Associated with every popular nonlinear estimation method is at least one 'artificial' linear regression. We define an artificial regression in terms of three conditions that it must satisfy. Then we show how artificial regressions can be useful for numerical optimization, testing hypotheses,...

Associated with every popular nonlinear estimation method is at least one "artificial" linear regression. We define an artificial regression in terms of three conditions that it must satisfy. Then we show how artificial regressions can be useful for numerical optimization, testing hypotheses,...

We examine the effect of single motherhood on children’s secondary school track choice using 12-year-old children drawn from the German Socio-Economic Panel. In line with previous studies for the U.S., the U.K. and Sweden, we find a negative correlation between single motherhood and...

We propose several Lagrange Multiplier tests of logit and probit models, which may be inexpensively computed by artificial linear regressions. These may be used to test for omitted variables and heteroskedasticity. We argue that one of these tests is likely to have better small-sample...

We propose several Lagrange Multiplier tests of logit and probit models, which may be inexpensively computed by artificial linear regressions. These may be used to test for omitted variables and heteroskedasticity. We argue that one of these tests is likely to have better small-sample...