rafmacalaba/datause-encoder-data huggingface dataset:
8 electricity. Countries with more imported natural gas in their energy mix before the crisis were more exposed to the natural gas price shocks that followed the Russian invasion of Ukraine because of supply disruptions to global gas markets. In comparison, countries with little gas consumption were less affected by supply decreases, as were countries able to rely on domestic gas production. This exposure measure is supported by the data in Figure 2 demonstrating the positive relationship between country-level gas import dependence in 2019 and the rise in electricity prices between 2019 and 2022.

Establishment-level pre-crisis energy intensity is constructed using data on firm-level energy consumption from the Carbon Disclosure Project (CDP) divided by revenue data from Factset in 2020.<sup>9</sup> Energy consumption is measured as fuel and purchased steam, heat, electricity, and cooling consumption in megawatt-hour (MWh) equivalents and revenue is measured in millions of 2020 US dollars. Establishments that belong to the same firm, but are located in different countries, have the same energy intensity in our data.

# **2.3 Firm-level data and matching of datasets**

We match establishment-level job vacancies data to firm-level data on energy consumption from CDP and balance sheet information from Factset (more details are provided in Supplementary Appendix Section A.3). Our final dataset is at the level of establishments defined as firm-countrysubnational region triplets, following Acemoglu et al. (2020).<sup>10</sup> CDP includes information on energy consumption during 2020 for 3,598 firms operating in the 16 countries in our sample. We use information available from CDP on each firm’s ISIN or CUSIP identifier code to match these firms to Factset. Factset is a private company that collates data on ‘firm-level entities’ from financial statements and other sources for publicly traded companies as well as data on entities’ supply chain relationships.<sup>11</sup> We use fuzzy matching methods to identify Factset entities in the Lightcast data on job open-

> 9Annual energy consumption is available only for 2020. While this value may have been impacted by the economic effects of the COVID-19 pandemic in 2020, we focus on energy intensity, i.e. energy consumption relative to sales, and since both are measured as of 2020 we believe this ratio is likely relatively constant across years.

> 10Acemoglu et al. (2020) define establishments of a firm in Lightcast (previously called Burning Glass) data as the collection of firm job vacancies in each US commuting zone. We define subnational regions as the highest-level administrative subdivision in each country, Territorial Level 2 (TL2) in OECD (2021).

> 11These Factset firm-level entities are defined as _de jure_ corporate institutions (e.g., firms and affiliates).
# **4. Findings**

# **4.1 Transfer, Scholarship, and Public Works Programs**

# _4.1.1 Education and Labor Market Outcomes_

The most studied form of SP programs that benefits young people are conditional cash transfer programs (CCTs). For some of these programs, especially in Latin America, sufficient time has passed for long-term (LT) evaluations. A 2016 review of CCTs – covering studies from 10 countries with follow-up durations between four and 13 years – has found that they cause higher levels of schooling among beneficiaries who were exposed to these programs when they were schoolaged, but yield mixed impacts on learning, labor force participation (LFP), and income (Molina-Millán et al. 2019). While the focus of this paper is youth, there is also a substantial literature on the impacts of CCTs on primary-school aged children (see Box 1).

5
- 28 -

Table 7: Mean Percentage of Total Instructional Time Devoted to Selected Subjects in the Primary School Curricula of Less-Developed Countries by Gross Primary Enrollment Rate (Standard deviations in parentheses) Gross Primary Enrollment Rate:

