rafmacalaba/datause-encoder-data huggingface dataset:
# **Appendix B: Key Country Characteristics**

# **Table B1: Key Country Characteristics**

||Indonesia|Bangla|desh|Sri La|nka|Ethiopia|
|---|---|---|---|---|---|---|
|Population (million)|227.3|143.|9|19.|4|75.9|
|Rural population (% of total population)|51.9%|73.3|%|84.7|%|83.6%|
|Human Development Index|0.572|0.47|8|0.66|2|0.327|
|GDP per capita (current US$)|1,258|475||97|5|200|
|Poverty headcount ratio at rural poverty line|||||||
|(% of rural population)|20%|43.8|%|24.7|%|39.3%|
|Poverty headcount ratio at urban poverty line<br>(% of urban population)|11.7%|28.4|%|7.9|%|35.1%|
|Agriculture, value added (% of GDP)|13.1%|19.2|%|13.2|%|47.9%|
|Social Institutions and Gender Index /<br>OECD<sup>a</sup>|0.128|0.24|5|0.05|9|0.233|
|Gender Inequality Index / UNDP<sup>b</sup>|0.549|0.60|2|0.44|7|-|
||Muslim 86.1%,|Muslim|89.5%,|Buddhist|69.1%,|Orthodox 43.5%,|
|Main religions (% of population)|Protestant 5.7%,|Hindu|9.6%,|Muslim|7.6%,|Muslim 33.9%,|
||Roman Catholic 3%|other 0|.9%|Hindu|7.1%|Protestant 18.6%|
||Female<br>Male|Female|Male|Female|Male|Female<br>Male|
|Life expectancy at birth (years)|68.7<br>65.5|68.1|67.3|77.0|69.5|57.5<br>54.5|
|Literacy rate, adult (% of population ages 15<br>and above)|86.8%<br>94.0%|51.0%|60.7%|89.1%|92.2%|18.0%<br>41.9%|
|Expected years of schooling|11.6<br>12.1|8.3|8.0|12.8|12.4|6.4<br>8.3|
|Labor force participation rate (% of<br>population ages 15-64)|52%<br>87.6%|61%|85.9%|39.5%|81.2%|80.8%<br>91.6%|
|Employees,agriculture(% of employment)|44.3%<br>43.8%|68.1%|41.8%|39.2%|31.6%|74.8%<br>83.2%|

Sources: World Development Indicators, UNDP, OECD, CIA Fact Book Years: Indonesia 2005 (2004 when not available), Bangladesh 2007 (2005 when not available), Sri Lanka 2003 (2002 when not available), Ethiopia 2006 (2005 or closest year when not available) a The SIGI was measured in 102 countries in 2009. It includes 12 indicators on social institutions, which are grouped into 5 categories: Family Code, Physical Integrity, Son Preference, Civil Liberties and Ownership Rights (0=low/no discrimination, 1=high discrimination).

b The Gender Inequality Index was measured in 138 countries in 2010. The index incorporates the following indicators: Labor force participation, educational attainment, parliamentary representation, adolescent fertility and maternal mortality (higher values indicate lower achievement).

51
**Figure 2:** SR over area quintile for 2017 (left) and 2018 (right) wave for Maize (top), Cowpea (middle), Groundnut (bottom)

<!-- Start of picture text --> 1 2 3 4 5 1 2 3 4 5<br>1 2 3 4 5 1 2 3 4 5<br>1 2 3 4 5 1 2 3 4 5<br>500 600<br>400<br>0 200<br>(Kg/Ha) (Kg/Ha) 0<br>−500<br>−200<br>−1000 −400<br>−600<br>6000<br>600<br>5000<br>4000 400<br>3000<br>(Kg/Ha) (Kg/Ha)<br>200<br>2000<br>1000 0<br>0<br>0<br>0<br>−500<br>−1000 −1000<br>(Kg/Ha) (Kg/Ha)<br>−1500<br>−2000<br>−2000<br>−3000 −2500<br><!-- End of picture text --> 27
**Table 48. Importance of IPA services: Efforts to improve the overall business environment in the country**

