rafmacalaba/datause-encoder-data huggingface dataset:
In order to test these ideas, we take the results of the Gauri and Brinks investigation – a list of cases for each of the five countries in the areas of health and education, plus an estimate of the number of people directly and indirectly benefited by this litigation – and extend the analysis with detailed estimates of the share of benefits going to disadvantaged classes in each of those countries. Where better data are available, we clarify and correct their estimates. All the data on which we rely are systematized and presented in a data Appendix, which is available from the authors. Since the boundaries of the ―disadvantaged‖ category are not entirely clear, and since the data in a few cases do not allow us to use the same definition of ―disadvantaged‖ across different countries, we estimate the potential pro-poor impact of litigation by examining whether the poor, defined in nearly all cases as those in the bottom two income quartiles, are over- or under-represented among the beneficiaries of litigation relative to their share of the population. Finally, we use these estimates to test our hypotheses regarding the pro-poor or anti-poor potential of different courts and different streams of social and economic rights litigation.

Overall, we find that the impact of courts varies considerably across our cases, but is very much pro-poor in two of the five countries – India and South Africa. By our measure, it is close to distribution-neutral in Indonesia and in Brazil, raising a counterpoint to the literature‘s findings about the regressive effect of health rights litigation in that latter country. And it is sharply anti-poor in Nigeria. To summarize the argument and findings, we predict, and find, that countries and policy areas characterized by judicial decisions with broader applicability beyond the litigants tend to avoid the presumed anti-poor bias of courts, while areas dominated by individual litigation and individualized effects are less likely to have pro-poor outcomes. Even where results in fact generalize beyond litigants, we find that the more a system relies on litigation that is _expected_ to have only individual effects, the more that litigation will center on 7
Bentham, J., P. Schofield, C. Pease-Watkin, and C. Blamires. 2002. _Rights,_ _Representation, and Reform: Nonsense Upon Stilts and Other Writings on the French Revolution_ : Oxford University Press, USA.

- Boerma, J. T., and Macro Systems. Institute for Resource Development. Demographic and Health Surveys. 1990. _Immunization : Levels, Trends, and Differentials_ , _Demographic and Health Surveys Comparative Studies ;_ . Columbia, Md., USA: Institute for Resource Development/Macro Systems.

- Collier, Paul. 2007. _The Bottom Billion : Why the Poorest Countries Are Failing and What Can Be Done About It_ . New York: Oxford University Press.

- Desai, Sonalde, and Soumya Alva. 1998. Maternal Education and Child Health : Is There a Strong Causal Relationship? _Demography_ 35(1): 71-81.

- Ehreth, J. 2003. The Global Value of Vaccination. _Vaccine_ 21(7-8): 596-600.

- Gage-Brandon, Anastasia J., A. Elisabeth Sommerfelt, and Andrea L. Piani. 1997. Household Structure and Childhood Immunication in Niger and Nigeria. _Demography_ 34(2): 295-309.

- Gauri, Varun, and Daniel M. Brinks. 2008. _Courting Social Justice: Judicial Enforcement of Social and Economic Rights in the Developing World_ . New York:: Cambridge University Press.

- ———. 2008. Introduction: The Elements of Legalization and the Triangular Shape of Social and Economic Rights. In _Courting Social Justice: Judicial Enforcement of Social and Economic Rights in the Developing World_ , edited by Varun Gauri and Daniel M. Brinks. New York: Cambridge University Press.

- Gauri, Varun, and Peyvand Khaleghian. 2002. Immunization in Developing Countries: Its Political and Institutional Determinants. _World Development_ 30(12): 2109-32.

- ———. 2002. Immunization in Developing Countries: Its Political and Organizational Determinants. _World Development_ 30(12): 2109-32.

- Goodliffe, J., and D. G. Hawkins. 2008. Explaining Commitment: States and the Convention against Torture. _The Journal of Politics_ 68(02): 358-71.

- Hafner-Burton, Emilie M.; Tsutsui, Kiyoteru. 2007. Justice Lost! The Failure of

- International Human Rights Law to Matter Where Needed Most. _Journal of Peace Research_ 44(4): 407-25.

- Hathaway, Oona A. 2002. Do Human Rights Treaties Make a Difference? _Yale Law Journal_ 111(8): 1935-2042.

