## ＜電子ブック＞Testing for Random Walk Coefficients in Regression and State Space Models

責任表示 by Martin Moryson Moryson, Martin SpringerLink (Online service) English (英語) Physica-Verlag HD 1998- Heidelberg, Germany シリーズ Contributions to Statistics Regression and state space models with time varying coefficients are treated in a thorough manner. State space models are introduced as a means to model time varying regression coefficients. The Kalma...n filter and smoother recursions are explained in an easy to understand fashion. The main part of the book deals with testing the null hypothesis of constant regression coefficients against the alternative that they follow a random walk. Different exact and large sample tests are presented and extensively compared based on Monte Carlo studies, so that the reader is guided in the question which test to choose in a particular situation. Moreover, different new tests are proposed which are suitable in situations with autocorrelated or heteroskedastic errors. Additionally, methods are developed to test for the constancy of regression coefficients in situations where one knows already that some coefficients follow a random walk, thereby one is enabled to find out which of the coefficients varies over time.続きを見る 1 Introduction2 The Linear State Space Model2.1 The Model Set-up2.2 Some Basic Results2.3 Interpretation of the State Space Model2.4 The Kalman Filter and Smoother2.5 Estimation of the Hyperparameters2.6 An Illustrative Example2.7 Forecasting3 Exact Tests for Univariate Random Walk Coefficients3.1 The Testing Problem3.2 An Exact F-Test3.3 A Point Optimal Invariant Test3.4 The Locally Best Invariant Test3.5 Simulation Study3.6 Appendix: Determination of Critical Values4 Asymptotic Tests for Univariate Random Walk Coefficients in Models with Stationary Regressors4.1 Introduction4.2 Asymptotic Distribution of the LM/LBI Test4.3 The Hansen Test4.4 The Modified Hansen Test4.5 The Test of Leybourne k McCabe4.6 Simulation Study5 Asymptotic Tests for Univariate Random Walk Coefficients in Models with Non-Stationary Regressors5.1 Introduction5.2 The Model and the Estimators5.3 Asymptotic Distribution of the LM/LBI Test in the Presence of I(1) Regressors5.4 Asymptotic Distribution of Test Statistics Based on OLS Estimators5.5 Asymptotic Distribution of Test Statistics Based on Asymptotically Efficient Estimators5.6 Testing the Constancy of the Intercept5.7 Simulation Study5.8 Tests with Polynomial Regressors6 Testing Trend Stationarity Against Difference Stationarity in Time Series6.1 Introduction6.2 The KPSS Test6.3 The Test of Leybourne & McCabe6.4 The Choi Test6.5 The Tsay Test6.6 POI and LBI Tests6.7 Simulation Study7 Testing for Multivariate Random Walk Coefficients in Regression Models7.1 The Testing Problem7.2 Exact Tests7.3 Simulation Study: Exact Tests7.4 Asymptotic Tests in Models with Stationary Regressors7.5 Simulation Study: Stationary Regressors7.6 Asymptotic Tests in Models with Integrated Regressors7.7 Simulation Study: Integrated Regressors8 Testing for Random Walk Coefficients in the Presence of Varying Coefficients Under H08.1 The Testing Problem8.2 Asymptotic Tests8.3 Simulation Study9 The Term Structure of German Interest Rates - Testing the Expectations Hypothesis9.1 The Data9.2 Tests9.3 Estimation of State Space Models9.4 Conclusions10 Résumé and ProspectsReferences.続きを見る http://hdl.handle.net/2324/1001400860 Full text available from SpringerLink ebooks - Mathematics and Statistics (Archive)

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レコードID 3667064 HB139-141 330.015195 Economics. Econometrics. Economics/Management Science. Econometrics. Statistics for Business/Economics/Mathematical Finance/Insurance. ssj0001298715 9783790811322(print) 9783642997990 2020.06.27 2021.05.09