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Regional Inequality in Latin America: Does It Mirror the European Pattern?

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Time and Space

Abstract

The aim of this chapter is to analyse the comparative evolution of regional inequality over the course of the historical economic development processes in four countries of South West Europe—France, Italy, Portugal and Spain—and nine countries of Latin America: Argentina, Bolivia, Brazil, Chile, Colombia, Mexico, Peru, Uruguay and Venezuela. Our analysis, which goes back to the nineteenth century, shows that regional income inequality has followed over time what appears now to be an N-shaped evolution in both regions. However, both experiences differ markedly and we identify the main stylized facts of these trajectories. First, Latin America begun the period with higher levels of regional inequality than Europe. Second, the increase in inequality up to the interwar years was more intense in Latin America than in Europe. Besides, the increasing disparities in Europe in this initial period were based on the high territorial concentration of industry while in Latin America inequality mainly grew responding to the specific geography of the natural resources. Third, both regions underwent a period of convergence between the aftermath of the World War II and the crisis of the 1970s, being the process more intense in the European case. In Europe, the spread of industrialization and structural change to a growing number of regions was determinant in the decrease in inequality. In the case of Latin America, however, it was the marked change in economic policy—import substitution industrialization—that constituted the driving force behind the regional convergence. Finally, the crisis of the 1970s and changes in the international political and economic consensus in the 1980s signalled the beginning of a new stage in the evolution of inequality. A context of increasing international economic integration brought to a halt the narrowing of the gap between richer and poorer regions, but in a lower degree in Europe compared to Latin America. In this case, the liberalism typical of the 1980s, as enshrined in the Washington Consensus, favoured reinsertion into the international goods and factor markets and led to the unequal growth of those regions best endowed with resources.

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Notes

  1. 1.

    World Bank (2009).

  2. 2.

    One example of the media’s interest in the spread of territorial inequality and its possible political implications is the in-depth report published in The Economist (2016). As for institutional interest, EUROSTAT produces an annual report on the problems associated with the issue: the European Regional Yearbook.

  3. 3.

    Barrios and Strobl (2009) also supply an economic basis for the relative growth dynamics identified by the literature on the technology gap and catch-up (Abramovitz 1994).

  4. 4.

    Similar results have also been found by Lessmann and Seidel (2017).

  5. 5.

    Our data set on regional GDP per capita borrows from previous research. For France, we obtained data from Combes et al. (2011), Díez-Minguela and Sanchis (2019) and Rosés and Sanchis (2019); the data for Italy came from Felice (2011, 2015), for Portugal, from Badia-Miró et al. (2012), and for Spain, from Martinez-Galarraga et al. (2015) and Tirado et al. (2016). We are grateful to Marc Badia-Miró, Emanuele Felice, Jordi Guilera, Pedro Lains and Joan R. Rosés for sharing unpublished data with us.

  6. 6.

    Over the years, South West Europe has come to be considered an economic area in its own right insofar as it is taken into account as such in current EU development policy and in historical works such as the Cambridge Economic History of Modern Europe (Broadberry and O’Rourke 2010). From a comparative perspective, the detailed study of this macroregion has two advantages as far as this chapter is concerned: first, the Latin character of these countries should enable us to achieve greater institutional proximity between them and the Latin American sample; and second, with the exception of France, the time it took before the region started on the path of economic development means that the evidence presented here, like in the case of Latin America, covers most of the time frame of the process.

  7. 7.

    For Spain, the sample covers all reference time points. Because of limitations in the estimates, the number of time points available for the other countries is lower. For Italy, there are no data for 1860 prior to unification, for Portugal the estimates do not begin until 1890, and for France the two decades between 1870 and 1890 are missing, as is 1940, during the World War II.

  8. 8.

    Figures for per capita GDP in 1990 Geary-Khamis US$ for France, Italy, Portugal and Spain are from the Maddison Project Database (Bolt and Van Zanden 2014). Figures for national population for 1860–1990 are from the original Maddison database, and for 1990–2010 from the Total Economy Database.

  9. 9.

    To account for price differences, EUROSTAT created the purchasing power standard (PPS). This is calculated by comparing the prices of a representative basket of goods and services across countries. It does not, however, account for within-country price dispersion, which means that the price levels used for Spain and all its regions are those of the capital city/region of Madrid.

  10. 10.