- Helfer, Laurence R. 2002. Overlegalizing Human Rights: International Relations Theory and the Commonwealth Caribbean Backlash against Human Rights Regimes. _Columbia Law Review_ 102(7): 1832-909.

- La Porta, Rafael, Florencio Lopez-De-Silanes, Andrei Shleifer, and Robert W. Vishny. 1997. Legal Determinants of External Finance. _Journal of finance_ 52(3): 1131-50.

- LeBlanc, Lawrence J. 1995. _The Convention on the Rights of the Child : United Nations Lawmaking on Human Rights_ , _Human Rights in International Perspective ;_ . Lincoln: University of Nebraska Press.

- Mahoney, R. T., S. Ramachandran, and Z. Y. Xu. 2000. The Introduction of New Vaccines into Developing Countries Ii. Vaccine Financing. _Vaccine_ 18(24): 262535.

- Moravcsik, Andrew. 1997. Taking Preferences Seriously: A Liberal Theory of International Politics. _International Organization_ 51: 513.

25
management quality: in general “they rely on their low cost advantage and mass production mode as their main competitive advantage instead of product innovation and quality of products and services.” Arguably Chinese managers are very astute in terms of very short run assembly line management, but without vision or plans for long technological advancement.<sup>13</sup>

# **4 What Factors Are Correlated with Managerial Performance Across the Convergence Path?**

## **4.1 Explanatory Variables**

The available data is a single cross section. The available covariates can be divided broadly into 3 categories: Human capital, firm characteristics, and firm ownership structure.

_Human Capital_

1. Manager studied abroad?

2. Manager has a degree?

3. Share of managers with a college degree.

4. Share of employees with a college degree.

_Firm Core Characteristics_

1. Multinational?: Indicator.

### 2. Firm Size: Number of reported employees.

> 13In addition, he finds relatively low acceptance of the importance of HR policy. In a survey of selfreported important practices of 30 top performing firms, only 15 reported detailed accounting of HR policy, five only mentioned it briefly, and 10 not at all. More generally, performance management often is based more on morality, political attitudes, seniority and maintenance of harmonious relations with colleagues than on productivity related performance. Cooke also offers an explanation for the relatively poor performance of the best firms which found resonance in our interviews in China in the fact that senior managers in SOEs are normally appointed by higher-level authorities and hence “These managers thus tend to be more preoccupied with their political performance than the financial performance of their enterprises.” Hence, it is possible that many ex state owned firms,while among the most established and relatively well run, still respond to non-profit oriented incentives. Recruitment and promotion in Ex SOEs and joint ventures in the automobile industry also seem dominated more by patronage decisions than those related to maximizing shareholder return.

12
an integral part of geographically-targeted poverty reduction strategies. Our review shows that capacity development is integral to improving productivity, stronger and equitable forest and land rights strengthen agency, and without effective public institutions and services, the poor cannot be expected to use their access to forest resources to escape poverty. Of course, communities have demands that go beyond income and the non-cash contributions of forests can be very important.<sup>26</sup> Our focus on gender analyses also points to the importance of understanding the implications of rural development strategies for women and men.

While the role forests play in enhancing rural resilience and food security is not fully addressed in this paper, social and environmental safeguards will certainly need to go hand in hand with any forest interventions that seek to reduce poverty. The FAO, CIFOR, IFRI and the WBG recently launched a global effort to develop a standard survey instrument, the Forestry Living Standards Measurement Survey, to measure forest use and the wellbeing of forest-dependent communities (FAO _et al_ ., 2016). Combining such field-based surveys with participatory gender-disaggregated information and satellite data may ensure that forest sustainability and poverty are simultaneously monitored.

Over time, poverty reduction in forest areas will likely be no different than what is seen in agricultural areas: ‘off-forest’ jobs and migration (Hecht _et al._ 2016) will play a significant role in changing the relationship between forests and people. We see this in trends in forest villages in middle-income countries such as Turkey and Albania (World Bank 2016b, IOM 2016). Thus, strategies that enable communities to seek these jobs while simultaneously strengthening their ability to benefit from forest resources in a sustainable manner will be key.

