rafmacalaba/datause-encoder-data huggingface dataset:
- 8 -

**Table** 2: **Key Debt Indicators, 1985-88**

(Percentage)

||Debt Se|rvice R|atio|a/|Debt-Ex|port<br>Rat|io|a/|
|---|---|---|---|---|---|---|---|---|
||1985 1986|1987|198|8 b/|1985 1986|1987|1988|bl|
|Developing<br>Countries|23.1 24.6|22.6|21.5||163.5 189.0|180.7|170.|0|
|Low-income<br>Countries|12.7 14.8|14.0|14.|5|156.7 177.1|182.1|180.|0|
|Middle-income<br>Countries|24.8 26.3|24.5|23.0||164.5 190.8|182.2|175.|0|
|Memorandum Items|||||||||
|Sub-Saharan<br>Africa|24.2 21.7|<br>18.4|20.5||191.8 273.4|307.6|315.0||
|HiCs|33.3 36.7|30.6|35.5||146.3 308.8|309.9|295.0||

a/ Debt ratios are based on long-term debt and associated service payments (on a cash basis) and do not include short-term debt or arrears. b/ Preliminary estimates.

Source: World Debt Tables 1988-89 The reason for this i3 obvious. Even the larger banks with long-term commitments to developing countries face difficult choices. On the one hand, their collective interest would be to step up "defensive" lending, provided a relaxation of the financing constraint in major debtors can stimulate investment and promote growth. This would lower the risk of future interruptions of debt service and improve the quality of existing loan assets. On the other hand, it is also in each bank's interest not to take the lead, as even the largest lenders could have only a marginal effect on total resource flows to any given HIC. The implicit value any new loan would therefore immediately fall to the level of prevailing secondary-market prices. That situation replicates the "no collusion" prisoners' dilemma.

That dilemma is reinforced bv the gradual erosion of the banks' consensus in support of a concerted strategy. The banks' business strategies vis-a-vis HICs now vary widely, depending on relative exposure levels, the ability to accumulate sufficient loss provisions and opportunities<sup>to</sup> diversify activities in the global finar-ial market. Creditor attitudes are also influenced by national regulatory v tax regimes that govern the tax and capitalization status of loan loss provisions.

These considerations have reduced the number of active creditors. By and large, only major international banks with multinational corporate clients
Table 1: **Summary Statistics** This table reports the summary statistics of the key variables used in our analysis. All variable definitions are in the Appendix.

|**Variable**|**Obs**|**Mean**|**Std. Dev.**|**Min**|**Max**|
|---|---|---|---|---|---|
|ROIC Star|97,241|0.100|0.300|0.000|1.000|
|ROIC|97,241|-32.354|250.464|-2955.128|443.913|
|Markups|78,668|0.971|0.227|0.150|1.763|
|ROIC<sup>TOT </sup>Star<br>|93,438|0.100|0.300|0.000|1.000|
|ROIC<sup>TOT</sup>|93,438|12.943|27.207|-129.511|150.167|
|Log(Assets)|93,438|5.448|1.988|-6.908|12.906|
|Log(Age)|93,438|2.666|0.744|1.099|4.205|
|Markups<sup>TOT</sup>|83,842|1.182|0.338|0.226|2.635|
|Market Share|91,683|0.014|0.036|0.000|0.323|
|HHI|91,966|0.093|0.082|0.028|0.596|
|RMAN|46,997|0.382|0.323|-0.050|1.380|
|CPS|46,997|0.318|0.352|-0.706|0.962|
|NRCOG|46,997|-0.181|0.300|-1.076|0.281|

