rafmacalaba/datause-encoder-data huggingface dataset:
# **REFRENCES**

- Bhatia, A V. 2002. “Sovereign Credit Ratings Methodology: An Evaluation.” IMF Working Paper, WP/02/170.

- Cantor R. and F. Packe. 1996. “Determinants and Impacts of Sovereign Credit Ratings.” _Economic Policy Review_ , October.

- Castillo, del Graciana. 2004. “Assessing Sovereign Risk” in Schiffrin A and Amer Bisat (eds), _Covering Globalization: A Reporter’s Handbook,_ Columbia University Press, July. The World Bank, Washington D.C.

- FitchRatings. 2002. “International Rating Methodology for Regional and Local Governments.” Criteria Report. April 4.

- ——. 2006a. “Rating Subnationals Above the Sovereign in the Euro Area – A Fine Tuning.” May 3.

- ——. 2006b. “International Rating Methodology for Regional and Local Governments.” Criteria Report, October 30.

- ——. 2008a. “International Rating Methodology for Regional and Local Governments.” Criteria Report, July 8.

- ——. 2008b. “European Local and Regional Governments Outlook 2009.” International Public Finance, December 17.

- ——. 2008c. “Health Sector Reforms Necessary for Polish Local Governments.” International Public Finance, April 21.

- Freire, M and J Petersen (eds). 2004. _Subnational Capital Markets in Developing Countries._ The World Bank, Washington D.C.

- Gaillard, Norbert. 2006. “Determinants of Moody’s and S&P’s Sub-sovereign Credit Rating.” Mimeo.

- Hilderman, Mara. 1999. “Opening the Black Box: The Rating Committee Process at Moody’s.” Moody’s Investors Service Rating Methodology (January).

- Ianchovichina, Elena, Lili Liu and Mohan Nagarajan. 2007, “Subnational Fiscal Sustainability Analysis: What Can We Learn from Tamil Nadu?” _Economic and Political Weekly_ , Vol. XLII, No. 52, December.

- Liu, Lili, and Michael Waibel.  2008a. “Subnational Borrowing, Insolvency and Regulations,” in Macro Federalism and Local Finance, ed. by Anwar Shah, World Bank, Washington, DC.

- ———. 2008b. “Subnational Insolvency: Cross-Country Experiences.” World Bank Policy Research Working Paper, WPS#4496, Washington, DC.

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The third speci...cation deals with the possibility that the potential negative e¤ects of heavy rainfall (and ‡ood) on wages may induce substitution e¤ects. We report IV estimates that control for agricultural wages and spatial cost of living index (using our main IV, the heavy rainfall dummy based on the period 2000-2009). The results are reported in columns (5) and (6) in Table 6. They con...rm the argument that the potential negative e¤ects on wages and prices are not relevant for our results.

## Alternative Time Period for the Rainfall Instrument

The heavy rainfall dummy we so far used for identi...cation is de...ned on the basis of 10 years data on average rainfall for the period 2000-2009. If our estimates are in fact the e¤ects of ‘economic status’(i.e, permanent income) of a household on bribing in schools, then the estimates should not change signi...cantly if we use average rainfall data from a somewhat di¤erent period. We checked the sensitivity of the estimates for alternative periods, and it is reassuring that the estimates remain robust. For example, consider the estimates using rainfall data for 1999-2005 presented in columns (7) and (8) in Table 6, they are almost identical to the estimates we found earlier using the 2000-2009 rainfall data.

# (9) Discussion and Interpretation of the IV Results

It is now widely appreciated that, when the monotonicity condition is satis...ed, the IV estimates provide us with Local Average Treatment E¤ect (LATE), i.e., they provide estimates of the average causal e¤ect for those households which are a¤ected by the instrument (i.e., the ‘compliers’). Since we exploit variations in the rainfall for our identi...cation, our estimates are most relevant for those households whose income primarily depends on the agricultural sector. However, note that ‡ood in a village not only a¤ects the agricultural sector, it also a¤ects the income in the rural non-farm sector adversely, as the demand for non-farm products goes down. The IV estimates are thus likely to be relevant for the vast majority of the households in the villages and small towns in Bangladesh.

A related important point is that our estimates pertain to a household’s long-term income (economic status), because we use ten year average rainfall data, thus the short-run rainfall variations are not used for identi...cation here. The results remain robust when we use alternative time periods for rainfall data, such as 1999-2005.

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To assess changes during the past decade, we subdivide the data into two periods and compute averages for each period. As Table 2 shows, we find little evidence of systematic improvement or deterioration, although some of the differences might be significant in a large-sample statistical analysis.

