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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.

Summary This paper investigates the quasi-maximum likelihood estimation of short dynamic panel data models. We consider their estimation on both fixed effects and random effects specifications and propose a Hausman test when exogenous variables are present. For a dynamic panel model, initial conditions play important roles in model structure and estimation, and they give rise to a between equation under the random effects framework. With the between equation properly defined, we show that the random effects model can be decomposed into a within equation and a between equation; hence, the random effects estimate is a pooling of the within and between estimates. Thus, our paper extends the pooling in the static panel data model (Maddala, 1971a) to the setting of dynamic panel data. This decomposition of a dynamic panel data model is revealing and valuable for estimation and the formulation of a Hausman test to test the possible correlation of individual effects with included regressors. Monte Carlo experiments are conducted to investigate the finite sample performance of estimators and the Hausman test. An empirical application of growth convergence in OECD countries is provided.

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.

Spatial econometrics relies on the spatial weights matrix to specify the cross-sectional dependence; however, the candidate spatial weights matrices might not be unique. This paper proposes a model selection procedure to choose a weights matrix from several candidates by using a Mallows type criterion. We prove that when the true weights matrix is not in the candidates, the procedure is asymptotically optimal in the sense of minimizing the squared loss; otherwise, the procedure can select the true weights matrix consistently. We then propose a model averaging procedure to reduce the squared loss. We also provide procedures for the spatial model with heteroscedasticity and endogenous regressors and the model with both spatial lag and spatial error. Monte Carlo experiments show that proposed procedures have satisfactory finite sample performances. We apply the model selection and model averaging procedures to study the market integration in China using historical rice prices.

This paper empirically examines international knowledge spillover through bilateral trade. We extend the knowledge production function using a spatial autoregressive term and time-varying weights matrices, and we estimate this model using a sample of 30 countries over the period 1975–2010. We find that there is a positive spillover effect of innovation from one country to its trade partners through bilateral import flows. The spillover effect accounts for approximately 1.3%–3.6% of the total effect of R&D input on innovation output over time.

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.

In spatial panel data models, when a spatial weights matrix is constructed from economic or social distance, spatial weights could be endogenous and also time varying. This paper presents model specification and proposes QMLE estimation of spatial dynamic panel data models with endogenous time varying spatial weights matrices. Asymptotic properties of the proposed QMLE are rigorously established. We extend the notion of spatial near-epoch dependence to allow time dependence. By using spatial-time LLN for near-epoch dependence process and CLT for martingale difference sequence, we establish the consistency and asymptotic normality of QMLE. Monte Carlo experiments show that the proposed estimators have satisfactory finite sample performance.

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.

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.

This paper first presents simple methods for conducting up to third-order bias and variance corrections for the quasi maximum likelihood (QML) estimators of the spatial parameter(s) in the fixed effects spatial panel data (FE-SPD) models. Then, it shows how the bias and variance corrections lead to refined t-ratios for spatial effects and for covariate effects. The implementation of these corrections depends on the proposed bootstrap methods of which validity is established. Monte Carlo results reveal that (i) the QML estimators of the spatial parameters can be quite biased, (ii) a second-order bias correction effectively removes the bias, and (iii) the proposed t-ratios are much more reliable than the usual t-ratios.

This paper investigates the first difference (FD) estimation of spatial dynamic panel data (SDPD) models with fixed effects using quasi-maximum likelihood (QML) approach, where both n and T are large. We show that the QML estimation for the SDPD with FD can be reduced to the direct estimation of individual effects, except for the estimation of variance parameter. After bias correction, these two approaches would yield asymptotically equivalent estimates for all parameters including the variance parameter. Our results extend the equivalence of LSDV estimate and GLS estimate of FD equation in the panel regression model to the spatial dynamic panel model, which includes the conventional dynamic panel as a special case. Our analysis highlights the importance of initial values rather than the many fixed effects in spatial panel 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.

Promotion of local leaders in China is decided by their upper-level governments which evaluate their performance based largely on local economic growth. Such a promotion scheme leads to tournament competition among local government leaders of the same level. We test the hypothesis of tournament competition by studying the spatial effects across Chinese prefectural-level cities. Employing spatial econometrics tools, we document a strong spatial effect for city-level total investment which fuels short-term economic growth. This spatial effect is shown to occur only for cities within the same province, but not for neighboring cities located in different provinces. We also find that within the same province, the spatial effect mainly exists for cities with similar economic ranking but not for cities that are geographically proximate. The spatial effect tends to diminish for city leaders who are close to the end of their political careers. These findings suggest that the spatial effect for investment is driven by strategic interactions among political rivals in tournament competition. We rule out alternative factors, such as economic spillovers and tax competition, as the key drivers of the observed spatial effect.

In this editorial, we summarize and comment on the papers published in issue 11.1 so as to raise the bar in applied spatial economic research and highlight new trends. The first paper employs the J-test to discriminate between two economic-theoretical explanations for the wage curve. The second applies a two-step ML procedure to measure the impact of volatility on economic growth. The third tests for endogeneity in the Spatial lag of X (SLX) model and whether or not the model should be extended to contain a spatial lag. The fourth utilizes the gravity model to test whether or not grids should be merged into larger units of observations. Finally, the last adopts a time-space recursive model to test the ripple effect and (linguistic) border effect hypotheses on housing prices in Belgium.

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.

Identi…cation of a spatial Durbin model is a concern in the spatial econometrics literature. The concern is similar to the identi…cation of the endogenous eect, the contextual eect and correlation eect in social interactions and networks. This paper considers identi…cation of spatial Durbin dynamic panel models under 2SLS and ML estimations. We show that the parameters are generally identi…ed via 2SLS moment relations or expected log likelihood or quasi-likelihood functions. Although identi…cation might fail under some particular situations with the 2SLS moments, parameters can be generally identi…ed via the quasi-likelihood function of a model with intuitively appealing identi…cation conditions. Monte Carlo experiments suggest that omitting relevant Durbin terms can result in signi…cant biases in regression estimates, while including an irrelevant Durbin term causes no obvious loss of e¢ ciency. Empirical illustration of the international spillover of economic growth through bilateral trade shows that inclusion of Durbin terms can be important.

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. ????????????????????????, ????????????, ???????????????????????????????????????????????????, ??????????????????????????????????????????, ????????????????????????????????????????????????????????????, ???????????????, ???????????