rafmacalaba/datause-encoder-data huggingface dataset:
for other infectious diseases such as inuenza, Ebola, Zika or Coronavirus. As cell phone usage has become prevalent throughout the developing world and cell phone providers are beginning to understand how the data they collect can be used by policymakers to implement better policies, measuring short term movement becomes easier. The collection and integration of high frequency data on infectious diseases then makes it possible to study these models that help policymakers better target interventions, and then document their impact. This could help countries lower the disease burden from existing infectious diseases and prevent epidemics of new diseases, leading to benecial economic and social consequences.

# References

- Adda, Jérôme (2016). Economic Activity and the Spread of Viral Diseases: Evidence from High Frequency Data. The Quarterly Journal of Economics 131.2, pp. 891941.

- Adhvaryu, Achyuta (2014). Learning, misallocation, and technology adoption: evidence from new malaria therapy in Tanzania. The Review of economic studies 81.4, pp. 13311365.

- Adriansen, Hanne Kirstine (2008). Understanding pastoral mobility: the case of Senegalese Fulani. The Geographical Journal 174.3, pp. 207222.

- Agence Nationale de la Statistique et de la Démographie - Ministére de l'Economie, des Finances et du Plan (2014). Enquete a l'ecoute du Senegal 2014.

- Aker, Jenny C and Christopher Ksoll (2019). Call Me Educated: Evidence from a Mobile Phone Experiment in Niger. Economics of Education Review.

- Alegana, Victor A et al. (2013). Estimation of malaria incidence in northern Namibia in 2009 using Bayesian conditional-autoregressive spatialtemporal models. Spatial and spatiotemporal epidemiology 7, pp. 2536.

- ANSD and ICF International (2015). Senegal DHS, 2014 - Final Report Continuous 2012-14.

- Apouey, Bénédicte, Gabriel Picone, and Joshua Wilde (2018). The Economics of Malaria Prevention. Oxford Research Encyclopedia of Economics and Finance.

39
- Baier, S. L., Yotov, Y. V., and Zylkin, T. (2019). On the widely differing effects of free trade agreements: Lessons from twenty years of trade integration. _Journal of International Economics_ , 116:206–226.

- Bajgar, M. and Javorcik, B. (2020). Climbing the Rungs of the Quality Ladder: FDI and Domestic Exporters in Romania. _Economic Journal_ , 130(628):937–955.

- Baldwin, R. E. (2000). Regulatory protectionism, developing nations, and a two-tier world trade system. _Brookings Trade Forum_ , 2000(1):237–280.

- Bernard, A. B., Jensen, J. B., Redding, S. J., and Schott, P. K. (2007). Firms in international trade. _Journal of Economic Perspectives_ , 21(3):105–130.

- Bernard, A. B., Jensen, J. B., Redding, S. J., and Schott, P. K. (2012). The empirics of firm heterogeneity and international trade. _Annual Review of Economics_ , 4(1):283–313.

- Bernard, A. B., Redding, S. J., and Schott, P. K. (2011). Multiproduct Firms and Trade Liberalization *. _The Quarterly Journal of Economics_ , 126(3):1271–1318.

- Blanga-Gubbay, M., Conconi, P., and Parenti, M. (2020). Lobbying for Globalization. CEPR Discussion Papers 14597, C.E.P.R. Discussion Papers.

- Broda, C. and Weinstein, D. E. (2006). Globalization and the gains from variety. _The Quarterly Journal of Economics_ , 121(2):541–585.

- Chaney, T. (2008). Distorted gravity: The intensive and extensive margins of international trade. _American Economic Review_ , 98(4):1707–21.

- Chen, M. X. and Mattoo, A. (2008). Regionalism in standards: good or bad for trade? _Canadian Journal of Economics/Revue canadienne d'économique_ , 41(3):838–863.

- Correia, S., Guimarães, P., and Zylkin, T. (2020). Fast poisson estimation with highdimensional fixed effects. _The Stata Journal: Promoting communications on statistics and Stata_ , 20(1):95–115.

25
-2-

new economic policies, for example, by vegrina production towards exports, or to leave the market.

