rafmacalaba/datause-encoder-data huggingface dataset:
_differs_ both within and between treining **modes** (Table **1).** Lengthier courses, in augmenting **Individual human capital** stocks, should lead to higher earnings.

**Trainees** completed their courses **in** different calendar years, from 1964-1967 (Table **2).** Year of course completion (COMP) is **added as** a continuous variable in serial form 1-4, corresponding to the years 19641967; the higher the value on the COMP coefficient, the lower would be expented earnings. Year of birth (YB) enters **as** a dummy variable (1947 - 0; 1948 - 1). Information on year of imigration was provided with the earnings data, by the National Insurance Institute. Since the labor market perform.nce of non-immigrants might be superior to that of Immigrants, a dummy variable imigrant status (IMM) was included (Israel born - 0; - Immigrant 1).

Table 2 Year of Course Completion by Training Mode

|Year of<br>Completion<br>1964|Vocational<br>Secondary<br>School<br>17|Apprenticeship<br>I-------I<br>-----<br>157|Industrial<br>School<br>..._____________<br>-----------------------<br>-|Short<br>Teenager<br>Course<br>_____________<br>--------<br>7|All<br>Modes<br>____<br>181|
|---|---|---|---|---|---|
|1965|217|339|17|33|606|
|1966|191|119|31|19|360|
|1967|40|41|5|-|86|

# Results

Turning first to the two dominant training alternatives, VOC and APP, annual positive earnings in these trades are regressed against training program (with APP entering as a dummy variable and VOC in the constant term), and against other relevant variables for each of the years 1969 tu 1976 (Table 3). Holding other variables constant, no significant differences between annual earnings of VOC and APP are reported apart from 1969, when the 10
- Group Insurance Scheme (GIS) and Group Saving Linked Insurance (GSLI): both are compulsory life insurance schemes; the GIS is for salaried workers in the public sector, whereas the GSLI is for all other workers.

On the spending side, social services and economic services account for over half of government expenditure. Table 2 presents a summary of government spending by sector. Social services, economic services, and general public services each account for about 29 percent of total spending. Social spending in Table 2 only reflects health and education services, while spending on contributory programs is not included. According to the Annual Financial Statement of FY2016-17, contributions to the Provident Fund amounted to Nu. 660.4 million in the same fiscal year.

Table 2. Government expenditure by sector, FY2016-17

|Sectors|Amount (Nu.Million)|% of Total|
|---|---|---|
|Social Services|15,087.73|28.6|
|Health Services|4,359.02|8.3|
|Education Services|10,728.71|20.4|
|Economic Services|15,058.83|28.6|
|RNR Services|6,764.55|12.8|
|Mining, Manufacturing & Industries Services|142.833|0.3|
|Transport & Communication Services|6,288.99|11.9|
|Energy Services|905.498|1.7|
|Other Economic Services|956.963|1.8|
|Housing & Public Amenities Services|2,109.68|4|
|General Public Services|15,219.90|28.9|
|General Public Services|10,475.73|19.9|
|Public Debt Services|4,744.17|9|
|Religion & Cultural Services|2,578.06|4.9|
|Public Order& Safety Services|2,657.87|5|
|Total|52,712.06|100|

_Source:_ Annual Financial Statements of the Royal Government of Bhutan. Ministry of Finance.

Social spending mainly covers education and health services while social protection programs are limited in Bhutan. Public education is free from primary to tertiary level. Health services are predominantly provided by the public sector and are also available free of charge. On the other hand, social protection programs are very limited. _Kidu_ is a key program aimed at alleviating the hardships of the most vulnerable population but information on Kidu receipt is not collected in the household survey.<sup>9</sup> Most recently during the COVID-19 pandemic, the Druk Gyalpo’s Relief Kidu provided temporary income support to vulnerable people, including the self-employed, who had suffered from livelihoods losses due to the COVID-19 crisis.

# **_Education Spending_**

> 9 The Bhutan Living Standards Survey does not collect information on Kidu receipt.

