rafmacalaba/datause-encoder-data huggingface dataset:
# **Table 7.** Sources of Data

- (1) Energy D ́etente (March, 2009)

- (2) Energy D ́etente (December, 2005)

- (3) N/A. Used median value for European countries.

- (4) Price from (1) and tax from OECD stats

- (5) IEA (2007) _Energy use in the New Millennium_

- (6) http://www.indiaenvironmentportal.org.in/content/review-international-policies-vehicle-motor fuel-efficiency

- (7) http://www.highbeam.com/doc/1G1’(1)43417929.html

- (8) http://www.autoproject.org.cn/english/new ~~a~~ dvance ~~e~~ n/Mex%20TRB%20presentation.pdf

- (9) N/A. Use median for the whole sample.

- (10) Carisma and Lowder (2008)

- (11) Willoughby (2002) based on estimates for Sao Paulo.

- (12) Creutzig and He (2009).

- (13) N/A. Use median for European countries.

- (14) Estimate similar to Bangkok and Kuala Lumpur from United Nations Economic and Social Commission for Asia and the Pacific (2007).

- (15) Ministry of Land, Infrastructure and Transport (2000).

- (16) Korea Transport Institute (KOTI).

- (17) Ochoa and Radian (1997).

- (18) Jayaram _et al._ (1995)

(19) http://www.latimes.com/news/nationworld/world/la-fg-russia-roads15-2009jul15,0,6188164.story

- (20) Parry and Small (2005).

- (21) Connelly and Supangan(2006.)

- (22) INFRA/IWW (2004).

- (23) Mohan (2002). Table found at http://www.vtpi.org/tca/tca0503.pdf

- (24) http://www.car-accidents.com/country-car-accidents/china-car-accidents-crash.html

- (25) Mendoza, Chavarr ́ıa and Mayoral (1998).

- (26) http://www.kommersant.com/p’(1)3563/r ~~5~~ 00/Traffic ~~a~~ ccident/

- (27) http://findarticles.com/p/articles/mi ~~q~~ a5327/is 291/ai ~~n~~ 29030852/

- (28) (22) as average accident costs in ~~C~~ /1,000 passenger and tonne-kilometres.

- (29) IEA World Energy Statistics and Balances.

- (30) IMF WEO Database.

16
of scarce budget resources to be achieved, in the scope and quality of budget reporting and auditing, and in tax administration. Moreover, failure to restrain public borrowing and to implement reforms in the electricity sector would pose serious risks to fiscal sustainability and to the country’s prospects for economic growth and poverty reduction over the medium to long term.

# **References**

Asian Development Bank (2007), “Republic of Tajikistan: Tax Administration Modernization and Governance Enhancement”, Technical Assistance Consultant’s Report.

De Broeck, Mark and Vincent Koen (2000), “The Great Contractions in Russia, the Baltics and the other countries of the Former Soviet Union: A View from the Supply Side”, Working Paper WP/00/32, International Monetary Fund.

Easterly, William and Stanley Fischer (1994), “The Soviet Economic Decline: Historical and Republican Data”, Policy Research Working Paper 1284, World Bank.

Estache, Antonio, Marianela Gonzalez and Lourdes Trujillo (2006), “Government Expenditures on Education, Health and Infrastructure: A Naïve Look at Levels, Outcomes and Efficiency”, World Bank.

Gray, Cheryl, Tracey Lane and Aristomene Varoudakis (eds) (2007), _Fiscal Policy and Economic Growth: Lessons of Eastern Europe and Central Asia_ ”, World Bank.

Harrison, Graham, Esil Martinsen and Sundar Somodi (2005), “A Program for Tax Administration Reform”, Technical Report Fiscal Affairs Department, International Monetary Fund.

