rafmacalaba/datause-encoder-data huggingface dataset:
# **2.3 External validity and comparison to Bloom Van Reenen Management Practices**

In 2013, prior to the interventions, we commissioned the LSE survey team responsible for the Bloom and Van Reenen (2007) World Management Surveys (WMS) to apply their methodology to a random sample of 180 firms representative of the Colombian manufacturing sector, as well as to a sub-sample of 72 companies from our sample with 40 or more employees.<sup>6</sup> Appendix 7 summarizes this survey process, and provides three key results. First, the mean and distribution of WMS management practices scores for our auto parts firms are similar to those of the overall manufacturing sector in Colombia (2.38 versus 2.54). Second, Colombia’s average management practices score shows firms are, on average, poorly managed in global terms, but similar to many other developing countries. The average score is just below that of firms in India and just above that in Kenya in the WMS. The auto parts sector in Colombia is thus a fairly typical sector for both the country, and for developing countries as a whole, in terms of management practices.

A final use of this baseline WMS data is to compare the Anexo K management measure, our main measure of management used in this paper, to the WMS. Appendix 5 shows that the two are significantly correlated in the cross-section at baseline, with a correlation of 0.26 between the two overall indices. The Anexo K has a stronger correlation (0.44) with the monitoring subcomponent of the WMS, reflecting a particular emphasis on measurement and monitoring than on other management practices.

# **2.4 Macroeconomic context**

The Colombian auto parts sector had sales grow at an annual average of 5.4 percent per year over the 2002 to 2012 period leading up to our experiment (Reina et al, 2014).<sup>7</sup> At the start of our study, imports averaged 68 percent of total sales in the sector, and were the main source of competition for most firms in our study. However, the country was hit by a combination of external and internal shocks starting in late 2013, which resulted in a large depreciation of the peso, from an average of 1930 COP to the USD in 2013 to approximately 3000 COP to the USD in each of 2015, 2016, and 2017. Domestic new vehicle sales fell from 326,000 units in 2014 to 238,000 units in 2017, a 27% drop (BBVA Research). Export sales of auto parts fell 51 percent in dollar terms over the 20132016 period, driven by weak economies in the main export destinations of the República

> 6 This size restriction was made since the WMS was designed for firms with 50 or more employees.

> 7 The report notes a nominal growth rate of 11.2 percent, which we deflate using the Colombian inflation rate taken from the World Development Indicators.

7
# **Literature**

Auriol, E. and Warlters, M. 2005. Taxation base in developing countries, Journal of Public Economics 89, p.625-646.

Bird, R., and Wallace, S., 2003. Is It Really So Hard to Tax the Hard-to-Tax? The Context and Role of Presumptive Taxes. ITP Paper 0307.

Bruhn, Miriam. 2011. Reforming Business Taxes: What Is the Effect on Private Sector Development? World Bank Viewpoint Public Policy for the Private Sector Note Number 330.

Bruhn, Miriam. 2013. A Tale of Two Species: Revisiting the Effect of Registration Reform on Informal Business Owners in Mexico. Journal of Development Economics, 103: 275-283.

Chetty, R., Friedman, J. Olsen, T. and Pistaferri, L. 2011. Adjustment Costs, Firm Responses, and Micro vs. Macro Labor Supply Elasticities: Evidence from Danish Tax Records, Quarterly Journal of Economics, 126, 749–804.

De Soto, H. 1989. The Other Path. The Invisibles Revolution in the Third World. New York: Basic Books.

Djankov, S., La Porta, R., Lopez-de-Silanes, F., and Shleifer, A., 2002. The Regulation of Entry. Quarterly Journal of Economics, vol. 117, 1–37.

Engelschalk, M., 2004. Creating a favorable environment for small business development in transition countries, in Alm, J, Martinez-Vazquez, J., & S. Wallace (Eds.), Taxing the hard-to-tax - lessons from theory and practice. Amsterdam: Elsevier.

Engelschalk, M. and Loeprick, J. (2014): MSME Taxation in Transition Economies: Country Experience on the costs and benefits of introducing special tax regimes. World Bank. Forthcoming.

Fajnzylber, P., Maloney, W., Montes-Rojas, G., 2011. Does formality improve micro-firm performance? Evidence from the Brazilian SIMPLES program. Journal of Development Economics, Elsevier, vol. 94(2), 262-276.

Farrel D. (2004): The Hidden Dangers of the Informal Economy.” McKinsey Quarterly, no. 3.

Feltenstein, A. and Shamloo, M. 2013. Tax reform, the informal economy and bank financing of capital formation. Int Tax and Public Finance, Vol 20:1, p.1-28.

Friedman, E., Johnson, S., Kaufmann, D., and Zoido-Lobaton, P. 2000. Dodging the grabbing hand: the determinants of unofficial activity in 69 countries. Journal of Public Economics Vol 76 (3), 459-493.