|VARIABLES|(1)<br>OLS|(2)<br>OLS|(3)<br>OLS|(4)<br>OLS|(5)<br>Ologit|(6)<br>Ologit|(7)<br>Ologit|(8)<br>Ologit|
|---|---|---|---|---|---|---|---|---|
|Services|-0.00663|0.00226|||-0.00976|0.0308|||
||(0.0503)|(0.0493)|||(0.111)|(0.114)|||
|Export % of sales|-0.000190|-0.000414|-0.000350|-0.000552|-0.000675|-0.000505|-0.000893|-0.000669|
||(0.000673)|(0.000663)|(0.000677)|(0.000678)|(0.00149)|(0.00155)|(0.00153)|(0.00161)|
|Share of sourcing via imports|5.88e-05|-0.000103|-0.000140|-0.000289|-0.000124|-0.000689|-0.000375|-0.00101|
||(0.000711)|(0.000718)|(0.000720)|(0.000728)|(0.00159)|(0.00167)|(0.00164)|(0.00173)|
|High-income source country|-0.218***|-0.147**|-0.220***|-0.153**|-0.503***|-0.325*|-0.515***|-0.349*|
||(0.0680)|(0.0696)|(0.0705)|(0.0707)|(0.165)|(0.176)|(0.177)|(0.184)|
|>250 employees|0.00641|0.0179|0.00275|0.0115|0.0142|0.0712|0.0147|0.0614|
||(0.0611)|(0.0619)|(0.0626)|(0.0627)|(0.137)|(0.145)|(0.145)|(0.152)|
|Cumulative inv. >US$10M|-0.00130|0.0654|-0.00391|0.0646|0.0443|0.162|0.0296|0.150|
||(0.0584)|(0.0581)|(0.0578)|(0.0573)|(0.131)|(0.137)|(0.133)|(0.140)|
|Years in country|-0.00139|-0.00279|-0.00126|-0.00292*|-0.00350|-0.00734*|-0.00306|-0.00738*|
||(0.00183)|(0.00177)|(0.00183)|(0.00176)|(0.00396)|(0.00409)|(0.00393)|(0.00403)|
|Level of foreign ownership (%)|-0.00126|0.000407|-0.00110|0.000513|-0.00277|0.00110|-0.00254|0.00130|
||(0.000972)|(0.00100)|(0.000967)|(0.00101)|(0.00233)|(0.00244)|(0.00237)|(0.00252)|
|Country fixed effects||X||X||X||X|
|Subsector fixed effects|||X|X|||X|X|
|Observations|2,424|2,424|2,424|2,424|2,424|2,424|2,424|2,424|
|R-squared|0.013|0.066|0.035|0.089|||||

Standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1

The dependent variable in all models is an ordered categorical variable corresponding to responses to the following question: "How important are the following services offered by Investment Promotion Agencies to your company in this country? Please rate each on a scale from 1 to 4 where 1 is not at all important and 4 is critically important. [Efforts to improve the overall business environment in the country]". Higher numbers denote more greater importance. Subsector fixed effects are at the ISIC A38 level.

Coefficients for constants (for OLS), cut points (for ordered logit), and fixed effects not shown in table.

65
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# 1B | Parameters

Let's fix this set of parameters:

- + Replacementrate— 60 % Riskpremium—2%. Risk-free rate—2 %. Volatility of risky return— 17 % Correlation between income and stockretum shocks -—0.2

- + Riskaversion coefficient—7 Contribution rate—6%

- + Expected life-span in retirement—16 years

- Discountfactor— 2%

- + Income profile > age-dependence +2 % economic growth

<!-- Start of picture text --> Probability to reach determined<br>replacement rate<br>Probability to reach determined repl. rate*<br>oE%<br>oon *replacement rate generated only by Life-cycle fund<br>aes res baled 7%<br>rom ms<br>=”<br>Bon aTh<br>Ba aw<br>ize<br>Ss ak<br>azk<br>2s<br>1s<br>Los ah a<br>is. m Ph<br>mn”<br>Life cycle BO) 33/93 50/50 50/40 FoyPO<br>Strategy<br>@ Replacement rate>35% 8 Replacementrate>45% © Replacement rate> 60%<br><!-- End of picture text -->
# **Table 16. Panel 5 years average, 2SLS estimations.**