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<u>Table 13: Percent change in emissions in 2030 relative to the baseline, ctd.</u>

||<br>NMVB|<br>NMVF|<br>Nox|<br>OC|<br>PM10|<br>PM2_5|SO2|
|---|---|---|---|---|---|---|---|
|World|0.0|0.4|0.4|1.2|0.7|0.7|-0.3|
|BRI Area|-0.2|0.5|0.5|1.2|0.7|0.7|-0.3|
|Cambodia|6.5|15.9|5.1|5.6|5.2|4.2|7.7|
|China|0.0|-0.3|-0.1|0.3|0.1|0.1|-0.7|
|Indonesia|0.7|0.5|0.2|0.5|0.5|0.4|0.1|
|Lao PDr|2.3|24.4|2.8|1.2|1.1|0.7|5.8|
|Malaysia|-22.5|2.7|1.1|3.5|-3.9|0.5|-2.3|
|Philippines|-1.9|0.9|0.4|0.5|-0.1|0.2|-0.6|
|Thailand|-23.7|2.8|0.3|3.4|-6.6|-1.1|-14.5|
|Vietnam|-0.6|-0.3|2.4|1.8|1.3|1.3|1.5|
|Rest of East Asia|3.1|1.9|1.4|1.4|1.6|1.3|1.2|
|Bangladesh|18.5|4.9|5.5|18.1|16.7|16.0|8.0|
|India|0.1|-0.1|-0.4|0.4|0.2|0.1|-1.3|
|Nepal|0.5|0.4|0.5|0.5|0.5|0.5|0.6|
|Pakistan|12.0|3.5|7.9|14.5|13.3|12.7|10.3|
|Sri Lanka|3.0|1.9|1.7|2.9|2.8|2.9|1.0|
|Rest of S. Asia|1.4|1.5|1.2|1.8|1.7|1.7|0.3|
|EU ECA|0.2|-0.1|-0.1|0.4|0.2|0.2|-0.6|
|Russian Federation|1.4|1.1|0.9|1.3|1.1|1.0|0.8|
|Poland|0.4|-0.1|-0.1|0.3|0.2|0.2|0.0|
|Rest of E. Europe|1.1|0.9|0.2|1.7|0.6|0.7|-1.1|
|Kazakhstan|1.7|0.0|0.3|1.1|0.8|0.9|0.2|
|Kyrgyz Republic|-6.1|3.9|4.4|1.1|0.5|0.6|-6.8|
|Rest of C. Asia|1.2|0.4|0.8|0.9|0.8|0.8|0.2|
|Iran,Islamic Rep.|4.6|2.6|3.0|2.3|2.8|2.6|3.8|
|Egypt,Arab Rep.|0.2|-0.1|0.1|0.2|0.0|0.1|0.0|
|Turkey|1.3|0.8|1.1|1.1|0.7|0.9|-4.7|
|Rest of MENA|-1.7|1.4|1.2|1.2|0.7|1.0|1.0|
|Kenya|2.0|2.2|1.1|4.4|1.6|3.2|0.3|
|Tanzania|1.9|3.6|3.3|5.8|4.7|5.1|1.5|
|Non-BRI Area|0.5|0.2|0.2|1.0|0.8|0.8|-0.5|
|Ethiopia|-6.9|1.3|1.9|3.5|1.6|2.9|1.5|
|Rest of SSA|1.1|0.4|0.1|0.9|1.0|0.9|-0.3|
|Lat. Am. & Car.|1.3|0.1|0.0|0.7|0.6|0.6|-1.0|
|United States|0.6|0.1|0.0|0.7|0.6|0.4|0.0|
|Rest of High-inc.|0.9|0.2|0.7|0.9|0.4|0.6|-0.8|
|Rest of W. Eur.|0.2|-0.1|0.2|0.4|0.2|0.3|-0.4|

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<!-- Start of picture text --> 20% 20 -<br>NUbef of Cb -aor<br>li 0 6 3 ' 9 1 2 11 11 5 10 10 1 3 9 4 2 2 0 0<br>-30%! 1 , , I I I I , -- I I I I * I I * I<br>65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 8 1 82<br>Yea d Obseen<br>Wod {Bm*- 408 7<br><!-- End of picture text -->

# Fgure 4: trend ot Sals Forecasts.
gave to the incipient Chilean industry, a markedly foreign air.”(p 94)<sup>7</sup> Collier & Sater (1996) document that thirty-six of the forty-six dressmakers counted in 1854 were French, Americans installed the flour mills and Americans and British built the railroads. The port of Valparaiso became a major center of commerce dominated by foreigners. In 1860, of the 909 establishments surveyed by the government, 674 belonged to foreigners. For the country as a whole, the list of officers and members of the executive committee of SOFOFA, the principal organization of industrialists for the country, showed that that only three Spanish surnames accompanied those of the other 18 members of the directorate (Loveman, 1979, p. 193). Further, by 1920, as with mining more generally in Mexico, the vast copper enterprises were entirely foreign.

