rafmacalaba/datause-encoder-data huggingface dataset:
9 biological sense.'<sup>5</sup> Where not otherwise specified, we follow this biologically-imprecise terminology and use the word 'species" to refer to any taxonomic unit eligible for protection under the Act The process of listing a species for protection begins when the species is proposed by FWS as a "candidate". During its period of candidacy, FWS gathers data from internal and external scientific sourcea in order to determine whether the species warrants listing and protection. The process stalls here for most candidates; out of over 3600 candidates for listing in 1993, there is insufficient scientific data to make a decision on about 3000.16 If sufficient scientific data exist and the data are judged to warrant listing, then FWS can place a formal proposal in the Federal Register. After a public comment period, FWS makes a final decision. A species may be listed as "endangered" or "threatened". An Uendangered" species is "in danger of extinction throughout all or a significant portion of its range". A "rtened species **is** "likely to become endangered in the foreseeable future.'<sup>7</sup> Both tpes are considered to be 'listed' and, while there are some legal distinctions, in practice they are given the same protection under the Act. For **the** remainder of the paper, we ignore the distinction between endangered and reatened species and we refer to all listed species as "endangered".

For good reasons, the decision to list a species is given considerable attention by the EWS. Once protected, endangered species can cause large disruptions and force developers to delay or even cancel projects that might harm the species. For expositional purposes, we can effectively divide the stipulations of the Endangered Species Act into 'protective' and 'recovery' measures. 'Protective' measures are restrictions on activities which harm listed species. These restictions are more stringent for public, especially federal, activities than for private activities. On federal land or in projects requiring federal permits, species are

> 5A vertebrate 'population" is a taxonomic group below the subspecies level. Our analysis **combines** subspecies and populations in the sanne category.

"This total includes **invertbrates and** plants as well as the vertebrate **s** tudied in this paper.

"iThe background and definitions are drawn **from** the Endangered Species Act of 1973 and from the FWS publication, Placing Animals and Plants on the List of **Endangered and** Threatened Species", U.S. Fish and Wildlife Sevice (1993). This publication also includes a detailed description of the listing **process.**
The Roots of Inequality: Estimating Inequality of Opportunity from Regression Trees<sup>*</sup> Paolo Brunori<sup></sup> , Paul Hufe<sup></sup> , Daniel Gerszon Mahler<sup>§</sup>

**_JEL-Codes:_** D31; D63; C38

**_Keywords:_** Equality of Opportunity; Machine Learning; Random Forests

> * We are grateful for comments received from participants during presentations held at the Institute for Social and Economic Research at the University of Essex, the Poverty and Applied Microeconomics Seminar at the World Bank, the Copenhagen Centre for Social Data Science at the University of Copenhagen, and the 13th Winter School on Social Choice Theory and Welfare at Canazei. Any errors remain our own.

>  Corresponding Author: University of Florence, Dipartimento di Scienze per l’Economia e l’Impresa, Via delle Pandette 32 - 50127 Firenze, Italy, `paolo.brunori@unifi.it` .

>  ifo Munich and LMU Munich, `hufe@ifo.de` .

> § University of Copenhagen and World Bank, `dmahler@worldbank.org` .
_the Joint Statistical Meetings Section on Survey Research Methods, Alexandria, VA: American Statistical Association_ , pp. 899-903.

- Takeda, Yuka. (2010) “Equivalence scales for measuring poverty in transitional Russia: Engel's food share method and the subjective economic well-being method.” _Applied Economics Letters_ 17(4): 351-355.

- Van Praag, Bernard MS, Bernard Van Praag, and Ada Ferrer-i-Carbonell. (2004). _Happiness quantified: A satisfaction calculus approach_ . Oxford  University Press (revised edition 2008).

- Yang, Yang. (2008). “Social inequalities in happiness in the United States, 1972 to 2004: An ageperiod-cohort analysis.” _American Sociological Review_ 73(2): 204-226.

