rafmacalaba/data-use-mentions-extended huggingface dataset:
strategy (CAS) documents are now required to diagnose the state of governance and the risks that corruption poses to Bank projects.

The Comprehensive Development Framework unveiled in 1999 underscores the importance of governance and public sector institutional reform issues in the Bank's development assistance dialogue. The World Bank Institute has initiated courses on corruption for developing country officials and conducted surveys on service delivery. The Bank has also put a greater emphasis on institutional reform and capacity building through its lending program.

Bank assistance for intemational efforts to curtail corruption has been mainly in the form of sponsorship of major conferences, dissemination notes and support for the adoption of the 1999 OECD Convention on Combating Bribery of Foreign Public Officials in International Business Transactions.

The impact of corruption on public service delivery performance and poverty alleviation is widely recognized (see e.g. Tomaszewska and Shah, 2000 for empirical evidence). A wide consensus has also recently emerged that corruption is a symptom of failed governance (see World Bank 2000) and hence curtailing corruption requires addressing the causes of mis-governance. Nevertheless, the menu of potential actions to curtail corruption is very large so a framework is needed that provides guidance on ordering potential actions. Prioritization of various actions depends on both the conceptual and empirical views of what works and what does not work in the context of particular countries. Such a framework is also needed for evaluating both Bank and country anticorruption programs. This note proposes a framework for such evaluations.

# **_A Simple Evaluation Framework_**

To focus attention on the corruption aspects of development programs, we use a framework based on the incentives for opportunistic behavior by public officials.<sup>3</sup> To distinguish between highly corrupt and largely corruption-free societies, consider the conditions that encourage public officials to seek out or accept corruption:

- The expected gains exceed the expected costs of undertaking a corrupt act.

- Little weight is placed on the cost that corruption imposes on others.

The first point is based on pure self-interest: corruption will only take place when
How Does India’s Rural Roads Program Affect the Grassroots? Findings from a Survey in Orissa Clive Bell<sup>_∗_</sup> and Susanne van Dillen First version: February, 2011. This version: August, 2012

# **Abstract**

This paper analyzes the effects of all-weather rural roads on households’ net output prices, education and health in a poor, drought-prone region of India. Of 30 villages originally surveyed in 2001-02, when two had such roads, a further nine received them between January 2007 and December 2009 under the program _Pradhan Mantri Gram Sadak Yojana_ . Cross-section comparisons involving all villages and ‘before and after’ comparisons in the nine yielded these findings: (i) net output prices were 5 per cent or more higher; (ii) substantially fewer days of schooling were lost due to bad weather, largely because teachers had fewer absences; (iii) the acutely sick received more timely treatment and were more likely to be treated in a hospital than in the nearest primary health clinic; and (iv) the respondents ranked the resulting benefits in the domains of health and education at least as highly as the ‘commercial’ ones.

Keywords: Rural roads, transport costs, education, health, India JEL Classification: O12, O18, Q12 Sector Board: Transport

> _∗_ University of Heidelberg, INF 330, D-69120 Heidelberg, Germany. We are much indebted to Bijaya Behera, who, as in previous surveys of these villages, organized and directed the field work, personally cleaned the data, and provided numerous insights based on his knowledge of the region and its people. Abhiroop Mukhopadhyay and Indira Rajaraman provided valuable comments on an earlier draft. We alone bear responsibility for any errors that remain. The re-survey was undertaken in connection with the preparation of a World Bank loan proposal. The views expressed in this paper are not, however, necessarily those of the World Bank or its Board.

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5 are likely to make for larger informality effects. First, there are minimal copayments and no joining fee in Thailand’s UC scheme – everyone is covered automatically with a 100 percent subsidy. By contrast, in _Seguro Popular_ households with the means to pay are supposed to contribute, so opting out of the formal sector scheme does not eliminate contributions.<sup>3</sup> Second, the relative generosity of the two schemes differs. Both are less generous than the social security scheme, but the gap is wider in Mexico: in 2000, spending per enrollee in _Seguro Popular_ was just 66 percent that of the social security program; by contrast, on a per-beneficiary basis Thailand’s UC scheme spends 85 percent of the amount spent by the social security scheme.<sup>4,5</sup> Third, the two countries’ social security schemes treat dependents differently: Mexico’s covers dependents while Thailand’s does not. Thus in Mexico once one household member is in the formal sector, there is no incentive – from a health coverage perspective – for additional members to seek a formal-sector job. In Thailand, by contrast, at least prior to the UC reform, the health coverage rules gave each household member an incentive to seek a formal-sector job. Health coverage rules prior to the reform thus created an incentive for Mexican households to limit the number of formalsector workers to one, but for Thai households to keep adding formal-sector workers. The informalizing effect of the Thai reform ought therefore to have been greater – a larger fraction of workers will have been encouraged to formalize prior to the reform, but discouraged from formalizing after the reform.