# **4.2  Regression Results**

Our regression exercise in this paper has two parts. First, we use the new database to test the association between effective protection and a variety of park characteristics in Asia/Pacific, Africa and LAC. We perform panel estimates by random effects, because we are primarily interested in the cross-sectional characteristics of parks. Our second exercise focuses on time series tests of the impact of park establishment on deforestation. For these tests, we estimate by fixed effects. Inspection of the data reveals that the outside/inside ratio is highly skewed, but its logarithm has a near-normal distribution. Accordingly, we use log ratios in our regressions.

# **4.2.1  Park Characteristics and Forest Protection**

The Hansen data provide consistent measurement of global tropical forest clearing at high resolution, so they offer an unprecedented opportunity for investigating the association between forest protection and park characteristics. In this section, we mobilize the WDPA database to test a wide variety of characteristics related to park size, age, IUCN status, management and legal status. We also incorporate annual dummy variables for 2001-2012 and our park establishment test variable, whose value is 0 for years prior to park establishment and 1 thereafter. We regard this exercise as a weak test of park establishment, since it does not control explicitly for time intervals before and after establishment. We will introduce such controls in the next section, which applies a strong test using fixed effects estimation.

10
- 20 -

Concerning remittances sent home for investment purposes, the Egyptian worker abroad will require a return on his deposits (in pound) equivalent to the international interest rate (or in the host country) plus the expected exchange rate changes relative to the Egyptian pound. Thus exchange rate management plays a critical role in the decision to send remittances home. Moreover, investors in Egypt are facing a substantial risk of not being able to convert their holdings back to foreign exchange as long as the exchange rate is not at an equilibrium level and/or the authorities prevent the black mtrket from developing. Moreover, even if the such a market exists freely, the volume of capital inflow would depend very much on a credible monetary policy which in turn, depends on a credible fiscal policy. Empirical evidence appears to have born out these points.!-

# C. Interest Rate and Investment Efficiency

To the extent that the Government may succeed in liberalizing the current restrictive system of investment regulation and in moving towards privatization of public sector enterprises, there will be an added pressure to reform interest rate policy. In a more liberalized investment environment and in a financial system dominated by the banking sector, interest rates will be the key financial prices to guide investment decisions and to ensure allocative efficiency. So far, however, interest rates have been of marginal importance in the process of resource allocation and in determining the efficiency of investment projects. Almost all investment projects undertaken by public sector companies, which account collectively for the lion share of the country's total capital formation, need to be approved by the Ministry of Planning. The key consideration governing the Ministry's decision regarding project selection and _WU_ 1I an informal study by the IMF (1989) on the determinants of recorded remittances in Egypt, it was found that recorded remittances are sensitive to the exchange rate differential but not the interest rates. The regression equation fails to show any significant effect of the interest rates. Two aspects of this study is particularly interesting. First, it is based explicitly on the recognition of macroeconomic factors as determinants of remittances, and developed within the framework of portfolio management. Second, the data developed by the author appear to be very comprehensive and painstakingly detailed.
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bids and either re-bid the area(s) or withdraw all or part of It

# from the bid tender.

(c) Direct Negogation - As earlier said, acreage which is not included or planned to be included in a bid tender should be permitted In the Rep to be licensed by the CA through direct negotiations. A party interested in entering into direct negotiations with the CA should be required to provide to the CA sufficient information fully to identify: itself, as a corporate or other entity; its area -nf interest, defined by geological coordinates; its technical competence and rfancal resources, fuUly described and documented; and complete terms and conditions it proposes for a PA. Thereafter, at the CA's discretion, it may enter into such direct negotiations with the applicant on such terms as it may deem appropriate, provided that they are consistent with both the PL and the Regs.

- (3) PIetroleum Operations -Under this heading, the Regs should address specific requirements to be met in the carrying out of petroleum operations under a PA. The most important of these normally include:

- (a) submission to the CA of the rightsholder's annual work program; timing and procedures for its approval;

- (b) prompt supply to the CA of quality copies of all greoogical, geophysical, well and other technical data developed for a contract area, subject of a PA, by the rightsholder;
Policy Research Working Paper 7662

# **Abstract**

Devolving property rights to local institutions has emerged as a compelling management strategy for natural resource management in developing countries. The use of property rights among fishing cooperatives operating in Mexico’s Gulf of California provides a compelling setting for theoretical and empirical analysis. A dynamic theoretical model demonstrates how fishing cooperatives’ management choices are shaped by the presence of property rights, the mobility of resources, and predictable environmental fluctuations. More aggressive management comes in the form of the cooperative leadership paying lower prices to cooperative members for their catch, as lower prices disincentivize fishing effort. The model’s implications are empirically tested using three years of daily logbook data on prices and catches for three cooperatives from the Gulf of California. One cooperative enjoys property rights while the other two do not. There is empirical evidence in support of the model: compared to the other cooperatives, the cooperative with strong property rights pays members a lower price, pays especially lower prices for less mobile species, and decreases prices when environmental fluctuations cause population growth rates to fall. The results from this case study demonstrate the viability of cooperative management of resources but also point toward quantitatively important limitations created by the mismatch between the scale of a property right and the scale of a resource.

