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Working Paper No. 332: Are New Shopping Centers Drivers of Development in Large Metropolitan Suburbs? The Interplay of Agglomeration and Competition Forces

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Abstract

We investigate to which extent shopping centers drive local economic development by studying how distance to newly established shopping centers affects the performance of incumbent firms, located in the suburbs of the three Swedish major metropolitan areas Stockholm, Gothenburg, and Malmö, 2000-2016. We use a regression setup with around 27,000 firm-year observations and explore the possible heterogeneity imposed on the results from two main elements of spatial economics theory: the size of the new retail area and the distance from the new retail area to the analyzed incumbents. We observe a clear difference in the direction of the effects of large versus small shopping centers. While competition forces are much stronger in the case of the establishment of large shopping centers, yielding a negative 5% on incumbent firm revenue and negative 3% on firm employment, results indicate the opposite pattern for smaller shopping centers; with firm revenue and firm employment increasing 4% and 3%, respectively. Moreover, we also observe that both agglomeration and competition effects attenuate sharply with distance from the new entrant, confirming one of the central premises of retail location theory. Finally, we observe that the geographical scope of the effects is much wider in the case of larger shopping centers, with estimates becoming statistically insignificant at about 9-10 km from the new entry, as compared to 3-4 km in the case of smaller retail centers.

Mihaescu, O., Korpi, M. & Öner, Ö. (2020). Are New Shopping Centers Drivers of Development in Large Metropolitan Suburbs? The Interplay of Agglomeration and Competition Forces. Ratio Working Paper Nr 332. Stockholm: Ratio.

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Author
Mihaescu, O., Korpi, M. & Öner, Ö.
Publication year
2020
Published in

Ratio Working Paper


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Published in

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In this paper, we build upon a monopsony framework, suggested by Card et. al. 2016, which links firm level productivity and rent-sharing to wage inequality. Specifically, our research questions address i) to which extent labor market concentration across firms (within different types of locally situated industries) affects variation in wages among workers within these firms and industries, and ii) how this variation in turn spills over into economy-wide inequality (measured at the level of local labor markets). Using linked employer-employee full population data for Sweden, and an AKM modelling framework to separate between worker- and firm-level heterogeneity, our results suggest that higher firm-level fixed effects (a measure of rent-sharing) is associated with lower labor market employer concentration, something which affects average wage income among firms accordingly. Addressing wage income inequality by applying our model to different segments of the local labor market income distribution, we find that reduced average employer concentration in larger cities accounts for almost all variation in the (positive) link between city size-and wage inequality, except for the largest metropolises where it captures around 30-50 percent of variation depending on the income segment that we focus on.

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Publication year

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Published in

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Abstract

Using geo-coded full-population grid-level data for the three largest metropolitan areas in Sweden, 1993-2016, this paper i) estimates the level and pace of ethnic segregation, ii) examines possible tipping points in this development, and iii) gauges the importance of several mitigating or exacerbating factors (such as the mix of housing area tenure type, different types of amenities, and crime). We use OLS and 2SLS to estimate outcomes at two different geographic levels; 250 x 250 square meter grids and SAMS areas (roughly equivalent to US census tracts), respectively. On average, we find that for every 1 percentage point increase in immigration, native growth is reduced by around -0.3 percentage points. Crime levels exacerbate developments and factors such as housing area tenure-type mix and access to various amenities slows it down, but only marginally so. Using repeated and single random sampling for cross-validation, and the twin common methodological approaches as suggested in the literature, we estimate possible tipping points in these segregation developments. In contrast to most other studies in the literature, none of our potential tipping points are however statistically significant when probing their relevance in explaining factual population developments, suggesting a rather more continuous – albeit steeply so – segregation process rather than a structural brake. In terms of tipping point methodology, our main findings are that fixed-point estimation is less robust than R-square maximization for small geographical units, and that the former consistently selects for lower tipping-point candidates than the latter.

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