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on Economic Geography |
| By: | Wolfgang Polasek (IHS (Austria); Rimini Centre for Economic Analysis (Italy)); Wolfgang Schwarzbauer (IHS (Austria)); Richard Sellner (IHS (Austria)) |
| Abstract: | Economists expect positive returns to investments in infrastructure. However a project with higher national returns might have less favorable eects on a regional level than the alternative. Therefore new infrastruc- ture should also be assessed on a regional level, but econom(etr)ic evalua- tion models are scarce, especially in regional science. This paper proposes new approaches to evaluate infrastructure by a dynamic spatial economet- ric model that allows long-term predictions. We investigate the regional eects for 2 Austrian railway projects and show that infrastructure returns are positive on an aggregate and at a regional level but spatial variation can be large. |
| Keywords: | Regional growth convergence, trac accessibility, infrastruc- ture evaluation, spatial econometrics |
| JEL: | C31 H43 H54 R11 R12 |
| Date: | 2009–01 |
| URL: | http://d.repec.org/n?u=RePEc:rim:rimwps:09-09&r=geo |
| By: | Roberto Patuelli (University of Lugano, Switzerland The Rimini Centre for Economic Analysis, Rimini, Italy); Daniel A. Griffith (University of Texas at Dallas, USA); Michael Tiefelsdorf (University of Texas at Dallas, USA); Peter Nijkamp (VU University Amsterdam, The Netherlands) |
| Abstract: | Regions, independent of their geographic level of aggregation, are known to be interrelated partly due to their relative locations. Similar economic performance among regions can be attributed to proximity. Consequently, a proper understanding, and accounting, of spatial liaisons is needed in order to effectively forecast regional economic variables. Several spatial econometric techniques are available in the literature, which deal with the spatial autocorrelation in geographically-referenced data. The experiments carried out in this paper are concerned with the analysis of the spatial autocorrelation observed for unemployment rates in 439 NUTS-3 German districts. We employ a semi-parametric approach – spatial filtering – in order to uncover spatial patterns that are consistently significant over time. We first provide a brief overview of the spatial filtering method and illustrate the data set. Subsequently, we describe the empirical application carried out: that is, the spatial filtering analysis of regional unemployment rates in Germany. Furthermore, we exploit the resulting spatial filter as an explanatory variable in a panel modelling framework. Additional explanatory variables, such as average daily wages, are used in concurrence with the spatial filter. Our experiments show that the computed spatial filters account for most of the residual spatial autocorrelation in the data. |
| Keywords: | spatial filtering, eigenvectors, Germany, unemployment |
| JEL: | C33 E24 R12 |
| Date: | 2009–01 |
| URL: | http://d.repec.org/n?u=RePEc:rim:rimwps:02-09&r=geo |
| By: | Chiara DEL BO; Massimo FLORIO |
| Abstract: | In this paper we examine the return of public investment in the EU regions. We consider different forms of infrastructure capital by examining the relationship between a set of infrastructure indicators and economic performance at the NUTS2 level with an empirical model derived from the production-function approach. From a social planner’s perspective, we want to see which form of infrastructure investment has higher returns, considering structural differences in regions. The main contribution of this paper is to consider the impact of different types of infrastructure on growth, disaggregated at the regional level in the European Union, with an explicit focus on the New Member States, and correcting for spatial dependence and heterogeneity issues. We find that the highest rates of return are associated mainly with TLC, quality and accessibility of the region’s transportation network, while endowment of traditional road and railway infrastructure has a positive but slightly lower impact. We also contribute to the debate on convergence, finding that the β-convergence hypothesis holds also when the model encompasses several controls. |
| Keywords: | Infrastructure capital, regional growth, convergence, spatial econometrics. |
| JEL: | H54 O11 E62 R11 |
| Date: | 2008–11–21 |
| URL: | http://d.repec.org/n?u=RePEc:mil:wpdepa:2008-37&r=geo |
| By: | Stephen J. Redding |
| Abstract: | Although a rich and extensive body of theoretical research on new economic geography hasemerged, empirical research remains comparatively less well developed. This paper reviewsthe existing empirical literature on the predictions of new economic geography models for thedistribution of income and production across space. The discussion highlights connectionswith other research in regional and urban economics, identification issues, potentialalternative explanations and possible areas for further research. |
| Keywords: | New economic geography, market access, industrial location, multiple equilibria |
| JEL: | F12 F14 O10 |
| Date: | 2009–04 |
| URL: | http://d.repec.org/n?u=RePEc:cep:cepdps:dp0925&r=geo |
| By: | González-Val, Rafael |
| Abstract: | This paper analyses the determinants of growth of American cities, understood as growth of the population or per capita income, from 1990 to 2000. This empirical analysis uses data from all cities with no size restriction (our sample contains data for 21,655 cities). The results show that while population growth in cities appears to be independent of initial size, the growth of city per capita income is negatively correlated to initial per capita income: the richest cities grew less in this period. To try to explain these differentiated behaviors, we examine the relationship between urban characteristics in 1990 and city growth (both in population and in per capita income) using a Multinomial Logit Model. The geographical situation of cities seems to play a key role in their growth. |
| Keywords: | City growth; Multinomial logit |
| JEL: | R00 R12 R11 |
| Date: | 2009–06–09 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:15636&r=geo |
| By: | Carlos Llano (Universidad Autonoma de Madrid, Spain The Rimini Centre for Economic Analysis, Rimini, Italy); Wolfgang Polasek (Institute for Advanced Studies, Vienna, Austria and The Rimini Centre for Economic Analysis, Italy); Richard Sellner (Institute for Advanced Studies, Vienna, Austria) |
| Abstract: | Completing data sets that are collected in heterogeneous units is a quite frequent problem. Chow and Lin (1971) were the rst to develop a unied framework for the three problems (interpolation, extrapolation and distribution) of predicting times series by related series (the `indicators'). This paper develops a spatial Chow-Lin procedure for cross-sectional and panel data and compares the classical and Bayesian estimation methods. We outline the error covariance structure in a spatial context and derive the BLUE for the ML and Bayesian MCMC estimation. Finally, we apply the procedure to Spanish regional GDP data between 2000-2004. We assume that only NUTS-2 GDP is known and predict GDP at NUTS-3 level by using socio-economic and spatial information available at NUTS-3. The spatial neighborhood is dened by either km distance, travel time, contiguity and trade relationships. After running some sensitivity analysis, we present the forecast accuracy criteria comparing the predicted values with the observed ones. |
| Keywords: | Interpolation, Spatial panel econometrics, MCMC, Spatial |
| Date: | 2009–01 |
| URL: | http://d.repec.org/n?u=RePEc:rim:rimwps:05-09&r=geo |
| By: | Ron Boschma; Koen Frenken |
| Abstract: | We propose an evolutionary perspective on the geography of network formation that is grounded in a dynamic proximity framework. In doing so, we root the proximity concept in an evolutionary approach to the geography of innovation networks. We discuss three topics. The first topic focuses on explaining the structure of networks. The second topic concentrates on explaining the effects of networks on the performance of actors. The third topic deals with the changing role of proximity dimensions in the formation and performance of innovation networks in the longer run. |
| Keywords: | evolutionary economic geography, knowledge networks, innovation networks, dynamic proximity |
| JEL: | R0 R1 R12 |
| Date: | 2009–06 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:0905&r=geo |
| By: | Fabio Manca (Faculty of Economics, University of Barcelona) |
| Abstract: | With this paper we build a two-region model where both innovation and imitation are performed. In particular imitation takes the form of technological spillovers that lagging regions may exploit given certain human capital conditions. We show how the high skill content of each region’s workforce (rather than the average human capital stock) is crucial to determine convergence towards the income level of the leader region and to exploit the technological spillovers coming from the frontier. The same applies to bureaucratic/institutional quality which are conductive to higher growth in the long run. We test successfully our theoretical result over Spanish regions for the period between 1960 and 1997. We exploit system GMM estimators which allow us to correctly deal with endogeneity problems and small sample bias. |
| Keywords: | Human Capital, Growth, Catch-Up. |
| Date: | 2009–06 |
| URL: | http://d.repec.org/n?u=RePEc:ira:wpaper:200913&r=geo |
| By: | Stefania Vitali; Mauro Napoletano; Giorgio Fagiolo |
| Abstract: | This paper employs a homogenous Þrms database to investigate industry localiza- tion in European countries. More speciÞcally, we compare, across industries and countries, the predictions of two of the most popular localization indices, i.e., the Ellison and Glaeser index (Ellison and Glaeser, 1997) and the Duranton and Over- man index (Duranton and Overman, 2005). We Þnd that, independently from the index used, localization is a pervasive phenomenon in all countries studied, but the degree of localization is very uneven across industries in each country. Furthermore, we Þnd that the two indices signiÞcantly diverge in predicting the intensity of the forces generating localization within each industry. Finally, we perform a cross- sectoral analysis of localized industries. We show that, in all countries, localized sectors are mainly ÒtraditionalÓ sectors (like jewelery, wine, and textiles) and sec- tors where scale economies are important. However, once one controls for countriesÕ industrial structures science-based sectors turn out to be the most localized ones. |
| Keywords: | Industry Localization, Manufacturing Industries, Localization Indices, Spatial Concentration, Spatial correlation, Cross-country studies |
| JEL: | R12 R3 |
