Limited information estimators and exogeneity tests for simultaneous probit models

Amemiya, 1978, The estimation of a simultaneous equation generalized probit model, Econometrica, 46, 1193, 10.2307/1911443

Andrews, 1987, Asymptotic results for generalized Wald tests, Econometric Theory, 3, 348, 10.1017/S0266466600010434

Godfrey, 1982, A simple derivation of the limited information maximum likelihood estimator, Economics Letters, 10, 277, 10.1016/0165-1765(82)90066-0

Hausman, 1978, Specification tests in econometrics, Econometrica, 46, 1251, 10.2307/1913827

Heckman, 1978, Dummy endogenous variables in a simultaneous equation system, Econometrica, 46, 931, 10.2307/1909757

Holly, 1982, A remark on Hausman's specification tests, Econometrica, 50, 749, 10.2307/1912612

Holly, 1986, Some useful equivalence properties of Hausman's test, Economics Letters, 20, 39, 10.1016/0165-1765(86)90076-5

Holly, 1982, Testing for exogeneity within a limited information framework

Lee, 1981, Simultaneous equation models with discrete and censored dependent variables

Newey, 1985, Maximum likelihood specification testing and conditional moment tests, Econometrica, 53, 1047, 10.2307/1911011

Newey, 1987, Efficient estimation of limited dependent variable models with endogenous explanatory variables, Journal of Econometrics, 36, 230, 10.1016/0304-4076(87)90001-7

Rao, 1971

Richard, 1975, A note on the information matrix of the multivariate normal distribution, Journal of Econometrics, 3, 57, 10.1016/0304-4076(75)90066-4

Rivers, 1984, Limited information estimators and exogeneity tests for simultaneous probit models

Smith, 1986, An exogeneity test for a simultaneous equation tobit model with an application to labor supply, Econometrica, 54, 679, 10.2307/1911314

Vuong, 1984, Two-stage conditional maximum likelihood estimation of econometric models

Vuong, 1987, Generalized inverses and asymptotic properties of Wald tests, Economics Letters, 24, 343, 10.1016/0165-1765(87)90069-3

Wald, 1943, Tests of statistical hypotheses concerning several parameters when the number of observations is large, Transactions of the American Mathematical Society, 54, 426, 10.1090/S0002-9947-1943-0012401-3