rafmacalaba/datause-encoder-data huggingface dataset:
Brunnermeier, Markus, Andrew Crockett, Charles Goodhart, Avinash D. Persaud, and Hyun Shin 2009, “Fundamental Principles of Financial Regulation,” _Geneva Reports on the World Economy_ no. 11, Preliminary Conference Draft, January.

Buiter, Willem H. 2007, “Central banks as market makers of last resort 5: a restatement,” September 2, FT.Com Maverecon blog.

Buiter, Willem H. 2008, “Central banks and financial crises,” Paper presented at the Federal Reserve Bank of Kansas City’s symposium on “Maintaining Stability in a Changing Financial System,” at Jackson Hole, Wyoming, on August 21-23, 2008.

Daniel, K., D. Hirshleifer, and A. Subrahmanyam 1996, “A Theory of Overconfidence, Self-Attribution, and Security Market Under-and Over-reactions,” Working Paper, Kellogg School of Management.

Diebold, W. Jr. 1977, “Introduction: Money and the Structure of International Politics,” in _Alternatives to Monetary Disorder_ . Hirsch, F., M. Doyle, E. Morse, eds., New York: Council on Foreign Relations.

Dobson, Wendy, and Paul R. Masson 2009, “Will the Renminbi Become a World Currency?” _China Economic Review_ , 20 (March): 124-35.

Froot, K. A., P. G. J. O’Connell, and M.S. Seasholes 2001, “The Portfolio Flows of International Investors”, _Journal of Financial Economics_ , 59:151-93.

Goldberg, Linda, and Deborah Leonard. 2003, “What Moves Sovereign Bond Markets? The Effects of Economic News on U.S. and German Yields.” _Current Issues_ (Federal Reserve Bank of New York) 9 (9).

Griffin, J. M., F. Nardari, and R.M. Stulz, 2004, Daily Cross-Border Equity Flows, Pushed or Pulled? _Review of Economics ad Statistics_ 86:641-57.

Group of Thirty 2009, “Financial Reform: A Framework for Financial Stability,” January 15, 2009.

IIF 2008, “Final Report of the IIF Committee on Market Best Practices,” Washington, DC: Institute for International Finance, July.

Masson, Paul R., and John Pattison 2009, _International Financial Policy Reform and Options for Canada: Think Globally, Act Locally_ , Ottawa: The Conference Board of Canada, February.

Seasholes, M.S. 2004, Re-examining Information Asymmetries in Emerging Stock Markets. Unpublished Working Paper, University of California, Berkeley, CA.

Singer, David Andrew 2004, “Capital Rules: The Domestic Politics of International Regulatory Harmonization.” _International Organization_ 58(3):531-565.

Stulz, R. M. 1999, International Portfolio Flows and Security Markets in M. Feldstein (ed.), _International Capital Flows_ , University of Chicago Press, Chicago, IL, 257-93.

26
prised between 2005 and 2010.<sup>12</sup> Of those, 3,180 (61%) belong to households which were deemed eligible for the _Oportunidades_ benefits - i.e. the value of their proxy-mean score is greater or equal than 0.69. Among eligible students, 2,161 (68%) are reported receiving at least one payment from _Oportunidades_ before applying to the COMIPEMS system.<sup>13</sup> As a result of a process of program expansion in urban areas which took place in the end of 2008, a very small fraction (1.2%) of ineligible applicants in our sample are reported receiving some program benefits before applying to the COMIPEMS system.

For the median household in our sample, the _Oportunidades_ transfer is between 27 and 28 percent of total household income. The large size of the income shock in our sample likely reflects the selection induced by the participation into the COMIPEMS system. When compared to the rest of the families in the ENCASEH survey, those with at least one child who applies for upper secondary education have in fact more children currently enrolled in grades 3-12. In fact, transfer amount for program eligible families who are not in the COMIPEMS sample are substantially lower: between 14 and 16 percent of total household income for the median household in our sample.<sup>14</sup> Only 9 percent of the COMIPEMS applicants in our sample list a vocational program as their first option, while 44 percent and 47 percent of the applicants respectively opt for the technical and the academic track. On average, when compared to the latter group of students, those who prefer a vocational education tend to perform worse in school (as measured by the score in the admission exam and in the cumulative grade point average in lower secondary), and they tend to come from more disadvantaged socio-economic backgrounds (as measured by parental education, the _Oportunidades_ eligibility score and the relative share of those who report to be working - with or without a wage).

