rafmacalaba/data-use-mentions-extended huggingface dataset:
from allowing patients to sue doctors for malpractice in the consumer forums, rather than the backlogged courts, was very large (it was the litigation stream with the second highest impact, in terms of numbers affected); most of the benefits went to those who utilized formal sector private medicine. And only 13% of patients utilizing formal private sector medicine came from the lowest two income quintiles. This is consistent with our expectation that Obligation cases tend to benefit those who already have access to services. But the other two other litigation streams with very large levels of impact in terms of numbers of people affected were pro-poor (in the sense that the lowest two income quintiles received more than 40% of the direct benefits of the cases). One set of cases focused on air quality in Delhi and other urban centers, and the other on the right to food, and particularly the provision of midday meals to students in government schools.

The Delhi clean air cases culminated in a 2001 order in which the Indian Supreme Court prompted the Delhi government to take a number of steps to require commercial vehicles in the city to use cleaner fuels. This resulted in sharply lower rates of respirable suspended particulate matter (RSPM) in the air around Delhi. A World Bank study for the number of lives saved and illness episodes averted in Delhi as a function of RSPM decline suggests that the litigation and the policies saved an estimated 14,323 lives in Delhi from 2002-2006 and significantly morbidity among about 523,000 people. The Supreme Court also directed sixteen additional Indian cities to adopt similar policies for air quality,<sup>8</sup> but the overall level of implementation in Agra, Ahmedabad, Faridibad, and other cities covered by the order is only 1% of that in Delhi, so no more than 27,949 people in other cities have been significantly affected..

For the estimate of disadvantaged beneficiaries, we assume the distribution of these illness episodes follows the distribution of asthma in the general population. WHO data show
following are the GTPs surveyed:

1. Generate electricity, heat, or fuel from renewable sources primarily for use within the establishment

2. Improve energy efficiency within the establishment 3. Reduce greenhouse gas emissions (other than by 1 and 2) 4. Either reduce the creation or release of pollutants or toxic compounds produced, or to remove pollutants or hazardous waste from the environment 5. Reduce or eliminate the creation of waste materials 6. Conserve natural resources In 2011, the BLS carried out the GTP survey. It sampled 35,000 firms stratified by region and 2-digit North American Industry Classification System (NAICS) sector. The survey results showed that 75 percent of firms used at least one GTP. Not surprisingly, the top GTP was improving energy efficiency, for which any firm using at least one Energy Star certified appliance would qualify, followed by reducing the creation of waste materials, for which any firm recycling waste—a widespread practice and mandatory in some cities in the U.S. The GTP is not exempt from the measurement challenges. First, while the survey provides examples of each GTP and includes the most salient types, it does not include an exhaustive list of GTPs, leaving room for respondents’ subjective interpretation on whether they use or not a GTP. Second, the respondents of the survey are not the workers themselves, but employers or CEOs, which might lead to biased answers about the importance and applicability of GTPs by workers.

> 24 BLS (2011) and BLS (2012b).

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Dinar, Shlomi, De Stefano, Lucia, Blankespoor, Brian, Katz, David. 2011. Climate Change and State Grievances: A Global Analysis of the Resilience of International River Treaties to Increased Water Variability. Paper presented at the International Studies Association Annual Congress, Montreal, Canada, March 16-19.

Dombrowski, Ines. 2007. _Conflict, Cooperation, and Institutions in International Water Management_ . Cheltenham, UK: Edward Elgar.

Drieschova, A., M. Giordano, and I. Fischhendler. 2008. ―Governance mechanisms to address flow variability in water treaties,‖ _Global Environmental Change_ , 18: 285–295.

- Drieschova, Alena and Itay Fischhendler. 2011. ―Toolkit: Mechanisms to Reduce Uncertainty in International Water Treaties,‖ _CLICO Report_ , Hebrew University of Jerusalem.

- Drury, A. Cooper, and Richard Stuart Olson. 1998. ―Disasters and Political Unrest: An Empirical Investigation,‖ _Journal of Contingencies and Crisis Management_ , 6(3): 153–161.

- Farquharson F., Meigh J., and Sutcliffe J. 1992. ―Regional flood frequency analysis in arid and semi-arid areas,‖ _Journal of Hydrolology_ , 138: 487–501.

Fekete, Balázs M., Charles J. Vörösmarty, John O. Roads, and Cort J. Willmott. 2004. ―Uncertainties in Precipitation and Their Impacts on Runoff Estimates,‖ _Journal of Climate_ , 17(2): 294-304.

