rafmacalaba/datause-encoder-data huggingface dataset:
3 From these measures of the years of schooling, I create a measure of educational capital. By analogy with the specification used in Mincer, I assume that the natural log of the wage in any period is a linear function of the years of schooling: ln(wv) =ln(wo) + _r*N_ where WN is the wage with N years of schooling, N is the number of years of schooling and r is the wage increment to a year's schooling<sup>2</sup> . The value of the stock of educational capital at any given time t can then be defined as the discounted value of the wage premia due to education: _HK(t) = ,_ '*(wM-wO) where wo is the wage of labor with no education<sup>3</sup> . This is just the value now of a given stock of schooling. After substituting in the formula for the educational wage premia into this definition and taking natural logs, the rate of growth of educational capital is approximately<sup>4</sup> : _AJk(Q)_ = Aln(exp'MA-1) z This is nat the "rate of returmw to schooling, which only happens to equal the wage increment under very special conditions. For growth accounting of the current stock the wage increment, not the rate of return is relevant.

3 Mulligan and Sala-i-Martin (1995) pursue this approach directly by calculating the human capital for the U.S. state by state by comparing the aggregate labor income versus the income of workers with no schooling.

4 There are two reasons this is only approximate. The discount factor is assumed constant and hence is factored out of the tirm rate of change. However, it does depend on the average age of the labor force (since the discount is only until time T (retirement)) which certainly varies systematcay across countries, but I am assuming that changes in this quantity over timc are snuH. The other, pomially more serious problem is that I dropped out the growth rate of the In (wo) term because I didn't know what to do with it. This seemns wrong.
Table 4: Dependent variable: Backward GVC <u>participation</u> shares <u>(EORA)</u>

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
|Regressions|IV - BE|IV|LS|LS|
|Avg. tari¤ rate (%)|-0.011***|-0.009***|-0.005***|-0.004**|
||(0.004)|(0.003)|(0.001)|(0.002)|
|FDI in‡ows (log)|0.038*<br>|0.030*<br>|0.018*<br>|0.014<br>|
||(0.020)|(0.018)|(0.010)|(0.010)|
|Distance to GVC hubs (log)|-0.090**|-0.112***|-0.118***|-0.080*|
||(0.038)|(0.041)|(0.044)|(0.046)|
|Political stability index|0.017|0.031**|0.040***|0.034**|
||(0.019)|(0.014)|(0.014)|(0.015)|
|Domestic industrial capacity|-0.040***|-0.031**|-0.022**|-0.023|
|(log)|(0.015)|(0.012)|(0.008)|(0.027)|
|Rents from resources / GDP|-0.003**|-0.003***|-0.003***|-0.003**|
|(%)|(0.001)|(0.001)|(0.001)|(0.001)|
|Capital / GDP (log)|0.045*|0.033|0.034|0.030|
||(0.026)|(0.024)|(0.023)|(0.023)|
|Land / GDP (log)|-0.021***|-0.019***|-0.019**|-0.021***|
||(0.006)|(0.007)|(0.007)|(0.007)|
|Med/High-skilled labor / GDP (log)|0.018|0.009|0.005|-0.010|
||(0.016)|(0.014)|(0.014)|(0.030)|
|Low-skilled labor / GDP (log)|0.011|0.017|0.015|0.015|
||(0.016)|(0.018)|(0.019)|(0.019)|
|Exch. rate appreciation|-0.000|-0.000|0.000|-0.000*|
||(0.000)|(0.000)|(0.000)|(0.000)|
|Import elasticity||||0.084|
|||||(0.250)|
|Import elasticity X Population (log)||||-0.009|
|||||(0.014)|
|Population (log)||||0.024<br>(0.037)|
|Statutory Corporate Tax Rate||||0.000|
|||||(0.001)|
|Transitional Economy Status||||0.039<br>(0.034)|

|Observations|290|121|121|121|
|---|---|---|---|---|
|R-squared|0.483|0.472|0.503|0.530|
|Number of countries|121|121|121|121|
|F stat for excluded IV||||1.41|
|AR Wald test for weak IV robust inference||3.43***|||
|KP rk LM statistic for underidenti...cation||22.07***|||
|Decade ...xed e¤ects|YES|NO|NO|NO|

Notes: LS standard errors in parentheses for Column (1); Robust standard errors for Columns (2)-(4); ***, **, and * indicate signi...cance levels of 1%, 5%, and 10%, respectively.

