rafmacalaba/datause-encoder-data huggingface dataset:
**Table A2. Profile of individuals by type of transition, characteristics of initial year in the period**

||**1999**|||**2006**|||
|---|---|---|---|---|---|---|
||stayed poor|escaped poverty|non-poor|stayed poor|escaped poverty|non-poor|
|_Demographics and location:_|||||||
|Household size (number of households members)|4.3|3.8|3.5|4.6|4.1|3.6|
|Household dependency rate (under 14 and over 65 years)|69.5|59.9|46.7|68.4|57.6|45.4|
|Household dependency rate (adults over 65)|5.8|2.5|4.4|3.9|1.2|2.7|
|Household dependency rate (children under 14)|63.7|57.3|42.2|64.5|56.4|42.6|
|Rural|64.1|58.5|42.3|74.2|47.7|48.8|
|_Labor market outcomes (household level):_|||||||
|Household employment rate|74.9|77.2|75.9|71.7|65.7|71.3|
|Household employment rate in agriculture|44.4|37.1|27.5|49.8|29.6|25.7|
|Household employment rate in manufacturing|11.6|11.3|16.2|4.5|5.5|7.1|
|Household employment rate in services|19.0|28.8|32.3|17.5|30.6|38.5|
|_Education - share of household members (15+) with:_|||||||
|Primary education|21.1|11.2|8.9|36.2|18.4|11.1|
|Secondary education|73.0|77.0|67.8|61.5|70.4|66.7|
|Tertiary education|5.9|11.8|23.3|2.3|11.2|22.2|
|_Income sources - share of households receiving:_|||||||
|Pensions|0.5|0.5|0.9|0.4|2.7|0.9|
|Social benefits|2.2|2.6|2.4|15.4|10.3|8.5|
|Wages|31.3|46.7|52.7|44.2|51.6|53.0|
|Remittances|0.1|0.1|0.2|17.9|11.9|26.6|

32
5 ensuring a steady flow of tourists every season. We note that in the data we consider, the expenditures are not spent on media or advertising but on their agents who, in turn, informationally lobby policymakers by informing them on issues that concern them. Since a welfare minded government is receptive to ideas that concern the safety of its citizens, informational lobbying may provide new information by the foreign principal about how they may have improved the security of their island, the resources they have invested in controlling the spread of a disease to their island, the steps they have taken to ensure the safety of U.S. citizens in the event of a natural calamity by building weather-proof shelter or an effective evacuation plan, and the investment they may have undertaken to make their hotels and buildings more able to withstand hurricanes.

Since tourists look up the State Department’s website for information on these and other issues before deciding upon their vacation destination, negative reporting on those accounts can decimate tourism. Lobbying may be directed at providing information to counter or soften any negative information that the State department may otherwise place on their website,<sup>7</sup> or provide positive information on how the government of a destination has undertaken activities to ensure the safety of tourists. This is the primary mechanism by which lobbying may influence tourism. The purpose of this paper is to investigate whether the data shows that this type of lobbying in fact achieves its purpose.

The data set used in the estimation of our empirical model was assembled using reports that FARA requires the U.S. Attorney General to make available to Congress. The report collects information about foreign agents operating within the United States. A foreign agent, in the view of the U.S. Department of Justice, is somebody who (a) engages in political activities or acts in a public relations capacity for a foreign principal, (b) solicits or dispenses anything of value within the United States for a foreign principal, or (c) who represents the interests of a

> 7 For example, despite an occasional incident of terrorist bombings in Delhi, the capital city of India, there has been no overtly negative assessment of the city as a tourist destination on the State Department’s website.  As another example, the government of Kazakhstan very effectively employed Washington lobbyists in 1999 to improve the country's image in the press and the U.S. Congress (See Harper's Magazine "Plenty of Loopholes in New Lobbying Regulations"  2007 <u>http://www.harpers.org/sb-plenty-of-loopholes-1168542976.html)  Recently, the government is</u> reported to have launched another lobbying effort  to provide information counteracting the negative image of the country portrayed by the character Borat in the popular movie "Cultural Learnings of America for Make Benefit Glorious Nation of Kazakhstan (2006)."
**Figure B3: Coefficient of Variance for Under‐five Mortality, Infant Mortality and Maternal Mortality, Rural and Urban, 2000‐2007**

