TY  - BOOK
AU  - Li,Cong
AU  - Racine,Jeffrey S.
TI  - A smooth nonparametric conditional density test for categorical responses
SN  - 02664666
AV  - HB139.T52 ECO 
PY  - 2013///
CY  - Cambridge
PB  - Cambridge University Press
KW  - Nonparametric statistics
KW  - Statistical distribution
KW  - Estimation theory
KW  - Statistical test
N2  - We propose a consistent kernel-based specification test for conditional density models when the dependent variable is categorical/discrete. The method is applicable to popular parametric binary choice models such as the logit and probit specification and their multinomial and ordered counterparts, along with parametric count models, among others. The test is valid when the conditional density function contains both categorical and real-valued covariates. Theoretical support for the test and for a bootstrap-based version of the test is provided. Monte Carlo simulations are conducted to assess the finite-sample performance of the proposed method
UR  - https://doi.org/10.1017/S0266466612000382
ER  -