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This cumulative dissertation consists of five chapters. In terms of research content, my thesis can be divided into two parts. Part one examines local interactions and spillover effects between small regional governments using spatial econometric methods. The second part focuses on patterns within municipalities and inspects which institutions of citizen participation, elections and local petitions, influence local housing policies. ...

This cumulative dissertation consists of five chapters. In terms of research content, my thesis can be divided into two parts. Part one examines local interactions and spillover effects between small regional governments using spatial econometric methods. The second part focuses on patterns within municipalities and inspects which institutions of citizen participation, elections and local petitions, influence local housing policies. ...

AbstractResource depletion and environmental pollution have seriously restricted the sustainable development of China's economy in recent years. How to transform the extensive growth mode to the intensive growth mode and realize the green development of economy is a great challenge for China. In this paper, we use the non‐radial and non‐angle Slack‐based Model (SBM) considering the undesired output, combined with the Malmquist–Luenberger productivity index, to measure regional green total factor productivity (GTFP). By constructing the green output density function, the theoretical model of the relationship between regional GTFP and industrial agglomeration is deduced, and the theoretical mechanism of the influence of industrial agglomeration on regional GTFP is analyzed. Based on panel data of 243 cities at the prefecture level in China from 2010 to 2019, this article employs the dynamic spatial panel model to empirically estimate the impact of industrial agglomeration on regional GTFP. The empirical results show that regional GTFP shows significant spatial autocorrelation and spatial clustering characteristics. The manufacturing agglomeration has significant negative impact on regional GTFP and produces negative spatial spillover effect on the surrounding regions, but does not produce congestion effect. The producer services agglomeration significantly improves regional GTFP and produces positive spatial spillover effect on the surrounding regions, and leads to congestion effect. The co‐agglomeration of producer services and manufacturing has significantly promoted the improvement of regional GTFP and produces positive spatial spillover effect on the surrounding regions. Finally, this article puts forward policy suggestions on how to promote regional GTFP and achieve green development from the perspective of industrial agglomeration.

This volume focuses on econometric models that confront estimation and inference issues occurring when sample data exhibit spatial or spatiotemporal dependence. This can arise when decisions or transactions of economic agents are related to the behaviour of nearby agents. Dependence of one observation on neighbouring observations violates the typical assumption of independence made in regression analysis. Contributions to this volume by leading experts in the field of spatial econometrics provide details regarding estimation and inference based on a variety of econometric methods including, maximum likelihood, Bayesian and hierarchical Bayes, instrumental variables, generalized method of moments, maximum entropy, non-parametric and spatiotemporal. An overview of spatial econometric models and methods is provided that places contributions to this volume in the context of existing literature. New methods for estimation and inference are introduced in this volume and Monte Carlo comparisons of existing methods are described. In addition to topics involving estimation and inference, approaches to model comparison and selection are set forth along with new tests for spatial dependence and functional form. These methods are applied to a variety of economic problems including: hedonic real estate pricing, agricultural harvests and disaster payments, voting behaviour, identification of edge cities, and regional labour markets. The volume is supported by a web site containing data sets and software to implement many of the methods described by contributors to this volume

The work discussed in Bivand and Brunstad (2003) was an attempt to throw light on apparent variability in regional convergence in relation to agriculture as a sector subject to powerful political measures, in Western Europe, 1989 1999. We tried to explore the possibility that some of the observed specification issues in current results are rooted in neglecting agricultural policy interventions, within the limitations imposed by data available. We also attempted to use this as a case setting for evaluating the appropriateness of geographically weighted regression (GWR) as a technique for assessing coef- ficient variability, over and above for instance country dummies, but possibly reflecting missing variables or other specification problems. The present study takes up a number of points made in conclusion in that paper. Since it is possible that the non-stationarity found there is related to further missing variables, including the inadequacy of the way in which agricultural subsidies are represented, we attempt to replace the agriculture variables with better estimates of producer subsidy equivalents for the base year. We also look at ways of handling changes in agricultural policy regime occurring between years and T. This raises the further challenge of looking at both spatial and temporal dimensions at the same time, which we will discuss, but are not likely to resolve satisfactorily. On the technical side, the tests on GWR estimates also need to be more firmly established. The GWR results also need to be tested for spatial autocorrelation, and re-worked in an adaptive weighting framework, although GWR does already involve a spatial weighting of the observations themselves. The paper is therefore also an account of the development of software contributed to the R project (R Development Core Team, 2004) as packages, in particular the spdep package for spatial econometrics, and the spgwr package for GWR fitting. In particular, specific issues regarding the handling of the Jacobian in fitting spatial simultaneous autoregressive (SAR) models, and in interpreting GWR output will be discussed. These will be set in the context of on-going work on semi-parametric spatial filtering, which it is hoped to add to spdep following contributions by Michael Tiefelsdorf, so that the weaknesses and strengths of alternative approaches can be compared. Concentrating on implementations in R is justified by the preliminary nature of many of these methods requiring open source and replicable statistical research approaches, so that others can, if they wish, see how results were calculated. One such technical issue is the representation of neighbours in the various approaches, and of the impact of symmetry requirements in conditional autoregressive (CAR) models typically used in MCMC estimation using Open- BUGS and elsewhere. Indeed, in many SAR models, symmetry is also required, or at least underlying symmetry, with the weights matrix in the rowstandardised weighting scheme typically being similar to a symmetric matrix. Using the Western European regional growth data augmented with agricultural policy variables, we will try to explore how far some as-yet unresolved technical questions impede progress with substantive interpretation. We will also try to show how these questions may be handled in other software settings, and how data can be moved between software platforms for analysis. In conclusion, the paper has two threads, one focussing on the analysis of the relationships between regional growth and agricultural policy, generating models needing testing, while the other attempts to meet the software demands generated in the first thread, and to incorporate on-going research in spatial data-analytic methods to respond adequately to the potential importance of the substantive research question.

This cumulative dissertation consists of five chapters. In terms of research content, my thesis can be divided into two parts. Part one examines local interactions and spillover effects between small regional governments using spatial econometric methods. The second part focuses on patterns within municipalities and inspects which institutions of citizen participation, elections and local petitions, influence local housing policies. ; Diese kumulative Dissertation besteht aus fünf Kapiteln und kann inhaltlich zweigeteilt betrachtet werden. Im ersten Teil werden lokale Interaktionen und Übertragungseffekte zwischen kleinen regionalen Verwaltungseinheiten unter Verwendung von regionalökonometrischer Methoden untersucht. Der zweite Teil untersucht Zusammenhänge innerhalb von Gemeinden und untersucht welche Instrumentarien lokaler Politikbeteiligung, Kommunalwahlen und lokale Bürgerbegehren, einen Einfluss auf die örtliche Wohnungspolitik haben.

AbstractThis study evaluates the impact of next‐generation‐access network coverage on the innovation efficiency of 278 Portuguese municipalities through a spatial panel data analysis focused on the period 2012–2015. We find evidence that the additional territorial coverage of next‐generation access networks has a significant, negative, indirect, and permanent effect on the innovation efficiency of Portuguese municipalities. Other results include significant time dependence effects and stronger marginal effects in the long run. Several extensions reinforce the qualitative nature of benchmark outcomes. From a regulatory point of view, this research identifies a trade‐off in the Portuguese telecommunications industry: universal (restricted) access to next‐generation access networks can reduce (improve) the innovation efficiency of Portuguese municipalities, respectively.