Quasi-Bayesian analysis of nonparametric instrumental variables models
نویسندگان
چکیده
منابع مشابه
Instrumental Variables Estimation of Nonparametric Models with Discrete Endogenous Regressors
This paper presents new instrumental variables estimators for nonparametric models with discrete endogenous regressors. The model speci cation is su ciently general to include structural models, triangular simultaneous equations and certain models of measurement error. Restricting the analysis to discrete endogenous regressors is an integral component of the analysis since a similar model with ...
متن کاملApplied Nonparametric Instrumental Variables Estimation
Instrumental variables are widely used in applied econometrics to achieve identification and carry out estimation and inference in models that contain endogenous explanatory variables. In most applications, the function of interest (e.g., an Engel curve or demand function) is assumed to be known up to finitely many parameters (e.g., a linear model), and instrumental variables are used identify ...
متن کاملSpecification Testing in Nonparametric Instrumental Variables Estimation
In nonparametric instrumental variables estimation, the function being estimated is the solution to an integral equation. A solution may not exist if, for example, the instrument is not valid. This paper discusses the problem of testing the null hypothesis that a solution exists against the alternative that there is no solution. We give necessary and sufficient conditions for existence of a sol...
متن کاملNonlinear and Nonparametric Regression and Instrumental Variables
We consider regression when the predictor is measured with error and an instrumental variable is available. The regression function can be modeled linearly, nonlinearly, or nonparametrically. Our major new result shows that the regression function and all parameters in the measurement error model are identified under relatively weak conditions, much weaker than previously known to imply identif...
متن کاملNonparametric Methods for Inference in the Presence of Instrumental Variables
We suggest two nonparametric approaches, based on kernel methods and orthogonal series to estimating regression functions in the presence of instrumental variables. For the first time in this class of problems, we derive optimal convergence rates, and show that they are attained by particular estimators. In the presence of instrumental variables the relation that identifies the regression funct...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 2013
ISSN: 0090-5364
DOI: 10.1214/13-aos1150