Heterogeneity and cross-sectional dependence in panels: Heterogeneous vs. homogeneous estimators (notice n° 545819)
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| fixed length control field | 02035cam a2200229 4500500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250121113829.0 |
| 041 ## - LANGUAGE CODE | |
| Language code of text/sound track or separate title | fre |
| 042 ## - AUTHENTICATION CODE | |
| Authentication code | dc |
| 100 10 - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Akgun, Oguzhan |
| Relator term | author |
| 245 00 - TITLE STATEMENT | |
| Title | Heterogeneity and cross-sectional dependence in panels: Heterogeneous vs. homogeneous estimators |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Date of publication, distribution, etc. | 2021.<br/> |
| 500 ## - GENERAL NOTE | |
| General note | 73 |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | This paper focuses on the comparison of homogeneous and heterogeneous panel data estimators, including partially heterogeneous ones, in the presence of cross-sectional dependence generated by common factors and spatial error dependence. Our specifications allow us to consider and contrast weak cross-sectional dependence and strong cross-sectional dependence in a general linear heterogeneous panel data model. An overview of the estimation procedures, including heterogeneous, homogeneous, and partially heterogeneous estimators, is presented. Then, an extensive Monte Carlo study is conducted using a general framework encompassing recent contributions in the literature, especially in terms of considering common factors and spatial dependence simultaneously. Our simulation results show that, even for small individual and time dimensions, heterogeneous estimators perform better in terms of bias, root mean squared error, size, and size-adjusted power compared to homogeneous estimators. Lastly, the superiority of the heterogeneous estimators is confirmed by an empirical application relating fiscal decentralization and government size in 22 OECD countries over the period 1973–2017. JEL classification codes: C13, C23 |
| 690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN) | |
| Topical term or geographic name as entry element | agricultural sector |
| 690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN) | |
| Topical term or geographic name as entry element | total factor productivity |
| 690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN) | |
| Topical term or geographic name as entry element | common agricultural policy |
| 690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN) | |
| Topical term or geographic name as entry element | productivity surplus account method |
| 700 10 - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Pirotte, Alain |
| Relator term | author |
| 700 10 - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Urga, Giovanni |
| Relator term | author |
| 786 0# - DATA SOURCE ENTRY | |
| Note | Revue d'économie politique | 131 | 1 | 2021-03-08 | p. 19-55 | 0373-2630 |
| 856 41 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://shs.cairn.info/journal-revue-d-economie-politique-2021-1-page-19?lang=en&redirect-ssocas=7080">https://shs.cairn.info/journal-revue-d-economie-politique-2021-1-page-19?lang=en&redirect-ssocas=7080</a> |
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