32
delivery and timely postnatal care. In the third study arm, both the CHW cooperative performance payments and demand-side transfers were implemented. The fourth study arm served as a control group, and pay-for-reporting was the only CPBF component implemented. In the two study arms in which payments were not linked to performance (the first and second), cooperatives received the average quarterly amounts given to cooperatives in the two study arms in which cooperatives were paid for performance (the third and fourth arms). This reflected the fact that the goal was to evaluate the impact of tying payments to performance and not the impact of different level of payments to the cooperatives. The percentage of the funds that had to be invested in the cooperatives’ incomegenerating activities, as well as the autonomy to decide how to allocate the money among the members, were the same in all treatment arms.

A baseline survey was fielded from February to May 2010 to measure outcomes prior to the launch of the program, and to establish internal validity of the study. For a household-level survey, 12 households with a woman aged 15-49 with a recent pregnancy or birth were selected from the catchment area of each of the 198 health centers. First, three cells (groups of villages) were randomly selected, and four villages within each cell were randomly selected. In each village, a field supervisor consulted the village leader and/or community health workers in order to identify the household with the most recent birth in each village.<sup>4</sup> This resulted in a sample of 2,376 households. In each village, the CHW in charge of maternal and neonatal health was to be interviewed. Interviews were completed with 2,005 CHWs (about 84 percent of the target). In addition, interviews were conducted with 197 cooperative presidents.

Implementation of the cooperative performance payments and demand-side in-kind incentives started in October 2010. Table 1 presents the unit fees paid to the cooperatives in the different implementation years. Most unit fees were halved by the end of 2011 and reduced by an additional 25 percent the following year. Four additional indicators related to tuberculosis and HIV testing were added during the implementation of the program. These indicators were added nationally and are not discussed in this paper. While the cooperative performance payments were implemented continuously until after the follow-up survey, health centers received their last payments for the demand-side transfers on February 2013.

> 4 During the fieldwork, the survey team learned that some villages, in five of the sectors, were served by health facilities different than the ones affiliated with the CHW cooperative selected for the sample. In these cases, additional households in the villages covered by the selected cooperatives were added to the sample.

7
countries, it risks making the classification substantially less useful to users. More importantly, it is unlikely to be found acceptable for operational purposes, thereby leading to an income classification that departs significantly from the operational guidelines.

One pragmatic approach is to use a hybrid based on an average of the two conversion factors: adjusted market exchange rates and PPPs. This would reduce the impact on the classification of switching to a PPP-based method, and—depending on the use to which the classification is put—there may be some justification for maintaining exchange rates in the formula. For example, market exchange rates provide a better measure of a country’s ability to service its international obligations and may, therefore, better reflect its creditworthiness. But there are several disadvantages, including that the PPP-based method would still need to use annual estimates based on extrapolation from benchmark years, it would still be subject to substantial periodic revision, and any method of combining the two series may be seen as an arbitrary choice.

It is also worth noting that the ranking of countries using either conversion method is very similar. Using data for 2010 (extracted from _World Development Indicators_ on May 30, 2014), the rank correlation coefficient is 0.99. And, as noted earlier, correlations between selected social indicators and GNI per capita using either market exchange rates or PPPs are relatively high.

The discussion leads us to the conclusion that market exchange rates, with appropriate adjustments to mitigate the impact of short-term volatility, continue to provide a reasonable and practical basis for preparing comparable GNI per capita estimates for use in classifying countries. We also conclude that the use of PPPs should be considered only when consistent annual estimates of PPPs are produced by the ICP.

# **6. Adjusting classification “cutoffs” over time**

The initial choice of the three threshold levels used in the income classification appears to have been made largely on pragmatic grounds. The cutoffs for defining the low and lower middle income thresholds were already in use in the World Bank’s operational guidelines process (for determining eligibility to “civil works preference” in IDA and “17 year terms” for IBRD) and the choice of high income threshold was made to rationalize the existing groupings of high income 22
This paper provides an overview of the recent literature in this area, with a particular emphasis on the interactions between public infrastructure, education, and health outcomes. In that sense, our coverage is broader than earlier surveys on the role of infrastructure and growth, such as those of Gramlich (1994), Kessides (1996), and more recently Romp and de Haan (2005). Unlike these studies, we focus squarely on the evidence on (and policy lessons for) developing countries and address econometric issues only sparingly—essentially to highlight the biases created by an inadequate account of the various ways through which public infrastructure may affect economic growth. However, we do not address issues associated with the political economy of infrastructure investment decisions—a topic that has attracted much interest in industrial countries in recent years (see, for instance, Valila and Mehrotra (2005), and Cadot, Roller, and Stephan (2006)).

