rafmacalaba/datause-encoder-data huggingface dataset:
Policy Research Working Paper 10869

# **Abstract**

This paper uses remotely sensed and farm-level data to assess the micro-level impacts of the war in Ukraine. Remotely sensed, high-resolution data on areas of war-induced agricultural field damage in different periods are combined with crop cover data for a 2019–23 panel of about 10,000 village councils. Estimates suggest that there were significant negative effects of field damage on crop area, with persistent, direct impacts, the size of which increased over time. However, the economic losses due to conflict-induced increased transport costs reduced profitability by more than 60 percent, far surpassing the losses from direct crop damage in conflict areas. The lack of diversification into less transport cost sensitive, higher value crops—even in areas far from the conflict zone—points to constraints to adaptation and diversification. By increasing the resilience of farmers in non-conflict areas, removing such constraints could accelerate post-conflict recovery and complement efforts toward reconstruction in directly affected areas.

This paper is a product of the Development Research Group, Development Economics. 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/prwp. The authors may be contacted at kdeininger@worldbank.org, dali1@worldbank.org, guido.lemoine@ec.europa.eu, Nataliia.kussul@gmail.com, and Andrii.shelestov@gmail.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
usage of health facilities in India—both in a relatively rich urban sample and a relatively poor rural sample—is higher than the U.S. average of 3.15 visits per person per year (NAMS advance data available at http://www.cdc.gov/nchs/data/ad/ad374.pdf). Because medicines that typically require prescriptions in the U.S. (such as antibiotics) are usually sold over-the-counter in India, it is likely that under similar prescription regimes, the differences in care seeking would be even higher. Other low-income countries have similar results. Across countries ranging from Burkina Faso (whose Gross National Income or GNI per capita was $230 in 1998) to Thailand (GNI per capita $2,740 in 1998), health care utilization is high among the population in general, and among the poorest quintile in particular (Mackinnon et al., 2000).

That patients in low-income countries can access facilities is encouraging. However, whether the higher usage of health facilities translates into better health is a matter of debate. In many countries, the level of expertise of medical care providers is low. In China, the use of barefoot doctors was widely advocated and used – although ironically, this program was abandoned in China just as the rest of the world began to emulate it. In India, the government provides valid licenses to a wide range of health care practitioners: from “real” doctors with a MBBS to a “Practicing Medical Physician” or PMP, whose only qualification is that the person has practiced medicine at some time. In addition, India’s government has brought a large number of semi-trained medical care providers into the medical practice, and “regularized” the use of alternative methods of treatment. African countries trained new cadres of clinicians that required very little formal medical education. In Tanzania, with four medical doctors for every 100,000 people, much care in the rural areas is provided by clinical officers (who have four years of secondary schooling and two additional years of medical training) and clinical assistants (who have only elementary education and three years of medical training).

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amount and quality of available public goods and services. Inflation is expected to increase nonviolent uprisings, because increases in food and energy prices are generally regarded as an important source of dissatisfaction with regimes (Chenoweth & Ulfelder, 2017). We also include a measure tracking the views of informed public opinion experts and business people of corruption in the public sector from Transparency International. Widespread governmentrelated corruption has been identified as a major source of dissatisfaction with the regime, including more recently during the Arab Spring (Arampatzi et al., 2018). However, the individual grievances inflicted by corruption might be more accurately captured by the subjective well-being variable.

In our regression models we control for political-opportunity factors by including a measure of the extent to which a country is an institutionalized autocracy. Autocracies tend to be less tolerant to public dissent, which increases the cost of mobilization while simultaneously reducing the probability that they will be successful (Chenowetz & Ulfelder, 2017). On the other hand, the tendency of autocracies to restrict civil rights and use repression might also motivate people to take to the streets. Our measure of democracy is derived from the Polity data set and ranges from 0 to 10, where 0 indicates that there are no autocratic policies in place, whereas a 10 indicates that a regime is a formal autocracy (Marshall & Jaggers, 2002). Because we include country fixed effects in our regression models, the autocracy variable merely captures variation in autocratic policies over time rather than variation between countries.

