rafmacalaba/datause-encoder-data huggingface dataset:
creditors and potential business partners make proper financial judgments. 16 For instance, in many countries commercial banks rely on the information found in the business registry to perform a risk analysis of the business before approaching the company to offer their financial products.

# _b) Legal watchdog:_

The business registry is at the front line in the effort to assure that a business operates transparently and within the bounds of the law. It acts as a guarantor of a solid, legal business environment by fostering transparency thereby aiding in preventing and exposing illegal activities such as money laundering and other financial crimes.

# _c) Policy tool for governments:_

In countries where firms are required to disclose annual financial reports, the registry is a key tool for shaping economic policies.<sup>17</sup> It provides policymakers with a vast amount of information (number of employees, revenue, business strength, etc.) that can be used to better shape economic and labor policies. Moreover, this information can also provide indicators for monitoring and evaluation of public policies, projects, and presidential goals in order to measure their success and impact (see Box 2).

# **Box 2: Business Indicators and Monitoring & Evaluation**

Monitoring and Evaluation (M&E) is becoming a key tool for governments to measure the impact and efficiency of their programs as well as the success of their presidential goals. Nevertheless, to have an autonomous and soundly institutionalized M&E system at the national level, the government must implement a system that can supply a constant flow of pertinent, audited, and accurate information. Therefore, the data collected by government agencies becomes the base to design credible indicators for M&E. In this regard, this study aims to identify a consistent methodology to define indicators for business demography, as well as to show the relation between business creation and economic development. Proving the relation between entrepreneurship and economic development (i.e. the impact of business creation on the reduction of the informal sector, GDP, etc.) highlights the relevance of entrepreneurship as an intermediate component for programs aimed to foster economic development.

The following chart illustrates the role of business demography indicators on a program aimed at poverty reduction. Although the log frame is oversimplified, it displays the different sets of indicators and the logic relation that takes place between the input and the goal, as well as the relevance of indicators for the monitoring and evaluation of the project.

> 16 For cross-country evidence see Berger, Klapper and Udell, 2001.

> 17 The decision to require mandatory public disclosure of financial statements for non-listed companies should be made independent of the potential use of the data for monitoring and benchmarking.  For further discussion, see Gielen, et al. (2006).

10
13 As a second step we computed the value of the inverse of Miils' ratio on the basis of the estimated vector parameters and we proceeded to use standard OLS to estimate the wage equation [8J. The results presented in Table 2 for the four years analyzed show that consideration of the selectivity bias is important in estimating a wage function. This is indicated by the statistical significance of the parameter associated to Ai and by the important change observed in the rest of the parameters when this variable is included in the model. 1 1 Table 2

|||Estim|ated Earning<br>by Selec|Functions Co<br>tivity<br>Bias|rrected|||
|---|---|---|---|---|---|---|---|
||Educ|Exp|Exp<sup>2</sup>|EducExp||Const.|R2|
|1968|.144<br>(30.3)*|.068<br>(15.6)*|<br>-.00086<br>(-13.1)*|<br>-.0011<br>(-4.96)*|-<br>_|-3.28<br>(-50.8)*|.465|
||.18<br>(8.19)*|.11<br> <br>(4.08)*|-.001<br>(-4.08)*|-.0018<br>(-3.84)*|1.10<br>1.74)|-4.35<br>(-7.01)*|.466|
|1977|.154<br>(27.6)*|.067<br>(13.5)*|-.00081<br>(-11.5)*|-.0011<br>(-4.79)*|-<br>-|-2.01<br>(-24.6)*|.431|
||.223<br>(6.07)*|.126<br> <br>(6.42)*|-.0017<br>(-5.92)*|-.0022<br>(-5.26)*|1.30<br>(3.12)*|-3.73<br> <br>(-6.70)*|.44|
|1980|.176<br>(28.0)*|.080<br>(14.3)*|-.0009<br>(-11.6)*|-.0020<br>(-7.17)*|-<br>-|-3.42<br>(-38.3)*|.426|
||.289<br>(9.88,*|.174<br> <br>(7.18)*|-.0022<br>(-6.60)*|-.0044<br>(-6.61)*|1.95<br>(3.98)*|-6.04<br> <br>(-9.09)*|.43|
|1985|.181<br>(26.5)*|.087<br>(14.5)*|-.0010<br>(-12.9)*|-.0017<br>(-5.86)*|-<br>-|-2.96<br>(-29.9)*|.441|
||.52|.390|-.0050|-.0107)|5.13|-11.26|.45|
||(11.3)*|(9.47)*|(-9.27)*|(-8.61)*|(7.43)*|(-10.1)*||

