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on Economic Geography |
| By: | Enrico Marelli (Department of Economics, Faculty of Economics, University of Brescia, Italy); Roberto Patuelli (Department of Economics, Faculty of Economics-Rimini, University of Bologna, Italy; The Rimini Centre for Economic Analysis (RCEA), Italy); Marcello Signorelli (Department of Economics, Finance and Statistics, Faculty of Political Sciences, University of Perugia, Italy) |
| Abstract: | In this paper we empirically assess the evolution for the EU regions of both employment and unemployment before and after the Global Crisis. After a review of the literature on the theories and key determinants of regional unemployment, we shall overview the main findings concerning the labour market impact of the Global Crisis. The empirical analysis will initially be carried out at the national level including all EU countries; subsequently, we shall focus on the EU regions (at the NUTS-2 level), in order to detect possible changes in the dispersion of regional unemployment rates after the crisis. Our econometric investigations aim to assess the effect, on labour market performance, of previous developments in regional labour markets time series, as well as the importance of structural characteristics of the labour markets, in terms of the sectoral specialization of the regional economies. In fact, the local industry mix may have played a crucial role in shaping labour market performance in response to the crisis. In addition, we consider further characteristics of the regional labour markets, by including indicators of the level of precarization of labour and of the share of long-term unemployed, as indicators of the efficiency of the local labour markets. From a methodological viewpoint, we exploit eigenvector decomposition-based spatial filtering techniques, which allow us to greatly reduce unobserved variable bias – a significant problem in cross-sectional models – by including indicators of latent unobserved spatial patterns. Finally, we render a geographical description of the heterogeneity influence of past labour market performance over the crisis period, showing that the past performance has a differentiated impact on recent labour market developments. |
| Keywords: | crisis, employment, unemployment, European Union, NUTS-2, spatial filtering, sectoral composition, spatially heterogeneous parameters |
| JEL: | C21 R12 |
| Date: | 2011–09 |
| URL: | http://d.repec.org/n?u=RePEc:rim:rimwps:39_11&r=geo |
| By: | Roberto Bande (University of Santiago and IDEGA); Marika Karanassou (Queen Mary, University of London and IZA) |
| Abstract: | On both theoretical and empirical grounds, this paper provides evidence that refutes the natural rate of unemployment (NRU) hypothesis as an explanation of the evolution of regional disparities in the unemployment rate. We first present our analytical framework, which follows the chain reaction theory (CRT) of unemployment and argues that (i) a system of interactive labour market equations, rather than a single-equation unemployment rate model, is better equipped to accommodate unemployment dynamics, and (ii) due to the interplay of frictions and growth in labour markets, the NRU ceases to be an attractor of the unemployment rate time path. We then provide evidence that the Spanish ecoomy is characterised by large and persistent disparities in the regional unemployment rates. Through standard kernel density tecnhiques, we demonstrate the existence of marked differences between two groups of high and low unemployment regions that remain stable in their composition through time. Finally, we review our empirical labour market model for each group of regions and evaluate the corresponding natural rates. Our findings confirm that the evolution of regional disparities cannot be attributed to disparities in the natural rates, given that these, although different, do not act as an attractor of unemployment. Thus, the NRUs offer little help in the formulation of labour market policies. |
| Keywords: | regional unemployment, disparities, kernel, natural rate, frictional growth |
| JEL: | R23 J64 |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:edg:anecon:0043&r=geo |
| By: | Andrés Rodríguez-Pose (IMDEA Social Sciences); Katja Novak (Slovenian Government) |
| Abstract: | This paper evaluates whether the learning mechanisms of the European Cohesion policy have contributed to improve the economic impact of Structural Fund expenditure over time. It intends to show whether the evolution of the policy in response to greater internal monitoring and consultation and external scrutiny and criticism has resulted in a more efficient and better targeted Cohesion policy. This is tested using an econometric model which evaluates the effect of Structural Fund expenditure on the growth of regional GDP per capita – conditional on factor endowments, institutional quality and initial conditions – during the last programming periods for which full sets of data are available (1994-1999 and 2000-2006). The results of the analysis unveil an increase in the effectiveness of the policy in successive periods. This positive association is robust to controlling for the level of development of the country and the relative economic position of a region within a country. The results also show that, when structural factors are taken into consideration, Structural Fund investment tends to yield higher returns in better-off countries and wealthier regions within countries. |
| Keywords: | Cohesion; regional development; economic growth, GDP per capita; regions; European Union |
| Date: | 2011–09–30 |
| URL: | http://d.repec.org/n?u=RePEc:imd:wpaper:wp2011-17&r=geo |