Two of Colombia’s subregions also show very strong immigrant dominance: In the dynamic port of Barranquilla 64% of establishments were foreign owned, 3 times what would be predicted by the male immigrant share, and tax records suggest that, as in Mexico, they were largest ones. Further, as in Chile, foreigners introduced steam technology for manufacturing and transport, revolutionizing navigation from the port to the interior of the country. As Becerra & Restrepo (1987) note, “the entrepreneurs of foreign origin occupied an indisputable place as pioneers across the 19th century, in the emergence of Barranquilla as the primary port of the country.”(p.35) High foreign participation is also notable in Santander where 50% of the most notable entrepreneurs were foreigners, roughly 8 times their representation in the population.

In Mexico, the industrial census shows that 50% of businesses were owned by immigrants or 26 times their share of the male population. As Annex 1 shows, the share of investment and production by foreigners is even greater, especially in mining, suggesting that our census data may be understating foreign influence in all countries. This is in line with Hansen (1971) who argues that industrialization was undertaken almost entirely by the resident

> 7 ... the lack of entrepreneurs and of qualified national workers gave to the incipient Chilean industry, a markedly foreign air. Anwandter and Meschner (Beer), Poppe (cotton), Tiffou (tanneries) Rudlof and Benedetti (shoes), Gleisner (furniture, tanning, soap), Kuppfer (smelting), Reiche (spinning), Sciaccaluga (canning), Goeckel (soap), Osthaus (rigging), are some of the names linked to the earliest manufacturing activities....p. 94.

8
All these political economy explanations rely on the assumption that institutions are weak. In particular, they assume that institutions are unable to constrain expropriation and discretionary redistribution by interest groups.

# **2.2 Country-level evidence**

This section discusses some of the empirical evidence on the socioeconomic impacts of resource abundance using country-level data. First, we examine the evidence on the resource curse. Then, guided by the analytical framework discussed in the previous section, we explore evidence on the possible explanations. Finally, we discuss the importance of institutions to understand the impact of natural resources.

## **2.2.1 Natural resource curse**

Sachs and Warner (1995, 2001) were among the first to formally explore the relation between resource abundance and economic growth. Using a cross-section of countries, they find that resource abundance (measured as the relative size of primary exports) is negatively correlated to gross domestic product (GDP) growth. Other studies, using similar methodology, also document a similar negative correlation between measures of resource abundance and growth (Gylfason, Herbertsson, and Zoega 1999; Leite and Weidmann 1999; Sala-i-Martin 1997).

The evidence of the natural resource curse is, however, far from conclusive (Lederman and Maloney 2007, 2008). Recent empirical work questions the robustness of the results to alternative specifications and measures of resource abundance. For instance, Alexeev and Conrad (2009) depart from the growth regression approach and use, as an outcome, income per capita. They show that an abundance of oil and mineral resources is associated with higher income per capita. They also fail to find support for a deterioration of institutions due to natural resources.

A fundamental critique is that the measure of resource abundance (usually the relative size of commodity exports) is endogenous. For instance, there may be other confounding factors, such as quality of institutions, which may affect both growth and size of commodity exports. In that case, the resource curse would just reflect the fact that countries with bad institutions have lower growth and are less industrialized, and thus more dependent on primary sectors.

8
source of advantage does not apply when we compare MENA’s performance with that of Sub-Saharan Africa since the latter had an even lower education stock (of 1.9 years) to begin with. In this case, MENA’s performance edge comes mostly from higher levels of public spending on education and better levels of undernourishment.<sup>10</sup>

**Table 5: Cross-regional differences in sample averages of determinants of schooling**

|Regions|Per capita<br>real growth|Average years of<br>schooling in|Education<br>spending per|Child<br>employment|Undernourishment<br>(%)|Urbanization<br>(%)|
|---|---|---|---|---|---|---|
||(%)|1970|capitaperyear|(%)|||
|MENA|2.3|2.3|252.3|10.4|7.0|55.3|
|EAP|2.9|3.9|74.8|10.6|15.6|32.6|
|ECA|1.9|6.0|197.4|10.1|7.8|61.3|
|LAC|1.7|4.4|219.6|8.1|11.8|71.3|
|SA|3.1|2.4|8.4|8.0|21.9|25.9|
|SSA|0.5|1.9|37.3|33.5|27.5|30.0|
|Sample|1.8|3.2|79.2|20.1|19.7|41.7|

