rafmacalaba/datause-encoder-data huggingface dataset:
# Twenty Years of Wage Inequality in Latin America

Julian Messina<sup>_∗_</sup> Joana Silva<sup>_†_</sup>

**JEL classifications:** F16, F41, J31

**Keywords:** Inequality, Labor Markets, Firm Dynamics, Development, Schooling and Experience Premiums, Informality

> _∗_ Julian Messina is a Lead Economist at the Inter-American Development Bank, Washington DC, USA; his email address is julianm@iadb.org.

> _†_ Joana Silva (corresponding author) is a Senior Research Economist at the World Bank, Washington DC, USA; her email is jsilva@worldbank.org.

The research for this paper was financed by the regional studies program of the Office of the Chief Economist for Latin America at the World Bank. The authors are grateful to the editor, Nina Pavcnik, and three anonymous referees, for helpful and constructive comments. The authors also would like to thank Claudia Aburto Ranca ̃no, Andr ́es Alvarez,<sup> ́</sup> Cynthia Arnson, David Autor, Ciro Avitabile, Jo ̃ao Pedro Azevedo, Olivier Bargain, Irene Brambilla, Santiago Caicedo, David Card, Augusto de la Torre, Marcela Eslava, Angel Estrada, Claudio Ferraz, Maria Marta Ferreyra, Jason Furman, Leonardo Gasparini, Roberta Gatti, Gustavo Gonzaga, Mary Hallward-Driemeier, Jonathan Heathcote, Alain Ize, Adriana Kugler, Daniel Lederman, Santiago Levy, Luis F. L ́opez-Calva, Nora Lustig, William Maloney, Jos ́e Gabriel Mart ́ınez, Na ́ercio Menezes-Filho, Samuel Pienknagura, Josefina Posadas, Rafael Prado Proen ̧ca, Rafael Puyana, Carlos Rodr ́ıguez-Castel ́an, Martin Sasson, Sergei Soares, Liliana Sousa, Barbara Stallings, Miguel Sz ́ekely, Daniel Valderrama, Carlos V ́egh, Hernando Zuleta, and participants at seminars and conferences for helpful debates, suggestions, and comments. Daniel M. Angel, Elizabeth Jaramillo, Alejandra Mart ́ınez, Sebastian Melo, Juan Pablo Uribe, and Lucila Venturi provided outstanding research assistance. Finally, the authors would like to thank the National Institute of Statistics of Ecuador (INEC) for access to the Ecuadorian social security records (IESS), and the Ministry of Employment of Brazil for providing access to the Rela ̧c ̃ao Anual de Informa ̧c ̃oes Sociais (RAIS) data. The authors are particularly grateful to Roberto Castillo, Rosangela Farias, Natalia Garz ́on, Karla Marra, Jociany Monteiro, and Diana Zambonino for warmly hosting us and for their unconditional help with these administrative data. A supplementary online appendix for this article can be found at the _World Bank Economic Review_ website. The views expressed in this paper are those of the authors only and not those of the World Bank or the Inter-American Development Bank.
# **REFERENCES**

- Bird, Richard (1994), "Colloquium on NAFTA and Tradition: Commentary: A View for the North," _Tax Law Review, 49_ (Summer).

- Blomstrom, Magnus and Ari Kokko (1997)"Regional Integration and Foreign Direct Investment: A conceptual Framework and Three Cases," Policy Research Working Paper 1750, The World Bank, Washington D.C. (April)

- Boadway, Robin and Neil Bruce (1992), "Pressures for the Harmonization of Income Taxation between Canada and the United States," in John B. Shoven and John Whalley, (editors) (1992), _Canada-U.S. Tax Comparisons ._ Chicago: University of Chicago Press.

- Brown, Drusilla K., Alan V. Deardoff, and Robert M. Stem (1992), "A North American Free Trade Agreement: Analytical Issues and a Computational Assessment," _The World Economy,_ January, pp 15 29.

- Bulmer-Thomas, Victor, Nikki Craske and Monica Serrano (1994) _Mexico and the North American Free Trade Agreement: Who Will Benefit?"_ St. Martin's Press. New York

- Cockfiled, Arthur J.(1998), _International Tax Policy Under NAFTA: The Impact of National Tax Differences on Capital Flows Under Regional Trade and Investment Integration,_ a dissertation submitted to the Department of Law, Stanford University.

- Ddvila Flores, Alejandro (2000), " Impactos Econ6micos del TLCAN en la Frontera Norte de M6xico," in Leycegui, Beatriz and Rafael Fernandez de Castro (editors), (2000), _Socios Naturales? Cinco Aiios del Tratado de Libre Comrcio de America del Norte ._ Instituto Tecnol6gico Aut6nomo de Mexico, Mexico D.F.

