Bootstrap-based Bias Correction and Inference for Dynamic Panels with Fixed Effects
| Autor: | Ilse Ruyssen, Ignace De Vos, Gerdie Everaert |
|---|---|
| Přispěvatelé: | Econometrics and Data Science |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
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Heteroscedasticity Computer science Monte Carlo method st0396 Inference Matrix (mathematics) Mathematics (miscellaneous) st0001 xtbcfe bootstrap-based bias correction dynamic panel data unbalanced higher order heteroscedasticity cross-sectional dependence Monte Carlo labour demand unbalanced DEPENDENCE Resampling DATA MODELS Econometrics cross-sectional dependence bootstrap-based bias correction bootstrap ESTIMATORS Monte Carlo ERROR-COMPONENTS Estimator xtbcfe higher order Function (mathematics) INSTRUMENTS labor demand Mathematics and Statistics dynamic panel data Algorithm heteroskedasticity |
| Zdroj: | Stata journal, 15(4):st0396, 986-1018. DPC Nederland STATA JOURNAL Ghent University Academic Bibliography Vos, I D, Everaert, G & Ruyssen, I 2018, ' Bootstrap-based Bias Correction and Inference for Dynamic Panels with Fixed Effects ', Stata journal, vol. 15, no. 4, st0396, pp. 986-1018 . https://doi.org/10.1177/1536867x1501500404 |
| ISSN: | 1536-867X 1536-8734 |
| DOI: | 10.1177/1536867x1501500404 |
| Popis: | In this article, we describe a new command, xtbcfe, that performs the iterative bootstrap-based bias correction for the fixed-effects estimator in dynamic panels proposed by Everaert and Pozzi (2007, Journal of Economic Dynamics and Control 31: 1160–1184). We first simplify the core of their algorithm by using the invariance principle and subsequently extend it to allow for unbalanced and higher-order dynamic panels. We implement various bootstrap error resampling schemes to account for general heteroskedasticity and contemporaneous cross-sectional dependence. Inference can be performed using a bootstrapped variance–covariance matrix or percentile intervals. Monte Carlo simulations show that the simplification of the original algorithm results in a further bias reduction for very small T. The Monte Carlo results also support the bootstrap-based bias correction in higher-order dynamic panels and panels with cross-sectional dependence. We illustrate the command with an empirical example estimating a dynamic labor–demand function. |
| Databáze: | OpenAIRE |
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