In addition, the degree of repression and state-inflicted political terror increases the perceived costs and decreases the probability of success of uprisings, and it may accordingly discourage participation in such events (Carey 2006; Davenport 2007; Francisco 2004). Therefore, we include a measure of state-inflicted _political terror_ derived from the politicalterror scale in Gibney et al. (2015). The scale ranges from 1 to 5, where a 5 indicates that terror (e.g. murders, disappearances, and torture) has expanded to the whole population. Although 17
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switching and the modal mix (MM) or modal shift effects, respectively. Finally, the fourth and fifth terms represent the transportation energy intensity (EI) effect and the economic activity (EA) effect, respectively. The study carries out decomposition analysis on an annual basis over the twenty five years period between 1980 and 2005.

# **3.2 Data**

This paper uses transport sector energy consumption data by fuel type and mode from the International Energy Agency (IEA). Fuels included are biofuel (i.e., ethanol), natural gas, liquefied petroleum gases (LPG), motor gasoline, aviation fuels (i.e., aviation gasoline, kerosene and jet fuel), diesel oil, residual fuel oil, and electricity. The use of coal for transportation is negligible in LAC countries, and so the study excludes it. The modes of transportation considered are domestic aviation, road, rail and domestic water transport<sup>6</sup> . The study excludes energy consumption in oil and gas pipeline transport.

Emission coefficients are based on the carbon contents of fuels and are obtained from Intergovernmental Panel on Climate Change (IPCC) Guidelines for National Greenhouse Gas Inventories (IPCC, 2006) for all fuels except electricity. Emission coefficients for electricity are derived using IEA data on electricity output and CO2 emissions from electricity production (IEA, 2007a, 2007b, 2007c). While CO2 emission factors for other transportation fuels (e.g., gasoline, diesel etc.) remain the same throughout the study period, CO2 emission factors for electricity vary with time. This is because, the carbon content of a fossil fuel is not expected to change over time, but CO2 emission coefficients of an electricity grid change over time as the electricity generation mix and thereby the input fuel mix for electricity generation changes every year. Moreover, the CO2 emission coefficient of a particular fossil fuel is the same for all countries, whereas the coefficient for electricity varies across the countries depending on their electricity generation mix. CO2 emissions are estimated by type of fuel and mode, using the corresponding fuel consumption and associated emission factors. Data on gross domestic product (GDP),

> 6 In energy statistics, energy consumption by international aviation and maritime transportation are not considered part of national energy consumption. These are treated separately under their international conventions (i.e., International Civil Aviation Organization and International Maritime Organization).

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the results suggest that the higher the economic freedom the more likely that the traders of the country request preferential treatment.

All the sectoral dummies included in the regressions are significant, and indicate that there are important differences between different sectors. Two sectoral dummies, machinery and minerals have negative coefficients, implying that exports in these sectors have a lower probability of requesting preferences given the value of these. Textiles, clothing and agriculture are the sectors where there is the highest probability of requesting preferential market access to the EU.

In columns 4 and 5 country specific dummies are included instead of country specific variables. As can be seen, the results of the former are similar to the previous results. In the fifth column, instead of including the variable measuring the hypothetical value of preferences and sectoral dummies separately, variables measuring the preferences by sector were included, proxied by the products of the Preference variable and industry dummies. For all sectors the preference scheme had a positive impact on the uptake of preferences, although with important differences between the sectors. The offered preferences had the highest impact for machinery, footwear, agriculture and clothing products. The sector where the preferences had the lowest effect on the uptake of preferences was minerals, which might reflect the low duty reductions provided for this sector under the preference scheme.

**Table 7 Results of Heckman estimation including sectoral dummies in both equations**

||(1<br>|)|(2<br>|)|(3<br>|)|(4<br>|)|
|---|---|---|---|---|---|---|---|---|
|Ldistance|Utilization<br>rate<br>-0.035<br>(0.012)**|request|Utilization<br>rate<br>-0.035<br>(0.013)**|request|Utilization<br>rate<br>-0.041<br>(0.015)**|request|Utilization<br>rate|request|
|LGDP|0.000|0.019|||0.002|0.018|||
||(0.003)|(0.002)**|||(0.003)|(0.002)**|||
|LGDP/pop|||0.005<br>(0.002)*|0.008<br>(0.001)**|||||
|LPOP|||||-0.009<br>(0.003)**|0.004<br>(0.002)*|||
|LPOPeu|||||0.040<br>(0.016)*|0.115<br>(0.011)**|||
|LGDP/POPeu|||-0.052<br>(0.016)**|-0.101<br>(0.010)**|||||
|LGDPeu|-0.031|0.012|||-0.067|-0.098|||
||(0.003)**|(0.002)**|||(0.016)**|(0.010)**|||
|Freedom index|0.004<br>(0.002)*|-0.003<br>(0.001)*|0.005<br>(0.002)**|0.004<br>(0.001)**|0.006<br>(0.002)**|-0.004<br>(0.002)**|||
|French colony|0.015|0.060|-0.001|0.082|0.019|0.065|||
||(0.013)|(0.014)**|(0.013)|(0.015)**|(0.014)|(0.014)**|||
|Non French<br>colony|0.012|-0.007|-0.003|0.016|0.017|0.006|||
||(0.008)|(0.006)|(0.008)|(0.006)**|(0.008)*|(0.006)|||