36
<!-- Start of picture text --> Figure 22: Belize’s Seat Capacities and Direct Airport Pairs with the Rest of the World<br> 900 14<br> 800<br>12<br> 700<br>10<br> 600<br> 500 8<br> 400 6<br> 300<br>4<br> 200<br>2<br> 100<br> - 0<br>2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013<br>Year<br>Estimated Seats Airport Pairs<br>Estimated Seats, thousands<br>Extra-Regional Airports Served<br><!-- End of picture text --> _Source: Authors’ calculation based on data by Diio (2014)._ Guyana’s connectivity with the outside world in general is very light, with less than 100,000 seats, and only with the U.S. and Canada (Table 19). The bulk of the connectivity is provided by Caribbean Airlines, both into the U.S. and, as of 2013, to Canada.

|**Table 19: Traff**<br>**Country**|**ic between Guy**<br>**Est. Seats**<br>**2013**|**ana and th**<br>**Share**|**e Rest of th**<br>**Annual**<br>**Growth**<br>**01-13**|**e World**<br>**Annual**<br>**Growth**<br>**08-13**|
|---|---|---|---|---|
|US|72,436|76.6%|-1.9%|3.7%|
|Canada|22,126|23.4%||4.5%|
|**Total**|**94,562**||**0.3%**|**3.9%**|

_Source: Authors’ calculation based on data by Diio (2014)._ Except for Delta Airlines, which introduced service to the Guyana in 2008, no other traditional airline from the U.S. is servicing Guyana. The competition between Delta and Caribbean airlines seems to be very strong: Delta grew its capacity from 39, 000 seats in 2008 to 88,000 in 2012, while Caribbean Airlines also grew their capacity from 28,000 to 64,000 seats in the same period. However, in 2013 while Caribbean has been building capacity to nearly 100,000 seats on the U.S. route, Delta has reduced its capacity to below 20,000. This interplay has created a dip in overall capacity, just as Caribbean Air added connectivity to Canada in 2013 (Figure 23).

52
Table 6: Effect of Family Planning Access on Unwanted Fertility for Women Without Schooling

||Last/Current Pre|gnancy Unwa|nted|
|---|---|---|---|
||OLS|IV Model<br>Plac|of Predicted<br>ement<sup>a</sup>|
||Model I<br>Model II|Model III|Model IV|
|Family planning|_−_0_._071|_−_0_._051||
||(0_._046)|(0_._071)||
|Family planning_×_age 15-19|_−_0_._073||_−_0_._104|
||(0_._104)||(0_._130)|
|Family planning_×_age 20-24|_−_0_._039<br>(0_._071)||_−_0_._001<br>(0_._130)|
|Family planning_×_age 25-29|_−_0_._079<br>(0_._071)||_−_0_._034<br>(0_._132)|
|Family planning_×_age 30-34|0_._034||0_._083|
||(0_._083)||(0_._120)|
|Family planning_×_age 35-39|_−_0_._142<sup>_∗∗_</sup>||_−_0_._124|
||(0_._061)||(0_._094)|
|Family planning_×_age 40-45|_−_0_._113||_−_0_._140|
||(0_._073)||(0_._107)|

**Notes.** * sign. at 10%; ** sign. at 5%; *** sign. at 1%. Linear probability model with robust standard errors clustered at community level in parentheses. Family planning indicates whether there was family planning available within 40 km in 1990. Additional variables not shown are region dummies, ethnic group dummies, five year age group dummies, dummies for religion, area of wereda, rainfall and rainfall squared of wereda, dummy for urban area, dummy for market in area, and dummies for road access all year and road access only during dry season. Number of observations for all models is 1340. Complete results including other explanatory variables are available on request. a Weighted IV estimation using Stata’s svy command with family planning access treated as endogenous.

