rafmacalaba/data-use-mentions-extended huggingface dataset:
Table 2. Size of the first pricing block, and differential between that and second

|1st<br>block<br>monthly<br>consumption threshold<br>(kWh)|Countries|Price differential between first and<br>second block (%)|
|---|---|---|
|300|Ghana, Zambia|Between 30 and 100|
|200|Mali|Less than 30|
|100|Mozambique|Over 100|
||Congo,Dem. Repof|Less than 10|
|50 or less|Uganda, Madagascar, Kenya, Nigeria, Tanzania,<br>Chad, Cote d’Ivoire, South Africa, Zimbabwe|Over 100|
||Ethiopia,Benin,Malawi|Between 30 and 100|
||Cameroon,Cape Verde,Burkina Faso|Less than 30|

_Source:_ Africa Infrastructure Country Diagnostic Power Tariff Database The second question is whether tariff levels on successive blocks rise steeply enough to ensure that costs can be fully recovered on higher volumes of consumption. This principle holds in many cases. Most countries with a first-block threshold set at subsistence consumption levels (50 kWh or less), have a price jump of over 100 percent to the second block (Uganda, Madagascar, Kenya, Nigeria, Tanzania, Chad, Côte d’Ivoire, South Africa, Zimbabwe), signaling a clear intention to differentiate among customers so that larger consumers contribute to cost recovery. But the tariff structures of a few countries—for example, the Democratic Republic of Congo, Cameroon, Cape Verde, and Burkina Faso— are not highly differentiated by consumption level. This makes the implementation of targeted subsidies difficult (table 2).

Thereafter, prices among higher consumption blocks do not rise as steeply as they do between the first and second block. In Burkina Faso, the second block is priced only 6 percent higher than the first one and the third block only 7 percent above the second one. In Ethiopia
on the pre-crisis food price data from 2004 to 2007. We include the

> 12 We note that the concavity of anticipated price shocks is partly driven by some outliers (i.e., those with anticipated price shocks above one), and therefore the concave relationship is not quite robust.  However, even without the concave relationship, the impact of anticipated price shocks on farm investments will be peaked around the similar points even after trimming these outliers.

23
*|0.92***|1.01***|0.57**|1.17***|3.68|-0.09|
|**Multiplier (β0)**|(0.13)|(0.24)|(0.23)|(0.41)|(3.19)|(1.19)|
|Obs|3,897|921|2,976|416|161|255|
|Controls/FEs:||Year|FE,State FEs,|Lagged GDP Gro|wth||
|||**Panel B**|**.2: Instrument**|**al Variables (First**|**stage)**||
|**Coeff (θ) on Leave-**|0.90***|0.90***|0.80***|0.82***|0.35|0.66***|
|**one-out spending**|(0.03)|(0.04)|(0.10)|(0.09)|(0.23)|(0.14)|
|F-stat|683.6|546.6|64.89|91.48|2.296|22.85|

Notes: Robust Standard Errors shown in parentheses (clustered at the NUTS2 for NUTS2 regressions). OLS and IV (second stage) are regressions on the annual change of investment as share of GDP on the scaled "modelled" EU Spending. Country level regressions exclude influential observations Croatia (2016) and Estonia (2011) discussed in the text. GDP growth (as a control) is winsorized at the 90% level for NUTS2 regions and at 98% for country level regressions (though investment data is not winsorized).
|||||||
|parameters:|||||||||
|_λ_|-0.426|(0.101) ***|||-0.402|(0.108) ***|||
|_ρ_|0.766|(0.039) ***|||0.766|(0.039) ***|||
|Endogenous sele|ction||||||||
|test:|||||||||
|Wald chi2|13.56|***|||10.94|***|||

34. One unexpected result may be that _RENT_ has a positive, not negative, coefficient, which is statistically significant. This contradicts economic theory: In a simply monocentric urban model, there must be negative correlation between travel time and housing rents. Our results imply that those who pay more for housing are more likely to use public transit to commute to their workplaces.
within industries does not appear to be directly associated with earnings. While the results from the Table 5 do indicate some compositional changes favoring females and low-skilled workers, these changes are not strong enough to establish income-level correlations.