||Less th|an 80Q|Greater t|han 8p %|
|---|---|---|---|---|
||N|=49|N=|61|
|Combined Lang.<br>|36.3<br>|(9.1)<br>|34.6<br>|(9.6)<br>|
|National Lang.|24.3|(13.7)|20.9|(12.4)|
|LocalLang.<br>|1.4<br>|(5.2)<br>|1.1<br>|(4.1)|
|Forcign Lang.|1.9|(2.9)|1.8|(3.9)|
|Official Lang.|8.0|(13.6)|9.3|(13.5)|
|Mathematics|18.5|(3.4)|17.9|(3.6)|
|Science|7.1|(3.9)|8.0|(3.4)|
|Comb.Social Sci.|8.8|(3.6)|8.2|(4.2)|
|Social Studies|4.2|_(5.1)_|_5.1_|(4.7)|
|History<br>|1.6|(1.8)|1.1|(1.9)|
|Geography|1.7|(1.9)|0.9|(1.6)|
|Civics|1.1|(2.1)|1.0|(1.9)|
|Comb.Moral|_5.1_|(6.3)|5.3|(4.4)|
|Religion|4.6|(6.5)|4.2|(4.8)|
|<br>Moral Ed.|0.4|<br>(1.1)|1.2|(2.6)|
|Ae;thetic Ed.|10.4|(4.2)|8.8|(4.4)|
|Music|4.1|(2.0)|3.4|(2.6)|
|Art|6.4|<br>(3.1)|_5.3_|(2.9)|
|Physical Education|8.1|(3.2)|6.2|(3.3)|
|Hygiene|0.8|(1.5)|1.8|(2.3)|
|Comb.Voc.Ed.|3.1|(3.8)|6.0|(5.4)|
|Manual Training|_1.5_|(2.7)|2.9|(4.0)|
|Agricultue|0.6|(1.4)|1.4|(2.6)|
|<br>Domestic Sci.|0.9|<br>(1.7)|1.3|(2.2)|
|Vocational Ed.|0.0||0.0||
|Business|0.0||0.1|(0.2)|
|Other|2.1|(4.0)|2.6|(4.3)|
groups of variables in the aggregate or extended model. Information deemed ‘superior’ and that is related to any group of elements in either the aggregate or extended accounts is a candidate for a linear constraint. Since both interregional and multi-regional economic accounts are comprehensive and detailed, there are many opportunities to introduce such constraints. A few general guidelines are notable.

Both the aggregate and extended accounts describe flows of payments and products in the form of a matrix with known adding-up and consistency requirements. Any information used to formulate new constraints—either equality or inequality linear constraints—can greatly diminish the feasible solution set of the calibration procedure. However, new constraints that are nonbinding add no information to the problem, but do increase the computational burdens.

Where and how information is used to formulate constraints depends on many factors. For example, the U.S. Government has published state measures of farm productivity that include estimates of purchased farm inputs by state for broad input categories. A pro-rated version of this data could form the basis for additional linear constraints for agricultural sector I-O flows in the model. Other restrictions could be designed to replicate certain highly reliable economic statistics that can be formed by special groupings of certain flow statistics contained in the account being estimated. Although such information must be carefully compiled, their incorporation in the form of constraints will improve the estimation accuracy greatly.

# **5. CONCLUSIONS AND DIRECTION FOR FUTURE RESEARCH**

This study constructed a mathematical programming model to estimate interregional trade patterns and input-output accounts based on an interregional accounting framework and initial estimates of interregional shipments in a national system of economic regions. The model is quite flexible in its data requirements and has desirable theoretical and empirical properties. An empirical test of the model using a 4-region, 10-sector example aggregated from a global trade database shows that the model performs remarkably well in discovering the true patterns of 23
<!-- Start of picture text --> 10% —Revenues<br>8%<br>6%<br>4%<br>2%<br>0%<br>-2%<br>2012 2015 2018 2021 2024<br><!-- End of picture text --> <!-- Start of picture text --> = Direct taxes<br>= Mining sector dividends<br>= Export taxes<br>25 ® Other indirect taxes<br>20 = Import taxes<br>16<br>1.0<br>0.50.0 - 1<br>0.5<br>2012 2014 2016 2018 2020 2022 2024 2026<br><!-- End of picture text -->
also have some direct impact on the real exchange rate. For example, policy reforms that improve productivity in the nontradeables sector might contribute to a real depreciation, and in addition prompt more aid inflows from donors that tie aid to policy performance, implying that E[aitεit] ≠0 . In this case, OLS estimates of the local projections regressions will not deliver a consistent estimate of the effects of aid on the real exchange rate at various horizons.<sup>2</sup> We address this endogeneity problem using an instrument developed in Kraay (2012b). The instrument exploits the fact that there are long lags between the approval and eventual full disbursement on individual aid projects in developing countries that are financed by concessional loans from official creditors. Such concessional loans are a major vehicle for providing aid to developing countries. They typically finance specific aid projects that take many years to implement, and the disbursements usually are tied to the stages of project implementation, rather than disbursing all at once upon loan approval. These disbursement delays can be used to isolate a component of disbursements in a given country-year that is associated with project and loan approval decisions made in previous years, before contemporaneous macroeconomic shocks are known.

