A methodology is developed for obtaining consistent moment estimators of the parameters in probit models that include both exogenous and endogenous variables. The approach is based on the use of instrumental variables in the formulation of moment conditions in order to solve a system of equations from which the consistent estimators are derived. The moment conditions also enable the correlations between the endogenous variables and the error terms to be estimated. Comparisons with uncorrected maximum likelihood and Heckman's classic two-stage method using simulated data demonstrate that the proposed method generates consistent estimators with relatively smaller mean square errors. We also apply our method to a real data case, confirming the good estimation properties of our new approach.
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Univ Basel, Dept Business & Econ, Peter Merian Weg 6, CH-4002 Basel, Switzerland
ESCP Business Sch, Heubnerweg 8-10, D-14059 Berlin, GermanyUniv Basel, Dept Business & Econ, Peter Merian Weg 6, CH-4002 Basel, Switzerland
机构:
Univ Chicago, Dept Publ Hlth Sci, 5841 S Maryland Ave,Room W255,MC2000, Chicago, IL 60637 USA
Univ Chicago, Dept Med, 5841 S Maryland Ave, Chicago, IL 60637 USAUniv Chicago, Dept Publ Hlth Sci, 5841 S Maryland Ave,Room W255,MC2000, Chicago, IL 60637 USA
Konetzka, R. Tamara
Yang, Fan
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Univ Colorado Denver, Colorado Sch Publ Hlth, Dept Biostat & Informat, Aurora, CO USAUniv Chicago, Dept Publ Hlth Sci, 5841 S Maryland Ave,Room W255,MC2000, Chicago, IL 60637 USA
Yang, Fan
Werner, Rachel M.
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Univ Penn, Div Gen Internal Med, Philadelphia, PA 19104 USAUniv Chicago, Dept Publ Hlth Sci, 5841 S Maryland Ave,Room W255,MC2000, Chicago, IL 60637 USA
机构:
Univ N Carolina, Dept Math & Stat, Charlotte, NC 28223 USA
Xiamen Univ, Wang Yanan Inst Studies Econ, MOE Key Lab Econometr, Xiamen 361005, Fujian, Peoples R China
Xiamen Univ, Fujian Key Lab Stat Sci, Xiamen 361005, Fujian, Peoples R ChinaUniv N Carolina, Dept Math & Stat, Charlotte, NC 28223 USA
Cai, Zongwu
Xiong, Huaiyu
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Wells Fargo Bank, San Francisco, CA 94102 USAUniv N Carolina, Dept Math & Stat, Charlotte, NC 28223 USA