Estimating Spatial Econometrics Models with Integrated Nested Laplace Approximation

Integrated Nested Laplace Approximation provides a fast and effective method for marginal inference on Bayesian hierarchical models. This methodology has been implemented in the R-INLA package which permits INLA to be used from within R statistical software. Although INLA is implemented as a general methodology, its use in practice is limited to the models implemented in the R-INLA package. Spatial autoregressive models are widely used in spatial econometrics but have until now been missing from the R-INLA package. In this paper, we describe the implementation and application of a new class of latent models in INLA made available through R-INLA. This new latent class implements a standard spatial lag model, which is widely used and that can be used to build more complex models in spatial econometrics. The implementation of this latent model in R-INLA also means that all the other features of INLA can be used for model fitting, model selection and inference in spatial econometrics, as will be shown in this paper. Finally, we will illustrate the use of this new latent model and its applications with two datasets based on Gaussian and binary outcomes

The Application Of Local Indicators For Categorical Data (LICD) In The Spatial Analysis Of Economic Development

Firstly, we identify classes of regions presenting different economic development levels using taxonomic methods of multivariate data analysis. Secondly, we apply a join-count test to examine spatial dependencies between regions. It examines the tendency to form the spatial clusters. The global test indicates general spatial interactions between regions, while local tests give detailed results separately for each region. The global test detects spatial clustering of economically poor regions but is statistically insignificant as regards well-developed regions. Thus, the local tests are also applied. They indicate the occurrence of five spatial clusters and three outliers in Poland. There are three clusters of wealth. Their development is based on a diffusion impact of regional economic centres. The areas of eastern and north western Poland include clusters of poverty. The first one is impeded by the presense of three indiviual growth centres, while the second one is out of range of diffusion influence of bigger agglomerations

Computing the Jacobian in spatial models : an applied survey

Despite attempts to get around the Jacobian in fitting spatial econometric models by using GMM and other approximations, it remains a central problem for maximum likelihood estimation. In principle, and for smaller data sets, the use of the eigenvalues of the spatial weights matrix provides a very rapid and satisfactory resolution. For somewhat larger problems, including those induced in spatial panel and dyadic (network) problems, solving the eigenproblem is not as attractive, and a number of alternatives have been proposed. This paper will survey chosen alternatives, and comment on their relative usefulness

Comparing estimation methods for spatial econometrics techniques using R

Recent advances in spatial econometrics model fitting techniques have made it more desirable to be able to compare results and timings. Results should correspond between implementations using different applications, while timings are more readily compared within a single application. A broad range of model fitting techniques are provided by the contributed R packages for spatial econometrics. These model fitting techniques are associated with methods for estimating impacts and some tests, which will also be presented and compared. This review constitutes an up-to-date demonstration of techniques now available in R, and mentions some that will shortly become more generally available

Spaces beyond the horizon? Alternative imaginative geographies between Europe and the Orient

Post-structuralist and post-colonial discourses in contemporary human geography often make reference to the works of Joseph Conrad, albeit not infrequently in an iconized fashion. This essay reviews some grounds for feeling that these readings are missing geographies of the Orient implicit not only in Conrad’s work, but in treatments of geographies of imprisonment and deportation east of the Vistula over centuries. Attention is drawn to the work of Adam Mickiewicz and Joseph Brodsky, and to the legacy of the czarist and soviet penal systems. The essay concludes by pointing to the contribution that broader, alternative views of empire and oppression may make in adding depth to our discourse

Dynamic externalities and regional manufacturing development in Poland

The impact of localization and urbanization economies on regional manufacturing development in Poland 1976-96 is assessed in terms of employment and the regional convergence or divergence of the economy. Current research on the role of dynamic production externalities in regional manufacturing development is examined, starting with a review of recent literature on the nature of such externalities in manufacturing location, and how positive externalities may influence the spatial clustering of manufacturing industries. The paper shows that radical changes have occurred in patterns of Polish regional manufacturing employment, both with regard to sectors and regions. Transition is refocussing the regional economy on strong regional centres, and on sectors regarded with little favour in the planned economy

After “Raising the Bar”: applied maximum likelihood estimation of families of models in spatial econometrics

Elhorst (2010) shows how the recent publication of LeSage and Pace (2009) in his expression “raises the bar” for our fitting of spatial econometrics models. By extending the family of models that deserve attention, Elhorst reveals the need to explore how they might be fitted, and discusses some alternatives. This paper attempts to take up this challenge with respect to implementation in the R spdep package for the maximum likelihood case, using a smaller data set to see whether earlier conclusions would be changed when newer techniques are used, and two larger data sets to examine model fitting issues

Open Source software and the knowledge economy: virtually free and virtually immeasurable

One of the most striking innovations to emerge with full vigour in the late 1990's, but building on earlier precedent, is Open Source software. While there are good technical reasons for releasing the source code of computer programs to anyone connected to the Internet, or willing to spend little more than the cost of a bottle of beer on a CDROM, the trend profoundly affects the measurement of research and technological development expenditure and investment. Since the software tools are not priced, knowledge, the practice of winning new knowledge, and the style in which new knowledge is won are sharply focused

Integrating GRASS 5.0 and R: GIS and modern statistics for data analysis

With the release of the open-source GIS GRASS 5.0 in early 1999, opportunities are presented for integration with the open-sourcestatistical data analysis programming environment. After reviewing these two software systems, an example is given of the advantages yielded by the complementing of GIS techniques with modern statistical analysis. The example shows how GTOPO30 digital elevation models, with a resolution of 30 seconds, may be subjected to geomorphometric analysis; the data are taken from the Kosovo region. In these examples, is run interactively within the GRASS 5.0 environment, transfering data by writing and reading text files; the operating system is Linux