rafmacalaba/datause-encoder-data huggingface dataset:
before. The results are also satisfactory with regard to the low democracy - low financial openness group, but not conclusive with regard to the other two intermediate classifications.

**Table 4: Multinomial Logit Results**

||Financial Openness (lii<br>Democracy<br>hig|gh),|Financial<br>Openness (Lo<br>Democracv|w),<br>Fina<br>Dem|ncial Openn<br>ocracy (Low|ess (Hig<br>l|h),|
|---|---|---|---|---|---|---|---|
||Coefficie Marginal z<br>nts<br>Effect|-statistic|Coefficients Marginal<br>Effect|z-statistic Coe|fficients Mar<br>Effe|ginal<br>ct|z-statistic|
|Log of Socila<br>Expenditure<br>per GDP<br>Log of<br>GDP/capita|<br>2.348**<br>0.148<br>1.2091'<br>0.076|2.66<br> <br>2.72|4<br>1.739*<br>0.16<br>5<br>0.318<br>0.03|9<br>2.195<br>1<br>0.826|-0.523<br>1.085*|-0.01<br>0.02|1<br>-0.538<br>2<br>2.241|
|constant|-15.209'<br>-0.960|-4.18|6<br>-6.430*<br>-0.62|7<br>-2.406|-7.860*|-0.15|8<br>-2.358|
|significant<br>significant<br>The referenc<br>**Table 5: P**|at 5% level for a two-t<br>at 1% level for a two-ta<br>e category is the_Finan_<br>**rediction Performa**|ailed z test<br>iled z test<br>_cilOpevm_<br>**nce of th**<br>Pr|_ss(Low)-denooaa(Loow_<br>gr<br>**e Multinomial Logi**<br>edicted dependent Variab|_)_<br>oup<br>**t Model**<br>le<br>Total|Percent<br>|||
||||||Correct|||
|Actual depen|dent variable|0|1<br>2<br>3|||||
|0 Financial<br>Democracy (L|Openness (Low),<br>ow)|13|2<br>0|2<br>17|0.765|||
|<br>1 Financial O<br>Democracy (|<br>penness (Low),<br>High)|5|3<br>1|6<br>15|0.200|||
|<br>2 Financial O<br>Democracy (L|<br>penness (High),<br>ow)|4|0<br>1|2<br>8|0.143|||
|<br>3 Financial O<br>Democracy(|<br>penness (High),<br>High)|1|2<br>0|25<br>28<br>II|0.893|||
|<br>Total||23|7<br>2|35<br>67|0.627|||

It can be seen that the multinomial logit provided a satisfactory prediction of the two extreme groups _(lowlow_ and _bhhg)_ while underpredicting the other two groups.

23
Page 73

- Buchanan, R. 1975. "Effects of Childbearing on Maternal Health." PoRulation Reports. Ser. J, No, 8.

- Buvinic, M., M. Lycette, and W. McGreevey, eds. 1983. Women and Poverty in the Third World. Baltimore: Johns Hopkins University Press.

- Caldwell, J.C. 1979. "Education as a Factor in Mortality Decline." Population Studies 33.

- Carloni, A.S. 1987. "Women in Development: AID's Experience, 1973-1985." Vol I Synthesis Paper, AID Program Evaluation Report No. 18, Washington, D.C.: U.S. Agency for International Development.

- Chamie, M. 1983. "National, Institutional and Household Factors Affecting Young Girls' School Attendance in Developing Societies." Washington, D.C., ICRW.

- Chatterjee, M. 1988. "Indian Women, Health and Productivity." Background Paper for World Bank Paper "India: Gender and Poverty", World Bank: Women in Development Division, Washington, D.C., processed.

- Chen, L., E. Hug, and S. D'Souza. 1981. "Sex Bias in the Family Allocation of Food and Health Care in Rural Bangladesh." Population and Development Review 7 (3) 435-474.

- Cochrane, S. 1979. Fertility and Education: What Do We Really Know, Baltimore, MD: Johns Hopkins University Press.

- Cochrane, S., J. Leslie, and D. O'Hara. 1980. "The Effects of Education on Health." World Bank Staff Working Paper 405, Washington, D.C.

- Collier, P. 1973. "Recent Changes in Rice Harvesting Methods." In Bulletin -of Indonesian Economic Studies 9(2).

- Collier, P. 1987. "Women in Development: Defining the Issues." Paper prepared for the World Bank: Women in Development Division, Washington, D.C.

