rafmacalaba/datause-encoder-data huggingface dataset:
<!-- Start of picture text --> b#<br><!-- End of picture text --> <!-- Start of picture text --> b#<br>8.0e-08<br>6.0e-08<br>F(b)#<br>4.0e-08<br>2.0e-08<br>0<br>0 5.00e+07 1.00e+08 1.50e+08 2.00e+08<br>Total Income<br>Density<br><!-- End of picture text -->

**Figure 1:** Total Individual Income Distribution for Colombia, Household Survey. Source: author’s calculations using the Great Integrated Household Survey (GEIH), 2010. Note: The analysis considers only positive total individual incomes and the population above the age of 20. The red bar indicates the legal threshold for mandatory tax filing, _b_ .

to be part of the tax records data, which, as discussed above, is the threshold _b_ for the methodology presented in this paper. The proportion of individuals who are not required to file a tax return is _F_ ( _b_ ). The figure illustrates the low representation of the richest individuals in the household survey. Incomes above the threshold _b_ (81 million pesos) are captured by the tax records, as shown in Figure 2.<sup>9</sup> Income is defined to include all sources reported by the individual in the tax return: wages and other labor payments; fees, commissions, and services; interest and financial income; other income (rents) minus 1/6 of the cost of deductions.<sup>10</sup> This definition of income is used in order to make it comparable with the income reported in the household survey, using the same adjustments as Alvaredo and Londoño (2013).

Table 1 shows the estimates of the Gini coefficient using the methodology described

> 9Figure 2 is truncated at the highest income levels for readability.

> 10Using 1/6 of the cost of deductions is ad hoc. The tax file does not provide any information about which deductions are included in this category. For more details, see Alvaredo and Londoño (2013).

13
# **II. DEVELOPING COUNTRY POLICIES**

The analysis in this section documents the great progress made by many developing country WTO members in liberalizing their trade regimes since the early 1990s (see also Drabek and Laird 1998; Finger and Schuknecht 1999). The liberalization has had several dimensions: (1) applied tariffs have been lowered; (2) the overall use of formal non-tariff barriers to trade has decreased in many countries; (3) services have been liberalized in many sectors; and (4) in general, the incidence of government intervention in trade has declined. The analysis also throws light on a number of outstanding issues in the reform agenda and some new challenges which have emerged. For example, unilateral liberalization has increased the gaps between tariff bindings and applied tariffs, increasing the uncertainty to exporters wishing to access these countries' markets as well as the opportunities for resurgent protectionism. Also, while the overall use of non-tariff measures has declined, the use of trade remedies, such as anti-dumping, as well as TBT and SPS controls on imports is on the increase.

The analysis of trade policies is based in part on information from 50 developing countries for which Trade Policy Reviews (TPRs) had been conducted under the GATT and the WTO<sup>1</sup> . The group includes 15 economies in Latin America and the Caribbean, 17 in Asia, 13 in Sub-Saharan Africa and five in Europe, Middle East and North Africa.<sup>2</sup> They account for over 95 percent of the total trade of the developing members of the WTO. Their policies and problems can be taken to represent the developing countries as a whole. For 40 of these countries the TPRs go back to 1990 and give us a perspective on the evolution of their policies over more than twenty years.<sup>3</sup> 3
which are developing), reveals that the H-statistic for Jordan is below the 0.52 average across all countries and the 0.55 average obtained across developing economies.

To identify the factors that explain differences in the H-statistic for Jordan vis-à-vis other countries, we estimate equation (3): where i is the country identifier, Z is a matrix of country characteristics discussed below, and u is the error term. We estimate equation (3) for 91 countries around the world using Bankscope data for the period 1994-2006 (see Table 7). The idea is to use the parameters from this estimation to determine the factors that explain the degree of competition in Jordan vis-à-vis other countries. In particular, we hope to compare Jordan to: (i) all other countries, (ii) all other developing countries, and (iii) a group of non-oil producing neighboring countries plus the Eastern European countries with similar GDP per capita.

