The Long-term Relationship Between Economic Development and Regional Inequality: South-West Europe, 1860-2010
by Alfonso Díez-Minguela (Universitat de València); Rafael González-Val (Universidad de Zaragoza, IEB); Julio Martinez-Galarraga (Universitat de València); María Teresa Sanchis (Universitat de València); and Daniel A. Tirado (Universitat de València).
Abstract: This paper analyses the long-term relationship between regional inequality and economic development. Our data set includes information on national and regional per-capita GDP for four countries: France, Italy, Portugal and Spain. Data are compiled on a decadal basis for the period 1860-2010, thus enabling the evolution of regional inequalities throughout the whole process of economic development to be examined. Using parametric and semiparametric regressions, our results confirm the rise and fall of regional inequalities over time, i.e. the existence of an inverted-U curve since the early stages of modern economic growth, as the Williamson hypothesis suggests. We also find evidence that, in recent decades, regional inequalities have been on the rise again. As a result, the long-term relationship between national economic development and spatial inequalities describes an elephant-shaped curve.
Distributed by NEP-HIS on 2018-02-26
Review by: Anna Missiaia
The relationship between economic development and inequality in a broad sense has been at the core of economic research for decades. In particular, the process of industrialization has been much investigated as a driver of inequality: Kuznets (1955) was the first to propose an inverted U-shaped pattern of income inequality driven by the initial forging ahead of the small high-wage industrial sector and a subsequent structural change, with more and more labour force moving out of agriculture into industry. The first to suggest that a similar pattern could take place in the spatial dimension was Williamson (1965), who showed that the process of industrialization could lead to an upswing of regional inequality because of the initial spatial concentration of the industrial sector, which eventually touches the less advanced regions. The paper by Díez-Minguela, González-Val, Martinez-Galarraga, Sanchis and Tirado circulated on NEP-HIS on 2018-02-26 deals with this latter inequality. The authors formally test what is the relationship between the coefficient of variation (in its Williamson formulation) of regional GDP per capita and a set of measures of economic development, most importantly the level of national GDP per capita. The authors use for the analysis four Southwestern European countries (France, Spain, Italy and Portugal). The paper starts in 1860 and therefore takes a much appreciated multi-country and long-run perspective compared to the original work by Williamson, who was looking only at the 20th century United States.
The work by Díez-Minguela and co-authors also relies on the framework developed by Barrios and Strobl (2009), going from a merely descriptive interpretation of an inverted U-shape of regional inequality to a theoretically-founded one. In particular, Barrios and Strobl (2009) use a growth model that takes into account region-specific technological shocks and their later diffusion on the entire national territory; they also include measures of trade openness to test the hypothesis that more market integration leads to more regional inequality; they finally consider regional policies implemented by the State to even out regional disparities. The original paper by Barrios and Strobl (2009) was only considering a sample of countries from 1975 onwards, basically overlooking the whole post-WWII industrial boom in some more developed countries. In this respect, the contribution by Díez-Minguela and coauthors is fundamental, as it proposes a long-run regional analysis not only confined to one specific country as it is customary in the field, but on a group of countries. The paper also proposes a formal testing of the drivers of regional inequality, moving forward from a mere descriptive approach. In terms of methodology, the authors propose an approach that makes use of both parametric and semi-parametric estimations. This is to take into account that the relationship might be different for different levels of GDP.
Moving on to the results, the first thing to note is that three out of four countries in the sample present an inverted U-shaped pattern between GDP per capita and regional inequality (as can be seen in Figure 1).
As for France, the authors suggest that the lack of a U-shaped pattern could be due to its early industrialization that pre-dates the first benchmark year available (1860). The analysis could thus be still capturing the downward part of the U-shape. In terms of the econometric analysis, the OLS regression confirms the predicted pattern through the significance of GDP per capita both in their quadratic and cubic forms.
One interesting discussion is on the controls used in the model: here both openness to trade and public expenditure are not significant, in spite of both being strong candidates for explaining regional inequality in the economic geography literature (see Rodríguez-Pose, 2012 on trade and Rodriguez-Pose and Ezcurra, 2010 on public spending). For the first variable (openness of trade), the explanation could be that the detrimental effect of trade on regional inequality could well have been offset by the increased integration of the financial and labour markets during the First Globalization.
Regarding the second control variable, public intervention (measured as public spending as a share of GDP): the authors admit that having a large public sector does not necessarily imply implementing effective cohesion policies. The example of Fascist Italy on this point is very illustrative: the 1920s and 1930s witnessed rising inequality in Italy, in spite of a growing intervention by the State in the economy and an alleged intent to favor the most backward parts of the country. In general, the impression is that more than one mechanism that is well present in empirical studies after WWII, might not be so in earlier periods. Finally, the authors test for the role of structural change in shaping regional inequality, which was the original explanation by Williamson (1965). This is measured as the non-agricultural value added and it is positive and significant in explaining the coefficient of variation of overall GDP per capita.
Although the paper represents an important step forward for explaining historical regional divergence, several aspects could be addressed in the future by either the authors or by other scholars in the same field. For instance, the use of only four countries from a specific part of Europe does not yet allow drawing general conclusions on the relationship between economic growth and inequality in the long run. As mentioned in the paper, several case studies from other parts of Europe do not entirely fit in the same path: this is the case of Belgium (Buyst, 2011) or Sweden (Enflo and Missiaia, 2018). It is possible that including more advanced economies such as Britain or even some peripheral but Northern ones in the sample might lead to re-consider the increase of regional inequality during modern industrial growth as a golden rule.
Barrios, S., Strobl, E., 2009. “The Dynamics of Regional Inequalities.” Regional Science and Urban Economics 39 (5), 575-591
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Díez Minguela, A., González-Val, R., Martínez-Galarraga, J., Sanchis, M. T., and Tirado, D. 2017. “The Long-term Relationship Between Economic Development and Regional Inequality: South-West Europe, 1860-2010.” EHES Working Papers in Economic History 119
Enflo, K. and Missiaia, A. 2017. “Between Malthus and the Industrial Take-off: Regional Inequality in Sweden, 1571-1850.” Lund Papers in Economic History
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