This paper is a product of the Operations and Strategy Team, Development Economics Vice Presidency. 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. Corresponding author may be contacted at sri@acumenllc.com.

_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
# 9.2 Bolivia

The information for Bolivia comes from Denevan (1992) for the East of the country. We also use estimates for the South Sierra derived from Cook (1981), implying a population density of 17.3 people per square kilometer for the South Sierra. In addition, Denevan (1992, p. 228) presents his preferred estimated population �gures for di�erent regions of Northeastern Bolivia: Floodplain (14.6 people per square kilometer), Lowland Savanna, mainly Mojos (2.0), Santa Cruz area (1.8), Upland Forest (1.2), Lowland Forest (0.2), and Superhumid Upland Forest (0.1). Using estimates for the area of each state belonging to each region, we estimate population density in each state.

# 9.3 Brazil

The main source of information is Denevan (1992, p. 226 and 231). Denevan presents estimated population density at time of contact for di�erent habitats in Greater Amazonia, which includes most of the Brazilian states except for portions of the coastal states in the South (Paran�a, Rio Grande do Sul, Santa Catarina, and Sao Paulo). The habitats (estimated population density at contact time) considered by Denevan are: Central coast (9.5 people per square kilometer), Floodplain (14.6), Lowland{Amazon Basin (0.2), Mangrove coasts (4.75)<sup>26</sup> , Upland and Central savannas (0.5). Using these estimates we classify each Brazilian state in each habitat and we estimate population density for the states. In the cases that a state has more than one habitat we use a weighted average considering the di�erent habitats. In order to identify the habitats of the di�erent regions we use information from the Natural Vegetation Map from the Perry-Casta~neda Library Map Collection of the University of Texas.

For the Southern states we also use information from Denevan (1992, Table 00.1) on the total population for Southern Coastal Brazil combined (which implies a population density of 4 people per square kilometer) with the previous information on the density for the di�erent habitats of the Greater Amazonia. Finally, we impute the population density of the state of Goias to the Federal District (Brasilia).

# 9.4 Chile

In the case of Chile there are no detailed estimates of population by state. Instead, there is some information on the location of several native groups, except for the Mapuche people. In this case, Cooper (1946) quoted in Denevan (1992) estimates a pre-contact

> 26For Mangrove coasts, Denevan states "probably considerably less than 9.5 per square kilometer". We use 50% of 9.5.

28
deterrent force.

According to the Armed Conflict Location and Event Database published by the Peace Research Institute of Oslo (http://www.acleddata.com/), the last major conflict event in the Liberian civil war occurred in late July 2003. This anticipated the signature of the Comprehensive Peace Agreement in Accra on 18 August 2003, which was soon followed by the deployment of ECOWAS forces. UNMIL assumed control of the peacekeeping operation as of 1 October 2003, two months after the end of major fighting. No subsequent major battle events were recorded. Thus, no major re-escalation occurred on UNMIL’s watch. Of course, there is no definitive way to attribute the post-Accra peace to UNMIL’s presence as opposed to being the result of natural progress in the peace process. Nevertheless, when the war ended with the Accra agreement in 2003, it ended everywhere in the country. Areas more or less proximate to UNMIL’s deployments may not have differed in this regard. In other words, while UNMIL had little active role to play in dealing with major aggression by armed groups, it is quite possible that UNMIL’s presence was a blanket deterrent for the entire country.

Other parts of the survey data allow us to assess these possibilities, as the survey included questions on events associated with the risk of conflict recurrence. We asked respondents a set of seven retrospective questions about whether they had witnessed activities that were indicative of the possibility of renewed conflict. These activities include whether one’s community experienced armed group fighting, ethnic violence, disappearances or presence of “unfamiliar” people, rumors about recruitment, rumors about possible attacks, people stockpiling food, or people fleeing. Each respondent could say “yes” or “no” to the questions. The questions were asked with reference to two periods: (1) the period just prior to the end of the war, and then (2) one randomly selected period in the post-conflict period—either mid-late 2003, late 2003-late 2005, or early 2006 to present.<sup>21</sup> We added the “yes” responses to create what we can call a “civilian insecurity index.” 21Respondents were only asked about one subsequent period to minimize fatigue from answering too many quesxx
owner notified us that the employee was no longer working, and we removed the subsidy. We believe this process and these spot checks were sufficient to root out minimize ‘phantom’ employees.