26
(Women’s Rights), the fourth to the resolution of non-violent disputes (Dispute Resolution), and finally to land titling and conflict in communities (Land Titling).<sup>3</sup> Fieldworkers for the project were experienced enumerators, most of whom had participated in previous data collection efforts on behalf of the statistics bureau. They underwent a rigorous weeklong training, including numerous field sessions. After the training but prior to the start of fieldwork, interviewers and supervisors were asked to complete the perceptions of the law section based on their own beliefs. Interviewers were not told they were participating in a methodological study; rather that it was an evaluation exercise as part of the training.

In general, the characteristics of the interviewers differed from those in the general population. Interviewers were younger and more likely to be male than respondents, and more highly educated as interviewers were required to have a minimum of completed secondary education, while only 12 percent of respondents met this criterion. (See Table 1 for further details.) The interviewer’s responses to the subjective questions were generally consistent with those given by respondents with similar characteristics. Limiting the respondent sample to urban residents with secondary education, and controlling for age and gender, there are statistically significant differences between interviewers and respondents only for question 4, Dispute Resolution. This is likely related to the fact that all of the interviewers live in the capital, Dili, were residents were in general less likely to indicate a preference for community over formal dispute resolution systems, though the limited sample size precludes a more formal test. Table 2 shows the comparison between the interviewer’s responses and those of the overall population.

As a pseudo comparison group for the subjective questions, I also test four more objective dichotomous variables also collected in the extension survey: whether or not the respondent attended a community meeting in the last 12 months, if the household had experienced problems with Siam Weed (an invasive species common to rural Timor-Leste), if the household’s farm had stone terraces (a wide spread agricultural practice), and whether the household had experienced a drought in the last two years. The full text of these questions is listed in the appendix. Table 3 shows the distribution and non-response rates for the objective variables.

# **4. Results**

_4.1 Fixed Effects Model_

> 3 To simplify the presentation of results, the five questions are given names linked to the general issue to which they relate.  These names are meant as a shorthand description only.  The actual phrasing of the question was designed to be neutral, and the full text is available in the appendix.

6
# **Figure 1: Migration networks and self-selection patterns**

ln _w_ <!-- Start of picture text --> μ 0 + δ 0 s<br>B = μ 1 + δ 1 s − e μπ −γ 1 s −γ 2 n<br>A = μ 1 + δ 1 s − e μπ −γ 1 s<br>μ 0<br>μ 1 − e μπ −γ 2 n<br>μ 1 − e μπ<br>s<br>' '<br>s L s L sU sU<br>Figure 2: Probability of First-time Migration in 1996-97<br>according to Education and Network Size for Males aged 15-49<br>OLS 2SLS<br>0 5 10 15 0 5 10 15<br>Years of Education Years of Education<br>10th 30th 10th - unadjusted 30th<br>50th 70th 50th - unadjusted 70th<br>90th 90th - unadjusted<br>.06 .06<br>.05 .05<br>.04 .04<br>.03 .03<br>Probability of Migration .02 Probability of Migration.02<br>.01 .01<br><!-- End of picture text --> Predicted probabilities obtained from OLS and 2SLS regressions in columns 3 and 6 of Table 3, for males in communities with population less than 100,000. Probabilities are plotted at the 10<sup>th</sup> , 30<sup>th</sup> , 50<sup>th</sup> , 70<sup>th</sup> , and 90<sup>th</sup> percentiles of the community migration prevalence distribution.

23
We first document substantial differences across India in terms of input usage. Counts of distinct material inputs are higher in urban settings than in rural locations—unconditionally and also after conditioning on plant size—and they are also higher in the organized sector than in the unorganized sector. At the district level, higher input usage in the organized sector is generally observed in wealthier districts and those with greater literacy rates. If looking within states, the usage is more closely associated with electricity access, population density, and closer spatial proximity to one of India’s largest cities. Plants in the organized sector utilizing a greater variety of inputs display a higher productivity, with the effects mostly concentrated among smaller plants with fewer than 50 employees. For the unorganized sector, there is very little correlation of input counts and local conditions, for better or for worse, and a modest link to productivity outcomes. These conditions identify for policy makers that input access is not an abstract theoretical concept, but finds direct expression in Indian outcomes, especially for small firms. Policies that can aid the development of input access (e.g., trade reforms, transportation development) may directly aid the productivity of these firms. As we discuss later, our work may also highlight that one of the costs of unorganized firms is less productive use of inputs and scaling.

