rafmacalaba/datause-encoder-data huggingface dataset:
14 coordinating tax reforms: can lost tariffs be recouped?

immediate revenue that leads stakeholders to resist trade reforms in poor countries, the focus is on short-term impacts.

The academic literature on coordinated trade and fiscal reforms in Nepal is scant. Khanal (2006) finds econometrically that trade reform in Nepal over the period 1990-2005 did not lower trade tax revenue. Cockburn (2006) uses a Computable General Equilibrium (CGE) model to study the poverty impact of tariff elimination. His innovation is to incorporate household data in the model to capture complex income and consumption effects. When tariffs are eliminated but 1.1 compensated by a uniform percent increase in consumption tax, he shows that urban poverty falls and rural poverty increases because initial tariffs protected agriculture.

# 1.3.1 _Theoretical Motivation_

In an economy with multiple distortions, reduction of one or a subset of distortions (such as tariffs) may not lead to Pareto welfare gains. This is the essence of the theory of second-best launched by Meade (1955) and Lipsey & Lancaster (1956). Welfare may also not be increasing in the number of reforms that are undertaken because of second-best interactions, except when _all_ distortions are simultaneously reduced. However, it is impossible to know all distortions and their cross-effects. The challenge in trade policy reform, therefore, is to “design small, feasible changes in the existing tariff structure that will result in a welfare improvement when the first-best policy of free trade is not feasible” (Turunen-Red and Woodland 1993, p. 145).<sup>20</sup> A more realistic objective of governments is to maximize revenue which can be used in ways to improve national welfare. When the condition that revenue

> 20 An example of such a feasible change is to remove the biggest distortions first (“Concertina” tariff reform rule). As shown by Bertrand & Vanek (1971), Hatta (1977) and Lloyd (1974), if the highest tariff is reduced to the next highest level, welfare can improve if the good whose tariff is being cut is a gross substitute of all other goods. The other well-known rule is the “proportionality rule” which shows that if all tariffs are reduced proportionally, welfare can be increased.
Policy ReseaRch WoRking PaPeR 4647

# **Abstract**

This paper uses nationally representative survey data from Mexico to compare households with savings accounts in formal financial institutions to their neighbors who do not have such accounts. The survey, which was conducted in 2005, contains information on nearly 5,000 households. The findings show that although neighboring banked and unbanked households have similar demographic and occupational profiles, the former are more educated and have markedly greater wealth. The median banked household spends 32 percent more per capita than the median unbanked household, and the median per capita wealth in banked households is 88 percent higher than that in unbanked households. The findings suggest that education levels, wealth, and unobserved household attributes that might be correlated with wealth and education play a major role in explaining who is banked.

This paper—a product of the Enterprise Analysis Unit, Finance and Private Sector Development Department—is part of a larger effort in the department to study access to financial services. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at SSharma1@ifc.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
stock of some firms led to increases in profits. To test (b), we use the 8 waves of the SLMS to regress reported profits on reported sales, firm fixed effects, and period fixed effects. The coefficient on reported sales is 0.130, with a t-statistic of 9.55. Hence reported profits are strongly responsive to periods of stronger sales for individual firms, providing evidence that reported profits are also useful for studying dynamics.

# **6. How important are recall errors?**

The fact that few microenterprises keep formal business records means that surveys usually must rely on recall to collect business revenue and profit data. Relatively few studies have tried to measure the accuracy of this recall. However, the results of two small studies (summarized in Liedholm, 1991) carried out on 81 entrepreneurs in Honduras and 80 entrepreneurs in Jamaica from 1979-80 give cause for concern. Each study collected data twice-weekly from firms for one year, and then at the end of the period asked them for their best estimate of sales, costs, and profits for the one-year period. In Honduras, mean sales from the one-year recall were 85 percent higher than those derived from twice-weekly visits, and only one-quarter of responses were within 25 percent of the enumerated values. In Jamaica, forty-five percent of respondents said they could not recall annual sales, and mean sales were underestimated by 20 percent for those who did offer a response.

Our analysis of firms in Sri Lanka offers suggests recall error for sales is important, but not as severe as these studies suggest. In the SLMS we asked March 2005 sales from firms in the April 2005 baseline survey, and then asked month by month sales for the first six months of 2005 in the second round in July 2005. Table 5 compares the distributions of the two reports of March 2005 sales, and Figure 1 plots log March sales in round 1 against log sales for the same month reported in round 2. One quarter of firms did not report March sales when asked in the second round. For the 428 firms reporting sales in both rounds, the mean (median) sales are 10 percent (16 percent) lower when asked the second time. The Pearson correlation between the two measures is 0.491, with a Spearman correlation of 0.65. These results therefore suggest recall error is important, providing a reason to keep the recall period at a month rather than for longer periods.

