Bootstrap tests for regression models

Bootstrap tests for regression models

Godfrey, Leslie

31,35 €(IVA inc.)

An accessible discussion examining computationally-intensive techniques and bootstrap methods, providing ways to improve the finite-sample performance of well-known asymptotic tests for regression models. This book uses the linear regression model as a framework for introducing simulation-based tests to help perform econometric analyses. INDICE: Preface - PART I: TESTS FOR LINEAR REGRESSION MODELS - Introduction - Tests for the Classical Linear Regression Model - Tests for Linear Regression Models Under Weaker Assumptions: Random Regressors and Non-Normal IID Errors - Tests for Generalized Linear Regression Models - Finite-Sample Propertiesof Asymptotic Tests - Non-Standard Tests for Linear Regression Models - Summary and Concluding Remarks - PART II: SIMULATION-BASED TESTS: BASIC IDEAS - Introduction - Some Simple Examples of Tests for IID Variables and Key Concepts -Simulation-Based Tests for Regression Models - Asymptotic Properties of Bootstrap Tests - The Double Bootstrap - Summary and Concluding Remarks - PART III:SIMULATION-BASED TESTS FOR REGRESSION MODELS WITH IID ERRORS: SOME STANDARD CASES - Introduction - A Monte Carlo Test of the Assumption of Normality - Simulation-Based Tests for Heteroskedasticity - Bootstrapping F Tests of Linear Coefficient Restrictions - Bootstrapping LM Tests for Serial Correlation in Dynamic Regression Models - Summary and Concluding Remarks - PART IV: SIMULATION-BASED TESTS FOR REGRESSION MODELS WITH IID ERRORS: SOME NON-STANDARD CASES - Introduction - Bootstrapping Predictive Tests - Using Bootstrap Methods with a Battery of OLS Diagnostic Tests - Bootstrapping Tests for Structural Breaks - Summary and Conclusions - PART V: BOOTSTRAP METHODS FOR REGRESSION MODELS WITH NON-IID ERRORS - Introduction - Bootstrap Methods for Independent Heteroskedastic Errors - Bootstrap Methods for Homoskedastic Autocorrelated Errors - Bootstrap Methods for Heteroskedastic Autocorrelated Errors - Summary and Concluding Remarks - PART VI: SIMULATION-BASED TESTS FOR REGRESSION MODELS WITH NON-IIDERRORS - Introduction - Bootstrapping Heteroskedasticity-Robust Regression Specification Error Tests - Bootstrapping Heteroskedasticity-Robust Autocorrelation Tests for Dynamic - Models - Bootstrapping Heteroskedasticity-Robust Structural Break Tests with an Unknown Breakpoint - Bootstrapping Autocorrelation-Robust Hausman Tests - Summary and Conclusions - PART VII: - Simulation-Based Tests for Non-Nested Regression Models - Introduction - Asymptotic Tests for Models with Non-Nested Regressors - Bootstrapping Tests for Models with Non-Nested Regressors - Bootstrapping the LLR Statistic with Non-Nested Models - Summary and Concluding Remarks - PART VIII: EPILOGUE - Bibliography - Author Index - Subject Index

  • ISBN: 978-0-230-20231-3
  • Editorial: Palgrave Macmillan
  • Encuadernacion: Rústica
  • Páginas: 344
  • Fecha Publicación: 30/07/2009
  • Nº Volúmenes: 1
  • Idioma: Inglés