rafmacalaba/datause-encoder-data huggingface dataset:
5 of their overall relations. Such variables may also indicate a history of inter-state conflict or cooperation, diminishing or enhancing prospects for treaty likelihood.<sup>ix</sup> This paper only considers the extent of inter-state trade given the availability of robust historical trade data.

In an effort to assess the link between trade, conflict and cooperation, the literature has been quite mixed. On the one hand, has been the general claim that increased trade between states should reduce incidents of militarized conflict between them and promote peace (Kant {1795} 1970; Polachek 1980; Arad and Hirsch 1981, 1983; Russett and Oneal 2001). The fear of losing gains from trade deters conflict. Along the same lines it has been argued that nations with cooperative political relations will engage in more trade, while conflictive nations are expected to trade less (Savage and Deutsch 1960; Nagy 1983; Pollins 1989). On the other hand has been the conjecture that high interstate trade, interdependence, and conflict are positively related (Waltz 1979). Higher interdependence increases frictions among the countries, and therefore may lead to conflict. Barbieri (2002:121), for example, finds that the higher the interdependence, and trade, between states the higher the likelihood of militarized conflict.

In the context of their general corollaries, both the trade-conflict and trade–peace camps have also provided useful conjectures that are quite analogous. Specifically, authors have asserted that increased inter-state trade indicates not only a history of cooperation between states (and interest in maintaining good relations) but also aids states in achieving negotiated settlements (Polachek 1980; Polachek 1997; Stein 2003; Polachek, Seiglie, and Xiang 2005; Pollins 1989; Barbieri 2002:121). Trade, it seems, also acts as a contract enforcing mechanism. Stein (2003), who argues that trade increases the likelihood of disputes between states, also claims that it provides states with an opportunity to resolve them at a lower level of interstate conflict. In essence, the coercive potential of trade reduces conflict, the occurrence of political crisis, and the need for militarized actions.

The above examination of the literature leads us to suppose that overall inter-state relations, measured by the extent of trade among them, is an appropriate measure for assessing the likelihood of environmental treaty negotiations (Neumayer 2002). Specifically, treaty likelihood will be enhanced, in the case of good, or strong, relations among states, or will be diminished in the case of poor, or weak, relations among states (Sigman 2004).

In the particular case of freshwater, another argument may be introduced regarding the relationship between trade and treaty formation—that of virtual water (Allan 1993, 1998, 2000,
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- Hart, 0. and Holmstrom, B. 1987. "The Theory of Contracts". In T.F. Bewley (ed.), Advances in Economic Theorv. Cambridge: Cambridge University Press, 71-155.

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40
**38**

Hayami, Yujiro and Vernon Ruttan (1985) _Agricultural Development: An International Perspective_ ; Baltimore : Johns Hopkins University Press.

InterAcademy Council (2004): _Realizing the Promise and Potential of African Agriculture: Science and Technology Strategies for Improving Agricultural Productivity and Food Security in Africa_ ; Report, Amsterdam, June.

Irz, Xavier, and Terry Roe (2005) “Seeds of Growth? Agricultural Productivity and The Transitional Dynamics of the Ramsey Model”, _European Review of Agricultural Economics_ , 32 (2): pp. 143-165.

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Jorgenson, Dale W., Frank M. Gollop, and Barbara M. Fraumeni (1987) “Productivity and U.S. Economic Growth”; Harvard Economic Studies, vol. 159 Cambridge, Mass.: Harvard University Press.

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Environment and Development: Penalized Non-parametric Inference of Global Trends in Deforestation, Pollution and Carbon Bo Pieter Johannes Andr ́ee<sup>1,2,3,*</sup> , Andres Chamorro<sup>1</sup> , Phoebe Spencer<sup>1</sup> , and Harun Dogo<sup>1</sup> 1 _World Bank Group_