- Collier, P. 1989. "Women and Structural Adjustment in Africa." Oxford University and World Bank: Women irn Development Division, Washington, D.C., processed.

- Dankelman, I. and J. Davidson, 1988. Women and Environment in the Third World. London: Earthscan Publications, Ltd.

- De Beyer, J. 1988. "Employment and Labor Market Issues." In Human Resources Development in Malawi: Issues for Consideration. Southern Africa Department, Population and Human Reso'trces Operations Division, World Bank, Washington, D.C.
Police System indicator from the Global Competitiveness project. This is not surprising: Foreign-owned firms have fewer connections with local residents, yet they have greater assets/streams of wealth. They are thus more likely to be targets and victims of crime.

Perhaps surprisingly, foreign firms have relatively higher productivity in more corrupt countries (as captured by the GC Corporate Ethics). This could reflect that foreign firms are less vulnerable than domestic firms from government expropriation, and are thus able to attain a higher level of productivity.

_Human capital._ Relative to domestic firms, foreign firms are more hampered in firm growth by higher _Enterprise Survey_ Skill Obstacles.

_Infrastructure and Access to Finance_ . Foreign-owned firms gain competitive advantages when domestic infrastructure or access to finance is worse. The coefficient of the interaction term between the foreign dummy and the Power Outage indicator from the Enterprise Survey for log labor productivity is positive and significant, which suggests that foreign firms have higher productivity advantages over domestic firms where local power outages are more frequent. The negative coefficient of the interaction term between the foreign dummy and the Getting Credit indicator from _Doing Business_ suggests that foreign firms have relatively higher productivity than domestic firms when the host country has worse access to finance. These findings are intuitive: Foreign-owned firms have more capital and can afford equipment to generate their own power. They are thus less vulnerable to problems with the local power supply or lack of finance, and their better access to critical inputs would naturally lead to competitive advantage over local firms in such poor business environments.

_Barriers to Entry_ . Foreign-owned firms are less burdened by difficulty in gaining access to land. The interaction between the foreign dummy and the Enterprise Survey’s Land Access Obstacle measure is positive and significant for firm employment growth. This likely reflects the fact that perhaps partly due to foreign firms’ stronger bargaining power, host countries often offer good deals on land when luring foreign direct investment (FDI) (Bai, Hsieh, and Song 2019), and land allocation policies thus bias the playing field in favor of firms reeiving FDI.

Foreign-owned firms benefit more from obtaining construction permits. The interaction term of the foreign firm dummy and the _Doing Business’_ Construction Permit measure is positive and (marginally) significant for log labor producitivty. It seems that foreign firms can benefit more from efforts to reduce administrative burdens once those firms have entered the market. This is not surprising. After entry, foreign firms must inevitably deal with government officials for further permits and approvals. Their lack of local connections could more 19
- duration of time spent away from birthplace or last place of previous residence<sup>5</sup>

- • purpose of their stay (visa type)

The above classification comes from Bilsborrow et al (1997), who also discuss other possible definitions such as those based on ethnicity. The United Nations (1998) defines a migrant as "any person who changes his or her country of usual residence", though residence may refer to a change both of residence or of residential status. Tourists and business travellers, among others, are therefore not included in the international migration statistics, as their movements do not involve changing their usual place of residence. Tourists are often recorded in separate statistics and business visitors are often not recorded among the migrant population.

Statistically, the migrant population can be equated directly with the number of foreigners: either those recorded by country of birth, the foreign-born, or that fraction of the population with foreign nationality, the foreign population. The confusion over migrants is exacerbated, however, by the fact that a migrant’s nationality need not be the same as their country of birth. Nationality can be changed; birthplace cannot (not legally, at any rate). Thus, one may be born locally but qualify as a foreign national if born to foreign parents, or conversely, one can be born a national but still be characterized as foreign-born if born overseas. Table 1 summarizes the various possibilities of what constitutes the foreign population under each definition, taking the examples of Ireland and the United Kingdom. Only domestic nationals residing in their home country of birth do not qualify as immigrants under one or other of the definitions. A third possibility is that one can adopt the nationality of one’s country of residence after some time via naturalization procedures.

