Author: Dongkoo Chang
Publisher:
ISBN:
Category :
Languages : en
Pages : 196
Book Description
X, 98 leaves, bound 29 cm.
Testing the Joint Hypothesis of Rationality and Neutrality Under Seasonal Cointegration
Author: Dongkoo Chang
Publisher:
ISBN:
Category :
Languages : en
Pages : 196
Book Description
X, 98 leaves, bound 29 cm.
Publisher:
ISBN:
Category :
Languages : en
Pages : 196
Book Description
X, 98 leaves, bound 29 cm.
Testing the joint hypothesis of rationality and neutrality under seasonal cointegration
Testing the Joint Hypothesis of Rationality Under Seasonal Cointegration
Testing the Joint Hypothesis of Rationality and Neutrally Under Seasonal Cointegration: the Case of Korea
Testing the Joint Hypothesis of Rationality and Neutrality Under Seasonal Cointegration
A Joint Test of the Rational Expectations - Permanent Income Hypothesis Under Seasonal Cointegration
Author: Tai-Hsin Huang
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
This study re-evaluates the validity of the joint rational expectations - permanent income hypothesis under the framework of seasonal cointegration using seasonally unadjusted quarterly data from Austria, Canada and Taiwan. Evidence is found that the consumption change only depends on the innovations of the income and the unemployment rate changes, and that agents are rational in forming their expectations, i.e., the joint hypothesis is supported by the data used. However, with the same data set, a similar test based on non-seasonal cointegration tends to reject the joint hypothesis, since the test ignores completely the possible stochastic seasonalities that may contain important information, as has been pointed out by Wallis (1974), embodied in the data.
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
This study re-evaluates the validity of the joint rational expectations - permanent income hypothesis under the framework of seasonal cointegration using seasonally unadjusted quarterly data from Austria, Canada and Taiwan. Evidence is found that the consumption change only depends on the innovations of the income and the unemployment rate changes, and that agents are rational in forming their expectations, i.e., the joint hypothesis is supported by the data used. However, with the same data set, a similar test based on non-seasonal cointegration tends to reject the joint hypothesis, since the test ignores completely the possible stochastic seasonalities that may contain important information, as has been pointed out by Wallis (1974), embodied in the data.
Cointegration, Causality, and Forecasting
Author: Halbert White
Publisher: Oxford University Press, USA
ISBN: 9780198296836
Category : Business & Economics
Languages : en
Pages : 512
Book Description
A collection of essays in honour of Clive Granger. The chapters are by some of the world's leading econometricians, all of whom have collaborated with and/or studied with both) Clive Granger. Central themes of Granger's work are reflected in the book with attention to tests for unit roots and cointegration, tests of misspecification, forecasting models and forecast evaluation, non-linear and non-parametric econometric techniques, and overall, a careful blend of practical empirical work and strong theory. The book shows the scope of Granger's research and the range of the profession that has been influenced by his work.
Publisher: Oxford University Press, USA
ISBN: 9780198296836
Category : Business & Economics
Languages : en
Pages : 512
Book Description
A collection of essays in honour of Clive Granger. The chapters are by some of the world's leading econometricians, all of whom have collaborated with and/or studied with both) Clive Granger. Central themes of Granger's work are reflected in the book with attention to tests for unit roots and cointegration, tests of misspecification, forecasting models and forecast evaluation, non-linear and non-parametric econometric techniques, and overall, a careful blend of practical empirical work and strong theory. The book shows the scope of Granger's research and the range of the profession that has been influenced by his work.
Time Series Models for Business and Economic Forecasting
Author: Philip Hans Franses
Publisher: Cambridge University Press
ISBN: 1139952129
Category : Business & Economics
Languages : en
Pages : 421
Book Description
With a new author team contributing decades of practical experience, this fully updated and thoroughly classroom-tested second edition textbook prepares students and practitioners to create effective forecasting models and master the techniques of time series analysis. Taking a practical and example-driven approach, this textbook summarises the most critical decisions, techniques and steps involved in creating forecasting models for business and economics. Students are led through the process with an entirely new set of carefully developed theoretical and practical exercises. Chapters examine the key features of economic time series, univariate time series analysis, trends, seasonality, aberrant observations, conditional heteroskedasticity and ARCH models, non-linearity and multivariate time series, making this a complete practical guide. Downloadable datasets are available online.
Publisher: Cambridge University Press
ISBN: 1139952129
Category : Business & Economics
Languages : en
Pages : 421
Book Description
With a new author team contributing decades of practical experience, this fully updated and thoroughly classroom-tested second edition textbook prepares students and practitioners to create effective forecasting models and master the techniques of time series analysis. Taking a practical and example-driven approach, this textbook summarises the most critical decisions, techniques and steps involved in creating forecasting models for business and economics. Students are led through the process with an entirely new set of carefully developed theoretical and practical exercises. Chapters examine the key features of economic time series, univariate time series analysis, trends, seasonality, aberrant observations, conditional heteroskedasticity and ARCH models, non-linearity and multivariate time series, making this a complete practical guide. Downloadable datasets are available online.