6
Dharmalingam and Morgan, 2004). For example, in India today, it seems important to have educated sons, but in order to get daughters married, it is equally important to have educated daughters. If the average levels of education among Muslim men are for example lower than among Hindu men, then there may be lower educational investments also required of Muslim women (Borooah and Iyer, 2005b). A related issue is land ownership – there may be a greater desire on the part of Hindus to have sons in order to keep land within the patrilineal family line. It is documented that land ownership among Muslims is less than among Hindus (Shariff, 1999). In summary, for reasons that stem both from theological considerations, and from the socio-economic characteristics of religious groups, there may be important differences between Hindus and Muslims in their fertility and mortality of sons compared to daughters. We next turn to a formal investigation of the socio-economic determinants of fertility and mortality differences between Hindus and Muslims.

# **3 Fertility, Mortality and Religion in India**

India today has a total population of just over 1.1 billion people. Census data shows that Hindus form over 80 percent of India’s population, while Muslims form approximately 15 percent. Muslims are the most significant ‘minority’ population and consist of approximately 150 million people. Our description of contemporary India uses data from the newly released 2005-06 National Family Health Survey (NFHS-3).<sup>7</sup> The NFHS interviewed a total of 123,385 women in 29 states of India. The survey is based on a sample of housesholds that is representative at the state as well as national level. The religious composition of the households is consistent with the findings of the Indian Census (2001): 82 percent of households are Hindu, 13 percent are Muslim, 3 percent are Christian, 2 percent are Sikh, and the remainder are other religions. Among Hindus, the caste composition of our population also mirrors the census. 44% of Hindu respondents reported that they belonged to a “Scheduled Caste” or a “Scheduled Tribe” (henceforth referred to as Dalits), and 44% of

> <u>7The</u> first NFHS survey was conducted in 1992-93, and the second in 1998-99. All three surveys were conducted in conjunction with the Ministry of Health and Family Welfare (MOHFW),Government of India. Funding for the survey was provided by the United States Agency for International Development (USAID), the United Kingdom Department for International Development (DFID), the Bill and Melinda Gates Foundation, UNICEF, UNFPA, and the government of India. Technical assistance was provided by Macro International Maryland, USA.

6
**2008-11**

|Albania|Greece|Pakistan|
|---|---|---|
|Algeria|Guatemala|Panama|
|Argentina|Honduras|Paraguay|
|Armenia|Hungary|Peru|
|Australia|India|Philippines|
|Austria|Indonesia|Poland|
|Bahrain, Kingdom of|Iran, Islamic Rep.|Portugal|
|Bangladesh|Ireland|Qatar|
|Belarus|Italy|Romania|
|Belgium|Japan|Russian Federation|
|Bolivia, Plurinational State of|Jordan|Rwanda (2009)|
|Botswana (2009)|Kazakhstan|Saudi Arabia, Kingdom of|
|Brazil (2011)|Kenya|Senegal|
|Bulgaria|Korea, Rep.|South Africa|
|Burundi (2011)|Kuwait, the State of|Spain|
|Cambodia|Kyrgyz Republic|Sri Lanka|
|Cameroon|Lebanese Republic|Sweden|
|Canada|Lesotho|Tanzania|
|Chile|Lithuania|Thailand|
|China (2011)|Madagascar|Trinidad and Tobago|
|Colombia|Malawi|Tunisia|
|Costa Rica|Malaysia|Turkey|
|Côte d'Ivoire|Mali|Uganda|
|Czech Republic|Mauritius|Ukraine|
|Democratic Rep. of the Congo|Mexico (2011)|United Kingdom|
|Denmark|Mongolia|United States of America|
|Dominican Republic|Morocco|Uruguay|
|Ecuador|Mozambique|Uzbekistan|
|Egypt, Arab Rep.|Namibia|Venezuela, RB|
|Ethiopia|Nepal|Vietnam|
|Finland|Netherlands|Yemen, Rep.|
|France|New Zealand|Zambia|
|Georgia|Nicaragua|Zimbabwe|
|Germany|Nigeria||
|Ghana|Oman||

Data sourced from the previous World Bank exercise (see Borchert et al., 2012), with some adjustments, see Section 2. All data correspond to 2008, except as indicated otherwise.

