rafmacalaba/datause-encoder-data huggingface dataset:
(SYS-GMM) developed by Arellano-Bover (1995) and Blundell-Bond (1998) for dynamic panel models.<sup>17</sup> It is well known that in such a modeling framework (see Beck and Katz, 2004) "...with a non-stationary dependent variable, the dispersion of the value of the coefficient in an AR (1) process found with different asymptotically equivalent methods often exceeds its standard errors." We therefore test whether the dependent variable was stationary.<sup>18</sup> Since the moment conditions used to estimate the models are valid only if there is no serial correlation in the idiosyncratic errors, an Arellano-Bond test of the hypothesis of no autocorrelation in the first-differenced errors and a Hansen-J test of the null hypothesis that over-identifying restrictions are valid are also performed for each model.<sup>19</sup> The Dif-Hansen statistic allows us to test that additional SYS-GMM moment conditions used are valid.<sup>20</sup> To avoid over-fitting bias, i.e., using too many moment conditions, we made sure that the number of instruments used (the lags of the dependent variable) is not "too high" relative to the number of observations.<sup>21</sup> The joint significance of the explanatory variables is testing with a Fisher test and endogeneity of the main variables of interest is addressed by means of a Hausman test.

Our econometric analysis of the impact of the level of economic and financial sector development of a country on its ability to attract private investment is built on a stepwise procedure that is organized around two main objectives. A first objective is to examine whether overall economic development and financial sector development levels are indeed key determinants of private investment. A second objective is to further explore the impact of the level of financial sector development, if found to be significant, by decomposing it into its banking sector and financial market components.

The first objective is tackled by means of regressions of the following general form: ' _privinvtit_   1 _privinvtit_  1   2 _growthit_  3 _findevit_  x   _it_ (1)

> governance have played in building commitment of the private sector to fund energy projects.

> 17 The general structure of this estimation method is sketched in the appendix.

> 18 This test showed that the dependent variable does not contain a unit root (details are available from the authors upon request).

> 19 While first-order autocorrelation is expected, rejecting the hypothesis of no serial correlation at higher orders implies that instruments are not valid. Note that Hansen-J test results are robust but can be weakened by the use of too many instruments.

> 20 With the estimation method used, however, Dif-Sargan test is not robust. We therefore present Dif-Hansen results instead.

13
19 improved macro-environments and poverty reduction is conditioned by other factors such as location and infrastructure, households' private and public endowments, and the occurrence of shocks.

To disentangle the effects of these disparate events and factors on the different sections of African society it is tempting to use economy-wide modeling techniques which can generate counterfactuals, and provide insights into the respective impacts of policies and other shocks. Much of the serious work to date on policy reform and poverty in Africa has relied on such modeling approaches (Bourguignon and Morrison, 1992; Sahn et al, 1997). Yet despite their strengths, these approaches also have a number of important limitations. The models typically impose a strong structure which sometimes leads to questions about their realism. They are most often calibrated at one point in time. As a result, they cannot always confidently track changes over time-the economic history. Indeed, such history usually involves policy-induced structural changes in the economy that are not captured in such experiments.

Exploiting different experiences across households, this section places emphasis instead on the micro-econometric evidence emerging from the much improved and richer household survey data sets. We begin by highlighting two _Poverty Dynamics_ studies-Dercon (2001) on Ethiopia, and Deininger and Okidi (2001) on Uganda. These are particularly informative for two reasons. First, both involve the use of panel data, which track changes in the living standards of the same households over much of the 1990s. Although not identical, both the methodologies they adopt and their results are similar.

