rafmacalaba/datause-encoder-data huggingface dataset:
# _4. Data Description and Methodology_

Our analysis relies on daily data that covers the period from January 1997 to March 2000 and is drawn, for the most part, from Bloomberg, IDC and Baseline. All market related data (e.g., oil and stock prices, bond yields, and emerging debt market returns) are based on daily closing prices. The bond yield reflects, as far as we can tell, actual transaction data. Whenever we found missing observations, we cross-checked the time series with other news sources and filled in the missing data or, if this was not possible, deleted the observation leaving 725 observations before taking lags. As a robustness check, we repeat the analysis with weekly closing data (140 observations) but report the results only for major specifications (Table 8 in the Appendix).

In terms of structural modeling, we avail ourselves of the results in Madan and Unal (2000) who derive credit spreads as a fumction of firm-specific variables in a hazard rate framework. In this setting, the hazard rate, i.e., the instantaneous probability of borrower default, governs the arrival of a sudden loss driven by structural parameters such as cash asset value or, in our case, the value of the supply and purchase agreements to Ras Gas investors. By expressing the hazard rate as a first-order approximation in terms of exogenous variables, we obtain Ras Gas credit spreads as a linear function of loss inducing risk factors, neglecting higher order terms.

Consequently, we take as our dependent variable the mid-closing spread of the 2013 Ras Gas bond yield over the 10 year benchmark US Treasury yield.<sup>25</sup> The explanatory variables are the risk factors affecting the contractual relationships at the heart of the Ras Gas project that we 25 According to Bim Hundal of Goldman Sachs, the bond is quite actively traded contrary to the 2006 one and, therefore, constitutes a much better measure of investor and market sentiment regarding the project's prospects.

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Parameters that are significantly correlated with employment growth include transport infrastructure, access to finance, access to cell phone communication, registration with a government office, a reduction in registration days, and reductions in violent social conflicts. Interestingly, and contrary to the perceptions of entrepreneurs, access to electricity does not turn out to significantly correlate with employment growth. But for those rural entrepreneurs who do use electricity, reliability matters. A decrease in interruptions could stimulate growth. Because most entrepreneurs are traders, these findings appear plausible.

The simulations are helpful to visualize the impact of potential gains if such improvements could be made, but should be read with caution. They rely on empirical data and methods that are subject to measurement error, do not fully consider some of the interactions that encompass the rural investment climate, do not address causality issues, and provide little guidance on how to achieve the selected improvements. It is evident from figure 16 that the estimated investment constraints have a large margin of error. Nevertheless, the simulations are useful in comparing the magnitude of individual investment climate variables with respect to their correlation with rural employment growth.

Removing the constraints of inadequate road infrastructure and finance would have the strongest effect on employment growth. The simulations assumed a 50% improvement of selected investment climate indicators.<sup>16</sup> The ranking of a constraint’s impact on growth does not change with different assumptions. Figure 16 shows that improved access to markets would have the strongest effect on employment growth, followed by access to rural finance. Interestingly, rural cell phone communication ranks third. Demand-side factors such as higher rural wages due to productivity

> 16 For example, mean distance to the next market was assumed to decrease from 17 to 11 kilometers.

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# **How accurate were projections of employment changes?**

_Employment became more sensitive to changes in GDP during the crisis._ We estimated the relationship between employment growth and GDP growth before and after the crisis, on the 37 countries that reported data for each of these variables. Our preferred estimates control for time-invariant characteristics of the country. They indicate that the employment elasticity rose during the crisis, from 0.16 before the crisis to 0.25 after the crisis (Table A4).<sup>23</sup> _This result is of importance since forecasts of employment changes are often based on methods that combine estimates of employment elasticities with GDP projections._ The ILO, for example, predicts present and future employment based on regressions of employment rates on GDP growth, controlling for time-invariant country characteristics (ILO, 2010, p.79). If the relationship between GDP growth and employment growth changes during the crisis, extrapolating from the past may lead to inaccurate estimates of employment loss.

_Thus predictions based on pre-crisis elasticities significantly underestimated employment loss during the crisis._ Projections of employment growth derived from pre-crisis elasticities predicted employment growth of 0.47 percent. However, in the countries analyzed, employment actually declined on average, although slightly, by -0.08 percent. Therefore, on average the employment estimates overstated employment growth by 0.55 percentage points. This is a significant overestimate, given that employment growth in total declined about 2 percentage points.

