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The innovativeness of a firm not only improves its own survival chances but also can generate externalities on its neighbouring firms. We empirically examine the role of agglomeration economies in how innovativeness affects firm survival in southern Italy, using spatial weights to model spillovers. Spatial Durbin probit model estimates confirm that innovation is an important determinant of firm survival, not only for firms that are themselves innovative but also for those located close to other innovative firms. Adequate definitions of spatial scale and spatial weights are important. Spillover benefits are enhanced by agglomeration economies, but only at a very local scale.

This editorial summarizes the papers published in issue 16(4) (2021). The first paper adopts a higher order spatial autoregressive model with endogenous spatial weight matrices. The second paper in...

This editorial summarizes the papers published in issue 16(3) (2021) in order to raise the bar in applied spatial economic research and highlight new trends and knowledge. The first paper analyses ...

There are missing links between research and policy that can be filled by better information on the real world. This is important not only to evaluate the contribution of research to the policymakers and to society, but also to design policies based on evidence. Three models for meeting such objectives are presented, emphasizing the role of (a) journals, (b) government and (c) researchers. We provide outline examples of the three approaches, focussing on regional demographic policies in Portugal. Los eslabones perdidos que hay entre la investigacion y las politicas pueden completarse con una mejor informacion sobre el mundo real. Esto es importante no solo para evaluar la contribucion de la investigacion a los responsables politicos y a la sociedad, sino tambien para disenar politicas basadas en la evidencia. Con el fin de alcanzar dichos objetivos se presentan tres modelos, en los que se destaca el papel de (a) las revistas cientificas, (b) el gobierno y (c) los investigadores. Se aportan descripciones de ejemplos de los tres enfoques, centrados en las politicas demograficas regionales de Portugal. 研究と政策との間には、現実世界に関するより良い情報によって埋めることができるギャップがある。これは政策立案者や社会に対する研究の貢献度を評価するだけでなく、エビデンスに基づいた政策の立案においても重要である。この目的のための3つのモデルを提示し、(a)研究雑誌、(b)政府、(c)研究者の役割に注目する。ポルトガルの地域の人口政策に焦点を当て、3つのアプローチの概要例を提示する。

This editorial summarises the papers published in issue 15.4 in order to raise the bar in applied spatial economic research and highlight new trends and knowledge. The first paper challenges the standard notion that more growth is better. The second paper challenges macroeconomic models by looking at them from a regional micro-grounded lens, where the effect of productivity shocks depends on the distribution of economic activity and the locations where shocks occur. The third paper investigates the wage-productivity nexus using the latest techniques on cross-sectional dependence. The fourth paper introduces a new method to determine regional price differentials. The fifth paper tests whether economic-theoretical insights obtained from urban economic models apply not only to cities in developed countries but also to those in developing countries. The sixth paper sets out an estimation method for a spatial random coefficients model for clusters of observations. The seventh paper proposes a new method for regionalizing national input-output tables. The final paper focuses on Big Data and its role in regional growth.

This editorial summarizes the papers published in issue 15(2) so as to raise the bar in applied spatial economic research and highlight new trends. The first paper combines a conditionally autoregressive process from the spatial statistics literature with a spatial Durbin error model from the spatial econometrics literature. The second paper feeds a multistage and multilevel data envelopment analysis with a microeconomic foundation. The third paper provides empirical evidence that Flegg's location quotient combined with a gravity model produces the most accurate interregional input-output multipliers. The fourth paper investigates the impact of inventor networks on the number of patents per capita in Brazil.

This editorial summarises the papers published in issue 14(4) so as to raise the bar in applied spatial economic research and highlight new trends. The first paper analyses the impact of re-exports on bilateral trade data. The second paper proposes a new measure for the popular smart specialisation index (S3). The third paper proposes a new solution for the so-called reflection problem in spatial or social interaction models. The fourth paper analyses bankruptcy spillovers in the state of Maryland. The final paper estimates a system of equations to analyse the mutual relationship between the domestic migration of highly-skilled graduates and innovation and productivity in U.S. states.

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.

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.

Purpose Literature, spanning industrial organization and strategic management disciplines, uses variance decomposition to understand the relative importance of firm, industry and business group effects in shaping profitability variations. Some literature analyzes firm profitability under transition to liberalization. Previous research has taken a static before-and-after view on institutional change. This paper aims to focus on the dynamic process of liberalization in India, analyzing how different institutional regime changes alter firm behavior leading to changes in profitability patterns. Design/methodology/approach Based on a panel data set of several thousand Indian firms, spanning the 26-year period between 1980-1981 and 2005-2006, the authors determine the relative importance of firm, industry and business group effects in explaining manufacturing firms’ profitability variances across different institutional phases. The authors evaluate three propositions that help assess transition dynamics between phases. They determine the quantum of catch-up or falling behind by firms. Findings Different industries emerge as profitability leaders, as the economy progresses through different liberalization phases. Business groups that have been more effective in resource appropriation, rent-seeking, politician management and non-market activities in a controlled regime are replaced as profit leaders by those that, in a free-market economy, can be capable of intra-business resource allocation tasks and leveraging corporate capabilities. Originality/value The approach demonstrates how to analyze the underlying detailed structure of firm-level data, and performance outcomes, to derive nuanced interpretation of factors giving rise to the effects that explain profitability variances, and how to assess the way these effects behave over time. The dynamic evidence-based approach highlights what factors matter, where, when and why, in influencing profitability variances, which are a key dimension of industrial and economic performance.

