rafmacalaba/data-use-mentions-extended huggingface dataset:
the World Bank’s enterprise surveys, the Doing Business report and industry studies are used for evidence on tax compliance costs for business.

Despite some reform effort over the past decade, South Asian tax systems remain complex with different regulations for different industries and types of firms. South Asian governments have introduced a number of changes to their tax laws in an effort to simplify tax systems and improve revenue collection. Corporate income tax rates were reduced throughout the region. India replaced an old fashioned sales tax that did not offer input credit with VAT; Pakistan made some progress in reducing the number of VAT exemptions; Sri Lanka unified the VAT rate at 12%;<sup>3</sup> and Bangladesh is working towards introduction of new VAT legislation, which will be in line with international standards. Nevertheless, a number of distortions remain – tax rates differ by type of industry, product and firm. This policy results in misallocation of resources, creates an unfair tax burden on firms that do not benefit from special schemes, and provides disincentives for firm formalization. It also increases the costs of tax administration, creates opportunities for corruption and results in public revenue losses.

The rest of this paper is organized as follows: section II discusses corporate tax regime in the region, section III outlines key weaknesses in the design of consumption taxes; section IV describes the main challenges in tax administration; and section V offers conclusions and suggestions for policy actions.

# **II. Corporate Income Taxes**

Corporate income tax rates in South Asia are higher than in other developing regions. The average corporate income tax rate for Bangladesh, India, Pakistan and Sri Lanka is 32% compared to the global average of 24%<sup>4</sup> (Figure 1 below). Corporate income tax rates have gone down in all regions over the past decade. While South Asian countries have followed the trend, they started with higher initial rates and reduced them by a smaller percentage than elsewhere in the world.
# **6 Limitations and Robustness**

That data that we have used here has several limitations.

First, there may be measurement error in utilization data due to poor recall or inaccurate records. To benchmark this possibility, the SDI survey data from Kenya was compared to the Kenya DHIS2 survey for the same period ( **Supplemental Appendix Figure 1** ) and found that caseloads were correlated in both reports, with a correlation of 0.79.<sup>8</sup> In addition, time and motion studies have documented similar caseloads in India and Viet Nam; and other studies that measured caseloads report similar averages to ours.<sup>20, 21, 23, 24</sup> Second, SDI data collected caseloads at the level of the facility, not the provider. This is less of a problem in small facilities, which are the majority, but a substantive portion of our results reflect the experience of patients at large, crowded facilities with multiple providers. In these cases, since no data exists on the actual work patterns of individual providers, we split caseloads equally among all providers present, assuming that the present providers were representative of staffing at the facility on a random day. Because the SDI randomly observed in-person providers at the place of practice, our analysis is robust to flexible daily staffing patterns _on average_ , but cannot fully account for changes such as providers who work part-time, providers who move between multiple facilities, and staffing patterns that are responsive to diurnal variation in demand. Ideally, future research would observe detailed work patterns for all clinic staff including precise patient assignments to each provider over a series of work days. In large facilities where we had to estimate the number of providers actually present, there are additional complications; we present a full description of this process and results robust to the exclusion of these facilities in **Supplemental Appendix Tables 2–4** .

Third, in terms of the implications for quality, multiple studies have found a large
guarantee fulfillment of the standards established in the regulations. One way of doing this would be through user surveys. Local authorities are closer to the subsidy beneficiaries and so in the best position to carry out such surveys; municipalities should therefore be active in monitoring public phones.

In some rural phone concessions the franchise-holder delegates responsibility for collecting payments to an administrator. Despite being public phones, they operate like private telephones in terms of billing, which raises two problems. Firstly, it makes it hard for the administrator to charge for long-distance calls, since invoices arrive with a delay. Secondly, if the administrator fails to pay the invoices on time, the service is cut off, thereby harming the entire community. Since 1999 it has been obligatory to install coinoperated phones, but this does not solve the problem of the telephones already installed. Another problem is that coin-operated telephones sometimes break down because the 32
# References

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Biesebroeck, Johannes Van (2005), “Firm Size Matters: Growth and Productivity Growth in African Manufacturing,” _Economic Development and Cultural Change_ 53(3): 545-583.

