **almost** zero (such as Sudan). More generally, Table<sup>1 indicates</sup> the countries for which the debt-overhang problem could not be rejected at various degrees of confidence. At the 90 percent level of<sup>confidence,</sup> only 4 countr-es pass the test.
# **References:**

Bain, Katherine and Norman Hicks (1998) "Building Social Capital and Reaching out to Excluded Groups: The challenge of Partnerships" Poverty Reduction and Economic Management Group, IBRD.

Besley, Timothy (1995) "Nonmarket Institutions for Credit and Risk Sharing in LowIncome Countries," _The Journal of Economic Perspectives,_ Vol. 9, Number 3, Summer 1995.

Case, Anne (1995) "Symposium on Consumption Smoothing in Developing Countries," _The Journal of Economic Perspectives,_ Vol. 9, Number 3, Summer 1995.

Cornia, Giovanni Andrea (1999) "Social Funds in Stabilization and Adjustment Programmes, Research for Action working paper 48, The United Nations University.

De Ferranti, David, Guillermo Perry, Indermit S. Gill and Luis Serven (2000), _Securing our Future in a Global Economy,_ World Bank Latin American and Caribbean Studies Viewpoints, Washington.

Fox, Jonathan, and John Gershman (1999), "Investing In Social Capital? Comparative Lessons from Ten World Bank Rural Development Projects in Mexico and the Philippines," mimeo, UC Santa Cruz.

Gelbach, Jonah B. and Lant Pritchett (1997), "More for the poor is less for the poor: the politics of targeting," Policy research working paper 1799, The World Bank.

Goodman, Margaret, Samuel Morley, Gabriel Siri and Elain Zuckerman (1997) "Social Investment Funds in Latin America: Past Performance and Future Role.

Hicks, Norman and Charles Griffin (1998) "Responding to Social Protection Needs during an Economic Crisis: A Note on Possible Actions for LAC." Mimeo IBRD.

Inter-American Development Bank (1997) Social Invesment Funds in Latin America: Past Performance and Future Role, by Margaet Goodman et al. Evaluation Office, Social Programs and Sustainable Development Deparment, March, Washington, DC.

Isham, Jonathan, Deepa Narayan, and Lant Pritchett (1995), "Does Participation Improve Performance? Establishing Causality with Subjective Data," _World Bank Economic Review_ 9:175-200.

Jalan, Jyotsna and Martin Ravallion (1999) "Estimating the Benefit Incidence of an Antipoverty Program by Propensity Score Matching." mimeo, IBRD.

22
# Capital Allocation in Developing Countries<sup>_∗_</sup>

Joel M. David<sup>_†_</sup> FRB Chicago Ana Paula Cusolito<sup>_‡_</sup> World Bank Venky Venkateswaran<sup>§</sup> NYU Stern/FRB Minneapolis Tatiana Didier<sup>_¶_</sup> World Bank

> _∗_ The views expressed herein are those of the authors and not necessarily those of the Federal Reserve Banks of Chicago or Minneapolis or the Federal Reserve System.

> _†_ joel.david@chi.frb.org.

> _‡_ acusolito@worldbank.org.

> §vvenkate@stern.nyu.edu.

> _¶_ tdidier@worldbank.org.
# **Table 3: Regression Results for Equation (6)**

|**Dep. Variable: Log (Mobile),s- **|**Log (Mobile)199oa**|
|---|---|
|**Variables**||
|**Constant**|**-9.16****<br>**(3.2)b**|
|**Log (Mobile)199o**|**-0.84****<br>**(13.0)**|
|**Log (Urban Population),o**|**0.78****<br>**(6.7)**|
|**Log (Income Per Capita**<br>**(IPC))irn**|**0.78****<br>**(3.0)**|
|**Log (Policy Index)1995**|**1.06****<br>**(2.5)**|
|**Log (IPC1999) **-**Log (IPC1990) **|**2.12****<br>**(4.0)**|
|**Observations**|**99**|
|**R**<sup>**2**</sup>|**.78**|
|**Adjusted R**<sup>**2**</sup>|**.77**|
|**F-Statistic**|**49.8**|

a Minimum mobile subscriptions set to 1 unit in 1990

**b** t-statistics in parentheses; White heteroskedasticity-consistent standard error and covariance estimates

*** *** Significant at .05 or greater by the standard criteria

o (.84) suggests very rapid adjustment toward long-run equilibrium subscription levels in the 1990's. The estimated elasticities for urban population, income per capita and procompetitive policy are positive, large and highly significant (.93, .93 and 1.26, after accounting for the estimated value of 0). Income growth during the 1990's also has a large estimated elasticity (2.12).