- Fernandez, Raquel (1997), "Returns to Regionalism: An Evaluation of Non-Traditional Gains form RTAS," NBER Working Paper No. 5970 (March).

- Fernandez de Castro, Rafael (2000), " Las Instituciones del TLCAN: Una Evaluaci6n a los Cinco Afios," in Leycegui, Beatriz and Rafael Fernandez de Castro (editors), (2000), _Socios Naturales? Cinco Anos del Tratado de Libre Comrcio de America del Norte_ . Instituto Tecnol6gico Aut6nomo de Mexico, Mexico D.F.

- Gordon, Roger and Eduardo Ley (1994), "Implications of Existing Tax Policy for Cross Border Activity Between the United States and Mexico after NAFTA" _National Tax Journal,_ 47, pp 35-41

- Gravelle, Jane G. (1986) "International Tax Competition: Does it Make a Difference for Tax Policy? 39 _National Tax Journal,_ pp 375-384

- Hinojosa Ojeda, Raul, David Runsten, Fernado De Paolis, and Nabil Kamel (2000), "The U.S. Employment Impacts of North American Integration After NAFAT: A Partial Equilibrium

25
_ 1.14 although they work loss number of days in a year than family and permanent workers. On the average there. are five casual laborers involved In :he farm operations of a household and they work about 62 days in a year. There are fewer people per household Involved In catual farm work In the South but they work more days than in the North.

Table L!3*: **Labor** Use on Farms by Region

||**Fai**<br>**ar**|**id Pwnmnt**|**Caw**|**il**||
|---|---|---|---|---|---|
|Region|Mean Size<br>of Farm<br>Households|Workers|Mean Days<br>Worked<br>Per Person<br>Per Year|Workers|Mean Days<br>Worked<br>Per Person<br>Per Year|
|**Ashanti**|5.2|1.7|214.8|2.9|49.4|
|**Brong**Ahao|5.2|1.8|218.6|3.5|55.0|
|Cental|5.5|1.7|233.0|7.0|74.7|
|Easrn|6.2|1.8|230.6|4.1|99.6|
|**GOmter**Accra|4.9|1.6|166.5|3.4|20.5|
|Norwrn|6.8|3.0|310.4|6.0|58.5|
|Upper East|6.0|5.0|264.2|7.0|38.2|
|Upper West|7.3|3.4|338.5|10.1|43.8|
|VoNt&|6.3|1.8|180.3|5.5|68.4|
|Western,|5.5|1.7|211.5|4.4|56.4|
|North|6.7|3.4|307.4|7.0|52.2|
|South|5.6|17|2125|45|65.1|
|Ghana|5.9|2.2|238 2|5.0|62.3|

# Purchased Inputs

Apart from farm knplements like axe, hoe, matchets, sickle, very few of the farm inputs are purchased. Lnilted amounts of fertilizer are used on food crops like maize, rice and pineapple. The major fertilizers used are NPK, urea and ammonium sulphate. Some cocoa farmers spray their trees wlth unden and gammalin Insecticide.

Farmers may purchase the seeds of knproved varieties from the Seed Company or other organizations Involved In seed multiplication. Hybrld cocoa seedlings may be obtained from the Cocoa Services Division of COCOBOD and oil pakl seedlings are obtained from the Oil Pakm Research Station at Kusl.
- 12 -

The social rates of return is the highest for primary education (14.4%), followed by secondary education (12.9%), implying that investment in these levels of schooling will promote both equity and efficiency objectives. These findings are consistent with those elsewhere that additional years of primary education will increase productivity and income among the poor 4. In secondary and higher education, the social rates of return are not very high due partly to higher government subsidy in terms of increased operating budget and teachers' salaries. This is also reflected in the index of subsidization particularly for higher education, which indicates the degree to which costs are borne out by the public sector compared to the private sector. In China, the index is only 4 percent for secondary education and 31 percent for higher education . The high private returns to secondary and higher education imply that investment in these levels lead to high wagepaying jobs, an important paradigm in a rapidly growing economy such as China. But, high wages may also reflect institutional pressures (minimum wages) rather than augmented productivity resulting from human capital formation by these levels of education'.