22
- 13 -

# 3. The Economic Environment for V.C. Development

Different surveys and studies about V.C. suggest that local and national governments can play important roles in creating the right conditions for V.C. development in promoting V.C. activities. Indeed millions of company foundations occur in the world every day despite recession, irnflation, high interest --ates, economic uncertainties and fear of failure. The fact that they occur "in spite of" such obstacles should not preclude governments from taking every possible action to remove the obstacles. The governments can contribute not only by improving the macroeconomic environment but also by providing infrastructure, by improving educational attitudes towards risk and entrepreneurship, by improving information, and by providing and promoting the availability of venture capital sources.

# 3.1. "Cultural" Environment

The single most important feature a government has to look over in promoting venture capital is the general positive attitude towards entrepreneurs and private enterprise. Venture activities have today a strong ideological appeal. In recent years throughout much of the developed world and also in many of the developing nations, government intervention in industry has come to be regarded as less desirable. These practical and philosophical attract.Lons have induced a number of countries to try to replicate the United States venture capital model. In Japan and the U.K., to mention just two countries, these attempts have resulted in venttre capital activity on a substantial scale. However, ideology alone is not enough and, in many other countries, a host of policies and regulations militate against private enterprise, particular SMEs: e.g., high wealth and income taxes, endless licensing and permits necessary to operate a business, high entrance barriers to some branches of industry, and, worst of all, an overall negative attitude towards rapidly earned wealth. In such environment the nationa'l talent tends to seek safety and prestige through employment in government or large corporations, through academia or in well respected professions, or else emigrate to a more "accepting" environment. Government can actively promote the conditions of the operation of venture capital, and V.C. can, in turn, be instrumental in providing opportunities to the national talent and reinforce positive attitudes towards entrepreneurism.

# 3.2 Financial and Non-Financial Support to Small Business

Many times the reference to "assistance to SMEs" is misunderstood as a subsidized way of maintaining inefficient operations under a "social" justification. In the context of this paper, assistance to SMEs should be understood as supporting the entrance of newcomers into new fields or into profitabie
# **1 Introduction**

Changes in energy prices are usually thought to have implications for the competitiveness of economies. Policies leading to higher energy prices therefore tend to be subjected to close scrutiny and much debate. Prominent examples include climate change policies such as environmental taxes and cap and trade systems. There are concerns that these policies, when unilaterally enforced, could hinder the ability of domestic industry to compete in export markets, especially in the short term and for energy-intensive sectors. Through their effects on energy prices, they may even induce firms to shift production to countries where emission constraints are less stringent, a response that may lead to an increase in global carbon emissions – the so-called carbon leakage effect. Another policy that may lead to unintended consequences for trade through energy price adjustments is energy crosssubsidization. Many countries, especially in Eastern Europe and South Asia, impose higher energy tariffs on industry to support lower rates for residential or agricultural consumers. Energy cross-subsidies may therefore hamper the international competitiveness of industries, although this has received little attention in the discussion on the economic incidence of energy subsidies.

In this paper, we examine the effect of energy costs on manufacturing exports.<sup>1</sup> Most studies in the literature have used direct energy consumption (energy consumption at the final stage of production) and domestic energy prices to compute energy costs faced by domestic industries. We contribute to the literature by considering both direct and indirect energy costs (energy consumption at intermediate stages of production). Taking into account indirect energy costs is important because even if a sector is not energy intensive on the basis of direct energy consumption, it may still be vulnerable to energy price shocks if it uses energy-intensive intermediate inputs. Furthermore, a sector that uses imported intermediate goods may also be indirectly affected by energy price changes in the origin countries.

Our paper relates to two strands of empirical literature. One strand consists of a small number of recent studies that analyze the relationship between energy prices and international trade using econometric techniques. For example, Aldy and Pizer (2015) use historical electricity price data for the United States to investigate how production and net imports

> 1Changes in energy prices could also affect transport costs, which in turn has implications for international trade flows (Bridgman, 2008; Chen and Hsu, 2012). Analysis on this aspect is beyond the scope of this paper.