The remainder of the paper is organized as follows. Section II briefly reviews the “conventional” channels through which public infrastructure is deemed to affect growth, namely, productivity, complementarity, and crowding-out effects. Section III identifies several other channels through which public capital in infrastructure may have an impact on growth. These include an indirect effect on labor productivity, an effect on adjustment costs associated with private investment, an impact on the durability of private capital, and an effect on education and health outcomes. In addition, we also highlight the fact that the impact of infrastructure on growth may be magnified as a result of interactions between health and education.

Dwelling on this discussion, Section IV illustrate the links among health, infrastructure, and growth in an endogenous growth model with transitional dynamics. After a brief description of the model and a characterization of the balanced growth path, we examine the short- and long-run effects of a revenue-neutral reallocation of public spending from health to infrastructure and discuss how these effects depend on the technology for producing goods and health services. We then derive the optimal (growth-maximizing) allocation of public expenditure and examine the properties of the optimal rule. Section V draws together some of the practical policy 5
is positive though not significant. In contrast, capital markets’ development significantly fosters private investment in developing countries’ power sector. These findings therefore suggest that the effects of the overall financial sector’s development are essentially driven by the level of domestic capital markets’ development.

**Table 13**

<u>SYS-GMM parameter estimates</u>

|Variable|Coefficient|Std error|
|---|---|---|
|_lag(privinvt)_|.7491106***|.0796758|
|_bsdev_|84.48461|126.4848|
|_cmdev_|231.4927**|122.9545|
|Obs.|307||
|Fisher test|F(3, 28)= 68.96***||
|Arellano Bond test - Order 1|-2.42***||
|Arellano Bond test - Order 2|-0.05||
|Hansen-J|chi2(69) = 22.96||
|Dif-Hansen|chi2(36)= 0.67||

When institutional and risk factors are added to the model as explanatory variables (Table 14), our findings emphasize that while the banking sector’s development surprisingly has adverse, but not significant, effects on private investment, domestic capital markets’ development positively and significantly affects private investment in developing countries’ power projects. Hence these results lead to the conclusion that the significant positive effects of the overall financial sector development on private investment found in Table 9 can be essentially explained by capital markets’ level of development. Moreover, as in Table 9, exchange rate risk seems to be the most important risk factor that may prevent private investors from participating to energy projects’ financing.

**Table 14**

|SYS-GM|M parameter estimates||
|---|---|---|
|Variable|Coefficient|Std error|
|_lag(privinvt)_|.6406816***|.0431686|
|_bsdev_|-54.11392|48.85219|
|_cmdev_|188.6785***|68.38535|
|_exchraterisk_|32.59895***|8.212808|
|Obs.|306||
|Fisher test|F(4, 28) = 105.93***||
|Arellano Bond test - Order 1|-2.37***||
|Arellano Bond test - Order 2|-0.08||
|Hansen-J|chi2(29) = 23.04||
|Dif-Hansen|chi2(15) = 8.21||

When controlling for the energy sector regulatory framework (Table 15), capital markets’ development still positively and significantly explains the volume of private investment while, 20
this problem in the high rates of unemployment in high‐income economies, such as the Eurozone. But the problem is beginning to show up even in middle‐income nations, such as China. As Simon Denyer (2016, p. A11) recently notes, referring to a study of 600 factories in Guangdong by the Hong Kong University of Science and Technology and Tsinghua University, “although the profits picture was mixed, companies had trimmed their workforce by 3.7 percent in 2014. Labor‐ intensive sectors were hit the hardest, with employment in textiles falling more than 10 percent.” Among emerging economies, this will create a divergence of performance, with the ones able to organize and take advantage of labor‐linking technologies to develop and grow. But down the road, as the advance of labor‐saving technology continues, this will be a challenge the world over; and we will have to think of new policies to tackle a global problem. This will be discussed briefly in the last section.