| Date: | 2009–06 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:0906&r=geo |
| By: | Torrisi, Gianpiero |
| Abstract: | This paper uses data contained in the Regional Public Accounts database to investigate the heterogeneity of the impact of public infrastructure across Italian regions basing the analysis also on institutional and political ground. The issue is here addressed linking the analysis of the impact of infrastructure on GDP with the issue of corruption by means of a random coefficient panel data model approach. I consider a novel objective measure of corruption that consists of the difference between a measure of the physical quantities of public infrastructure and the cumulative price government pays for public capital stocks. The empirical analysis confirms the existence of parameter heterogeneity across Italian regions and is also consistent with theoretical considerations that corruption negatively affects economic performance. |
| Keywords: | orruption; public expenditure; infrastructure; random coefficients; regional public accounts. |
| JEL: | H54 R58 O18 R11 |
| Date: | 2009–05 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:15487&r=geo |
| By: | Peter Claeys (Faculty of Economics, University of Barcelona); Fabio Manca (Faculty of Economics, University of Barcelona) |
| Abstract: | History tells that institutions evolve gradually over time, pushing new ideas across borders and cultures. Globalisation is argued to accelerate this process. We examine the spatial links of different political institutions across borders. Applying various tests for spatial proximity, we do not find evidence of contemporaneous spatial links. This result is robust to various measures of distance and of cultural proximity across countries. Instead, when we analyse long run dynamics diffusion of institutions seems to occur only gradually. |
| Keywords: | Institutions, spatial econometrics, spillover |
| Date: | 2009–06 |
| URL: | http://d.repec.org/n?u=RePEc:ira:wpaper:200911&r=geo |
| By: | Damiaan Persyn; Koen Algoed |
| Abstract: | Countries redistribute substantial amounts of wealth between regions through taxation and social security, even in the absence of an explicit regional policy. Economic theory suggests such redistribution might be distorting. This paper indeed finds that more redistribution leads to subsequent lower growth, but also slower interregional convergence. This may explain the observed lack of within-country convergence in the EU, in contrast to faster convergence between countries where such redistributive schemes do not exist. In contrast, investment in infrastructure or human and physical capital is found to foster both growth and convergence. |
| Keywords: | income redistribution, inequality, regional convergence |
| JEL: | O47 H3 |
| Date: | 2009 |
| URL: | http://d.repec.org/n?u=RePEc:ete:vivwps:4&r=geo |
| By: | Zhenlin Yang (School of Economics, Singapore Management University); Liangjun Su (School of Economics, Singapore Management University) |
| Abstract: | We propose an instrumental variable quantile regression (IVQR) estimator for spatial autoregressive (SAR) models. Like the GMM estimators of Lin and Lee (2006) and Kelejian and Prucha (2006), the IVQR estimator is robust against heteroscedasticity. Unlike the GMM estimators, the IVQR estimator is also robust against outliers and requires weaker moment conditions. More importantly, it allows us to characterize the heterogeneous impact of variables on different points (quantiles) of a response distribution. We derive the limiting distribution of the new estimator. Simulation results show that the new estimator performs well in finite samples at various quantile points. In the special case of median restriction, it outperforms the conventional QML estimator without taking into account of heteroscedasticity in the errors; it also outperforms the GMM estimators with or without considering the heteroscedasticity. |
| Keywords: | Spatial Autoregressive Model; Quantile Regression; Instrumental Variable; Quasi Maximum Likelihood; GMM; Robustness. |
| JEL: | C13 C21 C51 |
| Date: | 2007–08 |
| URL: | http://d.repec.org/n?u=RePEc:siu:wpaper:05-2007&r=geo |
| By: | Joseph I Daniel (Department of Economics,University of Delaware) |
| Abstract: | Congestion pricing of Canada’s four largest airports would save between seventy-two and one-hundred-five million dollars annually. Social cost of each aircraft movement would decrease by several hundred dollars at Toronto and Vancouver, and by about fifty dollars at Calgary and Montreal. Toronto currently experiences this congestion in spite of its slot control system. Congestion fees would be less than current weight-based landing fees on average. At projected traffic growth rates, social costs of landings and takeoffs would remain below current levels for at least five years—postponing the need for additional capacity. A stochastic bottleneck model indicates these substantial welfare gains regardless of whether dominant airlines internalize their self-imposed delays. This paper reports equilibrium congestion fee schedules by time of day and calculates equilibrium traffic rates, queuing delays, layover times, and connection times. |
| Keywords: | airport congestion pricing, stochastic queuing, bottleneck model, slot constraints. |
| JEL: | R4 H2 L5 L9 |
| Date: | 2009 |
| URL: | http://d.repec.org/n?u=RePEc:dlw:wpaper:09-02.&r=geo |