**Table 1: Pre-crisis employment elasticities understated employment losses.**

||Pre-crisis|Post-crisis|
|---|---|---|
|Elasticity|0.16|0.25|
|Average projected employment<br>growth(based onpost-crisis GDP)||0.47|
|Average actual employmentgrowth|1.88|-0.08|
|Average overestimate of<br>employmentgrowth||0.55|
|Average magnitude of discrepancy||1.9|

_Forecasting employment changes on the basis of GDP alone typically produces inaccurate estimates for individual countries._ The extent of the discrepancy between actual and predicted employment ranged from -10.5 to 6.5 percentage points. On average across the countries, the prediction was off by a magnitude of 1.9 percentage points.<sup>24</sup>

# **From evidence to policy responses**

_Evidence on labor market adjustments is an important input in the design of policy responses._ While economic growth has bottomed out and appears to be recovering in the advanced economies, labor

> 23 These estimates come from regressions, based on quarterly data, of annual percent change in employment growth on annual percent change in employment, controlling for country fixed effects. Separate regressions were run for the 8 quarters before the crisis and for the four during the crisis. Results are shown in appendix table A4. The increase in the employment elasticity from 0.16 to 0.25 is not statistically significant, but leads to economically meaningful discrepancies between predicted and actual employment.

> 24 In other words, the average of the absolute value of the discrepancy across countries and quarters is 1.9

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12 The increase in middle income Asia's market shares (Republic of Korea, Malaysia and Thailand are major exporters in this group) raised exports more than 700 percent what would have resulted from demand changes, while the corresponding increase for low income Asia (China, India and Pakistan are in this group) was over 380 percent. In contrast, the erosion of sub-Saharan Africa's market shares reduced exports by about 42 percent below what would have occurred if only demand changes occurred. The market share erosion effects were strongest for low income African countries where "potential" exports were reduced by about 52 percent.

A second important point concerning Africa's export experience is that the demand factor was lower than that for every other country group. Low income Asia's factor (778.6) indicates the overall increase in demand for its exports was almost 40 percent greater than for Africa's products, while that for all non-OECD countries was almost twice as great. Table 3, therefore, reinforces the findings from the previous (Table 1) product specific analysis. _Africa has experienced declining market shares for its major export products which were of declining relative importance in international trade._ Given that some countries in the regional groups exported (at least) small values of almost all three-digit SITC products in 1962-64, the previous analysis may have failed to properly reflect the importance of diversification on export growth.<sup>8</sup> Several indices are available which can provide useful insights concerning this issue. One such measure is the share of total exports that are accounted for by (say) the three largest three-digit SITC products. Two other indices of diversification have been 8The relationship between export diversification, trade and economic growth has been examined in a number of studies including Coppock (1962), Khalaf (1974) or MacBean (1966). It is generally held that diversification has positive implications for exports (particularly for the stability of export earnings) although the supporting empirical evidence is surprisingly mixed. A second related group of studies have also argued that countries have a number of legitimate reasons for wanting to achieve greater diversification in the geographic distribution of their trading partners (Hirschman 1945). Amjadi and Yeats (1995) show that sub-Saharan Africa is far more trade dependent on OECD Europe than is any other group of developing countries. Yeats (1990b) argues that as a result of this dependance, and the associated monopoly power it gives European countries, Africa pays considerably higher than average prices for its exports.
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4 of the reformed hospitals.<sup>1</sup> Writing more recently, Braithwaite et al. (2011) also conclude that there is little hard evidence on the impacts of hospital autonomization, but also suggest that the generation of hard evidence has not been helped by the rather strongly held ideological viewpoints among some of the researchers in the field. Braithwaite et al. conclude their review: ―The evidence is weak, and mixed. Our review suggests ... indicates that there is far more argumentation in favor of the merits of privatization and corporatization than scientific evaluation of their benefits. ... [T]he debates about the merits of privatization and corporatization are often vehicles for engaging in advocacy about a range of public policy issues. ... Where performance has improved after privatization or corporatization, it is possible for those in favor to argue causality, and opponents to say that the improvements would have occurred anyway. Where performance has not improved after privatization or corporatization, those who wanted it are able to claim that the idea was good but it was not implemented correctly, and those against it can say this outcome was predictable.‖ In this paper we present evidence on the impacts of a public hospital autonomization reform that was introduced in a staggered fashion across a developing country – Vietnam. The reforms increased the decision rights of hospital staff and managers, strengthened their residual claimant status, and forced hospitals to become less reliant on budget allocations and more reliant on user fees and income from the social health insurance agency. Parallel reforms sought to protect the poor by enrolling them in the social health insurance scheme (at the taxpayer‘s expense), instead of asking hospitals to exempt them from user fees (and forgo income in the process). The staggered roll-out of the reform over a period of six years starting in 2002 provides us with a quasi-natural experiment. In each year after 2002, we have some