| By: | FUKAO Kyoji; IKEUCHI Kenta; KIM YoungGak; KWON Hyeog Ug |
| Abstract: | Using a Melitz-style model of heterogeneous firms, Baldwin and Okubo (2006) recently presented a theoretical model in which self-sorting occurs and more productive factories choose to locate in more productive areas. The model suggests that firm-specific factors and regional factors affect each other through the endogeneity of location decisions. However, to date there have been few studies empirically testing this issue. Against this background, our aim is to examine the relationship between firms and location-specific factors in location decisions using factory-level panel data from Japan's Census of Manufactures. We begin by estimating how much of the differences in factories' TFP levels can be explained by both firm and location effects. The estimation results show that both effects have a significant impact on the productivity level of a factory, and that the firm effects are more important than the location effects. We also find a statistically significant negative correlation between firm effects and location effects, and investigate what causes this relationship. One potential explanation is that more productive firms may tend to set up new factories in less productive locations such as rural areas, where factor prices such as land prices and wage rates are usually low, in order to benefit from low factor prices. To examine this issue, we estimate a mixed logit model of location choice. The results indicate that more productive firms indeed tend to set up new factories in low-productivity locations, which is consistent with our hypothesis. |
| Date: | 2011–09 |
| URL: | http://d.repec.org/n?u=RePEc:eti:dpaper:11068&r=geo |
| By: | Thomas K. Bauer; Michael Fertig; Matthias Vorell |
| Abstract: | Using a unique dataset for Germany that links individual longitudinal data from the GSOEP to regional data from the federal employment agency and data of real estate prices, we evaluate the impact of neighborhood unemployment on individual employment propects. The panel setup and richness of the data allows us to overcome some of the identifi cation problems which are present in this strand of literature. The empirical results indicate that there is a signifi cant negative impact of neighborhood unemployment on the individual employment probability. |
| Keywords: | Social interactions; unemployment; neighborhood characteristics |
| JEL: | J65 R23 |
| Date: | 2011–09 |
| URL: | http://d.repec.org/n?u=RePEc:rwi:repape:0285&r=geo |
| By: | Berliant, Marcus; Yu, Chia-Ming |
| Abstract: | Canonical analysis of the classical general equilibrium model demonstrates the existence of an open and dense subset of standard economies that possess fully-revealing rational expectations equilibria. This paper shows that the analogous result is not true in urban economies under reasonable modifications for this field. An open subset of economies where none of the modified rational expectations equilibria fully reveals private information is found. There are two important pieces. First, there can be information about a location known by a consumer who does not live in that location in equilibrium, and thus the equilibrium rent does not reflect this information. Second, if a consumer's utility depends only on information about their (endogenous) location of residence, perturbations of utility naturally do not incorporate information about other locations conditional on the consumer's location of residence. Existence of equilibrium is proved. Space can prevent housing prices from transmitting information from informed to uninformed households, resulting in an inefficient outcome. |
| Keywords: | Urban Economics; General Equilibrium; Private Information; Rational Expectations |
| JEL: | R13 D82 D51 |
| Date: | 2011–09–27 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:33754&r=geo |
| By: | Bédia F. Aka; Souleymane S. Diallo |
| Abstract: | The objective of this paper is to examine how a small open economy such as Côte d’Ivoire (CI) can obtain growth-based internal tax resources, and how the tax system affects households and individuals through relative prices. A microsimulated CGE model is used to analyse the effects of an alternative tax system on households by utilizing a survey. It is postulated that the military and political crisis that started in 1999 with the first coup d’etat in Côte d’Ivoire is transitory and that CI has an internal tax policy capacity. This paper indicates that an alternative tax structure can reduce distortion in regional poverty, inequality for households, and in cities and small areas of the country. A model is formulated using Côte d’Ivoire’s 1998-based social accounting matrix and the 1998 population survey of 4,200 households. The main findings of this study are that the post-crisis tax policies envisioned by the government (reducing the tax rate on firms, reducing import taxes and increasing taxes on household income) result in an increase in poverty and inequality at the regional, city and small area levels. |
| Date: | 2011–01 |
| URL: | http://d.repec.org/n?u=RePEc:aer:rpaper:rp_218&r=geo |
| By: | Gordon Hughes (School of Economics, University of Edinburgh) |