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Bogetic, Zeljko, and Olasupo Olusi (2013), “Drivers of Firm-Level Productivity in Russia’s Manufacturing Sector” World Bank
Policy Research Working Paper 6094

# **Abstract**

Bank credit to Egypt’s private sector decreased over the last decade, despite a recapitalized banking system and high rates of economic growth. Recent macroeconomic turmoil has reinforced the trend. This paper explains the decrease based on credit supply and demand considerations by 1) presenting stylized facts regarding the evolution of the banks’ sources and fund use in 2005 to 2011, noting two different cycles of external capital flows, and 2) estimating private credit supply and demand equations using quarterly data from 1998 to 2011. The system of simultaneous equations is estimated both assuming continuous market clearing and allowing for transitory price rigidity entailing market disequilibrium. The main results are robust to the market clearing assumption. During the global financial crisis, a significant capital outflow stalled bank deposit growth, which in turn affected the private sector’s credit supply. At the same time, the banking sector increased credit to the government. Both factors reduced the private sector’s credit supply during the period under study. After the trough of the global crisis, capital flowed back into Egypt and deposit growth stopped being a drag on the supply side, but bank credit to the government continued to drive the decrease in the private sector’s credit supply. Beginning in the final quarter of 2010, capital flows reversed in tandem with global capital markets, and in January 2011 the popular uprising that ousted President Hosni Mubarak added an Egypt-specific shock that accentuated the outflow. Lending capacity dragged again, accounting for 10 percent of the estimated fall in private credit. Credit to the government continued to drain resources, accounting for 70–80 percent of the estimated total decline. Reduced economic activity contributed around 15 percent of the total fall in credit. The relative importance of these factors contrasts with that of the preceding capital inflow period, when credit to the government accounted for 54 percent of the estimated fall, while demand factors accounted for a similar percentage.

This paper is a product of the Economic Policy, Poverty and Gender
by multiple factors, and the intersection of poverty, rurality, and gender decreases the likelihood of children attending school: a poor girl living in a rural area is 25 percent less likely to attend school than a boy living in an urban area (World Bank 2012a).

**Figure 11. School enrollment rates, %, gross**

<!-- Start of picture text --> 100.0<br>77.9 79.2<br>80.0 74.4<br>67.6<br>64.7<br>60.0 54.7<br>47.0 46.3<br>40.3<br>36.2<br>40.0 38.1<br>31.0<br>17.1 16.8<br>20.0 15.9 14.6<br>9.0 7.8<br>0.0<br>Female Male Female Male Female Male<br>Primary Secondary Tertiary<br>2001 2008 latest available<br><!-- End of picture text --> _Source:_ WDI data retrieved May 2020.

_Note:_ Latest available year is 2017 for primary and secondary enrollment and 2015 for tertiary enrollment rates.

Early marriage is one of the main reasons girls (4–24 years) drop out of school. According to MICS 2014, early marriage was the third most common reason for girls’ dropout but was not a factor for boys, echoing broader analysis from the region showing that child marriage is one of the main reasons that girls leave school early (Wodon et al. 2017). MICS 2014 data indicate that 21 percent of girls in Sudan were married by the age of 15, but this rate rises to 26 percent if only girls in rural areas are considered. Though national child protection legislation was introduced in 2010, it does not cover protection for girls against early
undermines the cost-effectiveness of emissions reduction. In Phases 1 and 2, the cost per ton of abatement of CAT-R2 is 120 percent and 60 percent higher than that of CAT-NO, although allowance prices are lower. The presence of the RPS targets results in an inefficiently high renewable share, particularly in Phases 1 and 2.

Finally, we report “Leakage Rates” at the bottom of Table 4. The potential relocation of production and emissions to foreign countries that are not bound or less bound by emissions regulations is an important policy concern for countries implementing carbon pricing in traded sectors. The leakage rate is defined as the rise in emissions abroad relative to the domestic reductions achieved by the climate policy. Its magnitude is assessed using China’s import and export data and the average emissions intensity of imported and exported goods. We find that emissions leakage, across all cases, is generally small when compared to China’s emissions reduction.<sup>21</sup> Prior literature has demonstrated that TPS can mitigate emissions leakage due to their implicit output subsidies (Fischer & Fox, 2007; Holland, 2012). Our results confirm this: leakage rates under DEPS are approximately a quarter of those observed under the CAT system.

# **2. Relative contributions of overlapping policies**

While Table 4 focused on the stated overlaps, Figure 2 explores the contributions of different policy components to cost reductions under the DEPS, by comparing the impacts of the scenarios S2 and RN, as well as R2. In all three cases, the benchmarks are set to meet the same renewable energy and national emission targets.<sup>22</sup> Here, we focus on Phase 3, when IEP applies to a significant portion (25%) of electricity consumption.

