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Adaptive nonparametric instrumental variables estimation : empirical choice of the regularisation parameter

Horowitz, Joel - 2012

In nonparametric instrumental variables estimation, the mapping that identifies the function of interest, g say, is … discontinuous and must be regularised (that is, modified) to make consistent estimation possible. The amount of modification is … in applications are not yet available. This paper presents such a method for use in series estimation, where the …

Persistent link: https://www.econbiz.de/10009760143

Compactness of infinite dimensional parameter spaces

Freyberger, Joachim; Masten, Matthew - 2015

We provide general compactness results for many commonly used parameter spaces in nonparametric estimation. We consider … instrumental variables estimation. …

Persistent link: https://www.econbiz.de/10011412122

Recovering latent variables by matching

Arellano, Manuel; Bonhomme, Stéphane - 2020

We propose an optimal-transport-based matching method to nonparametrically estimate linear models with independent latent variables. The method consists in generating pseudo-observations from the latent variables, so that the Euclidean distance between the model’s predictions and their matched...

Persistent link: https://www.econbiz.de/10012152500

Nonparametric stochastic discount factor decomposition

Christensen, Timothy - 2015

We introduce econometric methods to perform estimation and inference on the permanent and transitory components of the …

Persistent link: https://www.econbiz.de/10010532537

Nonparametric Euler equation identification and estimation

Escanciano, Juan Carlos; Hoderlein, Stefan; Lewbel, Arthur - 2015

We consider nonparametric identification and estimation of pricing kernels, or equivalently of marginal utility … estimation with the computation of a matrix eigenvector problem. Our estimator avoids the ill-posed inverse issues associated …

Persistent link: https://www.econbiz.de/10011341255

Semiparametrically efficient estimation of the average linear regression function

Graham, Bryan S.; Pinto, Cristine Campos de Xavier - 2018

Let Y be an outcome of interest, X a vector of treatment measures, and W a vector of pre-treatment control variables. Here X may include (combinations of) continuous, discrete, and/or non-mutually exclusive "treatments". Consider the linear regression of Y onto X in a subpopulation homogenous in...

Persistent link: https://www.econbiz.de/10011924562

Perceived shocks and impulse responses

Giacomini, Raffaella; Lu, Jason; Smetanina, Katja - 2024

This paper develops a novel approach that leverages the information contained in expectations datasets to derive empirical measures of beliefs regarding economic shocks and their dynamic effects. Utilizing a panel of expectation revisions for a single variable across multiple horizons, we...

Persistent link: https://www.econbiz.de/10015123512

Identification and shape restrictions in nonparametric instrumental variables estimation

Freyberger, Joachim; Horowitz, Joel - 2013

This paper is concerned with inference about an unidentified linear function, L(g), where the function g satisfies the relation Y=g(X)+U; E(U |W)=0. In this relation, Y is the dependent variable, X is a possibly endogenous explanatory variable, W is an instrument for X and U is an unobserved...

Persistent link: https://www.econbiz.de/10009761386

Asymptotic theory for nonparametric regression with spatial data

Robinson, Peter M. - 2011

Nonparametric regression with spatial, or spatio-temporal, data is considered. The conditional mean of a dependent variable, given explanatory ones, is a nonparametric function, while the conditional covariance reflects spatial correlation. Conditional heteroscedasticity is also allowed, as well...

Persistent link: https://www.econbiz.de/10008906533

Identification and shape restrictions in nonparametric instrumental variables estimation

Freyberger, Joachim; Horowitz, