Spatial Economics of Income Distribution Across Borders: Drivers of Spatial Inequalities using Microsimulation

Luxembourg lies at the heart of a relatively seamless cross-border region. There effectively is a single labour market. There are, however, different national policy regimes and different rules in relation to how these policy regimes interact in impacting upon the distribution of income. There are also different housing markets within the cross-border region and differential costs of living which impact upon the standard of living. As a commuting region, transport costs are also important determinants of the standard of living. The EUROMOD microsimulation framework has been innovative in relation to cross-country comparisons in the relatively simple case where workers live and work in the same country. However as the single market has deepened and as cross-border commuting grows, it has become increasingly important to consider in more detail these interactions. Similarly as housing and other non-discretionary expenditures such as commuting costs have often grown at a different rate to the growth of earnings, it is important to consider distributional analysis at the relevant spatial scale that these markets operate. While EUROMOD has in the past considered the regional dimension at the NUTS II level, incorporating differential housing markets and commuting zones requires a finer level of spatial disaggregation. Microsimulation models become geographical when spatial information about the simulated entities is available (or estimated). Spatial microsimulation involves the creation of large-scale population microdata sets and the analysis of the impacts of any policy changes, which change the attributes contained in these micro databases in some way (Ballas et al 2005). Adding spatial detail to traditional microsimulation involves creating geographically-referenced microdata that refers to a particular locality. Since there are very few sources of geographically detailed microdata, there is a need to create these data using spatial microsimulation techniques by merging census and survey data to simulate a population of individuals within households (for different geographical units) whose characteristics are as close to the real population as it is possible to estimate (O'Donoghue et al., 2012). We therefore propose an innovation in two dimensions (i) considering the situation of cross-border workers in a cross-national comparison of incomes and (ii) downscaling the geographical unit of analysis to a finer spatial resolution of at least NUTS IV. In order to do this, we develop a spatial microsimulation model of the cross-border region, building upon EUROMOD and to incorporate cross-border tax and social security rules into the framework to assess the true impact of cross-border regulations on the standard of living. Very little has been done to understand the economic footprint of countries such as Luxembourg into outside commuting zones (cross-border regions). Building on our core capacities in microsimulation and distributional tools, we propose an innovative distributional approach for investigating the spatial economics of income distribution in the Luxembourg-centred cross-border area. The approach relies on combining census data, with EU-SILC and with an income generation model which incorporates the complexity of the tax-benefit rules of four systems (Luxembourg, Germany, Belgium and France) via the EUROMOD microsimulation model. We seek to pin down the role of demographics, labour market factors, returns, housing costs, commuting patterns and tax-benefit rules in explaining inter-regional differences in disposable income inequality. A special focus will be dedicated to understanding to what extent the policy difference increase or decrease the incentives for freedom of movement.