A Lagrange Multiplier-type Test for Idiosyncratic Unit Roots in the Exact Factor Model Under Misspecification PDF Download
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Author: Xingwu Zhou
Publisher:
ISBN:
Category :
Languages : en
Pages : 31
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Book Description
Author: Xingwu Zhou
Publisher:
ISBN:
Category :
Languages : en
Pages : 31
Get Book Here
Book Description
Author: Xingwu Zhou
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
In this article, an exact factor model is considered, and a Lagrange multiplier-type test is derived for a homogeneous unit root in the idiosyncratic component. It is shown that under sequential asymptotics, its null limiting distribution is standard normal, regardless of whether the factors are integrated, cointegrated or stationary. In a simulation study, the size and local power of the Lagrange multiplier-type test and some popular non-likelihood-based tests are compared. The simulation results show that the Lagrange multiplier-type test has the highest local power as the panel dimensions tend to infinity, with the actual size tending to the nominal size.
Author: Pentti Saikkonen
Publisher:
ISBN: 9789514540615
Category :
Languages : en
Pages : 34
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Author: Ramon Van den Akker
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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This paper considers testing for unit roots in Gaussian panels with crosssectional dependence generated by common factors. Within our setup we can analyze restricted versions of the two prevalent approaches in the literature, that of Moon & Perron (2004), who specify a factor model for the innovations, and the PANIC setup proposed in Bai & Ng (2004), who test common factors and idiosyncratic deviations separately for unit roots. We show that both frameworks lead to locally asymptotically normal (LAN) experiments with the same central sequence and Fisher information. Using Le Cam's theory of statistical experiments we obtain the local asymptotic power envelope for unit root tests. We show that the popular Moon & Perron (2004) and Bai & Ng (2010) tests only attain the power envelope in case there is no heterogeneity in the long-run variance of the idiosyncratic components. We develop a new test which is asymptotically uniformly most powerful irrespective of possible heterogeneity in the long-run variance of the idiosyncratic components. Monte Carlo simulations corroborate our asymptotic results and document significant gains in finite-sample power if the variances of the idiosyncratic shocks differ substantially among the cross sectional units.
Author: L. G. Godfrey
Publisher:
ISBN:
Category :
Languages : en
Pages : 252
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Author: Alain Hecq
Publisher:
ISBN:
Category :
Languages : en
Pages : 11
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Author: John H. H. Lee
Publisher:
ISBN: 9780867469417
Category :
Languages : en
Pages : 11
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Author: Jeffrey M. Wooldridge
Publisher: MIT Press
ISBN: 0262232588
Category : Business & Economics
Languages : en
Pages : 1095
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Book Description
The second edition of a comprehensive state-of-the-art graduate level text on microeconometric methods, substantially revised and updated. The second edition of this acclaimed graduate text provides a unified treatment of two methods used in contemporary econometric research, cross section and data panel methods. By focusing on assumptions that can be given behavioral content, the book maintains an appropriate level of rigor while emphasizing intuitive thinking. The analysis covers both linear and nonlinear models, including models with dynamics and/or individual heterogeneity. In addition to general estimation frameworks (particular methods of moments and maximum likelihood), specific linear and nonlinear methods are covered in detail, including probit and logit models and their multivariate, Tobit models, models for count data, censored and missing data schemes, causal (or treatment) effects, and duration analysis. Econometric Analysis of Cross Section and Panel Data was the first graduate econometrics text to focus on microeconomic data structures, allowing assumptions to be separated into population and sampling assumptions. This second edition has been substantially updated and revised. Improvements include a broader class of models for missing data problems; more detailed treatment of cluster problems, an important topic for empirical researchers; expanded discussion of "generalized instrumental variables" (GIV) estimation; new coverage (based on the author's own recent research) of inverse probability weighting; a more complete framework for estimating treatment effects with panel data, and a firmly established link between econometric approaches to nonlinear panel data and the "generalized estimating equation" literature popular in statistics and other fields. New attention is given to explaining when particular econometric methods can be applied; the goal is not only to tell readers what does work, but why certain "obvious" procedures do not. The numerous included exercises, both theoretical and computer-based, allow the reader to extend methods covered in the text and discover new insights.
Author: Yves Croissant
Publisher: John Wiley & Sons
ISBN: 1118949188
Category : Mathematics
Languages : en
Pages : 435
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Book Description
Panel Data Econometrics with R provides a tutorial for using R in the field of panel data econometrics. Illustrated throughout with examples in econometrics, political science, agriculture and epidemiology, this book presents classic methodology and applications as well as more advanced topics and recent developments in this field including error component models, spatial panels and dynamic models. They have developed the software programming in R and host replicable material on the book’s accompanying website.
Author: Jörg Breitung
Publisher:
ISBN: 9783865580979
Category :
Languages : en
Pages : 29
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