Table 4: Relationship between the green goods trade and earning across gender and skill levels (without industry fixed effects)

||All|Male|Female|High skilled|Low skilled|
|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|
|**Annual Earnings**||||||
|Green Goods Export Share|0.00149|0.00399|-0.00233|0.000207|0.00388|
||(0.64)|(1.66)|(-0.79)|(0.07)|(1.24)|
|Green Goods Import Share|0.0105***|0.00875***|0.0121***|0.00484**|0.0166***|
||(4.72)|(4.04)|(3.79)|(2.07)|(5.28)|
|Industry FE|No|No|No|No|No|
|Workers control|Yes|Yes|Yes|Yes|Yes|
|N|77544|52868|24676|15708|61836|
|adj. R-sq|0.365|0.360|0.388|0.036|0.123|

_Note: Results are based on repeated cross-sectional labor force survey data that are merged with industry level trade data. Industry fixed effects are at two-digit ISIC Rev 4 level. Worker’s control includes age, age squared, gender, marital status and 8 groups
_C O O R D I N AT I N G TA X R E F O R M S I N T H E P O O R E S T C O U N T R I E S : C A N L O S T TA R I F F S B E R E C O U P E D ?_ swarnim waglé<sup>1</sup> _Abstract_ A revenue-neutral switch from trade taxes to domestic consumption taxes is fraught with implementation challenges in countries with a large informal sector. It is shown for a sample of low-income countries over 25 years that they have had a mixed record of offsetting reductions in trade tax revenue. The then the case of a data paper analyzes specific Nepal, using unique set compiled from unpublished customs records of imports, tariffs and all other taxes levied at the border. It estimates changes to revenue and domestic production associated with two sets of reforms: i) proportional tariff cuts coordinated with a strictly enforced value-added tax; and ii) proposed tariff cuts under a regional free trade agreement. It is shown that a revenue-neutral tax reform is conditional on the effectiveness with which domestic taxes are enforced. Furthermore, loss of revenue as a result of intra-regional free trade can be minimized through judicious use of Sensitive Lists that still cover substantially all the trade as required by Article XXIV of the GATT.

Keywords: tariff, tax revenue, trade adjustment, Nepal JEL Classification: F13, F21, H20, O17 Sector Board: EPOL

> 1 Consultant, The World Bank. I am grateful to Prema-chandra Athukorala for helpful comments and guidance. I thank Paul Brenton, Mombert Hoppe and Olivier Jammes for facilitating the use of the Tariff Reform Impact Simulation Tool (TRIST) developed by the World Bank. I also thank Nepali officials in the Ministry of Finance and the Department of Customs for granting me access to the Automated System for Customs Data (ASYCUDA). And I acknowledge with gratitude Thomas Baunsgaard and Michael Keen of the International Monetary Fund (IMF) for sharing
|Women can work in the same|-3.485|-3.124|-3.290|-2.507|-2.610|-4.647*|-2.901|-3.433|
|industries as men Y:1 N:0|(2.240)|(2.156)|(2.158)|(2.105)|(2.379)|(2.417)|(3.128)|(3.094)|
|Exports (%, cell average)*GDP per<br>capita (logs)|||||||0.065<br>(0.056)|0.083<br>(0.072)|
|Exports (%, cell average)*WBL<br>Index||||||||-0.206<br>(0.367)|
|No. of Workers (logs)*WBL Index||||||||-3.269*<br>(1.737)|
|No. of Workers (logs)*Women can|||||||0.256|0.577|
|<br>work the same night hours as men<br>Y:1 N:0|||||||(0.709)|(0.720)|
|No. of Workers (logs)*Women can|||||||-0.464|-0.326|
|work in the same industries as men|||||||(0.534)|(0.524)|

No. of Workers (logs)*Women can work in the same industries as men Y:1 N:0 79
table shows the significant equalization effects of the three transfer schemes. According to an estimate for 1996, the Western states' per capita own revenue will be DM 3705, while that of the Eastern States will be DM 2030. After equalization, the Western States' per capita revenue will be DM 5510, and that of the Eastern States will be DM 5190.