> 2 _Department of Spatial Economics/SPINlab, VU Amsterdam, Netherlands_

> 3 _Tinbergen Institute_

> * _Corresponding Author: email bandree@worldbank.org or b.p.j.andree@vu.nl_

**Keywords:** Environment, Development, Penalized Inference, Non-parametric models, Kernel Regularized Least Squares.
However, most of the literature has focused on small-scale choice systems (such as in a number of cities in the United States). Denmark’s large and mature voucher system has been researched. Andersen (2005), Andersen and Serritzlew (2006), Nannestad (2004) and Rangvid (2008) reach the conclusion that, despite increments in competition, private schools do not perform academically better than public ones. These analyses suffer from weak instruments and non-robust methodologies. For the case of Sweden, Ahlin (2003) estimates the effect of a general school choice reform on student performance. Using a rich set of individual level data, increased school competition is shown to have statistically significant positive effects on student performance in mathematics, but no significant effects in English and Swedish. Interacting school competition with student characteristics, the results indicate that immigrant students and those in need of special education tend to gain more from increased school competition than others, while adverse effects on students from low education families are found in terms of English and Swedish performance. Also for Sweden, Sandström and Bergström (2004) analyze the effects of competition on public schools using data on 28,000 ninth graders. They account for potential endogeneity of the share of students attending independent schools by using instrumental variable estimation. Their findings support the hypothesis that school results in public schools improve due to competition. Research on Chile’s universal school choice model has been subject to a high level of scrutiny. The research is controversial, with several early articles presenting data to show that subsidized, private schools obtain higher standardized test scores than do public schools (Rodriguez 1988; Aedo and Larranaga 1994; Aedo 1997). A second batch of studies uses individual level information with large samples (Bravo et al 1999; Carnoy and McEwan 2000; Mizala and Romaguera 2000; Gallegos 2002; Vegas 2002). Several studies advance the previous estimations, with strategies to overcome the problem of self2
income or consumption and are often more appropriate for country-specific analysis. However, despite their many advantages, national official poverty measures are not comparable with the approaches used in other counties, in part because they are so tailored the specific country context. Thus, comparisons across countries (for instance, for the purposes of monitoring or benchmarking) require a harmonized approach, such as that conducted by the World Bank.

An additional reason that the World Bank uses a stand-alone approach to measure internationally comparable poverty rates is to account for differences in the cost of living between countries. To address this issue, the World Bank participates in the International Comparisons Program (ICP), a global effort to measure differences in the amount of goods and services a unit of one country’s currency can purchase in another country. The ICP exercise was most recently completed in 2011, which led to important updates to previous PPP measures.

The original dollar-a-day line was created in 1991 using 1985 PPPs and was estimated by taking an average of the national poverty lines in the world’s poorest countries. When a new set of PPPs was published in 1993, the line changed to $1.08 per day. PPPs were revised again in 2005, and the new line was estimated at $1.25.<sup>2</sup> For the most recent revision in 2011, the new line was estimated again using the national poverty lines of the poorest countries, as was the case in previous rounds. The result was a line set at $1.90 a-day. However, poverty by this measure is quite rare in Central Asia and is therefore excluded from the analysis that follows.

But in addition to the international “low income” poverty line, the World Bank also uses income class poverty lines which facilitate comparisons between countries at similar stages of development. The income class poverty lines are defined for the lower middle-income and upper middle-income countries and are based on the national poverty lines of the countries in each group. As such, they provide a more appropriate threshold to measure poverty for countries in each income class. The lines are defined at $3.2 (for lower middle-income countries) and $5.5 (for upper middle-income countries). The welfare measures of income or consumption used are the same as those used for the international poverty line. Cross-country comparisons of poverty measured at these lines are presented in Figure 1.

> 2 For more details on the updated lines from Francisco Ferreira, Dean Joliffe and Espen Prydz, follow this link

9
# **Regional Economic Integration and Agricultural Trade**

Junichi Goto* The World Bank

*The author is grateful to Takamasa Akiyama, John Baffes, Koichi Hamada, Will Martin, Donald Mitchell, Panos Varangis, Alan Winters, and seminar participants at the World Bank for helpful comments and suggestions on earlier versions of the paper; Tassos Haniotis for invaluable data on EC trade; and Jean Jacobson for her assistance with the manuscript.
# Targets andfuture challenges

Making future projections for the prevalence of HIV/AIDS is methodologically problematic. The spread of HIV/AIDS from vulnerable groups to the general population suggests that the past trend of increasing prevalence is likely to continue for the next few years.

Serious policy changes is required to achieve the HIV/AIDS reduction targets. The Government has articulated its HIV/AIDS strategy for the next five years and the goal proposed here (Box 8) captures the direction outlined in the strategy. Recent work suggests that reaching this goal poses a number of serious institutional, practical and attitudinal challenges (United Nations, 2001). These include a review of the government’s “social evils” policy towards sex workers and injecting drug users. This policy tends to stigmatise these people and treat them as criminals, instead of regarding them as patients that need help. Massive efforts to change behavior, promote the use of condoms and safe needles, and improve treatment of sexually transmitted diseases are required

## Box 8. MDG Goal Six: Combat HIV/AIDS, otialaria and other disease

Vietnam Development Goal: Reduce HIV/AIDS infection and eradicate other major diseases Target 1: slow the increase in the spread of HIV/AIDs by 2005 and halve the rate of increase by 2010. Source: Socialist Republic of Vietnam (2002) Targets for contraceptive prevalence ambitious but achievable - The Government hopes that 70 per cent of couples will be using modern contraceptive methods by 2010, up from an estimated 40 percent in 1990. Recent analysis suggests that this is ambitious but also achievable if past improvements are continued into the next decade. This would set Vietnam on course for achieving “universal” (75 percent) access to modern contraceptive methods by 2015 (Figure 14).

