In discrete
choice models, a typical individual chooses an alternative out of a set with a
finite number of alternatives. Each
alternative is characterized by a vector of attributes. The individual is assumed to choose the
one that maximizes his utility over the set of alternatives. The utility that the individual derives
from each alternative is assumed to possess observable and unobservable
components. Estimation of discrete
choice models allow one to predict the demand for new products, when these are
characterized by a vector of attributes that existent products possess. They also allow one to make welfare
calculations, once the utilities of the consumers are estimated.

**Published
papers:**

Briesch, R., P. Chintagunta, and
R.L. Matzkin (2009) "Nonparametric Discrete Choice Models with
Unobserved Heterogeneity," *Journal of
Business and Economic Statistics, *, Vol. 28, No. 2.

Matzkin, R.L. (2008) “Non-parametric Structural
Models” forthcoming in *The
New Palgrave Dictionary in Economics,* Macmillan.

Matzkin, R.L. (2008) “Non-parametric Structural
Models” forthcoming in *The
New Palgrave Dictionary in Economics,* Macmillan.

Matzkin, R.L.
(2007) “Nonparametric Identification,” in *Handbook of Econometrics,* Vol. 6b,
edited by J.J. Heckman and E.E. Leamer, Elsevier Science.

Matzkin, R.L.
(2007) “Nonparametric Survey Response Errors,” *International
Economic Review, *Vol. 48, No. 4.

Matzkin, R.L.
(2007) “Heterogeneous Choice,” in *Advances in Economics and Econometrics, Theory
and Applications, Ninth World Congress of the Econometric Society,* edited by R. Blundell, W. Newey, and T. Persson, Cambridge University Press.

Altonji, J. and
R.L. Matzkin (2005), “Cross Section and Panel Data Estimators for Nonseparable Models with Endogenous Regressors,” *Econometrica, *Vol.
73, No. 3, leading article, p. 1053-1102.

Briesch, R., P.
Chintagunta, and R.L. Matzkin (2002), “Semiparametric
Estimation of Choice Brand Behavior,” *Journal of the
American Statistical Association,* Vol. 97, No. 460, Applications and Case
Studies, p. 973-982.

Matzkin,
R.L. (1994) “Restrictions of Economic Theory in
Nonparametric Methods,” *Handbook of Econometrics,* Vol. 4, edited
by C.F. Engel and D.L. McFadden, Elsevier.

Matzkin, R.L.
(1993) “Nonparametric Identification and
Estimation of Polychotomous Choice Models,” *Journal of Econometrics*, Vol. 58.

Matzkin, R.L.
(1992) “Nonparametric and Distribution-Free Estimation of the
Binary Choice and the Threshold Crossing Models”, * Econometrica*, Vol. 60, No. 2, leading article, P. 239.

Matzkin, R.L.
(1991) “Semiparametric Estimation of Monotone and Concave Utility Functions
for Polychotomous Choice Models,’’ * Econometrica*, Vol. 59, No. 5, pp. 1315-1327.

Matzkin, R.L.
(1991) “A Nonparametric Maximum Rank Correlation Estimator” in *Nonparametric and Semiparametric Methods in
Econometrics and Statistics*, Cambridge: Cambridge University Press, edited
by W. Barnett, J. Powell, and G. Tauchen.

Matzkin, R.L.
(1991), “A Nonparametric Maximum Rank Correlation
Estimator”
in Barnett, J. Powell, and G. Tauchen (eds.) *Nonparametric and Semiparametric
Methods in Econometrics and Statistics*, Cambridge: Cambridge University Press.

**Some
discussion papers:**

Matzkin, R.L.
(2011) "Identification of Limited Dependent Variable
Models with Simultaneity and Unobserved Heterogeneity," mimeo, UCLA.

Matzkin, R.L. (2005)
"Identification in Nonparametric Simultaneous
Equations," mimeo, Northwestern University.

Jensen, M., P.
Liu, D. McFadden, and R.L. Matzkin (2004) “The Browser War: Econometric
analysis of Markov-Perfect Equilibrium in Markets with Network Effects,”
mimeo, University of California at Berkeley.

Matzkin, R.L. (2004) "Unobservable Instruments," mimeo, Northwestern University.