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4 paper we attempt to describe ways and means by which such reforms affect various interest groups (including government agencies and users), and how each group may affect the implementation of each reform. We also attempt to develop an approach to estimate the political risks associated with implementation of institutional reforms in the water sector. We first describe ways in which political impacts and political risks were handled in the literature dealing with various reforms and economic adjustment projects. The survey of the literature provides some needed qualitative relationships observed over the years in various countries. Then we propose a procedure which can be used to calculate the political risks, expressed as the likelihood of achieving a given reform. We use available data from the NDP project in Pakistan (World Bank, 1997) to apply our framework; and make inkages to the political economy of the water and drainage sector as they are reflected through the NDP project. We focus on the major institutional reforms and the main.interest groups associated with the NDP. We conclude by providing for risk mitigating and management that should assist the government of Pakistan to cope with the political risks of the various reforms in the NDP.

# **POLITICAL ECONOMY OF REFORMS, POLITICAL INFLUENCE AND POLITICAL RISK ASSESSMENT**

To be able to assess the political risks associated with institutional reforms, it is necessary to know how the stakeholders (also called interest groups or players) are affected by the reforms, what their interests are, and their ability to impact the reforms. A quantitative evaluation of risk can be estimated once the extent of the political effects on the institutional reforms is known.

Although the literature contains a rich set of studies on the political economy of institutional reforms in general (Paul, 1990; Azis, 1994; Bromley, 1989; Nelson, 1992; Haggard et al., 1995; Rose-Ackerman, 1997; Stallings and Brock, 1993), and in the agricultural sector in particular (Bhalla, 1991; Brandao and Carvalho, 1991; Garcia, 1991; Nabi, 1986; Hamid et al., 1991; Rose-Ackerman and Evenson, 1985; Sturzenegger, 1991), very few studies exist that address the political economy of reforms in the water sector. In addition, to the best of our knowledge the literature does not provide direct quantitative estimates of political influence and the political risk of reforms. However, the available literature provides several directions which
# **Table 3: Single Equation Probit Results**

||(1)|(2)|
|---|---|---|
|**Dependent Variable**|**Crisis in t**|**Crisis in t**|
|Ratio of external liabilities to external<br>assets (t-1)|0.005|0.006|
||(1.16)|(1.48)|
|Share of domestic credit to the<br>banking sector in GDP|**-0.021**|**-0.025**|
||(2.59)**|(3.07)**|
|Change in current account surplus<br>(t-1)|**-0.001**|**-0.001**|
||(1.80)*|(1.81)*|
|Increase in capital flight (t-1)|**0.00002**|**0.00002**|
||(7.73)**|(7.60)**|
|Change in ratio of M2 to non-gold<br>reserves|**0.054**|**0.055**|
||(4.44)**|(4.55)**|
|Fall in output (t+1)||0.004|
|||(0.30)|
|Overall fit|<1%|<1%|
|Observations|2341|2298|

Robust z statistics in parentheses

*significant at 10%;** significant at 5%; *** significant at 1% † Without country-specific weights
Policy Research Working Paper 7267

# **Abstract**

This study investigates the impact of World Bank development policy lending for public sector governance on the quality of public sector management and institutions. The World Bank’s Country Policy and Institutional Assessments (CPIA) are used to measure the latter, the study considers only policy conditions targeted at improvements in those areas. The analysis uses a comprehensive country-year panel data set of aid receiving-countries and finds a significant and inverse U-shaped effect of public sector conditions on the quality of public sector governance. For most observed values in the data, the impact is positive, but it turns negative beyond a value of 80 conditions. At that point, the predicted CPIA score is about 0.25 point (0.3 standard deviation) higher than with zero conditions. For most observations, the number of cumulative conditions is below 80, so the estimated effect of more conditions is generally positive. The analysis corrects for potential endogeneity and shows that the results are robust to sample restrictions, the use of an alternative governance measure, and the inclusion of an extended set of control variables. Falsification tests are also consistent with a causal interpretation from conditions to quality of public sector governance. The paper shows that conditions related to public financial management and tax reforms are more effective than those related to anticorruption or civil service and administrative reform, where progress requires changing the behavior of a larger set of “deconcentrated” actors. The paper concludes by describing some innovative ideas in the Bank’s ambitious new public sector management strategy that could improve the effectiveness of its support for public sector governance reform.

