A Primer for Spatial Econometrics [electronic resource] : With Applications in R /
Arbia, G.author.
This book aims at meeting the growing demand in the field by introducing the basic spatial econometrics methodologies to a wide variety of researchers. It provides a practical guide that illustrates the potential of spatial econometric modelling, discusses problems and solutions and interprets empirical results.
Description based upon print version of record.
Cover; Contents; List of Figures; List of Examples; Foreword; Preface and Acknowledgements; 1 The Classical Linear Regression Model; 1.1 The basic linear regression model; 1.2 Non-sphericity of the disturbances; 1.3 Endogeneity; 1.4 R Codes: running a regression; Key Terms and Concepts Introduced; Questions; Exercises; References to the Chapter; 2 Some Important Spatial Definitions; 2.1 The Spatial Weight Matrix W and the definition of Spatial Lag; 2.2 Testing spatial autocorrelation among OLS residuals without an explicit alternative hypothesis; 2.3 R Codes; Key Terms and Concepts Introduced
QuestionsExercises; References to the Chapter; 3 Spatial Linear Regression Models; 3.1 Generalities; 3.2 Pure spatial autoregression; 3.3 The classical model with spatially lagged non-stochastic regressors; 3.4 The Spatial Error Model (SEM); 3.5 The Spatial Lag Model (SLM); 3.6 The general SARAR(1,1) Model; 3.7 Testing spatial autocorrelation among the residuals with an explicit alternative hypothesis; 3.8 Interpretation of the parameters in spatial econometric models; 3.9 R Codes: estimating linear spatial models; Key Terms and Concepts Introduced; Questions; Exercises
References to the Chapter4 Further Topics in Spatial Econometrics; 4.1 Heteroscedastic innovations; 4.2 Spatial models for binary response variables; 4.3 Spatial panel data models (Written by Giovanni Millo); 4.4 Non-stationary spatial econometric models; 4.5 R Codes; Key Terms and Concepts Introduced; Questions; Exercises; References to the Chapter; 5 Alternative Model Specifications for Big Datasets; 5.1 Introduction; 5.2 The MESS specification; 5.3 The unilateral approximation approach; 5.4 A composite likelihood approach; 5.5 R Codes; Key Terms and Concepts Introduced; Questions
ExercisesReferences to the Chapter; 6 Conclusions: What's Next?; Solutions to the Exercises; Index
Includes bibliographical references and index.
This book aims at meeting the growing demand in the field by introducing the basic spatial econometrics methodologies to a wide variety of researchers. It provides a practical guide that illustrates the potential of spatial econometric modelling, discusses problems and solutions and interprets empirical results.
Economic theory.
Regional economics.
Spatial economics.
Econometrics.
Statistics .
Urban economics.
Economic Theory/Quantitative Economics/Mathematical Methods.
Regional/Spatial Science.
Econometrics.
Statistics for Business, Management, Economics, Finance, Insurance.
Urban Economics.