to family planning services for at least two years at the time of the survey, whereas our family planning access measure reflects long-run access. In other words, the results capture the difference between having long-term exposure to family planning compared to relatively short-term or no exposure. To capture control over fertility, women without children are coded as not having had an unwanted birth or pregnancy; women who have not had any children have presumably been able to avoid a pregnancy at least in part because of access to family planning. The average effects indicate that longer exposure to family planning reduces the risk of an unwanted birth or pregnancy but the effects are not statistically significant. The results by age group show that mainly older women benefit from family planning in terms of avoiding unwanted fertility. For both women aged 35 to 39 and 40 to 45 there is a substantial reduction in the probability of last birth or current pregnancy being unwanted with the effects statistically significant for women 35 to 39 for the OLS results. That there is a reduction in unwanted fertility among the older women indicates that the reductions in fertility is likely due to family planning access and not health facilities.

Finally, Table 7 presents the estimated impact of long-term access to family planning on whether a 20
WPS 3799

# **Pending Issues in Protection, Productivity Growth, and Poverty Reduction**<sup>∗</sup>

Omar Arias, Andreas Blom, Mariano Bosch, Wendy Cunningham, Ariel Fiszbein, Gladys Lopez Acevedo, William Maloney, Jaime Saavedra, Carolina SanchezParamo, Mauricio Santamaria, and Lucas Siga

**Abstract:** This paper selectively synthesizes much of the research on Latin American and Caribbean labor markets in recent years.  Several themes emerge that are particularly relevant to on going policy dialogues. First, labor legislation matters, but markets may be less segmented than previously thought. The impetus to voluntary informality, which appears to be a substantial fraction of the sector, implies that the design of social safety nets and labor legislation needs to take a more integrated view of the labor market taking into account the cost-benefit analysis workers and firms make about whether to interact with formal institutions. Second, the impact of labor market institutions on productivity growth has probably been underemphasized. Draconian firing restrictions increase litigation and uncertainty surrounding worker separations, reduce turnover and job creation, and poorly protect workers.  But theory and anecdotal evidence also suggest that they, and other related state or union induced rigidities, may have an even greater disincentive effect on technological adoption, which accounts for half of economic growth.  Finally institutions can affect poverty and equity, although the effects seem generally small and channels are not always clear. Overall, the present constellation of labor regulations serves workers and firms poorly and both could benefit from substantial reform.

## World Bank Policy Research Working Paper 3799, December 2005

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

> ∗ Executive Summary of Labor Stocktaking in the Latin American and Caribbean Region as part of the Global Labor Stocktaking exercise.
hours is 18 percent higher than boys working the same number of hours, but it is only 3.6 percent higher than boys' attainment when they work 10 to 20 hours per day. However, because the evidence is contemporaneous rather than retrospective, the effects of work on educational attainment over the lifeti;me are unclear. Econometric analysis would be necessary to measure the precise magnitude of these effects.

**Table 9: Level of Educational Attainment for Age** by **Hours Worked for Girls and** Boys

|Hours<br>WorkedPer<br>Day.|.|:1|:||:Ur<br>**:Rural-**|ban||Total||
|---|---|---|---|---|---|---|---|---|---|
||_-Boys_|_:Gils_|_Tot_|Boys|Girls|Total|Boys|Girls|Total|
|h=O|3.37|3.79|3.59|2.14|2.51|2.35|3.18|3.54|3.37|
|O<h<=5|3.30|4.17|3.58|2.03|2.46|2.17|2.55|3.13|2.74|
|5<h<=10|3.51|4.17|3.73|2.15|2.59|2.27|2.77|3.42|2.97|
|10<h<=20|3.27|3.39|3.32|2.43|3.29|2.70|2.88|3.36|3.05|
|Total|3.37|3.81|3.59|2.12|2.51|2.31|3.08|3.51|3.29|