> 12 Only a small percentage (about 3%) of students who have filled the ranking of their preferred options, do not take part in the COMIPEMS exam. We could not geocode the address of residence for roughly 10% of applicants. However, neither sample attrition rates vary systematically around the program eligibility threshold.

> 13Program take-up rates are fairly high when compared with the corresponding figures reported in the existing evaluation studies of the urban component of _Oportunidades_ [Angelucci and Attanasio, 2009]. Previous studies used the urban evaluation surveys (ENCELURB) which entails roughly 18-24 months between program inception and observed outcomes, whereas we observe eligible households for up to six years after program inception. In fact, take-up rates in our sample increase from 40% in 2005 to 79% in 2010.

> 14Those figures are in line with previous studies that considered the urban component of the _Oportunidades_ program [Angelucci and Attanasio, 2013].

9
: The next section, titled “Governance,” evaluates progress achieved in the area of institutional reform. This section deals with the way governments manage their resources.** In this respect, Latin American countries have generally had two deficiencies, which the current wave of reforms are attempting to remedy. The first is that a large share of government resources was spent on a bloated and ineffective bureaucracy. Public employment was used to reward political loyalties, and in order to accommodate the surplus of employees, new government departments were created, tasks were duplicated, and bureaucratic paper work was made more lengthy and complicated. The recent empirical-growth literature provides substantial evidence that in countries whose government spendsa large share of its revenues to maintain a large bureaucracy, economic-growth performance suffers. Using pooled crosscountry and time-series information, these empirical studies® find that an increase in government consumption, of which wages and salaries to public employees are the largest component, negatively affects the rate of per capita GDP growth. In order to measure the progress achieved by Latin American countries in this respect, the ratio ofwages and salaries of government employees io primary expenditures is considered. The level of government used in the evaluation is the central government, except in the case of Argentina, Brazil and Colombia, countries for which the general government is used. Given the decentralized nature of these countries’ governments, and the fact that fiscal reform in local governments there is not proceeding at the same pace as in the central government, it is essential to consider general government as the unit ofanalysis for those countries.. As Chart 12 shows, a few countries in the region -- namely, the Dominican Republic, El _ Salvador, Peru, and Uruguay -- have shown in the last ten years a clear tendency to spend less for the services of the bureaucracy. Chart 12 also shows that there is considerable variation in the share of government primary expenditures devoted to public employees’ salaries, from nearly 50 percent in the Bahamas, Costa Rica, and Ecuador in the mid-1990s to below 20 percent in Chile and Peru, in the same period. Clearly, the salary-to-expenditure ratio in public administration depends not only on whether the bureaucracy is bloated, but also on structural characteristics such as whether the

> *4 ‘The distinction made between appropriate government institutions and policies for proper management of public resources is conceptual, and thus, artificial. The distinction is made here for the ease of exposition and to. provide emphasis on different aspects of reform in the public sector. * See Barro and Sala-i-Martin (1995); Barro and Lee (1994); Caselli, Esquivel, and Lefort (1996); and Easterly, Loayza, and Montiel (1997).

19
Public engineering efforts to reduce disaster risk have also demonstrated costeffectiveness. A World Bank appraisal of a flood protection project in Argentina suggested an internal rate of return of 20 percent, and a range of other flood and hurricane protection projects in the developing world (in countries including the Philippines, Argentina, Peru, Indonesia, China and Brazil) have estimated cost-benefit ratios of two and above (Moench et. al. 2007, see also OECD, 2008, Healy, 2008, Mechler, 2005).<sup>27</sup>

# **The Role of Irrationalities, Market and Government Failures**

Retrofit of private homes against earthquakes may have some of the lowest returns in the arsenal of disaster risk reduction measures, then – but even these measures may be priority investments in comparatively wealthy communities at high risk from large earthquakes and low existing building standards. And other mitigation measures involving public construction protecting against more common disaster risks, for example, carry higher benefit-cost ratios. Yet many such measures remain unimplemented.

It is unlikely that rational, fully informed calculations of the costs and benefits of the whole range of mitigation measures are the sole (or perhaps even the primary) reason for their limited adoption by individuals or governments, then. Greater expenditure on mitigation measures will make more sense in areas where natural disasters are particularly common, and yet the depressing result of cross-country analysis is that, allowing for income and other factors, areas repeatedly exposed to disasters do not see lower per-disaster mortality rates, as we have seen. This suggests mitigation measures are underutilized even where they would carry the highest returns.