Notes: t - ratios appear in parentheses. * indicates the estimate is significant with a 95? confidence interval.
in the latter case, children are exposed to effects which arise outside the CPBA resulting from increased community support and awareness for school readiness.

|Table 1. Cohorts, intervention exposure, and surveys (excludes CPBA admin. and community data)|
|---|

|<br>**Year**|<br>**2014**|<br>**2015**|<br>**2016**|<br>**2017**|
|---|---|---|---|---|
|**Interventions**||School readiness<br>CLRW grades 1|School readiness<br>CLRW grades 1&2|School readiness<br>CLRW grades 1&2|
|**Surveys**|TEHCI Mar<br>TEGRA Nov||TEGRA Feb & Oct|TEHCI<br>TEGRA Mar & Oct|
|**Cohort born 2014**<br>Intervention<br>Data||Age 0<br>School readiness|Age 1<br>School readiness|Age 2<br>School readiness<br>TECHI|
|**Cohort born 2013**|Age 0|Age 1|Age 2|Age 3|
|Intervention<br>Data||School readiness|School readiness|School readiness<br>TEHCI|
|**Cohort born 2012**<br>Intervention<br>Data|Age 1|Age 2<br>School readiness|Age 3<br>School readiness|Age 4<br>School readiness<br>TEHCI|
|**Cohort born 2011**<br>Intervention<br>Data|Age 2|Age 3<br>School readiness|Age 4<br>School readiness|Age 5, Grade 1<br>CLRW<br>TEGRA|
|**Cohort born 2010**|Age 3|Age 4|Age 5, Grade 1|Age 6, Grade 2|
|Intervention<br>Data|TEHCI|School readiness|CLRW<br>TEGRA|CLRW<br>TEGRA|
|**Cohort born 2009**<br>Intervention<br>Data|Age 4<br>TEHCI|Age 5, Grade 1<br>CLRW|Age 6, Grade 2<br>CLRW<br>TEGRA|Age 7, Grade 3<br>TEGRA Oct.|
|**Cohort born 2008**<br>Intervention<br>Data|Age 5, Grade 1<br>TEHCI / TEGRA|Age 6, Grade 2|Age 7, Grade 3|Age 8, Grade 4|
|**Cohort born 2007**<br>Intervention<br>Data|Age 6, Grade 2<br>TEGRA|Age 7, Grade 3|Age 8, Grade 4|Age 9, Grade 5|

# <u>3. Effect of the school readiness intervention</u>

The school readiness intervention was expected to affect children’s school readiness primarily by improving caregiver-child interaction including through early stimulation in the household. The intervention supported community leaders to establish a CPBA, and if a CPBA was established, it provided training and mentoring to the volunteer facilitators. By participating in CPBAs, caregivers learn new types of interactions that they can do at home with their children that promote school readiness. Children participating in the CPBAs are also exposed to socialization and new learning opportunities. This section presents the effects of the school readiness 11
Policy Research Working Paper 8938

# **Abstract**

This analysis assesses the role of skills, human capital endowment, and migration as determinants of Sub-Saharan Africa’s participation in manufacturing global value chains. Due to lack of reliable data on skilled labor, skilled and unskilled labor contents in exports were generated from the Global Trade Analysis Project database. A panel of 23 countries for which data on skills and manufacturing global value chains are available for 19 subsectors was constructed. A fixed-effect gravity model was used to estimate the determinants of backward and forward global value chain participation. The estimates obtained from the sample are compared with global data covering 115 countries for benchmarking purposes. The results indicate that for economies in Sub-Saharan Africa, skilled labor seems to be the strongest determinant of participation in backward and forward global value chains. Similarly, initial human capital endowment has a strong positive impact on global value chain participation at the global level. However, countries with relatively high initial capital endowment benefit more by incorporating foreign value-added products in their manufacturing exports. Finally, countries that receive net inflows of migrants tend to engage better in backward and forward global value chains than those with net outflows of migrants. The findings suggest that policies to improve Sub-Saharan Africa’s integration in manufacturing global value chains should target: shifting from unskilled to skilled labor-intensive backward and forward global value chain activities; upgrading the quality of the labor force, since unskilled workers are so far the most available and the most used in manufacturing global value chains; investing in the quality of human capital; and promoting intraregional skills mobility.

