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Can I read A Simple Estimator for Quantile Panel Data Models Using Smoothed Quantile Regressions on EtoBox?
A Simple Estimator for Quantile Panel Data Models Using Smoothed Quantile Regressions by Liang Chen; Yulong Huo is a Economics, Econometrics and Finance article available to read on EtoBox.
What is A Simple Estimator for Quantile Panel Data Models Using Smoothed Quantile Regressions about?
Summary This paper considers panel data models where the idiosyncratic errors are subject to conditonal quantile restrictions. We propose a two-step estimator based on smoothed quantile regressions that is easy to implement. The asymptotic distribution of the estimator is established, and the analytical expression of its asymptotic bias is derived. Building on these results, we show how to make asymptotically valid inference on the basis of both analytical and split-panel jackknife bias corrections. Finite-sample simulations are used to support our theoretical analysis and to illustrate the importance of bias correction in quantile regressions for panel data. Finally, in an empirical application, the proposed method is used to study the growth effects of foreign direct investment.
Who reads A Simple Estimator for Quantile Panel Data Models Using Smoothed Quantile Regressions?
It is typically read by researchers, students, and practitioners in Economics, Econometrics and Finance.
- Author
- Liang Chen; Yulong Huo
- Publisher
- John Wiley and Sons; Oxford University Press; Blackwell Publishing Inc.; Oxford University Press (OUP) (ISSN 1368-4221)
- Published
- 2020
- Language
- EN
- Field
- Economics, Econometrics and Finance (Social Sciences)