Given the variety of nationality criteria and the differences between countries in their willingness to naturalize immigrants, we find the foreign-born criterion more useful for economic analysis, and in our final version of the data, we make use of nationality statistics only where foreign birth data are unavailable. It is also the case that the former corresponds more closely to the notion of international movement: defined by country of birth, a person will generally have had to move at some point in their life to be classified as a migrant.<sup>6</sup>

> 5 Though it is increasingly recognized that distinguishing between shorter and longer term migrants is useful for policy making etc. this division is ignored here since censuses generally fail to make this distinction. Indeed, countries seldom accurately distinguish these alternative series. 6 The caveat is that sometimes country borders are moved, creating apparent migrants out of static households.

5
However, once the impact of indirect taxes is taken into account, the redistributive effort is largely reversed as the Gini for consumable income is nearly as high as it was prior to any fiscal intervention (Figure 4), more so than in other countries in the region, including Poland. Once spending on education and health is taken into account, the overall fiscal effort is inequality-reducing, although less so than other countries.

# **The impact on poverty**

<!-- Start of picture text --> Figure 4. Emerging markets: Gini Coefficient<br>(pensions as deferred income)<br>0.50<br>Georgia<br>(2013)<br>0.45<br>Poland<br>(2014)<br>0.40 Armenia<br>(2011)<br>0.35<br>Russia (2010)<br>Croatia<br>0.30 (2014)<br>0.25<br>Market Income Disposable Consumable Final Income<br>Income Income<br><!-- End of picture text --> Source: Armenia: Younger et al (2016); Georgia: Cancho & Bondarenko (2016); Poland: Goraus & Inchauste (2016); Russia: Lopez-Calvo et al (2016); <u>Croatia: own estimates using Croatian PIS and HBS 2014.</u> Beyond the impact on inequality, which measures the relative position of households, it is important to see the impact on poverty, which depends on the absolute level of income of a household. The results suggest that the combination of taxes and social spending was poverty increasing in 2014 **.** The share of the population whose market income (including pensions) was below the per capita US$10 PPP-a-day poverty line was 28 percent (Table 3). Once the burdens of direct and indirect taxes are considered, these are larger than the direct benefits received from transfers, so that the share of the population whose consumable income is below the US$10 PPPa-day poverty line increases to 50 percent. Similarly, if one were to use Eurostat’s relative poverty line of 60 percent of the median equivalized disposable income, the headcount poverty rate increases from 20.5 percent for disposable income to 28.8 percent for consumable income. Most of the increase in poverty is on account of the burden of indirect taxes, as households are not being compensated for this burden through direct transfers. Even for extreme levels of poverty (such as those captured by the US$2.50-a-day poverty line), social transfers are insufficient to mitigate the burden of taxes so that the level of extreme poverty after taxes and transfers is higher than before taxes and transfers are considered (Table 3). The poverty gap and the severity of poverty decline for all poverty lines when going from market to disposable income, but once indirect taxes are incorporated into the analysis, this effect is reversed.

15
|**Country**|**Intervention**|**Effect**<br>**Sizes**|**Country**<br>**GNI Per**<br>**Capita,**<br>**2015 PPP**|**Labor**<br>**Share of**<br>**Income,**<br>**latest**<br>**available**<br>**year**|**Average**<br>**income,**<br>**2015**<br>**PPP**|**Return to**<br>**literacy**|**Percentage**<br>**change in**<br>**earnings**|**NPV$**|
|---|---|---|---|---|---|---|---|---|
|Peru|ICT in pedagogy|0.04|11,960|0.23|2,736|0.72|0.03|1,247|
|Ecuador|Computer lab + learning<br>software|0.06|11,190|0.37|4,140|0.72|0.04|3,093|
|Peru|One Laptop Per Child +<br>applications|0.07|11,960|0.23|2,736|0.72|0.05|2,530|
|India|Curriculum supplement|0.07|6,020|0.29|1,769|0.51|0.04|1,024|
|China|CAL sessions to minority<br>|0.13|14,160|0.49|6,941|0.24|0.03|3,725|
||students||||||||
|||S|chool Based Ma|nagement|||||
|Senegal|School grant application|‐0.42|2,390|0.21|497|0.59|‐0.25|‐1,991|
|Senegal|School grant application|‐0.21|2,390|0.21|497|0.59|‐0.12|‐1,026|
|Senegal|School grant application|‐0.14|2,390|0.21|497|0.59|‐0.08|‐684|
|Mexico|Grant+school plan+parent<br>association|‐0.07|17,150|0.28|4,738|0.72|‐0.05|‐4,382|
|Mexico|School grant to parent<br>association|‐0.07|17,150|0.28|4,738|0.72|‐0.05|‐4,788|