Individually, both IEP and the implicit electricity tax under the RPS improve the costeffectiveness of the DEPS, with the most benefits coming from the RPS-introduced endogenous electricity taxes. The difference in cost per ton of abatement between the R2 and RN cases under the
decisions whose effects are narrow and tied to the initial litigants, or whether the impact is the product of broader, more _erga omnes_ -like decisions.

Using the results of the Gauri and Brinks investigation, we can identify broad national trends in this regard, with some sub-national variation. In general, South Africa and India are the two countries with the most _erga omnes_ -like effects. Both of these countries spring from, or were heavily influenced by, the common law tradition. In South Africa, as seen in Table 1, below, the court decisions are either Regulation cases or Provision cases given broadly policy-like effects. There are no consequential Private Obligation cases in the mix (Brinks and Gauri 2008: 330). The key decisions are made by the centralized Constitutional Court, have the force of precedent, and bind legislators and future litigants alike, thus extending their reach through both indirectlegal effects and indirect-policymaking effects. Similarly, India relies more than any other country on Regulation cases, which we expect to have the most progressive impact, and very little on Provision cases. What Provision cases there are – the cooked noonday meal cases, for instance – produce their effect through large-scale policy changes, affecting vast numbers of people beyond the individual litigants (Gauri and Brinks 2008: 328). South Africa in general, then, and India‘s Provision and Regulation cases are expected to be more pro-poor. The Indian sample, however, also includes very important Obligations cases, which we expect to have a less egalitarian effect, regardless of the effect of precedent.

Most of the impact of SE litigation in Indonesia comes from an abstract challenge to the national education budget. By definition, this course of litigation affects non-litigants, and thus is expected to have a more progressive effect. The other cases in this country should be less progressive – they are Provisions cases with narrower effects. Brazil is the paradigmatic case for individual effects from individual provisions cases. We expect its Provisions decisions to be less 17
.040|0.924|
|**Property owner**||||||
|Index: Perceptions of service delivery fairness|570|-0.000|0.070|0.084|0.404|
|Index: Perceptions of service delivery quality|589|0.000|-0.016|0.079|0.840|
|Index: Relationship with tenants|371|-0.000|-0.043|0.105|0.680|
|**Tenant**||||||
|Index: Perceptions of service delivery fairness|357|0.000|0.030|0.107|0.779|
|Index: Perceptions of service delivery quality|402|0.000|0.086|0.101|0.395|
|Index: Psychological well-being|403|0.000|0.139|0.105|0.186|
|Index: Community activism|403|0.000|-0.084|0.101|0.411|
|Relationship with property owner (scale of 1 to 10)|403|8.266|0.232|0.241|0.337|

*** ** * _Notes_ . p<0.01, p<0.05, p<0.1. Sample includes all compounds that were included in the follow up survey: control and treatment compounds in enforcement-treatment clusters. Property owner and compound water outcomes are from the property owner survey. Tenant outcomes are from the tenant survey. Indices are computed following Anderson (2008), normalized by the control group. All monetary amounts are in USD using an exchange rate of 100:1, unless otherwise stated. [1] In minutes.

35
slight decline and stabilization in global debt. The IMF projects a gradual decline in advanced economies and a small increase in EMDEs, while forecasts for EMDEs excluding China show a slight decline and stabilization over 2021-25. The S&P forecast is similar and implies a small increase in EMDE debt over the next four years and a small decrease in advanced economy debt. Data are available for 39 advanced economies and 153 EMDEs from the IMF’s October 2021 World Economic Outlook. Data are available for 36 advanced economies and 85 EMDEs from S&P’s Sovereign Risk Indicators, 2021 Estimates.

> 6 The study used government debt forecasts made by the IMF for the period 1995-2020 and the Economist Intelligence Unit (EIU) for the period 2007-2020, covering an unbalanced panel of 174 countries.

> 7 A forecast evaluation exercise by the U.S. Congressional Budget Office also found debt forecast errors were larger following recessions (CBO 2019). The average error of forecasts five years after a U.S. budget year was -0.6 percentage points of GDP (an underestimate), and the average absolute error was 7.1 percentage points of GDP.