| Abstract: | Econometricians have begun to devote more attention to spatial interactions when carrying out applied econometric studies. In part, this is motivated by an explicit focus on spatial interactions in policy formulation or market behavior, but it may also reflect concern about the role of omitted variables that are or may be spatially correlated. The classic models of spatial autocorrelation or spatial error rely upon a predefined matrix of spatial weights W, which may be derived from an explicit model of spatial interactions but which, alternatively, could be viewed as a flexible approximation to an unknown set of spatial links similar to the use of a translog cost function. With spatial panel data, it is possible, in principle, to regard W as potentially estimable, though the number of time periods would have to be large relative to the number of spatial panel units unless severe restrictions are placed upon the structure of the spatial interactions. While the estimation of W may be infeasible for most real data, there is a strong, formal similarity between spatial panel models and nonspatial panel models in which the variance-covariance matrix of panel errors is not diagonal. One important variant of this type of model is the random-coefficient model in which slope coefficients differ across panel units so that interest focuses on the mean slope coefficient across panel units. In certain applications--for example, cross-country (macro-)economic data--the assumption that reaction coefficients are identical across panel units is not intuitively plausible. Instead of just sweeping differences in coefficients into a general error term, the random-coefficient model allows the analyst to focus on the common component of responses to changes in the independent variables while retaining the information about the error structure associated with coefficients that are random across panel units but constant over time for each panel unit. At present, Stata's spatial procedures include a range of user-written routines that are designed to deal with cross-sectional spatial data. The recent release of a set of programs (including spmat, spivreg, and spreg) written by Drukker, Prucha, and Raciborski provides Stata's users with the opportunity to fit a wide range of standard spatial econometric models for cross-sectional data. Extending such procedures to deal with panel data is nontrivial, in part because there are important issues about how panels with incomplete data should be treated. The casewise exclusion of missing data is automatic for cross-sectional data, but omitting a whole panel unit because some of the data in the panel are missing will typically lead to a very large reduction in the size of the working dataset. For example, it is very rare for international datasets on macroeconomic or other data to be complete, so that casewise exclusion of missing data will generate datasets that contain many fewer countries or time periods than might otherwise be usable. The theoretical literature on econometric models for the analysis of spatial panels has flourished in the last decade with notable contributions from LeSage and Pace, Elhorst, and Pfaffermayr, among others. In some cases, authors have made available specific code for the implementation of the techniques that they have developed. However, the programming language of choice for such methods has been MATLAB, which is expensive and has a fairly steep learning curve for nonusers. Many of the procedures assume that there are no missing data and the procedures may not be able to handle large datasets because the model specifications can easily become unmanageable if either N (the number of spatial units) or T (the number of time periods) becomes large. The presentation will cover a set of user-written maximum likelihood procedures for fitting models with a variety of spatial structures including the spatial error model, the spatial Durbin model, the spatial autocorrelation model, and certain combinations of these models--the terminology is attributable to LeSage and Pace (2009). A suite of MATLAB programs to fit these models for both random and fixed effects has been compiled by Elhorst (2010) and provides the basis for the implementation in Stata/Mata. Methods of dealing with missing data, including the implementation of an approach proposed by Pfaffermayr (2009), will be discussed. The problem of missing data is most severe when data on the dependent variable are missing in the spatial autocorrelation model because it means that information on spatial interactions may be greatly reduced by the exclusion of countries or other panel units. In such cases, some form of imputation may be essential, so the presentation will consider alternative methods of imputation. It should be noted that mi does not support panel data procedures in general, and the relatively high cost of fitting spatial panel models means that it may be difficult to combine mi with spatial procedures for practical applications. A second aspect of spatial panel models that will be covered in the presentation concerns the links between such models and random-coefficient models that can be fit using procedures such as xtrc or the user-written procedure xtmg. The classic formulation of random-coefficient models assumes that the variance-covariance model of panel errors is diagonal but heteroskedastic. This is an implausible assumption for most cross-country datasets, so it is important to consider how it may be relaxed, either by allowing for explicit spatial interactions or by using a consistent estimator of the cross-country variance-covariance model. The user-written procedures introduced in the presentation will be illustrated by applications drawn from analyses of demand for infrastructure, health outcomes, and climate for cross-country data covering the developing and developed world plus regions in China. |
| Date: | 2011–09–26 |
| URL: | http://d.repec.org/n?u=RePEc:boc:usug11:12&r=geo |
| By: | Gerald A. Carlino; Jake K. Carr; Robert M. Hunt; Tony E. Smith |