Second, both countries experienced far-reaching reforms in economic policy, inducing changes in market institutions, relative prices and producer responses. The rural sector in Ethiopia had previously been largely ignored and heavily taxed. But agricultural reforms initiated in the early 1990s included the abolition of food delivery quota for farmers, and a relaxation (and later abolition) of restrictions on private grain trades. These measures substantially reduced the food marketing margins between surplus and deficit regions. The Birr was devalued by 142 percent and the foreign exchange markets liberalized. This positively affected the farm-gate prices of tradables, such as coffee and chat, though the effect was somewhat muted due to the existence of parallel markets. Producer prices for coffee evolved favorably during the period, partly because of an increase in the world price.
|Ever temporarily closed during<br>the COVID-19 outbreak|-0.551***|-0.372|0.155|-0.262|0.339|0.430|-0.132|-0.099|
|---|---|---|---|---|---|---|---|---|
||(0.104)|(0.260)|(0.342)|(0.327)|(0.302)|(0.269)|(0.443)|(0.584)|
|Adjusting or converting their<br>production or services|0.110|0.339**|-0.147|-0.613**|0.739**|1.166**|0.326|0.408|
||(0.114)|(0.145)|(0.285)|(0.268)|(0.318)|(0.494)|(0.309)|(0.407)|
|Started or increased online<br>business activity|-0.393*|-0.590**|0.413|0.849*|-0.611|-0.450|-0.839**|-0.896*|
||(0.231)|(0.258)|(0.535)|(0.481)|(0.423)|(0.438)|(0.426)|(0.504)|
|Started or increased delivery of<br>goods, services or carryout|0.235*|0.425*|-0.578*|-0.691|0.513|0.066|1.425**|1.386**|
||(0.127)|(0.248)|(0.347)|(0.479)|(0.493)|(0.509)|(0.598)|(0.649)|
|Started or increased remote work|0.176**|0.100|0.271|0.212|-0.980***|-1.012***|-0.254|-0.231|
||(0.085)|(0.165)|(0.268)|(0.329)|(0.344)|(0.361)|(0.325)|(0.357)|
|Exporting directly (at least 10%<br>of sales)|0.142|0.246|0.144|0.461|0.267|0.141|0.823|1.080|
||(0.097)|(0.159)|(0.434)|(0.515)|(0.573)|(0.661)|(0.743)|(0.750)|
|Constant|0.234**|0.233|-1.970***|-2.636***|-1.965***|-1.433***|-3.242***|-3.222***|
||(0.092)|(0.237)|(0.487)|(0.435)|(0.363)|(0.369)|(0.483)|(0.535)|
|Number of observations|619|469|630|473|679|522|554|427|
|r2_w|0.224|0.342|||||||
|r2_b|0.091|0.069|||||||
|r2_o|0.079|0.065|||||||
|rho|0.629|0.679|||||||

Notes: This table reports panel regressions with individual firm fixed effects for the Georgia COV-ES data. Columns 3 through 8 report marginal effects from logistic regressions. Sampling weights from the ES are used. Standard errors are shown in parenthesis. All standard errors are clustered at survey strata, and *, **, *** denotes the significance level at 10%, 5%, and 1%, respectively. See Section 6 for more details.

51
nutrients from sugar-mill and distillery wastes (IEA, 2006a). However, the diversion of agricultural residues, such as bagasse, as an energy input to biofuel production reduces the amount of crop residues available for recycling, which could degrade soil quality, and soil organic matter in particular (Fresco et al., 2007). Hill et al. (2006) explain that soybean production for biodiesel in the US requires far less fertilizer and pesticide per unit of energy produced than maize production for ethanol, and that both feedstocks fare poorly in comparison to second generation feedstocks such as switchgrass, woody plants or diverse mixtures of prairie grasses and forbs. Finally, the IEA (2006a) finds that perennial lignocellulosic crops such as eucalyptus, poplar, willow or grasses can be grown on poor-quality land, increasing soil carbon and quality, with less-intensive management and fewer fossil-energy inputs.

# **8. Impacts of Biofuels on Land Use**

The demand for land to produce biofuels augments the traditional demands of agriculture and forestry. Moreover, global population growth as well as rising per capita consumption of developing countries can be expected to increase demand for land for food supply in the future. While some of this demand may be met with improved crop yields per unit area, which has been increasing at about 1.5% in recent decades for staple crops, this would only increase production by 40% by 2030, requiring a conservatively estimated 500 Mha more land to be brought into cultivation in order to meet the additional demand for food alone (Bustamante et al, 2009). There exist a large number of studies estimating land requirement to meet specified biofuel targets (see Gurgel et al., 2007; FAPRI, 2008; Nowicki et al., 2007; European Commission, 2006; OECD, 2006; FAO, 2008c; Ravindranath et al., 2009; Ozdemir et al, 2009; Russi, 2008). However, the results vary considerably due difference in methodological approach, different assumptions about crops used and conversion efficiencies from biomass to fuel.

