Statistical inference in a random coefficient panel model
This paper studies the asymptotics of the Weighted Least Squares (WLS) estimator of the autoregressive root in a panel Random Coefficient Autoregression (RCA). We show that, in an RCA context, there is no “unit root problem” : the WLS estimator is always asymptotically normal, irrespective of the av...
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| Format: | Article |
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Elsevier
2016
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| Online Access: | https://eprints.nottingham.ac.uk/46953/ |
| _version_ | 1848797435731640320 |
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| author | Horváth, Lajos Trapani, Lorenzo |
| author_facet | Horváth, Lajos Trapani, Lorenzo |
| author_sort | Horváth, Lajos |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | This paper studies the asymptotics of the Weighted Least Squares (WLS) estimator of the autoregressive root in a panel Random Coefficient Autoregression (RCA). We show that, in an RCA context, there is no “unit root problem” : the WLS estimator is always asymptotically normal, irrespective of the average value of the autoregressive root, of whether the autoregressive coefficient is random or not, and of the presence and degree of cross dependence. Our simulations indicate that the estimator has good properties, and that confidence intervals have the correct coverage even for sample sizes as small as (N,T)=(10,25)(N,T)=(10,25). We illustrate our findings through two applications to macroeconomic and financial variables. |
| first_indexed | 2025-11-14T20:03:50Z |
| format | Article |
| id | nottingham-46953 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T20:03:50Z |
| publishDate | 2016 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-469532020-05-04T20:02:05Z https://eprints.nottingham.ac.uk/46953/ Statistical inference in a random coefficient panel model Horváth, Lajos Trapani, Lorenzo This paper studies the asymptotics of the Weighted Least Squares (WLS) estimator of the autoregressive root in a panel Random Coefficient Autoregression (RCA). We show that, in an RCA context, there is no “unit root problem” : the WLS estimator is always asymptotically normal, irrespective of the average value of the autoregressive root, of whether the autoregressive coefficient is random or not, and of the presence and degree of cross dependence. Our simulations indicate that the estimator has good properties, and that confidence intervals have the correct coverage even for sample sizes as small as (N,T)=(10,25)(N,T)=(10,25). We illustrate our findings through two applications to macroeconomic and financial variables. Elsevier 2016-07 Article PeerReviewed Horváth, Lajos and Trapani, Lorenzo (2016) Statistical inference in a random coefficient panel model. Journal of Econometrics, 193 (1). pp. 54-75. ISSN 0304-4076 Random Coefficient Autoregression; Panel data; WLS estimator; Common factors http://www.sciencedirect.com/science/article/pii/S0304407616300203 doi:10.1016/j.jeconom.2016.01.006 doi:10.1016/j.jeconom.2016.01.006 |
| spellingShingle | Random Coefficient Autoregression; Panel data; WLS estimator; Common factors Horváth, Lajos Trapani, Lorenzo Statistical inference in a random coefficient panel model |
| title | Statistical inference in a random coefficient panel model |
| title_full | Statistical inference in a random coefficient panel model |
| title_fullStr | Statistical inference in a random coefficient panel model |
| title_full_unstemmed | Statistical inference in a random coefficient panel model |
| title_short | Statistical inference in a random coefficient panel model |
| title_sort | statistical inference in a random coefficient panel model |
| topic | Random Coefficient Autoregression; Panel data; WLS estimator; Common factors |
| url | https://eprints.nottingham.ac.uk/46953/ https://eprints.nottingham.ac.uk/46953/ https://eprints.nottingham.ac.uk/46953/ |