T able 2.3. Per Capita Revenue Relative to the National Average before and after Transfers: Estimates for 1996

|Ow|n Revenue|After|Interstate|Supplementary|
|---|---|---|---|---|
|||VAT sharing|Equalization|Grants|
|Western States|11%|5%|2%|1%|
|Eastern States|-39%|-18%|-7%|_-5%_|

Source: Data provided by Prof. Wolfgang Fottingger.

# 2.5. The United Kingdom

Unlike federally structured states such as American, Canada, and Gennany, the United Kingdom is a unitary state in which local governments derive their powers and functions from the central government. The central government can, at any time, by the ordinary process of legislation, change the powers of local authorities or abolish them altogether.

14
Honduras the proportions are 6, 5, 4, and 2 percent, respectively. However, it is possible that this reason is correlated with economic factors, since access to education services can be associated with the economic capacity of individuals and households for financing transport costs to where the service is provided.

The declared reasons for dropping out also differ by gender. For males, economic reasons are most often cited, while females are more likely to cite personal reasons, including having to perform household tasks (see Figure 14). In most countries, a larger share of males declare lack of interest as the main cause for having left school, although this category is highly relevant for females as well. In order to go beyond these individual perceptions, the following sections examine empirical correlations and causal evidence on dropouts, utilizing the structure of the conceptual framework presented above.

# **3.1 Empirical correlations: Personal and household characteristics**

Rigorous assessment of the causal relationships suggested by the conceptual framework requires data that is unfortunately not readily available in Central America. In particular, long-term and detailed longitudinal data that follows individuals from early life through at least adolescence would allow researchers to link early indicators, such as primary learning outcomes, to eventual dropout. This type of data has not been collected. However, several natural experiments, caused by weather shocks in particular, have been exploited in Central America, the broader Latin America region, and globally – insights gained from these will be mentioned below. In Section 4, evidence from randomized evaluations of interventions aimed particularly at reducing dropout will be discussed.

Given the limited causal evidence, we focus in this section on verifying the existence and magnitude of correlations between dropout and the factors identified by the conceptual framework. In particular, we estimate the marginal effect of variables captured in household surveys on the probability of being enrolled in school in each country for youth ages 15 to 17.<sup>16</sup> We estimate a probit regression for each country using the
Disease 2019; and SIH/SUS. Estimates assume a price shock of 20%.

Figure 5 depicts the progressive pattern of the long-term estimated medical expenditure changes after implementing a taxation on processed and ultra-processed foods. The lowest consumption decile presents the highest gains, with estimated changes in medical expenditure being almost twice as large as the second decile, three times as large as the third, and 113 times as large as the top consumption decile. While our analysis does not allow us to estimate fiscal impacts on SUS, the public health care system, it suggests that a taxation on processed and ultra-processed foods would have a positive impact in terms of reduced demands and medical expenditure.

_Figure 5_ - Changes in medical expenditure <!-- Start of picture text --> 7.00% 6.56%<br>6.00%<br>5.00%<br>4.00%<br>3.17%<br>3.00%<br>2.02%<br>2.00% 1.45%<br>1.00%<br>0.71%<br>1.00% 0.48%<br>0.31% 0.19%<br>0.06%<br>0.00%<br>1 2 3 4 5 6 7 8 9 10<br>Consumption decile<br>Processed and ultra-processed foods<br>Change in medical costs<br><!-- End of picture text --> Source: Estimates based on POF 2017/2018; Global Burden of Disease 2019; and SIH/SUS. Estimates assume a price shock of 20%.

