Spatial inequality and development — Is there an inverted-U relationship?

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract This paper studies the hypothesis of an inverted-U-shaped relationship between spatial inequality and economic development. The theory of Kuznets (1955) and Williamson (1965) suggests that (spatial) inequality first increases in the process of development, then peaks, and then decreases. To test this hypothesis I have used a unique panel data set of spatial inequalities in 55 countries at different stages of economic development, covering the period 1980-2009. Parametric and semiparametric regressions are carried out using cross-section and (unbalanced) panel data. The results provide strong support for the existence of an inverted U, but importantly I also find spatial inequalities to increase again at very high levels of economic development. Although many factors may be contributing to this rise, one explanation rests on the process of tertiarization, i.e., the structural shift from industrial production towards a service base in the highest-developed economies. Terms of use: Documents inJEL-Code: D310, R100, O150.

Regional inequality, convergence, and its determinants – A view from outer space

“…However, those countries that could be called middle-income countries in their respective country groups, such as Namibia or Zambia, have relatively high regional inequalities. This result supports previous evidence of an inverted U-shaped relationship between economic development and regional inequality [see Williamson (1965), Barrios and Strobl (2009), and Lessmann (2014)]. Importantly, our data on the very poorest countries in the world allow us to estimate the upward sloping part of the Kuznets curve in regional inequalities.…”

“…This region will grow faster, and regional inequality will rise, until a convergence process begins that reduces inequality. Empirical evidence for the inverted U hypothesis in regional inequality exists, e.g., Williamson (1965) and Lessmann (2014). Moreover, Lessmann (2014) finds some evidence that regional inequality increases again at very high levels of development in a sample of 56 countries.…”

“…While it is easy to obtain regional data for developed countries through the regional statistics of the OECD and other public sources, doing so becomes difficult if less developed regions of the world are under study. Recent studies by Gennaioli et al (2013Gennaioli et al ( , 2014 and Lessmann (2014) have made great progress in this field providing cross-country data sets for up to 110 countries and panel data for 83 countries and 56 countries, respectively. However, the poorest regions of the world are still blank spots on the map, which limits the informative value of the results to the particular country samples.…”

“…We start with the empirical model by Lessmann (2014), who analyzes the inverted U relationship between regional inequality and development. Using cross-sectional regressions with long period averages, we find support for the inverted U but with increasing inequalities at very high levels of economic development.…”

Regional Growth and Regional Decline

“…More recently, Barrios and Strobl (2009) examine the relationship using data for 12 European countries over 1975-2000. The data plotted in their figure 2 suggest that regional inequality is increasing at lower levels of development, before either levelling off or reducing somewhat, but rarely returning to its initial level. For a much larger set of countries, Lessmann (2011) finds some evidence for the inverse-U relationship over 1980-2009, with regional inequality peaking at a development level close to that of, say, Mexico or the Czech Republic. He also finds some evidence that regional inequality increases at very high levels of GDP per capita (roughly, Canada's level).…”