We present estimators for nonparametric functions that depend on unobservable random vari-ables in nonadditive ways. The distributions of the unobservable random terms are assumed to be unknown. We show how properties that may be implied by economic theory, such as monotonicity, homogeneity of degree one, and separability can be used to identify the unknown, nonparametric functions and distributions. We also present convenient normalizations, to use when the properties of the functions are unknown. The estimators for the nonparametric distributions and for the non-parametric functions and their derivatives are shown to be consistent and asymptotically normal. The results of a limited simulation study are presented
Multinomial choice and other nonlinear models are often used to estimate demand. We show how to nonp...
This paper develops a semiparametric method for estimating the nonrandom part V ( ) of a random util...
This paper studies the estimation of fully nonparametric models in which we can not identify the val...
We present estimators for nonparametric functions that are nonadditive in unobservable random terms....
This paper studies the identification and estimation of a nonparametric nonseparable dyadic model wh...
In structural economic models, individuals are usually characterized as solving a de-cision problem ...
When one wants to estimate a model without specifying the functions and distributions parametrically...
summary:The problem of estimation of distribution functions or fractiles of non- negative random var...
in Economic Theory and Econometrics ” for their useful comments. We are also thankful to Myrna Woode...
This paper explores the adoption of a probabilistic nonparametric estimator in economics. First, it ...
This paper is concerned with identification and estimation of non-separable models. It studies a ver...
This dissertation studies econometric questions in the context of three different methods that are f...
In this paper we give simple proofs of identification results in discrete choice models for the case...
This paper develops a semiparametric method for estimating the nonrandom part V ( ) of a random util...
Linearity in a causal relationship between a dependent variable and a set of regressors is a common ...
Multinomial choice and other nonlinear models are often used to estimate demand. We show how to nonp...
This paper develops a semiparametric method for estimating the nonrandom part V ( ) of a random util...
This paper studies the estimation of fully nonparametric models in which we can not identify the val...
We present estimators for nonparametric functions that are nonadditive in unobservable random terms....
This paper studies the identification and estimation of a nonparametric nonseparable dyadic model wh...
In structural economic models, individuals are usually characterized as solving a de-cision problem ...
When one wants to estimate a model without specifying the functions and distributions parametrically...
summary:The problem of estimation of distribution functions or fractiles of non- negative random var...
in Economic Theory and Econometrics ” for their useful comments. We are also thankful to Myrna Woode...
This paper explores the adoption of a probabilistic nonparametric estimator in economics. First, it ...
This paper is concerned with identification and estimation of non-separable models. It studies a ver...
This dissertation studies econometric questions in the context of three different methods that are f...
In this paper we give simple proofs of identification results in discrete choice models for the case...
This paper develops a semiparametric method for estimating the nonrandom part V ( ) of a random util...
Linearity in a causal relationship between a dependent variable and a set of regressors is a common ...
Multinomial choice and other nonlinear models are often used to estimate demand. We show how to nonp...
This paper develops a semiparametric method for estimating the nonrandom part V ( ) of a random util...
This paper studies the estimation of fully nonparametric models in which we can not identify the val...