2
- 13 -

**_Enforcement through Supervision/Regulatory Forbearance._** The Banlk of Thailand had inadequate powers to intervene and close weak and insolvent institutions. This severely curtailed enforcement of the prudential regulatory framework as the ultimate sanction for non-compliance-intervention and closure of an institution--was not a credible threat. Enforcement actions were also hampered by the fact that the authority to license banks lay with the Ministry of Finance while the BoT was the supervisory authority. Any action related to the withdrawal of a license thus needed to be approved and coordinated with the Ministry of Finance. And finally, banks closure had been a very rare occurrence in Thailand. The last time supervisors forced a bank to close its door was in 1965.

# **c. Performance and Condition of Financial Institutions**

Table 3 summarizes selected performance indicators for cormmercial banks and finance companies prior to financial sector liberalization and the opening of the capital account. As the table shows, the financial sector was still recovering from the 1983-87 crisis as reflected in relatively weak returns on assets and equity. Since financial institutions were subject to lenient interest accrual norms-they were allowed to accrue interest for up to 12 month (6 months) for secured (unsecured) loans-these performance indicators most probably overstate profits. Moreover, the financial sector continued to experience portfolio problems as mirrored in a relatively high ratio of nonperforming loans to total loans which amounted to 7 percent for commercial. Similarly, a number of finance companies and several banks were still supported by the BoT via various measures.<sup>2 2</sup>

**Table 3. Performance Indicators of Commercial Banks and Finance Companies** (%)

||**Commerc**|**ial Banks**|**Fin**|**cos**|
|---|---|---|---|---|
||**1987**|**1988**|**1987**|**1988**|
|**ROAE**|14.5|15.5|9.25|8.537|
|**ROAA**|**0.8**|**0.9**|**0.51**|0.7|
|**NPL/ Total Loans**|7||||
|**Provision for Loan**|0.7|0.8|||
|**losses/Total Loans**|||||
|**Capital/Asset Ratio**|5.6|5.9|||
|**Loan/Deposit Ratio**|**96.2**|**94.2**|**116.6**|115.7|
|_Source:_World Bank 1990.|||||

**22** The **World Bank (1990).**
Todd and Wolpin (2006) use an _ex ante_ model to generate child schooling estimates that compare reasonably well with experimental results. For children aged 12-15 years, the model predicts the effects of _PROGRESA_ on school enrollments to be in the same direction as experimental results, but underestimates them by 21-25 percent. However, when the sample is disaggregated into age groups of 12-13 years and 14-15 years, the results compare less well, particularly among boys. The _ex ante_ model does not predict any change in outcomes for boys aged 12-13 years and significantly overestimates the effects of the program for the 14-15 years age group. Todd and Wolpin also use a particular sample that is not comparable with the one used by Skoufias and Parker (2001) and Schultz (2000) to generate _ex post_ results. They restrict their sample of analysis from the original 24,077 households surveyed under _PROGRESA_ to only landless households where the spouse of the household head is a woman under 50 years of age, reducing their data sample to 3,401 households (and then by 209 more due to data problems).

Attanasio et al (2005) present a complex model to simulate _ex ante_ the likely effects of _PROGRESA_ , as well as that of a hypothetical program that differs from _PROGRESA_ in the way the transfers vary by the grade attended by the child. They do not compare the results of the first exercise with _ex post_ results and instead only present the _ex ante_ program impacts for different age groups. According to our computations using their estimates, the change in enrollment due to _PROGRESA_ predicted by their model translates to enrollment increases of approximately 2 and 5.4 percent among children of age 10-13 years and 14-17 years respectively.<sup>3</sup> In comparison, the enrollment increases attributed to _PROGRESA_ – as estimated by the _ex post_ evaluations of Skoufias and Parker (2001) and Schultz (2000) – are 2.4 and 7.5 percent for children of age 10-13 years and 14-17 years, respectively. The Attanasio et al model is thus able to generate predictions that match up quite well with _ex post_ evaluation results, even as its complexity and challenges of implementation are considerable.<sup>4</sup> Leite (2007) applies the BFL model to data from PNAD ( _Pesquisa Nacional por Amostra de Domicílios_ ) 1999 in Brazil to forecast an increase of 3.9 percent in the enrollment rate of poor

> 3 Our computations involve extrapolating from the enrollment difference presented in Figure 1 of Attanasio et al (2005), by assigning weights to each age group in Figure 1 and using the baseline survey. 4 These authors also propose the use of a structural model to analyze issues that remain unexplored by standard Difference-in-Difference (henceforth DID) estimators. For example, they estimate that the performance of _PROGRESA_ could have been improved by offering more resources to older age cohorts of children such as secondary school students and less to younger age cohorts or primary school students.