Following Claessens and Laeven (2004), we include as regressors variables that capture countries’ market structure, contestability, macroeconomic conditions, and general level of development. Furthermore, we also include variables that capture the extent of transparency in the system. In particular, as indicators of market structure, we include the concentration ratio (defined as the share of assets held by the five largest banks), the number of banks per population, the share of assets owned by government banks, and the share of assets owned by foreign banks. To capture market contestability, we include the number of documents or procedures required to obtain a banking license, the fraction of applications for bank licenses denied, and an index of the extent of restrictions on bank activities. We also include the log of the minimum capital required to open a bank and the capital adequacy ratio, since high capital requirements are likely to deter entry. We include an index of bank auditing requirements and an index of bank disclosure requirements as measures of bank transparency. All the variables discussed so far come from the Barth, Caprio, and Levine (2001) database. We control for the impact of macroeconomic conditions by including the inflation rate and the real GDP growth. These variables come from the _World Development Indicators_ . As measures of institutional development, we include GDP per capita from the _World Development Indicators_ and, alternatively, an index of property rights from the _Heritage Foundation._

- 8 -
22 57. Concern about rapid population growth has steadily increased in developing countries, but the ability and resources to mount effective family planning programs are limited in vaAious regions. Research was conducted in FY88 on experience in and out of the Bank with service delivery to poorly served groups at the periphery. This PHR Department research indicates that Bank-financed population (and health and nutrition) projects are often not designed to target clients at the periphery. The research paper, "Costs, Payments and Incentives in Family Planning Programs: A Review for Developing Countries,O reviewed different country approaches to (1) charging for, or providing free, different contraceptive methods and services in the public and private sectors and (2) incentives to encourage contraceptive use. In connection with its policy-related work, PHRHN prepared its annual demographic projections by region, country department and major economic groupings. World population projections and related demographic statistics were updated and published.

# III. THE BANK' S COMNITHENT TO AND CAPACITLY M E.N_ ACTIMITE

58. Population is a subsector of PHN in terms of lending, but population issues are critical to many areas of development and thus to the overall mission of the Bank. In this section we review the history of Bank involvement in the population field and consider the strengths and weaknesses of the Bank's recent population activities.

# A. Thl DemogXrahic Context

59. The world's population doubled between 1950 and 1988 and nearly 90% of this increase occurred in developing countries. Although the rate of population growth has slowed -- to 1.7% per year -- annual growth rates remain high in several developing regions: about 2% in south Asia, over 2% in Latin America and over 3% in Africa. At an annual growth rate of 3%, a population doubles every 23 years. The reason for this rapid rate of growth is declining mortality rates -- as yet unmatched by declines in fertility.

60. Reduced rates of population growth could contribute to development and individual health, but an estimated 300 million couples who wish to control their fertility do not have the means to do so. If couples had only the number of children they say they want, the fertility rate in Pakistan would be four children per woman instead of six; in Egypt it would be three instead of five. In many Sub-Saharan African countries, few women wish to stop childbearing, but many wish to delay the birth of their next child. In Ghana, for example, 37% of the women who want another child want to wait at least two years. This desire to space children in part reflects women's recognition that the health of mother and child are improved by birth intervals of at least two years. Data from 34 countries show that neonatal mortality is 70% higher if the mother has a child under two when her next child is born; the mortality rate is 90% higher in the post-neonatal period. Children born to women under 20 and into large families also experience higher mortality.
The unemployed and people who work in voluntary services were also excluded. The same variables and sample definitions are used for all surveys, which gives us comparable economy-year results. For every survey, the top 0.5 percent of the sample was eliminated to avoid possible biases due to wage outliers. Like many other studies, school attainment is defined by the highest grade attended and completed; experience is defined as potential years of experience, where this is defined as age minus years of schooling minus six (as the typical school starting age). Both variables are measured in years. Annex Table 1 presents the list of economies and years used in this study, along with the returns to schooling (both as an aggregate variable and by levels).