> 1 The studies of the UK‘s National Health Service (NHS) by Propper and colleagues (Propper 1996; Propper _et al._ 2004; Propper _et al._ 2008; Gaynor _et al._ 2011; Propper 2012) are an exception: they use data during prereform periods and on unreformed hospitals to generate difference-in-difference estimates of hospital reform impacts. However, Propper and her colleagues do not investigate the effects of autonomization per se, but rather the effect of competition in an environment where (some) hospitals had been granted some degree of autonomy (the degree of autonomy was increased during the 2000‘s).
and under USD 500 per container in Malaysia and Singapore.<sup>7</sup> Uncertainty over delivery times is a significant cost burden on manufactured exports. The port at Dar es Salaam, Tanzania, is regarded as more efficient and container throughput has been growing much faster there.

Due to a lack of investment, Kenya’s railways have significantly declined and are considered rather poor providers of freight transportation services since the 1980s.<sup>8</sup> Road transportation is the primary means of overland transport. But some sections of the key ―Northern Corridor‖ are in very poor condition.

Kenya’s problems with its ports, rail and road transportation facilities were highlighted by Kenya’s ranking on the international Logistics Perception Index of 2004.<sup>9</sup> Of the 70 countries in the 2004 survey, Kenya was ranked as the least logistically friendly (World Bank, 2007). In Africa, the survey included South Africa, Zambia, Ghana and Nigeria. For 2006, the survey expanded to include 150 countries, and Kenya ranks at number 75--below several African countries, but above average for the region.

# **Telecommunications**

As of 2007, Kenya’s telecommunications services were expensive compared with other SubSaharan African countries and even more when compared with those of East and South Asia. Relative to countries with comparable income, Kenya had fewer fixed lines per capita, less than half the level of international calls per subscriber and higher Internet charges. Perhaps more important is the low efficiency of service provision (see World Bank, 2007, pp.45-47). Kenya currently requires that telephone companies must be at least 30 percent owned by Kenyan nationals. Problems related to the licensing of the third mobile telephone provider<sup>10</sup> and the ―Second National Operator‖ were primarily due to this 7 World Bank staff estimates.

8 In the hope of improved performance, Kenya’s railways were turned over to Rift Valley Railways, a South African company, in November 2006.

9 The Logistics Perception Index measures the perceptions of managerial level personnel of international freight forwarding companies. It is published by the Global Facilitation Partnership for Transportation and Trade and available at: www.gfptt.org.

10 Regarding the third mobile telephone operator, a consortium of a local investor (Kenya National Federation of Cooperatives, KNFC) and foreign investors (Econet Wireless) won the tender in February 2004. But the consortium was put together to meet the 30 percent local ownership requirement, not because of business reasons. Citing deals 9
**Table 5. Summary of Cost-Inefficiency Cases**

|Inefficient|EXPGDP|Potential<br>revisions of<br>spending in<br>the sample|Expenditure<br>per capita in<br>PPP|Potential<br>revisions of<br>spending in<br>the sample|Expenditure<br>in current $ per capita|Potential<br>revisions of<br>spending in<br>the sample|
|---|---|---|---|---|---|---|
|B1lg.um|_i55.2_||10024|1J|||
|Hungary|54.5|7|||||
|Poland|50.7|15|||||
|StQvem|....|10..35.|2.||||
|Czech<br>Republic|48.5|7|||||
|Greece|47.1|2|||||
|Portugal|39.3|1|||.||

Note: See Appendix II for details.

Source: Fakin and de Crombrugghe (1996), p.<sup>2</sup> 3; 22-25 for detailed description of results.

Judged by the sample of the OECD and CEC's, the striking result is that a transition economy can find between 7 and 15 countries" which spend a lower share of current GDP, and reach better results on all the performance indicators selected for the test. It may seem that the private sector in CEC can contribute to the satisfaction of our performance indicators. This doesn't invalidate our indicators at all. On the contrary, it reminds especially transition countries that the welfare objectives of the society require a government intervention only where there is a The list of countries is given in appendix III.

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the Doha agenda or global free trade. These vectors are derived from simulations of the GTAP model. We take these new price vectors as exogenous shifts in the terms of trade facing Russia.