This paper is a product of the Human Development and Public Services Team, Development Research Group. 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 sknack@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
# **F SURVEY EXPERIMENT**

_Survey Details_ The sample size was chosen to guarantee two conditions: (i) that the sample represents the population universe with an estimated margin of error of ± 2.5%, and that (ii) we would be able to detect a difference of at least 2% in the primary outcomes between treatment and control groups. The sampling method was probabilistic and stratified using the geostatistical tool of the Colombian Statistics Agency (DANE), which contains information about the urban blocks, locality, and economic strata in Bogot ́a. It was stratified by gender (female and male), two age groups (21–28 and 29+), and economic strata (high, medium, and low). The number of respondents needed in each subgroup was calculated so that the proportion of respondents in each stratum corresponded to the real proportion of inhabitants in that stratum out of the total sample universe. We only surveyed one member per household. The surveyed individual was the one with the closest birthday date to the day when the survey was carried out. The survey involved face-toface interviews conducted in Spanish. The participants were asked 35 questions, which took approximately 45 minutes and were structured in 6 modules: (i) sociodemographics characteristics, (ii) social desirability measurements, (iii) list experiment, (iv) attitudes toward Venezuelan migrants, (v) political views on migrant integration policies and voting intentions, and (vi) general knowledge about the PEP program. Respondents answered the modules in the order listed above; this order was carefully chosen to prevent priming the control group before asking about their prosocial behaviors and attitudes towards migrants. The last module was used to assess the control group’s knowledge about the PEP program.

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# **1 Introduction**

Tax collection in low-income countries is very different from what is observed in higher income settings since state capacity determines the ability of governments to enforce taxation. Tax revenue is equivalent to about 16% of GDP in OECD countries but less than 12% in low-income ones. The composition of collected taxes is also very different: where high-income countries collect over 50% of their total taxes through income taxes, low- and middle-income countries collect less than 30% and rely much more on taxes on goods and services.

Collecting income taxes can be particularly hard for governments given the complexity involved in correctly assessing liabilities (Gordon & Li, 2009). However, the capacity to obtain and process the type of information needed to assess income tax liabilities is rapidly increasing in several low- and middle-income countries. International organizations are committed to improving tax capacity: approximately $200 million in Official Development Assistance (ODA) was aimed at improving tax capacity in 2014 (International Monetary Fund et al., 2016). Nonetheless, these improvements in "government intelligence" and access to technology do not translate automatically into higher compliance but require other actions by the authorities (Okunogbe & Santoro, 2021). For example, communicating to taxpayers the new information available to the tax authority might trigger higher compliance if their beliefs about the probability of punishment are updated.

In this paper we partner with the Tax Authority in Honduras (SAR, for _Servicio de Administración de Rentas_ ) to experimentally estimate the impact of providing information to taxpayers about SAR’s knowledge on their transactions. Using a recently developed risk model, we conduct an experiment with approximately 32,000 taxpayers considered to be at-risk of noncompliance. Taxpayers in the control group receive a reg– ular reminder about the income tax filing deadline a usual communication provided by the tax authority. In contrast, those in the treatment group are informed that the tax authority observes specific transactions they engaged in, implying knowledge about (part) of their realized revenue. In that sense, we see our experimental treatment as providing taxpayers with data about the information set available to the tax authority. That allows us to estimate the average effect of treatment assignment on a range of compliance outcomes, measured using administrative data on tax filing.

While there is strong evidence that the average effect of these types of interventions is positive (see Mascagni (2018) and Castro & Scartascini (2015) for recent reviews), this is not inconsistent with negative or null impacts on some subset of taxpayers (De Neve et al., 2021). We argue that measuring this heterogeneity is crucial for authorities to better target this kind of intervention. While the return on investment of these interventions is often perceived to be extremely high given the very low marginal costs of letter or 2