6
United Nations CEDAW Committee on Botswana CEDAW/C/BOT/3 <u>http://www.bayefsky.com/docs.php/area/reports/treaty/cedaw/opt/0/state/23/node/4/filename/bot swana_cedaw_c_bot_3</u> <u>United Nations Development Program: 2012</u> _<u>: Global Commission on HIV and the Law; Risks, Rights and Health.</u>_ <u>UNDP HIV/AIDS Group. New York.</u> United Nations Human Rights Council (2008), Working Group on the Universal Periodic Review, Third Session, Geneva, 1-15 December 2008, Botswana at 4. A/HRC/WG/6/3/BWA/1 5 September 2008 Van Allen, Judith. _Feminism and Social Democracy in Botswana,_ Socialism and Democracy Online, March 13 2011 <u>http://sdonline.org/45/feminism-and-social-democracy-in-botswana/</u> World Bank. 2012. Botswana Country Overview. <u>http://www.worldbank.org/en/country/botswana/overview</u> World Bank. 2013. 50 Years of Expanding Legal Rights of Women Around the World. <u>http://wbl.worldbank.org/data/timeseries</u> 16
Table 7: Estimating the effect of migrants’ legal status on occupations after return, unconditional on return migration

||(1)<br>Migrate|(2)<br>Illegal|(3)<br>Return|(4)<br>Occupation<br>upon return|
|---|---|---|---|---|
|Age|0.012***<br>(0.001)|-0.072**<br>(0.034)|-0.014**<br>(0.006)|0.021<br>(0.015)|
|Age squared|-0.000***|0.001*|0.000***|-0.001***|
||(0.000)|(0.000)|(0.000)|(0.000)|
|No education|0.019***|0.492***|-0.029|2.970***|
||(0.004)|(0.121)|(0.021)|(0.073)|
|Primary or preparatory|0.032***|0.463***|0.050**|2.837***|
||(0.004)|(0.130)|(0.022)|(0.071)|
|Secondary|0.017***|0.416***|0.033*|2.102***|
||(0.003)|(0.107)|(0.017)|(0.059)|
|Rural|0.009***|0.260***|0.008|0.099**|
||(0.003)|(0.085)|(0.015)|(0.040)|
|Oil prices|0.013***<br>(0.000)||||
|Diplomatic exchange||-0.267***<br>(0.103)|||
|Confict|||0.046***<br>(0.013)||
|Illegal status||||-0.121<br>(0.253)|
|Legal status||||0.189<br>(0.189)|
|Observations|14,879|1,955|2,071|10,764|
|Parental controls|Yes|Yes|Yes|Yes|
|Decades of migration dummies|Yes|Yes|Yes|No|
|Labor market controls in Egypt|No|No|No|Yes|
|Predicted occupation: Non-mig.:|5.394; Illegal mi|g.=5.255; Legal|mig.=5.306||

Robust standard errors in parentheses. *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1 _Notes_ : Equation 1 is the probability of temporary migration. Equation 2 is the probability of undocumented migration. Equation 3 is the probability of return migration. Equation 4 models the occupational ranking upon return. For identification of equation (1), we use the inflation adjusted historical oil prices (in US dollars). For identification of equation (2), we use the diplomatic exchange, which is the diplomatic representation of each country of destination of Egyptian migrants in Egypt at time of migration. It is a dummy variable equal zero if there is no evidence of diplomatic exchange and is equal one if there is evidence of diplomatic exchange at the level of charg ́e d’affaires, minister, ambassador or other. For identification of equation (3), we use the number of active armed conflicts that is both country and year specific from the Uppsala Conflict Data Project (UCDP). Equation (4) estimates the effect of illegality on occupational ranking upon return, unconditional on return migration. Occupational ranking is computed according to the ISCO-88 one digit classification. The greater the ranking, the higher is the occupation classified in the occupational ladder. The predicted occupational ranking for non-migrants, illegal migrants, and legal migrants are reported in the last row.

41