This paper is a product of the Office of the Chief Economist, Africa Region, commissioned as part of the _‘Industrialization for Jobs in Africa’_ regional study. 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 nyameogo@worldbank.org and kjammeh@worldbank.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, 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
located in a relatively secular country and targets a secular customer segment. Moreover, a moral appeal with no religious association also induced considerably higher repayment rates, while a religious placebo message with no reference to debt repayment did not. This suggests that our results are indeed driven by the moral content of the message, rather than its religious connotation. Still, studying how moral incentives operate in other settings remains a useful avenue for future research.

# **References**

- **Agarwal, Sumit, Paige Martha Skiba, and Jeremy Tobacman** , “Payday Loans and Credit Cards: New Liquidity and Credit Scoring Puzzles,” _American Economic Review_ , 2009, _99_ (2), 412–417.

- **, Souphala Chomsisengphet, Neale Mahoney, and Johannes Stroebel** , “Regulating Consumer Financial Products: Evidence from Credit Cards,” _Quarterly Journal of Economics_ , 2014, _130_ (1), 111–164.

- **Akerlof, George A. and Rachel E. Kranton** , “Economics and Identity,” _Quarterly Journal of Economics_ , 2000, _115_ , 715–753.

- **Andreoni, James** , “Giving with Impure Altruism: applications to Charity and Ricardian Equivalence,” _Journal of Political Economy_ , 1989, _97_ , 1447–1458.

, “Impure Altruism and Donations to Public Goods: A Theory of Warm-Glow Giving,” _The Economic Journal_ , 1990, _100_ , 464–477.

- **Barro, Robert J. and Rachel M. McCleary** , “Religion and Economy,” _Journal of Economic Perspectives_ , 2006, _20_ (1), 49–72.

- **Becker, Sascha O. and Ludger Woessmann** , “Was Weber Wrong? A Human Capital Theory of Protestant Economic History,” _The Quarterly Journal of Economics_ , 2009, _124_ (2), 531–596.

- **B ́enabou, Roland and Jean Tirole** , “Intrinsic and Extrinsic Motivation,” _Review of Economic Studies_ , 2003, _70_ (3), 489–520.

- **and** , “Incentives and Prosocial Behavior,” _American Economic Review_ , 2006, _96_ (5), 1652–

- 1678.

- **, Davide Ticchi, and Andrea Vindigni** , “Forbidden Fruits: The Political Economy of Science, Religion, and Growth,” _Working Paper_ , 2015.

- **Benartzi, Shlomo and Richard H. Thaler** , “Save More Tomorrow: Using Behavioral Economics to Increase Employee Saving,” _Journal of Political Economy_ , 2004, _112_ (1), 1–187.

- **Benjamin, Daniel J., James J. Choi, and Geoffrey W. Fisher** , “Religious Identity and Economic Behavior,” _Forthcoming, Review of Economic and Statistics_ , 2015.

20
Table 3: Trade Policy under the WTO for Selected Economies, 2012

|WTO member economy|MFN|Bind-|Binding|Cov-|Max-|MFN|TTB|
|---|---|---|---|---|---|---|---|
||applied<br>rate,<br>simple<br>average|ing<br>rate,<br>simple<br>average|coverage|erage<br>of<br>ap-<br>plied<br>duties|imum<br>applied<br>rate|applied<br>rate,<br>agricul-<br>ture only|coverage|
|||||><br>15<br>per-<br>cent||||
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|G20 High-income||||||||
|Australia|2.7|10.0|97.1|0.1|28.0|1.2|1.0|
|Canada|4.3|6.9|99.7|6.9|551.0|16.2|1.2|
|European Union|5.5|5.2|100.0|5.1|605.0|13.2|3.0|
|Japan|4.6|5.2|99.7|3.8|692.0|16.6|<0.1|
|Saudi Arabia|5.1|11.3|100.0|0.4|427.0|6.2|NA|
|South Korea|13.3|16.6|94.6|10.4|887.0|52.7|0.5|
|United States|3.4|3.5|100.0|2.7|350.0|4.7|6.8|
|G20 Emerging||||||||
|Argentina|12.5|31.9|100.0|36.0|35.0|10.5|3.2|
|Brazil|13.5|31.4|100.0|36.2|55.0|10.1|1.9|
|China (2011)|9.6|10.0|100.0|14.6|65.0|15.6|1.3|
|India|13.7|48.6|73.8|19.6|150.0|33.5|6.5|
|Indonesia|7.0|37.1|96.6|1.6|150.0|7.9|1.7|
|Mexico|7.8|36.1|100.0|13.8|254.0|21.2|1.1|
|Russia|10.0|7.8|100.0|11.7|292.0|13.3|NA|
|South Africa|7.6|19.0|96.4|20.6|>1000|8.4|0.6|
|Turkey|9.6|28.6|50.3|10.8|225.0|41.2|4.9|
|Developing, other*||||||||
|Bangladesh (2011)|14.4|169.2|15.5|40.1|25.0|17.2|**|
|Burma|5.6|83.4|17.6|5.0|40.0|8.6|**|
|DR of the Congo|NA|96.2|100.0|NA|NA|NA|**|
|Egypt|16.8|36.7|99.4|19.2|>1000|66.7|NA|
|Ethiopia<sup>y </sup>(observer only)|17.3|**|**|50.8|35.0|22.4|**|
|Iran<sup>y </sup>(observer only, 2011)|26.6|**|**|45.7|400.0|30.4|**|
|Nigeria (2011)|11.7|119.1|19.1|39.0|35.0|15.5|**|
|Pakistan|13.5|59.9|98.7|36.1|100.0|15.5|0.3|
|Philippines|6.2|25.7|67.0|3.1|65.0|9.8|0.1|
|Thailand|9.8|27.8|75.0|22.6|142.0|21.8|0.7|
|Vietnam|9.5|11.4|100.0|24.7|135.0|16.1|NA|