The rise of labor‐saving and labor‐shifting technology would not matter much if the resultant increased earnings, such as from profits and patents, were equitably distributed, because it would simply mean that people would work less and enjoy the bounties of new technology as visualized by several philosophers, from Plato and Thomas More to Rabindranath Tagore and Bertrand Russell. But the amount of work, far from decreasing, has actually risen, because the shrinking demand for labor has been met with harder work by those who have no share in the dividends of the new technology and live by their labor alone (Piketty 2013). This constitutes the core of the policy challenge that we certainly will not solve in a day, but needs to be initiated in debates and discussion on policy, for not to solve this is to blight the chances of sustainable development.

# **2. Technological Change and the Share of Wages**

One of the most troubling statistical trends in recent times that has received scant attention from economists and policy makers is that of the falling share of the wage bill, sharply and uniformly, in industrialized nations and, more erratically and less sharply, in emerging economies. For instance, the aggregate wage bill as a percentage of GDP in the United States was 61% in 1975 and is 57% now. Over the same period, the same ratio in Australia fell from 67% to 54%, in Canada from 61% to 55%, in Japan from 77% to 60%, in Turkey it fell from 43% in 1995 to 34% now. All this is displayed in Table 1; these nations are not exceptions but rather the norm.

What I am arguing is that the trends we see are only to be expected, given the march of labor‐saving technology. The trend is further reinforced in high‐income countries because of labor‐linking innovation by which the jobs base is being eroded by competition from low‐wage labor in well‐organized developing countries. It is not surprising that the trend is marked and almost unbroken across the high‐income nations. This is true not just for the countries 4
Table A6: Nigeria-Educational attainment of children and their parents by five-year birth cohort

||Average years<br>of schooling|No schooling|Primary|Secondary|Tertiary|
|---|---|---|---|---|---|
|Son||||||
|1942-1946|4.4|45.3|34.2|16.0|4.4|
|1947-1951|4.2|51.1|27.1|16.4|5.5|
|1952-1956|5.5|37.8|32.0|23.9|6.3|
|1957-1961|5.8|37.3|30.3|24.8|7.6|
|1962-1966|7.0|30.7|25.6|35.5|8.2|
|1967-1971|7.6|26.2|25.1|39.4|9.3|
|1972-1976|7.5|23.9|26.3|44.7|5.2|
|1977-1981|8.1|22.7|20.2|49.3|7.8|
|1982-1986|9.4|17.0|12.4|60.1|10.5|
|1987-1991|9.6|11.1|9.8|75.3|3.8|
|Daughter||||||
|1942-1946|1.5|77.8|15.7|6.5|0.0|
|1947-1951|2.1|69.6|21.1|7.6|1.7|
|1952-1956|2.8|59.5|29.7|8.1|2.7|
|1957-1961|3.2|61.6|22.2|13.4|2.8|
|1962-1966|4.5|49.9|24.4|21.7|4.0|
|1967-1971|4.2|51.1|24.7|22.0|2.1|
|1972-1976|5.1|42.0|27.8|27.0|3.2|
|1977-1981|5.6|41.0|22.5|33.1|3.4|
|1982-1986|6.4|37.4|17.1|41.7|3.8|
|1987-1991|7.8|26.8|11.4|58.6|3.2|
|Mother||||||
|1942-1946|0.1|98.3|1.7|0.0|0.0|
|1947-1951|0.3|94.8|4.7|0.5|0.0|
|1952-1956|0.4|93.7|5.6|0.6|0.0|
|1957-1961|0.5|92.5|5.5|1.7|0.3|
|1962-1966|0.8|88.2|9.2|2.3|0.3|
|1967-1971|0.9|86.2|10.9|2.8|0.2|
|1972-1976|1.3|81.4|14.2|4.1|0.4|
|1977-1981|1.7|76.9|16.4|5.9|0.7|
|1982-1986|2.6|66.8|19.9|11.6|1.7|
|1987-1991|3.7|55.9|23.8|18.6|1.6|
|Father||||||
|1942-1946|0.5|92.7|5.6|1.5|0.2|
|1947-1951|0.8|88.9|7.9|2.9|0.3|
|1952-1956|1.0|84.6|12.9|1.9|0.6|
|1957-1961|1.1|85.2|10.4|4.1|0.3|
|1962-1966|1.5|80.9|13.1|5.1|1.0|
|1967-1971|1.8|76.4|15.7|6.5|1.4|
|1972-1976|2.1|73.2|17.3|8.0|1.5|
|1977-1981|2.9|65.8|19.9|11.5|2.9|
|1982-1986|3.6|59.3|21.8|14.6|4.3|
|1987-1991|4.9|47.0|25.6|21.2|6.3|