# **IV. RESULTS**

The basic earnings functions, equations (1) and (2), were applied to three different groups: (i) total sample, (ii) males and (iii) females (given the well-known differences in behavior for males and females in the labor market). As shown in the first three data rows of Table 1, the average rate of return to another year of schooling is 10 percent for the total sample. When considering only males, the rate of return to another year of schooling is 9.6 percent, and for females the rate of returns is much higher, at 11.7 percent. All of these estimates are based on 819 observations from 139 economies between 1970 and 2013. These results are similar to many other reviews of the literature.

|**Table 1. Summary statistics of**<br>|**the returns to s**<br>|**chooling**||
|---|---|---|---|
|**Variable**|**Mean**||**N**|
|Years of schooling total|10.1|(3.3)|819|
|Years of schooling male|9.6|(3.2)|819|
|Years of schoolingfemale|11.7|(3.3)|819|
|Primary schooling total|10.6|(6.4)|547|
|Secondary schooling total|7.2|(3.6)|619|
|Tertiaryschoolingtotal|15.2|(5.8)|762|
|Primary schooling male|10.0|(6.6)|543|
|Secondary schooling male|7.1|(3.8)|614|
|Tertiaryschoolingmale|15.2|(5.8)|745|
|Primary schooling female|10.9|(7.6)|519|
|Secondary schooling female|8.7|(4.6)|607|
|Tertiaryschoolingfemale|16.8|(6.1)|738|

Note: Standard deviations in parentheses The returns are also estimated for levels of schooling, shown in the second, third and fourth block of rows in Table 1. In particular, the second block presents the returns for the total sample, the third for males, and the fourth for females.

Table 1 clearly corroborates a fact already known in the literature: the returns to education for females are higher than for males. This is true not only when considering 7
significant intergenerational occupational and educational persistence for both daughters and sons in 1988. The intergenerational persistence in educational attainment in 1988 is significantly stronger for daughters. The intergenerational persistence in the occupation choices has virtually disappeared by 2002, for both sons and daughters, but there is no evidence that educational mobility has improved. For sons, the evidence from OLS regressions indicates an increase in intergenerational persistence in educational attainment in 2002 compared to 1988.

The results from OLS regressions are somewhat qualified by the sensitivity analysis using a biprobit model following AET (2005). The sensitivity analysis shows that the observed persistence in the education of sons in 1988 can be fully explained away by very low level of positive correlations in ability across generations due to genetic or other unobserved factors (it becomes insignificant when  0.05 ).<sup>15</sup> In contrast, the persistence in educational attainment for daughters in 1988 is much stronger (it remains significant even when  0.15 ). The educational persistence in the case of daughters has remained largely unchanged (marginally declined, at best) according to the AET (2005) sensitivity analysis, while the educational persistence among sons has become much stronger (it is statistically significant at the 1 percent level when  0.20 ).

The AET (2005) sensitivity analysis for occupation shows that, in 1988, the intergenerational links in occupation choices remain significant when we allow for low to moderate (positive) correlation in ability across generations (they remain significant at the 5 percent level when  0.10 ). The most striking result from the sensitivity analysis is that the estimated intergenerational occupational link in 2002 is either negative or very low and statistically not significant for both sons and daughters implying equality of opportunity in occupational choices. The evidence from

> 15  is the correlation between the error terms in parental and a child’s education or occupation equations.

> A value of  0.05 implies that a child with at least one parent in non‐farm is 5 percentage points more likely to participate in non‐farm solely due to unobserved common factors such as genetic endowment and preference.

8
# of the E.U. on the type of goods exported by LDCs tend to be higher.

The second column of Table 1 provides the amount of the subsidy after a 33 % reduction in bound tariffs by all WTO members. The subsidy tends to be larger than the currently forgone tariff revenue because exports from SRCs increase due to the world price rise, which is itself caused by the multilateral tariff reductions. The total subsidy to SRCs granted by the TRIAD amounts to $768 million, and again 88% of it is paid by the E.U.

Table 1. Budgetary impact of moving towards the subsidy scheme in Doha<sup>a</sup> (millions of U.S. dollars)

||Subsidy|Subsidy|Cost of Switch|Preference Erosion|
|---|---|---|---|---|
||(current MFN)|(Post-Doha MFN)<sup>b</sup>|(Post-Doha MFN)<sup>c</sup>|(Post-Doha MFN)<sup>d</sup>|
|E.U.|669|674|208|441|
|Japan|31|32|6|17|
|U.S.|63|64|21|166|
|Total|763|768|235|624|

Source: Authors calculations.

a. A decomposition of subsidies and preference erosion by SRC is provided in Table A1.

b. Assumes a 33% reduction in MFN tariffs by all WTO members. See (8).