Our study is motivated by the pivotal work of Goldberg et al. (2010a,b). Goldberg et al. (2010a,b) identify how trade liberalization for India increased the number of imported inputs used by organized sector firms included in the Prowess database. These authors further show a link of this development to a larger number of products that the firm produced, with this metric showing one aspect of firm productivity. In many respects, we step back from these more advanced studies: rather than focus on the causal change in inputs within the organized sector due to a particular reform or event, we want to first characterize the differences in input access that exist spatially and across different sectors of the economy. To the best of our knowledge, neither of these dimensions has been studied in the Indian context, yet establishing these facts and perspectives is an important stepping stone for understanding how events like trade reform or large infrastructure projects like highway improvements (e.g., Datta 2011, Ghani, Goswami, and Kerr 2012b) will influence the distribution of activity across the economy. It also allows us to understand better the degree to which the growth seen in the organized sector by Goldberg et 3
# **References**

- Aldy, Joseph E. and William A. Pizer, (forthcoming), “The US Competitiveness Impacts of Domestic Greenhouse Gas Mitigation Policies: Report for the Pew Center on Global Climate Change.

- Armington, Paul, (1969), “A Theory of Demand for Products Distinguished by Place of Production,” _IMF Staff Papers_ , Vol. 16, pp. 159-178.

- Atkinson, Giles, Kirk Hamilton, Giovanni Ruta and Dominique van der Mensbrugghe (2009), “Trade in ‘Virtual Carbon’: Empirical Results and Implications for Policy,” Background paper for World Development Report 2010, The World Bank, Washington, DC.

- Babiker, Mustafa (2005), “Climate change policy, market structure, and carbon leakage,” _Journal of International Economics_ , 65, pp. 421-445.

- Bhagwati, Jagdish and Petros C. Mavroidis, (2007), “Is Action Against US Exports for Failure to Sign the Kyoto Protocol WTO-legal?” _World Trade Review_ 6: 299-310

- Birdsall, Nancy and Arvind Subramanian (2009),”Energy, not Emissions: Equitable BurdenSharing on Climate Change,” mimeo. Washington D.C.

- Burniaux, Jean-Marc and Joaquim Oliveira Martins, (2000), “Carbon Emission Leakages: A General Equilibrium View,” Economics Department Working Papers, No. 242, May, OECD, Paris, France.

- Burniaux, Jean-Marc, Giuseppe Nicoletti and Joaquim Oliveira-Martins (1992), “GREEN: A Global Model for Quantifying the Costs of Policies to Curb CO2 Emissions,” OECD Economic Studies, No. 19, Winter 1992, pp. 49-92, OECD, Paris.

- Cline, William R. (2007), “Global Warming and Agriculture: Impact Estimates by Country,” Center for Global Development and Peterson Institute for International Economics, Washington, DC.

- Fisher, Carolyn, and Alan K. Fox (2009), “Comparing Policies to Combat Emissions Leakage,” Resources for the Future Discussion Paper 09-02, February.

- Friedman, Thomas (2009), New York Times. September 27. Available at <u>http://www.nytimes.com</u> (Accessed on October 5, 2009).

- Grossman, Gene, 1982, “Border Tax Adjustment,” _Journal of International Economics_ , vol. 10, no. 1, February 1980.

- Grubb and Niehoff (2006), “Allocation and Competitiveness in the EU Emissions Trading Scheme: Policy Overview. Climate Policy 6(1):137-160.

- Ho, Mun, Richard D. Morgenstern, Jhih-Shyang Shih (2008), “Impact of Carbon Price Polciies on US Industry. RFF Discussion Paper 08-37. Washington DC: Resources for the Future.