It may be that the rational agent model fails with rare catastrophic events, and that consumers and citizens do not correctly evaluate the costs and benefits of (in)action regarding ‘acts of God’ (Praeter and Lindell, 2000). A number of common irrational decision-making devices used by individuals can impact the level of risk-reduction effort undertaken. Experimental and natural observation suggest that people use budgeting heuristics which pressure against mitigation spending, that they display biases in intertemporal planning and chose inaction in the face of uncertainty, and that they ignore the risks of an event (however catastrophic it might be) if the event is seen as below some threshold of probability (Camerer and Kunreuther, 1989). It is very difficult to calculate the benefits accorded by mitigation as we have seen, suggesting an information gap. Combined with the human tendency to remain passive in the face of uncertain events, this may encourage inadequate mitigation response. For individuals and businesses, there may be excessive faith in government mitigation measures, which further reduces their own incentive to act (Box 10).

> 27 Although studies do suggest that further flood control measures in Japan would carry very low benefitcost ratios (OECD, 2008).

17
consumed by the rich but also by the middle-classes and some poor in _rich_ countries;<sup>16</sup> second, income of rich people in each individual country that is missed out by surveys (for example, property incomes). All actual recipients of these incomes are globally-rich because the middle-class and even the poor from the rich world are in the top quintile of global income distribution, but the difference between the two aggregates is spread much more widely: some of it is imputed to the poor in the poor countries which, we know, receive none of it.

Consider the following example. Let the poverty line be $PPP1 per capita per day. Let average per capita disposable income from surveys of several groups of the poor in India may be $0.75, $0.8, $0.85. Now, suppose (very realistically) that India's GDI is some 35 percent higher than disposable income. We know that most of these 35 percent is received by the rich, either because they benefit from publicly-funded education or because they fail to report their property incomes. What the authors (in particular, Sala-iMartin, 2002 and Bhalla 2002) then do is to multiply incomes of the poor by the factor of 1.35. Then, suddenly, none of them is any longer poor: they have all crossed the poverty threshold!<sup>17</sup> But if we decide that “income” in global studies should be the same concept as in national studies of inequality—that is household per capita disposable income—the problem is not solved yet. This is because national definitions of survey income are very different, and the more countries we include, the more different they become. A huge effort, conducted by Luxembourg Income Study, has gone into standardization of national definitions. A similar project is underway at the World Bank using Living Standards Measurement Surveys (LSMS). Yet the standardization covers only a small portion of all countries and surveys. The main differences arise in the treatment of selfemployed income (what are business expenditures for the self-employed?), valuation of

> 16 Disposable household income retrieved from surveys in West European nations amounts to about 60 percent of GDI. A bulk of that difference is explained by health and education consumption. Publiclyfinanced health and education as share of GDI is much less in poor countries.

> 17  On the additional pitfalls caused by the use of averages from national accounts and distributions from household surveys, see Ravallion (2000), Deaton and Dreze (2002), and Deaton (2003).

10
continue. Secondly, in the absence of pollution intensity data from Vietnam, we have used pollution measures from the U.S. as proxies (as suggested by previous IPPS studies). Should pollution intensity data from Vietnam become available, it would be useful to re-examine the issue using Indian measures of pollution intensities.

Despite these caveats, this study has highlighted important gaps in the environmental policy implementation in Vietnam and enables us to make useful recommendations. In order to make specific policy recommendations on future steps, we need to identify the manufacturing sectors that have resulted in greatest increase in water pollution intensive output and toxic pollution intensive exports. Annex 3 shows the important water pollution intensive sectors as: iron and steel, non-ferrous metals, industrial chemicals, rubber and leather products. These sectors are also considered significant contributors for toxic pollution (in addition to ceramics) and consistently rank high based on the Linear Acute Human Toxic Intensity (LAHTI)<sup>13</sup> . Analyses of Vietnamese exports shows that the sectors have shown highest increase in exports are: textile (91 percent), leather (49 percent), and rubber products (26 percent)<sup>14</sup> . Of these the textile industry is also large consumer for industrial chemicals. Therefore, increased textiles exports seems to have also fueled a simultaneous increase in industrial chemicals. Similarly, export revenues from craft villages have increased significantly in recent years to the tune of almost half a billion US dollars a year. These are again a major sources of toxic and water pollution. It is thus not surprising to note that Vietnam’s exports are getting dirtier over time since its export specialization has moved away from more tradition oil and other primary commodities towards manufacturing especially leather and textile industries. The results also suggest that foreign direct investment in Vietnam reflects a similar trend with toxic intensive heavy and light industries attracting most FDI.