Food and Agricultural Organization. 2006. The Africa Dams Database. <u>http://www.fao.org/geonetwork/srv/en/metadata.show?id=38077</u> Gerlak, Andrea and Keith Grant. 2009. The Correlates of Cooperative Institutions for International Rivers. In: Thomas Volgy, Zlatko Šabič, Petra Roter, and Andrea Gerlak, A. (Ed.): Mapping the New World Order, Oxford: Wiley Blackwell.

Gleditsch, Nils Petter, Kathryn Furlong, Havard Hegre, Bethany Lacina, and Taylor
# follows,

_VAT revenue compliance rate Potential base of VAT Average VAT rate_ The VAT evasion rate data are obtained from Silvani and Brondolo (1993) for Chile, Honduras, Guatemala, Panama, Uruguay, Argentina, Ecuador, Mexico, Bolivia, Colombia and Peru. For Brazil, Costa Rica and Venezuela, the compliance rates are not available. However, the revenue productivity (the percentage of GDP collected per point of the VAT rate) can be obtained from the IMF. Data on countries with both compliance rate and revenue productivity are used to fit a line relating these two measures. The relationship is then used to estimate the compliance rates for those three countries.

2. Fraction of labor force not contributing to social security. This variable is obtained from _Averting The Old Age Crisis,_ the World Bank, 1995. The variable measures the number of workers not contributing to social security as a percentage of the labor force. Data are available for all Latin American countries in our sample. The years for which data are available, however, are not the same. For most countries the figures correspond to years around 1991, but for some the latest available year is in the mid 80's (e.g. Bolivia 1985, and Guatemala 1986).

# Infrastructure:

1. Electricity Consumption (KWH per person) in 1992. This is calculated as electricity production x (1 - system losses). Electricity production (KWH per person) and system

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percent respectively. Annual data from 1996–2013 for low- and middle-income countries with fuel >25 percent of total exports. Country fixed effects are included in the regression. RMSE = root mean square error, or sample standard deviation.

# **8. Conclusions**

The evidence does not support the notion that natural resource wealth promotes fiscal indiscipline in general. The permanent income theory suggests that the appropriate response to a resource windfall should depend on how long it lasts. A temporary windfall should be largely saved since the permanent increase in consumption will be small compared with the windfall. The less temporary the windfall is, the larger the proportion that it is appropriate to take in increased consumption.

30
do not raise flags regarding the

> 8 Kilic and Sohnesen (2019) report on a randomized survey experiment that was conducted in Malawi in 2016 and that shows that <mark>observationally equivalent, as well as identical, households in fact answer the same questions differently depending on whether they are interviewed with a short questionnaire or its longer counterpart. The authors find large and statistically significant differences in reporting across a range of topics and question types, which can lead to a difference of 3 to 7 percentage points in predicted poverty estimates, depending on the imputation model. The authors, however, demonstrate that the imputation model using only the predictors that are elicited prior to the</mark>

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organized as follows. Section 2 describes the employed data. Section 3 explains the estimation methodology and identification. Section 4 discusses the estimation results and their robustness checks. Section 5 concludes.

# **2. Data**

Our analysis uses data from the Business Pulse Surveys (BPS) developed by the World Bank to monitor the impact of the COVID-19 pandemic on the private sector. The questionnaire collects information on several dimensions of firm performance, spanning from basic economic indicators—such as the operating status of the business, year of establishment, sales, and employment—as well as firm-specific practices such as managerial practices, technology adoption, and implementation of energy-efficient measures. Firms were surveyed from April 2020 (about end-2019 performance) to June 2023 in several waves, <mark>providing a unique perspectve on the private sector's response to the pandemic and the subsequent economic disturbances caused by the fast post-COVID-19 recovery, Russia’s invasion of Ukraine, and the associated energy price surges and fuctuatons.</mark> Our sample comprises an unbalanced panel of 63,716 observations drawn from 24 countries across four regions (Eastern and Central Europe, Latin America and the Caribbean, South Asia and the Pacific, and Sub4
To ensure comparability between treatment and control groups, we conducted additional balance tests, calculating the standardized differences for both continuous and categorical variables. Standardized differences are increasingly favored over p-values in comparing groups in clinical trials and observational studies, with a threshold of 0.10 or less indicating balanced covariates between groups.

