Spatial Econometric Interaction Modelling
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| Author | : Roberto Patuelli |
| Publisher | : Springer |
| Total Pages | : 466 |
| Release | : 2016-07-25 |
| Genre | : Business & Economics |
| ISBN | : 3319301969 |
This contributed volume applies spatial and space-time econometric methods to spatial interaction modeling. The first part of the book addresses general cutting-edge methodological questions in spatial econometric interaction modeling, which concern aspects such as coefficient interpretation, constrained estimation, and scale effects. The second part deals with technical solutions to particular estimation issues, such as intraregional flows, Bayesian PPML and VAR estimation. The final part presents a number of empirical applications, ranging from interregional tourism competition and domestic trade to space-time migration modeling and residential relocation.
| Author | : Harry Kelejian |
| Publisher | : Academic Press |
| Total Pages | : 460 |
| Release | : 2017-07-20 |
| Genre | : Business & Economics |
| ISBN | : 0128133929 |
Spatial Econometrics provides a modern, powerful and flexible skillset to early career researchers interested in entering this rapidly expanding discipline. It articulates the principles and current practice of modern spatial econometrics and spatial statistics, combining rigorous depth of presentation with unusual depth of coverage. Introducing and formalizing the principles of, and 'need' for, models which define spatial interactions, the book provides a comprehensive framework for almost every major facet of modern science. Subjects covered at length include spatial regression models, weighting matrices, estimation procedures and the complications associated with their use. The work particularly focuses on models of uncertainty and estimation under various complications relating to model specifications, data problems, tests of hypotheses, along with systems and panel data extensions which are covered in exhaustive detail. Extensions discussing pre-test procedures and Bayesian methodologies are provided at length. Throughout, direct applications of spatial models are described in detail, with copious illustrative empirical examples demonstrating how readers might implement spatial analysis in research projects. Designed as a textbook and reference companion, every chapter concludes with a set of questions for formal or self--study. Finally, the book includes extensive supplementing information in a large sample theory in the R programming language that supports early career econometricians interested in the implementation of statistical procedures covered. - Combines advanced theoretical foundations with cutting-edge computational developments in R - Builds from solid foundations, to more sophisticated extensions that are intended to jumpstart research careers in spatial econometrics - Written by two of the most accomplished and extensively published econometricians working in the discipline - Describes fundamental principles intuitively, but without sacrificing rigor - Provides empirical illustrations for many spatial methods across diverse field - Emphasizes a modern treatment of the field using the generalized method of moments (GMM) approach - Explores sophisticated modern research methodologies, including pre-test procedures and Bayesian data analysis
| Author | : Luc Anselin |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 432 |
| Release | : 2012-12-06 |
| Genre | : Business & Economics |
| ISBN | : 3642798772 |
The promising new directions for research and applications described here include alternative model specifications, estimators and tests for regression models and new perspectives on dealing with spatial effects in models with limited dependent variables and space-time data.
| Author | : James LeSage |
| Publisher | : CRC Press |
| Total Pages | : 362 |
| Release | : 2009-01-20 |
| Genre | : Business & Economics |
| ISBN | : 1420064258 |
Although interest in spatial regression models has surged in recent years, a comprehensive, up-to-date text on these approaches does not exist. Filling this void, Introduction to Spatial Econometrics presents a variety of regression methods used to analyze spatial data samples that violate the traditional assumption of independence between observat
| Author | : J. Paul Elhorst |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 125 |
| Release | : 2013-09-30 |
| Genre | : Business & Economics |
| ISBN | : 3642403409 |
This book provides an overview of three generations of spatial econometric models: models based on cross-sectional data, static models based on spatial panels and dynamic spatial panel data models. The book not only presents different model specifications and their corresponding estimators, but also critically discusses the purposes for which these models can be used and how their results should be interpreted.