48
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for agricultural marketing. Highways opened for defense purposes offer export outlets previously unavailable; railroads built to carry minerals also move coffee and cocoa; port facilities built to import wheat can export corn or cassava chips. The policy issue is whether the potential increases in agricultural marketing are adequate to justify substantial additional investments in this type of infrastructure. The mirror question is whether any significant diversification can take place without such infrastructure in place. Only specific project analysis can answer thes'e questions, but it is important to set the analysis in the appropriate context. Potential gains in flexibility of the agricultural economy made possible by diversification do not show up automatically in the costbenefit appraisal of such investments in infrastructure. Planners must find innovative techniques for incorporating such potential gains in efficiency (and income distribution).

5.17 Several nitty-gritty initiatives in agricultural marketing cart help create a more conducive environment for agricultural diversification. For example, government agencies can set up rural buying stations where growers can meet regularly with traders. Daily radio broadcasts can provide information on wholesale and rural market prices for nontraditional commodities as well as the staples sold by farmers. Governments can facilitate the industry's development of appropriate grades and standards to lower transactions costs. and it can provide effective institutional arrangements to make contract farming less risky for both farmer and processor.

5.18 A focus on quality standards and processing opportunities broadens the concept of diversification to include vertical diversification--that is, adding value to the staple commodity itself through more attention to consumer demand for more attractive rice and more convenient forms in which to use it. Vertical diversification in fruits and vegetables has only limited potential for the domestic market, and world markets are highly competitive.44 But innovations in processing techniques, especially aseptic 44/ This point is emphasized in World Bank, "Indonesia: Agriculture Assessment" (1986).
countries (such as Mexico) is disproportionately concentrated in very small firms, compared to employment in richer countries (such as the United States).<sup>10</sup> Next, we compare the distribution of legal form of organization in Mexico and the United States. Table 2 presents for different legal form categories the total number of firms and employment for both Mexico and the United States. In Mexico, a much larger share of employment is concentrated in individual proprietorships (38 percent vs. 6 percent in the U.S.). Since the majority of proprietorships are smaller firms, this finding is consistent with the firm size distribution results from Table 1.

Table 3 shows Mexican state level data for three measures of firm size and for the degree of foreign ownership of firms. The firm size measures are based on data for domestically-owned firms only. The first column shows the simple average firm size, calculated as the sum of employees and contract employees<sup>11</sup> divided by the number of units reported in the census. For Mexico as a whole, there are an average of 13.6 employees per unit reporting in the census, which is close to the average in the median European country reported by KRZ (2002). As KRZ (2002) point out, the simple average number of employees per firm can be misleading because the average may be brought down by a large number of very small firms. For example, the average size of firms in an industry in which a single firm hires 10,000 employees and 9 firms hire 1 employee each is roughly 1,000. If the same industry instead had 99 firms hiring 1 employee each, the average firm size would be roughly 100. But in the sense of most theories of firm size, these two industries are not as different as is indicated by the difference in simple average

> 10 We find similar results if we compare Mexico with OECD countries other than the United States using data on firm size distribution of firms in OECD countries used before by Cabral and Mata (2002). 11 In order to avoid labor laws requiring firms to share profits with employees, firms sometimes establish independent entities which exist only to hire and provide workers to the firm. These workers are reported as contract employees.

