Marcello Graziano (p), Kevin Meyer, Wendong Zhang, Pengfei Liu

Massimiliano Carlo Pietro Rizzati

Waterborne Escherichia coli (E. coli) represents a pervasive water quality problem across the United States. In the Laurentian Great Lakes basin, the presence of E. coli has become problematic for rural communities, especially in Michigan where agricultural run-off and ineffective policies have made these outbreaks endemic. Combining the universe of housing transaction dataset from 2009 to 2017 with the State of Michigan water sampling dataset, we investigate and quantify the negative impacts of E. coli outbreaks on local housing prices. Based on a hedonic model, we estimate an impact of - 2.9% on housing prices for every mile closer a house is to an E. coli outbreak. We further apply a difference-in-differences model and estimate an overall impact of -2.3% for houses in the treatment group relative to the control group.

Morten Frisch (p), Marina Toger

Marcello Graziano

Mobile Phone Network (MPN) data is an increasingly popular source of Big Data-sets available to social and regional scientists. The potentially rich empirical data promises insights in individual and collective mobility patterns. However, data is usually collected for the purpose of billing network users and not for spatio-temporal analysis. Its suitability as empirical material for studies is therefore not guaranteed. This paper attempts to assess the material's suitability for inequality focused investigations on neighborhood level.

This paper explores the variation and relations between the dynamic populations in Mobile Phone Data and that of static population registry data. By comparing the nighttime population of Mobile Phone users and that of registry data – this paper will explore variations in the over- and undercounting of populations after neighborhood socioeconomic variables. The paper will also engage with the variations of ambient populations in neighborhoods over time. Further, the paper will assess the effects of MAUP in the aggregation of the highly detailed MPN data.

The paper relies on spatial clustering and spatial regression. Particular attention is placed on spatio-temporal clustering techniques. The MPN data used for the paper comes from the MIND-database available at Uppsala University. Similarly, the registry data used in this paper comes from the PLACE-database at Uppsala University.

Paula Ibarra-Silva (p)

Morten Frisch

This research proposes a perspective that integrates neoclassical economy theory, economic geography, and institutional approach to examine the contribution of different approaches to explaining income inequality in Chile. Inequality has been a concern during the late decades and recently the concern has increased due the COVID -19 crisis around the world (Cörvers and Mayhew, 2021). Chile represents a particular/unique case of extreme of income concentration with top income earners capturing a considerable part of all the income (Palma 2014; PNUD 2018). Gonzalez (2020) argues that inequality in Chile is not only economic in scope, but also is extended to the social and political scope and Rodriguez (2017) calculated the gini coefficient on the personal income distribution in Chile from 1850 to 2009, which has varied only between around 0.5 and 0.6 over the last 160 years. Inequality is therefore not a new phenomenon in Chile. Literature on regional inequality has been traditionally focused on regional economy with neoclassical economic theory. In addition, economic geography in the form of the geographical economic predicts the spatial agglomeration of economic activities. Furthermore, the Institutional approach, with institutional economics and new institutionalism, have the main premise that “institutions matter” for economic development. Each of these perspectives offers an explanation for regional disparities that could potentially be applied to the Chilean case. The objective of the proposed research is to estimate the extent to which regions differ in income in Chile and evaluate the ability of economic, geographical and institutional approaches to explain the observed differences.
Empirical studies about regional inequality have been developed mainly for European countries and north America mainly at national level, and little research at regional level. In addition, empirical work in the Latin American context is limited and mainly at national level. For the Chilean case, research about inequality has tended to focus on national level rather than at regional and less attention has been paid to consider different approaches.

Silvia María Franco Anaya (p)

Paula Ibarra-Silva

The increasing concentration of wealth is becoming an increasingly important issue in inequality analysis. The importance of including wealth in household inequality analysis is gaining attention. However, there are currently no datasets that provide the necessary level of geographical detail to analyze differences across European regions. This paper aims to fill this gap by analyzing European households. The applied methodology estimates asset poverty indicators across European regions by combining the Household Finance and Consumption Survey (HFCS) conducted by the ECB, national central banks of the Eurosystem, and national statistical institutes, and the European Living Conditions Survey (EUSILC) conducted by Eurostat. The key variable of interest is only present in the HFCS, while in the EUSILC, the same independent variables used in the HFCS are included with the advantage of being disaggregated by region. The main advantages of the proposed technique are its consistency with national aggregates and the fact that it does not require strong distributional assumptions. As a result, we will develop an analysis of regional heterogeneity in the distribution of wealth among European households. The results from this estimation will improve our understanding of inequality in Europe, providing data to analyze the extent of social convergence, the degree of heterogeneity in wealth distribution across European regions, the evaluation and control of public policies, among other things.

Massimiliano Carlo Pietro Rizzati (p)

Silvia María Franco Anaya

Abstract Economic Geography studies the formation and the evolution of economic spatial inequality. This study wants to enrich this literature by investigating the case of heterogeneous agents operating under bounded rationality in complex spatial structures. To achieve this, I propose a flexible macroeconomic Agent-based model endowed with Households and Firms interacting on a given spatial network. The agents’ decision heuristics embed and reproduce the features usually employed in mainstream Economic Geography models, as relocation, migration, trade and transportation costs. This permits to evaluate and compare the predictions of Economic geography into a disequilibrium bounded rationality setting, to check the emergence and stability of agglomerated configurations by the economic agents, and to test policies, such as the variation of the transportation costs. The flexibility of the spatial structure, which consists in a network of locations provided in the initial calibration of the model, allows to check these results on a wide variety of spatial environments, including realistic ones. I test different relocation protocols for the agents, as well as different spatial maps, and perform experiments on different Transportation costs level. I find that the spatial configuration assumed by the model is deeply influenced by the chosen relocation metric and by the chosen spatial network. Usual New Economic Geography patterns of agglomeration might emerge, but seems to results from different mechanisms.