Gauthier, B. and Gersovitz, M. 1997. Revenue Erosion Through Exemption and Evasion in Cameroon, 1993. Journal of Public Economics Vol 64 (3), p. 407-24.

Gauthier, B and Reinikka, R. 2006. Shifting Tax Burdens through Exemptions and Evasion: an Empirical Investigation of Uganda. Journal of African Economies Vol. 15 (3), 373-398.

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WPS3324

# Health Care Decisions as a Family Matter Intrahousehold Education Externalities and the Utilization of Health Services

## **Magnus Lindelöw**

The World Bank Centre for Study of African Economies, Oxford University Email: mlindelow@worldbank.org

### World Bank Policy Research Working Paper 3324, June 2004

_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._

> I am grateful to the National Statistics Institute (INE) in Mozambique for granting me permission to use the 1996/97 Household Survey. Ken Simler provided invaluable support in accessing and interpreting the data. I have also benefited from comments and suggestions from Marcel Fafchamps, Pieter Serneels, Adriaan Soetevent, and Mattias Lundberg.
been based on a minority of the tariff lines (those available in the printed data of the Russian Customs Service).<sup>6</sup> Recently, however, Oleksandr Shepotylo and I (see, Shepotylo and Tarr, forthcoming) have obtained data that allowed us to calculate the actual Russian tariffs. Briefly, our key results are the following. The average tariff in Russia has increased between 2001 and 2003 from about 11.5 percent to between 13 and 14.5 percent, but it has held steady in 2004 and 2005. This places Russia’s tariffs at a level slightly higher than other middle-income countries and considerably higher than the OECD countries. The tariff structure became much more diverse between 2001 and 2003, but the dispersion of the tariff moderated in 2004 and 2005. Notably the trade weighted standard deviation of the tariff approximately doubled from 9.5 percent in 2001 to 18 percent in 2003, but then fell to 15.2 percent by 2005 . “Tariff peaks,” that is, tariff lines with very high tariffs, are more of a problem in 2005 than in 2001, but less so than in 2003. The reason for the increase in the tariffs is the specific tariffs, as the ad valorem rates have not increased. More tariff lines are subject to specific tariffs in 2003-2005 than in 2001, and the appreciation of the euro, relative to 2001 has increased the ad valorem equivalent of the specific tariffs. The food sector and light industry are the aggregate sectors with the highest tariff rates—their tariff rates in 2005 were 23.1 percent and 19.5 percent on a trade-weighted basis. At the two digit level, motor vehicles, footwear, leather products and sugar are among the most highly protected.

Our aggregate results are summarized in table 1. For the most recent year, Russia’s MFN tariffs were about 12.1 percent on a simple average basis or 14 percent on a trade weighted basis in 2005, where we have taken into account the ad valorem equivalents of Russia’s specific tariffs. We find that ignoring the specific tariffs results in a reduction in the calculated average tariff to about 11 percent. Independent of how the members of the Working Party have calculated Russian tariffs, an average Russian tariff of the 8 percent implies a decline.

**Civil Aircraft and Capital Goods and Equipment.** One of the more contentious areas of tariff negotiation was civil aircraft. Tariffs on wide body aircraft will be reduced from 20 to 7.5 percent in the four years following accession. Russia has agreed to substantial tariff reductions in construction, agricultural and scientific equipment, as well as medical devices. Tariffs in these sectors will average 5 percent.

# **Services Commitments**

Some of the most important and internally controversial commitments by Russia are in the area of services.

**Insurance.** Russia will significantly increase its commitments to multinational insurance providers. It will allow 100 percent foreign ownership of non-life insurance

6 The annual report of the Russian Customs Service publishes trade data for about 1600 tariff categories. There are over 11,000. tariff lines, so the Customs Service aggregates many tariff lines in this publication.

5
# HOW THE PROPOSED BASEL GUIDELINES ON RATING-AGENCY ASSESSMENTS WOULD AFFECT DEVELOPING COUNTRIES

by Giovanni Ferri, Li-Gang Liu, and Giovanni Majnoni * World Bank; University of Bari (Italy) JEL classification numbers: G15, G18, G21 Keywords: external credit ratings, bank capital asset requirements

* We wish to thank Noemi L. Giszpenc and Hosook Hwang for valuable research assistance. Helpful comments on a previous version of the paper were provided by Lea Carty, Stjin Claessens, Cem Karacadag and by participants of the New York University Conference on "Credit Ratings and the New Basel Guidelines on Capital Adequacy for Bank Credit Assets" and in the World Bank "Annual Bank Conference on Development Economics".
sector financial intermediaries to set up information services for their mutual benefit and for clients. Government could initially provide information services directly, as in the case of the Central de Deudores in Argentina, and later let the private sector take over (Calomiris, 1997; World Bank, 1998). Government could also provide infrastructure that would ease the flow of private information. It could disseminate information on bank credit risk collected in its banking supervisory capacity and establish a centralized registry for collateral.34