Where will the land for additional biofuel production come from? Gurgel et al. (2007) find that the expansion of biofuel cultivation will occur largely at the expense of natural forest and pasture land (especially when no land supply response is assumed), whereas cropland, managed forest, and natural grassland show little net change. Much of this land dedicated to biofuel feedstock cultivation is found in Africa and Central and South America, and also, to a lesser extent, in the 34
Policy Research Working Paper 5612

# **Abstract**

Many countries in the MENA region have established partial credit guarantee schemes to facilitate SME access to finance. These schemes can play an important role, especially in a period where MENA governments are making efforts to improve the effectiveness of credit registries and bureaus and strengthen creditor rights. This paper reviews the design of partial credit guarantee schemes in MENA, and assesses their preliminary outcomes. The paper is based on a survey conducted in 10 MENA countries in early 2010. The authors find that the average size of guarantee schemes in MENA (measured by the total value of outstanding guarantees) is in line with the international average, although there are wide differences across countries, and some schemes seem too small to make any significant impact. Most importantly, the number of guarantees looks generally small while their average value looks large. This suggests that guarantee schemes are not yet reaching the smaller firms. Guarantee schemes in MENA look financially sound and most schemes have room to grow. However, this growth should be accompanied by an improvement of some key design and management features, as well as the introduction of systematic impact evaluation reviews.

This paper is a product of the Financial and Private Sector Development Unit, Middle East and North Africa Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank. org. The authors may be contacted at rrocha@worldbank.org, zarvai@worldbank.org, and ysaadanihassani@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
BOTSWANA’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE highly subsidized, artificially boosting traffic at very high fiscal costs. The situation was not sustainable and passenger services were completely stopped in Botswana in 2009, partly because of safety concerns and primarily because the subsidy from freight could no longer be sustained (Bullock 2009).

**Table 4. Railway indicators for Botswana and select other countries, 2000–05**

||CFM (Angola)|**BR (Botswana)**|CEAR (Malawi)|Nacala Railroad<br>(Mozambique)|Beira Railroad<br>(Mozambique)|Ressano Garcia Line<br>(Mozambique)|Transnamib (Namibia)|Spoornet (South Africa)|RSZ (Zambia)|NRZ (Zimbabwe)|
|---|---|---|---|---|---|---|---|---|---|---|
|Concessioned (1)/ state run (0)|0|**0**|0|1|1|0|0|0|1|0|
|Freight density (1,000 tonne-<br>km/km)|469|**827**|90|270|663|364|475|2,427|406|902|
|Passenger density (1,000<br>passenger-km/km)|—|**—**|38|103|44|44|33|60|92|166|
|Labor productivity (1,000 traffic<br>units per employee)|580|**722**|131|710|281|—|484|3,308|502|390|
|Locomotive productivity (million<br>traffic units per locomotive)|30|**41**|3|25|13|—|25|33|25|8|
|Carriage productivity (1,000<br>passenger-km per carriage)|4,046|**2,391**|1,176|3,333|750|—|—|—|3,286|—|
|Wagon productivity (1,000 net<br>tonne-km per wagon)|950|**987**|82|260|476|—|805|913|377|195|
|Freight yield (US cents/tonne-<br>km)|—|**—**|6|5|3|3|—|—|4|—|
|Passenger yield (US<br>cents/passenger-km)|—|**—**|1|0.9|0.5|1|—|—|1|—|
|_Source:_Bullock 2009. Derived fro<br>_Note:_* With 2.5 passenger-km equ<br>— = Not available.|m AICD rail<br>ivalent to|operator d<br>1 traffic un|atabase(<br>it, 1 tonne-|www.infrastr<br>km equivale|uctureafrica<br>nt to 1 traffi|.org/aicd/too<br>c unit.|ls/data<br>).||||

14
# Cohort Size and Youth Employment Outcomes<sup>*</sup>

David Newhouse<sup>†</sup> Claudia Wolff<sup>‡</sup>

> * Acknowledgments: We would like to thank David Canning for guidance, and Arup Banerji, Sangeeta Raja, and David Robalino for their support, for related work on cohort size and labor market outcomes in Africa. We are grateful to Kathleen Beegle, John Giles, Juanna Jönsen, Erik Lindqvist  and Cem Mete for helpful comments, and to Claudio Montenegro for providing access to the International Income Distribution Database. Part of the study was funded by the generous contribution of the Bank-Netherlands Partnership Program (BNPP). Keywords: Youth Employment; Cohort size; Demographics JEL codes: O10, J11, J21

> † World Bank, Social Protection and Labor , and IZA

> ‡ World Bank, Social Protection and Labor and Stockholm School of Economics
compared to no growth in developed countries. Approximately one-half of world sugar imports are now by developing countries compared to less than one-third in 1980. These shifts have diminished the importance of developed country imports and the importance of EU and U.S. quota imports, which now account for only 7 percent of total world import quantities compared to 13 percent in 1982.

