rafmacalaba/datause-encoder-data huggingface dataset:
by higher human capital endowments, and it is mostly due to higher premiums that men receive on their endowments compared with women—that is, a woman must be overprepared to gain the same wage for a given job as a man. From the lowest wage quantiles to the highest quantiles, this premium grows by almost four times, showing the magnitude of the glass ceiling faced by Tunisian women. In fact, wage discrimination against Tunisian women is no different from that in the rest of the world. Much like the conclusions reached by Arulampalam, Booth, and Bryan (2007), Pendakur and Woodcock (2010), and Zucco (2019), among others, Tunisia exhibits a high glass ceiling for women because they are required to be vastly more qualified than their male counterparts, especially for high-earning positions.

Second, this experiment creates an artificial supply of applicants, whereas in reality the rate at which females apply for jobs may differ from that of male job seekers. For example, in the engineering field it is plausible that female engineers submit fewer applications for actual engineering jobs and more for less demanding jobs in which the supply of female job seekers exceeds the demand for labor because of the inability of women to compete with men in view of their long working hours or other childcare and household responsibilities.<sup>17</sup> Third, the higher concentration of female graduates than male graduates in some majors, such as marketing and finance, could mean there is an oversupply of female graduates for the number of jobs available in those fields, translating into higher unemployment rates among female graduates, even when there is positive discrimination is favor of women.

Fourth, the positive discrimination in favor of women could be related to how the profile of advertised jobs in some fields may fit certain gender stereotype beliefs held by employers. For example, many of the jobs advertised on the online portal for the finance field were for assistants, and a higher share of marketing jobs required knowledge of Microsoft Office and less advanced computer skills, as well as languages. This finding is in line with evidence found elsewhere. According to the World Economic Forum (2016), the IT industry has a significant gender gap in female hirees, whereas women are more highly represented in sectors related to services.

> 17 Unfortunately, no data are available to further verify this hypothesis. Implementing panel surveys in the future to carefully track the choices of graduates over time would be a good first step.

43
is the rate of depreciation of the nominal exchange with the real exchange rate defined as _Et_ = _StPY,t_<sup>_∗/PY,t_,</sup> is the external risk premium, is the equity risk premium, are the respective sectors’ expected discounted streams of future dividends, is the stochastic discount factor, and _T_<sup> ̃</sup> _CH,t_ , _T_<sup> ̃</sup> _A,t_ , _T_<sup> ̃</sup> _H,t_ , and _T_<sup> ̃</sup> _R,t_ are tax revenues as specified below.

Eq. (1) states that the utility from relaxing the budget constraint by one unit is equal to the marginal utility of the consumption which this unit provides. Eq. (2) is a variant of the Euler equation and determines how the households smooth consumption optimally. It relates the marginal consumption utility of a unit of income in _t_ to the utility this unit would yield if saved and consumed in _t_ + 1. Eq. (3) is the risk-adjusted uncovered interest parity condition and it pins down the change of the exchange rate which adjusts to eliminate any arbitrage opportunity making the household indifferent between holding international debt or any other asset. Eq. (4) states that equity returns exceed the risk free bond rate by an equity risk premium, Γ _Sε_ Γ _S,tRS,t_ (abstracting from capital taxes). Note that _RSZ,t_ = _RSR,t_ = _RSF,t ≡ RS,t_ and note that the equity return rate is defined as Eq. (5) states that the rate of high-skilled wage inflation should be such that the marginal disutility from increasing labor supply by one unit should be equal to the marginal utility which the additional consumption provided from that unit of labor generates. The markup, _εWH,tμH_ , arising from monopoly power drives a wedge between the marginal rate of substitution between differentiated labor varieties and the high-skilled real wage. Eq. (6) is simply the budget constraint. Note that we normalize the total number of equity shares to one. Define _pS,t_ = _PS,t/PY,t_ as the price of an equity share expressed in the price of the final good.