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Tingting Xu, A., B. Weijun Gao, C. Yanxue Li, and D. Fanyue Qian. 2021. “Impact of the COVID-19 Pandemic on the Reduction of Electricity Demand and the Integration of Renewable Energy into the Power Grid.” Journal of Renewable and Sustainable Energy 13 (2): 026304. https://doi.org/10.1063/5.0045825.

Yuan, Qi, Bing Qi, Deyun Hu, Junjiao Wang, Jian Zhang, Huanqiang Yang, Shanshan Zhang, Lei Liu, Liang Xu, and Weijun Li. 2021. “Spatiotemporal Variations and Reduction of Air Pollutants during the COVID-19 Pandemic in a Megacity of Yangtze River Delta in China.” The Science of the Total Environment 751 (January): 141820. https://doi.org/10/gmd6c3.

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may actually seem undesirable. It might seem that changes to that order would impose huge costs that would not be justified by the expected benefits.

While it is easy for those in the West to look at the caste system as an example of societal rigidity, there are examples in the West as well. Consider the overwhelming evidence on climate change. A large subgroup of the US population (a recent estimate is 35%) has created a belief system that there is not solid evidence that the Earth is warming.<sup>53</sup> Change to halt global warming requires collective action. Given the opposition of this group, the action that is required is not (so far) forthcoming. Given the strength of their prior beliefs, additional evidence seems to have little bearing on the climate change skeptics’ beliefs.<sup>54</sup> Another source of societal rigidity can be a low level of trust. Appendix A shows that an economy can be characterized by multiple equilibria with respect to trust and trustworthiness, arising from differences in socially determined preferences and beliefs and not, as in section 2.3, from differences in social capital, i.e., payoffs in the context of a repeated game. In the trust equilibrium in the appendix, the lack of trust can fundamentally _change_ the individual. The identity that is elicited (or primed) in the no-trust equilibrium is different from the one that is primed in the trust equilibrium. While the "trustworthy" individual that is primed in his direct interactions with others could be justified as part of a rational Bayesian equilibrium (it is optimal for him to act in a trustworthy way in interactions with other trustworthy individuals, but to act in a selfish and opportunistic way if he believes he is interacting with non-trustworthy people), his trustworthy mode of interaction carries over into other interactions. He behaves, more generally, in a trustworthy way.

In principle, in models of trust based on repeated games, it is possible to engineer a shift from a notrust equilibrium to a trust equilibrium. There is no lingering effect on “fundamentals” of the episode in which the economy seemed stuck in a no-trust equilibrium. In contrast, in models of trust based on priming identity, once the no-trust identity is primed, it may be difficult to put the genie back into the bottle. Personalities are shaped. Behavior patterns get entrenched and are

> 53 Pew Research Center (2014), section 7 .

> 54 It is increasingly difficult for the climate change deniers to hold onto their position.  Even then, evidence that climate is changing does not answer the question of the cause, the extent to which it is the result of human behavior.  But one doesn't have to answer that question to frame a policy response:  reductions in carbon emissions could still be the best way of preventing the untoward events that would otherwise occur.

54
is also changing. Financing in the form of school fees decreased for vocational schools between 2008 and 2015, even in terms of absolute value, while it increased for regular schools during the same period when public financing was increasing in both types of schools—and faster in regular schools. This is somewhat consistent with the observation above that the household demand for regular schools continues to increase while that for vocational schools seems have tapered off.

Figure 3.6 Composition of school financing 2008, 2012, 2015 (in CNY) <!-- Start of picture text --> Vocational Regular<br>300,000,000 300,000,000<br>250,000,000 250,000,000<br>200,000,000 200,000,000<br>150,000,000 150,000,000<br>100,000,000 100,000,000<br>50,000,000 50,000,000<br>0 0<br>Gov. spending School fee Other Gov. spending School fee Other<br>2008 2012 2015 2008 2012 2015<br><!-- End of picture text --> _Source:_ National Bureau of Statistics of China 2008, 2012, and 2015a.

Relatively, school fees play a lesser role in both types of schools. In 2008, school fees represented 20–30 percent of total school financing. The ratio has reduced to 15 percent for academic schools and merely 6 percent for vocational schools—dwarfed by a fast increase of spending from government sources (Figure 3.7). Nonetheless, this does not mean that households are decreasing their overall education spending—the spending can be high in the form of tutoring and other expenditures.

Figure 3.7 Trend of share of school fees in total senior secondary school financing <!-- Start of picture text --> 30%<br>28%<br>27%<br>25%<br>20%<br>18%<br>16%<br>15% 15%<br>10%<br>6%<br>5%<br>0%<br>2008 2012 2015<br>Voc Reg<br><!-- End of picture text --> _Source:_ National Bureau of Statistics of China 2008, 2012, and 2015a; authors’ calculation.