The papers in this special issue cover a wide range of areas in the methodology and application of spatial econometrics. The first develops a generalized method of moments (GMM) estimator for the spatial regression model from a second-order approximation to the maximum likelihood (ML). The second develops Bayesian estimation in a stochastic frontier model with network dependence in efficiencies, with application to industry dynamics. The third studies cross-country convergence under the Lotka–Volterra model and obtains new insights into spatial spillovers. The penultimate paper develops robust specification tests for the social interactions model under both ML and GMM frameworks. The final paper proposes identification and GMM estimation in a high-order spatial autoregressive model with heterogeneity, common factors and spatial error dependence.

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 (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.

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.

Functional regression over irregular domains: variation in the shadow price of living space. Spatial Economic Analysis. Hedonic house price models need to account for spatial heterogeneity – the variation in the functional surface of shadow prices. In this context, the complexity of spatial domains raises issues for traditional spatial econometric methods. Specifically, discontinuities in the spatial surface need to be accounted for, including irregular boundaries, peninsulas and interior holes. Motivated by an application to housing markets, we develop a method for estimating the functional surface of a regression coefficient that varies over such an irregular spatial domain. Spatially varying coefficients for a specific regressor are estimated by a combination of three smoothing problems using splines based on finite element analysis. The effect of additional regressors is also allowed. We verify finite sample performance using a simulation study, and develop an application to the Aveiro–Ilhavo ...

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.

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.

In addition to the three special issue papers, issue 15.1 contains two papers on input-output analysis. The first paper provides a thorough analysis of the cross entropy (CE) method to build input-output tables at sub-territorial levels or to update them in time. The second paper proposes a spatial input-output location quotient accounting for the co-location of related industries within the same area and for spatial spillovers of concentration into neighboring areas.

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.

Spatial heterogeneity, spatial dependence and spatial scale constitute key features of spatial analysis of housing markets. However, the common practice of modelling spatial dependence as being generated by spatial interactions through a known spatial weights matrix is often not satisfactory. While existing estimators of spatial weights matrices are based on repeat sales or panel data, this paper takes the approach to a cross-section setting. Specifically, based on an a priori definition of housing submarkets and the assumption of a multifactor model, we develop maximum likelihood methodology to estimate hedonic models that facilitate understanding of both spatial heterogeneity and spatial interactions. The methodology, based on statistical orthogonal factor analysis, applied to the urban housing market of Aveiro (Portugal) at two different spatial scales, provides exciting inferences on the spatial structure of the housing market. RESUME L'heterogeneite spatiale, la dependance spatiale et l’eche...

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. ResumeCet editorial resume et commente les articles parus dans le numero 11(3) afin de placer la barre de la recherche economique spatiale appliquee plus haut et de souligner les nouvelles tendances. Le premier article propose des indicateurs spatiaux et non-spatiaux pour presenter les reseaux de compagnies aeriennes partout dans le monde. Le deuxieme article expose un modele de gravite type a deux regimes dote d'un parametre de seuil endogene pour evaluer l'impact des conditions du marche du travail sur les flux migratoires interregionaux. Le troisieme article emploie des donnees microeconomiques afin d'expliquer les flux migratoires des etudiants a destination des etablissements d'enseignement superieur. Le quatrieme article compte parmi les premiers a se servir des quotients de localisation sur base de la simulation dans le contexte d'un modele des entrees-sorties multiregional. Pour terminer, le dernier article fournit un modele purement economico-theorique sur les prix limites des cooperatives dans le cadre de la concurrence spatiale. ResumenEste editorial es un resumen y una observacion acerca de los articulos publicados en el numero 11(3) con la finalidad de elevar el liston en la investigacion economica espacial aplicada y resaltar las nuevas tendencias. En el primer articulo se proponen indicadores espaciales y no espaciales para describir las redes de las companias aereas de todo el mundo. En el segundo articulo se presenta un modelo de tipo gravitacional de dos regimenes con un parametro de umbral endogeno para evaluar el efecto de las condiciones del mercado laboral en los flujos de migracion interregional. En el tercer articulo se utilizan datos micro para explicar los flujos de migracion estudiantil a centros de educacion superior. El cuarto articulo es uno de los primeros en utilizar cocientes de localizacion basados en una simulacion en un modelo plurirregional de entradas y salidas. Finalmente, el ultimo articulo ofrece un modelo puramente economico-teorico sobre el precio del limite de las cooperativas en el contexto de la competencia espacial. ????????????????????????, ????????????, ???????????????????????????????????????????????????, ??????????????????????????????????????????, ????????????????????????????????????????????????????????????, ???????????????, ???????????

While much of the literature on cross-section dependence has focused on estimation of the regression coefficients in the underlying model, estimation and inferences on the magnitude and strength of spillovers and interactions has been largely ignored. At the same time, such inferences are important in many applications, not least because they have structural interpretations and provide useful inferences and structural explanation for the strength of any interactions. In this paper we propose GMM methods designed to uncover underlying (hidden) interactions in social networks and committees. Special attention is paid to the interval censored regression model. Small sample performance is examined through a Monte Carlo study. Our methods are applied to a study of committee decision making within the Bank of England's Monetary Policy Committee. RESUME Bien qu'une grande partie de la litterature sur la dependance transversale se soit concentree sur l'estimation des coefficients de regression dans le mo...