<!-- Start of picture text -->
1.20 Coefficient of<br>variance<br>1.10<br>1.00<br>0.90<br>U5M rural<br>0.80 U5M urban<br>IMR rural<br>0.70<br>IMR urban<br>0.60 MMR rural<br>MMR urban<br>0.50<br>0.40<br>0.30<br>2000 2001 2002 2003 2004 2005 2006 2007<br><!-- End of picture text -->

_Source: DevInfo_ 41
in the mandate, the corporate plan adds some tension between conducting prudent banking and maximizing development impact. DBSA’s target is a return on equity of 5 percent per annum.<sup>14</sup>

# **2.2 Implementing the Mandate**

It is not only necessary to have a clearly delimited mandate, but also to be able to implement it. Therefore, SFIs need to put in place mechanisms to bring mandates into the priorities of the company. Traditional mechanisms include the development of a corporate plan and some type of performance indicators for aligning the business strategy with the mandate of the company.

**Table 2 Main Highlights in Corporate Plans**

|**BDC**|**BancoEstado**|**DBSA**|**Finnvera**|
|---|---|---|---|
|Client Satisfaction|Financial Results|Development Impact|Minimum amount of<br>guarantees and loans|
|Employment Engagement|Client Satisfaction|Sustainability|Minimum lending to<br>startups|
|Efficiency Ratio|Organizational Capacity|Organizational Capability|Minimum lending to<br>growing and<br>internationalizing<br>companies|
|Outstanding BDC Financing|Portfolio||Distribution of lending by<br>risk category (minimum<br>percentage of lending to<br>riskier segments of the<br>market)|
|BDC Consulting Revenue|||Employment creation<br>(typically estimated by the<br>companies)|
|Return on Common Equity|||Minimum ratio between<br>loans and guarantees|
||||Maximum lending to<br>affiliates|
||||ECA objectives|
||||Efficiency cost ratio|
||||Capital adequacy ratio.|

Sources: BDC, BancoEstado, DBSA and Finnvera As shown in Table 2, governments/SFIs have different approaches for implementing the mandates. While the BDC mandate is well defined and the company is focused on the target sector, the performance indicators are more aligned with client satisfaction and efficiency. In DBSA’s case, with a more broadly defined mandate, the performance indicators put more emphasis on aligning DBSA’s business with a more specific mandate. Finnvera’s corporate plan

> 14 South African privately owned commercial banks typically have a 10 percent return as a target,

13
Table 3 shows the 10 poorest communes. Only the commune ID is provided with the associated district in which the commune is located<sup>3</sup> . The second and third columns show the 10 poorest communes in terms of prevalence, while the fourth and fifth columns show the 10 communes with the largest numbers of poor people. The table shows that the poorest by prevalence commune is in Betioky-Atsimo district while by number of poor people, the poorest commune is in Antananarivo district where poverty rate is one of the lowest.

**Table 3: Communes with highest estimated poverty rates**

|**Rank**|**H**|**ighest rate**|||**Highest numbe**|**r**|
|---|---|---|---|---|---|---|
||**Commune Id**|**District**|**Poverty**<br>**rate**|**Commune**<br>**Id**|**District**|**Estimated**<br>**Number of**<br>**poor**|
|Poorest|51827|Betioky-<br>Atsimo|99.2|11104|Antananarivo|132,330|
|2|23510|Ikongo|99.1|11105|Antananarivo|116,006|
|3|23513|Ikongo|99.0|11101|Antananarivo|101,600|
|4|51829|Betioky-<br>Atsimo|99.0|11102|Antananarivo|67,882|
|5|51823|Betioky-<br>Atsimo|98.9|11106|Antananarivo|57,074|
|6|51824|Betioky-<br>Atsimo|98.9|41102|Mahajanga-1|55,586|
|7|51825|Betioky-<br>Atsimo|98.9|51305|Morombe|53,842|
|8|51818|Betioky-<br>Atsimo|98.8|52101|Ambovombe-<br>Androy|51,662|
|9|51821|Betioky-<br>Atsimo|98.8|13107|Miarinarivo|50,751|
|10|51830|Betioky-<br>Atsimo|98.8|61101|Antsiranana-1|47,019|