Source: Calculations based on PNAD 1996 37. Educational attainment may also depend on the age at which girls and boys begin to work. While conclusions cannot be made about the causal effects of age of entry into the labor market on educational attainment, individuals will likely not catch up in terms of educational attainment once they have entered the labor market or reached adulthood. Overall, as expected, the later children begin to work, the higher the attainment levels, although it does not increase monotonically. Table 10 shows educational attainment for children ages 4 to 15+ in both rural and urban areas. It is interesting to note that while on average girls have higher educational attainment, girls who begin working between the ages of 11 and 14 have lower levels of educational attainment than boys. The trend is present in both urban and rural areas but to a lesser degree in the latter case. The reasons for these gender differences could be an area of future research.

15
||Table 6. I|mpacts onConsum|ption andFood|Security||||
|---|---|---|---|---|---|---|---|
||Total value of|Annualize|d percapita (in F|CFA) ...|Foo|dSecurity Ind|ices|
||warrantagecrops|Total|Food|Non-food|||Resilience|
|Panel A: Householdrandomization<br>|(inFCFA)<br>(1)<br>|expenditures<br>(1)<br>|expenditures <br>(2)<br>|—expenditures<br>(3)<br>|Fcs!<br>(4)<br>|FSS?<br>(5)<br>|Index?<br>(6)<br>|
|Accesstowartantage,|147,188.416**<br>|15,262.363"*<br>||1,325.114<br>|12,713.282***<br>|1.941<br>|-0.061<br>|0.408<br>|
||(58,766.627)|<br>(6.795.019)|<br>(4,178.551)|(4.470.186)|(3.445)|(0.112)|(0.588)|
|Observations|518|518|518|518|518|513|517|
|Control mean|439298|123082|72848|49699|62.57|-1.969|2.775|
|PanelB: Village randomization (Sampl|e: Non-lotteryparticip|ants andControl|lotteryparticipan|ts)||||
|Hightreatment village|40,400.680|-2,065.567|4,475.503|-5,470.520|-4.740|-0.054|0.351|
||(47,646.148)|(7,087.364)|(4,494.362)|—-(4,290.873)|(3.586)|(0.117)|(0.961)|
|Observations|434|434|434|434|434|434|434|
|Lowtreatmentvillagemean|433344|125063|71692|52806|63.80|-1.943|2.655|

Notes: In Panel A, the sample is restricted to lottery participants. In Panel B, the sample is restricted to all control households and non-lottery participants. Standard errors are clustered by village and presented in parentheses. *, **, *** indicate significance at the 1, 5, and 10 percent respectively.

' The food consumption score (FCS) developed by the World Food Programme which measures both dietary diversity and food frequency which weights the frequency and nutritional value of different food groups consumed in the last 7 days. > The food security score (FSS) also constructed according to WFP guidelines that takes values from -1 to -4 depending on the severity of food shortages.

3 The inverse of the WFP coping strategies index (CSI) referred to as the resilience index which weights the frequency and severity of actions taken by households to cope with food shortages.
- 55 -

Figure 3

# APPRENTICESHIPS WITH NO GEN EDUC

<!-- Start of picture text --> 110-<br>100-<br>Go<br>170 .Xan~~~~l<br>JSO<br>.. 10 X 0<br><!-- End of picture text -->

