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Despite the vast research about discrimination, there is little evidence about how space interacts with it. Our main hypothesis is that a discriminated group could have incentives to stay together, even if the location is less dynamic—avoiding areas where firms do not usually hire workers of their group. A virtuous and/or vicious circle emerges for each group, even in the long run. Using USA as an example, this article introduces a theoretical economic model to explain the incentives of ethnic groups in terms of location. We extend the well-known model of discrimination with imperfect information to a spatial framework. The results seem to indicate that the initial population distribution and the barriers to agglomerate activity (transport costs), as well as the behavior of employees, are key elements to determine the equilibrium. As a general conclusion, discrimination processes could clearly modify the location pattern of the population. Hence, the discriminated group could suffer from lower incentives to move from non-agglomerated areas to dynamic areas. These processes could help to explain why some populations prefer to maintain their traditional location in poor areas even if there are places with higher wages or better quality of life. [ABSTRACT FROM AUTHOR]

Difference in terms of cost-of-living between rural and urban areas is a frequent theoretical analysis in Regional Economics. Lack of routine measures in rural areas does not usually allow to observe changes in rural costs. We adapt the Big Mac index, typically used to measure purchasing power parity between countries, as a potential quick and inexpensive indicator of short-term local price variations. With a national random sample of McDonald's stores repeated in time, we find prices grew slightly faster in rural areas than in urban areas. Spatial transmission of prices seems to be limited to very localized effects, meaning that rural price increases are not due to urban spillover effects. [ABSTRACT FROM AUTHOR]

The extensive literature on economic convergence has explored a wide variety of ways of measuring convergence in addition to finely tuning and improving the applicable econometric techniques. However, very few contributions analyze the relevance of the spatial level of analysis. Our hypothesis is that studying the convergence at the level of large regions (states) could conceal intraregional heterogeneity. This hypothesis is consistent with the New Economic Geography framework, which highlighted core-periphery patterns at the local level. However, this polarization mechanism may become difficult to identify with aggregated data or neoclassical dynamics operating at the same time. This paper proposes a multilevel approach to study this question. It allows the identification of possible heterogeneous local patterns of behavior within regions. It is applied to the US economy in a hierarchy of two levels: states and counties. The results show high intraclass correlation, indicating significant variance within states. An overall pattern of convergence is observed in line with previous results, although some states present internal patterns of divergence or significant changes in the rate of convergence. [ABSTRACT FROM AUTHOR]

The concentration of economic activity across space is a stylized fact of the literature in regional and urban economics. In the case of the United States (US), only 35 counties at the top of the distribution, out of a total of 3,138, generate more than one third of the country's total personal income. Furthermore, US urban structure follows Zipf's law. Under these conditions of concentration, we should presumably find some kind of granular hypothesis as suggested by Gabaix (Econometrica 79(3):733-772, ). This hypothesis means that the idiosyncratic behavior of the large units should be capable of explaining a significant part of the aggregate shocks. Gabaix found evidence to corroborate this hypothesis for firms: the idiosyncratic movements of the 100 largest firms in the US appear to explain about one third of the variations in output growth. In this paper we analyze whether this behavior is present in the case of urban concentration, as can be expected taking into account the degree of spatial concentration in the economy. We use data from the Bureau of Economic Analysis on personal income, which is disaggregated at a local level, US counties, from 1969 to 2011. The granular residual of the largest cities is calculated and used to explain the US aggregate economic evolution. The overall results provide support for the granular hypothesis: the idiosyncratic shocks to the top counties can explain a significant fraction of the volatility of US aggregate data. [ABSTRACT FROM AUTHOR]