The world sugar market has also been affected by the increased consumption of alternative caloric sweetener, high-fructose corn syrups (HFCS). This alternative sweetener accounts for about 40 percent of total caloric sweeteners consumption in Japan and nearly half in the United States (Figure 8). However, some medical researchers are now questioning whether HFCS is absorbed differently than sugar by the body and whether this difference may contribute to obesity by stifling the body's ability to feel full and thereby encouraging eating more. If these concerns are substantiated by research finding, then it could shift consumer demand back towards sugar and would have some impact on world sugar imports and prices. At the same time, there is increasing concern over the health consequences of obesity in the United States and this could reduce consumption of all caloric sweeteners.

**Figure 8. U.S. Sugar and HFCS Consumption, 1970-2003**

<!-- Start of picture text --> U.S. Sugar and HFCS Consumption<br>12<br>10<br>Sugar<br>8<br>6<br>HFCS<br>4<br>2<br>0<br>1970 1975 1980 1985 1990 1995 2000<br>Source: USDA<br>Million Metric Tons<br><!-- End of picture text --> Some Caribbean sugar producers may benefit from higher world market sugar prices while losing the benefits of access to preferential markets. If sugar trade preferences erode as expected, it would have some impact on world sugar prices because sugar producers with lower preference prices would reduce output. World sugar prices would increase and exports from developing countries, and some developed countries, would increase. The extent of the price increases would depend on how much preference prices erode and whether this was part of a global sugar policy reform. According to Sheales, et al. (1999), the full liberalization of the world sugar market would result in a 41 percent increase in world sugar prices. Wohlgenant (1999) estimated that global liberalization would result in a 43 percent increase in world price, and Borrell and Pearce (1999) estimated that world prices would increase by 38 percent. Partial liberalization 22
# **Preface**

This paper is part of a broader project on life annuities and retirement products, coordinated by Roberto Rocha, program manager in the Financial Markets Policy Unit of the Financial and Private Sector Development Vice-Presidency of the World Bank.<sup>2</sup> The project was initiated in 2004 to fill an apparent gap in the pension literature, especially in the literature addressing the payout phase of defined-contribution pension systems.

Many countries that have implemented systemic pension reforms and introduced private pension systems are now facing the challenge of organizing the payout phase for retiring workers. This entails introducing a well-regulated market for retirement products, covering the effective regulation and supervision of retirement products, marketing activities, providers and intermediaries. However, the literature on the payout phase is generally focused on a few countries and topics and does not address in sufficient detail the institutional and regulatory issues faced by policymakers in reforming countries.

The World Bank project fills this gap by reviewing in detail a number of representative country cases, including Australia, Chile, Denmark, Sweden, and Switzerland. These countries have large mandatory or quasi-mandatory private pension systems operating primarily on a definedcontribution basis and have already entered the payout phase. Moreover, their institutional and regulatory arrangements for the payout phase are different in many aspects, including decentralized and centralized arrangements for the provision of life and term annuities, different menus of retirement products, different approaches to price regulation and risk sharing, different marketing rules, and different capital rules for providers. Therefore these countries provide a rich variety of experiences and policy lessons for other reforming countries.

The current paper provides a summary and update of a longer study on the Chilean market for retirement products that was published a few years ago (Rocha and Thorburn, 2007). The paper highlights the numerous changes in the Chilean pension systems that were introduced in 2008, assesses their potential impact, and updates most of the statistical material.

2 Roberto Rocha is currently Senior Advisor at the Middle East and North Africa Region of the World Bank
**<u>Table 7: Welfare Loss from the VAT by Area of Residence and Poverty Status</u>**

||**All**|**R**|**ural**|**Urb**|**an**|
|---|---|---|---|---|---|
|||Poor|Non-Poor|Poor|Non-Poor|
||8|% Increase|in cereal, meat, a|nd other foods||
|Compensating variation (x1000)|-106.979|-68.207|-116.034|-101.383|-170.638|
||[0.479]|[0.414]|[0.977]|[0.560]|[1.507]|
||1|2% Increase|in cereal, meat,|and other food|s|
|Compensating variation (x1000)|-126.648|-78.499|-134.753|-119.87|-209.263|
||[0.586]|[0.474]|[1.159]|[0.678]|[1.899]|
|||Expe|nditure ratio to ru|ral poor||
|Mean food expenditure|1.647|1.000|1.728|1.558|2.786|
|Observations|21,239|6,766|4,785|5,743|3,945|