Source: Authors’ estimations

# Small area stunting maps

In Demographic and Health Surveys (DHS), stunting is measured through the collection of anthropometric data from children under the age of five. Specifically, children's height is measured and compared to standardized growth references, typically provided by the World Health Organization (WHO) Child Growth Standards. Stunting is assessed by calculating the height-for-age z-score (HAZ) for each child, which quantifies how many standard deviations their height deviates from the median height of a healthy reference population. Children with a HAZ score of less than -2 are classified as stunted, indicating that their height falls significantly below the expected average for their age. The 2021 DHS in Madagascar uses this data to monitor and assess the prevalence and severity of stunting in different countries, providing valuable insights for public health interventions and policy planning.

3 We deliberately kept the names of the communes anonymous.

11 | P a g e
(2010).<sup>74</sup> On the destination side,<sup>75</sup> we find that higher DFD decreases the relative volume of bilateral exports in financially vulnerable sectors in columns (10)-(12). This result strongly contrasts with the positive effect of higher DFD on relative bilateral FDI in financially vulnerable sectors that we have consistently found. The diametrically different responses of FDI and exports to higher DFD suggest that the latter encourages firms to substitute (presumably horizontal) FDI for exports.<sup>76</sup> This is likely because higher DFD allows more firms in a given sector to satisfy the greater need for external finance that engaging in FDI requires relative to exporting. Hence, in a roundabout way, we find again that the external funds raised in host countries complement the external funds raised in the source country rather than being substitutes. In doing so, they influence the

# **6 Conclusion**

This paper sought to improve our understanding of the effects of financial development in source and destination countries on foreign direct investment (FDI). We investigated the existence and relative strength of the various effects of source countries’ financial development (SFD) and destination countries’ financial development (DFD) by employing a difference-in-differences approach where we exploited differences in financial vulnerability across sectors to assert the causal impacts of financial development on FDI. For this purpose, we used unique sector-specific bilateral data on greenfield FDI between a large number of source and destination countries during the 2003-2006 period.

Our empirical results unambiguously indicate that a sophisticated and well-functioning financial system in both source and destination countries is a key determinant of FDI at the extensive and intensive margins,

> 74They argue that financial constraints matter more for FDI than for exporting because engaging in FDI involves higher fixed costs and a larger scale of production. A corollary is that firms are more likely to choose exporting over engaging in FDI in presence of tight

> 75The destination side of exports has frequently been understudied in past research on financial development and international trade. For example, DFD is ignored by Beck (2002, 2003). Manova (2013) focuses on SFD but reports in a footnote that DFD has positive but small effects on exports.

> 76This indication that greenfield FDI in our database is mostly horizontal fits with the negative competition effect that we have uncovered at the intensive margin of greenfield FDI.

39
- González, R. M., Marrero, G. A., Rodríguez-López, J., & Marrero, Á. S. (2019). Analyzing CO2 emissions from passenger cars in Europe: A dynamic panel data approach. _Energy Policy_ , _129_ , 1271–1281. https://doi.org/10.1016/j.enpol.2019.03.031

- Hang, Y., Wang, Q., Zhou, D., & Zhang, L. (2019). Factors influencing the progress in decoupling economic growth from carbon dioxide emissions in China’s manufacturing industry. _Resources, Conservation and Recycling_ , _146_ , 77–88. https://doi.org/10.1016/J.RESCONREC.2019.03.034