Two additional observations may be made regarding MENA’s experience. Since we have data on public spending levels, we can calculate the increase in education stock per dollar spent. This is shown for 12 individual MENA countries as well as for regions in Table 6. It is clear from this that MENA achieved a low payoff: the education stock in MENA increased by 2.02 years over the 40-year period between 1970 and 2010 for every $100 spent per capita per year. This is well below the payoff achieved by such regions as South Asia, Sub-Saharan Africa and East Asia, though somewhat better than that achieved by Latin America. Individual MENA countries also do not perform well on this measure, the best rank achieved being 40 by Yemen. It would appear then that the increase in education stocks in MENA countries described in earlier sections of this paper were achieved at comparatively high cost. In addition, one should note that the quality of education achieved leaves much to be desired. The limited though growing body of comparative data on education quality shows most MENA countries clustered towards the bottom of the global distribution with scores below those to be expected on the basis of their per capita income levels (World Bank, 2013, p.172). While the challenge of building schools and getting children into them has been met successfully, that of converting all this schooling into productive learning remains to be met in the future.

> 10 Technically, these comparisons are being made in terms of predicted values rather than actual values.

10
# Business Cycles, Economic Crises, and the Poor: Testing for Asymmetric Effects

Pierre-Richard Agenor The World Bank Washington DC 20433

*1 would like to thank, without implication, Fernando Blumenschein and Francisco Ferreira for very helpful discussions and advice on the data for Brazil used in the paper, Joshua Aizenman, Alejandro lzquierdo, and Roberto Steiner for comments on a previous draft, and Nihal Bayraktar for excellent research assistance.
Two weeks after the registration process and before program implementation, enumerators went to schools to collect baseline information on social-emotional skills, fluid intelligence, and emotion regulation. To reduce the risk of fatigue among students, we collected these data over two days. On the first day, we asked students to complete the tasks used to collect data on social-emotional skills on a tablet. On the following day, the students completed the tasks used to collect fluid-intelligence and emotion-regulation data. In each school, we organized several classrooms in which students were scheduled to arrive in groups at specific times. Once the groups arrived, we gave the instructions to them and each student a tablet. Enumerators followed with students who had gave up questions.

Before the intervention commenced, we were given access to students’ administrative records, which included behavior at school and academic performance (specifically, math grades). Teachers submitted this information as printed reports for their students enrolled in the school. We collected, digitized, and cleaned all these paper reports for the students registered in the program and enrolled in the participating schools in El Salvador, Guatemala, and Honduras. One field coordinator per country was responsible for checking that the digitized data were consistent. Because of ethical protocol, we were unable to keep the records of students who did not consent to participate in the study.

We collected data on the characteristics of the participant schools from the 2018 Educational Censuses for El Salvador and Guatemala and from a school-level survey conducted by the authors for Honduras. We were able to obtain information on school location, enrollment, equipment available, and infrastructure, among other aspects. Last, we collected data on homicide rates at the municipality level from each country’s national police, which we use as a stratification variable.

**Short-term follow-up data collection.** As presented in the project timeline in Figure 3, the implementation of the ASP and intervention curricula was completed by the end of September 2019. We started short-term follow-up data collection in October 2019, while the students were still enrolled in school and before they took final exams, to maximize our ability to locate them. During this process, we gathered the same data (on social-

16
34

**Figure 2: Inequality and Vehicle Thefts per Capita**

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flexible enough to encourage initial development and attract investment. Tariff flexibility permits new entrants to appropriately handle risk and uncertainty.

As the first phase of investment mobilization and competitionfor the market in the Mexican distribution projects is now concluding, regulators and policymakers face enormous challenges in the next few years. One will be to consistently and transparently apply and enforce regulations and to coordinate among government agencies to successfully perform these tasks.

