Introduction to Spatial Econometrics (Statistics: A Series of Textbooks and Monographs)

Product Description

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 observations. It explores a wide range of alternative topics, including maximum likelihood and Bayesian estimation, various types of spatial regression specifications, and applied modeling situations involving different circumstances.

Leaders in this field, the authors clarify the often-mystifying phenomenon of simultaneous spatial dependence. By presenting new methods, they help with the interpretation of spatial regression models, especially ones that include spatial lags of the dependent variable. The authors also examine the relationship between spatiotemporal processes and long-run equilibrium states that are characterized by simultaneous spatial dependence. MATLAB® toolboxes useful for spatial econometric estimation are available on the authors’ websites.

This work covers spatial econometric modeling as well as numerous applied illustrations of the methods. It encompasses many recent advances in spatial econometric models―including some previously unpublished results.

Review

Altogether, this book should be of great value for everyone interested in spatial econometric models. It not only provides a thorough overview of the topic but also nicely illustrates the application of spatial econometrics for different types of data.―Matthias Arnold, Statistical Papers (2011) 52
Without any doubt, the book by LeSage and Pace is a welcome addition to the spatial econometrics literature and will surely be a compulsory reference in this field. Although some good books on spatial statistics have come up in recent years, none of them is as specific as this one. … A nice feature of this text is that readers who are interested in implementing its methods could use MATLAB code that is publicly available on [two] Web sites … All in all we should thank the authors of this book for such a great effort in compiling and updating essential content of spatial econometrics.―Journal of the Royal Statistical Society, Series A, April 2011
LeSage and Pace present a distinctive introduction to spatial econometrics. … Chapters 5 and 6 provide what might be considered the first in-depth review of Bayesian methods in a spatial econometric context, including approaches to model comparison. … a good introduction to the field. The outstanding overview of Bayesian spatial econometric methods and interesting discussions of not-so-introductory topics such as space time and limited dependent variable models make this a book worth having in your bookshelf.―Journal of the American Statistical Association, Sept. 2010, Vol. 105, No. 491
Make room on your bookshelf. It is about time that such a text has been published. A variety of readers will gain from its breadth and timeliness. Students will be happy to find a single source of knowledge; faculty will be happy to have an updated text; and researchers will benefit from a comprehensive reflection on spatial econometrics. LeSage and Pace’s Introduction to Spatial Econometrics shines by offering a much-needed, state-of-the-art summary of spatial econometric methods.―Kathleen P. Bell, Journal of Regional Science, Vol. 50, No. 5, 2010
… This textbook is a good resource for advanced undergraduate and graduate courses, and it provides a useful tool for empirical researchers who are interested in the application of spatial models. … [It] provides readers with a summary of some recent developments in spatial econometric models, especially with respect to the Bayesian approach. In addition, the book provides several chapters that are not treated formally in other similar textbooks, such as spatiotemporal models, matrix exponential spatial models, and limited de