### Abstract

We analyze linear panel regression models with interactive fixed effects and predetermined regressors, for example lagged-dependent variables. The first-order asymptotic theory of the least squares (LS) estimator of the regression coefficients is worked out in the limit where both the cross-sectional dimension and the number of time periods become large. We find two sources of asymptotic bias of the LS estimator: bias due to correlation or heteroscedasticity of the idiosyncratic error term, and bias due to predetermined (as opposed to strictly exogenous) regressors. We provide a bias-corrected LS estimator. We also present bias-corrected versions of the three classical test statistics (Wald, LR, and LM test) and show their asymptotic distribution is a χ^{2}-distribution. Monte Carlo simulations show the bias correction of the LS estimator and of the test statistics also work well for finite sample sizes.

Original language | English |
---|---|

Pages (from-to) | 158-195 |

Number of pages | 38 |

Journal | Econometric Theory |

Volume | 33 |

Issue number | 1 |

DOIs | |

Publication status | Published - 2017 Feb 1 |

### All Science Journal Classification (ASJC) codes

- Social Sciences (miscellaneous)
- Economics and Econometrics

## Fingerprint Dive into the research topics of 'Dynamic linear panel regression models with interactive fixed effects'. Together they form a unique fingerprint.

## Cite this

*Econometric Theory*,

*33*(1), 158-195. https://doi.org/10.1017/S0266466615000328