Another challenge is how to handle projected growth in Pemex's transportation systemestimated at an annual rate of 11 percent and spurred by growth in demand from electricity generators (annual growth rate of 14.89 percent). According to the permit granted by the CRE to Pemex for transporting natural gas, Pemex will meet this new demand by expanding its pipeline capacity, but there could still be bottlenecks during peak periods (table 3).24 Especially important is the 1,597 kilometer-long pipeline system in the Reynosa and Monterrey operating sectors, where a huge increase in demand is expected and where two of the three compression stations are obsolete.<sup>2 5</sup>

**Table 3. Maximum Average Transport Capacity of Pemex's National Pipeline System**

|Units|Year 1|Year 2|Year 3|Year 4|Year S|
|---|---|---|---|---|---|
|MMGcalUYear|421.5|445.3|445.3|459.5|459.5|
|MMCFD|4,824|5,096|5,096|5,259|5,259|

_Source:_ Comisi6n Reguladora de Energia (1999).

Government policy for ensuring sufficient pipeline capacity to clear gas markets is premised on consumers paying Pemex for expansion of the pipeline system. This is presumed to generate enough savings to gas consumers that they would be willing to pay for such investment.<sup>26</sup> According to Pemex's transportation permit, pipeline expansion can be financed in two ways. A "rolled in" methodology can be applied when the expansion will benefit all consumers; an incremental cost method is applied in other cases.

Perhaps the greatest issue in the immediate term will be the evolution of competition _in_ the market. In the Directive on Firsthand Sales the CRE identified some regulatory mechanisms for Pemex gas marketing activities. Asymmetry of information is most pronounced in this area. The many strategic games that Pemex can play with contracts for different types of consumers will be difficult for a small regulator to cope with.

24 These calculations are based on estimates of injection and extraction requirements at each node (Comisi6n Reguladora de Energia 1999, appendix 3.1), flow and capacity technical information for each transportation sector (annex 3, appendix 3.1 and 3.2), repowering needs at each compression station (appendix 3.1), and investment needs for expansion of the pipeline network (annex 6.2.1).

**25** There are three compression stations. Two are old "reciprocating" compression stations, "Ojo Caliente" and "Santa Catarina," with more than 30 years of operation which experience huge drops in pressure and low volumes. In the Reynosa sector a "turbo compression" station was constructed in 1997. 26 Brito and Rosell6n (1999).

28
**Table A1.3: Bias in beta estimation due to investment horizon length**

|**Type**|**Assumed investment**|**Assumed investment**|
|---|---|---|
||**horizon is too long**|**horizon is too short**|
|Aggressive stock (J > 1)|Beta is over-estimated|Beta is under-estimated|
|Neutral stock (J3=1)|Beta is correctly estimated|Beta is correctly estimated|
|Defensive stock**(**<1)|Beta is under-estimated|Beta is over-estimated|

The authors argue that the true horizon for most investors is likely to be more than a year, thus estimates based on a period length shorter than this will tend to underestimate high beta values and over-estimate low ones.

# **A1.3.4 International differences in interval effects**

The biases in estimated beta values for different national markets are unlikely to be of the same degree and may not even be in the same direction. First, the availability of quotation data for some markets should reduce misestimation in these cases, while serious biases remain in other markets. Second, differences in transaction costs and trading methods may affect the extent of adjustment delays and non-synchronous trading problems, such that the degree of autocorrelation in market returns, varies between countries.

Third, there is some evidence that the size of the relevant stock market affects the seriousness of the intervalling effect. Berglund et al. (1983)13 find the length of the adjustment process to be related to the total turnover of the exchange rather than the trading frequency of the particular stock, such that adjustment takes longer in a small stock market. Martikainen and Perttunen (1991)14 demonstrate that, contrary to the findings of Handa _et al._ (1989), the size effect tends to increase rather than decrease with the return interval in a thin stock market.

> **13 Berglund,** Wahlroos and Ornmark (1983), 'The Weak-form Efficiency of the Finnish and Scandinavian Stock Exchanges', _Scandinavian Journal of Economics,_ 85, 521-530.

**14 Martikainen** and Perttunen (1991), 'Return Intervals, Systematic Risk Estimates and Firm Size', _Economic Letters,_ 36, 311-315.

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