10
probability in each individual cluster following a change (a one standard deviation shock) in the indicator specified in the vertical axis. A positive value represents an increase in the probability of being in that cluster; e.g., greater exchange rate flexibility increases the probability of being in the higher growth and higher vulnerability (H) cluster. The opposite is the case for negative values; e.g., greater financial openness reduces the probability of being in the higher growth and lower vulnerability (G) cluster. The standard deviation shocks are derived from the data for the countries covered and that were observed during the period 2000-08. The charts are based on the 2-year average estimation.

As is the case with trade, financial openness also appears to increase vulnerability. However, it appears to do so in a similar magnitude in both the higher growth and higher vulnerability (H) cluster and the lower growth and higher vulnerability (V) cluster. Financial openness also appears to reduce quite significantly the probability of being in a higher growth and lower vulnerability (G) cluster, an effect that does not take place in trade openness. In other words, financial openness might deliver high growth, but might also lead to the worst of all possible outcomes (cluster V). Thus, financial openness appears to act primarily at the level of the vulnerability dimension. Interestingly, the type of financial openness also matters. If FDI plays an important role, then countries are more likely to end in either cluster L or cluster G, suggesting that FDI type financing sources have stronger stability features than other financing sources. While these results are in many ways in line with our priors, they still serve to 12
# **2.5  Other Types of Female Empowerment**

Whereas the papers discussed so far are concerned with the effects of female access to financial resources, another branch of the literature puts the spotlight on measures of female bargaining power. Thomas (1994) uses the relative education level of the wife compared to the husband as a proxy for bargaining power. Based on data from the United States, Brazil, and Ghana, the paper documents that the mother's education has a bigger effect on the nutritional status of girls (measured by height for age) compared to the father's education, while the opposite is true for boys.

Another important determinant of bargaining power in marriage should be the value of the outside option. Rubalcava and Thomas (2000) exploit variation over time and across U.S. states in the aid paid to single women with children (Aid to Families with Dependent Children, AFDC). AFDC improves the outside option of married women with children, and therefore might affect their bargaining power in marriage. Based on PSID data from 1968 through 1992, the authors show that the presence of AFDC indeed has a significant impact on expenditure shares with marriage. This is especially true for low-income households with children, those most likely to benefit from AFDC in case of separation. Interestingly, and contrary to studies from developing countries, the food budget share is lower when female bargaining power is higher.<sup>9</sup> Additional data from the Consumer Expenditure Survey (CEX) shows that the share allocated to child goods (toys, baby clothing, baby furniture) increases, while the share of “male” goods (alcohol, car maintenance, sports entertainment) decreases. The authors also find an increase in health care spending, which they interpret as human capital investment.

Bargaining power may also increase in asset holdings. This idea is explored by Doss (2006). Using data from the Ghana Living Standards Surveys in 1991/92 and 1998/99, the
the nonfarm business sector, divided by the population measure. Consequently, the di↵erence in the variation of _HRt_ over _HCt_ is due to variation in employment.<sup>24</sup> Figure 9 displays the annual growth rate of total hours versus the annual growth rate of total employment. As the figure shows, the two series are highly correlated displaying similar fluctuations which suggests that employment is the main driving force of total hours. For this reason, we also present _alternative measures_ of _HRt_ and _HCt_ , computed simply as employment divided by population.<sup>25</sup> As in Fisher (2006), the price index of capital investment, _PK_ , corresponds to the price of total investment and is constructed with the equipment deflator and the NIPA (National Income and Product Accounts) deflators for residential and nonresidential structures, consumer durables and government investment. The equipment deflator was constructed by Gordon (1990) for the years up to 1980 and was extended by Cummins and Violante (2002) for the years up until 2000. We extend the Gordon-Cummins-Violante index further to 2007 using the pattern of NIPA investment price series. The rest of the data were taken from the NIPA tables. The price index, _PGDPt_ , used to deflate the price of capital investment is the implied deflator from chained real GDP. Aggregate output in the consumption good sector is nominal GDP net of R&D investment as reported in the BEA-NSF satellite account, deflated by the implied GDP deflator. Outputs _YRt_ and _YCt_ are obtained by dividing real R&D investment and real aggregate output in the consumption good sector by the population

> 24Previous studies also indicate that most variation in total hours is due to variation in employment than variation in individual hours (e.g. Hansen (1985), Castro and Coen-Pirani (2008)), especially at annual frequencies.

> 25The theory could also be summarized by an indivisible labor model a la Hansen (1985) and Rogerson (1988). In that case, the optimality