Amadou Barry, Karim Oualkacha, Arthur Charpentier
arXiv 10 Aug 2021 · Econometrics
arXiv:2108.04737 · PDF · DOI · OpenAlex · Extracted main text
The fixed-effects model estimates the regressor effects on the mean of the response, which is inadequate to summarize the variable relationships in the presence of heteroscedasticity. In this paper, we adapt the asymmetric least squares (expectile) regression to the fixed-effects model and propose a new model: expectile regression with fixed-effects $(\ERFE).$ The $\ERFE$ model applies the within transformation strategy to concentrate out the incidental parameter and estimates the regressor effects on the expectiles of the response distribution. The $\ERFE$ model captures the data heteroscedasticity and eliminates any bias resulting from the correlation between the regressors and the omitted factors. We derive the asymptotic properties of the $\ERFE$ estimators and suggest robust estimators of its covariance matrix. Our simulations show that the $\ERFE$ estimator is unbiased and outperforms its competitors. Our real data analysis shows its ability to capture data heteroscedasticity (see our R package, \url{github.com/AmBarry/erfe}).
appendix boundary found by none_found · 100% of the source is main text. Read the extracted text to check this.
The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Cornwell, C. and Rupert, P (1988) Efficient estimation with panel data: An empirical comparison of instrumental variables estimators | 0.928 | 4 | 3 | 100% |
| 2 | Koenker, R (2004) Quantile regression for longitudinal data | 0.928 | 4 | 3 | 100% |
| 3 | Baltagi, B. and Khanti-Akom, S (1990) On efficient estimation with panel data: An empirical comparison of instrumental variables estimators | 0.737 | 3 | 2 | 100% |
| 4 | Newey, W. K. and Powell, J. L (1987) Asymmetric least squares estimation and testing | 0.737 | 3 | 2 | 100% |
| 5 | Chen, L., Wei, L.-J., and Parzen, M. I (2004) Quantile Regression for Correlated Observations, pages 51–69 | 0.644 | 2 | 2 | 100% |
| 6 | Greene, W. H (2011) Econometric analysis | 0.644 | 2 | 2 | 100% |
| 7 | Yin, G. and Cai, J (2005) Quantile Regression Models with Multivariate Failure Time Data | 0.644 | 2 | 2 | 100% |
| 8 | Kocherginsky, M., He, X., and Mu, Y (2005) Practical Confidence Intervals for Regression Quantiles | 0.644 | 2 | 2 | 100% |
| 9 | Baltagi, B (2008) Econometric Analysis of Panel Data | 0.585 | 3 | 1 | 100% |
| 10 | Cameron, A. and Trivedi, P (2005) Microeconometrics | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 27 scored citations.