38
- 1.41 -

# Table LC.S: Arc Elasticiltes of Cocoa Supply

|Scenario&<br>Horizon|120-140|Cocoa BuyIng<br>140-160|Price Intervals<br>160-180|180-200|
|---|---|---|---|---|
|hbed Paourm<br>|||||
|20 years|1.573|0.584|0.472|0.448|
|<br>30 years<br>50 yeaus<br>Averag|1.213<br>1.149<br>1.312|0.441<br>0.537<br>0.521|0 461<br>0.501<br>0.478|0 468<br>0.481<br>0.456|
|Paon|||||
|20 years<br>|0.973<br>|0.439<br>|0.264<br>|0.274<br>|
|<br>30 yer|0.775|0.414|0.285|0.328|
|<br>50 years|0.916|0.355|0.286|0.315|
|<br>Aveage|0.888|0.403|0.279|0.306|
|PcpusaionandIoomGrowlh|||||
|<br>Cuas A:<br>Conudant Wage|||||
|<br>2sr yeus|_1.746_|0.714|0.392|0.373|
|<br>30years|<br>1.986|<br>0.913|<br>0.579|0.324|
|<br>50 years<br>|2.634<br>|1.616|0.786|0.476|
|<br>Average|2.122|1.061|0.586|0.391|
|Case B:<br>ocreasing<br>Wage<br>|||||
|<br><br>20 yura|2.043<br>|0.815|0.429|0.436|
|<br>30yeoas|2.567|1.042|0.690|0.366|
|<br>50 years|3.493|2.038|1.056|0.658|
|<br>Averwa|2.701|1.298|0.725|0.487|
|qiA In Populon&**hoame**<br> <br> <br>|||||
|<br>Vf<br>Zo<br>**Food**h|||||
|20**years**|0.043|2.019|**1.606**|0.562|
|<br>30**yas**|0.042|3.059|<br>1.931|0.710|
|<br>**50 years**|0.041|4.286|3.106|1.087|
|<br>**Aveagoe**|0.042|3.121|2.215|0.786|

transition to hybrid varieties that other producing countrles have essentially completed. Thus, supply roughly reproduces the shape of the age yield curve for hybrid cocoa trees In this scenario with fixed supplies of laind and labor.

The long gestatlon period of cocoa Investments converts the supply response to price Into a stock adjustment problem skiilar to the stock adjustment of any long-lived capital asset when relative profitability changes. Flgure l.C.2 presents the sequence of stock levels of cocoa acreage defining the adjustment path for each price experklent. Note that acreage stocks converge fairly rapidly (I.e., one to two periods) to the nelghborhood of the desired level, but further adjustments are necessary due to the unbalanced nature of the age composition of Initial stocks. Not surprisingly, acreage stocks show much less variation than cocoa production, which is constrained by the age compositlon of stocks.
early and prime working ages. Second we define skilled individuals as those who have at least a complete post secondary education. Third, we normalize our measure of wages to monthly payments. Fourth, we drop the top and the bottom 1 percent of wages reported within a particular district to omit outliers.<sup>7</sup> Fifth, we identify 10 industries which are merged with the data on greenfield FDI, namely: Agriculture, Extraction, Manufacturing, Construction, Utilities, Commerce, Transport and Communications, Financial and Business Services, Public, and Other Services. The number of sectors was constrained by the maximum disaggregation avaiable in the I2D2 database.

The evolution of the skill premium can be seen in Figure 2. Here the skill premium is defined as the ratio of skilled to unskilled wages, adjusted for years of experience. A striking observation is that for both men and women the skill premium has been declining in most countries in our sample. The general downward trend in the wage premium was also documented by Cruz and Milet (2017).<sup>8</sup> Vietnam is an exception but the last year observed is 2008. In the Philippines it has not changed much over the years. In Ethiopia it has declined for men but increased slightly for women from 2004 to 2012. Hence according to this metric at least these emerging economies have not seen major increases in inequality as measured by the skill premium in the last decade<sup>9</sup> . Another interesting fact is that the skill premium is much higher for women than men. In Ethiopia for example, while skilled women make 3 times more than unskilled women in 2014, down from 5 times in 2004, skilled men make only 2 times more than unskilled men, down from 2.6 times more in 2004. Note that despite the drop in the skill premium, in all countries wages are higher for men relative to women and for skilled relative to unskilled workers. Unskilled women are always at the bottom of the wage distribution, while skilled men are at the top.

The general downward trend in the skill premium is often mirrored by an upward

> 7Our results are robust to keeping these observations.

> 8The rises in wage skill premia and job polarization are common trends associated with skillbiased technologies that have been observed in advanced economies. Maloney and Molina (2016) find no evidence of job polarization for developing countries.