Source: tari¤ data taken from WTO, ITC, and UNCTAD (2013) and temporary trade barrier (TTB) data taken from Bown (2014). Notes: parentheses indicate data availability for year other than 2012. *selected other developing countries chosen as those with 2012 populations greater than 50 million. **indicates non-user (or un-reported user) of the policy instrument. NA = not available. G20=Group of 20. y indicates WTO non-member. Columns (1), (2), (5) and (6) are ad valorem rates, and columns (3), (4), and (7) are shares of import products.

122
Improving the literacy of workers and making more information available could help to increase the elasticity of demand with respect to price variables.<sup>34</sup> In recent years, several agencies, in particular the Chilean Superintendence of Pension Fund Administrators ( _Superintendencia de Administradoras de Fondos de Pensiones_ , SAFP) and the Mexican Consar have made efforts to improve the information provided to affiliates by PFAs, and their websites present a vast amount of information that can be easily accessed by affiliates. In Mexico, for instance, the account statement sent by the managers to affiliates compared commissions and rates of return in the industry and it now includes information on the “net rate of return.” For the most part, however, information provided to members is less than adequate across the LAC region and far more can be done in educating workers.

# **IV. The Determinants of Overly Concentrated Pension Fund Portfolios**

Pension fund assets in the LAC countries that implemented DC pillars have grown and continue to grow at a rapid pace, but portfolios remain overly concentrated which can affect rates of return and thus future replacement rates. This section reviews portfolio composition and performance and examines the factors that have led to such portfolio concentration.

# **IV.1. Rapid Asset Growth**

**Figure 8:** Chile: Pension fund assets as a share of GDP, 1981-2005 (percent)

The growth of pension fund **Figure 8:** Chile: Pension fund assets as a share of GDP, assets in LAC has been impressive. In 1981-2005 (percent) Chile, the pioneer reformer in LAC, 70 **57.5** assets managed by pension funds 60 reached almost 58 percent of GDP in 50 2005 (Figure 8). The average for other 40 LAC countries that implemented 30 structural pension reforms has already 20 reached 18 percent of GDP (Figure 9). When OECD countries are considered, 10 **0.9** only 11 out of its 30 members had larger 0 pension assets as shares of GDP in 2005 1980 1985 1990 1995 2000 2005 than the LAC average (Figure 10). At Source: Based on data from FIAP, SAFP, and WDI. least two factors can be related to this asset growth: (a) in some countries, such as El Salvador, coverage has expanded in the 2000s, and (b) contribution rates (as shares of wages). This increasing trend is likely to continue in the foreseeable future and rates of return are expected to be the main driving source of growth.<sup>35</sup> In 2015, assets in the funded pension systems as shares of GDP are projected to reach around 90 percent in Chile, 44 percent in Bolivia, 31 percent in Argentina, 28 percent in Peru, 26 percent in Mexico, 25 percent in Colombia and 13 percent in Uruguay (Palacios 2003).

> 34 See Appendix 4.

> 35 See, for example, Davis (2003) and OECD (2006b).

