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- handle: 10670/1.e4mdnm
- halshs: halshs-03672612
- doi: 10.1016/j.econmod.2021.01.014
- WOS: 000684561700010
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info:eu-repo/semantics/altIdentifier/doi/10.1016/j.econmod.2021.01.014
Mots-clés
Time-invariant variables Panel data Pretest estimator Instrumental variables Mundlak estimator Hausman-Taylor estimator C - Mathematical and Quantitative Methods/C.C0 - General/C.C0.C01 - Econometrics C - Mathematical and Quantitative Methods/C.C2 - Single Equation Models • Single Variables/C.C2.C22 - Time-Series Models • Dynamic Quantile Regressions • Dynamic Treatment Effect Models • Diffusion Processes C - Mathematical and Quantitative Methods/C.C2 - Single Equation Models • Single Variables/C.C2.C23 - Panel Data Models • Spatio-temporal ModelsSujets proches
Hours (Time) Squares, Least Method of least squares Pattern ModelCiter ce document
Jean-Bernard Chatelain et al., « Inference on time-invariant variables using panel data: A pretest estimator », HAL-SHS : économie et finance, ID : 10.1016/j.econmod.2021.01.014
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Résumé
For static panel data models that include endogenous time-invariant variables correlated with individual effects, exogenous averages over time of time-varying variables can be internal instruments. To pretest their exogeneity, we first estimate a random effects model that includes all averages over time of time-varying variables (Mundlak, 1978; Krishnakumar, 2006). Internal instruments are then selected if their parameter is statistically different from zero (Mundlak, 1978; Hausman and Taylor, 1981). Finally, we estimate a Hausman-Taylor (1981) model using these internal instruments. We then evaluate the biases of currently used alternative estimators in a Monte-Carlo simulation: repeated between, ordinary least squares, two-stage restricted between, Oaxaca-Geisler estimator, fixed effect vector decomposition, and random effects (restricted generalized least squares).