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structure provided the blueprint on which decentralized governance was modeled on a national scale. Karnataka, on average, has well-functioning _gram sabhas_ with a consistent structure and format of the meeting. Duties and responsibilities govern a major part of discussions, and delegated officers are deeply embedded in discussions with the publics. Among the people, there is a good level of awareness of local programs and development works and the duties of elected leaders. The quality of public participation is inflected by village literacy level. SHGs in Karnataka started in 2000-01 with the Stree Shakthi program launched by the state government. The program is focused on forming women into groups of 15-20 for the purpose of thrift and credit and eventually leading to the uptake of income generation activities. Government estimates put the current number of groups at 1.4 lakhs and the membership strength at 21 lakh women.<sup>11</sup>

**Tamil Nadu** has implemented the institutions and measures of decentralization, but, due to the weak financial devolution to the panchayats, _gram sabhas_ lack direct financial powers of matching budgetary allocations to people’s needs. However, _gram sabhas_ meet regularly and follow a standardized procedure. The _gram sabha_ transcripts present strong evidence of administrative transparency and information dissemination. Tamil Nadu leads all other Indian states in launching a state-wide SHG program. Called the Tamil Nadu Women’s Empowerment Project ( _Mahalir Thittam_ program), the SHG program was first started in 1989/ 90 in a select district.  By 1997-98, the program was launched state-wide and received prominent state support despite regime changes.

# **DATA & ANALYTICAL METHOD**

The data consist of the complete transcripts of 255<sup>12</sup> _gram sabhas_ selected from two districts in each of the four South Indian states: AP: Chittoor and Medak; KN: Dakshin Kanada and Bidar; 18
governments to pursue public policy objectives and are not given the resources to do so. . . the repeated use of such uncompensated quasi-fiscal activities leads to loss accumulation, underinvestment, and/or excess borrowing by the affected SOEs” (Ter-Minassian 2019, 51). Moreover, imposing QFOs on SOEs can create dependency, because excessive losses from QFOs lead SOEs to ask for (and receive) subsidies (fiscal transfers to cover operational losses), which can lead to moral hazard.

QFOs are key to explaining the underperformance of SOEs, because the services infrastructure SOEs provide are basic and essential; voters can directly connect their effectiveness to the SOEs and hence to the government. In addition, because SOEs maximize access to infrastructure services to the population, they often have to operate in remote and unprofitable areas. In addition, they are often subject to government interference and compelled to perform QFOs in the form of consumption subsidies to enable basic access for low-income households. As a consequence of these QFOs, SOEs often incur operating losses, which tend to increase over time and generate dependence on government transfers to operate.

Governments can compensate SOEs for QFOs in ways that avoid losses, but doing so is usually complicated by two problems. First, to budget for QFOs, governments need to estimate their cost ex ante. They can underestimate the cost of the QFOs or the negative effects they may cause because of the moral hazard they create. Second, having the government use SOEs to perform QFOs generates moral hazard because SOEs can overestimate the cost of the QFOs or request additional funds to cover losses generated for QFO–related operations. Hence, state ownership offers advantages and disadvantages for infrastructure SOEs. Because of them, it is not clear how strong or weak their financial performance is and how much they over or underperform similar private firms in the same sectors.

In this paper, we compare the size, cost structure, fiscal support, and financial performance of infrastructure SOEs across countries and relative to private firms, using data from the World Bank Infrastructure SOEs Database, which covers 135 SOEs in 19 countries between 2000 and 2018. We examine the role of state ownership in four sectors: power, airlines and airports, railways, and roads.

The analysis reveals that infrastructure SOEs are large and perform poorly, generating significant fiscal risk. We introduce new measures of performance net of fiscal transfers and examine previously uncovered patterns of subsidies by sector. We show that relative to comparable private firms, infrastructure SOEs are less efficient, represent a larger share of GDP, have larger liabilities as a share of GDP and larger employment costs as a share of revenues, and yield lower returns on assets.

3
Limiting the samples to only children, defined in the previous section as individuals below 18 years of age, leads to sample sizes of about 13,000 children in the GHS surveys and 89,033 in the MICS survey. Table 1 provides an overview of the exact sample sizes for each wave and poverty measure. Sample sizes vary following the definition of the various deprivations, data availability only for a limited age group and response rate. In the case of the GHS, the survey limits itself to individuals of households with consumption data.

As the table below shows, the non-response rates are particularly high for the severe health and food deprivations and hence, results of these deprivations should be treated with caution. Moreover, these large non-response rates or responses falling beyond the biologically possible in terms of weight and length or height for the food deprivation measurement, urges for more emphasis on quality data collection.

