FDML versus GMM for Dynamic Panel Models with Roots Near Unity
This paper evaluates the first-differenced maximum likelihood (FDML) and the continuously updating system generalized method of moments (CU-GMM) estimators of dynamic panel models when the data is close to non-stationary. This case is far from trivial, as a high degree of persistence is the norm rat...
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MDPI AG
2021-08-01
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| Series: | Journal of Risk and Financial Management |
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| Online Access: | https://www.mdpi.com/1911-8074/14/9/405 |
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doaj-5e45d453774148aebbd1517cb4bf9e332021-09-26T00:32:29ZengMDPI AGJournal of Risk and Financial Management1911-80661911-80742021-08-011440540510.3390/jrfm14090405FDML versus GMM for Dynamic Panel Models with Roots Near UnityAdrian Mehic0Department of Economics, Lund University, SE-223 63 Lund, SwedenThis paper evaluates the first-differenced maximum likelihood (FDML) and the continuously updating system generalized method of moments (CU-GMM) estimators of dynamic panel models when the data is close to non-stationary. This case is far from trivial, as a high degree of persistence is the norm rather than the exception in economic panels, particularly in financial management. While the CU-GMM is shown to have lower bias and higher power, it suffers from severe size distortions, which are exacerbated when the data approaches non-stationarity.https://www.mdpi.com/1911-8074/14/9/405dynamic panel datapersistenceFDML estimation |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Adrian Mehic |
| spellingShingle |
Adrian Mehic FDML versus GMM for Dynamic Panel Models with Roots Near Unity Journal of Risk and Financial Management dynamic panel data persistence FDML estimation |
| author_facet |
Adrian Mehic |
| author_sort |
Adrian Mehic |
| title |
FDML versus GMM for Dynamic Panel Models with Roots Near Unity |
| title_short |
FDML versus GMM for Dynamic Panel Models with Roots Near Unity |
| title_full |
FDML versus GMM for Dynamic Panel Models with Roots Near Unity |
| title_fullStr |
FDML versus GMM for Dynamic Panel Models with Roots Near Unity |
| title_full_unstemmed |
FDML versus GMM for Dynamic Panel Models with Roots Near Unity |
| title_sort |
fdml versus gmm for dynamic panel models with roots near unity |
| publisher |
MDPI AG |
| series |
Journal of Risk and Financial Management |
| issn |
1911-8066 1911-8074 |
| publishDate |
2021-08-01 |
| description |
This paper evaluates the first-differenced maximum likelihood (FDML) and the continuously updating system generalized method of moments (CU-GMM) estimators of dynamic panel models when the data is close to non-stationary. This case is far from trivial, as a high degree of persistence is the norm rather than the exception in economic panels, particularly in financial management. While the CU-GMM is shown to have lower bias and higher power, it suffers from severe size distortions, which are exacerbated when the data approaches non-stationarity. |
| topic |
dynamic panel data persistence FDML estimation |
| url |
https://www.mdpi.com/1911-8074/14/9/405 |
| work_keys_str_mv |
AT adrianmehic fdmlversusgmmfordynamicpanelmodelswithrootsnearunity |
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