Abstract
This article analyzes, within the context of the standard multiple regression model, the problem of handling inequality constraints specifying the signs of certain regression coefficients. It is common econometric practice when regression coefficients are encountered with incorrect sign to delete the variables in question and reestimate the equation. This article shows that this procedure causes bias and can lead to inefficient parameter estimates. Furthermore, we show that grossly exaggerated statements concerning significance levels are likely to be made when other regression coefficients in the model are tested with the final regression obtained after deleting variables with incorrect sign.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 913-925 |
| Number of pages | 13 |
| Journal | Journal of the American Statistical Association |
| Volume | 65 |
| Issue number | 330 |
| DOIs | |
| State | Published - 1970 |
| Externally published | Yes |
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ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty
Cite this
Multiple regression with inequality constraints : Pretesting bias, hypothesis testing and efficiency. / Lovell, Michael C.; Prescott, Edward.
In: Journal of the American Statistical Association, Vol. 65, No. 330, 1970, p. 913-925.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Multiple regression with inequality constraints
T2 - Pretesting bias, hypothesis testing and efficiency
AU - Lovell, Michael C.
AU - Prescott, Edward
PY - 1970
Y1 - 1970
N2 - This article analyzes, within the context of the standard multiple regression model, the problem of handling inequality constraints specifying the signs of certain regression coefficients. It is common econometric practice when regression coefficients are encountered with incorrect sign to delete the variables in question and reestimate the equation. This article shows that this procedure causes bias and can lead to inefficient parameter estimates. Furthermore, we show that grossly exaggerated statements concerning significance levels are likely to be made when other regression coefficients in the model are tested with the final regression obtained after deleting variables with incorrect sign.
AB - This article analyzes, within the context of the standard multiple regression model, the problem of handling inequality constraints specifying the signs of certain regression coefficients. It is common econometric practice when regression coefficients are encountered with incorrect sign to delete the variables in question and reestimate the equation. This article shows that this procedure causes bias and can lead to inefficient parameter estimates. Furthermore, we show that grossly exaggerated statements concerning significance levels are likely to be made when other regression coefficients in the model are tested with the final regression obtained after deleting variables with incorrect sign.
UR - http://www.scopus.com/inward/record.url?scp=0012667910&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0012667910&partnerID=8YFLogxK
U2 - 10.1080/01621459.1970.10481134
DO - 10.1080/01621459.1970.10481134
M3 - Article
VL - 65
SP - 913
EP - 925
JO - Journal of the American Statistical Association
JF - Journal of the American Statistical Association
SN - 0162-1459
IS - 330
ER -