_Table 5: Rates of Return to Education (Percent), 1993_

||_Private_<br>_Rate of Return_|_Social_<br>_Rate of Return_|_Index of_<br>_Subsidization_<br>_(a)_|
|---|---|---|---|
|Primary|18.0|14.4|1.25|
|Secondary|13.4|12.9|1.04|
|Higher|15.1|11.3|1.31|

Note: see Technical Annex A for detail (a) The ratio of private to social rates of return. _Source:_ Staff calculations from MOL Survey 1993 Table 6 reports the basic Mincerian earnings functions, showing that the overall marginal private rate of return to one year of extra schooling, irrespective of education level, is around 12.5 percent. The marginal returns to education for three levels of education are displayed in the last column. These rates are consistent with the earlier 4See for example, Lockheed, Jamison and Lau, 1980,"Farmer Education and Farm Efficiency: A Survey in Education and Income" _World Bank Staff Working_ Paper No 402. Authors found that on average, farmers with four years or more of primary education were at least 7 percent more productive than those with no primary schooling.

**5** Labor productivity improved slowly until 1987. See I.J. Singh,"Industrial productivity in Socialist Economies", 1991.
if 1 _≥ ms_<sup>_≥p>_0,</sup><sup>_eij_iscalleda</sup><sup>_p_</sup><sup>**_-stableedge_**or</sup><sup>_p_</sup><sup>**_-stableconnection_**.3</sup> A network _M_ consisting of only _p_ -stable connections of _Nt_ is called _p_ **_-stable network_** of _Nt_ .

**Definition 2:** Let _Rt_ be the cDCC matrix defined in Section 2.1. At time _t_ , let _<u>ρ</u>_ <u>(</u> _t_ ) be the mean of the lower triangular part of _Rt_ , and _σ_ ( _t_ ) be its standard deviation. A correlation level _ρij_ ( _t_ ) _∈ Rt_ is called _c_ **_-strong_** if _ρij_ ( _t_ ) _≥_ _<u>ρ</u>_ <u>(</u> _t_ ) + _c · σ_ ( _t_ ) where the constant _c ≥_ 0.<sup>4</sup><sup>_,_5</sup>

Then our approach is as follows: For a pre-determined strength level _c_ , we construct a dynamic network _Nt_ consisting of nodes connected by only _c_ -strong correlations at time _t_ , where nodes represent the sample countries. Next, for the considered time period, we construct _M_ ; the _p_ -stable network of _Nt_ . For relatively high _p_ values, we can intuitively state that members connected in _M_ are integrated. As _c_ -level is chosen higher, this integration degree gets stronger.

In the following section, we will study the integration/segmentation structure of the EMU bond markets by analyzing the _p_ -stable connections. For the sake of simplicity in our setup, we introduce the following definition which will be our main focus throughout the rest of this study.

> 3It is clear that every _p_ 1-stable connection is also _p_ 2-stable for any _p_ 2 _≤ p_ 1 _≤_ 1.

> 4It would be naive to choose a fixed threshold level to determine if a correlation value is strong or not. Several studies in the literature have shown that correlations are timevarying and tend to increase in turbulent times. Therefore, a fixed choice would most likely introduce a bias depending on the global conditions. With our model, the threshold level is determined endogenously and updated everyday. Thus, possible bias arising due to changing global conditions is minimized.

> 5When _c <_ 0, _c_ -strong correlation levels become below the average. In order to consider a reasonable strength concept for correlations, minimum _c_ should be taken as 0.

7
80 If the transformation of China’s economic system followed such lines, the role of the government would become more “traditional” than today. By that I mean that the government would focus on policies to encouraging market-supporting institutions, improving the infrastructure, stimulating investment in human capital, contributing to a stable macroeconomic environment, mitigating major market failures, including those in insurance markets, taking actions against negative externalities of various types, and redistributing income in favor of poor geographical areas and population groups – rather than intervening in individual firms.

It is, however, generally realized that major improvements in the social arrangements would require much more government financing (taxes and/or mandatory insurance fees). Although tax revenues could already be increased through more efficient tax collection, considerably increased policy ambitions in the social field certainly require higher tax _rates_ . It would also be important to reform the system of intergovernmental financial relations by transferring more funds from central to local governments, in particular in poor geographical areas.

In spite of the modest ambitions of social policies during the period of economic reforms, life expectancy and adult literacy are rather impressive in China as compared to other countries with about the same per capita GDP. Indeed, according to several cross country evaluations, China ranks higher in terms of such “social” (or “human”) variables than in terms of per capita GDP – in spite of the rather low priority given to social issues during the reform period.<sup>155</sup> There are at least two ways of explaining this apparent paradox. One could be that the high life expectancy and the widespread adult literacy are to a considerable extent an “inheritance” from the pre-reform period, when widely distributed, although quite simple, health care and basic education were emphasized. As regards health, another explanation could be that China more than other countries with a similar

> 155 For instance, while China was ranked as country number 96 in terms of GDP per capita (measured on a PPP basis) in 2003, it was ranked as number 85 in terms of the HDI index (UNDP, 2005, p. 81). This index – the Human Development Index (HDI) is based on a number of broad economic and social indicators.