- Huang, Y., Zhu, H., & Zhang, Z. (2020). The heterogeneous effect of driving factors on carbon emission intensity in the Chinese transport sector: Evidence from dynamic panel quantile regression. _Science of The Total Environment_ , _727_ , 138578. https://doi.org/10.1016/J.SCITOTENV.2020.138578

- Huo, T., Ma, Y., Yu, T., Cai, W., Liu, B., & Ren, H. (2021). Decoupling and decomposition analysis of residential building carbon emissions from residential income: Evidence from the provincial level in China. _Environmental Impact Assessment Review_ , _86_ , 106487. https://doi.org/10.1016/J.EIAR.2020.106487

IEA. (2020). _Energy Technology Perspectives 2020_ . www.iea.org/t&c/

- IPCC, Edenhofer, O., Sokona, Y., Minx, J. C., Farahani, E., Kadner, S., Seyboth, K., Adler, A., Baum, I., Brunner, S., Kriemann, B., Savolainen Web Manager Steffen Schlömer, J., von Stechow, C., & Zwickel Senior Scientist, T. (2014). _Climate Change 2014 Mitigation of Climate Change Working Group III Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change_ . Cambridge University Press. www.cambridge.org

- Jiang, X.-T., Dong, J.-F., Wang, X.-M., & Li, R.-R. (2016). The Multilevel Index Decomposition of EnergyRelated Carbon Emission and Its Decoupling with Economic Growth in USA. _Sustainability 2016, Vol. 8, Page 857_ , _8_ (9), 857. https://doi.org/10.3390/SU8090857

- JJ Jiang, B. Y. D. X. J. T. (2017). Provincial-level carbon emission drivers and emission reduction strategies in China: combining multi-layer LMDI decomposition with hierarchical clustering. _J Clean Prod_ , _169_ , 178–190. https://doi.org/10.1016/j.jclepro.2017.03.189

- Kim, S. (2019). Decomposition Analysis of Greenhouse Gas Emissions in Korea’s Transportation Sector. _Sustainability_ , _11_ (7), 1986. https://doi.org/10.3390/su11071986

Kwon, T. H. (2005). Decomposition of factors determining the trend of CO2 emissions from car travel in Great Britain (1970-2000). _Ecological Economics_ , _53_ (2), 261–275. https://doi.org/10.1016/j.ecolecon.2004.06.028

- Lakshmanan, T. R., & Han, X. (1997). Factors underlying transportation CO2 emissions in the U.S.A.: A decomposition analysis. _Transportation Research Part D: Transport and Environment_ , _2_ (1), 1–15. https://doi.org/10.1016/S1361-9209(96)00011-9

- Li, A., Zhang, A., Zhou, Y., & Yao, X. (2017). Decomposition analysis of factors affecting carbon dioxide emissions across provinces in China. _Journal of Cleaner Production_ , _141_ , 1428–1444. https://doi.org/10.1016/J.JCLEPRO.2016.09.206

18
# Mapping Returns of Private Equity Investments in Emerging Markets<sup>*</sup>

Florian M ̈olders<sup>†</sup> Edgar Salgado<sup>‡</sup>

**JEL Classification** : F21, G24, G32, O16

**Keywords** : equity markets, private equity, private sector development, venture capital

*We thank Kostas Kollias, Susan Lund, Paolo Mauro, Cesaire Meh, Tristan Reed, and the IFC Economics BBL Series participants for comments and suggestions. The authors would like to thank Soumya Agrawal for her invaluable assistance in ensuring data accuracy. The views expressed in this paper are those of the authors and do not necessarily represent those of the World Bank Group. All results have been reviewed to ensure that no confidential information is disclosed.

> †International Finance Corporation, email: fmoelders@ifc.org, corresponding author.