Since no nationally representative survey produces reliable estimates at the ward level, we utilized Tanzania’s latest Census (2022) to compare household-level indicators across treatment and control wards. These indicators included demographics, educational attainment, labor market participation, housing characteristics, and access to public services. In all cases, the absolute standardized differences were below 0.1 (see appendix 1), demonstrating balance between the two groups. Similarly, we computed the standardized differences using survey data from the firms, and here too, the values did not exceed 0.1, further confirming the comparability of treatment and control groups (see appendix 2).

# **3.2 Estimation Strategy**

To analyze the impact of the presence of TRA officials on survey responses, the following equation was estimated: Where:

- _Yiw_ : Outcome variable for business _i_ in ward _w_ .

- _Tw_ : Treatment indicator, equal to 1 if the ward _w_ was in the treatment group (TRA official present), and 0 otherwise.

- **X** _iw_ : Vector of control variables capturing business characteristics (e.g., sector, size, turnover).

- _α_ : Constant term.

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Policy Research Working Paper 7898

# **Abstract**

Do higher food prices help or hinder poverty reduction? Despite much debate, existing research has almost solely relied on simulation models to address this question. In this paper World Bank poverty estimates are used to systematically test the relationship between changes in poverty and exogenous changes in real domestic food prices. The paper uncovers indicative evidence that increases in food prices are associated with reductions in poverty, not increases. A likely empirical explanation is the relatively strong agricultural supply and wage responses to food price increases, and the fact that the majority of the world’s poor still heavily rely on agriculture or agriculture-related activities to earn a living.

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. The author may be contacted at d.headey@cgiar.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
<!-- Start of picture text --> UK: Real Credit<br>(in percent)<br>1967 1977 1987 1997 2007 2017<br>year<br> Medium-term cycle Real credit growth (y/y)<br>80<br>60<br>40<br>20<br>0<br>-20<br><!-- End of picture text -->

# **Figure VI-4: Growth of GDP and Credit Cycle Peaks**

## **A- Oil exporter**

<!-- Start of picture text --> BHR: Growth of GDP and Credit Cycle Peaks IRN: Growth of GDP and Credit Cycle Peaks<br>1967 1977 1987 1997 2007 2017 1967 1977 1987 1997 2007 2017<br>year year<br>Growth of GDP Peak Growth of GDP Peak<br>KWT: Growth of GDP and Credit Cycle Peaks OMN: Growth of GDP and Credit Cycle Peaks<br>1967 1977 1987 1997 2007 2017 1967 1977 1987 1997 2007 2017<br>year year<br>Growth of GDP Peak Growth of GDP Peak<br>ARE: Growth of GDP and Credit Cycle Peaks DZA: Growth of GDP and Credit Cycle Peaks<br>1967 1977 1987 1997 2007 2017 1967 1977 1987 1997 2007 2017<br>year year<br>Growth of GDP Peak Growth of GDP Peak<br>15 1 40 1<br>10 .8 .8<br>20<br>5 .6 .6<br>0<br>percent 0 .4 percent .4<br>local_peak_BHR local_peak_IRN<br>-5 .2 -20 .2<br>-10 0 -40 0<br>40 1 80 1<br>.8 60 .8<br>20<br>percent 0 .6.4 local_peak_KWT percent 4020 .6.4 local_peak_OMN<br>.2 0
and other community and personal services, the proportion was much higher. Two thirds of second jobs are in the service sector. The shares of individuals engaged in managerial, professional and technical occupations in secondary jobs are higher that those in primary jobs. Appendix Figure 4 sums up some recent trends in employment patterns in Latvia.

# **E. UNEMPLOYMENT RATES**

This section will look at the structure of unemployment in Latvia. In Figure 6, it was shown that the level of unemployment in Latvia is still high by international standards. As elsewhere, youth unemployment is higher than unemployment among older workers (see Appendix Figure 3). However, as shown in Figure 11, the ratio of youth to adult unemployment rates, as well as the female – male unemployment ratio is among the lowest in Europe. This suggests that, relative to other European countries, youth and women in Latvia have relatively advantageous employment prospects.

**Figure 11.  Ratio of Unemployment Rates by Age and Gender. CEC-10 and EU-15, 2002**

<!-- Start of picture text --> 3.50<br>3.00<br>2.50<br>2.00 young-adult<br>1.50 women-men<br>1.00<br>0.50<br>0.00<br>RO SI PL CZ HU SK BG LV EE LT EU-<br>15<br><!-- End of picture text --> _Source_ : Canstat 2003/3, OECD, and author’s calculation.

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