This paper considers the most important aspects of model uncertainty for spatial regression models, namely the appropriate spatial weight matrix to be employed and the appropriate explanatory vari- ables. We focus on the spatial Durbin model (SDM) specification in this study that nests most models used in the regional growth literature, and develop a simple Bayesian model averaging approach that provides a unified and formal treatment of these aspects of model uncertainty for SDM growth models. The approach expands on the work by LeSage and Fischer (2008) by reducing the computational costs through the use of Bayesian information criterion model weights and a matrix exponential specification of the SDM model. The spatial Durbin matrix exponential model has theoretical and computational advantages over the spatial autoregressive specification due to the ease of inversion, differentiation and integration of the matrix expo- nential. In particular, the matrix exponential has a simple matrix determinant which vanishes for the case of a spatial weight matrix with a trace of zero (LeSage and Pace 2007). This allows for a larger domain of spatial growth regression models to be analysed with this approach, including models based on different classes of spatial weight matrices. The working of the approach is illustrated for the case of 32 potential determinants and three classes of spatial weight matrices (contiguity-based, k-nearest neighbor and distance-based spatial weight matrices), using a dataset of income per capita growth for 273 European regions. (authors' abstract)

This paper presents a theoretical growth model that accounts for technological interdependence among regions in a Mankiw-Romer-Weil world. The reasoning behind the theoretical work is that technological ideas cannot be fully appropriated by investors and these ideas may diffuse and increase the productivity of other firms. We link the diffusion of ideas to spatial proximity and allow for ideas to flow to nearby regional economies. Through the magic of solving for the reduced form of the theoretical model and the magic of spatial autoregressive processes, the simple dependence on a small number of neighbouring regions leads to a reduced form theoretical model and an associated empirical model where changes in a single region can potentially impact all other regions. This implies that conventional regression interpretations of the parameter estimates would be wrong. The proper way to interpret the model has to rely on matrices of partial derivatives of the dependent variable with respect to changes in the Mankiw-Romer-Weil variables, using scalar summary measures for reporting the estimates of the marginal impacts from the model. The summary impact measure estimates indicate that technological interdependence among European regions works through physical rather than human capital externalities. (author's abstract) / Series: Working Papers in Regional Science

Spatial interaction models represent a class of models that are used for modeling origin destination flow data. The interest in such models is motivated by the need to understand and explain the flows of tangible entities such as persons or commodities or intangible ones such as capital, information or knowledge between regions. The focus here is on the log-normal version of the model. In this context, we consider spatial econometric specifications that can be used to accommodate two types of dependence scenarios, one involving endogenous interaction and the other exogenous interaction. These model specifications replace the conventional assumption of independence between origin-destination-flows with formal approaches that allow for two different types of spatial dependence in flow magnitudes. (authors' abstract) / Series: Working Papers in Regional Science

Studies conducted for the US have found a positive effect of human capital endowments on employment growth, with human capital endowments diverging at the same time. In contrast, studies for European countries have found convergence of human capital endowments. This paper tests these relationships for 99 Austrian districts for the observation period 1971-2011 by estimating how the presence of high-skilled employment affects total, low-skilled and high-skilled employment growth. To this end, OLS, fixed effects and first difference regressions are estimated. The results show continuous convergence of high-skilled employment which, however, slowed downed significantly since the 1990s. In contrast to previous studies, evidence for positive effects of high-skilled on total and low-skilled employment is only weak and varies over time. Furthermore, the results show that total and high-skilled employment in suburban areas grew faster than in other regions, while districts which bordered the Eastern Bloc were disadvantaged. Nevertheless, spatial neighbourhood effects within Austria are only weak. (authors' abstract) / Series: Working Papers in Regional Science

