One-Dimensional Inference in Autoregressive Models With the Potential Presence of a Unit Root.
This paper examines the problem of testing and confidence set construction for one-dimensional functions of the coefficients in autoregressive (AR( p)) models with potentially persistent time series. The primary example concerns inference on impulse responses. A new asymptotic framework is suggested...
| Publicado en: | Econometrica Vol. 80; no. 1; pp. 173 - 213 |
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| Formato: | Artículo |
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Wiley-Blackwell
Jan2012
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=70230480&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 70230480 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00129682 ECN jtl: Econometrica issn: 00129682 maglogo: Y pubinfo: dt: Jan2012 vid: 80 iid: 1 pid: 480 pub: Wiley-Blackwell artinfo: ui: 70230480 10.3982/ECTA9371 ppf: 173 ppct: 40 formats: tig: atl: One-Dimensional Inference in Autoregressive Models With the Potential Presence of a Unit Root. aug: au: Mikusheva, Anna affil: Dept. of Economics, Massachusetts Institute of Technology, 50 Memorial Drive, Building E52, Cambridge, MA 02142, U.S.A.; su: Impulse response Approximation algorithms Asymptotic distribution Statistics Least squares Mathematical models sug: subj: Impulse response Approximation algorithms Asymptotic distribution Statistics Least squares Mathematical models ab: This paper examines the problem of testing and confidence set construction for one-dimensional functions of the coefficients in autoregressive (AR( p)) models with potentially persistent time series. The primary example concerns inference on impulse responses. A new asymptotic framework is suggested and some new theoretical properties of known procedures are demonstrated. I show that the likelihood ratio (LR) and LR statistics for a linear hypothesis in an AR( p) can be uniformly approximated by a weighted average of local-to-unity and normal distributions. The corresponding weights depend on the weight placed on the largest root in the null hypothesis. The suggested approximation is uniform over the set of all linear hypotheses. The same family of distributions approximates the LR and LR statistics for tests about impulse responses, and the approximation is uniform over the horizon of the impulse response. I establish the size properties of tests about impulse responses proposed by Inoue and Kilian (2002) and Gospodinov (2004), and theoretically explain some of the empirical findings of Pesavento and Rossi (2007). An adaptation of the grid bootstrap for impulse response functions is suggested and its properties are examined. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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