20
The last two decades have witnessed rising administrative protection via antidumping (AD) measures. When countries negotiate lower tariffs in trade agreements, domestic industries that desire protection against imports can employ several methods to gain temporary protection. The most popular of these methods is to claim that the trade partner is dumping or selling below the “fair value.” This claim is often made and often generates temporary protection, even if it is not true (Konings and Vandenbussche 2008; Aggarwal 2007). AD is an effective loophole that has been exploited by both developed and developing countries.<sup>1</sup> According to the records of the Global Antidumping Database of the World Bank (Bown 2010), roughly 4,500 AD petitions have been filed in the last 20 years by more than 40 countries.

This study empirically examines the pricing effect of AD duties using highly disaggregated firm-level Brazilian export data. First, we examine the effect of AD duties that are imposed on Brazilian exporters on the export prices that they charge in their trading partners’ markets. Second, we investigate the effect of potential (retaliatory) AD measures on the export prices of products that Brazilian firms export to markets that may file AD petitions against the firms. When an AD petition is filed by domestic industries and exporters’ flexibility to price discriminate between the home and target countries is restrained because of the threat of retaliation, we expect the exporting firms to respond by increasing the prices of their shipments to the target country to reduce the dumping margin and avoid that threat. In other words, potential AD duties can have price-increasing effects similar to imposed duties because of retaliatory incentives. Our findings clearly demonstrate such an impact.

In addition to the proliferation of AD duties, several studies have analyzed their pricing and trading effects. For instance, Prusa (2001) and Ganguli (2008) estimate the effect of AD duties on the products being imported and show that these duties have a dramatic impact on 2
to endline. We, therefore, first examine whether or not there is structure, both, to selection into the treatment group and attrition, which could undermine our econometric approach, where we rely on difference-in-difference estimators. Imbalance between treatment and control groups could undermine the key assumption of parallel trends. For example, given that men and women face different barriers in the labor market, we should not expect employment to evolve in the same way for men and women after the treatment. We would expect to observe a difference-in-differences for a treatment group where women are more common than in the reference group, even without the program.

To test for imbalances, we run a simple regression of treatment and attrition indicators at baseline on the socio-economic and demographic controls, GRIT indicators, self-reported optimism, employment status and risk. Table 4 (Column 1 for the treatment analysis, Column 2 for the attrition analysis) shows some signs of structure. In particular, host status and risk preferences are significantly different between treatment and control, with

> 9 For example, “hummus” is used to refer to chickpeas in general but can also be used for the dish involving mashed chickpeas, tahini, lemon and garlic in Lebanon. In other dialects, some qualifiers are required to specify this dish (e.g. hummus ne’em, or smooth hummus). This is akin to identifying a British or American individual using similar variations in foodstuffs such as courgette / zucchini; coriander / cilantro; etc. 10 Specifically, we regress variables with missing observations on the list of all variables with a complete record. We then use the predicted values from this regression to populate the missing variables. Where appropriate, predicted values are rounded to the nearest integer and within answer codes of that variable. In a second round, this process is repeated on the full set of actual and predicted values from the first stage.

11
**Figure 13: “In the city or area where you live, are you satisfied with...” (2019) (% of adults)**

<!-- Start of picture text --> availability of affordable housing 32%<br>availability of quality healthcare 37%<br>quality of water 46%<br>quality of air 58%<br>educational system or the schools 38%<br>roads and highways 37%<br>public transportation systems 55%<br><!-- End of picture text --> Source: Gallup World Poll, 2019.

Kurds have low confidence in national institutions—but they are mostly satisfied with public services in the city or area where they live (figure 14). Kurds and Sunnis are about 30 percentage points more likely than Shias to be satisfied with the quality of water services. Perceptions of local health services have improved among adults living in Baghdad. Among Kurds, the share of adults satisfied with the quality of health care dropped by 10 percentage points from 2010-2019; among Shias, the share dropped by 21 percentage points. Satisfaction with the quality of education remains relatively unchanged for Sunnis and Kurds, but declines over time for Shias and adults living in Baghdad.

16
3 the Intemational Labor Organization, for a large number of countries on a uniform basis); average wages as a multiple of per capita GDP; and what secondary sources do exist concerning the ratio of public to private wages for a few countries in each region.

