Duc Nguyen (p)

Attila Varga

This paper uses the synthetic control method to construct comparison units for West-German cities. We use these as counterfactuals to assess the long-run impact of the WWII bombings on the economic activity of 52 West-German cities, and the West-German city size distribution. We extend the literature in that we do not only look for whether cities following the WWII bombing shock are mean-reverting or not, but the use of counterfactuals allows us to distinguish whether individual cities experienced a positive or negative impact as well. We find a permanent impact on the majority of cities, where the ratio of positive to negative impact cities is around 5 to 6. Also higher populated metropolitan cities before WWII tend to either return or be positive impact cities, while negative impact cities mostly consist of lower populated places with the exception of Berlin. We also find a non-random decline of the majority of counterfactual cities around the 1960s. Overall, our findings support a hybrid theory, where the determinants of a city’s size are underlying mutable locational fundamentals, and increasing returns.

Nora Schindler (p), Biliana Yontcheva, Dieter Pennerstorfer, Christoph Weiss

Attila Varga

Many Western economies have experienced significant changes in the distribution of personal incomes over the last decades. The rising income inequality in the U.S. and in some European countries has attracted public, political and scholarly attention. A large empirical and theoretical literature relates income distribution and inequality to a number of social and economic outcomes (such as economic growth, international trade, well-being, health, criminality, education, to mention a few dimensions only). This project aims at studying a type of interaction between income inequality and market outcomes that has not yet been explored extensively: the effects of different degrees of income inequality on firms' behaviour in imperfectly competitive product markets.

The analysis is motivated by the following simple argument. Since rich and poor consumers buy different consumer goods in different amounts, the initial degree of income inequality influences the size of market demand and/or its elasticity and hence the intensity of competition, entry and product differentiation strategies. Income inequality entails heterogeneity in consumer preferences, and product differentiation is the market response to this heterogeneity.

The empirical analysis is carried out for an important non-tradeable consumption amenity: restaurants. The market for restaurants is particularly well-suited to the aims of the proposed project.
Firstly, different dimensions of product differentiation are relevant in this market and are significant in the consumers' decision to eat out in a restaurant: the quality of restaurants (measured by consumer ratings and/or expert reviews), the variety of restaurants (i.e. different cuisines), as well as the geographical location of restaurants. Within this paper we will focus our empirical analysis on the horizontal product differentiation. Secondly, the different dimensions of product differentiation in this market are easily measured. Conveniently, there exists a wealth of information about restaurants on the Internet, including quality indicators, cuisine types as well as precise address information which allows accurate geographic matching of restaurants to demographic data. Thirdly, consumer heterogeneity is important in this market, since consumer demand for specific cuisines will differ between rich and poor consumers. The availability of detailed information on the spatial distribution of population, income and income inequality allows an empirical identification of the impact of income inequality on consumer demand and firm conduct (product differentiation). And finally, the restaurant market represents a good case for investigating the hierarchical structure of demand: we expect to find a relationship between the number of varieties and the composition of those varieties.

Lorenz Benedikt Fischer (p)

Attila Varga

Many questions in urban and regional economics can be characterized as including both a spatial and a time dimension. However, often one of these dimensions is neglected in empirical work. This paper highlights the dangers of methodological inertia, investigating the effect of neglecting the spatial or the time dimension when in fact both are important. A tale of two research teams, one living in a purely dynamic and the other in a purely spatial world of thinking, sets the scene. Because the researcher teams' choices to omit a dimension change the assumed optimal estimation strategies, the issue is more difficult to analyze than a typical omitted variables problem. First, the bias of omitting a relevant dimension is approximated analytically. Second, Monte Carlo simulations show that the neglected dimension projects onto the other, with potentially disastrous results. Interestingly, dynamic models are bound to overestimate autoregressive behavior whenever the spatial dimension is important. The same holds true for the opposite case.

Zofia Bednarowska-Michaiel (p)

Attila Varga

Mobilities is one of the social reasons for spatial inequalities and spatial segregation. It is generally recognized in regional research. Economic or urban studies conceptualize the mobilities similarly to this paradigm but do not recognize the full complexity of mobilities. In the new mobilities paradigm (Sheller and Urry 2006) understanding mobilities are more than just a transportation, commuting infrastructure, but also looking from perspective of people’s uneven mobilities potential – motility. Motility is the ability to be mobile in social and geographical understanding of movement, and the notion links spatial and social mobility (Kaufmann, Joye, and Bergman 2004:750).
Transportation mode is related to class and race but also motility is greatly affected by race and class. People of color and immigrants cycle less (Manville, Taylor, and Blumenberg 2018:26; Transport for London 2011).
Spatial racism in mobilities is researched here using a spatial model of London as a case study, as the previous model proved mobilities to contribute to regional development (Bednarowska, 2018). The main method is spatial econometrics with the Durbin component (Elhorst 2010; LeSage and Pace 2009). This way I aim to recognize intersectionality of mobilities injustice and spatial discrimination.