Standard errors in brackets, 100 bootstrap replications Note: Gini coefficient of welfare loss = 0.32 and 0.33 Source: 2012 1-2-3 Survey, DRC Table 7 presents the welfare and equity impacts of price increases by poverty status and area of residence. The welfare impacts of the price changes are sizable for all analytical groups. Households in both rural and urban areas suffer aggregate welfare losses ranging from 68,207 to 170,638 FC in total household expenditure on food as a direct consequence of the introduction of the VAT in the case of an 8.0 percent price increase. They are even higher for a 12 percent price increase. These welfare losses are statistically different from zero and amount to 10 to 12 percent decrease in food expenditure. The ratio of welfare losses to total food expenditure varies across analytical groups but more so between urban and rural areas irrespective or poverty status.

In addition to the measure of the proportionate welfare loss, we compute the Gini coefficient for the welfare loss (actually the absolute value of the welfare loss). Notice that a strictly positive Gini coefficient shows progressivity in this setup because it implies that the welfare loss is concentrated at high levels of expenditure. We find a Gini coefficient of 0.32 and 0.33 for effective tax rates of 8.0 and 12.0 percent respectively. These results further support the idea that the VAT is progressive. They also highlight the increasingly progressive nature of the VAT as the statutory tax rate rises.

19
**Figure 4. Skilled immigration in OECD areas**

# **_A. Destination of skilled immigrants in percent of the OECD_**

<!-- Start of picture text --> 60%<br>50%<br>40%<br>30%<br>20%<br>10%<br>0%<br>Year 1990 Year 2000<br>USA<br>EU-15 Can.<br>Austr.<br>Others<br><!-- End of picture text -->

# **_B. Skilled immigrants in percent of the immigration stock_**

<!-- Start of picture text --> 60%<br>50%<br>40%<br>30%<br>20%<br>10%<br>0%<br>Variation 2000-1990 Year 1990 Year 2000<br>USA<br>EU-15 Can.<br>Austr. OECD<br><!-- End of picture text -->

# **_C. Percentage of skilled immigrants from low income countries_**

<!-- Start of picture text --> 30%<br>25%<br>20%<br>15%<br>10%<br>5%<br>0%<br>Variation 2000-1990 Year 1990 Year 2000<br>USA<br>EU-15 Can.<br>Austr. OECD<br><!-- End of picture text -->
Table 4: Life Satisfaction Equation - Pooled World Sample

|||lifesat|
|---|---|---|
|Bonding|Importance of family|0.256|
|||(13.87)**|
||Importance of religion|0.229<br>**|
|||(16.75)|
||Importance of work|0.04|
|||(3.68)**|
||Important child qualities: obedience|0.071|
|||(5.73)**|
||Trust in institutions|0.215|
|||(16.09)**|
|Bridging|Important child qualities: independence|-0.005|
|||-0.46|
||Important child qualities: imagination|-0.02|
|||-1.7|
||Trust in people|0.206|
|||(14.48)**|
||Justified homosexuality|-0.106|
|||(7.57)**|
|Controls|female|0.057|
|||(5.65)**|
||ae|-0041|
||g|.<br>|
|||(18.42)**|
||age2|0|
|||(20.55)**|
||lower education|-0.088|
|||(4.01)**|
||upper education|0.098|
|||(6.50)**|
||married|0.307|
|||(24.18)**|
||no children|0.112|
|||(8.03)**|
||children three or more|0.032|
|||(2.33)*|
||good health|0.591|
|||(36.57)**|
||bad health|-0.77|
|||(31.29)**|
||breadwinner|-0.021|
|||-1.78|
||employment status - part-time|-0.045|
|||(2.13)*|
||employment status - self-employed|0.03|
|||-1.56|
||employment status - unemployed|-0.413|
|||(16.13)**|
||economically inactive|0.029|
|||(2.22)*|
||l i|0368|
||ow ncome group|-.<br>|
|||(20.32)**|
||high income group|0.293|
|||(9.68)**|
||Observations|240811|

Robust z-statistics in parentheses. * significant at 5% level; ** significant at 1% level Countries and years dummies omitted.

29