46
Abdool Karim, Quarraisha, Salim S. Abdool Karim, Janet A. Frohlich, Anneke C. Grobler, Cheryl Baxter, Leila E. Mansoor, Ayesha B. M. Kharsany, Sengeziwe Sibeko, Koleka P. Mlisana, Zaheen Omar, Tanuja N. Gengiah, Silvia Maarschalk, Natasha Arulappan, Mukelisiwe Mlotshwa, Lynn Morris, Douglas Taylor, and on behalf of the CAPRISA 004 Trial Group. 2010. 'Effectiveness and Safety of Tenofovir Gel, an Antiretroviral Microbicide, for the Prevention of HIV Infection in Women', _Science_ , 329: 1168-74.

- Abdool Karim, S. S., B. A. Richardson, G. Ramjee, I. F. Hoffman, Z. M. Chirenje, T. Taha, M. Kapina, L. Maslankowski, A. Coletti, A. Profy, T. R. Moench, E. PiwowarManning, B. Masse, S. L. Hillier, L. Soto-Torres, and H. I. V. Prevention Trials Network 035 Study Team. 2011. 'Safety and effectiveness of BufferGel and 0.5% PRO2000 gel for the prevention of HIV infection in women', _AIDS_ , 25: 957-66.

- Ahmed, S., T. Lutalo, M. Wawer, D. Serwadda, N. K. Sewankambo, F. Nalugoda, F. Makumbi, F. Wabwire-Mangen, N. Kiwanuka, G. Kigozi, M. Kiddugavu, and R. Gray. 2001. 'HIV incidence and sexually transmitted disease prevalence associated with condom use: a population study in Rakai, Uganda', _AIDS_ , 15: 2171-9.

- Arroyo, M. A., W. B. Sateren, D. Serwadda, R. H. Gray, M. J. Wawer, N. K. Sewankambo, N. Kiwanuka, G. Kigozi, F. Wabwire-Mangen, M. Eller, L. A. Eller, D. L. Birx, M. L. Robb, and F. E. McCutchan. 2006. 'Higher HIV-1 incidence and genetic complexity along main roads in Rakai District, Uganda', _J Acquir Immune Defic Syndr_ , 43: 440-5.

- Assembly, United Nations General. 2012. "Report of the Secretary-General: United to End AIDS: Achieving the Targets of the 2011 Political Declaration." In.

- Aulagnier, M., W. Janssens, I. De Beer, G. van Rooy, E. Gaeb, C. Hesp, J. van der Gaag, and T. F. Rinke de Wit. 2011. 'Incidence of HIV in Windhoek, Namibia: demographic and socio-economic associations', _PLoS One_ , 6: e25860.

- Auvert, B., D. Taljaard, E. Lagarde, J. Sobngwi-Tambekou, R. Sitta, and A. Puren. 2005. 'Randomized, controlled intervention trial of male circumcision for reduction of HIV infection risk: the ANRS 1265 Trial', _PLoS Med_ , 2: e298.

- Baeten, J. M., D. Donnell, P. Ndase, N. R. Mugo, J. D. Campbell, J. Wangisi, J. W. Tappero, E. A. Bukusi, C. R. Cohen, E. Katabira, A. Ronald, E. Tumwesigye, E. Were, K. H. Fife, J. Kiarie, C. Farquhar, G. John-Stewart, A. Kakia, J. Odoyo, A. Mucunguzi, E. Nakku-Joloba, R. Twesigye, K. Ngure, C. Apaka, H. Tamooh, F. Gabona, A. Mujugira, D. Panteleeff, K. K. Thomas, L. Kidoguchi, M. Krows, J. Revall, S. Morrison, H. Haugen, M. Emmanuel-Ogier, L. Ondrejcek, R. W. Coombs, L. Frenkel, C. Hendrix, N. N. Bumpus, D. Bangsberg, J. E. Haberer, W. S. Stevens, J. R. Lingappa, C. Celum, and E. P. Study Team Partners Pr. 2012. 'Antiretroviral prophylaxis for HIV prevention in heterosexual men and women', _N Engl J Med_ , 367: 399-410.