On the macroeconomic side, the most important developments in 1980-82 were export orientation and disinflation.' The comprehensive stabilization/liberalization program included policies aimed at trade liberalization, real depreciation of the exchange rate and reduction of domestic absorption. The economy responded quickly. The Gross National Product (GNP) growth rate, which was negative in 1979 and 1980 picked up and reached 4.1% in 1981 and 4.6% in 1982; although below the 1973-77 average of 6.5%, the increase in growth rates did reflect a recovery. In the meantime, the composition of demand changed drastically: The rate of growth of domestic absorption, averaging 8.2% in 1973-77, was only 1.6 and 2.8% in 1981 and 1982. While the contribution of foreign balance to GNP growth was negative between 1973-77, it was positive in the 1980's--with the exception of 1983.2 Exports grew by 47 and 25% in constant Turkish lira prices in 1981 and 1982 respectively. The decline in the rate of inflation was even more dramatic. The annual rate of change of the wholesale price index declined from around 107% in 1980 to 37% in 1981 and 25% in 1982 (see Figure 1). In short, 1980-82 were years of drastic realignments in major macroeconomic variables, which were bound to affect corporate performance.

The deregulation episode in the financial markerc lasted two and a half years. The objective of increasing deposits and financial savings in general 1 For a detailed overview of macroeconomic policies and performance in the 1970s and 1980s, see Celasun and Rodrik (1987).

**2** Data from OECD, Economic Survey: Turkey, various issues. Let Y, A and B stand for GNP, domestic absorption and the current account surplus respectively, all in constant prices. Then, Y - A + B and Y - aA + bB where hats denote percentage changes, a - A/Y and bA- B/Y. The contribution of foreign balance to GNP growth is defined as bB.
WPS3919

# <u>MEXICO: TWO DECADES OF THE EVOLUTION OF EDUCATION AND INEQUALITY</u>

Gladys López-Acevedo (LCSPE) <u>gacevedo@worldbank.org</u> � Latin America and the Caribbean Region Poverty Reduction and Economic Management Division The World Bank JEL Codes: I00, C20, D30

# **Abstract**

Mexico experienced a pronounced increase in the degree of inequality and earnings inequality over the 1980s and mid-1990s. Contrary to the trend in the distribution of total income inequality, there has been an improvement in the distribution of earnings inequality since 1996. This paper shows the following results. First, education has the highest gross contribution in explaining changes in earnings distribution. Second, both changes in the distribution of education and in the relative earnings among educational groups have always been in phase with the alterations in the earnings distribution. Specifically, when the income profile effect related to education became steeper and the inequality of education increased, the earnings distribution worsened (as in the 19881996 period). Third, changes in the relative earnings among educational groups are always the leading force behind changes in inequality.

Key words: Economic Development, Salary Wage Differentials, Rate of Return World Bank Policy Research Working Paper 3919, May 2006 _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._

> � I wish to thank Monica Tinajero for her help in processing the several databases used in this paper and Barrett Sheridan for his editorial assistance.  The paper also has been accepted for publication  in the Handbook of Education, UCLA.
# **References**

Acemoglu, D. 1999. “Changes in Unemployment and Wage Inequality: An Alternative Theory and Some Evidence”. _The American Economic Review_ , 89(5), pp. 1259-78.

Acemoglu, D. and D. Autor. 2011. “Skills, Tasks and Technologies: Implications for Employment and Earnings”. In Orley Ashenfelter and David Card (eds.) Handbook of Labor Economics, Vol. 4, Part B, 1043-1171. Amsterdam: Elsevier.

Almeida, R., C. Corseuil, and J. Poole. 2017a. “The Impact of Digital Technologies on Employment and Skills: Do Labor Policies Matter?”. World Bank Policy Research Working Paper 8187.

Almeida, R., A.M. Fernandes, and M. Viollaz. 2019. “Software Adoption, Employment Composition, and the Skill Content of Occupations in Chilean Firms”. _Journal of Development Studies_ , Forthcoming, 2019.

Artuç, E., L. Christiaensen, and H. Winkler. 2018. “Does Automation in Rich Countries Hurt Developing Ones? Evidence from US and Mexico”. Mimeo.

Autor, D., F. Levy, and R. Murnane. 2003. “The Skill Content of Recent Technological Change: An Empirical Exploration”. _Quarterly Journal of Economics_ , 118(4), pp. 1279-1333.

Autor, D. and D. Dorn. 2013. “The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market”. _The American Economic Review_ , 103(5), pp. 1553–1597.

Autor, D. 2014. “Skills, Education, and the Rise of Earnings Inequality among the ‘Other 99 Percent’”. _Science_ , 344(6186), pp. 843-851.

Autor, D., D. Dorn, and G.H. Hanson. 2015. “Untangling Trade and Technology: Evidence From Local Labour Markets”. The Economic Journal, 125, pp. 621-646.

Bernard, A., and J. Jensen. 1999. “Exceptional Exporter performance: Cause, Effect, or Both?”. _Journal of International Economics_ , 47, pp. 1-25.