> In another study, the China Center for Modernization Research (2005) concludes that China is in about the same position in terms of “economic modernization” as the most modern countries today were 100 years ago, while the lag is 80 years in terms of “social modernization”. While economic modernization is then measured by variables such as GDP per capita and the share of the population and the share of GDP produced in agriculture, human modernization is measured by health variables, such as average life expectancy, and basic education variables, such as adult literacy rates.
8 1983 resource transfers from officia: creditors have remained positive, but to every category they have fallen, except to the HIC's and Latin America, which have received more. Partly the overall decline reflects the interest burden, and for some manufacturing exporters it may reflect a positive decision to borrow less when even official loans were becoming more expeneive in real terms. The decision to increase net transfers to Latin America probably reflects political decisions by creditor governments to use official lending to avert a breakdown of relations with commercial creditors.

Note that the net transfers from official creditors to middle-income debtors are far less than what commercial creditors took out. So there has been no global bail out. It was probably more common that the carrot of official lending, small as it was relative to total debt of HICs, helped keep debtors at the negotiating table with commercial creditors, who succeeded there in getting large net resource transfers.

III. Resource Transfers and Investment Since 1980 most developing countries have had negative net resource transfers along with lower investment rates, and slower or negative output growth. Some observers argue that the primary chain of causal connections has run from debt crisis to negative transfers to curtailed investment to stagnant output (Sachs, 1986; Husain, 1988). Feedback loops only made matters worse. Did a more positive resource balance (corr-ponding to more negative transfer to creditors) lead to lower investment?

The simple cross-sectional correlation between the share of GDP going to investment and the share going to resource balance has the predicted
26 Table 5: Comparison of WRI and TRI estimates with and without simplifying elasticity assumption, sub-set of covered products,<sup>a</sup> 1960 to 2007 (percent)

|Usin<br>produ|g elastic<br>ctsforw|ity data f<br>hichdata|or subse<br> are ava|t of<br>ilable|With<br>|simplify<br>andfora|ing elas<br> sub-set|ticity ass<br> ofprodu|umption<br>cts<sup>a</sup>|Co<br>differe|mpariso<br>nce betw|n (perce<br>een(1)-|ntage poi<br>(5) and (|nt<br>6)-(10)|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|(11)|(12)|(13)|(14)|(15)|
|1960-|1970-|1980-|1990-|2000-|1960-|1970-|1980-|1990-|2000-|1960-|1970-|1980-|1990-|2000-|
|69|79|89|99|07|69|79|89|99|07|69|79|89|99|07|
|**Trade Reduction Indexes**|||||||||||||||
|EU<br>68|51|65|34|22|75|55|74|40|24|7|3|10|6|2|
|EFTA<br>37|24|25|24|55|41|29|25|27|57|4|4|0|3|2|
|ECA<br>na|na|na|5|7|na|na|na|8|11|-|-|-|4|4|
|NA<br>1|1|3|3|2|4|3|8|5|4|2|2|5|2|2|
|Japan & Korea<br>50|61|99|124|103|58|81|137|163|128|8|20|38|39|25|
|Oceania<br>-2|-2|-4|-1|0|-5|-4|-6|-3|0|-3|-1|-2|-2|0|
|**Welfare Reduction Indexes**|||||||||||||||
|EU<br>103|102|109|57|40|116|113|123|62|42|13|11|14|6|2|
|EFTA<br>108|100|138|173|147|126|113|146|181|148|18|13|8|8|1|
|ECA<br>na|na|na|39|45|na|na|na|41|43|-|-|-|2|-1|
|NA<br>13|11|27|19|20|16|14|35|23|23|4|3|9|4|4|
|Japan & Korea<br>70|101|162|201|171|77|119|201|246|205|6|18|39|46|34|
|Oceania<br>20|19|16|10|4|24|23|20|14|5|5|4|4|4|1|

Sources: Authors’ calculations based on data in Anderson and Valenzuela (2008) and elasticity estimates from Roningen (2001) and Tyers and Anderson (1992).

a. The TRI and WRI estimates in these columns are for a sub-set of farm products for which we have elasticity data (so as to enable direct comparison of the results with and without the simplifying elasticity assumption).
Almost two-thirds (65%) of village funds have a savings facility, and 55% of funds require borrowers to do some saving. The minimum deposit size averages 181 baht (or 70, if the median value is used), but 52% of funds require monthly deposits, which average 67 baht (50, using the median value). About two-fifths (41%) of funds do not pay interest on savings; for the others, the median interest paid is 5% p.a.