| Abstract: | The authors study the location and productivity of more than 1,000 research and development (R&D) labs located in the Northeast corridor of the U.S. Using a variety of spatial econometric techniques, they find that these labs are substantially more concentrated in space than the underlying distribution of manufacturing activity. Ripley's K-function tests over a variety of spatial scales reveal that the strongest evidence of concentration occurs at two discrete distances: one at about one-quarter of a mile and another at about 40 miles. These findings are consistent with empirical research that suggests that some spillovers depreciate very rapidly with distance, while others operate at the spatial scale of labor markets. The authors also find that R&D labs in some industries (e.g., chemicals, including drugs) are substantially more spatially concentrated than are R&D labs as a whole.> > Tests using local K-functions reveal several concentrations of R&D labs (Boston, New York-Northern New Jersey, Philadelphia-Wilmington, and Washington, DC) that appear to represent research clusters. The authors verify this conjecture using significance-maximizing techniques (e.g., SATSCAN) that also address econometric issues related to "multiple testing" and spatial autocorrelation.> > The authors develop a new procedure for identifying clusters — the multiscale core-cluster approach — to identify labs that appear to be clustered at a variety of spatial scales. They document that while locations in these clusters are often related to basic infrastructure, such as access to major roads, there is significant variation in the composition of labs across these clusters. Finally, the authors show that R&D labs located in clusters defined by this approach are, all else equal, substantially more productive in terms of the patents or citation-weighted patents they receive.> |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedpwp:11-42&r=geo |
| By: | Yves Zenou (Stockholm University, IFN, and CREAM) |
| Abstract: | We develop a search-matching model with rural-urban migration and an explicit land market. Wages, job creation, urban housing prices are endogenous and we characterize the steady-state equilibrium. We then consider three different policies: a transportation policy that improves the public transport system in the city, an entry-cost policy that encourages investment in the city and a restricting-migration policy that imposes some costs on migrants. We show that all these policies can increase urban employment but the transportation policy has much more drastic effects. This is because a decrease in commuting costs has both a direct positive effect on land rents, which discourages migrants to move to the city, and a direct negative effect on urban wages, which reduces job creation and thus migration. When these two effects are combined with search frictions, the interactions between the land and the labor markets have amplifying positive effects on urban employment. Thus, improving the transport infrastructure in cities can increase urban employment despite the induced migration from rural areas. |
| Keywords: | Rural-urban migration, transportation policies, entry costs, restricting migration |
| JEL: | D83 J61 O18 R14 |
| Date: | 2010–11 |
| URL: | http://d.repec.org/n?u=RePEc:crm:wpaper:1027&r=geo |
| By: | Francisca G-C Richter; Youngme Seo |
| Abstract: | Overall regional conditions such as employment, geography, and amenities, favor the co-movement of housing prices in central cities and their suburbs. Simultaneously, over half a century of sprawl may induce a negative relation between suburban and central city home prices, with central city values falling relative to suburban home values. What happens to the relationship between subhousing markets when cities are shocked by the foreclosure crisis? This paper builds repeat-sales indices to explore home price dynamics before and after the foreclosure crisis in the Cleveland area, a market that in the aggregate had little home price appreciation prior to the crisis, but significant follow-up depreciation. The analysis finds evidence that connectedness, expressed as the relative importance of neighboring housing market conditions in explaining city home prices, increases among submarkets even as they experience varying levels of foreclosure rates, and that foreclosure effects give little sign of receding in the near future. The analysis is relevant to the discussion of economic recovery among city and suburban communities as the nation faces high inventories of soon-to-be foreclosed properties. |
| Keywords: | Housing ; Housing policy ; Foreclosure |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedcwp:1119&r=geo |
| By: | Giorgio Fazio; Davide Piacentino (-) |
| Abstract: | Empirical convergence analysis is typically envisaged from a macro aggregate perspective. However, researchers have recently highlighted how investigating convergence at the disaggregate level may yield interesting insights into the convergence debate. In this paper, we suggest an approach that allows exploiting large micro panels to test for convergence. Compared to the traditional convergence analysis, this approach allows obtaining beta- and sigma-like convergence parameters for both the micro and the macro level of interest. We provide a practical example that analyses productivity convergence across firms and provinces using a large sample of Italian firms. |
| Keywords: | Convergence, Multilevel Models, Italian Firms. |
| JEL: | C33 D20 O47 |
| Date: | 2011–07–26 |
| URL: | http://d.repec.org/n?u=RePEc:prt:dpaper:9_2011&r=geo |
| By: | Marco Crocco (Cedeplar/UFMG); Fabiana Santos (Cedeplar/UFMG); Ana Tereza Lanna Figueiredo (PUC Minas) |
