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 Annals of Regional Science   [SJR: 0.405]   [H-I: 42]   [8 followers]  Follow         Hybrid journal (It can contain Open Access articles)    ISSN (Print) 1432-0592 - ISSN (Online) 0570-1864    Published by Springer-Verlag  [2355 journals]
• Use and interpretation of spatial autoregressive probit models
• Authors: Donald J. Lacombe; James P. LeSage
Pages: 1 - 24
Abstract: Abstract Applications of spatial probit regression models that have appeared in the literature have incorrectly interpreted estimates from these models. Spatially dependent choices frequently arise in various modeling scenarios, including situations involving analysis of regional voting behavior, decisions by states or cities to change tax rates relative to neighboring jurisdictions, decisions by households to move or stay in a particular location. We use county-level voting results from the 2004 presidential election as an illustrative example of some issues that arise when drawing inferences from spatial probit model estimates. Although the voting example holds particular intuitive appeal that allows us to focus on interpretive issues, there are numerous other situations where these same considerations come into play. Past work regarding Bayesian Markov Chain Monte Carlo estimation of spatial probit models from LeSage and Pace (Introduction to spatial econometrics. Taylor and Francis, New York, 2009) is used, as well as derivations from LeSage et al. (J R Stat Soc Ser A Stat Soc 174(4):1007–1027, 2011) regarding proper interpretation of the partial derivative impacts from changes in the explanatory variables on the probability of voting for a candidate. As in the case of conventional probit models, the effects arising from changes in the explanatory variables depend in a nonlinear way on the levels of these variables. In non-spatial probit regressions, a common way to explore the nonlinearity in this relationship is to calculate “marginal effects” estimates using particular values of the explanatory variables (e.g., mean values or quintile intervals). The motivation for this practice is consideration of how the impact of changing explanatory variable values varies across the range of values encompassed by the sample data. Given the nonlinear nature of the normal cumulative density function transform on which the (non-spatial) probit model relies, we know that changes in explanatory variable values near the mean may have a very different impact on decision probabilities than changes in very low or high values. For spatial probit regression models, the effects or impacts from changes in the explanatory variables are more highly nonlinear. In addition, since spatial models rely on observations that each represent a location or region located on a map, the levels of the explanatory variables can be viewed as varying over space. We discuss important implications of this for proper interpretation of spatial probit regression models in the context of our election application.
PubDate: 2018-01-01
DOI: 10.1007/s00168-015-0705-x
Issue No: Vol. 60, No. 1 (2018)

• Spatial lag dependence in the presence of missing observations
• Authors: Takahisa Yokoi
Pages: 25 - 40
Abstract: Abstract We explore the estimation effectiveness of spatial lag models in the presence of missing observations. Spatial lag models are used to measure interdependency between dependent variables. If there are no missing data, it is easy to interpret this spatial autocorrelation process. Very sparsely sampled data are sometimes used in empirical studies. For such data, we observe only a small part of a population containing possible mutual dependencies. Simulation studies based on artificial data confirm the relation between the sampling rate and selection ratio of spatial and non-spatial models. Our findings include the following: (1) Negative spatial autocorrelation of the data-generating process (DGP) may not be observed. (2) Positive spatial autocorrelation of the DGP may be observed, but it is downward-biased. (3) We obtain less-biased estimates if we use a non-row-standardized weight matrix. (4) Non-spatial models tend to be selected in preference to the correct model, the spatial lag model. (5) Estimates of regression coefficients remain almost unbiased.
PubDate: 2018-01-01
DOI: 10.1007/s00168-015-0737-2
Issue No: Vol. 60, No. 1 (2018)

• Spatiotemporal analysis of German real-estate prices
• Authors: Philipp Otto; Wolfgang Schmid
Pages: 41 - 72
Abstract: Abstract In this paper, we provide a spatiotemporal examination of German real-estate prices in 412 administrative districts. The price process is spatially autocorrelated and stationary over the considered period from 1995 to 2010. To quantify both spatial and temporal effects of the process, we apply different spatiotemporal models. These models are consistently estimated by the maximum likelihood approach, and they are compared with respect to the impact of shocks on fundamental quantities. Moreover, we interpret the economic importance of our results with respect to migrational issues. We show that the willingness of individuals to move or to commute decreased in Germany during the considered years. Furthermore, we include a detailed interpretation of the so-called ripple effect.
PubDate: 2018-01-01
DOI: 10.1007/s00168-016-0789-y
Issue No: Vol. 60, No. 1 (2018)

• The impact of trails on property values: a spatial analysis
• Authors: Matthew Gnagey; Therese Grijalva
Pages: 73 - 97
Abstract: Abstract Convenient and local access to open green space is highly valued in many communities, particularly those comprised largely of individuals who participate in natural resource outdoor recreation. Understanding the value outdoor recreation communities place on access to open space is critical for informing policy decisions on land use including zoning and other restrictions, government open space purchases, and open space access points such as trailheads. In this article, we analyze the impact of trail access on property values in Ogden, Utah, using spatial hedonic pricing models. We consistently find substantial premiums for properties located closer to trailheads. Using a spatial Durbin error model, we find a 0.6% direct effect premium for each minute closer in driving time to the nearest trailhead, and a 1.4% premium when accounting for the total impact. We also find direct premiums between 0.4 and 1.9% for each minute closer in driving time to individual trailheads in this region. Additionally, homes adjacent to trailheads do not experience negative spillovers that homeowners may experience from increased traffic and congestion.
PubDate: 2018-01-01
DOI: 10.1007/s00168-017-0846-1
Issue No: Vol. 60, No. 1 (2018)

• How immigration reduced volunteering in the USA: 2005–2011
• Authors: Tiago Freire; Xiaoye Li
Pages: 119 - 141
Abstract: Abstract In this study, we show that an inflow of immigrants reduces volunteering, a proxy of social capital investment, in receiving communities. Since the 1960s, there has been a large decrease in social capital in the USA as well as a considerable inflow of immigrants. This increased heterogeneity of US cities may have increased the cost of investing in social capital, and thereby, reduced such investment. By using the current population survey September Volunteer Supplement for 2005–2011, we examine the relationship between the proportion of foreign-born people and social capital investment by US-born individuals, proxied by volunteering. Once we correct for immigrants’ self-selection to different destinations using a supply–push instrumental variable, we find that a 1 standard deviation increase in the proportion of foreign-born individuals in a state reduces the probability of US-born individuals volunteering by 0.09–0.15 standard deviations and cuts number of hours volunteered by 0.13–0.21 standard deviations.
PubDate: 2018-01-01
DOI: 10.1007/s00168-017-0848-z
Issue No: Vol. 60, No. 1 (2018)

• Grid and shake: spatial aggregation and the robustness of regionally
estimated elasticities
• Authors: Gábor Békés; Péter Harasztosi
Pages: 143 - 170
Abstract: Abstract This paper proposes a simple and transparent method for measuring spatial robustness of regionally estimated coefficients and considers the role of the administrative districts and of the size of regions. The procedure offers a new solution for a practical empirical issue: comparing the variables of interest across spatially aggregated units. It improves upon existing methods, especially when spatial units are heterogeneous. To illustrate the method, we use Hungarian data and compare estimates of agglomeration externalities at various levels of aggregation. Using the procedure, we find that the method of spatial aggregation seems to be of equal importance to the specification of the econometric model.
PubDate: 2018-01-01
DOI: 10.1007/s00168-017-0849-y
Issue No: Vol. 60, No. 1 (2018)

• The fall and rise of business cycle co-movements in Imperial
Austria’s regions
• Authors: Carlo Ciccarelli; Anna Missiaia
Pages: 171 - 193
Abstract: Abstract This paper investigates regional business cycle co-movements in Austria–Hungary from 1867 to 1913. Economic theory suggests that rising market integration induces sectoral specialisation, resulting in a reduction in the correlation of regional GDP cycles (Krugman effect). However, the synchronisation of business cycles is expected to increase because of the growing inter-linkages among regions led by the adoption of common currency and common economic policies (Frankel and Rose effect). We show that in the case of nineteenth-century Austria–Hungary the specialisation effect, most likely amplified by the stock market crisis of 1873, prevailed during 1867–1890, while the common currency/policy effect prevailed during 1890–1913, when the gold standard was adopted in both Austria and Hungary. However, core and peripheral regions contributed differently to the correlation of business fluctuations.
PubDate: 2018-01-01
DOI: 10.1007/s00168-017-0850-5
Issue No: Vol. 60, No. 1 (2018)

• Conditional and joint tests for spatial effects in discrete Markov chain
models of regional income distribution dynamics
• Authors: Wei Kang; Sergio J. Rey
Abstract: Abstract Spatial effects have been recognized to play an important role in transitional dynamics of regional incomes. Detection and evaluation of both spatial heterogeneity and spatial dependence in discrete Markov chain models, which have been widely applied to the study of regional income distribution dynamics and convergence, are vital, but under-explored issues. Indeed, in this spatiotemporal setting, spatial effects can take much more complex forms than that in a pure cross-sectional setting. In this paper, we address two test frameworks. The first is a conditional spatial Markov chains test framework, which can be used to detect spatial heterogeneity and temporally lagged spatial dependence; the second is a joint spatial Markov chains test framework, which tests for contemporaneous spatial dependence. A series of Monte Carlo experiments are designed to examine size, power and robustness properties of these tests for a range of sample sizes (spatial $$\times$$ temporal dimensions), for different levels of discretization granularity and for different number of regimes. Results indicate that all tests display good size property except when sample size is fairly small. All tests for spatial dependence are similar in almost all aspects—size, power and robustness. Conditional spatial Markov tests for spatial heterogeneity have highest power for detecting spatial heterogeneity. Granularity of discretization has a major impact on the size properties of the tests when sample size is fairly small.
PubDate: 2018-01-06
DOI: 10.1007/s00168-017-0859-9

• Special issue on youth and graduate migration
• Authors: Alessandra Faggian; Jonathan Corcoran; Francisco Rowe
Pages: 571 - 575
PubDate: 2017-11-01
DOI: 10.1007/s00168-017-0845-2
Issue No: Vol. 59, No. 3 (2017)

• Why do they return' Beyond the economic drivers of graduate return
migration
• Authors: Riccardo Crescenzi; Nancy Holman; Enrico Orru’
Pages: 603 - 627
Abstract: Abstract This paper explores the factors that shape the location choices of formerly mobile graduates (FMGs) initially resident in Sardinia, Italy, a less developed European region. Combining qualitative and quantitative techniques, the paper examines the reasons why some individuals decide to return after their studies, the factors that shape their decisions and how these choices unfolded in space and time. It counters the literature, which suggests that migration is a one-off linear process driven only by wealth-maximising behaviour, positing rather that access to opportunities in open meritocratic job markets and circular migration trajectories are far more salient to FMGs. This suggests that policy makers should concentrate on promoting labour market opportunities and invest in social networks that will aid brain circulation.
PubDate: 2017-11-01
DOI: 10.1007/s00168-016-0762-9
Issue No: Vol. 59, No. 3 (2017)

• Do natural amenities influence undergraduate student migration
decisions'
• Authors: Kathryn R. Dotzel
Pages: 677 - 705
Abstract: Abstract The primary objective of this paper is to examine the influence of natural amenities on student migration decisions using institution-level data from the National Center for Education Statistics’ Integrated Postsecondary Education Data System. We surpass the scope of previous studies focused on natural amenities, which rely on a limited selection of state-level measures, by matching interpolated weather station- and county-level climate data to each post-secondary institution. Results suggest that students consider natural amenities in their migration to college decision and, in a number of cases, preferences for natural amenities vary based on origin state amenity conditions. Nonetheless, migration decisions are dominated by origin state educational opportunities and by proximity of the student’s origin state to the state of college attendance.
PubDate: 2017-11-01
DOI: 10.1007/s00168-016-0765-6
Issue No: Vol. 59, No. 3 (2017)

• Moving home again' Never! The locational choices of graduates in
Sweden
• Authors: Lina Bjerke; Charlotta Mellander
Pages: 707 - 729
Abstract: Abstract Two major challenges in Europe’s rural areas are an aging population and the diminishing share of human capital. While this pattern has been occurring for a long time, the effects are becoming acutely visible and impactful. The long-term loss of younger individuals has in many ways “drained” the labor market and the economic market power of rural areas. This is the context of our research: the locational choice of university graduates from an urban–rural perspective. Using micro data covering the entire Swedish population, we identify all university graduates from the year 2001. We analyze them with respect to whether they live in a rural or urban region before starting university and where they live after graduation at two points in time: 5 and 10 years. We use a series of multinomial logit regressions to determine what factors affect their short-term and long-term choices of location. We find that having children is one of the most influential factors for moving back home after graduation, irrespective of type of region. We find only minor differences between the two time perspectives.
PubDate: 2017-11-01
DOI: 10.1007/s00168-016-0777-2
Issue No: Vol. 59, No. 3 (2017)

• International mobility and wages: an analysis of Italian Ph.D. graduates
• Authors: Marco Di Cintio; Emanuele Grassi
Pages: 759 - 791
Abstract: Abstract Following a recent stream of research that focuses on the migration of high-skilled workers, this paper examines the wage performance of two cohorts of Italian Ph.D. graduates associated with international mobility. After controlling for the endogeneity of the migration decision, we find that labor mobility is associated with higher wages and that selection on unobservable traits is essential to address the issue of the returns to migration. Additionally, we do not find evidence of individual heterogeneity in the response of wages to migration. We also show that our results are always confirmed when we include two exclusion restrictions in the empirical model and when we restrict the analysis to different subpopulations.
PubDate: 2017-11-01
DOI: 10.1007/s00168-016-0749-6
Issue No: Vol. 59, No. 3 (2017)

• Human capital spillovers in Dutch cities: consumption or productivity'
• Authors: Viktor A. Venhorst
Pages: 793 - 817
Abstract: Abstract We study the recursive relationship between the ability of Dutch cities to attract recent graduate human capital to their labour—or housing markets and a city’s skills structure, using a comprehensive dataset and a novel operationalisation strategy. We disentangle production and consumption spillovers by separating out human capital employed in a city’s labour market and human capital present in a city’s resident population, respectively. We do so for both the recent graduates flowing into Dutch cities to find work and a residential location, as well as for the incumbent workers and population. We control for the effects of a city’s skills endowments, its (non-) economic characteristics and those of other relevant cities. We find positive effects of a relatively strong graduate labour market inflow on the share of higher and scientific-level jobs. Production spillovers therefore predominantly occur among the higher skilled. Contrary to the higher educated incumbent population, which appears to prefer high skilled services, recent graduate inflows to residential areas have positive effects on the share of jobs requiring lower and medium skills. Consumption spillovers from graduate residential inflows thus occur between higher and lower skilled.
PubDate: 2017-11-01
DOI: 10.1007/s00168-016-0754-9
Issue No: Vol. 59, No. 3 (2017)

• The influence of distance types on co-patenting and co-publishing in the
USA and Europe over time
• Authors: Rafael Lata; Sidonia von Proff; Thomas Brenner
Abstract: Abstract This study focuses on diverse dimensions of distance shaping collaboration in Europe and the USA during the time period 1999–2009. We take a comparative perspective by analysing two different collaboration networks (patents and publications) and two different economic areas, in order to examine differences in collaboration activities. In particular, we investigate how the collaboration intensity between regions has been influenced by spatial, technological, and cultural distance and whether these distances have lost importance over time in the distinct networks. The study adopts a panel spatial interaction modelling perspective. The results show that indeed the impact of various kinds of distances differs between Europe and the USA and changes over time.
PubDate: 2017-12-08
DOI: 10.1007/s00168-017-0857-y

• Regional determinants of economic resilience
• Authors: Paolo Di Caro; Ugo Fratesi
Abstract: Abstract The economic resilience approach recently spread among regional scientists and economic geographers has provided new challenges to empirical researchers interested in studying the overall temporary and persistent consequences of the recent crisis and, more broadly, economic shocks. One of the open issues in this literature is the identification of the determinants of resilience, that is, the factors that influence the evolutionary dynamic process of robustness and adaptability registered in particular places. The selected sample of papers in this special issue provides original contributions for answering the question about what determines regional economic resilience. The common findings of the contributions can be seen as quite robust by relying upon different measures of resilience, cases, methodologies and time periods. Three main conclusions arise from the special issue: most of the determinants of economic resilience show regularities across time and space. The factors that contribute to explain the economic performance of places in normal times are also useful for understanding the patterns observed during and after recessionary events. Policymakers can play an active role in sustaining resilient economies by addressing resources and efforts in the right policy areas without waiting for crises.
PubDate: 2017-11-30
DOI: 10.1007/s00168-017-0858-x

• Classifying vocational training markets
• Authors: Corinna Kleinert; Alexander Vosseler; Uwe Blien
Abstract: Abstract The German educational system is characterized by a large sector of dual vocational training, which facilitates integration into the labour market. This system creates a specific training market for school leavers, which is characterized by strong regional disparities. These differences as well as their consequences have not been systematically analysed in previous research. In a theory-guided analysis this paper examines empirically which structural ‘handicaps’ affect regional transition rates from school to training and how regional training markets may be classified according to these structural factors. To this end, a new method is applied which combines regression and cluster analysis to avoid arbitrariness in the selection of classification variables. It generates a well-interpretable classification of vocational education markets, which is of broad use in research and labour market policy. The method may be applied to solve a broad variety of similar research problems in regional science.
PubDate: 2017-11-15
DOI: 10.1007/s00168-017-0856-z

• Agglomeration externalities, competition and productivity: empirical
evidence from firms located in Ukraine
• Authors: Andrzej Cieślik; Iryna Gauger; Jan Jakub Michałek
Abstract: Abstract This paper studies role of agglomeration externalities and market structure in determination of total factor productivity (TFP) of Ukrainian firms, having controlled for individual firm characteristics. We use micro-level data for manufacturing and service sectors in years 2005 and 2013. Our empirical results confirm the importance of various agglomeration externalities as well as competition in determination of TFP of Ukrainian firms. In addition, we find the statistically significant link between the total factor productivity, intangible assets, capital intensity, firm size, ownership status and firm internationalization (exports and imports).
PubDate: 2017-10-19
DOI: 10.1007/s00168-017-0851-4

• Regional growth differences in China for 1995–2013: an empirical
integrative analysis of their sources
• Authors: Hongbo Wang; Dan Rickman
Abstract: Abstract An integrative empirical analysis of several regional economic outcome variables in China for the period of 1995–2013 reveal the major sources of regional growth differences in China. Patterns of growth in population, per capita income, gross regional product, housing prices and changes in unemployment rates are identified using principal components analysis. Regression analysis of principal component scores is applied to identify geographic and administrative status patterns in the sources of the growth. The analysis suggests that shifts in labor supply largely were responsible for the regional growth differences over the period, though shifts in labor demand were nearly equally as important. The results have implications for evaluating the success of regional development policies such as the Western Development Strategy.
PubDate: 2017-10-17
DOI: 10.1007/s00168-017-0847-0

• Interactions between regional public and private investment: evidence from
Japanese prefectures
• Authors: Tomomi Miyazaki
Abstract: Abstract This study examines the effects of government investment on private capital formation, considering both regional and sectoral distinctions in Japan. The empirical results show that a crowding-out effect is observed in rural areas for several industries that contribute to regional economic growth. This suggests that the allocation of public stimulus investment packages to stagnant regions in Japan might act as a regional growth constraint as well as an obstacle to the capital formation, and stagnant regions cannot evade the stagnation even if the central government plans economic stimuli toward such regions, including public investment.
PubDate: 2017-10-11
DOI: 10.1007/s00168-017-0852-3

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