> 9Maps for all 7 countries documenting the skill premium’s evolution by region are available on request.

7
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25
# **5** Figure Real Cocoa Prices

## At constant $1980

<!-- Start of picture text --> 1980$/MT (Thousands)<br>6<br>5<br>4<br>3<br>21<br>1<br><!-- End of picture text --> 1950/51 1955/56 1960/61 1965/66 1970/71 1975/76 1980/81l 1985/86 year World price Ivory prod pr Ghana prod pr 5 yr MA wld price Deflated by CPI or MUV
B), while under scenarios A and C households would lose 1.6 and 2.0 percent of their consumable income, respectively. In all the three scenarios, those who formalize experience a decline in incomes and higher poverty rates. We can also see that the target group (the informal employees) would still face high opportunity costs of formalization, although those will be partly offset by the tax maneuver. In case of the tax maneuver followed by 50 percent formalization, under scenario B average incomes of the formalized are lower by 14.2 percent compared to the baseline scenario and their poverty rate is higher by 9.8 p.p. than in the baseline, which are lower losses than in the case of enforced formalization (see lines 2 and 3 of panel 2B of Table 6).

**Table 6: Simulated changes in indicators of income distribution and fiscal budget, reform 2 scenarios**

|||Formaliza|tion rate:||
|---|---|---|---|---|
||0%|10%|20%|50%|
|||Scenar|io 2A||
|Income of 1st decile, %|-1.5|-1.5|-1.5|-1.5|
|Income of the formalized, %|0.0|-1.8|-1.9|-1.8|
|Income total, %|-1.6|-1.6|-1.6|-1.6|
|Absolute poverty rate of the formalized, p.p.|0.0|1.9|1.9|1.8|
|Absolute poverty rate, p.p.|0.8|0.8|0.8|0.8|
|Gini index, p.p.|0.0|0.0|0.0|0.0|
|Total budget balance, %ofGDP|-0.9|-0.7|-0.5|0.0|
|||Scenar|io 2B||
|Income of 1st decile, %|0.8|0.6|0.3|-0.4|
|Income of the formalized, %|0.0|-13.4|-13.3|-14.2|
|Income total, %|0.9|0.7|0.5|-0.2|
|Absolute poverty rate of the formalized, p.p.|0.0|11.6|9.1|9.8|
|Absolute poverty rate, p.p.|-0.2|0.0|0.2|0.6|
|Gini index, p.p.|0.0|0.0|0.1|0.3|
|<br>Total budget balance, %ofGDP|-0.6|-0.5|-0.3|0.2|
|||Scenar|io 2C||
|Income of 1st decile, %|-1.5|-1.5|-1.6|-1.9|
|Income of the formalized, %|0.0|-6.8|-6.7|-7.0|
|Income total, %|-1.6|-1.7|-1.8|-2.0|
|Absolute poverty rate of the formalized, p.p.|0.0|5.1|4.1|3.7|
|<br>Absolute poverty rate, p.p.|0.8|0.9|0.9|1.0|
|<br>Gini index, p.p.|0.0|0.0|0.0|0.1|
|Total budget balance, %of GDP|-0.9|-0.7|-0.5|0.0|

Source: Authors’ calculations using RUSMOD for 2017 policy year and 2016 RLMS-HSE data.

Figure 9 shows the results of reform 2 with the assumption that nobody formalizes by income deciles and socio-demographic groups. In this case the distributional impact of the tax maneuver completely depends on our assumptions about the economic incidence of SIC. If it falls on workers (scenario B), the benefit from SIC reduction is higher than the additional burden of higher VAT, and is beneficial for all the income deciles. The relative effect is of similar size across the distribution. Not surprisingly, households with fewer children and adult only households benefit the most. The situation reverts if the economic incidence of SIC reduction does not favor employees (scenarios A and C). In this case, households are assumed to carry the burden of higher VAT and no additional benefit due to lower SIC, which results in a negative effect for all the population subgroups.