Constantinescu, C., A. Mattoo, and M. Ruta. 2017. “Trade Developments in 2016: Policy Uncertainty Weighs on World Trade”. World Bank Group.

Cortes, G. M., N. Jaimovich, and H. E. Siu. 2016. “Disappearing Routine Jobs: Who, How, and Why?”. NBER Working Paper 22918.

Di Carlo, E., S. Lo Bello, S. Monroy-Taborda, A.M. Oviedo, M.L. Sanchez-Puerta, and I. Santos. 2016. “The Skill Content of Occupations across Low and Middle Income Countries: Evidence from Harmonized Data”. IZA Discussion Paper 10224.

Ebenstein, A., A. Harrison, M. McMillan, and S. Phillips. 2014. “Estimating the Impact of Trade and Offshoring on American Workers using the Current Population Surveys”. _Review of Economics and Statistics_ , 96(4), pp. 581–595.

Grossman, G. M., and E. Rossi-Hansberg. 2008. “Trading Tasks: A Simple Theory of Offshoring”. _American Economic Review_ , 98(5), pp. 1978–1997.

Goos, M. and A. Manning. 2007. “Lousy and Lovely Jobs: The Rising Polarization of Work in Britain”. _Review of Economics and Statistics_ , 89(1), pp. 118-33.

21
Until now, we have mainly considered the issue of the choice of the time window by simply varying the window to exposure, using _t_<sup>_′_</sup> _∈_ 1 _,_ 3 _,_ 6. However, this treatment may not be sufficient and, in fact, obfuscate cumulative effects. Since a 3-month window is inclusive, the 1-month window, and the 6-month window is inclusive of both, the widening of time windows can increase the likelihood that a longer time window is, in fact, inclusive of exposure to more events. Since we have GPS-linked ACLED data over the full period before each GHS round, this conjecture can be tested. Specifically, in the full sample (excluding Borno) the likelihood that any individual was exposed to a herder-related violent event is a minuscule 0 _._ 8 percent. However, conditional on having been exposed to a violent event in the six months prior (that is, violence exposure in _t −_ 2 _, ...,_ 6, outside of _t −_ 1), the likelihood of exposure to violence in the last month increases to 8 _._ 2 percent, indicating a factor increase of 13.6x.<sup>33</sup> That is, very recent violence exposure is much higher in areas with other, _recent_ exposure.

If individuals change their labor supply decisions based upon their expectation of violence, then a reasonable assumption would be that continued exposure to such violence would elicit different reactions than among those for individuals who were not recently exposed to some herder-related violent event. To consider these possibilities, we amend equation (1) by adding an interaction term for exposure to another, recent event. Specifically, we fix the time window of our treatment to one month ( _t_<sup>_′_</sup> = 1), interacted with a dummy variable taking the value of one if there was other, recent exposure in the five months prior to that last month ( _−t_<sup>_′_</sup> = 6), giving: To make the key coefficients of interest more tractable, the terms in equation (2) can be simplified in terms of the marginal effects of interest (dropping the subscripts for simplicity). Specifically: Where equation (3) is the marginal effect of herder-related violence exposure, _given no other recent violence exposure_ . Equation (4) gives the marginal effect of exposure to violence _given some exposure to recent violence_ , specifically at ( _−t_<sup>_′_</sup> = 6). As a result, the term _δpv − βpv_ would capture a heightened or muted response based on individuals reacting to violence exposure under the shadow of other, repeated violent events related to the conflict. Given the above discussion, a non-zero effect in equation (4) would be of particular interest, as it would indicate a stronger (or weaker) labor response under the shadow of

> 33The average among individuals not previously exposed is _._ 006, compared to that of _._ 082 for recently exposed households, giving _._ 082 _/._ 006 _≈_ 13 _._ 6.

14
- 32 -

Administration Institute (ESAP) and National Cadastre Agency (IGAC), agencies which provide training for local level officials and revised estimates of property values respectively; (f) and a timetable for the national government to reorganize and transfer functions toward the 1992 deadline.

33. The full implementation of Law 12 will have a major impact on the finances of municipalities. By 1992, municipalities in the aggregate will receive 852 more resources than they would have under the old sharing formula.<sup>2 2</sup> For small municipalities, the increase is due to an increase in their share and to an assumed greater fiscal effort since, due to relatively slow growth, they would have lost revenues on a population basis alone. For larger cities, the increase is due mainly to their increase in population share and to a lesser extent to the rising proportion of the IVA (impuesto al valor agregado or VAT) being shared. These changes will have a major impact on the finances of municipalities. The dependence of municipalities on transfers will rise dramatically--for all municipalities from 382 to 58% of current revenues and especially for small municipalities from 67 to 83% of current revenues.<sup>2 3</sup> Without these transfers it is estimated that municipalities in general--and small municipalities in particular--would not be able to finance their current expenditures out of their own revenues.