38
agencies and exchequers. Cash-strapped irrigation departments, unable to sustain investments in infrastructure, are looking to transfer operational responsibilities to farmers. Further, the possibility of increased floods and droughts from climate change has re-focused attention on water-use efficiency and the need for local scrutiny and control. There is also the general trend towards all forms of decentralization in government functions, which has found support in the irrigation sector.

In practical terms, participatory irrigation has resulted in the growth of a larger number of farmer-run irrigation or water user associations. These associations have taken on numerous functions that were previously the responsibility of national irrigation agencies. This has meant a reduced role for government agencies in operation and maintenance (O&M), fee collection, water management, and conflict resolution.

Though participatory irrigation management is widespread, there is surprisingly little evidence about its impacts (Araral 2005). There are several studies that focus on government savings; however, fewer have sought to quantify impacts on farm productivity or water conservation (see Araral 2005 and Vermillion 1997). A recent exception is a study by Wang et al. (2006), which examines the role of water user associations in influencing water savings in China. They find that monetary incentives to water managers can contribute to water savings; however, these savings do not result in any increase in the incidence of poverty.

4
because the data was often missing. We do not include humanitarian cash assistance in the computation of total expenditure because survey respondents would not count cash assistance as part of their spending but rather as part of their income.

**Table 1.** Characteristics of male and female Principal Applicant (PA) Households

||**20**<br>|**13-14 Wa**<br>|**ve**<br>|**20**<br>|**17-18 Wa**<br>|**ve**<br>|
|---|---|---|---|---|---|---|
|Variable|Male<br>PA|Female<br>PA|All<br>PAs|Male<br>PA|Female<br>PA|All<br>PAs|
|All PAs, %|72.6|27.4||62.0|38.0||
|Age of PA|38.0|40.5|38.7|41.9|44.1|42.7|
|Elderly PA (%)|3.9|6.5|4.6|6.5|10.2|7.9|
|Married PAs below 18 (#)|10.0|11.0|22.0|0.0|2.0|2.0|
|Marital Status of PA|||||||
|Married with spouse in the hh|75.3|9.9|57.4|88.0|18.4|61.6|
|Married without spouse in the|||||||
|hh|8.8|54.3|21.2|6.0|40.3|19.0|
|Single or engaged|14.6|7.7|12.7|4.9|7.9|6.0|
|Divorced or separated|0.6|5.4|1.9|0.7|8.6|3.7|
|Widowed|0.8|22.7|6.8|0.5|24.8|9.7|
|Education of PA|||||||
|Less than 6 years|16.6|28.5|19.8|18.8|33.1|24.2|
|6-11 years|61.8|54.2|59.7|61.8|52.2|58.1|
|More than 12 years|18.5|14.9|17.5|19.5|14.7|17.6|
|Family Type|||||||
|Couple with children|65.7|8.8|50.1|73.5|13.9|50.9|
|Couple without children|6.0|0.8|4.6|6.3|1.7|4.6|
|Single caregivers|4.6|47.8|16.5|5.0|36.5|16.9|
|Single -person|16.6|20.3|17.6|7.3|21.3|12.6|
|Unaccompanied children|0.7|1.1|0.8|0.1|0.2|0.1|
|Non-nuclear and other hhs|6.5|21.2|10.5|7.7|26.5|14.9|