- Bao, L., J. A. Salomon, T. Brown, A. E. Raftery, and D. R. Hogan. 2012. 'Modelling national HIV/AIDS epidemics: revised approach in the UNAIDS Estimation and Projection Package 2011', _Sex Transm Infect_ , 88 Suppl 2: i3-10.

70
Inman, R. P. 1992. “Can Philadelphia Escape Its Fiscal Crisis With Another Tax Increase?” _Business Review of the Federal Reserve Bank of Philadelphia_ , SeptOct, 5-20.

- Keefer, Philip, and Stuti Khemani, 2005. “Democracy, Public Expenditures, and the Poor.” _World Bank Research Observer_ , Forthcoming, Spring 2005

- Keefer, Philip 2002. “Clientelism, Credibility and Democracy.” World Bank, Development Research Group, Washington, D.C. Processed.

- Khemani, Stuti, 2004a. “Local Government Accountability for Service Delivery in Nigeria.” World Bank, Development Research Group, Washington, D.C. Processed.

- Khemani, Stuti, 2004b. “Partisan Politics and Fiscal Discipline in a Federation: Evidence from the states of India.” World Bank, Development Research Group, Washington, D.C. Processed.

- Khemani, Stuti, 2003. “Does Delegation of Fiscal Policy to an Independent Agency Make a Difference? Evidence from intergovernmental transfers in India.” World Bank, Development Research Group, Washington, D.C. Processed.

- Khemani, Stuti, 2001. “Decentralization and Accountability: Are voters more vigilant in local than in national elections?” Policy Research Working Paper 2557. World Bank, Washington, D.C.

- Litvack, Jennie, Junaid Ahmad, and Richard Bird. 1998. _Rethinking Decentralization in Developing Countries_ . Washington, D.C.: World Bank.

- Mansuri, G. and V. Rao. 2003. “Community Based (and Driven) Development: A Critical Review.” _World Bank Research Observer_ 19(1): 1-33.

- Mathew and Nayak, 1996. “Panchayats at Work.” _Economic and Political Weekly_ , July 6, 1996, page 1765.

- McLure, Charles E., Jr. 1999. "The Tax Assignment Problem: Conceptual and Administrative Considerations in Achieving Subnational Fiscal Autonomy," Presented to Seminar on Intergovernmental Fiscal Relations and Local Financial Management organized by National Economic and Social Development Board of the Royal Thai Government and the World Bank, Chiang Mai, Thailand, February 24-March 5. <u>http://www1.worldbank.org/wbiep/decentralization/Topic06_Printer.htm</u>

- Nickson, Andrew, and Claudia Vargas. 2002. “The Limitations of Water Regulation: The Failure of the Cochabamba Concession in Bolivia.” _Bulletin of Latin American Research_ 21(1):99–120.

- Persson, Torsten and Guido Tabellini 2000. _Political Economics: Explaining Public Policy_ . Cambridge, MA: The MIT Press

- Pradeep Chhibber, Sandeep Shastri, and Richard Sisson, 2003. “The State, Voluntary Associations, and the Provision of Public Goods in India.” Department of Political Science, University of California at Berkeley. Processed.

26
WPS3970

# **Do Reorganization Costs Matter for Efficiency? Evidence from a Bankruptcy Reform in Colombia**

## Xavier Giné and Inessa Love<sup>*</sup>

### **Abstract**

This paper studies the effect of reorganization costs on the efficiency of bankruptcy laws. We develop a simple model that predicts that in a regime with high costs, the law fails to achieve the efficient outcome of liquidating unviable businesses and reorganizing viable ones. We test the model using the Colombian bankruptcy reform of 1999. Using data from 1,924 firms filing for bankruptcy between 1996 and 2003, we find that the pre-reform reorganization proceeding was so inefficient that it failed to separate economically viable firms from inefficient ones. In contrast, by substantially lowering reorganization costs, the reform improved the selection of viable firms into reorganization. In this sense, the new law increased the efficiency of the bankruptcy system in Colombia.