The present paper provides first microlevel (indirect) empirical evidence on changes in the determinants of firm profitability, the role of fixed and sunk costs, as well as the nature of competition for a transition economy. We estimate size thresholds required to support different numbers of firms for four retail and professional service industries in a large number of geographic markets in Slovakia. The three time periods in the analysis (1995, 2001 and 2010) characterize different stages of the transition process. Specific emphasis is given to spatial spill-over effects between local markets. Estimation results obtained from a spatial ordered probit model suggest that entry barriers have declined considerably (except for restaurants) and the intensity of competition has increased. We further find that demand spill-overs and/or the effects associated with a positive correlation in unobservable explanatory variables seem to outweigh negative spill-over effects caused by competitive forces between neighboring cities and villages. The importance of these spatial spill-over effects differs across industries. / Series: Department of Economics Working Paper Series

In this paper we analyse regional growth in Central and Eastern Europe in the second half of the 1990s, a period in which pronounced disparities between a group of catching-up regions and another group of falling back regions appeared. We aim to identify the factors behind a dynamic growth performance and the weaknesses leading to poor growth and thus investigate the role of (foreign) investment, education and innovation as well as geographical factors in a model of economic growth. The key relationships proposed by this model are then estimated with empirical data for the period 1995-2000 using spatial econometric tools. We find that foreign direct investment was paramount for regional growth in that period. EU border regions and capital areas clearly outperformed others. Further, regional growth clusters have appeared. Surprisingly, the high level of secondary education in Eastern European regions played no role with growth. Higher education, in contrast served to facilitate technology transfer. (author's abstract) / Series: EI Working Papers / Europainstitut

Spatial interaction models of the gravity type are used in conjunction with sample data on flows between origin and destination locations to analyse international and interregional trade, commodity, migration and commuting patterns. The focus is on the classical log-normal model version and spatial econometric extensions that have recently appeared in the literature. These new models replace the conventional assumption of independence between origin-destination flows with formal approaches that allow for spatial dependence in flow magnitudes. The paper also discusses problems that arise in applied practice when estimating (log-normal) spatial interaction models. (authors' abstract)

This paper adopts a spatial econometric perspective to analyse regional convergence of per capita income in Europe in 1995 to 2000 and, moreover, relaxes the assumption of a single steady-state growth path which appears to be out of tune with reality of empirical dynamics. The two-club spatial error convergence model with groupwise heteroskedasticity is found to be most appropriate for the data at hand. Two empirical key findings are worthwhile to note. The first is that the data provide much support for unconditional ß-convergence in Europe. The second is that the usual convergence conclusions hold. But they do so for reasons that are not revealed by the classical test equation that is typical in mainstream economics literature. (authors' abstract)

The present article provides first microlevel (indirect) empirical evidence on changes in entry barriers, the determinants of firm profitability as well as the nature of competition for a transition economy. We estimate size thresholds required to support different numbers of firms for several retail and professional service industries in a large number of geographic markets in Slovakia. The 3 time periods in the analysis (1995, 2001 and 2010) characterize different stages of the transition process. Specific emphasis is given to spatial spill-over effects between local markets. Estimation results obtained from a spatial ordered probit model suggest that entry barriers have declined considerably (except for restaurants) and that the intensity of competition has increased on average. We further find that demand spill-overs and/or the effects associated with a positive correlation in unobservable explanatory variables seem to outweigh negative spill-over effects caused by competitive forces between neighbouring cities and villages. The importance of these spatial spill-over effects differs across industries.

This study investigates whether there is a link between the successful implementation of European cohesion policy and the voters' attitudes towards the EU. Using the French presidential elections in 2017 as a case study, we do not solely consider regional funds expenditures but also its induced effects in a region as further potential determinant of pro-European or eurosceptic voting behavior. In order to measure the effectiveness of EU structural funds and Cohesion Fund assignment, firm-level employment effects in French NUTS-2 regions stemming from project allocation during the multi-annual financial framework 2007-2013 are estimated. The obtained average treatment effects are, in a next step, used together with other regional characteristics to capture the citizens' perceived exposure to the EU in an empirical voting model for the French presidential election in 2017. The estimation results reveal a significant negative relationship between the effectiveness of EU funds allocation and the vote share of the eurosceptic candidate Marine Le Pen. / Series: Department of Economics Working Paper Series