Some of our key results are as follows. The mean welfare gain to Russia from its WTO accession, averaged over all households is 7.3 percent of Russian consumption (with a standard deviation of 2.2 percent of consumption) in the medium run. We find that virtually all households obtain at least some increase in their income. Nearly all the household gains fall between 2.0 percent and 25 percent of consumption. Poor households do slightly better than rich households because the wage rate of unskilled labor rises more than the return on capital. If an inappropriately specified constant returns to scale model were employed the gains from WTO accession would be only about 1.2 percent of consumption with about 7 percent of households expected to lose, i.e., the WTO accession estimates are decisively affected by liberalization of barriers against foreign direct investment in business services sectors and endogenous productivity effects in business services and goods.

Regarding the impact on Russia of cuts in the tariffs and subsidies of other countries, we find that global free trade (which encompasses free trade in goods outside of Russia and the elimination of export subsidies, with domestic support for agriculture retained) would result in a weighted average gain to households in Russia of 0.2 percent of consumption, with a standard deviation of 0.2 percent of consumption. We estimate that a successful completion of the Doha Development Agenda (which we model as the elimination of export subsidies, substantial cuts in tariffs outside of Russia and reduction in domestic support for agriculture) would result in a weighted average gain to households of –0.3 percent of consumption. Russia, as a net food importer, loses from subsidy elimination, and the gains to Russia from tariff cuts in other 3
Do men really have greater socio-emotional skills than women? Evidence from Tanzanian youth<sup>∗</sup> Rachel Cassidy Smita Das Clara Delavallade Elijah Kipchumba Julietha Komba

**Keywords:** youth employment, socioemotional skills, measurement, gender, social desirability **JEL Classification:** J16, J24, 015

> ∗Cassidy: World Bank Africa Gender Innovation Lab (GIL), rcassidy@worldbank.org; Das: Innovations for Poverty Action and World Bank GIL, sdas@poverty-action.org; Delavallade: World Bank GIL, cdelavallade@worldbank.org; Kipchumba: Trinity College Dublin, kipchume@tcd.ie; Komba: BRAC Tanzania, kombajulietha88@gmail.com. This paper is a product of the World Bank GIL in the Africa Region Chief Economist office. We thank Innovations for Poverty Action and BRAC Tanzania, especially Munshi Sulaiman for their collaboration with project design and implementation, as well as Ariel Gruver, Alev Gurbuz Cuneo and Josephine Tassy for excellent research assistance. We also thank Aidan Clerkin, Julian Jamison, Estelle Koussoub ́e and L ́ea Rouanet for useful comments on earlier drafts of this paper. This work was funded by the International Development Research Centre (IDRC), Wellspring Philanthropic Fund and the World Bank Umbrella Fund for Gender Equality (UFGE). The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.
credit or overdraft, a rise in the share of the firm’s working capital and fixed assets financed by banks, a reduction in the interest rates paid on loans, and an increase in the maturity of bank loans. The impact is economically significant: registry reform increases access to bank finance by almost 8 percentage points and access to loans by 7 percentage points. These are sizeable effects considering that in our sample, about 60 percent of firms have access to finance and 47 percent have a loan. There is also some evidence that the impact of the introduction of registries for movable assets on firms’ access to bank finance is larger among smaller firms, who also report a reduction in a subjective, perception-based measure of finance obstacles.

Our paper is related to the large literature that investigates whether collateral reduces credit rationing and increases access to finance, which follows the seminal work of Stiglitz and Weiss (1981). However, this literature largely focuses on the US and other developed countries.<sup>6</sup> One of the few related papers that uses non-US data is Liberti and Mian (2010), who investigate how financial development affects the costs and types of collateral used in 15 countries. They find that the cost of collateral declines with improved financial development. More relevant for our study, they also find that in more financially developed countries firms can use more “firmspecific” assets, i.e., movable assets. However, they do not investigate the impact of the cost of collateral on firms’ access to finance as their data come from one large multinational bank, neither do they explore changes in collateral laws and the introduction of collateral registries for movable assets, which is the focus of our paper.

Another related and recent study is by Nguyen and Qian (2012), who investigate the prevalence and determinants of the use of collateral in 43 countries and find that in countries with better institutions, firms are less likely to pledge collateral. However, their study does not consider the relationship between movable collateral registries and access to finance.

> 6 See Steijvers and Voordeckers (2009) for a recent survey.

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