||(1)|(2)|(3)|(4)|(5)|
|---|---|---|---|---|---|
||Fixed Effects,<br>2SLS|Fixed Effects,<br>2SLS|Fixed Effects,<br>2SLS|Fixed Effects,<br>2SLS|Fixed Effects,<br>2SLS|
||pcGDPgrowth|pcGDPgrowth|pcGDPgrowth|pcGDPgrowth|pcGDPgrowth|
|Constant|-5.587|-17.221|-7.866|-20.282|-8.576|
||(2.496)**|(6.732)**|(7.535)|(6.758)***|(11.968)|
|GDPpc|-0.000|0.000|-0.000|-0.000|0.004|
||(0.000)**|(0.000)|(0.000)|(0.000)|(0.002)*|
|Invt/gdp|0.143|0.267|0.216|0.043|0.205|
||(0.031)***|(0.070)***|(0.065)***|(0.054)|(0.104)**|
|lifeexpect|0.106|0.239|0.094|0.340|0.071|
||(0.042)**|(0.109)**|(0.124)|(0.106)***|(0.192)|
|m2/gdp|-0.057|-0.040|-0.043|-0.030|-0.081|
||(0.017)***|(0.033)|(0.031)|(0.033)|(0.053)|
|imports/gdp|0.038|-0.070|0.023|0.045|-0.025|
||(0.021)*|(0.050)|(0.039)|(0.039)|(0.076)|
|inflation|-0.001|-0.001|-0.001|-0.001|-0.001|
||(0.000)***|(0.000)***|(0.000)***|(0.000)***|(0.000)**|
|main|-0.002||||-0.082|
||(0.005)||||(0.052)|
|egc||6.211|||38.411|
|||(2.714)**|||(20.499)*|
|rail|||2.650||-11.985|
||||(7.567)||(14.405)|
|pav||||-0.459|-6.015|
|||||(1.889)|(5.749)|
|Observations|362|218|177|202|148|
|Haus test endog<br>p-value|60.17***|38.84***|0.15|13.12|7.28|

Standard errors in parentheses. * significant at 10%; ** significant at 5%; *** significant at 1%. Instruments: Lagged infrastructure, agri/gdp71, population density 71, population 71. Full set of period dummies included.

36
# I. INTRODUCTION

In recent years, foreign banks have achieved an increasingly important role in many developing countries. In Argentina, Chile, the Czech Republic, Hungary, and Poland, foreigncontrolled banks hold over fifty percent of total banking sector assets. Although foreign bank penetration is more modest in other developing countries, including many in Asia, Africa, the Middle East, and the Former Soviet Union, it has increased in most countries over the past decade. While foreign bank entry might improve financial intermediation by increasing competition, improving stability, and enhancing sector efficiency, some observers have suggested that it might also have some adverse effects. Among other things, opponents argue that increased foreign bank penetration in developing countries might reduce access to credit, particularly for small and medium-sized enterprises (SMEs). So far, however, the empirical evidence on this issue has been ambiguous.

Recent cross-country studies find that entry by foreign banks increases both competition and banking sector stability, factors that should benefit all borrowers. Using an 80-country sample of developed and developing countries between 1988 and 1995, Claessens _et al._ (2000) find that entry by foreign banks reduced both the profitability and expenses of domestic banks. In line with these results, Barth _et al_ (2001 c) find that net interest margins and overhead costs were lower in countries with fewer restrictions on entry into banking, whether for foreign or domestic banks. In addition, they also show that major banking crises were less frequent in countries with fewer limitations on foreign bank entry and ownership.' Dages _et al._ (2000) argue that foreign bank penetration does not necessarily threaten financial sector stability by showing that foreign banks in Argentina and Mexico exhibited stronger and less volatile loan growth than 2
Policy Research Working Paper 10861

# **Abstract**

This study examined whether psychosocial stimulation, parental distress, and enrollment in pre- primary education had different associations with early child development outcomes for boys and girls in Pakistan. Using data from a nationally representative phone survey in Pakistan, it assessed these relationships for two cohorts of children— those aged 0–35 months and those aged 36–72 months. The study found that among very young children (0–35 months), lower parental distress and higher psychosocial stimulation were strongly associated with better child development for both boys and girls. Girls were more sensitive to higher levels of parental distress and lower levels of psychosocial stimulation than boys. On average, girls in the sample fared worse compared to boys in their developmental outcomes in the context of low levels of stimulation and high levels of parental distress. Among the older age cohort (36–72 months), lower psychosocial stimulation and higher parental distress were each similarly associated with lower child development outcomes, regardless of child gender. Access to early childhood education was associated with better child development outcomes for both genders. The results confirm existing evidence that early learning opportunities in the first six years of life are important supports for promoting early child development for all children and suggest that girls aged 0–35 months in this sample may be uniquely sensitive to psychosocial stimulation and parental distress.

This paper is a product of the Education Global Practice. 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 ahasan1@worldbank.org. A verified reproducibility package for this paper is available at http://reproducibility.worldbank.org, click **here** for direct access.