### World Bank Policy Research Working Paper 3970, July 2006

_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 view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._ _____________________________________________

> * Emails: <u>xgine@worldbank.org</u> and <u>ilove@worldbank.org. Both authors are affiliated with the</u> World Bank, 1818 H Street, Washington, DC 20433. We wish to thank Fernando Montes-Negret for sparking our interest in this topic, Enrique Aguirre and the Superintendencia de Sociedades for the data and Rodolfo Danies Lacouture, the Superintendent, for insightful comments on an earlier draft. We also wish to thank Jaime Alberto Gomez, Jorge Pinzón, Felipe Trias and Carlos Urrutia for very useful conversations about the intricacies of the bankruptcy law in Colombia. We finally wish to thank Rei Odawara for excellent research assistance and to Jishnu Das, Asli Demirguc-Kunt, Quy-Toan Do, Leora Klapper, Soledad Martínez Peria, Claudio Raddatz and Kenichi Ueda for valuable comments.

1
The development focus of the Bank’s journal articles comes through in Figures 2 and 3, which use “word clouds” to display the frequency of the 150 most-common words in the titles of articles in the “economics, econometrics and finance” group in the SCOPUS database. The Bank’s focus on development and developing countries is evident. So too is its emphasis on agriculture, poverty, inequality and rural issues; the words “agriculture”, “poverty”, “inequality” and “rural” are not on the university word clouds. Health features equally prominently in both word clouds; education and trade feature in both, but are more prominent in the Bank’s.

Table 2 shows the number of papers explicitly mentioning the name of a developing country. Berkeley, Harvard and Oxford all come out ahead of the Bank, but the Bank’s article count is around 1.5 times the average among the 14 universities and far in excess of the other development agencies. The Bank ranks third, fifth and second respectively in terms of articles explicitly mentioning Africa, China and India in their titles. Harvard outranks the Bank on all three, and on China the Bank’s count is somewhat less than the average count of the 14 universities. But on Africa and India, the Bank’s count is respectively 1.6 times and twice the average count among the 14 universities.

These figures are consistent with the findings of Das et al. (2009) who, using a database of over 76,000 empirical economics papers published since 1985, found that publications on specific countries (adjusted for population size) increased with the country’s GDP per capita with an elasticity of 0.62. (Naturally research on the US is well represented, though not more so than one would expect given the country’s GDP.) They found the Bank’s economics research to be more skewed toward low and middle-income countries compared to that of the top five US universities (Harvard, MIT, Chicago, Stanford and Princeton). If one focuses on publications on countries _except_ the US in the top 200 economics journals, the Bank has a similar number of publications to these universities. The difference is that half of the Bank’s publications reported research findings on the poorest 40% of countries (ranked by GDP per capita), while those countries only accounted for about one quarter of the publications in the top five universities.

The Bank’s development focus also comes through strongly in the last two columns of Table 2. The penultimate column focuses on articles in the top 16 development economics journals, as identified by Barrett et al. (2000).<sup>8</sup> The Bank’s publication count in these journals is

> 8   They include World Bank Economic Review, World Development, Journal of Development Economics, Economic Development and Cultural Change, Journal of Development Studies, American Economic Review,

9
and consulting & engineering segments of the EGS industry, might also contribute to making environmental data collection more widespread and affordable.

No entity within and around a GVC should be expected to know everything about everyone, of course. This would hardly be possible anyway, due to the presence of proprietary information and communication costs. The parties involved in greening a GVC will then be asymmetrically informed. This brings about incentive issues that we now turn to.

# **3.  Setting proper incentives**

Motivating heterogeneous entities endowed with differential information and diverging preferences towards a common goal is a generic challenge of any organization. As far as GVCs are concerned, this task must be jointly undertaken at the firm, supply chain, national and global levels, through managerial means and processes, buyer-supplier relationships, government regulation and global governance.