> ‡International Finance Corporation, email: esalgadochavez@ifc.org
Policy Research Working Paper 10853

# **Abstract**

Financial sector reforms are part of the strategies that countries follow to exit from fragility, but the content and focus of these reforms and the priority they are given relative to other policies vary from country to country. Based on an archival search of publicly available World Bank and the International Monetary Fund country documents, this paper investigates and compares the experiences of seven countries (Armenia, Benin, Cambodia, the Dominican Republic, Rwanda, Senegal, and Viet Nam) that successfully and sustainably exited fragility during the 1980s and 1990s, focusing on the financial sector reforms that were implemented around the time of the exit. The review suggests a few broad patterns. Regardless of the original causes of fragility, successful exit strategies always included financial sector reforms, which invariably focused on short-term goals: stopping bank losses, establishing monetary control, and re-starting the engine of financial intermediation and the flow of credit to the economy. Longer-term financial development goals, such as financial deepening, were recognized as important, but the requisite policy interventions came later, after the financial sector had been restored to health and was able to discharge its basic functions. Crucially, substantial, hands-on, long-term technical assistance and capacity building were in all cases necessary to ensure the long-term success of these reforms.

This paper is a product of the Finance, Competitiveness and Innovation 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 pcalice@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
Policy Research Working Paper 7577

# **Abstract**

This study investigates the existence of political rents in bank lending, using a comprehensive loan-level data set of the universe of commercial loans in Mexico from 2003 to 2012. Identification relies on changes in the state of origin of a senate committee chairman as a source of exogenous variation in firms’ political relationship. The study finds that banks offer favorable loan terms to politically connected firms with larger loan quantities, lower loan spreads, longer maturities, and lower collateral requirements. Furthermore, political loans exhibit higher default rates. To isolate the bank supply channel, a rich set of fixed-effects is included with various specifications. The favorable lending increases with the strength of a firm’s political connection, varies gradually along the political cycle, and is mainly offered by large and domestic banks. Consistent with the quid pro quo hypothesis, the study finds that banks that extend political loans receive significantly more government borrowings with better credit quality. The study also shows that the greater credit supply due to political connection leads to a large and significant increase in firm-level employment and assets. The study provides estimates of the total social cost of political lending and net revenue for banks that are engaged in rent - provision activity. Finally, a series of robustness tests are per formed to rule out alternative mechanisms and explanations.

This paper is a product of the Finance and Private Sector Development Team, Development Research Group. 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://econ.worldbank.org. The authors may be contacted at cruizortega@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
evidence from administrative data shared by the Project Management Implementation Unit (PMIU) of the Punjab Education Sector Reform Project (PERSP). Lastly, I use data from the nationally representative cross-sectional household survey – the 2004-2005 Pakistan Social and Living Standards Measurement Survey (PSLM) to support some of the assumptions made in the empirical analyses that follow.

# **V. Evidence of program impact on child enrollment**

The main question this paper seeks to answer is how the stipend causes time allocation in recipient households to change. In order for any changes to be attributable to the stipend program, the program must be having an effect on girls’ enrollment to begin with. The LEAPS household surveys did not ask respondents to report the grade in which they were enrolled at baseline.<sup>7</sup> This is problematic because in the absence of a self-report imputing the grade at baseline would necessitate making a very particular set of assumptions. For instance, one might assume that education in Pakistan begins at age six. Then, assuming further that there is no grade repetition or dropout everyone who began school at this age should be in grade six by age twelve, grade seven by age thirteen and grade eight by age fourteen. Neither of these assumptions is very plausible given what is known about educational trajectories of children from developing countries in general and Pakistan in particular. Similarly, if I were to subtract the number of years since baseline from the grade reported in subsequent rounds, I would be forced to assume that no one dropped out and that no one repeated a grade. Both of these

> 7 It is important to remember throughout this paper that the LEAPS survey was not fielded to evaluate the stipend program. Thus there are some limitations in the data that necessitate particular (some might say peculiar) assumptions as the analysis progresses. To the extent possible I will justify the choices using evidence from the PSLM data. The program seeks to increase enrollment in grades 6-8 for girls in public schools.

8