# APPRENTICESHIPS WITH PRIM EDUC

<!-- Start of picture text --> 130 -<br>I l<br>JSO<br>0 10 20<br>09m' JL -<br><!-- End of picture text --> o - 2 years of apprenticeship training I - 4 years of apprenticeship training - 6 years of apprenticeship training
|Variable|(1)<br>Treated|(2)<br>Control|(3)<br>Difference|(4)<br>t<br>statistic|(5)<br>p-value|
|---|---|---|---|---|---|
|Tech Sophistication|1.90|1.89|0.01|0.29|0.77|
|Medium|0.27|0.25|0.02|0.55|0.58|
|Large|0.26|0.24|0.02|0.64|0.52|
|Age 6 to 10|0.25|0.28|-0.03|-0.94|0.35|
|Age 11 to 15|0.19|0.22|-0.03|-0.94|0.35|
|Age 16+|0.36|0.26|0.09***|2.93|0.00|
|Export|0.26|0.20|0.06**|2.07|0.04|
|Foreign Owned|0.13|0.14|-0.01|-0.41|0.68|
|Change in mobility|-30.73|-28.38|-2.35|-1.42|0.16|
|Work experience|17.83|16.49|1.34*|1.85|0.07|
|Post-graduate degree|0.16|0.15|0.01|0.58|0.57|
|Studying abroad|0.22|0.21|0.01|0.34|0.74|
|Experience in large business|0.31|0.30|0.01|0.45|0.65|
|Management Z-score|0.20|0.15|0.05|1.03|0.30|
|Senegal Agriculture|0.06|0.04|0.01|0.80|0.42|
|Vietnam Agriculture|0.06|0.07|-0.01|-0.42|0.68|
|Brazil Manufacturing less exposed|0.02|0.03|-0.01|-0.70|0.49|
|Senegal Manufacturing less exposed|0.04|0.02|0.01|1.01|0.31|
|Vietnam Manufacturing less exposed|0.11|0.11|0.01|0.44|0.66|
|Brazil Manufacturing more exposed|0.06|0.07|-0.01|-0.55|0.58|
|Senegal Manufacturing more exposed|0.08|0.06|0.01|0.80|0.42|
|Vietnam Manufacturing more exposed|0.06|0.06|0.00|0.00|1.00|
|Brazil Services less exposed|0.03|0.01|0.02|2.16|0.03|
|Senegal Services less exposed|0.15|0.15|0.00|0.19|0.85|
|Vietnam Services less exposed|0.21|0.24|-0.03|-1.16|0.25|
|Brazil Services more exposed|0.00|0.01|0.00|-0.82|0.41|
|Senegal Services more exposed|0.05|0.05|0.00|0.00|1.00|
|Vietnam Services more exposed|0.06|0.08|-0.02|-0.93|0.35|

Table B8: PSM Balanced Covariate Differences between Treated and Control Group. _∗∗∗p <_ 0 _._ 01 _, ∗∗ p <_ 0 _._ 05 _, ∗p <_ 0 _._ 1 Robust standard errors in parentheses. Treatment group is the firms that increased use of digital technology.

38
than they otherwise would. Assuming that _p_ and/or _θ_ is small, a withholding rate increase raises total tax revenue.

## 2.4 Withholding and Salience of Enforcement

If taxpayers are not fully aware of third-party reporting about them (i.e. misperceive _RT_ ), the withholding system may aect their behavior through a salience channel. Third-party reporting mechanisms usually require information reports to be submitted by the reporting agent to the tax authorities, but not necessarily to the taxpayer. Withholding mechanism, however, normally require the withholding agent to inform both the tax authorities and the taxpayer about the amount of tax withheld, so as to enable the taxpayer to make a reclaim.<sup>14</sup> For taxpayers unaware of third-party reporting, the introduction of withholding thus raises (their perception of) third-party reported sales from 0 to _RT_ and moves reported prots from _π_ ˆ<sup>_∗_</sup> (0) to _π_ ˆ<sup>_∗_</sup> ( _RT_ ) with _π_ ˆ<sup>_∗_</sup> ( _RT_ ) _> π_ ˆ<sup>_∗_</sup> (0) if _p_<sup>_′_</sup> = 0 . Furthermore, the introduction of withholding and the associated communication of the amount of tax withheld to the taxpayer by the withholding agent may increase the salience of tax enforcement in general, captured by the audit probability _p_ in our simple framework. For instance, taxpayers may react to a perceived audit probability _p_ ̃ which is a function of the number of times they have witnessed tax enforcement in practice (e.g. have observed an audit or received a communication from the tax authorities). Being confronted with the tax withholding mechanism (another form of enforcement) may then lead taxpayers to revise _p_ ̃ upwards and increase _π._ ˆ<sup>15</sup> We proceed to estimate the impact of third-party reporting and withholding empirically using policy variation in Costa Rica.