24
The analysis of the figure below shows three clear characteristics of the Moroccan labor market. The first characteristic is that the level of inactivity has increased relatively to employment and unemployment and for all groups between 1999 and 2011. This is visible by looking at the dots that move over time towards West and South-West of the figure. The second is that the labor market is clearly segmented along gender and location lines. Urban and rural men and women occupy a very distinct position on the graph with rural men being on the North-West extreme and urban women being on the South-West extreme. And the third characteristic is that the four groups maintain this distinct position throughout the decade considered with small movements and no overlaps with other groups.

More in detail, for men, the dominant position is employment. More than 60% of men aged 15 and above are employed in both urban and rural areas. In urban areas, the share of employment is stable and fluctuates around 60%, the unemployment share decreases while that of inactivity increases. This illustrates that the decline in the unemployment rate and in the LFPR is due to an exit of job seekers to inactivity. In rural areas, the share of employment is higher (around 80%) and decreased slightly over the period, the unemployment share is stable while that of inactivity increased. This suggests that in this area, the decline in the LFPR and the employment rate for men is due to job losses.

For women, the situation is entirely different with inactivity being the most relevant status. At least 60% of working age women are inactive regardless of the place of residence (80% urban and 60% rural). Moreover, this situation is exacerbated by the changing structure over the whole period. Indeed, whatever the place of residence, the share of inactivity is increasing, mostly to the detriment of employment, the share of unemployment being stable. This shows that there are strong barriers to the participation of women in economic activity, especially in urban areas, and that women have not been able to join the labor force in greater shares.

**Figure 3 – Structure of the working age population (1999-2011)**

<!-- Start of picture text --> 100 0 1999 2005 2011<br>80 20<br>Rural Men<br>All Men<br>60 40<br>Urban Men<br>Employment Unemployment<br>40 60<br>Rural Women<br>All Women<br>20 80<br>Urban Women<br>0 100<br>100 80 60 40 20 0<br>Inactivity<br><!-- End of picture text --> Source: Authors’ estimations from LFSs 1999-2011.

6
> example).  _t_ , _s_ is the school level error term that includes all the unobserved school characteristics  that we assumed are uncorrelated with the explanatory variables for the time being.<sup>12</sup>

The vector of school characteristics includes total enrollment, total dropout, student-teacher ratio, textbooks per student, teacher manual per teacher, school type, school head type, whether the school was an elementary leader school (a school considered to be a leader among others in the district) and whether the school had received SIIF funds.<sup>13</sup> School type consists of four categories: complete combination and multi-grade schools; complete large and medium school; complete small schools; and primary schools. School head type consisted of three categories: head principal, head teacher, and teacher in charge. Table 1 summarizes the descriptive statistics for all schools and by treatment status of the school.

 0 is the intercept showing the average test scores of the SBM and non-SBM schools;  1 shows the change between 2002-03 and 2004-05;  2 is the difference in the treatment and control group; and  3 is the DID estimator capturing the differences between the control and treatment groups, before and after the intervention. More specifically, it measures the SBM effect as the change in average school-level test scores among two groups before and after the 2003 SBM intervention. These groups included: the “first batch,” or the schools that received SBM first (treatment group) to schools that received the intervention later and those that did not receive the intervention at all (comparison group).

In order to obtain the DID estimates, we created a panel dataset from our original dataset of 5,167 schools. Since we had test scores for all three years, we simply replicated this data for every year to obtain a panel dataset with 15,501 observations. In this dataset, each school is observed in each of the three years (2002-03 to 2004-05).

In order to use the DID estimates in this context, we need to be certain that the difference in postintervention outcomes between SBM and non-SBM schools would have been identical in the absence of the intervention. However, this assumption is impossible to test because we do not actually observe the counterfactual. We can nonetheless test whether pre-intervention and “mid-term” educational outcomes

> 12 The intervention might alter the number of children enrolling in a particular school. If as a consequence the distribution of students’ skills changes in treatment schools (with respect to control schools), then the program impact estimates are likely to be biased. We will explore the existence of this bias in section five when discuss the caveats. The characteristics of the average student in the school are also included in the error term because of lack of data on individual students’ characteristics. 13 School Improvement and Innovation Facility that granted funds to schools based on proposals for school improvement programs.