<!-- Start of picture text --> TRANSPARENT<br>ANALYSIS<br>G<br>R E<br>N<br>S<br>I P<br>Y E<br>K A<br>C A<br>R P<br>LI R<br>O E<br>O C<br>W R<br>H<br>S<br>P<br><!-- End of picture text --> _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, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
Nicoletti, Giuseppe, Stefano Scarpetta, and Olivier Boylaud. 1999. “Summary Indicators of Product Market Regulation with an Extension to Employment Protection Legislation,” OECD Economics Department Working Paper, No. 226. Paris.

OECD. 2002. Regulatory Policies in OECD Countries: From Interventionism to Regulatory Governance. Paris.

OECD. 2005. OECD Economic Surveys. Brazil. Paris.

OECD. 2007. OECD Economic Surveys. Ukraine. Paris.

Schultze, Charles. 1977. The Private Use of public Interest. Brookings Institution. Washington, DC.

28
The first full PRSP adopted in 2008 and the President’s long-term vision (“ _chemin d’avenir_ ” or "path to the future") envisages the transition to a modernized, industrialized and diversified economy. A number of reforms aimed at achieving this goal have already been completed or are under way. Some positive developments can be recorded, including an acceleration of growth in the non-oil sector, especially in construction and in private services. Nevertheless, the economy remains highly sensitive to the volatility of oil prices and production.<sup>2</sup>

**Table 1:** Key Economic Indicators, 2006-2010

|_(percent of GDP, unless otherwise indicated)_|2006|2007|2008|2009|2010|average<br>2000-2010|
|---|---|---|---|---|---|---|
|**Real sector**|||||||
|Real GDPgrowth(%)|6.2|-1.6|5.6|7.5|8.8|5.0|
|Oil (%)|6.8|-17.2|6.1|16.2|13.8|1.9|
|Non-oil(%)|6.0|6.6|5.4|3.9|6.5|7.3|
|Primary sector|6.4|-11.8|5.9|10.5|11.8|2.4|
|Secondary sector|8.0|9.5|6.6|5.4|6.4|10.8|
|Construction and public works|7.4|10.3|7.6|8.7|8.9|12.8|
|Tertiary sector|5.7|6.6|5.0|5.4|5.8|7.0|
|Transport and telecommunication|6.3|8.3|6.8|6.1|7.1|9.9|
|Commerce|5.9|7.1|6.0|7.5|7.5|9.3|
|Real GDP per capita (USD 2000)|1,197|1,156|1,199|1,265|1,348|1,157|
|Consumer price inflation (%)|4.7|2.6|6.0|4.3|5.0|3.2|
|Nominal GDP(CFAF billion)|4,043|4,023|5,311|4,530|5,947|3,454|
|**External sector**|||||||
|Exports of goods and non-factor services|85.7|76.7|73.3|70.8|84.5|79.7|
|Imports of goods and non-factor services|49.4|53.5|46.7|50.9|50.7|50.0|
|Current account balance|2.1|-7.9|1.2|-8.8|5.1|-0.1|
|**Fiscal sector**|||||||
|Total revenue and grants|44.4|39.5|46.6|29.2|37.5|34.7|
|Oil revenue|37.9|32.1|40.1|20.7|29.6|26.8|
|Non-oil revenue|6.4|7.0|6.1|8.2|7.8|7.6|
|Total expenditure and net lending|27.9|30.0|23.4|24.6|21.5|26.0|
|Current expenditure|18.4|19.6|14.9|13.9|11.4|17.4|
|Capital expenditure|9.4|10.4|8.6|10.7|10.1|8.6|
|Non-oil primary balance (% of non-oil GDP)|-54.2|-59.0|-49.1|-39.1|-34.4|-40.1|
|Overall fiscal balance(commitment basis,incl.grants)|16.5|9.4|23.1|4.6|16.0|8.7|

_Source:_ WB staff calculation based on data from the IMF and the Congolese authorities. n/a = not available.

Social indicators remain low and are not in line with those of other lower middle-income countries. According to cross-country regressions, Congo’s social indicators should be substantially higher given its high GNI per capita. This is illustrated by Figure 1 and Figure 2, showing the under-5 and maternal mortality rate in relation to the GNI per capita. It is obvious that Congo’s performance is similar to that of low-income countries rather than middle-income countries.

> 2 See World Bank (2010c) for a detailed discussion of the risks associated with oil price volatility in the Republic of Congo.

2
their local governments much more room for increasing local taxes and, consequently, to have more revenue to set aside for distribution through participatory budgeting schemes.

