In binary discrete regression models like logit or probit the omis-sion of a relevant regressor (even if it is orthogonal) depresses the re-maining b coefficients towards zero. For the probit model, Wooldridge(2002) has shown that this bias does not carry over to the effect ofthe regressor on...

In binary discrete regression models like logit or probit the omis-sion of a relevant regressor (even if it is orthogonal) depresses the re-maining b coefficients towards zero. For the probit model, Wooldridge(2002) has shown that this bias does not carry over to the effect ofthe regressor on...

In binary discrete regression models like logit or probit the omis- sion of a relevant regressor (even if it is orthogonal) depresses the re- maining <font face="Symbol">b</font> coefficients towards zero. For the probit model, Wooldridge (2002) has shown that this bias does not carry over to the effect of the regressor...

With the advent of improved data collection techniques, the applied econometrician can nowadays have access to very large data bases. Sometimes, however, these can have fairly low informational content. For example, a typical response rate in direct mailings is below 1%. Given the small fraction...

In binary discrete regression models like logit or probit the omis-sion of a relevant regressor (even if it is orthogonal) depresses the re-maining b coefficients towards zero. For the probit model, Wooldridge(2002) has shown that this bias does not carry over to the effect ofthe regressor on...