These findings suggest that while trade liberalization measures have been pursued to promote economic growth in Vietnam, they have led to some potentially adverse environmental consequences. These results suggest that there is a trade-off between the

> 13 Wheeler, et. al. (1994)

> 14 Source: International Trade Statistics, ITC: http://www.intracen.org/menus/countries.htm

25
_27_ _Annex A. Mehodology_

# _Estimating deaths by specific cause_

To estimate new regressions for 22 specific causes of death, data for around 1970 and around 1985 were pooled. As noted earlier, Latin America and Caribbean countries had no data for some causes for 1985, requiring the inclusion of 1970 data. Altogether, 1970 data for 65 countries (34 of them developing, mostly Latin American) and 1985 data for 69 countries (38 developing) were used. Because of the number of causes for which estimates could not be produced, the U.S.S.R. and India were excluded, but China was included. Data quality varies for the countries included, but imposing a more rigorous standard would bias the sample strongly toward developed countries.

For each country, mortality rates by cause were first adjusted to correspond to overall mortality levels in the World Bank estimates and projections. Rates based on fewer than 10,000 people in the age-sex group were excluded. Three equations were then estimated for each disease in each age-sex group: a quadratic specification, where the rate for the specific cause depended on the rate for the major cause and the square of this rate, as well as on a dummy variable for data year; a corresponding linear specification; and a specification in which the rate for the specific cause depended only on two, dummy variables, for developing country status and data year.

If the quadratic term achieved a 5 percent level of significance, the quadratic equation was chosen; if not, and the linear term achieved a 5 percent level of significance, the linear equation was chosen; and in all remaining cases, the dummy variable equation was chosen. Of the 264 final equations, half were quadratic, a third linear, and the remainder dummy variable equations. The dummy vanable for data year had a significant effect in 20 percent of the equations chosen.

Mortality rates for some specific causes of death were predicted better than rates for others. R<sup>2</sup> did vary much more by cause than by age-sex group, permitting the grouping of equations by cause:

- a. mean 12 over .70: diarrhea, acute respiratory infection, other cardiovascular diseases, and unspecified causes

- b. mean _11_ between .35 and .60: tuberculosis, measles, chronic obstructive pulmonary disease, other infectious and parasitic diseases, cerebrovascular disease, nephritis/cirrhosis/ulcers, miaonutrient disorders, and malnutrition

- c. mean R<sup>2</sup> between .20 and .25: intestinal parasites, ischemic heart disease, and diabetes

- d. mean R<sup>2</sup> below .20: polio, malaria, yellow fever/dengue/encephalitis, schistosomiasis/filariasis, mental disorders, and oral health diseases.

The last group also accounted for almost all the dummy variable equations. Mortality rates for causes in this group did not covary with mortality levels for broader categories, and developed or developing country averages were essentially applied for these causes.
37 interpretation of this finding is unclear; in future work we hope to clarify the interpretation of this finding further.

Our empirical results are presented in Table I. As is true of most of our empirical work, the coefficients are estimated in a simple regression of the log of the ratio of credit (or quasi-money) on a constant and the log of real per capita income measured in American dollars. Throughout, our focus is on the slope coefficient. The actual data is displayed in scatterplots of the log of the credit/income ratio against the log of real income per capita (with bordering univariate distributions and box-and-whiskers plots) in the accompanying figui:e. The data is displayed in three ways: 1) pooled across all years and developing countries; 2) pooled only across regions; and 3) pooled only across specific years. Pooled data for the ratio of quasi-money to income is also displayed in the figure.

The first six rows of Table I describe our benchmark results. The slopes are positive and significantly so, in both economic and statistical terms. We estimate that a one percent increase in real per capita income is aesociated with an increase in the ratio of private credit to GDP of 0.42%; the comparable increase in the ratio of quasi-money to GDP is similar, 0.56%. 42 The intercepts of both equations are significantly negative at conventional significance levels (this is also true in virtually all perturbations of the basic equations).

These results are quite robust to a variety of perturbations of the basic framework; some of the sensitivity analysis is explicitly tabulated in Table I. For instance, the finding of a positive and significant slope is robust to: the exact measure of credit used; sub-sampling by region or year; accounting for country-specific "fixed effect" means; and inclusion of yearspecific time dummies, a linear trend, or inflation. We have also taken non-overlapping five year averages of our data to smooth out business cycle

> 42 The results here are consistent with Hanson and NeaL (1986), who found in a cross-section study of 36 LDCB that the quantity of Liquid assets relative to GDP varied positively with GDP. Our interpretation of this relationship -- which emphasizes the development of intermediation -- is somewhat different though. For this reason, we restricted attention to the non-Mi component of M2.