# 3 Context and Data

Costa Rica's tax system relies predominantly on the income tax for rms and the sales tax. Firms in Costa Rica register either as persona física (unincorporated rm, i.e. self-employed individuals) or as persona jurídica (corporation), using the D140 registration form. There are no size thresholds or other requirements obliging rms to chose one rm type or the other, but the governance structure and income tax schedule for the two rm types dier.<sup>16</sup> This section presents rst the income and sales tax system in Costa Rica, and then the compliance mechanisms used to enforce taxes, and nally the administrative data used in this study.

> 14See Figure XII for an illustration of the type of information provided by card processing companies in Costa Rica to aliated businesses.

> 15Note however that a model as in Finkelstein (2009), in which salience merely increases the link between the perceived and actual tax rate, but without moving the misperception in a particular direction, a change in salience has an ambigious eect on taxpayer behavior.

> 16 Wage earners are taxed according to yet another tax schedule, which features three tax brackets with marginal rates of 0, 10 and 15% respectively. The highest kink for wage earners is below the lowest kink for the self-employed.

9
Firebaugh, G., 2000, "The trend in between-nation income inequality," _Annual Review of Sociology,_ forthcoming.

- Flora, Peter, Franz Kraus and Winfried Pfenning (1983), State, Economy and Society in Western Europe, 1815-1975, A Data Handbook in Two Volumes, Frankfurt: Campus Verlag.

- Gans, J. and M. Smart, 1996, "Political equilibrium with single-crossing preferences," _Journal of Public Economics,_ 59, 219-237.

- Gouveia, M. and N.A. Masia, 1998, "Does the median voter model explain the size of government? Evidence from the states," _Public Choice,_ 97, 159-177.

- Helliwell, J., 1994, "Empirical linkages between democracy and economic growth," _British Journal of Political Science,_ 24, 225-248.

- Hewitt, C., 1977, "The effect of political democracy and social democracy on equality

- in industrial societies: A cross-national comparison," _American Sociological Review,_ 42, 420-464.

- Huntington, S.P. and J. Nelson, 1976, _No easy choice: Political participation in developing countries,_ Cambridge, MA, Harvard University Press.

- Husted, T.A. and L.W. Kenny, 1997, "The effect of the expansion of the votiilg franchise on the size of government," _Journal of Political Economy,_ 105, 5482.

- Jaggers, K. and T. Gurr, 1995, "Tracking democracy's third wave with Polity m data," _Journal of Peace Research,_ 32, 469-482.

- Justman, M. and M. Gradstein, 1999a, "The Industrial Revolution, political transition, and the subsequent decline in inequality in 19 th century Britain," _Explorations in Economic History,_ 36, 109-127.

32
0vS.

# IACLE 10: ASSuIPIIONS

1989 1990 1991 1992 1993 1994 1995 BASE YEAR: 1988 CLOSURE: RE D} COHMa ASSU"WTIONS ON DEBT-RESTRUCTURING:

|Reb|TEAR Of RESTRUCTURING:<br>Exit<br>Bonds:<br>I||||||||
|---|---|---|---|---|---|---|---|---|
||neres ae||||||||
|ASeb|<br>Amortization Schedule|.|.|.5|2.5X|2.5X|2.5X|2.31|
|AOEB|Equity:<br>Additionslit||||||||
|.<br>Rk|y<br>Rate of Return|0.02<br>002|0.0X<br>|0.0X<br>|0.0X<br>|0.0<br>|0.0X<br>|0.0X|
|<br>|<br>|.|0.02|0.02|0.02|0.02|0.02|0.02|
|A.dNbb|Iof Debt-Equity<br>Staps<br>financed<br>by Noney Creation|50X|50X|502|502|50e|502|502|