- c. Assumes a 33% reduction in MFN tariffs by all WTO members and an additional 8.3% for TRIAD. See (10). d. Assumes a 33% reduction in MFN tariffs by all WTO members. See equation (17).

The third column of Table 1 provides an estimate of the budgetary cost implied by the move towards the subsidy scheme. As is clear from (9) this cost arises because the tariff charged on the imports from the SRC falls but the subsidy rate does not. Moreover, this shortfall applies to a larger volume of imports because the MFN tariff reductions increase world prices. The total budgetary cost for the TRIAD is $235 million, of which most is incurred by the E.U. The budgetary cost for Japan and the U.S. are marginal.<sup>36</sup> Note that the third column in Table 1 excludes the impact of additional MFN tariff reduction that the move towards the subsidy scheme would allow. This would change the amount of the subsidy as well as the tariff revenue collected on imports from SRCs and the rest of the world and will be accounted for in our welfare calculation in Table 2.

> 36 As a comparison, $235 million represents around 2 minutes of TRIAD’s agricultural support or 0.0001 %.

17
|**Topic**|**Country**|**Reference**|**Methodology**<br>**Intervention**|**Area**|**Child Labor Outcomes**|**Age**|
|---|---|---|---|---|---|---|
|School<br>Construction|Burkina Faso|De Hoop and<br>Rosati (2014)|RDD<br>Along with school construction, the<br>program provided incentives to children<br>to attend school and a mechanism for<br>mobilizing community support for<br>education in general, focusing on girls’<br>education.|Rural|Children’s participation in<br>household chores and economic<br>activities (work outside the<br>household, work for pay outside<br>the household, work in the family<br>business or selling goods in the<br>street, farming, and tending<br>animals)over thepast 7 days|5-12|
|School<br>Vouchers|Colombia|Angrist et al.<br>(2002)|RCT<br>The program provided vouchers to low-<br>income high school students renewable<br>annually conditional on satisfactory<br>academicprogress.|Urban|Participation and hours worked, no<br>definition on work given|15 on<br>average|
|UCT|Ecuador|Schady and<br>Araujo (2006)|IV<br>Recipient poor households received $15<br>per month per family without conditions<br>attached. Transfers are made to women.|Urban<br>and<br>Rural|Children engaged in paid and<br>unpaid work in the family farm or<br>enterprise during the previous 7<br>days.|6-17|
|UCT|Ecuador|Edmonds and<br>Schady (2012)|IV<br>Recipient poor households received $15<br>per month per family without conditions<br>attached.|Urban<br>and<br>Rural|Children engaged in paid (outside<br>the child's home) and unpaid (work<br>in the family farm or enterprise,<br>chores) employment during the<br>previous 7 days.|11-16|
|Business and<br>vocational<br>training|El Salvador|Kovrova and<br>Rosati (2016)|RDD<br>Mothers of child laborers were offered: i)<br>vocational training ii) business training<br>and preparation of a business plan; and<br>iii) a starting kit to kick-start the<br>enterprise (value between US$ 100 and<br>US$ 300/).<br>Children not enrolled in school were<br>offered training to help them enter<br>school at the appropriate level for their<br>age.|Urban|Economic activities for pay or<br>unpaid, household chores|5-15|
|Child Labor<br>Measurement|Ethiopia|Dammert et<br>al. (2016)|RCT<br>Survey design was randomized into 2<br>groups i) proxy answers the questions on<br>child labor ii) self reported information<br>on child labor.|Rural|Participation in economic activities<br>over the past week|6 – 14|

