Econometrics Structural Change (34 results)

Paperback. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

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Hardcover. Condition: Fair. No Jacket. Condition : Fair/ usable study copy in marked covers. Ex university library with associated markings. Hard cover, no jacket. 206pp. No annotations or highlighting to text. AGE TONED PAGES. Photo on request.

gebundene Ausgabe. Condition: Gut. 128 Seiten Der Erhaltungszustand des hier angebotenen Werks ist trotz seiner Bibliotheksnutzung sehr sauber. Es befindet sich neben dem Rückenschild lediglich ein Bibliotheksstempel im Buch; ordnungsgemäß entwidmet. Leichte altersbedingte Anbräunung des Papiers. Das Buch ist in eine Plastikfolie eingeklebt. In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 300. …

Condition: very good. Amsterdam : North-Holland Publishing Co. , 1976. Hardcover. ix,206 pp. 23 cm. (Contributions to economic analysis, ISSN 0573-8555, 97). Original edition. Condition : very good copy. ISBN 9780444109668. Keywords : ECONOMICS.

Soft. Condition: Good. Reprinted. Spine lightly sunned, closed edges lightly foxed, some pencil notes to earlier pages, otherwise clean and tidy. Size: 8vo.

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Hardcover/ Pappband. Condition: Gut. 206 Cover shows mild wear. Guter Zustand/ Good Ex-Library. With figures and tables. Spine slightly damaged by removing of a label. ha1054325 Sprache: Englisch Gewicht in Gramm: 350.

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Hardback. Condition: New. Volume 1 covers statistical methods related to unit roots, trend breaks and their interplay. Testing for unit roots has been a topic of wide interest and the author was at the forefront of this research. The book covers important topics such as the Phillips-Perron unit root test and theoretical analyses about their properties, how this and other tests could be improved, and ingredients needed to achieve better tests and the proposal of a new class of tests. Also included are theoretical studies related to time series models with unit roots and the effect of span versus sampling interval on the power of the tests. Moreover, this book deals with the issue of trend breaks and their effect on unit root tests. This research agenda fostered by the author showed that trend breaks and unit roots can easily be confused. Hence, the need for new testing procedures, which are covered.Volume 2 is about statistical methods related to structural change in time series models. The approach adopted is off-line whereby one wants to test for structural change using a historical dataset and perform hypothesis testing. A distinctive feature is the allowance for multiple structural changes. The methods discussed have, and continue to be, applied in a variety of fields including economics, finance, life science, physics and climate change. The articles included address issues of estimation, testing and/or inference in a variety of models: short-memory regressors and errors, trends with integrated and/or stationary errors, autoregressions, cointegrated models, multivariate systems of equations, endogenous regressors, long-memory series, among others. Other issues covered include the problems of non-monotonic power and the pitfalls of adopting a local asymptotic framework. Empirical analyses are provided for the US real interest rate, the US GDP, the volatility of asset returns and climate change.…

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Condition: New. pp. 550.

Hardback. Condition: New. Volume 1 covers statistical methods related to unit roots, trend breaks and their interplay. Testing for unit roots has been a topic of wide interest and the author was at the forefront of this research. The book covers important topics such as the Phillips-Perron unit root test and theoretical analyses about their properties, how this and other tests could be improved, and ingredients needed to achieve better tests and the proposal of a new class of tests. Also included are theoretical studies related to time series models with unit roots and the effect of span versus sampling interval on the power of the tests. Moreover, this book deals with the issue of trend breaks and their effect on unit root tests. This research agenda fostered by the author showed that trend breaks and unit roots can easily be confused. Hence, the need for new testing procedures, which are covered.Volume 2 is about statistical methods related to structural change in time series models. The approach adopted is off-line whereby one wants to test for structural change using a historical dataset and perform hypothesis testing. A distinctive feature is the allowance for multiple structural changes. The methods discussed have, and continue to be, applied in a variety of fields including economics, finance, life science, physics and climate change. The articles included address issues of estimation, testing and/or inference in a variety of models: short-memory regressors and errors, trends with integrated and/or stationary errors, autoregressions, cointegrated models, multivariate systems of equations, endogenous regressors, long-memory series, among others. Other issues covered include the problems of non-monotonic power and the pitfalls of adopting a local asymptotic framework. Empirical analyses are provided for the US real interest rate, the US GDP, the volatility of asset returns and climate change.…

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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Econometric models are made up of assumptions which never exactly match reality. Among the most contested ones is the requirement that the coefficients of an econometric model remain stable over time. Recent years have therefore seen numerous attempts to test for it or to model possible structural change when it can no longer be ignored. This collection of papers from Empirical Economics mirrors part of this development. The point of departure of most studies in this volume is the standard linear regression model Yt = x;fJt + U (t = I, . , 1), t where notation is obvious and where the index t emphasises the fact that structural change is mostly discussed and encountered in a time series context. It is much less of a problem for cross section data, although many tests apply there as well. The null hypothesis of most tests for structural change is that fJt = fJo for all t, i.e. that the same regression applies to all time periods in the sample and that the disturbances u are well behaved. The well known Chow test for instance assumes t that there is a single structural shift at a known point in time, i.e. that fJt = fJo (t< t\*), and fJt = fJo + t1fJ (t' . t\*), where t\* is known. 144 pp. Englisch. …

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Econometric models are made up of assumptions which never exactly match reality. Among the most contested ones is the requirement that the coefficients of an econometric model remain stable over time. Recent years have therefore seen numerous attempts to te.…

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Econometric models are made up of assumptions which never exactly match reality. Among the most contested ones is the requirement that the coefficients of an econometric model remain stable over time. Recent years have therefore seen numerous attempts to test for it or to model possible structural change when it can no longer be ignored. This collection of papers from Empirical Economics mirrors part of this development. The point of departure of most studies in this volume is the standard linear regression model Yt = x;fJt + U (t = I, . , 1), t where notation is obvious and where the index t emphasises the fact that structural change is mostly discussed and encountered in a time series context. It is much less of a problem for cross section data, although many tests apply there as well. The null hypothesis of most tests for structural change is that fJt = fJo for all t, i.e. that the same regression applies to all time periods in the sample and that the disturbances u are well behaved. The well known Chow test for instance assumes t that there is a single structural shift at a known point in time, i.e. that fJt = fJo (t< t\*), and fJt = fJo + t1fJ (t' . t\*), where t\* is known.…