- °

-

## Figure 14. Contraceptive Prevalence Rate (CPR) progress and targets 1990-2015

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Source: ADB and WHO (2002) 31
due to collusive behavior of incumbent banks, but often the result of structural weaknesses in the legal and institutional framework that prevent, for example, the orderly resolution and exit of weak banks or provide implicit subsidies for “too‐big‐to‐fail” systemic banks. If that is the case, **strengthening regulatory and supervisory capacities** can help to alleviate these shortcomings and to reduce rates by fostering competition.

_Risk premium (risk perceptions)_ : If the main reason for high interest rates is information asymmetry resulting in large risk premia, solutions should focus on addressing the underlying information gaps. The **promotion of credit bureaus** can be a useful policy approach to facilitate access to more detailed financial records of potential borrowers and help to reduce risk premia and banks’ screening costs (Maimbo and Gallegos, 2014). In countries without comprehensive national identification systems, promoting ways to reliably and **cost‐ effectively verify a borrower’s identity** are also important measures to reduce information asymmetries. Risk premia can also be reduced by more **efficient loan foreclosure procedures** , including the introduction of small claim procedures, summary procedures for uncontested debt, or alternative dispute resolution procedures, that allow banks to limit the losses stemming from default of the borrower (Beck and Fuchs, 2004). Risk premia can also be lowered by choosing the **appropriate lending technology,** which Berger and Udell (2006) defines as a combination of primary information source, screening and underwriting policies/procedures, loan contract structure, and monitoring strategies/mechanisms.

_Overhead costs:_ If high interest rates are driven by high general administrative costs, some of the policy measures mentioned above can reduce the application costs, i.e. credit bureau and reliable borrowers’ IDs. With respect to credit delivery, measures to promote alternative delivery channels, such as agent networks, and to promote the digitalization of financial services in general can help reduce such costs.

_Cost of funds:_ In some instances, the underlying source of the distortions are large fiscal borrowing needs, in combination with shallow domestic debt markets and limited access to global debt markets, that drain liquidity and push up Treasury yields. As the government yield curve serves as the risk‐free benchmark to price financial products and often as the de‐facto floor for wholesale deposits of the relevant maturities in an economy, Treasury yields affect banks’ costs of funds and ultimately their lending rates. Addressing this source of distortion 37
# **Implementing Precaution in Benefit-Cost Analysis: The Case of Deep Seabed Mining**

Kerry Krutilla*#, David H. Good*, Mike Toman**, Tijen Arin**

- O’Neill School of Public and Environmental Affairs Indiana University, Bloomington Indiana

** World Bank

#Lead author:  krutilla@indiana.edu

# Acknowledgement and Disclaimer.

The authors wish to thank the World Bank for financial support and accesses to information sources. For many helpful comments and suggestions, the authors are also grateful to Nicholas Treich and other conferees at the European Society for Benefit-Cost Analysis first annual meeting at the Toulouse School of Economics, November 2019; Bryan Land and other participants at a World Bank stakeholder meeting in Sydney Australia, November 2018; Jonathan Wiener, of Duke University; Steve Grimsley, a Senior Geophysical Advisor, previously of Hess Corporation; and Chris Colton, founder of Hexis Energy Trading, LLC. Carl BrownGrimm and Shu-Chuan Chiu provided essential research assistance. Notwithstanding this excellent input, the authors bear exclusive responsibility for the findings, judgements, and conclusions in this article.

JEL Codes: D61, D82, K32, Q57 Keywords: seabed mining, fundamental uncertainty, benefit cost analysis
# **Table 4: Non-farm employment: Robustness check**

||Low Return<br>Type of<br>Wage em|High Return <br>Non-farm Em<br>ployment|Self<br> Employment<br>ployment|
|---|---|---|---|
|**_Marginal effects: Multinomial regression1_**||||
|<br>Distance to Major cities (log)|0.021|-0.009|0.003|
||(1.56)|(0.51)|(0.19)|
|Distance* All Crop Suitability|-0.003|-0.010|-0.007|
||(2.09)*|(3.19)**|(2.30)*|
|Test of joint significance (χ<sup>2</sup>)|4.36|32.8|11.45|
|P-value|0.11|0|0.003|
|**_Marginal effects: Multinomial regression2_**||||
|<br>Travel Time to Major cities (log)|0.008|-0.048|-0.018|
||(1.04)|(3.26)**|(1.20)|
|Travel Time* Cash Crop Suitability|-0.002|-0.007|-0.006|
||(1.89)|(3.17)**|(2.64)**|
|Test of joint significance (χ<sup>2</sup>)|3.79|26.7|11.74|
|<br>P-value|0.15|0|0.003|