| Abstract: | Despite the fact that after the second half of the 1990s studies of financial exclusion have gained strength among the studies about poverty and regional and social inequalities, a few studies about this problem had appear in the Brazilian economic literature. The present work contributes to the debate by carrying out an investigation of the phenomenon of financial exclusion within Brazilian regions. The main hypothesis of the study is that of financial exclusion is not disassociated from the e space in which it happens. Through of the use of proxies, two dimensions of the financial exclusion has been studied: the access to financial services and the its suitability. |
| Keywords: | financial exclusion, liquidity preference, banks, regional economics. |
| JEL: | G2 R1 E44 |
| Date: | 2011–09 |
| URL: | http://d.repec.org/n?u=RePEc:cdp:texdis:td450&r=geo |
| By: | Martinho, Vítor João Pereira Domingues |
| Abstract: | We built a model analyzing, through cross-section estimation methods, the influence of spatial effects in the productivity conditional convergence in the economic sectors of NUTs III of mainland Portugal between 1995 and 2002. Taking into account the estimation results, it is stated once again that the indications of convergence are greater in industry, and it can be seen that spatial spillover effects, spatial lag and spatial error, do not condition the convergence of productivity in the several economic sectors of Portuguese region in the period under consideration. |
| Keywords: | endogenous growth theory; spatial econometrics; Portuguese Regions |
| JEL: | O18 C20 C50 R11 |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:33711&r=geo |
| By: | Martinho, Vítor João Pereira Domingues |
| Abstract: | We built a model analyzing, through cross-section estimation methods, the influence of spatial effects and human capital in the conditional productivity convergence in the economic sectors of NUTs III of mainland Portugal between 1995 and 2002. Taking into account the estimation results, it is stated once again that the indications of convergence are greater in industry, and it can be seen that spatial spillover effects, spatial lag and spatial error, do not condition the convergence of productivity in the various economic sectors of Portuguese region in the period under consideration. In contrast the human capital condition the productivity convergence. |
| Keywords: | endogenous growth theory; spatial econometrics; Portuguese Regions |
| JEL: | O18 C20 C50 R11 |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:33712&r=geo |
| By: | Martinho, Vítor João Pereira Domingues |
| Abstract: | We built a model analyzing the importance which the natural advantages and local resources are in the manufacturing industry location, in relation with the "spillovers" effects and industrial policies. To this, we estimate the Rybczynski equation matrix for the various manufacturing industries in Portugal, at regional level (NUTS II) and for the period 1986 to 1994. As a summary conclusion, noted that the location of manufacturing in Portugal is still mostly explained by specific factors, with a tendency to increase in some cases the explanation by these factors, having the effect "spillovers" and industrial policies little importance in this context. |
| Keywords: | geographical concentration; Portuguese regions; linear models |
| JEL: | C20 C50 R39 O14 |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:33734&r=geo |
| By: | Martinho, Vítor João Pereira Domingues |
| Abstract: | We built a model identifying the determinants that affect the mobility of labor. The empirical part of the work will be performed for the NUTS II of Portugal, from 1996 to 2002. As main conclusion it can be said, for the NUTS II (1996-2002), which is confirmed the existence of some labor mobility in Portugal and that regional mobility is mainly influenced positively by the output growth and negatively by the unemployment rates and by the weight of the agricultural sector (1)(Martinho, 2011). |
| Keywords: | net migration; Portuguese regions; panel estimations; linear models |
| JEL: | C20 C50 O15 R23 |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:33717&r=geo |
| By: | Martinho, Vítor João Pereira Domingues |
| Abstract: | We built a model identifying the determinants that affect the mobility of labor. The empirical part of the work will be performed for the NUTS III of Portugal, from 1991 and 2001. At this level of spatial disaggregation (and in this period) the basic equipment (amenities), particularly in terms of availability of housing, are the main determinants of migration (1)(Martinho 2011). |
| Keywords: | net migration; Portuguese regions; cross-section estimations |
| JEL: | C20 C50 O15 R23 |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:33718&r=geo |
| By: | Martinho, Vítor João Pereira Domingues |
| Abstract: | We built a model analyzing, through cross-section estimation methods, the influence of spatial effects in the conditional product convergence in the parishes’ economies of mainland Portugal between 1991 and 2001 (the last year with data available for this spatial disaggregation level). Taking into account the estimation results, it is stated that there are not indications of convergence (the population is in the littoral of Portugal) and it can be seen that spatial spillover effects, spatial lag (capturing spatial autocorrelation through a spatially lagged dependent variable) and spatial error (capturing spatial autocorrelation through a spatially lagged error term) condition the convergence of product of Portuguese parishes in the period under consideration. |
| Keywords: | endogenous growth theory; spatial econometrics; Portuguese context |
| JEL: | O18 C20 C50 R11 |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:33713&r=geo |