1994
DOI: 10.1016/0304-4076(94)90062-0
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A two-stage estimator for probit models with structural group effects

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Cited by 76 publications
(32 citation statements)
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“…We therefore estimate a random effects probit model to obtain efficient estimates in two stages. See Borjas and Sueyoshi (1994) for a thorough discussion of the technique, and for proof that the estimation technique provides asymptotically unbiased inferences if the number of observations per group (in our case, MA / year combination) is sufficiently large.…”
Section: Estimates Of the Effect Of Immigration On The Private /Publimentioning
confidence: 99%
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“…We therefore estimate a random effects probit model to obtain efficient estimates in two stages. See Borjas and Sueyoshi (1994) for a thorough discussion of the technique, and for proof that the estimation technique provides asymptotically unbiased inferences if the number of observations per group (in our case, MA / year combination) is sufficiently large.…”
Section: Estimates Of the Effect Of Immigration On The Private /Publimentioning
confidence: 99%
“…As suggested in Borjas and Sueyoshi (1994), we estimate the second-stage regression using generalized least squares (GLS). Specifically, we use the weights on each MA in the second-stage regression.…”
Section: Estimates Of the Effect Of Immigration On The Private /Publimentioning
confidence: 99%
See 1 more Smart Citation
“…9 Borjas and Sueyoshi (1994) show that when the first stage is a probit, the weights necessary to recover the coefficients that would have obtained in a one step procedure are more complicated than the inverse of the squared standard errors. I show that the results are not sensitive to the weights.…”
Section: Empirical Strategymentioning
confidence: 99%
“…I employ a two-stage random effects logit developed by Borjas and Sueyoshi (1994). First, separate logit models are estimated for each quarter from 1980 to 1994.…”
Section: Methodsmentioning
confidence: 99%