| 000 | 01362nam a22002537a 4500 | ||
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| 003 | ZW-GwMSU | ||
| 005 | 20240322104046.0 | ||
| 008 | 240322b |||||||| |||| 00| 0 eng d | ||
| 022 | _a02664666 | ||
| 040 |
_aMSU _bEnglish _cMSU _erda |
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| 050 | 0 | 0 | _aHB139.T52 ECO |
| 100 | 1 |
_aJun, Sung Jae _eauthor |
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| 245 | 1 | 0 |
_aAdding regressors to obtain efficiency _ccreated by Sung Jae Jun and Joris Pinkse |
| 264 | 1 |
_aCambridge: _bCambridge University Press, _c2009. |
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| 336 |
_2rdacontent _atext _btxt |
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| 337 |
_2rdamedia _aunmediated _bn |
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| 338 |
_2rdacarrier _avolume _bnc |
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| 440 |
_aEconometric theory _vVolume 25, number 1, |
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| 520 | 3 | _aIt is well known that in standard linear regression models with independent and identically distributed data and homoskedasticity, adding “irrelevant regressors” hurts (asymptotic) efficiency unless such irrelevant regressors are orthogonal to the remaining regressors. But we have found that under (conditional) heteroskedasticity “irrelevant regressors” can always be found such that one can achieve the asymptotic variance of the generalized least squares estimator by adding the “irrelevant regressors” to the model. | |
| 650 |
_aEstimation theory _vEfficiency _xRegression analysis |
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| 700 | 1 |
_aPinkse, Joris _eauthor |
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| 856 | _uhttps://doi.org/10.1017/S0266466608090567 | ||
| 942 |
_2lcc _cJA |
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| 999 |
_c164514 _d164514 |
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