> 3 It needs to be acknowledged that in practice contributions are less than would be expected from application of the means-testing rule to household survey data, and are a good deal lower for most workers than the social security contribution.

> 4 The Thai scheme excludes a few high-cost interventions (e.g. renal transplants) but for the most
This study picks up where the previous study concluded and addresses the outstanding question of longer-term impacts. One hypothesis we previously posed for the mixed results was related to a multi-tasking problem. While the financial education curriculum urged students to save, budget, and spend wisely, it did so simultaneously, and the concurrent emphasis may have been overbearing. Furthermore, a closer examination of the course books suggests that while the curriculum offered very clear direction on actions such as saving and budgeting (both are good), there was no such indication when it came to purchasing items on expensive credit cards or installment plans. The course instead urged greater awareness and understanding of the pros and cons of spending choices but did not outright discourage the use of credit. Hence, it is likely that while students keenly followed the directions to save and budget, they did less well when such clear direction was not provided.

This type of multi-tasking problem is linked to the literature in psychology on willpower depletion. Moreover, while the school-based intervention provided the opportunity for repeated instruction and exercises that allow for sustained learning, short-term results from Bruhn et al. (2016) suggested that students tended to follow clear directions for some topics (savings, budgeting), but wavered in other aspects where direction was less clear (spending and borrowing).

In the long term, such multi-tasking problems can potentially smooth out with students having more time and opportunity to absorb and experience financial decisions, and subsequently apply learnings from the curriculum to adjust course from financial mistakes.

In this study, we test this new hypothesis on longer-term impacts by following students from the original study for the next nine years, from 2012 to 2020.

For the long-term impact evaluation, we rely on administrative data sources, housed at the BCB. Using administrative data was the most obvious choice since we do not have students’ contact information or addresses. All data for the short-term impact evaluation was collected in schools and the students would have left those schools by now (most of them would have graduated
The model also matches important moments of the data that we did not include in the SMM. The top panel of Table A2 reports the average sector wage as well as the employment transition probabilities.<sup>21</sup> As it can be seen, the model and the data correspond quite well. We can also assess investment patterns by looking at the direction of investment. In the bottom panel of Table A2, we show the percentage of rms that disinvest ( _I <_ 0 ), the percentage of rms with investment inaction ( _I_ = 0 ), and the percentage of rms that invest ( _I >_ 0 ). We do this unconditionally and for two types of rm: low-capital (below the average capital stock) and high-capital (above the average capital stock). On average, the data and the model also correspond well, and especially so for low- _K_ rms.

To further analyze the goodness of t of the model, we present the comparison of several rmlevel outcomes in Figure A3. Panels (a)-(c) show the kernel density estimates of the distribution of employment, capital and prots using the rm datasolid lineand the simulated data from the SMMdashed line. The densities t well. In panels (d) and (e) we present the distribution of log employment and prots conditional of dierent percentiles of the rm capital stock. This prediction corresponds well with the log employment from the rm-level data.<sup>22</sup> We can match the conditional distribution of prots as well.

> 21 Wages are normalized with respect to the average wage across sectors and time.

> 22In the SMM simulated data, there is a linear relationship between log employment and log capital due to the homotheticity of the Cobb-Douglas index in the production function.

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al., 2003, 2006; Rohde et al., 2024). For instance, Mendonça et al. (2017) estimate that perennial lakes, mainly GDEs, trap some 0.33 billion tons of CO2 per year, corresponding to about 1% of the present global CO2 emissions.

GDEs play a crucial role in supporting the livelihoods of some of the most vulnerable populations in Sub-Saharan Africa, such as pastoralists (Rohde et al., 2024). The role of GDEs can often be indirect, for instance, through the hydraulic lift provided by certain tree species. However, GDEs are not consistently identified and mapped on a large scale, especially in developing countries. This data gap is significant, as GDEs, particularly in arid regions, are highly susceptible to even minor fluctuations in groundwater levels, which can jeopardize their survival.

A new World Bank database of GDEs in Sub-Saharan Africa shows their diversity and importance to people living in poverty (Rodella, Zaveri and Bertone, 2023). The database was compiled using a wide range of sources reflecting local and academic knowledge and identifies more than 200 GDEs across four main geographic types—inland surface waters (riverine, lacustrine, and wetland ecosystems); coastal and marine ecosystems (coastal and near-shore marine ecosystems), terrestrial springs (near spring and springs influenced zone ecosystems; includes oases); and terrestrial vegetation (sparse vegetation ecosystems and forests and woodlands ecosystems).