_Source_ : Own calculations based on ProGres and JD-HV database. _Note_ : PA = principal applicant. PA is determined at the time of registration. This table contains data on 42,505 observations in 2013 and 40,483 observations in 2018. To make both waves comparable, we excluded observations in wave one that did not receive the home visit questionnaire or that reported having no expenditure. For this reason, this table contains figures that slightly differ from Table 1 in Hanmer et al. (2019), which had 54,408 observations.

Our data enable insights into the change in refugee households’ composition five years after their original displacement. The share of PAs (that we classify as household heads) that are women has risen from 27 to 38 percent between 2013 and 2018. Interestingly however, the characteristics of Syrian households observed in the data seem to be similar in both waves. For example, PAs in 201718 are about four years older on average compared to PAs in 2013-14. This is partly because most 11
Figure 2.2 a. Terms of Trade 1992=100 <!-- Start of picture text --> 160<br>' ^ Argentina '-Chile<br>140 _ Ecuador Mexico<br>*'Venezuela, RB<br>120<br>100<br>80<br>60 -<br>1995 1996 1997 1998 1999 2000 2001<br>140 -<br>0Argentina Brazil<br>130 _ 'Colombia Peru<br>120<br>110<br>100<br>90 ,<br>1995 1996 1997 1998 1999 2000 2001<br><!-- End of picture text --> Source: WDI 1995-00 and domestic sources 2001.
# PPR Working Paper Series

||ICa|Authg|_DA_|Contact<br>for pager|
|---|---|---|---|---|
|WPS307|On the Accuracy of Economic<br>Observations: Do Sub-Saharan<br>Trade Statistics Mean Anything|Alexander J. Yeats|November 1989|J. Epps<br>33710|
|WPS308|Harmonizing Tax Policies in Central<br>America|Yalcin M. Baran|November 1989|T. Watana<br>31882|
|WPS309|Honduras-Public Sector Finances,<br>Issues, and Policy Suggestions<br>to Resolve Them|Yalcin M. Baran|November 1989|T. Watana<br>31882|
|WPS310|A Macroeconomic Consistency<br>Framework for Zimbabwe|Ali Khadr<br>Klaus Schmidt-Hebbel|||
|WPS311|Macroeconomic Performance<br>Before and After Disinflation in<br>Israel|Leonardo Leiderman<br>Nissan Liviatan|November 1989||
|WPS312|Improvir.g Public Enterprise<br>Performance: Lessons from<br>South Korea|Mary M. Shirley|October 1989|R. Malcolm<br>61708|
|WPS313|The Evolution of Paradigms of<br>Environmental Management in<br>Development|Michael E. Colby|||
|WPS314|Primary Commodiy Prices and<br>Macroeconomic Variables: A Long-<br>run Relationship|Theodosios Palaskas<br>Panos Varangis|November 1989|D. Gustafson<br>33714|
|WPS315|Notes on Patents, Distortions,<br>and Development|Julio Nogues|||
|WPS316|The Macroeconomics of Populism<br>in Latin America|Rudiger Dornbusch<br>Sebastian Edwards|||
|WPS317|Price and Quality Competitiveness<br>of Socialist Countries' Exports|Zdenek Drabek<br>Andrzej Olechowski|||
|WPS318|Debt Buybacks Can Indicate<br>Sovereign Countries' Willingness<br>to Raise Investment and Repay<br>Debt When Partial Debt Relief is<br>Offered: Theory and Tests|Sankarshan Acharya<br>Ishac Diwan|||
|WPS319|Trends in South-South Trade and<br>the Potential in Non-Discriminatory<br>Liberalization of Barriers|Refik Erzan<br>|||