7
# **Table A15:  Global Integrity Index  (GII)**

**Data Provider Description Website Data Source Type Respondents Frequency Coverage Public Access Description**

## Global Integrity

Nongovernmental organization located in Washington, United States, advocating integrity and accountability in government.

www.globalintegrity.org Global Integrity Index Expert Assessment Local country experts and peer reviewers recruited by Global Integrity Every three years between 2003 and 2006, yearly since Mostly developing country sample Yes The Global Integrity Index uses some 300 indicators to assess the existence and effectiveness of anti-corruption mechanisms that promote public integrity. They typically pair an indication of the "in law'" existence of a particular institutions with an "in practice" assessment of its functioning. We use a simple average of the "in practice" components of each of the indicated GII indicators, in keeping with our practice of relying purely on perceptions-based data in the WGI. Note that in 2007 we have carried forward scores for those countries that were covered in 2006 but not in current year.

|**Voice and Accountability**|2007|2006|2005|2004|2003|2002|2000|1998|1996|
|---|---|---|---|---|---|---|---|---|---|
|Civil Society Organizations|X|X|X|X|X|..|..|..|..|
|Media|X|X|X|X|X|..|..|..|..|
|Public Access to Information|X|X|X|X|X|..|..|..|..|
|Voting & Citizen Participation|X|X|X|X|X|..|..|..|..|
|Election Integrity|X|X|X|X|X|..|..|..|..|
|Political Financing|X|X|X|X|X|..|..|..|..|
|**Political Stability and Absence of Violence**||||||||||
|NA|..|..|..|..|..|..|..|..|..|
|**Government Effectiveness**||||||||||
|NA|..|..|..|..|..|..|..|..|..|
|**Regulatory Quality**||||||||||
|NA|..|..|..|..|..|..|..|..|..|
|**Rule of Law**||||||||||
|Executive Accountability|X|X|X|X|X|..|..|..|..|
|Judicial Accountability|X|X|X|X|X|..|..|..|..|
|Rule of Law|X|X|X|X|X|..|..|..|..|
|Law Enforcement|X|X|X|X|X|..|..|..|..|
|**Control of Corruption**||||||||||
|Anti-Corruption Law|X|X|X|X|X|..|..|..|..|
|Anti-Corruption Agency|X|X|X|X|X|..|..|..|..|
|**Country coverage**|**66**|**41**|**25**|**25**|**25**|**..**|**..**|**..**|**..**|
|**Year of Publication**|**2007**|**2006**|**2004**|**2004**|**2004**|**..**|**..**|**..**|**..**|

53
**THE ECONOMICS OF THE INFORMAL SECTOR A Simple Model and Some Empirical Evidence from Latin America**

Norman V. Loayza' The World Bank, Washington, D.C. 20433 'Excellent research assistance by Daniel Wolfenzon and Wanhong Hu is gratefully acknowledged. I am grateful for feedback provided by participants at the Carnegie-Rochester Conference on Public Policy in Pittsburgh, in November 1995. 1 specially acknowledge the comments from Patrick Asea, my discussant at the Carnegie-Rochester Conference, and Allan Meltzer, the Conference's organizer. I also benefited greatly from the comments of PierreRichard Agenor, Alberto Alesina, Cevdet Denizer, David Dollar, Edward Glaeser, Aart Kray, Philip Lane, Luis Serven, Klaus Schmidt-Hebbel, and participants at the World Bank Macroeconomics and Growth Seminar.
<!-- Start of picture text --> Education . vevevevteeeevsresesese deceeetereeecerereeesteretstered@eereeersn@beess<br>Entertainment fees, admissions, reading |r<br>Furniture and fixtures |-- 0 Hes ° vos<br>Entertainment equipment and subscription TV Jor Op<br>Appliances, phones, computers with associated services | Orr<br>0 Re) 1 1.5 2<br>© Income elasticity: low<br>Income elasticity: high<br><!-- End of picture text -->
# TABLE I

TARIFF SCHEDULE VALID SINCE NOVEMBER 1ST, 2008

||Accumulated<br><sup>3</sup>|consumption<br>||
|---|---|---|---|
|Category|(m/|year)|Unit price per m<sup>3</sup>|
||From|To||
|R1|0|500||
|R21|501|650||
|R22|651|800|0.144|
|R23|801|1000|0.156|
|R31|1001|1250|0.247|
|R32|1251|1500|0.332|
|R33|1501|1800|0.437|
|R34|1801|+∞|0.517|

_Notes_ : The econometric analysis focuses on the discontinuity between the categories R32 and R33.

26