This dataset allows for novel analysis of the potential impacts of intervention affecting groundwater directly and indirectly. For instance, water extraction from aquifers by pumping systems can lead to the overexploitation of groundwater resources and a decrease in groundwater storage, which can, in turn, cause a loss of discharge from groundwater to wetlands, springs, streams/rivers, or coastal areas (McCallum et al., 2013). In addition, a decline in groundwater storage can lead to a decrease in the water table (Wada et al., 2010), rendering groundwater inaccessible to terrestrial vegetation (Barron et
# **A.3 Parameterizing the electricity sub-model**

The parameters of the electricity sub-model are based on three main sources of data – the Input-Output table, the Electric Power Industry Statistics,<sup>21</sup> and the International Energy Agency (2010) “Projected Costs of Generating Electricity”.

The elasticities are summarized in Table A2

# **A.4 Parameters, exogenous variables and data sources**

The key input into the model is the Social Accounting Matrix (SAM) for 2010. This traces the flow of commodities and payments among the producers, household, government and rest of the world. The SAM is assembled from the 2007 benchmark input output table.<sup>22</sup> A summary of this SAM is given in Figure A4, the actual matrix used is disaggregated to the 33 sectors and commodities. From this we derive the labor and capital incomes, the tax revenues for each type of tax, the expenditures on specific commodities by the household, government and foreign sectors, and government payments of all types in equation A76.

These payments are combined with employment and capital input data to give the compensation rates for labor and capital for each sector. The estimates for employment and capital stocks by sector are taken from a productivity study of China (Cao, Ho, Jorgenson, Ren, Sun and Yue 2009) that supplements the official data with labor force surveys. The various tax and subsidy rates are not statutory rates but are implied average rates derived by dividing revenues by the related denominator – value of industy output, capital income, total value added, and imports.

The exogenous variables in the model include total population, working age population, saving rates, dividend payout rates, government taxes and deficits, world prices for traded goods, current account deficits, rate of productivity growth, rate of improvement in capital and labor quality, and work force participation. These variables may, of course, be endogenous (i.e. they interact among each
2015). Single-country studies on house prices and house price developments mainly focus on developed economies, particularly OECD countries, EU countries, and the United States or Canada (e.g., Alter & Mahoney 2021; Davis & Heathcote 2005; Knoll et al. 2017; Philiponnet & Turrini 2017).

Most studies investigate determinants of house prices over time. Jordà et al. (2016), for instance, have gathered time series data on disaggregated bank credit for 17 advanced economies since 1870. With this historical data for the total value of the residential housing stock (structures and land), the authors relate household mortgage debt to asset values, showing that the rise in mortgage credit has financed a substantial expansion of home ownership from about 40 percent in 1950 to 60 percent in the 2000s. Similarly, Knoll et al. (2017) assess how house prices have evolved over time for 14 advanced economies, gathering historical house price data to estimate what drives changes in house prices. The authors show that changes in house prices are largely attributed to changes in land prices. This finding is corroborated by others who also attribute rising property prices to sharp increases in residential land prices, while construction costs have remained relatively stable over time (e.g., Glaeser & Ward 2009; Gyourko et al. 2013). In major metropolitan areas, it is not uncommon for the cost of land to exceed 40 percent of total property price; in extreme cases, like San Francisco, the share can stretch to as much as 80 percent (McKinsey Global Institute 2014).

Gao et al. (2019) dissect property features into two groups when predicting house prices: non-geographical features, such as the number of bedrooms and floor space area, and geographical features, such as the distance to the city center and the quality of nearby schools. This is also documented by Gröbel and

> 9 <u>https://www.numbeo.com/property-investment/</u>

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import protection – i.e., between a policy-imposing economy and a particular trading partner. This bilateral emphasis is important given the discriminatory (i.e., trading partner-specific) nature of import protection.<sup>4</sup> Third, we construct our trade barrier measures at the quarterly frequency and use quarterly macroeconomic data. This allows us to better address the relationship between business cycles, exchange rates, and import restrictions and capture the precise timing of any trade policy changes taking place during the Great Recession.<sup>5</sup> The rest of the paper proceeds as follows. Section 2 presents the predictions of the theoretical literature on temporary trade barrier policies such as antidumping, safeguards, and countervailing duties, the empirical model, and the panel dataset that is used to estimate the model. Section 3 presents our basic results regarding the relationship between trade restrictions and macroeconomic fluctuations based on historical data leading up to the Great Recession. Section 4 analyzes the import protection response after the onset of the worldwide financial crisis. Section 5 concludes.

# **2. Theory, Empirical Model and Data**

# **2.1. Theoretical models of temporary trade barriers and macroeconomic shocks**

A large theoretical literature examines the role of temporary trade barriers in international agreements such as the GATT and WTO. Nevertheless, despite substantial research documenting the countercyclical nature of business cycles and import protection dating back to at least the Great Depression (Irwin, 2011a,b), there is not one universal theory linking imposition of new import restrictions to macroeconomic shocks. Bagwell and Staiger (2003), Crowley (2010) and Knetter and Prusa (2003) are the theoretical contributions that inform our basic empirical approach.