In order to determine whether the effectiveness of the wage subsidy differs with the availability of complementary inputs, we also carried out two supplementary interventions. The first was a savings intervention, in which individuals were offered a savings account in which we matched deposits made up to a specified amount. This took place before the wage subsidies started, and the goal of this intervention was to enable firm owners to build up a balance of savings, which they could then use to supplement the worker with any additional capital required to make this worker more productive. The second was a business training intervention, which also took place before the wage subsidies started. Firm owners were offered the ILO’s Improve Your Business (IYB) training, to allow for the possibility that better business practices are needed in order to be able to successfully employ additional labor. Appendix 3 describes these supplementary interventions in more detail.

# **3.3 Randomization and Balance**

After the baseline survey was conducted with those in the booster sample, we stratified firms into six strata using geographic region (Colombo, Kandy, or Galle/Matara) and sector (retail or manufacturing and services). Within each stratum we then randomly assigned 18.7% to the control group (286/1533), 16.3% (250/1533) to get the wage subsidy program alone, 19.3% (297/1533) to get the wage subsidy and the supplementary savings program, 19.3% (297/1533) to get the wage subsidy and the supplementary training program, 7.3% (112/1533) to get the supplementary savings program alone, 9.2% (141/1533) to get the supplementary training program alone, and 9.8% (150) to get the supplementary training and savings programs.

Given the number of groups and the irregular sample sizes across groups, it was not possible to stratify further within strata in doing the randomization.<sup>5</sup> In order to improve balance further on a set of key variables likely to be related to business outcomes we therefore employed a rerandomization procedure. We re-randomized 1,000 times and in each randomization conducted an F-test for equality of means across the seven treatment groups for a set of 13 baseline variables

> 5 We chose to put more observations in treatment groups where we were concerned that take-up would be more of an issue, in order to have sufficient observations in each cell with which to examine intervention take-up.

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Panel (b) shows that life expectancy in the short run (when holding other factors constant) is almost 5.1 years shorter in the warmest regions compared to the regions with the most optimal temperatures. However, the relationship between temperature and life expectancy is not very tight. Indeed, the wide confidence interval on the estimated relationship suggests that there is no statistically significant relationship between temperature and life expectancy.

<!-- Start of picture text --> Figure 1: Estimated short-term relations between<br>temperature/precipitation and income/life expectancy in Chile<br>(a) Temperature and Income (b) Temperature and life expectancy<br>1715 78<br>1515<br>73<br>1315<br>68<br>1115<br>63<br>915<br>58<br>715<br>53<br>515<br>48<br>315<br>115 43<br>5 7 9 11 13 15 17 19<br>5 7 9 11 13 15 17 19<br>Average annual temperature (oC)<br>Average annual temperature (oC)<br>(c) Precipitation and Income (d) Precipitation and life expectancy<br>1715 78<br>1515<br>73<br>1315<br>68<br>1115<br>63<br>915<br>58<br>715<br>53<br>515<br>48<br>315<br>115 43<br>0 0.5 1 1.5 2 2.5 3<br>0 0.5 1 1.5 2 2.5 3<br>Average annual rainfall (m)<br>Average annual rainfall (m)<br>Life expectancy (years)<br>Per capita income (USD/month)<br>Life expectancy (years)<br>Per capita income (USD/month)<br><!-- End of picture text --> _Source:_ Graphical representation of the estimation findings from Table 3. _Note:_ The thick red line represents the point estimate from Table 3, whereas the thin black lines delimit the 95% confidence intervals as estimated using Stata’s lincom command.

Panel (c) and (d) suggest that people in Chile do better with either very little rain or with a lot of rain. For intermediate amounts of rain, both incomes and life expectancy are lower. This is somewhat counter-intuitive, but the findings are robust.

9
**Figure 50: Profits for the 5 Largest State-owned Chinese Banks**

<!-- Start of picture text --> 600<br>500<br>400<br>300<br>200<br>100<br>0<br>2003 2004 2005 2006 2007 2008 2009 2010<br>Industrial & Commercial Bank of China China Construction Bank<br>Bank of China Agricultural Bank of China<br>Bank of Communcation<br>RMB, billions<br><!-- End of picture text --> Source: Bankscope.

<!-- Start of picture text --> Figure 51: Profits for China Mobile<br>140<br>120<br>100<br>80<br>60<br>40<br>20<br>0<br>1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010<br>Source: China Mobile, Annual Investor Reports.<br>RMB, billions<br><!-- End of picture text --> 68