<u>Source: Extracts from Souza (2001).</u> Despite the association between budget size and citizens' empowerment, budgets in developing countries are never adequate to provide basic services for marginalized populations. For this reason, such association must be seen in light of the power that citizens have to allocate not total budgets, but their relative increases. Other considerations include seeing the appropriateness of the budget size –both capital and recurrent– relative to short, medium and long term expenditure needs. Citizens may have power to influence budgetary allocations at a specific point in time, but that may create future budgetary commitments that would affect their power to influence future budgetary allocations. This is especially problematic when large capital budgets are allocated with short-term perspectives, disregarding the future recurrent expenditures that such investments would generate. Also, in contexts of high budget constraints, heavy capital investments in one year may preclude other short and long term capital investments. As a result the power of future generations to influence budget allocations may decline. One way to deal with this, which has began to operate in many developing countries –yet imperfectly– is by passing multi-year budgets that push for the alignment of budget costs and benefits in longer –than annual– periods of time.

**_2.2.2. Budget flexibility:_** In addition to size, the flexibility, or portion of the budget over which citizens have power, also determines the capacity of local governments to meet local preferences. If budgets are too rigid, or the portion that citizens can influence is too narrow, then citizens’ are unlikely to choose to engage, because the chances of affecting outcomes will be slim (Gaventa and Valderrama 1999). “Flexibility” refers to two factors in local budgeting:

(i) the level of local governments’ control over non own-source revenues, and (ii) the relationship between capital and current expenditures.

Regarding the first, local control is often constrained by the conditional aid, block grants, and borrowing that reaches local treasuries with specific conditions and predetermined objectives. A high proportion of these revenue sources reduce flexibility for spending according to local preferences, which in turn affects the level of citizen engagement in spending decisions. Concerning the relative amount of capital to current expenditures, citizens –and sometimes local governments– have little capacity to influence this relationship.

Local budgets in developing countries typically have a large component of current spending (mainly wages), which is difficult to reduce in order to increase the capital budget. In Mongolia, for example, research found that the budgets of local governments mostly cover current spending only (mainly wages and goods and services, see Table 1) without reflecting the priorities of capital expenditures (Center of Mongol Management 2005).

16
Table 1 b

# MILITICAL lRY OF THIRfY EIIT SIDIES

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Table C7: Results Pooled: Work Categories - Heterogeneity by Public/Private

||(1)<br>Employee|(2)<br>Apprentice/Intern|(3)<br>Employer|(4)<br>Self-Employed|
|---|---|---|---|---|
|Offered Training|0.00|0.00|0.02|0.05|
||(0.04)|(0.04)|(0.02)|(0.03)|
|Offered * Public|0.05|0.01|-0.03|-0.06|
||(0.05)|(0.04)|(0.02)|(0.04)|
|Control Mean: Public|0.34|0.19|0.03|0.15|
|Control Mean: Private|0.36|0.23|0.03|0.19|
|Observations|2,597|2,597|2,597|2,597|
|p-value public|0.08|0.58|0.20|0.60|

Notes: Offered Training is the coefficient from a pooled OLS regression of the outcome (including three rounds of follow-up data, 4, 10, and 15 months after the end of the program) on an indicator for being offered the training. We control for the baseline value of the dependent variable, stratification dummies and survey wave dummies. Standard errors are clustered at the respondent level.

Table C8: Results Pooled: Job Benefits - Heterogeneity by Public/Private

||(1)<br>Area<br>Studies|(2)<br>Contract<br>Written|(3)<br>Contract<br>Permanent|(4)<br>Job<br>Benefts|(5)<br>Registered<br>Firm|
|---|---|---|---|---|---|
|Offered Training|0.04|-0.01|0.00|-0.03|0.03|
||(0.05)|(0.05)|(0.03)|(0.03)|(0.05)|
|Offered * Public|-0.04|0.07|0.04|0.04|0.04|
||(0.06)|(0.05)|(0.03)|(0.04)|(0.06)|
|Control Mean: Public|0.36|0.30|0.11|0.16|0.39|
|Control Mean: Private|0.47|0.29|0.08|0.14|0.41|
|Observations|2,597|2,597|2,597|2,597|2,597|
|p-value public|0.91|0.04|0.00|0.39|0.01|

Notes: Offered Training is the coefficient from a pooled OLS regression of the outcome (including three rounds of follow-up data, 4, 10, and 15 months after the end of the program) on an indicator for being offered the training. We control for the baseline value of the dependent variable, stratification dummies and survey wave dummies. Standard errors are clustered at the respondent level.

46