34. Law 12 represents a welcome attempt to transfer greater resources to municipalities, give them incentives to raise their own resources (at least for smaller municipalities), and initiate some measures to increase 22/ See IBRD (1987), 2D. cit, p. 39 23/ Ibid, p. 40.
and to illustrate its usefulness with an example that is relevant for development policy. The proposed method is potentially applicable to a wide range of questions. Its main use is to investigate whether a particular dimension of social structure may be involved in resource misallocation. It does so by checking that the pattern of flows across agents is consistent with the existence of frictions associated with a particular social structure. If no evidence is found, it implies that this particular aspect of social structure could not have caused the misallocation.<sup>2</sup> The methodology is implemented by focusing on land allocation in village economies. Factor markets in developing countries are plagued by incomplete information and unclear property rights that lead to high transaction costs and are thought to hinder the allocation of productive factors (de Janvry et al., 1991; Pender and Fafchamps, 2005; Otsuka, 2007). Pre-existing social networks are thought to play an important role in alleviating these issues by increasing trust, decreasing information asymmetries, and reducing transaction costs. Such markets are thus a good test case for the methodology presented here.

Land ownership is notoriously unequal in many agrarian societies. At the same time, traditional agricultural systems are often characterized by decreasing returns to scale beyond a minimum scale of operations (see Ali and Deininger (2015) for an excellent recent review of the literature). A more efficient and equitable allocation of cultivated acreage thus requires temporary transfers of land from land-rich to land-poor farming households. It is also well known that homophily and discrimination are common in market and non-market exchange: many people prefer to trade and exchange favors with people who are socially proximate. The question therefore arises of whether homophily and discrimination contribute to the unequal allocation of cultivated acreage. Access to agricultural land is a sensitive political issue in many developing countries because it is a major determinant of household welfare. Whenever access to land is impeded – or perceived to be impeded – by ethnic and other social divides, this can lead to violence, as has been seen in a number of developing countries. Identifying the dimensions of social structure that contribute to unequal access to land can thus make a valuable contribution to conflict prevention.

The empirical analysis takes advantage of an unusually rich dataset on land and labor trans3
22 the Table 11.3.

In the tests for inflation we cannot reject the hypothesis that inflation is a random walk with drift. We first observe in the PhillipsPerron set of tests that 0(*3) does not reject the hypothesis HO: (Bqamp,#a-l) at a 102 significance level. The statistics Z(a), Z(ta) do not reject the hypothesis of a unit root (a-1) either. We then use the statistic Z(02) and we reject the null Hot (C-p-0, a-1) at a 52 or 12 significance level depending on the residuals we use for estimating the nuisance parameters o and au<sup>2</sup> . We therefore conclude that model (17.b) is the more appropriate and {<sup>1</sup> t) follow. a random walk with drift<sup>21</sup> .

The tests for the time series properties of the log of the real money stock (mt) also do not reject the hypothesis of an I(1) process. In model, (17.c) the statistics Z(03), Z(a) and Z(tq) do not reject their respective null hypothesis at a 102 significance level. Z(02) rejects the null (/mBm0,6ml) at a 5 significance level. Again we accept the hypothesis of a random walk with drift<sup>22</sup> .

The tests for the regulated deposit interest rate also select the random walk with drift. None of the statistics based on model (17.c), 20 The PP tests involve the estimation of two nuisance parameters, through the statistics S<sup>2</sup> u, S<sup>2</sup> Tl;which are sensitive to the estimators we use for the ut's. Both, the residuals of model (15.a) and the first differences (yt - ytt 1) can be used for estimating them under the null of a driftless random walk (p1-B0, al). S<sup>2</sup> 1 yields a consistent estimator of a when 1 grows at the controlled rate T-17, which in our case is _33-113-3.2._ 21 DF ard Augmented Dickey-Fuller (ADF) tests using up to four lagged differences do not reject the unit root hypothesis in model (15.b) for the rate of inflation.