Here we see strong evidence of the digital divide: Across countries, long-run equilibrium subscriptions have an approximately unit-elastic relationship with income per capita. This implies a large, persistent gap between high- and low-income countries, at least until the former achieve very high rates of penetration. The urban population result suggests that network economies provide a significant advantage for more urbanized societies. However, the results for the World Bank index and economic growth also suggest that policy matters a great deal. Income growth induces mobile phone expansion with an elasticity greater than two. Although recent studies of economic growth assign increased importance to exogenous shocks (Easterly, et. al., 1993; Easterly, 2000), they continue to find that countries with liberal economic policies enjoy a significant growth advantage.

9
TABLE **2: Female Participation, Employment and Unemployment***

||Argent|ina|Braz|il|Costa R|ica|
|---|---|---|---|---|---|---|
||1988|1997|1989|1995|1989|1995|
|Employed women(%)|37.4|37.1|42.3|46.3|56.7|57.7|
|Salaried|72.6|74.4|59.3|51.8|71.0|71.0|
|Self-employed**|23.5|20.4|36.2|41.7|23.0|20.8|
|Other**|3.9|5.2|4.5|6.5|6.1|8.2|
|Unemployment Rate|6.5|17.4|3.8|9.3|4.4|5.7|
|Overall Participation Rate|40.0|44.9|43.9|51.0|59.3|61.1|
|Out of labor Market (%)|60.0|_55.1_|56.1|49.0|40.7|38.9|

*Employed women is a percentage of women aged 15-70. Unemployment rate corresponds to unemployed women as a percentage of all women participating in the labor markets (ie. employed plus unemployed).

**Self-employed includes domestic Service, and "Other" includes family workers, and non-specified sector. Source: EPH, Argentina; PNAD, Brazil and EHPM, Costa Rica. Figures are author's estimations.

26
able to replicate the findings of Udry (1996) by focusing on a subset of villages that are in close proximity to the areas underlying Udry’s analysis, Akresh cannot recover the same relationships based on the data collected in other parts of the country. This discrepancy highlights the importance of revisiting the body of evidence on the gender gap in sub-Saharan Africa by using nationally-representative data.

Another limitation observed in the second strand of the relevant literature is the disproportionate focus on West Africa. It is important to investigate the extent and correlates of the gender gap in alternative sub-Saharan African settings with different sets of rights and obligations that differently affect the distribution of productive resources across men and women. Finally, in the case of empirical studies that document statistically insignificant differences in agricultural productivity between female-managed and male-managed plots, conditional on plot-level observable and household-level unobservable attributes, the analytical framework is not set up to isolate relative contributions of relevant attributes towards the observed gender gap for the purpose of prioritizing areas for policy interventions.

# 3. MALAWI: AGRICUTURAL PRODUCTIVITY AND GENDER

# 3.1.  THE COUNTRY CONTEXT<sup>13</sup>

Malawi is a small, population-dense, land-locked country in Southern Africa, with 94,080 square kilometers of land. The 2010 mid-year population projection and annual population growth rate stand at 14.5 million persons and 3.25 percent, respectively, and 85 percent of the population reside in rural areas (NSO, 2012). Agriculture is not only the backbone of Malawi’s economy but also an essential part of its social fabric. The sector accounts for 30 percent of the Gross Domestic Product (GDP), and 84 percent of Malawian households own and/or cultivate land<sup>14</sup> . The production system is overwhelmingly rainfed, characterized by limited access to irrigation and diminishing average land holding sizes due to population pressures. The rainfall is unimodal, and maize is the main staple crop, grown by nearly 100 percent of the farming household population.<sup>15</sup> Over the last two decades, agricultural productivity, as measured by maize yields (kilogram/hectare), has been erratic, as shown in Figure 1. The factors that are commonly cited as underlying the agricultural productivity trend include weather variability, declining soil fertility, limited use of improved agricultural technologies and sustainable land management practices, rationed agricultural extension services, market failures, and underdeveloped and poorly maintained infrastructure (World Bank, 2007). The majority of the farming households

> 13 Unless otherwise stated, the statistics reported in Section 3.1 originate from data.worldbank.org/country/Malawi. 14 The GDP contribution of agriculture is for 2011. The estimate of the percentage of Malawian households owning and/or cultivating land is based on the Third Integrated Household Survey (IHS3) data. 15 The estimate is based on the IHS3 data.

7