The key identifying assumption is that, while loan approval decisions may respond to current and past macroeconomic shocks, they do not respond to future shocks. If, in addition, loans disbursed as scheduled at the time of approval, then subsequent disbursements on these loans would be uncorrelated with contemporaneous macroeconomic shocks. However, as discussed in more detail in Kraay (2012a,b), this additional assumption is not very plausible, as disbursement decisions on existing loans are made in real time, and may very well respond to contemporaneous shocks. Instead, we rely on a synthetic measure of predicted disbursements, which combines actual loan approvals with "typical" disbursement rates for other loans from the same creditor, in the same region and decade. As a result, the only country-specific variation in predicted disbursements comes from loan approvals from previous years. Conditional on the identifying assumption that these do not respond to future shocks, predicted

> 2 Another potential source of endogeneity is the correlation between the lags of the dependent variable and the unobserved country effect in the error term, which we control for using country fixed effects.  This correlation becomes negligible as the time series dimension becomes large.  Monte Carlo evidence in Judson and Owen (1999) suggests a bias in the fixed effects estimator of only about 1-3% of the true value of β when T= 20 (their Table 1). While they do report larger biases in the fixed-effects estimator of the coefficient on the lagged dependent variable of 12-17% of the true parameter value, this parameter is not our main interest.  In our setting, the median number of time series observations per country is T= 28

7
# 6. BIBLIOGRAPHY

- Anastassopoulos, Jean-Pierre C., "The French Experience: Conflicts with Goverm-nent," in Raymond Vernon and Yair Aharoni, eds., _State-Owned Enterprise in the Western Economies._ London: Croom Helm, 1981. pp. 99-116.

- Banks, Jeffrey and R. Sundaram, "Long-lived Principles, Short-lived Agents," University of Rochester, _Rochester Center for Economic Research Working Paper 353,_ July 1993.

- Bates, Robert, _Markets and States in Tropical Africa: The Political Basis ofAgricultural Policies._ Berkeley: Univ. of California Press, 1981.

- Besley, Timothy and Anne Case, "Does Electoral Accountability Affect Economic Policy Choices? Evidence From Gubernatorial Term Limits," _Quarterly Journal of Economics,_ August 1995, pp.769-798.

- Bolzico, Javier and Maria Figueroa, "Clasificacion de Deudores y su Previsionamiento", _Novedades Economicas,_ Junio 1994, pp. 6-7.

- Caprio, Gerard, "Bank Regulation: The Case of the Missing Model" _World Bank Policy Research Working Paper_ 1574, January 1996.

- Caprio, Gerard and Daniela Klingebiel, "Bank Insolvency: Bad Luck, Bad Policy, or Bad Banking?" paper presented at the World Bank's Annual Conference on Development Economics, 1996.

- Central Bank of the Republic of Argentina, "Main Features of the Regulatory Framework of the Argentina Financial System," mimeo, September 1996.

- Central Bank of the Republic of Argentina., _Boletin Monetario and Financiero,_ December, 1996

- Clarke, George R.G. and Robert Cull "Why Privatize? The Case of Argentina's Public Provincial Banks," Worlld Bank mimeo, 1997.

- Cox, D. "Regression Models and Life Tables." _Journal of the Royal Statistical Society B,_ 1972, 34, pp. 187-220.

- Cox, Gary W. and Matthew D. McCubbins, "Structure and Policy: The Institutional Determinants of Policy Outcomes," mimeo, October 1996.

- Cull, Robert. "Financial Sector adjustment Lending: A Mid-Course Analysis," World Bank mimeo, July, 1997.