- IPCC (2000), _Special Report on Emissions Scenarios_ , Nakićenović, Nebojša and Rob Swart, editors, Cambridge University Press, Cambridge, UK.

21
Source: Authors’ calculation using ITC/World Bank database Tariffs have been reduced across sectors but are still high for agricultural products. Agricultural sectors such as foodstuffs, animal and animal products, and vegetables (MFN trade‐weighted average over 15 percent) have seen tariff rates cut by half, but remain relatively high (see Figure 10). On average tariff reductions across sectors range between 32 and 62 percent on average.

Figure 10: Tariffs have been reduced across sectors but are still high for agricultural products Source: Authors’ calculation using ITC/World Bank database There is room left for further liberalization, especially in lower income countries. Low‐income and lower‐middle‐income countries still have trade‐weighted preferential tariff levels over 5 percent on average (see Figure 11.a). When preferential tariffs are split by level of development of importing and exporting countries, trade‐weighted preferential tariffs imposed by South countries on the North and on the South are respectively more than 2.7 times and 2 times higher than those imposed by the North (see Figure 11.b).

11
Within the T3 hybrid set of economic and care subcategories, the following disaggregations were created and located within the post-fiscal income and geographic distributions (Table 4). Two of the most common subcategories in the general population are households where male earnings account for more than 60 percent of all earnings, and households in these two subcategories are more often urban and in the top three quintiles of the income distribution (rather than in the bottom two quintiles). The most common subcategory of households where females account for greater than 60 percent of all earnings are those households with no young- or old-age dependents; this subcategory is also far more likely to be urban-based and far less likely to belong to the bottom two quintiles of the income distribution.

Table 4. Household Types Based on Armenia ILCS 2020 Demographics + Income (proxy for intrahousehold roles and bargaining power) + Presence of children and elderly (proxy for care needs and domestic responsibilities)

|Subcategory T4||Population<br>Share (%)|Bottom 40<br>(%)|Top 60<br>(%)|Rural<br>(%)|
|---|---|---|---|---|---|
|Dependents|Female (>60% earnings)|1.2|37|63|46|
|+ Elderly|Male (> 60% earnings)|3.4|51|49|44|
||No labor earnings|1.5|61|39|54|
|Dependents,|Female (>60% earnings)|3.9|46|54|43|
|No elderly|Male (> 60% earnings)|19.7|45|55|46|
||No labor earnings|5.6|59|55|46|
|No dependents,|Female (>60% earnings)|4.4|35|65|29|
|Elderly|Male (> 60% earnings)|7.4|43|57|36|
||No labor earnings|7.3|39|61|34|
|No dependents,|Female (>60% earnings)|10.5|31|69|30|
|No elderly|Male (> 60% earnings)|28.1|31|69|38|
||No labor earnings|6.8|47|53|61|

_Note:_ ILCS = Integrated Living Conditions Survey.

# b. Findings: Impact of Taxes and Transfers across Household Types

In Armenia, direct taxes and the public contributory pension system have a large impact on improving the relative income position of either female-headed households or households where female earnings account for at least 60 percent of cumulative household income. At the same time, dual earner households contribute the highest pre-fiscal income share to income taxes while benefiting the least from direct transfers, which is an implicit disincentive for households to allocate all their labor supply to formal labor markets. Taken together, and conditional on cultural practices or community- or household-level arrangements that prioritize men as “primary” income 19
**A RICARDIAN ANALYSIS OF THE IMPACT OF CLIMATE CHANGE ON AFRICAN CROPLAND**<sup>**1**</sup>

**Pradeep Kurukulasuriya and Robert Mendelsohn**<sup>**2**</sup>

> 1 An earlier version of this Working Paper was published as CEEPA Discussion Paper number 8.

> 2 School of Forestry and Environmental Studies, Yale University, 230 Prospect St, New Haven, CT 06511, USA. E-mails: pradeep.kurukulasuriya@yale.edu;  robert.mendelsohn@yale.edu. The authors wish to thank Rashid Hassan, David Maddison and Ariel Dinar for their comments. The special effort of Jeffrey Lecksel in fixing some of the maps in this paper are much appreciated.