A second mechanism for mitigating risk is to require loan guarantees. VF borrowers are expected to have guarantors, typically two (in 78% of village funds) or three (in 16% of cases). The guarantors are rarely called upon to make good on a loan – certainly this was so in 90% of the villages surveyed – but in the remaining cases there was recourse to the guarantors, typically for one or two loans per village. Three percent of villages reported turning to guarantors to repay more than two loans.

It is also possible to reduce risk by requiring borrowers to repay in installments. About one VF in four expects borrowers to repay monthly, although for two-thirds of loans the payment is make at the end of the year (or the term of the loan), as Table 15 shows. Fully 84% of loans are repaid to the VF in cash and collected at the village prior to being deposited in the bank where the VF has an account – again probably a mechanism to help ensure timely repayment. An estimated 19% of loans are repaid directly to a bank (with the overlap representing loans that are repaid partly in cash and partly to a bank).

**<mark>Table 15.  Repayment Procedures</mark>**

|Repaymentperiod|% breakdown|
|---|---|
|Weekly|0.2|
|Monthly|28.1|
|Quarterly|1.6|
|Yearly|62.0|
|At end of term|6.1|
|Other|2.1|

Source: Village Fund Survey, 2010.

The bulk (88%) of VFs have subcommittees, or designated committee members, to encourage loan repayment; nearly two-thirds (64%) allow overdue loans to be rescheduled; but just 6% are willing to consider further loans to individuals whose loans have been rescheduled.

VF officers and committees frequently complain that they do not get as much support as they would like from the regional or central office. Most say they would like help with bookkeeping (87%), management (83%), assessing the creditworthiness of borrowers (68%), or for other matters (98%). The need for maintaining and upgrading skills can easily be overlooked in such a highly decentralized organization.

25
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Table 1: SCPs by Departament in Colombia

|Department|Number of|Number of|% Total|%|SCP Enrollment|by Type of Inst|itution|
|---|---|---|---|---|---|---|---|
||Programs|HEIs|Enrollment<br>in SCP|SENA|Technological<br>and Technical<br>Institutes|Technological<br>Schools|Universities|
|Antioquia|371.2|44.26|40.39|64.37|4.98|23.99|6.66|
|Atlantico|180.24|19.82|27.54|46.36|28.58|18.83|6.22|
|Bogota|621.61|74.8|32.72|41.7|32.39|20.42|5.5|
|Bolivar|143.8|14.9|43.79|64.08|15.13|15.55|5.25|
|Caldas|81.94|12.49|26.7|78.12|11.22|0.88|9.78|
|Cordoba|57.23|9.39|22.55|84.42|11.6|1.69|2.29|
|Meta|71.18|13.25|29.49|79.51|12.3|7.32|0.86|
|Nariño|77.84|12.18|23.28|84.68|2.2|9.06|4.06|
|N. de Santander|106.94|12.35|20.83|61.22|22.44|0.2|16.14|
|Risaralda|97.46|12.31|33.84|62.99|14.88|11.03|11.09|
|Santander|185.16|21.52|40.6|66.41|20.54|8.08|4.96|
|Tolima|111.19|11.78|44.89|59.77|29.88|1.75|8.6|
|Valle|262.29|33.81|34.77|53.76|23.01|9.06|14.16|

Note: This table displays information for the 13 departments that contain the metropolitan areas included in our empirical analysis. For each variable, it shows average over years between 2003 and 2019. Percentage of enrollment in short-cycle programs is relative to total higher education enrollment in the department. The last four columns correspond to the percentage of SCP enrollment by institution type (they add up to one by department).

# **2.3 Economic Activity Measures**

We study program entry and exit at the market level, defined as a combination of location and field of study. Our sample include 312 markets (13 locations times 24 fields of study). By definition, an HEI that offers programs in multiple fields of study participates in multiple markets; in a given year, it might open or close programs in some markets but not others.

Given our market definition, we construct explanatory variables at the location-field level. To study the responsiveness of SCP supply to changes in local economic activity, an challenge is the lack of a direct mapping from higher education fields of study to economic activity sectors. We overcome it by constructing two measures of the local demand for graduates from a given field, GDP by field and field relative employment. Below we describe the measures; in Section 4 we justify their exogeneity.

**GDP by field** . We construct a Bartik-style (Bartik, 1991), shift-share variable using OLE and DANE data to measure shocks to the local economic activity associated with a field of study. For a given year, we interact sector-level aggregate activity at the national level with local time-invariant employment shares by field and economic sector as follows:

10