20
Table A.6: Effects of mining using continuous distance measures and distance spline.

|VARIABLES|(1)<br>Working|(2)<br>Service|(3)<br>Sales|(4)<br>Agriculture|
|---|---|---|---|---|
|_Panel A : Continuous distance_|||||
|Distance to closest active mine|-0.016***|-0.001|-0.000|-0.011***|
||(0.003)|(0.001)|(0.002)|(0.003)|
|_Panel B : Sample limit to 200km_|||||
|Distance to closest active mine|-0.030***<br>(0.007)|-0.009***<br>(0.002)|0.005<br>(0.005)|-0.030***<br>(0.010)|
|_Panel C : Log distance_|||||
|ln Distance to closest active mine|-0.023***<br>(0.004)|-0.007***<br>(0.002)|0.002<br>(0.003)|-0.015***<br>(0.005)|
|_Panel D : Horse race log distance_|||||
|ln Distance to closest active mine|-0.000|-0.005***|-0.001|0.011*|
||(0.005)|(0.002)|(0.004)|(0.006)|
|ln Distance to closest mine|-0.028***<br>(0.004)|-0.002*<br>(0.001)|0.005*<br>(0.003)|-0.031***<br>(0.004)|
|_Panel E: Spatial lag model_|||||
|Distance to closest active mine|||||
|0-10km|0.027|0.032***|0.003|-0.038*|
||(0.018)|(0.011)|(0.013)|(0.020)|
|10-20km|0.028**|0.019***|-0.015|0.021|
||(0.012)|(0.006)|(0.010)|(0.016)|
|20-30km|0.022**|0.001|-0.008|0.033**|
||(0.011)|(0.005)|(0.008)|(0.013)|
|30-40km|0.004|0.010**|-0.026***|0.024*|
||(0.011)|(0.005)|(0.008)|(0.014)|
|40-50km|0.022**|-0.003|-0.019**|0.047***|
||(0.011)|(0.004)|(0.008)|(0.014)|
|Observations|495,832|495,832|495,832|495,832|

Robust standard errors clustered at the DHS cluster level in parentheses. All regressions controlfor year and region fixed effects, regional time trends, living in an urban area, age, yearsof education, and religious beliefs. *** p<0.01, ** p<0.05, * p<0.1

# **A.3 Additional robustness tests**

In this section we perform a series of robustness tests for the main results. We start by limiting the range of the control group as people living in areas far away may be too different for a meaningful comparison. Reducing the sample to include a control group within 200 km, the sample is reduced to half the initial size. Nonetheless, we see in Table A.7 that all effects point in the same direction and are still statistically significant.

Another concern is that we capture unobserved time-variant heterogeneity across clusters rather than the effects of mines. Access to infrastructure is one possible factor at work, and we include proximity to roads as an extra control variable to see whether the results remain robust. Unfortunately, the road data is not time variant and is only available for a subset of countries. The results are presented in Table A.8, using data from the African Development Bank for Benin, Central African Republic, Cameroon, DRC, Mali, Niger, Senegal, and Togo. We see that 34
- 36 -

urban **areas** is **a** more effective **means** to reach the poor than **are** subsidized prices and constralned supply. During a period of service expansion, econoLic prices are often higher than marginal costs in order to ration supply; such prices **are** also necessary from a financial viewpoint to fund new investment and suppout additional debt. If economic prices prevailed, many public services could greatly reduce their requirements for general tax revenue, leaving those sources for sectors with less ability to generate internal funds.

144. Actual practice in the developing countries is far from this ideal. In most sectors the Bank's recommendations have approached it only marginally, because the fiscal dimension of public sector pricing has been largely ignored. Firding a practical way to resurrect that missing element and incorporate it into pricing **advice** at all levels is a clear priority.

# Suimarv of Maior RecoMMendations

1. Research based on case studies should be undertaken to quantify the expected fiscal and sectoral benefits from an across-the-board policy of efficiency pricing for public sector goods and services. In addition to quantifying potential benefits, the research should aim to develop a widely applicable methodology for integrating fiscal objectives into project and sectoral pricing analyses. Such a methodology must be robust from the macroeconomic perspective, and must bridge the gap between fiscal considerations (e.g., the choice of tax instruments, budgetary allocation devices ) and project/sectoral objectives (e.g., allocational efficiency, X-efficiency, financial vLability).

2. A review of financial covenants across sectors should be undertaken to identify which approaches have been most successful in promoting financial viability. In addition, ways should be sought to more closely integrate the economic and financial_analyses with respect to prilcing issues.

3. Several cross-sectoral issues have been identified where additional research or policy work is needed. These include:

- (i) application of congestion pricing (paras. 26, 69+)

- (ii) earmarking and sectoral budgeting (29, 121+)

- (iii) link between economic costing and X-officiency (49)

- (iv) better supervision and use of pricing/costing studies (57+)

- (v) sunuary of issues affecting the opportunity cost of capital (68)

- (vi) survey of systems of public enterprise taxation (103+)

4. In addition, a number of recommendations have been made in the Annexes for sector-specific work. These include, with their text references:

- (i) coal

- price rationing for scarce domestic coal grades (para. 35)

- incorporation of environmental costs

- scope for increased taxation

- (ii) education - widespread dissemination of existing research - empirical trial of economic costing (22)