All regressions include individual characteristics (gender, education, age), household characteristics (size, land ownership, asset ownership, electricity connection), village characteristics (if village has electricity, NGO programs, credit programs, market), distance to town and an intercept term as regressors. Robust z statistics in parentheses Significant levels: * = 5%, ** = 1%

**Table 5: Non-farm employment: Alternative classification of nonfarm employment**

|Depen|Factory<br>Workers<br>dent variable= t|Se<br>W<br>ype|rvices<br>O<br>orkers<br>W<br>of nonfarm|ther<br>orkers<br>occupation|
|---|---|---|---|---|
|**_Marginal effects: Multinomial regression_**|||||
|Distance to Major cities (log)|-0.024||-0.002|-0.002|
||(1.88)||(0.13)|(0.17)|
|Distance* Cash Crop Suitability|-0.006||-0.011|0.000|
||(1.90)||(4.29)**|(0.24)|
|Distance to towns|0.0001||-0.001|-0.0002|
||(0.32)||(1.98)*|(0.87)|

Regression includes individual characteristics (gender, education, age), household characteristics (size, land ownership, asset ownership, electricity connection), village characteristics (if village has electricity, NGO programs, credit programs, market), distance to town and an intercept term as regressors. Robust z statistics in parentheses Significant levels: * = 5%, ** = 1%
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# Admission Is Free Only If Your Dad Is Rich! Distributional E¤ects of Corruption in Schools in Developing Countries

M. Shahe Emran<sup>1</sup> IPD, Columbia University Asadul Islam Monash University Forhad Shilpi World Bank Key Words: Corruption, Bribes, Education, Schools, Inequality, Income E¤ect, Bargaining Power, Regressive E¤ects, Educational Mobility JEL Codes: O15, O12, K42, I2

> 1 We are grateful to Matthew Lindquist, Dilip Mookherjee, Hillary Hoynes, Je¤rey Wooldridge, Larry Katz, Rajeev Dehejia, Arif Mamun, Ali Pratik, Paul Carrillo, Virginia Robano, Ra...qul Hassan, Niaz Asadullah, Zhaoyang Hou and seminar participants at Monash University for helpful discussions and/or comments on earlier drafts. We thank Transparency International Bangladesh and Iftekhrauzzaman for access to the NHSC (2010) data used in this study. The standard disclaimer applies.

1
Annex 6 presents the impact of social protection on poverty reduction with same budget but at different levels of poverty alleviation efficiency, for all the countries in ASPIRE grouped by income level. The four scenarios are (i) the baseline, with actual efficiency in the country, (ii) if efficiency is lower than the global average, raise it to the global average, (iii) if efficiency is lower than the average of the top quartile of efficiencies, raise it o that level, and (iv) raise efficiency to the observed global maximum. Figure 10 shows for what percentage of countries in each income grouping this sequence of raising efficiency succeeds in attaining the target of halving the poverty gap through social protection.

As seen in Figure 10, with the current BCR of each country (the baseline), 40 percent of countries meet the poverty reduction target for social protection that is proposed in this paper. This increases to 59 percent of countries meeting the target when using the mean benefit-cost ratio of all the countries

**FIGURE 8: BENEFIT-COST RATIOS, BY COUNTRY INCOME GROUPINGS**

**FIGURE 9: BUDGET AS A PERCENT OF POVERTY GAP, BY COUNTRY INCOME GROUPINGS**

<!-- Start of picture text --> 0.40<br>0.35<br>0.30<br>BCR -top 25%<br>0.25<br>0.20<br>0.15<br>BCR - mean<br>0.10<br>0.05<br>0.00<br>LIC LMIC UMIC HIC<br><!-- End of picture text --> <!-- Start of picture text --> 200<br>180<br>160<br>140<br>120<br>100<br>80<br>60<br>40<br>20<br>0<br>LIC LMIC UMIC HIC<br><!-- End of picture text --> _Source: Authors calculations_ _Source: Authors calculations_ (0.082), 70 percent of countries when using the BCR of the top quartile (0.217), and 76 percent of countries when using the somewhat unrealistic maximum value (0.400). In LICs, even with increased efficiency to the maximum (0.4), the fiscal resources are insufficient in more than half of countries, suggesting a need to reallocate existing non-social protection expenditure and/or mobilize additional budgetary resources.

20