4 Antidumping is explicitly a bilateral policy. Although it was often imposed simultaneously on multiple foreign trading partners in the 1980s and 1990s (see Hansen and Prusa, 1996), there is less evidence of this more recently (e.g., Bown, 2010).
in these countries with a lesser role to play in this regard. Harding and Javorcik (2011) also found that, under certain circumstances, investment promotion efforts could be reasonably cost-effective.<sup>38</sup> While information asymmetries are seen as a relevant cost component that service suppliers confront when trading through Mode 3, no precise cost estimates exist to measure their importance relative to other pertinent Mode 3 trade cost components. However, as is explained in subsection 4.2, investor surveys do not tend to rank information gaps at the top of the most binding constraints affecting investment decisions. Today, specialized information services available on various mobile platforms and disseminated through specialized investment location advisory firms furnish investors (particularly larger ones with deeper pockets for advisory services) with significant amounts of pertinent data regarding potential locations and attendant regulatory requirements.

> 38 Harding and Javorcik (2011) found that a dollar spent on investment promotion leads to 189 dollars of FDI inflows. In other words, bringing a dollar of FDI inflows costs half a cent in investment promotion expenditures. An alternative approach leads us to conclude that an additional job created by a foreign affiliate requires 78 dollars in investment promotion spending.

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Jilin Heilongjiang Shanghai Jiangsu Zhejiang Anhui Fujian Jiangxi Shandong Henan Hubei Hunan Guangdong Guangxi Hainan Chongqing Sichuan Guizhou Yunnan Tibet Shaanxi Gansu Qinghai Ningxia Xinjiang<br><!-- End of picture text --> _Source:_ National Bureau of Statistics of China 2016a.

- **Gender gap.** Comparison between 2014 and 2015 shows that the average years of schooling attained is increasing, but the male-female gap is noticeable (Figure 3.10). Similarly, the real gap can be even larger given that female labor force participation is lower than that of males. In 2015, the data of employed labor force comprised 58 percent males and 42 percent females. In 2014, it was 55 percent and 45 percent, respectively.

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Figure 3 shows the development in employment by industrial sector in the period from 1964 to 1994.2 The total number of formal employees in Zimbabwe reached 1.263.700 in 1994, starting at 736.600 in 1964.

The service sector is the largest employer followed by the agricultural and manufactwuing sectors.<sup>3</sup> Employment increased for all three major sectors over the thirty year period. There is no clear trend in agriculture, leading to only a minor increase (10 percent') as compared to 160 percent and 125 percent increase in the manufacturing and service sectors, respectively.

**Figure 3 Employment by sector in thousands (1964-94)**

<!-- Start of picture text --> 6.5<br>5.5 Agricufture<br>~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~anufacuturin<br>_ > G_ t~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~lectricity<br>4.5 Distribution<br>0 = _ > + ~~~~~~~~~~~~~~~~~~~~~~~~~~Mining<br>3.5 -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~Service<br>2.5<br>1.5<br>C (CO C O N I ND CD Co N CD tO O (N<br><!-- End of picture text --> Data source: CSO. Note: Series are log (employees in thousands).

2 The service sector includes public administration, education, health, private
Policy Research Working Paper 10707

# **Abstract**

Governments often use simplified business tax systems, such as presumptive tax regimes, to register and tax small and microenterprises. Despite concerns about how such regimes could disproportionately affect female-owned and low-revenue entrepreneurs, there is a lack of empirical analysis examining the tax burden. The presumptive tax in Ethiopia has a complex assessment system, where the tax liabilities are determined according to the activity type and turnover (99 activities and 19 turnover bands), and some activities do not have a tax-free threshold. This paper uses two rounds of data in the Ethiopian Socioeconomic Surveys and the tax code to analyze the equity and gender implications of the presumptive tax on small and microenterprises by imputing the effective tax rates. There are three key findings. First, the effective tax rates are higher for businesses in the lowest quartile at 4.3 percent of turnover compared to 1.5 percent for businesses in the highest quartile, using the most recent survey, resulting in a regressive system. Second, male-owned businesses tend to operate in sectors without a tax-free threshold and are more likely than female-owned businesses to face higher tax rates. Third, the effective tax rates are high for businesses in food and beverage services, which is female-dominated, and for transit services, which is male-dominated, due to the lack of a tax-free threshold for these sectors. The study finds that an alternative presumptive tax system with a single tax rate on turnover and an exemption for all low-revenue businesses would be simpler for tax assessment and more progressive.

This paper is a product of the Development Data 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 author may be contacted at hkomatsu@worldbank.org. A verified reproducibility package for this paper is available at http: