Raising the bar (5)

Raising the bar (5). Spatial Economic Analysis. This editorial summarizes and comments on the papers published in this issue 12(1) so as to raise the bar in applied spatial economic research and highlight new trends. The first paper examines the impact of the level of education on the decision to migrate and finds that it is approximately twice as large if both variables are modelled simultaneously. The second paper is one of the first papers to introduce a spatial component to models of international environmental agreements and to develop an exciting overlap with New Economic Geography. The third paper provides a tool, applied to Beijing, with which urban economic planners can investigate the role of variation and selection mechanisms in cluster development and identify possible paths of growth. The fourth paper contributes to the existing literature on retail geography by examining the role of consumption possibilities as an urban amenity. The fifth paper develops a Bayesian estimator of a linear regression model with spatial lags among the dependent variable, the explanatory variables and the disturbances. Finally, the sixth paper develops a semi-parametric generalized method of moments (GMM) estimator for a spatial autoregressive model with space-varying coefficients of the explanatory variables and a spatial autoregressive coefficient common to all units.     

Raising the bar (10)

This editorial summarizes the papers published in issue 14(1) so as to raise the bar in applied spatial economic research and highlight new trends. The first paper applies the Shapley-based decomposition approach to determine the impact of firm-, linkage- and location-specific factors to the survival probability of enterprises. The second paper applies Bayesian comparison methods to identify simultaneously the most likely spatial econometric model and spatial weight matrix explaining new business creation. The third paper compares the performance of continuous and discrete approaches to explain subjective well-being across space. The fourth paper applies a multiple imputation approach to determine regional purchasing power parities at the NUTS-3 level using data available at the NUTS-2 level. Finally, the last paper constructs a regional input–output table for Japan from its national counterpart using and comparing the performance of four non-survey techniques.     

Raising the bar (6)

Raising the bar (6). Spatial Economic Analysis. This editorial summarizes and comments on the papers published in issue 12(4) so as to raise the bar in applied spatial economic research and highlight new trends. The first paper addresses the question of whether ‘jobs follow people’ or ‘people follow jobs’. The second paper develops a new methodology to determine functional regions. The third paper is a major contribution to the growing literature on new modelling approaches and applications of disaster impact models. The fourth paper focuses on the costs and benefits of higher education. The fifth paper develops a two-step procedure to identify endogenously spatial regimes in the first step using geographically weighted regression, and to account for spatial dependence in the second step. Finally, the sixth paper estimates a dynamic spatial panel data model to explain house prices and to show that restricted housing supply in the city of Cambridge, UK, has some undesirable labour market effects.     

Raising the bar (7)

This editorial summarises the papers published in issue 13.1 so as to raise the bar in applied spatial economic research and highlight new trends. The first paper adopts a scale neutral approach to investigate the spatial mechanisms that cause regional innovation and growth. The second paper claims that population-weighting when calculating indices of regional inequality might lead to inconsistent outcomes. The third paper estimates the effect of distance between family residence and higher education institution on a student's academic performance, thereby accounting for endogenous regressors. The fourth paper shows an inverted U-shaped relationship between economic development at region of origin and the propensity to migrate using a multilevel approach. The fifth paper provides spatial econometric evidence of price competition between sellers of used books on Amazon.com. The last paper estimates a hedonic housing price equation and parameterizes the spatial weight matrix to determine how far back in time buyers, sellers and realtors are looking at the housing market.     

Bootstrap J-Test for Panel Data Models with Spatially Dependent Error Components,a Spatial Lag and Additional Endogenous Variables

We develop a bootstrap J-test method for testing a panel model against one non-nested alternative when the competing specifications are estimated by Feasible Generalised Spatial Two Stage Least Squares/Generalised Method of Moments (FGS2SLS/GMM). Both models incorporate spatially correlated error components, thus accounting for spatial heterogeneity via random effects, and accommodate endogenous regressors other than the spatially lagged dependent variable. The proposed scheme is applied to a testing problem involving non-nested wage equations as motivated by the Wage Curve literature and the New Economic Geography theory. Results show that our bootstrap test is a reliable and effective procedure for correcting asymptotic reference critical values and distinguishing between the two rival hypotheses.     

Raising the bar (9)

ABSTRACT

This editorial summarizes the papers published in issue 13(4) so as to raise the bar in applied spatial economic research and highlight new trends. The first paper develops an economic geography model with trade costs in all sectors and different shares of unskilled labour in all locations. The second paper translates an economic geography model into a dynamic spatial econometric model and then estimates the unknown parameters to test for congestion spillover effects among Chinese cities. The following paper also investigates spillover effects, but of sovereign and banking risks across countries. The fourth paper empirically examines if a higher market potential results in higher average productivity and lower productivity dispersion of Italian retailers. The fifth paper demonstrates that modelling more than one spatial lag in the independent variables, using different specifications of the spatial weight matrix, can be used as a tool to correct for an omitted variable bias. The final paper develops a test for the existence of non-parametric non-linearities in a linear spatial econometric model.     

Raising the bar (4)

This editorial summarizes and comments on the papers published in issue 11(4) so as to raise the bar in applied spatial economic research and highlight new trends. The first paper deals with common factors and spatial dependence in the error term specification of a production function model. The second paper sets forth a New Economic Geography (NEG) model with production activities that vary in their complexity, so as to analyse the impact on specialization patterns across different regions. The third paper measures the efficiency of local public investments using a relatively unknown econometric technique in which the time span over which the variables in the regression equation are measured is increased by one time period every run. The fourth paper adopts a conditional quantile regression approach to determine the impact of people employed in informal jobs on the wage distribution in Colombia and five of its regions. Finally, the last paper proposes and tests two new Bayesian variable selection approaches for spatial econometric models.     

Raising the bar (8)

This editorial summarizes the papers published in issue 13(3) so as to raise the bar in applied spatial economic research and highlight new trends. The first paper challenges the home market hypothesis that large countries host more firms relative to their size than small countries by considering the lobbying activities of multinational firms. The second paper analyzes the implications of a spatial weight matrix used to estimate a spatial econometric model that depends on an endogenous economic variable. By adding a spatial context, the third paper provides a novel contribution to the literature on international norms in de facto measures of human rights performance. The fourth paper examines the determinants of accepting informal work in Poland. The fifth paper deals with non-stationarity and cointegration in a dynamic spatial econometric panel data model when the number of observations in the time – rather than in the cross-sectional– domain tends to infinity.     

Raising the bar (2)

In this editorial we summarise and comment on the papers published in issue 11.2 so as to raise the bar in applied spatial economic research and highlight new trends. The first paper analyses which regions in Europe were resilient to the great Recession and which ones were not. The second and the third develop a competing-destinations gravity model to explain respectively which hospitals people go to depending on their residential location and which regions migrants go to on entering Europe. The fourth proposes a Bayesian approach to obtain likely values if data on certain spatial units are missing. Finally, the last paper tries to explain the spreading of people in sprawling cities.     

Raising the bar (11)

This editorial summarizes the papers published in issue 14(2) so as to raise the bar in applied spatial economic research and highlight new trends. The first paper deals with past and current challenges for regional science research. The second paper investigates whether people living in deprived neighbourhoods have less chance of succeeding in a job application. The third paper finds evidence that real estate firms can avoid price competition when market shares of their allies increase in the vicinity. The fourth paper is methodological: it considers a spatial autoregressive (SAR) model with heterogeneous coefficients and extensively analyzes the impact of this extension on the direct and indirect effects estimates. The fifth paper proposes an innovative method to estimate the elements of the spatial weight matrix in a spatial econometric model. The final paper is econometric–theoretical: it proposes a new generalized method of moments (GMM) estimator of the coefficients of a SAR model if the error terms are heteroskedastic of an unknown form.     

On the Link between Volatility and Growth: A Spatial Econometrics Approach

This paper examines the link between macro volatility and economic growth in the lens of spatial econometrics. We present an unconstrained spatial Durbin Ramey-Ramey model. We test the extended model in a panel of 78 countries to investigate all the possible dimensions along which spatial interactions can affect the link between macro volatility and growth. In contrast to previous literature, we split the effects of volatility on growth into direct and indirect effects using partial derivative impacts approach. We found that both the direct and indirect effects of volatility on growth are negative; the latter effect suggesting the transmission of volatility shocks to neighbouring countries. Growth rates observed in neighbouring countries has a positive effect on growth rate of a particular country.     

Decomposing the declining volatility of long-term inflation expectations

The level and volatility of survey-based measures of long-term inflation expectations have come down dramatically over the past several decades. To capture these changes in inflation dynamics, we embed both short- and long-term expectations into a medium-scale VAR model with stochastic volatility. The model estimates attribute most of the marked decline in the volatility of expectations to smaller shocks to long-run inflation expectations. According to our estimates, the volatility of shocks plummeted in the early to mid-1980s, moved to a somewhat higher level that prevailed for much of the 1990s, and then declined to and remained at very low levels.     

Estimation of variance of housing prices using spatial conditional heteroskedasticity (SARCH) model with an application to Boston housing price data

In this paper we investigate housing price volatility within a spatial econometrics setting. We propose an extended spatial regression model of the real estate market that includes the effects of both conditional heteroskedasticity and spatial autocorrelation. Our suggested model has features similar to those of autoregressive conditional heteroskedasticity (ARCH) in the time-series context. We utilize the spatial ARCH (SARCH) model to analyze Boston housing price data used by Harrison and Rubinfeld (1978) and Gilley and Pace (1996). We show that measuring the variability of housing prices is an important issue and our SARCH model captures the conditional spatial variability of Boston housing prices. We argue that there is a different source of spatial variation, which is independent of traditional housing and neighborhood characteristics, and is captured by the SARCH model.     

SPATIAL LIMITED DEPENDENT VARIABLE MODELS: A REVIEW FOCUSED ON SPECIFICATION,ESTIMATION, AND HEALTH ECONOMICS APPLICATIONS

Modeling individual choices is one of the main aim in microeconometrics. Discrete choice models have been widely used to describe economic agents' utility functions and most of them play a paramount role in applied health economics. On the other hand, spatial econometrics collects a series of econometric tools, which are particularly useful when we deal with spatially distributed data sets. Accounting for spatial dependence can avoid inconsistency problems of the commonly used statistical estimators. However, the complex structure of spatial dependence in most of the nonlinear models still precludes a large diffusion of these spatial techniques. The purpose of this paper is then twofold. The former is to review the main methodological problems and their different solutions in spatial nonlinear modeling. The latter is to review their applications to health issues, especially those appeared in the last few years, by highlighting the main reasons why spatial discrete neighboring effects should be considered and suggesting possible future lines of development in this emerging field. Particular attention has been paid to cross‐sectional spatial discrete choice modeling. However, discussions on the main methodological advancements in other spatial limited dependent variable models and spatial panel data models are also included.     

Modeling regional economic dynamics: Spatial dependence,spatial heterogeneity and nonlinearities

Spatial modeling of economic phenomena requires the adoption of complex econometric tools, which allow us to deal with important methodological issues, such as spatial dependence, spatial unobserved heterogeneity and nonlinearities. In this paper we describe some recently developed econometric approaches (i.e. Spatial Autoregressive Semiparametric Geoadditive Models), which address the three issues simultaneously. We also illustrate the relative performance of these methods with an application to the case of house prices in the Lucas County.     

Raising the Bar (3)

This editorial summarizes and comments on the papers published in issue 11(3) so as to raise the bar in applied spatial economic research and highlight new trends. The first paper proposes spatial and a-spatial indicators to describe the networks of airline companies around the world. The second paper sets forth a two-regime gravity-type model with an endogenous threshold parameter to assess the effect of labour market conditions on interregional migration flows. The third paper utilizes micro-data to explain student migration flows to higher education institutions. The fourth paper is among the first to make use of simulation-based location quotients in a multiregional input–output model. Finally, the last paper provides a purely economic–theoretical model on cooperative limit pricing in the context of spatial competition.     

Instability spillovers in the banking sector: A spatial econometrics approach

In the study, we employ a dynamic spatial panel model to identify factors that are the sources of instability spillover in the banking sector. Using a sample of publicly listed banks, we document that the stability of a bank depends not only on its own characteristics and the macroeconomic conditions of its home country, but also on the stability of other banks in the same and other countries. We find weak evidence that the spillover effects are greater from domestic banks than from foreign ones. This study has significant implications for market regulators in terms of the role of country interdependence as a spillover mechanism during times of financial turbulence.     

Applied Spatial Econometrics: Raising the Bar

Abstract

This paper places the key issues and implications of the new ‘introductory’ book on spatial econometrics by James LeSage & Kelley Pace (2009) in a broader perspective: the argument in favour of the spatial Durbin model, the use of indirect effects as a more valid basis for testing whether spatial spillovers are significant, the use of Bayesian posterior model probabilities to determine which spatial weights matrix best describes the data, and the book's contribution to the literature on spatio-temporal models. The main conclusion is that the state of the art of applied spatial econometrics has taken a step change with the publication of this book.

Relever le niveau de l'économetrie spatial appliquée

RÉSUMÉ La présente communication place les principales questions et implications du nouvel ouvrage d'introduction sur l'économétries spatiale de James LeSage & Kelley Pace (2009) dans un contexte plus général: l'argument favorisant le modèle spatial de Durbin, l'emploi d'effets indirects comme base plus valable pour évaluer l'aspect significatif des déversements spatiaux, l'emploi des probabilités d'un modèle baysien postérieur pour évaluer laquelle des matrices de poids spatiaux décrit le mieux les donnes, et la contribution de l'ouvrage la documentation sur les modèles spatio-temporels. La principale conclusion est qu'avec la publication de cet ouvrage, l'état de l'art de l'économétries spatiale applique a effectué un grand pas en avant.

Alzar el nivel de la econometría espacial aplicada

RÉSUMÉ Este trabajo plantea las cuestiones e implicaciones clave del nuevo libro introductorio sobre económetra espacial de James LeSage & Kelley Pace (2009) dentro de una perspectiva más amplia: el argumento a favor del modelo espacial Durbin, el uso de efectos indirectos como una base más válida para poner a prueba si los desbordamientos espaciales son significativos, el uso de probabilidades posteriores bayesianas para descubrir que matriz de pesos espaciales describe mejor los datos, y la contribución del libro a la bibliógrafa sobre modelos espaciotemporales. La principal conclusión es que la econometría espacial aplicada más avanzada ha experimentado un cambio radical con la publicación de este libro.