    Our data set on regional GDP per capita borrows from research presented by various authors in this volume. For Argentina we use data from Araoz et al. (2020), for Bolivia data from Peres-Cajias (2020), for Brazil data from Bucciferro and Ferreira da Souza (2020), for Chile data from Badia-Miró (2020), for Colombia data from Meisel and Hahn de Castro (2020), for Mexico data from Aguilar-Retureta et al. (2020), for Peru data from Seminario et al. (2020), for Uruguay data from Martinez-Galarraga et al. (2020) and for Venezuela data from de Corso and Tirado-Fabregat (2020). We are extremely grateful to all these authors for sharing their research with us.

  11. 11.

    GDP per capita for Argentina, Bolivia, Brazil, Chile, Colombia, Mexico, Peru, Uruguay and Venezuela in 1990 Geary-Khamis US$ were also retrieved from the Maddison Project Database (Bolt and Van Zanden 2014).

  12. 12.

    See the chapter on methodology (Díez-Minguela and Sanchis 2020) for details regarding the size of the regions considered in the case of each country included in this volume.

  13. 13.

    See Williamson (1965), Ezcurra and Rapún (2006), Rodríguez-Pose (2012) and Lessmann (2014). The use of a weighted index is particularly suitable in the case of Latin America given the huge differences in size between regions in different countries.

  14. 14.

    Estimates for regional GDP (at current prices) for 1920 could have an upward bias because of World War I’s impact on prices.

  15. 15.

    The region also recorded high levels of personal inequality. Territorial inequality can therefore be seen as another historical dimension of a characteristic typical of this group of countries.

  16. 16.

    In the case of Argentina, the trend continues upwards until 1980.

  17. 17.

    This is a standard measurement used in the empirical literature to capture trade openness (Frankel and Rose 2002), although some authors have proposed alternative indicators (Alcalá and Ciccone 2004; Hirte and Lessmann 2014). The data on trade openness ratios are taken from Federico and Tena-Junguito (2016).

  18. 18.

    The number of observations in this case falls to 85 given the lack of available data for calculating the openness rate for Bolivia.

  19. 19.

    To be more specific, the estimated coefficients would mean that inequality would on average increase up to a GDP per capita level of 1074 US$ and then decrease until a GDP per capita level of 15,367 US$ is reached, after which it would rise again. These values are consistent with the income levels at which maximum and minimum levels of inequality are reached in various countries of the sample (Fig. 6.2).

  20. 20.

    The analysis of Latin American countries does not include other economic control variables such as the Krugman specialization index or the government expenditure/GDP ratio because it was not possible to construct them for all the countries and all the reference time points that make up the sample. This is why it makes more sense to consider the inclusion of a dummy variable to capture any differential effect associated with the country.

  21. 21.

    One explanation for this could be that, as Hirte and Lessmann (2014) point out, since globalization involves the integration of the goods, capital and labour markets, the effects of increasing international integration in the capital and labour markets might perhaps be compensating for any cost in terms of regional inequality caused by the growth in trade. It should also be considered that the effects of increased integration on territorial inequality are not analysed in this exercise. In other words, the picture given of the possible relationship between both variables is static and non-dynamic.

  22. 22.

    A parallel to this evolution can be found in the dynamic of interpersonal income inequality, which has also increased since the late 1970s (Milanovic 2016; Atkinson et al. 2011). Gluschenko (2017) shows how the weighted indexes of territorial inequality widely used in the literature—such as the Williamson index—approximate the interpersonal inequality of the whole population.

  23. 23.

    Empirical tests that prove the existence of this relationship can be found in Rodríguez-Pose (2012), Rodríguez-Pose and Gill (2006), Ezcurra and Rodríguez-Pose (2014) and Hirte and Lessmann (2014). An exception is Milanovic (2005), who analyses the five most populated countries in the world (Brazils, China, India, Indonesia and the United States) from approximately 1980 to 2000 and finds no link between trade openness and regional inequality.

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Martinez-Galarraga, J., Nicolini, E.A., Tirado-Fabregat, D.A., Willebald, H. (2020). Regional Inequality in Latin America: Does It Mirror the European Pattern?. In: Tirado-Fabregat, D.A., Badia-Miró, M., Willebald, H. (eds) Time and Space. Palgrave Studies in Economic History. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-47553-6_14

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