# **11.3.5 Signaling reputational capital: the role of private risk-takers**

As noted, sensitivity to capital losses motivates investors to use information to select wellreputed financial intermediaries. In the banking sector, deposit insurance schemes could be designed so as to induce much closer attention from (both large and small) depositors on the true status of their banks.<sup>35</sup> This would be achieved, for instance, if insurance premiums were correlated with bank risks and made known to depositors, since a higher premium would indicate a lower reputational capital. Such an incentive would be further strengthened if the insurance was provided by competing private insurers, as these would seek to correlate premiums with risks as closely as possible and thus generate a strong demand for good-quality information from banks. Similarly, limited insurance coverage would likely induce depositors to assess more carefully their banks. Another strong incentive would hold if depositors were asked to co-pay insurance premniums correlated with bank risks, and if premiums were to vary with the extent of insurance coverage purchased.

Another market-based signaling device for reputational capital would be provided by requiring intermediaries to finance a small portion of their non-reserve assets with subordinated debt (uninsured certificates of deposits) bearing an interest rate not greater than the riskless rate plus a given spread and held by _well-informed_ market agents (Keehn, 1989; Wall, 1989; Calomiris, 1997). Subordinate-debt holders would have an incentive to monitor debtors' compliance with the risk-cap requirement and to sell at discount the debt of under-performing institutions. This device would supply the market with reliable signals on the intermediaries' reputational capital, provided there was a liquid secondary market for the subordinated debt and that the debt-issue requirement was credible and effective in the first place3<sup>6</sup> 24
Where it is proposed to consider internal models, then it may well be desirable, or in some cases necessary, for collaboration with other supervisors. As part of the FSAP procedures, we see that the level of collaboration between supervisors on issues relating to individual firms is less than it is with respect to more general issues. The opportunity exists for increased collaboration. For supervisors in emerging and developing markets, such collaboration should be seen as an opportunity to obtain useful assistance and expertise.

_Steps to enhance supervisory capacity should be taken in preparation for a changing environment. Enhancements should be directed at finding additional expert staff, conduct of on-site inspections of company risk management practices, and the updating of statistical data collections._ _Consideration should be given to making increased use of professionals to assist the supervisor._ _In some cases, supervisors may also have to develop capacities that address the specific nature of reinsurance company supervision._ _Collaboration with other supervisors will serve as a useful tool for supervisors in emerging and developing markets._

# _5.5 Building a Third Pillar_

The third pillar will be weak in many jurisdictions. The providers of equity may not impose great pressure on the local management of firms simply because the companies are not listed or not listed in the jurisdiction. Public reporting may be of limited value where they do not permit reasonable comparison of companies.

Where consumers are less sophisticated or familiar with financial services then the market for products will also not provide as much of an aid to the supervision of companies as it would where consumer familiarity with financial issues is more developed.

The opportunity exists for other parties to play a role and encourage the development of the insurance sector third pillar. In many countries, audit firms may prepare an industry overview report on a regular basis. While the effectiveness of this activity depends on sufficient timely information available, this can be encouraged by supervisors. In some cases, ratings agencies may also be engaged in this task, although the sovereign rating ceiling can be an issue meaning that it may not be of commercial interest in some cases.

Supervisors or other authorities can act to enhance consumer education through the effective operation of customer complaint schemes, education programs, and 39
level. Given that our survey is cross sectional—i.e. our information about grades, facets of aspirations, and other information is at the same point in time—this bias may be particularly relevant. In our survey, grades that were given by schools are actually from the semester before students reported their aspirations, so the risk of reverse causality—the estimated outcome causing one of his supposed determinants—may be high. Another source of reverse causality may arise between the schooling outcomes and the measures of socioemotional skills we control for. For example, having higher grades may contribute to boosting self-esteem (Almlund et al. 2011).

**Endogeneity of controls.** Our measures of socioemotional skills (self-esteem, sense of belonging, growth mindset, and perseverance, among others), which we control for in regressions given their proven impact on schooling outcomes in other contexts, may contribute to shape aspirations and expectations and generate endogeneity. While there is little research so far on the topic, two studies in Italy and India find that self-efficacy, a belief that captures one’s confidence about his ability to successfully achieve goals, drives aspirations (Bandura et al. 2001; Roy, Morton, and Bhattacharya 2018).

**Omitted variable bias.** Our data may lack some important determinants of our outcomes of interest, such as students’ cognitive skills — mental abilities such as comprehension and reasoning— which are a great determinant of academic performance and school attainment, or other socioemotional skills we do not measure. In this case, we would be unable to observe relevant differences across individuals that may explain their differences in outcomes and misinterpret the latter as the result of the characteristics we measure.