- Donahue, John D., _The Privatization Decision._ New York: Basic Books, 1989.

24
15 or - the direction of the estimated impact over each horizon. Asterisks identify results that are statistically significant at the 10% level or better. We now discuss the results in turn.

# 4.2.1 _Money and fiscal deficits_

An expansion of money balances (measured in dollars at the official exchange rate) raises the premium in the shon run in all cases. In Sudan, Turkey and Mexico, it raises the premium in the long run as well. These results imply that money growth in excess of the rate of official depreciation will raise the parallel premium. Given the tight link between government deficits and money growth in many of these countries, this suggests that a major reason for persistently high premia in some of the case study countries may be inconsistency between the deficit and exchange rate policy.

As discussed in Lizondo (1990), the theoretical literature is nearly unanimous in predicting that an increase in the fiscal deficit, other things equal, leads to an increase in the premium.'<sup>2</sup> Figure 4 uses a larger cross-section to confirm that countries that on average have large budget deficits also tend to have large premia in the foreign exchange market."3 This finding is corroborated by time series/cross section evidence for a large sample of developing countries in Ghei and Kiguel (1992); Marion (1992) provides similar evidence of Belgium, France and Italy.

# 4.2.2 _Interest rates and expected depreciation_

Table 4 also shows that increases in the interest parity differential increase the premium in the short run, as predicted by the theory; in some cases, this effect persists in the long run. Since variation in this variable is dominated by changes in expected depreciation, this implies a powerful role for exchange rate expectations in determining the premium.

> **2** The main exceptions are models in which Ricardian equivalence holds and prices are fully flexible, a set of circumstances that is not very relevant from an empirical point of view.

" The figure uses average values of variables for the period 1976-89. The simple correlation between the two variables is positive (.39) and statistically significant.
is considerable movement in the area and it is impossih'3e to keep track of all short-term migratioai. In view of the seasonal nature of many ..f these movements, it was decided to astinate the mid-period population by taking the average number of children present in the area. The end of period populations had been updated to take account of losses or omissions picked up in the annual re-enumeration of the population. These results from period life table calculations are summarized in Table 2.

Table 2: Childhood mortality for PHC and non-PHC villages south of Farafenni before and after the introduction of bednets

||Prima|ry Health<br>villages|Care|Non-Prim<br>v|ary Healt<br>illages|h care|
|---|---|---|---|---|---|---|
||IMRT|<br>**4q1**|5qI|IMR|**4q**<br>||<br>sqo|
|1988-89|0.110|0.157|0.249|0.093|0.100|0.184|
|Deaths|59|75|134|35|32|67|
|1989-90|0.072|0.045|0.114|0.116|0.103|0.207|
|Deaths|41|25|66|43|35|78|

Note: The separation factors for the calculation of the probabilities of surviving or dying were taken from the data, since in almost all cages, dates of birth an," death were known in the form of day, month and year. IMR = infant mortality rate.

The data in Table 2 have several interesting features. One is the level of childhood mortality indicated. Although we have come to expect values of around 100 per thousand for infant mortality, it is a surprise to see that this value is still the figure in The Gambia where there has been a good Primary Health Care system since 1983 and where immunization coverage is remarkably high. Each year from 1985 onwards, The Gambian government has carried out an EPI survey around December-January with the results shown in Table 3. The figures for the whole country in 1989 and 1990 are very impressive, especially so since 8
cause of death information altogether, as has been done in much of the previous research on the determinants of child mortality, is not necessarily the best approach either.

Table 2 shows the distribution of reported cause of death by age group from the 1992 CHS along with comparable data from rural Pakistan, based on the verbal autopsy method, and a less developed country (LDC) aggregated number based on a different estimation methodology.<sup>8</sup> Results from the CHS are broadly consistent with conventional epidemiological wisdom: birth-related causes constitute the principal cause of death within the first month of birth (43%), while ARI and diarrhea diseases become more important after the first month. The overall distribution of causes of death in rural China resembles that in rural Pakistan,<sup>9</sup> except that diarrhea-caused U5 mortality is much smaller in China (6% versus 21%), probably reflecting better sanitary conditions in China. The aggregate LDC figures highlight four leading causes of death. Ranked in descending order, these are birth-related causes, other illnesses (unspecified), ARI and diarrhea. The relative importance of ARI vis a vis diarrhea related death in China is more or less in line with the LDC aggregate. We can conclude from these comparisons that the information collected on cause of death in the CHS is relatively sensible. However, it remains to be seen whether a more detailed analysis of these data will deliver sensible and credible results.