Another, more general regional limitation relates to the ongoing conflicts in the country. Any results based on the data sources used here in particular from the North-East and to a certain extent the South-South regions need to be treated with caution, as both the GHS and MICS data collection were limited to only the accessible areas. Even though (Azad et al. 2018) did not find a correlation between conflict and poverty status, as conflict seems to be affecting also non-poor households, there is a concern that conflict increases deprivations, such as educational deprivation suggested in work by Bertoni et al. (2018) and that excluding highly conflict affected areas may underestimate results. While conflict is a concern in three regions of Nigeria, the North East (Boko Haram insurgency), North Central (farmer – herder conflict over land access) and South-South (militant and pirate groups targeting in particular the oil sector), it is only in the North East and to some, but much lesser extent, in the South-South that enumeration areas were declared not accessible for data collection, due to security concerns. This limits in especially the representativeness of the data of Borno, Adamawa, Yobe and Delta states, likely resulting in underestimates of poverty in those states.

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<!-- Start of picture text --> Poly bning, and Re"srch |<br>Poputldon, Health, and Nutrition<br><!-- End of picture text -->

Many developing countries are trying to improve the routine collection of health informiation by strengthening surveys, censuses, and registration systems. At the international level, too, efforts are under way to provide information on health and health interventions, including statistical reporting programs of the U.N. and the World Bank.

In view of the limited financial resources in the developing countries, would a world health survey complement these health infonmation systems and contribute to long-term health care? Is it reasonable to expect that such a survey could identify the pattems and causes of disease and at the same time measure the effectiveness of investments in health?

tradeoffs. Considering the variety of health problems and priorities in developing countries, it is probably more important to develop the expertise to conduct and analyze health studies than to devise a standard questionnaire to collect health &ktta. As for the cost-effectiveness of health programs, a world health survey is not the appropriate vehicle for such evaluations, but it can address such concems as access, coverage, patient costs, and financing systems.

This paper is a product of the Population, Health, and Nutrition Division, Population and Human Resources Department. Copies are available free from the World Bank, 1818 H Street NW, Washington DC 20433. Please contact Anelia Menciano, room S6278, extension 33612.

Although a series of coordinated country health studies could be valuable, there are many The PPR Working Paper Series disseminates the findings of work under way in the Bank's Policy, Planning, and Research Complex. An objective of the series is to get these findings out quickly, even if presentations are less than fully polished. The findings, interpretations, and conclusions in these papers do not necessarily represent official policy of the Bank.

Copyright i 1988 by the International Bank for Reconstruction and Development/The World Bank
contracts, concessions, Greenfield contracts and divestitures – have been applied to all segments of the energy supply chain; however, their relative prevalence differs significantly. For generation, Greenfield contracts for Independent Power Projects are more than twice as likely to be adopted as divestitures or concessions, while management contracts are barely used at all. For distribution, divestitures and concessions are significantly more prevalent than management or Greenfield contracts. For transmission, divestitures, concessions and Greenfield contracts have been used to a similar extent, while management contracts are rarely adopted.

**Figure 6.2: Prevalence of different forms of private sector participation along the electricity supply**

**chain**

|**Percentage of countries**<br>**with**|**Generation**|**Transmission**|**Distribution**|**Any of**<br>**These**|
|---|---|---|---|---|
|Management contracts|2|0*|8*|10|
|Concessions|18**|5**|16|39|
|Greenfield contracts<br>(BOT/BOO)|57**|9**|3**|69|
|Divestiture|29**|7**|25**|61|
|Anyof These|63|14|40|70|

Source: Own elaboration based on World Bank’s Private Participation in Infrastructure 1990‐2015 databases

****** Differences are statistically significant at the 5% level ***** Differences are statistically significant at the 10% level

# **Box 1: Index for measuring the extent of private sector participation reform in a country**

Since there are multiple dimensions to private sector participation reforms, an index is needed to aggregate over all of these dimensions and get a comparative measure of the extent of reform effort in any given country. The table below explains how the scores would be created for the two dimensions of private sector participation reform, namely: scope or how much of the electricity supply chain is affected and coverage or what share of business units at each stage of the electricity supply chain are affected.

|Scope<br><br>50 percent weighting for private sector activity in generation (G)<br><br>50percent for distribution forprivate sector activityin distribution(D)|
|---|
|Coverage<br>(c)<br><br>Percentage of generation capacity with private sector participation<br><br>Percentage of distribution utilities withprivate sectorparticipation|
|Based on these ratings, a summary Private Sector Participation Index can be computed for each<br>country and over time, based on the following formula: where_c_represents the share of the segment<br>that is privatized;_G_is the index for generation;_D_is the index for distribution;_i_indexes the country;<br>and_t_the time period. The index ranges from 0 if no private sector participation reform has taken<br>place to 100 if all generation and distribution companies have experienced private sector<br>participation.<br>������� ������ ������������� ��������0.5 ∗�<sup>�</sup>��� 0.5 ∗�<sup>�</sup>��|

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