These difficulties preclude the inclusion of all countries. We were able to collect and verify government employment and wage data for 80-100 countries in the early 1990s, including all sizable countries in every region (with the single exception of Brazil - and Mexico) the largest such survey to-date, accounting for about 90 percent of the world's population. (see Figure 2). As the source statements in the Statistical Appendix explain in detail, country by country, the information covered in this survey was obtained from international surveys, intemational and national country reports, World Bank, UN, OECD and IMF reports--and was verified with IMF and World Bank country economists and in many cases with World Bank Resident Missions. Note that the Appendix tables show all countries, whether or not reliable and complete data could be found. The text tables and the regional averages are based only on countries for which reliable data could be found or estimated concerning: central government administration employment; local government administration employment; teachers; and health personnel. In the course of the research, we also came across information on employment in state-owned enterprises and the military. This information is partial, not verified, and not used in the text: it is included in the Statistical Appendix because of the low cost of doing so and because it may be useful to the reader for other purposes. However, this paper deals exclusively with government employment and wages and - not at all with employment in public enterprises or the military which raises quite different policy and empirical questions.

Although the size of the sample for each region is sufficiently large to make it representative of the region as a whole (see Figure 2), the above qualifications make it clear that one should take the regional averages shown
# **vii. Does public employment crowd- out private employment?**

So far, we have analyzed the determinants of public employment without any reference to the private sector employment. However, it is possible that both variables are related and we have omitted the relationship from the analysis. There is mixed evidence of crowding out in the literature. On the one hand, Behar & Mok (2013) find that public employment fully crowds out private employment using a cross section of developing and advanced countries. Similarly, Malley & Moutos (1996) argue that increases in government employment can have a negative effect on private employment and support this hypothesis with Swedish data. On the other hand, Faggio & Overman (2014) use data on local labor markets in England to show that the impact of public sector employment has no identifiable effect on total private sector employment.

First, we examine some stylized facts of our data set. The scatter plot between private and public employment shows a negative correlation between public sector and private sector employment (Figure 10).<sup>15</sup> The plot of public employment and unemployment rates shows no clear relationship in the data (Figure 11). The measure of public sector employment seems to be more closely related with private employment or the unemployment rate, while the other two measures show more dispersion and a flatter relationship.

Figure 10: Public and private employment <!-- Start of picture text --> 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1<br>Central Gov. General Gov.<br>1 1<br>.8 .8<br>.6 .6<br>Private Sector .4 Private Sector .4<br>.2 .2<br>0 0<br><!-- End of picture text -->

> 15 Each observation is a country in a specific year.

22
There is also evidence from a range of studies that electrification reduces fertility rates in rural areas, with positive impacts for women. For example, census data from across Latin America suggests a systematic negative association between birth propensities and household electrification status in rural areas. One probable channel for the impact of electrification on fertility is through television.

There is a small but important body of evidence on the impacts of television on gender roles and women‘s empowerment, substantiating the frequent references to this in the case study literature and identifying a potential causal mechanisms. For example, Jensen and Oster (2009) find that access to cable television results in lower acceptance of spousal abuse, lower son preference, more autonomy, and greater likelihood of sending young girls to school in rural India. Chong and La Ferrara (2009) find that access to the television network that carries _telenovelas_ in Brazil resulted in higher divorce rates, which may be related to empowerment of women. The impact of TV may stem from imitation of role models of emancipated women in fictional TV dramas.

It would appear that the social benefits of electricity can be enhanced in situations where mass media present an image of empowered women and gender equity. There may also be important complementarities between investments in electricity and in new cooking technologies, with resulting benefits for family health and income.

Supplying electricity to community facilities can have positive effects on women and girls, for example through improving school quality; health care (e.g., refrigeration to maintain cold chain); security and street lighting; social capital from lighting community spaces; and improved economic options for small enterprises.

Engaging women in the supply of electricity and motive energy can also increase their welfare but the evidence is scarce. There is a clear need for rigorous studies to identify key design elements to obtaining benefits for women in energy supply.

x