Aside from the misreporting issue, cause of death is often simply unknown. This problem crops up not only in the CHS, but, as the data from rural Pakistan reveal, in surveys that use the verbal autopsy method as well. Rather than drop observations with unknown cause of death, and thereby risk a sample selection bias in our survival analysis, we impute unknown causes to one of the five identified categories (ARI, diarrhea, tetanus, birth related and other illnesses) using the following procedure. First, we use a multinomial logit model to estimate the probabilities of the five specified causes as functions of socio-economic characteristics of the household and community, a set of province dummies, and a fifth order polynomial in the age of death of the child. Based

> 8 The LDC aggregate is based on estimates from Global Burden of Disease Study 2000. The cause of death have been estimated based on data from national vital registration system, population laboratories and epidemiological studies. For most countries particularly in poor regions, vital registration systems are not available, therefore, the cause of death is extrapolated using specially developed statistical methods (Murray etc, 2001).

> 9 The Pakistan survey collected causes of death for more than 1,000 deaths occurring in rural areas between 1990-94.

5
Policy ReseaRch WoRking PaPeR 4401

# **Abstract**

The authors show in this paper that increasing the transparency of the trading environment can be an important complement to traditional liberalization of tariff and non-tariff barriers. Our definition of transparency is grounded in a transaction cost analysis. The authors focus on two dimensions of transparency: predictability (reducing the cost of uncertainty) and simplification (reducing information costs). Using the Asia Pacific Economic Cooperation (APEC) member economies as a case study, the authors construct indices of importer and exporter transparency for the region from a wide range of sources. Our results from a gravity model suggest that improving trade-related transparency in APEC could hold significant benefits by raising intraAPEC trade by proximately $148 billion or 7.5 pecent of baseline trade in the region.

This paper—a product of the Trade Team, Development Research Group—is part of is part of a broader “Transparency and Competitiveness” project supported through a Trust Fund established by the Australian Department for Foreign Affairs and Trade and the Australian Agency for International Development (AUSAID). The work here is aligned with and has benefited from a project on Trade Costs and Facilitation at the Bank with support of the U.K. Department for International Development. This paper is based on a report prepared for the Asia-Pacific Economic Cooperation. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at helblem@who.int, bshepherd@worldbank.org, or jswilson@worldbank.org _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 views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Policy Research Working Paper Series**

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|WPS2710 Breaking up the Collective Farm:<br>Welfare Outcomes of Vietnam's<br>Massive Land Privatization|Martin Ravallion<br>Dominique van de Walle|November 2001|C. Cunanan<br>32301|
|WPS2711 Identifying Class Size Effects in<br>Developing Countries: Evidence from<br>Rural Schools in Bolivia|Miguel Urquiola<br>|November 2001|H. Sladovich<br>37698|
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|WPS2714 On Decomposing the Causes of<br>Health Sector Inequalities with an<br>Application to Malnutrition Inequalitie<br>in Vietnam|Adam Wagstaff<br>Eddy van Doorslaer<br>s Naoko Watanabe|November 2001|H. Sladovich<br>37698|
|WPS2715 Paying for Health Care: Quantifying<br>Fairness, Catastrophe, and<br>Impoverishment, with Applications to<br>Vietnam, 1993-98|Adam Wagstaff<br>Eddy van Doorslaer|November 2001|H. Sladovich<br>37698|
|WPS2716 Does Foreign Bank Penetration<br>Reduce Access to Credit in<br>Developing Countries? Evidence<br>from Asking Borrowers|George R. G. Clarke<br>Robert Cull<br>Maria Soledad Martinez P|November 2001<br>eria|P. Sintim-Aboagye<br>37644|