Abstract
Suppose the tails of the noise distribution in a regression exhibit power law behavior. Then the
distribution of the OLS regression estimator inherits this tail behavior. This is relevant for regressions involving financial data. We derive explicit finite sample expressions for the tail probabilities of the distribution of the OLS estimator. These are useful for inference. Simulations for medium
sized samples reveal considerable deviations of the coefficient estimates from their true values, in line with our theoretical formulas. The formulas provide a benchmark for judging the observed highly variable cross country estimates of the expectations coefficient in yield curve regressions.
distribution of the OLS regression estimator inherits this tail behavior. This is relevant for regressions involving financial data. We derive explicit finite sample expressions for the tail probabilities of the distribution of the OLS estimator. These are useful for inference. Simulations for medium
sized samples reveal considerable deviations of the coefficient estimates from their true values, in line with our theoretical formulas. The formulas provide a benchmark for judging the observed highly variable cross country estimates of the expectations coefficient in yield curve regressions.
| Original language | English |
|---|---|
| Journal | Journal of Econometrics |
| Volume | 172 |
| Issue number | 2 |
| Pages (from-to) | 205-221 |
| ISSN | 0304-4076 |
| DOIs | |
| Publication status | Published - Feb 2013 |