552 Discrete Choice Modeling
Goldberger, A. (1987)Functional Form and Utility: A Review of Consumer Demand Theory.
Boulder, Colo: Westview Press.
Gourieroux, C. and A. Monfort (1996)Simulation-Based Methods Econometric Methods. Oxford:
Oxford University Press.
Greene, W. (1992) A statistical model for credit scoring. Department of Economics, Stern
School of Business, New York University, Working Paper 92–29.
Greene, W. (1995) Sample selection in the poisson regression model. Working Paper No.
EC-95–6, Department of Economics, Stern School of Business, New York University.
Greene, W. (1996) Marginal effects in the bivariate probit model. Working Paper No. 96–11,
Department of Economics, Stern School of Business, New York University.
Greene, W. (1997) FIML estimation of sample selection models for count data. Working Paper
No. 97–02, Department of Economics, Stern School of Business, New York University.
Greene, W. (1998) Gender economics courses in liberal arts colleges: further results.Journal
of Economic Education 29 (4), 291–300.
Greene, W. (2001) Fixed and random effects in nonlinear models. Working Paper No. EC-01–
01, Department of Economics, Stern School of Business, New York University.
Greene, W. (2004a) Convenient estimators for the panel probit model.Empirical Economics
29 (1), 21–47.
Greene, W. (2004b) Fixed effects and bias due to the incidental parameters problem in the
Tobit model.Econometric Reviews 23 (2), 125–47.
Greene, W. (2006) Censored data and truncated distributions. In T. Mills and K. Patterson
(eds.),Palgrave Handbook of Econometrics,Volume 1. Basingstoke: Palgrave Macmillan.
Greene, W. (2007a) LIMDEP/NLOGIT manual. Plainview, New York: Econometric
Software, Inc.
Greene, W. (2007b) A method of incorporating sample selection in a nonlinear model.
Working Paper No. 07–16, Department of Economics, Stern School of Business, New York
University.
Greene, W. (2008a)Econometric Analysis(sixth edition). Upper Saddle River: Prentice Hall.
Greene, W. (2008b) Functional forms for the negative binomial model for count data.
Economics Letters 99 , 585–90.
Greene, W. and D. Hensher (2006) Accounting for heterogeneity in the variance of unob-
served effects in mixed logit models. Transportation Research, B: Methodology 40 (1),
75–92.
Greene, W., S. Rhine and M. Toussaint-Comeau (2006) The importance of check-cashing
businesses to the unbanked: a look at racial/ethnic differences.Review of Economics and
Statistics 88 (1), 146–57.
Groot, W. and H.M. Van den Brink (2003) Firm-related training tracks: a random effects
ordered probit model. University of Amsterdam, http://www1.fee.uva.nl/scholar/wp/wp23-
01.pdf.
Gurmu, S. (1997) Semi-parametric estimation of hurdle regression models with an application
to Medicaid utilization.Journal of Applied Econometrics 12 (3), 225–42.
Hardle, W. and C. Manski (1993) Nonparametric and semiparametric approaches to discrete
response analysis.Journal of Econometrics 58 , 1–274.
Harris, M. and X. Zhao (2007) Modelling tobacco consumption with a zero inflated ordered
probit model. School of Business and Economics, Monash University, Working Paper 14/04.
Hausman, J., B. Hall and Z. Griliches (1984) Economic models for count data with an
application to the patents–R&D relationship.Econometrica 52 , 909–38.
Heckman, J. (1978) State dependence against the hypothesis of spurious state dependence.
Annalse de l’INSEE 30 , 227–69.
Heckman, J. (1979) Sample selection bias as a specification error.Econometrica 47 , 153–61.
Heckman, J. (1981a) Statistical models for discrete panel data. In C. Manski and D. McFadden
(eds.),Structural Analysis of Discrete Data with Econometric Applications. Cambridge, Mass.:
MIT Press.