This paper was funded by the GEF and the World Bank. It is part of a larger study on the effect of climate change on agriculture in Africa, managed by the World Bank and coordinated by the Centre for Environmental Economics and Policy in Africa (CEEPA), University of Pretoria, South Africa.

1
Policy Research Working Paper 8728

# **Abstract**

An asset and liability management framework for managing risks arising from sovereign foreign exchange obligations requires a joint analysis of (i) the external financial liabilities resulting from a country’s sovereign debt and (ii) the foreign exchange assets of its central bank. Governments often issue sizable amounts of debt denominated in foreign currencies, subjecting their fiscal positions to foreign exchange volatilities. Prudent management of a sovereign’s foreign exchange position under an asset and liability management framework enables governments to mitigate risks at the lowest possible cost, hence increasing resilience to external shocks. Based on the challenges associated with the implementation of an asset and liability management framework, this study recommends a practical approach that includes analysis of the foreign exchange positions of central bank reserves and central government debt portfolios and optimization of the net position. The proposed model is tested, using the foreign exchange reserve and external debt data of seven countries (Albania, Ghana, FYR Macedonia, South Africa, the Republic of Korea, Tunisia, and Uruguay). The paper employs quantitative methods to explore the impact of an overarching asset and liability management strategy and integrated approach on the efficient management of foreign exchange risk. It provides policy recommendations on ways to minimize the risk of foreign exchange mismatches and increase the return on foreign exchange reserves.

This paper is a product of the World Bank Treasury. 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://www.worldbank.org/research. The authors may be contacted at ccangoz@worldbank.org and cwang@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
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38

# TABLE 4 (cont'd)

# OWN AND CROSS PRICE ELASTICITIES OF INPNrS

# IN PRIMARY PRODUCIION

(At means of estimated shares)

# NIGERIA

|Elasticity of:|Labor|Material|E-own|
|---|---|---|---|
|With respect to:||||
|Labor|-0.391|0.148|0.233|
|Material|0.385|_-0.155_|0.742|
|E-own|0.006|0.007|0.975|

# INDONESIA

|Elasticity of:|Labor|Material|E-own|
|---|---|---|---|
|With respect to:||||
|Labor|-0.535|0.197|0.257|
|Material|0.5 15|-0.217|0.686|
|E-own|0.020|0.020|-0.943|
-20-

reports do not allow for changes in working capital In the calculation of the self-financing ratio and, as a result, this ratio Is overstated. In many cases, the self-financing ratio would be negative If the ratio had been correctly calculated and nn average would be about one quarter less than the ratio estimated In the SAR.

All self-financing ratios have been recalculated In accordance with OMS 2.2. Within their limited applicability, the resuls show that the forecasting error was In fact high. About 31% of projects had self-financing ratios more than 20 percentage points lower than forecast at ccmpletion. The forecasting error has tended to increase during the 1970s and has shown continued deterioration In the 1980$ as a result of both overoptimism and poor performance by the Borrowers. At the same time, the actual values of the self-financing ratio have also worsened over time, starting at an average of 25% in 1966-73 but falling to 17% by 1980-85.

During the 19509 and 1960s, an OED study reported that the selffinancing ratio Improved on average during the course of project implementation; however, for projects approved during the period 1968483, there was an average deterioration of 6 percentage points during project Implementation. This tendency Is particularly problematic since the financing of both the project and the sector Investment program Is generally expected to be supported by an Increasing percentage of Intemally generated funds. This objective Is sought not only In connection with economic pricing and to ensure basic financial soundness of the utility but also as part of the overall macroeconomic objective of using the power tariff to mobilize resources for one of the most capital Intensive sectors In any country.

# Debt Service Coveraae Ratio

The debt service ratio for one third of projects did not meet appraisal forecests and, of these projects, one half were 100 percentage points lower than forecast. The average debt service coverage ratio was