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# **Table 1. Oil Subsidy and CO2 production**

|**Dependent**<br>**Variable:**<br>|**(1) All samp**|**le countries**|**CO2 Em**<br>**(2) MENA**|**issions**<br>**subsample**|**(3) MENA oilgr**|**oup subsample**|
|---|---|---|---|---|---|---|
|**populaton**|0.00000120|0.00000415<sup>***</sup>|0.00000278|0.00000179|0.00000986<sup>***</sup>|0.0000103<sup>**</sup>|
||(1.43)|(2.86)|(0.72)|(0.38)|(4.10)|(3.00)|
|**GDP**|1.99e-10<sup>***</sup>|7.27e-11<sup>**</sup>|1.72e-10<sup>*</sup>|2.16e-10|1.94e-10<sup>**</sup>|3.03e-10<sup>*</sup>|
||(14.52)|(2.60)|(1.89)|(1.21)|(3.48)|(2.25)|
|**fossil fuel**<br>**subsidies as a**|-660695926.3|-484726044.4|-121424410.6|25300623.5|376621923.3<sup>**</sup>|426192820.8<sup>*</sup>|
|**share of GDP**|||||||
||(-1.56)|(-1.63)|(-0.48)|(0.12)|(3.23)|(2.28)|
|**lag fossil fuel**<br>**subsidies as a**||-61638905.0||-207020669.6||200854871.4|
|**share of GDP**|||||||
|||(-0.35)||(-1.17)||(1.08)|
|**Constant**|125.4|-51.83|27.30|26.49|-158.4<sup>*</sup>|-260.1|
||(1.57)|(-0.38)|(0.29)|(0.24)|(-2.27)|(-1.90)|
|**_N_**|369|328|99|88|63|56|

_t_ statistics in parentheses.<sup>*</sup> _p_ < 0.1,<sup>**</sup> _p_ < 0.05,<sup>***</sup> _p_ < 0.01. Data is from International Energy Commission for 2011-2018. All regressions control for country & time fixed effect & use robust error. Fossil fuel subsidies increase carbon footprint only for MENA oil exporters. To address possible cointegration issues, besides country level time fixed effect aggregate the trend variables, year and its square, were added and controls. Further, any potential cointegration, for example to omitted variables, would occur between CO2 emissions, population and GDP. As such, this would not affect the coefficients of the variables of interest, fossil fuel subsidies and its lag.

38
above was about 5.1%, by 1993 this rate had decreased to about 2%. Among high school students, prevalence rates also decreased rapidly between 1985 and 1992: from 13.1% to 3.1%. In the second half of the 1990s, the prevalence rate among 12<sup>th</sup> graders in the US has fluctuated between 3% and 6% (UNODC, 2005a, using information from SAMHSA). The percentage of the population reporting current (during the month before the interview) and occasional (one to eleven times during the twelve months before the interview) use of cocaine also shows the same pattern (see Figure 9). Other indicators, such as the trend in cocaine treatment admissions, show a decreasing tendency of cocaine use between 1992 and 2002 (the last year recorded). While the primary admission rate<sup>25</sup> for cocaine per 100,000 inhabitants (age 12 or older) was about 125 in 1992, by 2002 it had decreased by approximately 24% to about 100 (SAMHSA, 2005).<sup>26</sup> Among high school students, the evidence on cocaine consumption trends is somehow mixed. While measures of 30day prevalence rates for cocaine use among 12<sup>th</sup> graders began to increase and then peaked in 1999 and then decreased until 2003 (see Figure 10), the perception of harmfulness of cocaine consumption<sup>27</sup> —as perceived by 12<sup>th</sup> graders—seems to have declined in the last few years recorded (University of Michigan (2004)).

In Europe, however, cocaine consumption, according to most estimates, has been on the rise over the last few years.<sup>28</sup> For instance, in Spain, the country that shows the highest rates of cocaine consumption in Europe, the prevalence of cocaine use among the general population (age 15 to 64) increased from 1.5% in 1995 to 2.7% in 2003; in the Netherlands it

> 25 The primary substance is the main substance reported at the time of admission.

> 26 Cocaine admissions as percent of all admissions also declined from about 17.5% in 1992 to about 13% in 2002.

> 27 When they respond to the question: _How much do you think people risk harming themselves (physically or in other ways), if they try cocaine powder once or twice, and occasionally._

> 28 European countries, probably with the exception of Spain, show prevalence rates of consumption much lower than those in the US.

18