22 DF tests in which the errors are corrected for seasonality fail to reject the unit root hypothesis in "odel (15.b).
pirate _i_ enters, then _Ti_<sup>_τ_(</sup><sup>_aτ_</sup> _i_<sup>) is given by</sup> Second, high ability pirates are the first to enter, followed by their lower-ability peers: entry in period _τ_ is characterized by a cutoff _<u>a</u>_ <u>(</u> _δi, n_<sup>_τ−_1</sup> _, ν_<sup>_τ_</sup> _, κ_<sup>_τ_</sup> ) such that pirate _i_ enters in _τ_ period if and only if The measure of the set of entrants (i.e. the number of observed attacks) in period _τ_ is thus given by

# **4 Estimation**

## **4.1 Data Description**

The data set that we use in this paper comes from two main sources. The first consists of data on pirate attacks provided by the International Maritime Bureau’s Piracy Reporting Center, thereafter referred to as the IMB data. The Piracy Reporting Center collects information on all self-reported pirate-related incidents around the world.<sup>7</sup> We classify an attack as carried out by Somali pirates if it took place along the coast of Somalia, the Arab Republic of Egypt, Eritrea, the Islamic Republic of Iran, Iraq, Kenya, Oman, Saudi Arabia, Seychelles, Tanzania, the United Arab Emirates, the Republic of Yemen, or anywhere in the Red Sea, Arabian Sea, Gulf of Aden, or Gulf of Oman. We then drop from the data all attacks that are not carried out by Somali pirates. Moreover World Bank (2013) checked local news outlets for information on attacks that took place along the coast of India and in the strait of Hormuz; four incidents were not attributed to Somali pirates and were dropped accordingly from the data. Attacks in our data span from 2000 to 2012, 7Given the self-reported nature of the information, under-reporting could be expected in the earlier years when piracy was not yet salient, potentially leading to an underestimate of the effect of law enforcement.

19
|Actual discharge from vessel|LKCMB|2021-12-05-21.09.51.000000|Full|
|---|---|---|---|
|Actual loaded on vessel|LKCMB|2021-12-09-03.26.28.000000|Full|
|Actual vessel departure|LKCMB|2021-12-09-07.18.00.000000|Full|
|Actual vessel arrival|INVTZ|2021-12-15-12.09.00.000000|Full|
|Actual discharge from vessel|INVTZ|2021-12-16-05.28.00.000000|Full|
|Actualgate out|INVTZ|2021-12-22-06.11.00.000000|Full|
|Actualgate in|NPBRG|2022-02-03-09.15.00.000000|Full|
|Actualgate out|NPBRG|2022-02-17-18.16.00.000000|Full|
|Actualgate in|NPBRG|2022-02-18-09.52.00.000000|Empty|

_Table 4: Rules that consistent events must follow (TradeLens dataset)_

|**Prior event**|**Prior location**|**Event**|**Next location**|**Posterior event**|
|---|---|---|---|---|
|Vessel arrival|same|'Actual discharge from vessel'|same|Gate out<br>Rail departure<br>Loaded on vessels<br>Barge departure|
|Gate in<br>Rail arrival<br>Discharge from vessel<br>Barge arrival|same|'Actual loaded on vessel'|same|Vessel departure|
|Vessel departure|previous|'Actual vessel arrival'|same|Discharge from vessel|
|Loaded on vessel|same|'Actual vessel departure'|next|Vessel arrival|
|Gate out|previous|'Actual gate in'|same|Gate out<br>Rail departure<br>Loaded on vessel|
|Gate in<br>Discharge from vessel<br>Rail arrival|same|'Actual gate out'|next|Gate in|
|Rail departure|previous|'Actual rail arrival'|same|Gate out<br>Loaded on vessel<br>Barge departure|
|Gate in<br>Discharge from vessel|same|'Actual rail departure'|next|Rail arrival|

17
# **Figure 7: Shares of PW and Annuities**

Shares of PW and Annuities in the number of Normal Old Age Pensions (in %) <!-- Start of picture text --> 80%<br>60%<br>40%<br>20%<br>0%<br>1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007<br>Annuities PW<br>Shares of PW and Annuities in Early Retirement Pensions (in %)<br>120%<br>100%<br>80%<br>60%<br>40%<br>20%<br>0%<br>1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007<br>Annuities PW<br>Shares of Old Age and Early Retirees in the Total Stock of PWs<br>80%<br>60%<br>40%<br>20%<br>0%<br>1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007<br>Old Age Early retiree<br>Shares of Old Age and Early Retirees in the Total number of Annuities<br>80%<br>60%<br>40%<br>20%<br>0%<br>1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007<br>Old Age Early retiree<br><!-- End of picture text --> <!-- Start of picture text --> Source: SP<br><!-- End of picture text --> 17