Time-Varying Panel Data Models with an Additive Factor Structure
In this paper, we study a nonlinear panel data model with time-varying regression coefficients associated with an additive factor structure. In our model, factor loadings are unknown functions of observable variables which can capture time-varying and heterogeneous covariate information. A profile marginal integration (PMI) method is proposed to estimate unknown coefficient functions, factors and their loadings jointly in a number of simple steps, which can result in closed-form expressions for the proposed estimators. Meanwhile, we propose specification testing for model nonlinearity and time-variation in coefficients. Asymptotic distributions for both the proposed PMI estimators and the test statistics are established. Simulation studies and an empirical application on US mutual fund returns are conducted to demonstrate the finite sample performance of our estimation and testing methods. Empirical results suggest that classic parametric methods ignoring model nonlinearity and time-variation may provide invalid inference due to possible model misspecification issues
Year of publication: |
[2022]
|
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Authors: | Liu, Fei ; Gao, Jiti ; Yang, Yanrong |
Publisher: |
[S.l.] : SSRN |
Subject: | Panel | Panel study | Schätztheorie | Estimation theory |
Saved in:
freely available
Extent: | 1 Online-Ressource (50 p) |
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Type of publication: | Book / Working Paper |
Language: | English |
Notes: | Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments November 13, 2020 erstellt |
Other identifiers: | 10.2139/ssrn.3729869 [DOI] |
Classification: | C14 - Semiparametric and Nonparametric Methods ; C23 - Models with Panel Data ; C33 - Models with Panel Data |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10013309716
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