- 20 -
of students at once, or if they target brighter students, as was “widely believed” according to Hogg (2006, p.18)). On the other hand, abductions may be more likely where abductees are more likely to join the Maoists forces, and so the People’s Army may have disproportionately abducted children from areas which were lagging behind. There are also some surprising figures in the abductions data provided by INSEC, such as a total of only 284 abductions by Maoists in Rolpa during the whole conflict.

Taken together, the results presented in this section give no support to the hypothesis that the Nepalese civil conflict had a negative effect on schooling overall. There is a robust but small positive effect of the intensity of the insurgency on female educational attainment. This effect is not accompanied by an increase in the probability of enrollment in education, suggesting that the positive effect on attainment is driven by a faster progression from one grade to the next rather than an increase in enrollment. There is also suggestive evidence of a small decrease in female primary schooling completion where insurgents were more prone to abductions. Finally, districts controlled by Maoists have tended to experience larger primary schooling gains over the period, for both genders.

# 5.3. Marriage

Table 8 presents results from regressions of the probability of being married by the age of 15, for women interviewed individually in the 2006 DHS, restricting (Columns (2) and (4)) or not (Columns (1) and (3)) the sample to women who were already living in the place where they were interviewed at the start of the conflict. The regressions corresponding to the first two columns consider the impact of overall conflict intensity during 1996-2006 as measured by conflict-related casualties. The regressions in the two last columns further include an interaction term between the treatment cohort indicator and the total number of abductions by Maoists (per 1000 inhabitants).

# Table 8 goes about here

When women are assigned the conflict exposure corresponding to the district in which they are surveyed, irrespective of whether they already lived in the same place in 1996, fighting intensity does not appear to affect the probability of early marriage (Column 1). However, consistent with the idea that restricting the sample to women who have not moved since the beginning of the conflict reduces measurement error, the magnitude of the effect of conflict intensity increases and becomes statistically significant in Column (2). Adding the abductions variable in Column (3) shows a very significant increase in the probability of early marriage due 25
historically observed levels. However, the path from U.S. macropollcy via U.S. agricultural markets does exist and Is the subject of analysis. Note, however, that this path of U.S. macropolicy Impacts on Mexican agricultural markets through Its effect on U.S. agricultural markets. An analysis of the effects of U.S. macropollcy on U.S. agriculture using llnkage variab!es from the FAIRMODEL to the USAGMKTS model is given In Just (1989b). Briefly, Just generates elasticity responses by computing the effects on USAGMKTS variables of one percent changes in base case levels of the following U.S. macropolicy instruments: Treasury bill rate, government expenditure, personai Income tax rate and the federal deficit.

# V The USAGMKTS **Model**

The Jus3t model (1989a) of U.S. agricultural markets, USAGMKTS, Is similar to MEXAGMKT in structure as one would expect given that both models were designed to be complementary components of an interlinKed family of models. However,the USAGMKTS model (and the FAIRMODEL) are quarterly models, whereas MEXAGMKTS Is necessarily annual owing to the weaker data base for Mexico. Thus, USAGMKTS has nine crop supply equations (for feedgrains and soybeans), twelve crop demand equatlons (for feedgrains and soybeans), ten livestock supply equatlons (for cattle, hogs and broilers), nine livestock demand equations (for beef, pork and broiler chicken) and one dollar exchange rate (trade-weighted) equation for a total of 41 equatlons and endogenous varlables. To model the complexity of U.S. agricultural policies, Just defines sixteen exogenous policy variables. To model the effect of macroeconomic policies on U.S. agricultural variables, he needs only five varlables from the FAIRMODEL -- overall GNP deflator, tMirty-day
Policy ReseaRch WoRking PaPeR 4371

# **Abstract**

The post-communist transition to social health insurance in many of the Central and Eastern European and Central Asian countries provides a unique opportunity to try to answer some of the unresolved issues in the debate over the relative merits of social health insurance and taxfinanced health systems. This paper employs a regressionbased generalization of the difference-in-differences method and instrumental variables on panel data from 28 countries for the period 1990-2004. The authors find that, controlling for any concurrent provider payment reforms, adoption of social health insurance increased national health spending and hospital activity rates, but did not lead to better health outcomes. The authors also find that adoption of social health insurance reduced employment in the economy as a whole and increased unemployment, although it did not apparently increase the size of the informal economy.

This paper—a product of the Human Development and Public Services Team, Development Economics Research Group—is part of a larger effort in the department to shed new light on health financing and delivery issues. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The corresponding author may be contacted at awagstaff@worldbank.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, 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