| Author | : Lina Mallozzi |
| Publisher | : Springer |
| Total Pages | : 332 |
| Release | : 2017-04-04 |
| Genre | : Business & Economics |
| ISBN | : 3319526545 |
Facility location theory develops the idea of locating one or more facilities by optimizing suitable criteria such as minimizing transportation cost, or capturing the largest market share. The contributions in this book focus an approach to facility location theory through game theoretical tools highlighting situations where a location decision is faced by several decision makers and leading to a game theoretical framework in non-cooperative and cooperative methods. Models and methods regarding the facility location via game theory are explored and applications are illustrated through economics, engineering, and physics. Mathematicians, engineers, economists and computer scientists working in theory, applications and computational aspects of facility location problems using game theory will find this book useful.
| Author | : Manfred M. Fischer |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 801 |
| Release | : 2009-12-24 |
| Genre | : Business & Economics |
| ISBN | : 3642036473 |
The Handbook is written for academics, researchers, practitioners and advanced graduate students. It has been designed to be read by those new or starting out in the field of spatial analysis as well as by those who are already familiar with the field. The chapters have been written in such a way that readers who are new to the field will gain important overview and insight. At the same time, those readers who are already practitioners in the field will gain through the advanced and/or updated tools and new materials and state-of-the-art developments included. This volume provides an accounting of the diversity of current and emergent approaches, not available elsewhere despite the many excellent journals and te- books that exist. Most of the chapters are original, some few are reprints from the Journal of Geographical Systems, Geographical Analysis, The Review of Regional Studies and Letters of Spatial and Resource Sciences. We let our contributors - velop, from their particular perspective and insights, their own strategies for m- ping the part of terrain for which they were responsible. As the chapters were submitted, we became the first consumers of the project we had initiated. We gained from depth, breadth and distinctiveness of our contributors’ insights and, in particular, the presence of links between them.
| Author | : Luc Anselin |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 516 |
| Release | : 2013-03-09 |
| Genre | : Business & Economics |
| ISBN | : 3662056178 |
World-renowned experts in spatial statistics and spatial econometrics present the latest advances in specification and estimation of spatial econometric models. This includes information on the development of tools and software, and various applications. The text introduces new tests and estimators for spatial regression models, including discrete choice and simultaneous equation models. The performance of techniques is demonstrated through simulation results and a wide array of applications related to economic growth, international trade, knowledge externalities, population-employment dynamics, urban crime, land use, and environmental issues. An exciting new text for academics with a theoretical interest in spatial statistics and econometrics, and for practitioners looking for modern and up-to-date techniques.
| Author | : Katarzyna Kopczewska |
| Publisher | : Routledge |
| Total Pages | : 760 |
| Release | : 2020-11-25 |
| Genre | : Business & Economics |
| ISBN | : 1000079783 |
This textbook is a comprehensive introduction to applied spatial data analysis using R. Each chapter walks the reader through a different method, explaining how to interpret the results and what conclusions can be drawn. The author team showcases key topics, including unsupervised learning, causal inference, spatial weight matrices, spatial econometrics, heterogeneity and bootstrapping. It is accompanied by a suite of data and R code on Github to help readers practise techniques via replication and exercises. This text will be a valuable resource for advanced students of econometrics, spatial planning and regional science. It will also be suitable for researchers and data scientists working with spatial data.
| Author | : L. Anselin |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 295 |
| Release | : 2013-03-09 |
| Genre | : Business & Economics |
| ISBN | : 9401577994 |
Spatial econometrics deals with spatial dependence and spatial heterogeneity, critical aspects of the data used by regional scientists. These characteristics may cause standard econometric techniques to become inappropriate. In this book, I combine several recent research results to construct a comprehensive approach to the incorporation of spatial effects in econometrics. My primary focus is to demonstrate how these spatial effects can be considered as special cases of general frameworks in standard econometrics, and to outline how they necessitate a separate set of methods and techniques, encompassed within the field of spatial econometrics. My viewpoint differs from that taken in the discussion of spatial autocorrelation in spatial statistics - e.g., most recently by Cliff and Ord (1981) and Upton and Fingleton (1985) - in that I am mostly concerned with the relevance of spatial effects on model specification, estimation and other inference, in what I caIl a model-driven approach, as opposed to a data-driven approach in spatial statistics. I attempt to combine a rigorous econometric perspective with a comprehensive treatment of methodological issues in spatial analysis.
