What do instrumental variable models deliver with discrete dependent variables?
نویسندگان
چکیده
منابع مشابه
Instrumental Variable Models for Discrete Outcomes
Single equation instrumental variable models for discrete outcomes are shown to be set not point identifying for the structural functions that deliver the values of the discrete outcome. Identi ed sets are derived for a general nonparametric model and sharp set identi cation is demonstrated. Point identi cation is typically not achieved by imposing parametric restrictions. The extent of an iden...
متن کاملGeneralised instrumental variable models
The ability to allow for flexible forms of unobserved heterogeneity is an essential ingredient in modern microeconometrics. In this paper we extend the application of instrumental variable (IV) methods to a wide class of problems in which multiple values of unobservable variables can be associated with particular combinations of observed endogenous and exogenous variables. In our Generalized In...
متن کاملGeneralized instrumental variable models
The ability to allow for flexible forms of unobserved heterogeneity is an essential ingredient in modern microeconometrics. In this paper we extend the application of instrumental variable (IV) methods to a wide class of problems in which multiple values of unobservable variables can be associated with particular combinations of observed endogenous and exogenous variables. In our Generalized In...
متن کاملRecentered and Rescaled Instrumental Variable Estimation of Tobit and Probit Models with Errors in Variables
Since Durbin (1954) and Sargan (1958), instrumental variable (IV) method has long been one of the most popular procedures among economists and other social scientists to handle linear models with errors-in-variables. A direct application of this method to nonlinear errors-in-variables models, however, fails to yield consistent estimators. This article restricts attention to Tobit and Probit mod...
متن کامل[hal-00261403, v1] On instrumental variable-based methods for errors-in-variables model identification
In this paper, the problem of identifying stochastic linear discrete-time systems from noisy input/output data is addressed. The input noise is supposed to be white, while the output noise is assumed to be coloured. Some methods based on instrumental variable techniques are studied and compared to a least squares bias compensation scheme with the help of Monte Carlo simulations.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2013