Bernard Fingleton

Where is the Economics in Spatial Econometrics

Spatial econometrics has been criticized by some economists because some model specifications have been driven by data-analytic considerations rather than having a firm foundation in economic theory. In particular this applies to the so-called W matrix, which is integral to the structure of endogenous and exogenous spatial lags, and to spatial error processes, and which are almost the sine qua non of spatial econometrics. Moreover it has been suggested that the significance of a spatially lagged dependent variable involving W may be misleading, since it may be simply picking up the effects of omitted spatially dependent variables, incorrectly suggesting the existence of a spillover mechanism. In this paper we review the theoretical and empirical rationale for network dependence and spatial externalities as embodied in spatially lagged variables, arguing that failing to acknowledge their presence at least leads to biased inference, can be a cause of inconsistent estimation, and leads to an incorrect understanding of true causal processes.

Estimates of Time to Economic Convergence: An Analysis of Regions of the European Union

According to the simplest neoclassical theory, closer integration will ultimately eliminate the current differences in per capita incomes between European Union (EU) regions. Models based on the Keynesian tradition and endogenous growth theory suggest different outcomes. This article looks at the evidence for convergence along neoclassical lines and also from a point of view that accepts the critique of neoclassical theory. Estimates are made of the time it will take for two different forms of equilibrium to be realized. From a neoclassical perspective, there is only weak evidence that EU regions are converging in terms of their output per capita, requiring more than two centuries for approximate convergence to be achieved. From a non-neoclassical perspective, stochastic equilibrium will require more than three centuries, although the hypothesis that the regions have already achieved stochastic equilibrium cannot be dismissed.

Recessionary Shocks and Regional Employment: Evidence on the Resilience of U.K. Regions

We analyze the resilience of U.K. regions to employment shocks. Two basic notions of resilience are distinguished. With engineering resilience, there is an underlying stable growth path to which a regional economy rebounds following a shock. With ecological resilience, shocks can permanently affect the growth path of the regional economy. Our data set consists of quarterly employment series for 12 U.K. regions (NUTS I) for the period 1971–2010. Using a seemingly unrelated regression (SUR) model specification, we test for the relevance of (engineering) resilience of U.K. regional employment to the four recessionary shocks in our sample. It turns out that U.K. regions do indeed differ in their resilience, but that these differences mainly concern the initial resistance to these shocks and not so much the recovery stage. The SUR model does not allow shocks to have permanent effects and it also does not take the possibility of time differentiated shock spillovers between the 12 regions into account. To this end, we also estimate a vector error‐correction model (VECM) specification where employment shocks can have permanent effects and where also interregional employment linkages are included. We find that employment shocks typically have permanent effects when it concerns the own‐region effects. Permanent effects can also be found for the impact on other regions but the interregional effects are typically only significant for nearby regions.

European regional growth

This book is the outcome of three major influences. First, the ongoing integration of the European regional economies and the need to understand what this means for European economic and social cohesion. Second, the development of geo-economic theories ranging from neoclassical growth theory and endogenous growth theory to new theories of economic geography. Third, the development of techniques of spatial data analysis, simulation, data visualization and spatial econometrics. The outcome is a collection of chapters which apply these methods, motivated by a variety of theoretical stances, in order to advance our understanding of European regional growth. The book provides powerful and detailed analyses of the causes of income, productivity and employment variations across Europes regions, and insights into their future prospects.

Specification and Testing of Markov Chain Models: An Application to Convergence in the European Union

Recently Markov chains have been used to analyze the convergence properties of national and regional per capita incomes. This paper highlights their applicability and importance for economists and illustrates some of the potential pitfalls associated with this approach. The empirical conclusions, based on data for the period 1975 to 1993, are that the regions of the European Union appear to be converging to a form of equilibrium characterized by stable proportions of economies at a range of output per capita levels, and by a permanent chance of mobility between all levels, consistent with the existence of multiple steady states across countries. Copyright 1997 by Blackwell Publishing Ltd

EXTERNALITIES, ECONOMIC GEOGRAPHY, AND SPATIAL ECONOMETRICS: CONCEPTUAL AND MODELING DEVELOPMENTS

On the assumption that it is sometimes necessary to take a step sideways to make progress, this article describes the author’s preferred spatial econometric modeling approach based around recent theory developed in the field of urban economics. This has many features in common with geographical economics but is seen as more amenable to the analysis of externalities and to the development of new, more realistic, economic geography theory.

A Generalized Method of Moments Estimator for a Spatial Panel Model with an Endogenous Spatial Lag and Spatial Moving Average Errors

Abstract This paper proposes a new generalized method of moments (GMM) estimator for spatial panel models with spatial moving average errors combined with a spatially autoregressive dependent variable. Monte Carlo results are given suggesting that the GMM estimator is consistent. The estimator is applied to English real estate price data.

Spatial Econometrics, Economic Geography, Dynamics and Equilibrium: A ‘Third Way’?

An important item of agreement between the ‘new’ economic geography and economic geography ‘proper’ is the role of increasing returns in regional economic development. This provides a focal point for the model proposed in this paper, which suggests a ‘third way’ somewhere between the analysis provided by these ‘two’ competing modes of explanation. The paper provides empirical evidence supporting the proposed model using data on manufacturing productivity growth across 178 NUTS2 regions of the European Union. The paper also includes expressions for an equilibrium implied by the fitted model and argues that this helps to identify the proposed ‘third’ way as an approach which is clearly different from the first two ways.

Estimating and Forecasting with a Dynamic Spatial Panel Data Model

This paper focuses on the estimation and predictive performance of several estimators for the dynamic and autoregressive spatial lag panel data model with spatially correlated disturbances. In the spirit of Arellano and Bond (1991) and Mutl (2006), a dynamic spatial GMM estimator is proposed based on Kapoor, Kelejian and Prucha (2007) for the Spatial AutoRegressive (SAR) error model. The main idea is to mix non-spatial and spatial instruments to obtain consistent estimates of the parameters. Then, a linear predictor of this spatial dynamic model is derived. Using Monte Carlo simulations, we compare the performance of the GMM spatial estimator to that of spatial and non-spatial estimators and illustrate our approach with an application to new economic geography.

Regional economic growth and convergence: insights from a spatial econometric perspective

Economists, economic geographers and regional scientists have suggested different and contrasting explanations of why regions grow at different rates, and what kind of convergence, if any, one might expect from a system of interacting regions. Despite significant differences of approach, there are nevertheless common themes arising from the literature which bring an element of cohesion to a diverse subject matter, namely the relevance for understanding of returns to scale, externalities and catch up mechanisms, and the role of exogenous shocks in real-world turbulence. The chapter first reviews the growth literature, emphasising the importance of these themes, and sets the modelling approach adopted in the chapter in the context of the wider literature. It then gives new expressions for the equilibrium implied by various related models, and an iterative approach is developed to accommodate turbulence leading to “stochastic equilibrium.” As an illustration of the potential of the general methodology, the chapter finally focuses on a preferred single equation spatial econometric model (Anselin, 1988b; Anselin and Florax, 1995b). This model leads to substantive empirical evidence regarding causes of productivity growth variations, and the parameter estimates are used to calculate steady-states and stochastic equilibrium for manufacturing productivity ratios for 178 regions of the European Union (EU) (Armstrong, 1995; Cheshire and Carbonaro, 1995).