# **3.1  Within firms**

Gabel and Sinclair-Desgagné (2000) highlight and discuss several managerial instruments that firms – large or small, formal or informal – can use internally to foster compliance with environmental objectives. These instruments include performance rewards, monitoring and auditing of nonfinancial objectives, task design and allocation, decision-making processes, employee selection and training, and improving the firm’s culture. Large divisional corporations can also add transfer prices to this list.

# ▪ _Performance rewards_

According to Avila and Whitehead (1993), Dow Chemical’s performance improvement review had a number of elements – among which environmental performance – built into its bonus scheme for employees. Whether such a scheme was optimal, however, is another question. **_Incentive pay is a double-edge sword: it can work very well in some contexts, but lead to disaster in others._** An important feature to be dealt with here is that asking an employee to meet new environmental objectives amounts to expanding her usual agenda. Serious environmental programs being broad and complex, this might expose her to _informational overload_ . Returns to extra managerial effort might then decrease rapidly, and the fate of the firm might end up resting on dangerous but timesaving habits, misleading but convenient heuristics, and deficient but cosmetic problem solving.

In addition to the threat of informational overload, it might be difficult to _balance incentives_ between the pursuit of regular business activities and the reduction of environmental externalities. In a classical article on the subject, Holmstrom and Milgrom (1991) explain that: (...) when there are multiple tasks, incentive pay serves not only to allocate risks and to motivate hard work, it also serves to direct the allocation of the agents’ attention among their various duties. (...) the desirability of providing incentives for any one activity 8
39

||Russia|Slovakia|Slovenia|Spain|Sweden|Switzerland|Turkey|UK|Ukraine|US|
|---|---|---|---|---|---|---|---|---|---|---|
|Barley|0.24|0.80|0.80|0.70|0.60|0.60|0.80|0.70|0.80|0.99|
|Beef|0.25|0.30|0.30|0.55|0.57|0.57|0.30|0.55|0.30|0.60|
|Cotton|-|-|-|-|-|-|0.15|-|-|0.74|
|Egg|0.25|0.35|0.35|0.75|0.75|0.75|0.35|0.75|0.35|0.55|
|Hazelnut|-|-|-|-|-|-|0.20|-|-|-|
|Maize|0.38|0.30|0.30|0.60|-|0.65|0.30|-|0.30|0.48|
|Milk|0.20|0.30|0.30|0.65|0.60|0.60|0.30|0.65|0.30|0.50|
|Oat|0.24|0.80|-|0.70|0.60|0.60|-|0.70|0.80|-|
|Oilseed|-|-|-|-|-|0.30|-|-|-|-|
|Pigmeat|0.40|0.45|0.45|0.90|0.80|0.80|-|0.90|0.45|1.00|
|Potato|-|0.80|-|0.70|0.60|-|0.80|0.70|0.80|0.99|
|Poultry|0.50|0.70|0.70|0.80|0.75|0.75|0.70|0.80|0.70|0.65|
|Rapeseed|-|0.30|-|0.75|0.30|-|-|0.75|-|-|
|Rice|-|-|-|0.35|-|-|0.30|-|-|0.40|
|Rye|0.24|0.80|-|-|-|-|-|-|0.80|-|
|Sheepmeat|-|0.35|0.35|0.70|0.80|0.80|0.35|0.70|-|0.80|
|Sorghum|-|-|-|-|-|-|-|-|-|0.99|
|Soybean|-|0.45|-|0.40|-|-|-|-|-|0.60|
|Sugar|0.16|0.20|0.20|0.15|0.45|0.45|0.20|0.15|0.20|0.50|
|Sunflower|0.15|0.30|-|0.75|-|-|0.30|-|0.30|-|
|Tobacco|-|-|-|-|-|-|0.20|-|-|-|
|Wheat|0.23|0.25|0.25|0.50|0.80|0.80|0.25|0.50|0.25|0.60|
|Wine|-|0.20|-|0.20|-|-|-|-|-|-|
|Wool|-|-|-|-|-|-|-|-|-|0.80|

Sources: Authors’ compilation from Roningen (2001) and Tyers and Anderson (1992, Appendix Tables A2 to A4).