**Measurement error** . There is a risk, as with every survey, that our survey measures people’s characteristics with error. For example, some students may understand differently subtle questions on aspirations. Besides, survey-based measures of mindsets and socioemotional skills are notoriously noisy, especially in low- and middle-income countries (Lajaaj and Macours 2019). School grades also have a degree of subjectivity.

**Selection bias.** Another caveat is that the relationships we explore only represent the population of students who attend public, secular schools,<sup>4</sup> which is selective given that it excludes youth who quit school earlier as well as those who attend private schools, religious schools, or technical and remedial schools. According to the Institute for Statistics of the United Nations Educational, Scientific and Cultural Organization (UNESCO), 81 percent of girls and 75 of boys of age to be enrolled in junior-

> 4 In the Indonesian education system these schools are known as _Sekolah Menengah Pertama Negeri_ .

10
consumption in China, a critical question is how the emission trading scheme would help substitute fossil energy sources with non-fossil ones.

The study aims to analyze the economy-wide impacts of the national ETS, and especially focuses on the distribution effect among different provinces and economic sectors. It investigates how much each province will reduce its GHG emissions by 2030 to meet the NDC; and how the provinces would trade their emission allowances under alternative schemes for initial allocations of emission allowances. It assesses the economic costs (impacts on GDP), household consumption and welfare, investment, commodity prices and international trade of goods and services.

Since the economic impacts of a carbon pricing policy are sensitive to the selection of a baseline, we used information from a bottom-up engineering model, TIMES, that is capable of representing detailed technologies, of correcting the baseline estimated by the CGE model. This is important because CGE models tend to inflate emission baselines. Researchers often adjust the inflation by using an autonomous energy efficiency index (AEEI) parameter. However, the selection of the index is arbitrary. Instead of doing so, we used a correction factor informed by Timilsina et al. (2019), which examines the deviation of the baseline when the CGE model is linked with a bottom-up TIMES model developed for China.

There exists a rich literature examining the ETS for controlling environmental pollution. The classic economic theory suggests that an ETS is cost-effective compared to command and control policy for limiting environmental pollution (Coase, 1960; Rose and Tietenberg, 1993). Investigating the ETS for controlling greenhouse gas emissions (GHG) in China, Jotzo and Loschel (2014), Bohringer et al. (2014), Zhang et al. (2014) and Wu et al. (2014) suggest that an ETS could be an efficient policy to reduce GHG emissions in China and thereby could help achieve its climate change mitigation targets. Hübler et al. (2014) assess the economic cost of an ETS in China.<sup>3</sup> Cui et al. (2013, 2014) design an ETS for China based on the carbon

> 3 It finds that the ETS required to lower China’s emissions intensity per GDP by 45% from 2005 level in 2020 would cause 1% welfare reduction from the business-as-usual (BAU) scenario.

3
$1.82 line results in a global poverty estimate that is 0.4 percentage points _higher_ than the World Bank (2014a, 2014b) estimate of poverty in 2011, and 0.4 percentage points _lower_ than the corresponding poverty estimate for 2030.

When considering the less optimistic growth scenario based on the 20-year average growth rate, the $1.82 line results in a global poverty estimate for 2030 that is a percentage point less than the projection to 2030 based on the $1.25 line. The poverty estimate starts out 0.4 percentage points higher than the World Bank (2014a, 2014b) estimate for 2011, but by 2030, the global poverty estimate based on the $1.82 line is 5.8 percent. The 2030 projection based on the $1.25 line and 20-year average growth rate is 6.8 percent. In short, even though the $1.82 line results in poverty estimates that are greater than those estimated by the $1.25 line, this ranking is reversed under both growth projections. The more rapid decline in global poverty seen under the 2011 PPPs is mainly because the global poverty profile in 2011 PPPs has a higher concentration of poverty in countries which are expected to grow relatively faster until 2030 than the profile based on the 2005 PPPs, assuming the 10 and 20 year historic growth rates.

Table 3 compares the projected regional profile of poverty at the $1.25 line (2005 PPPs) with the profiles based on the $1.82 and $1.92 lines (2011 PPPs) for three points in time: 1990, 2011, and 2030. The projections for 2030 are based on the country-specific 10-year historic average growth rates. Notably, projections for 2030 for all three lines suggest that there will be close to 400 million poor people in 2030 – the vast majority of whom will be in Sub-Saharan Africa (more than 85 percent across all three cases considered). For example, assuming countryaverage growth based on the 10-year history, the $1.82 line estimates that 362 million people will be poor, of whom, 317 million (or 88 percent) will be in Sub-Saharan Africa.

26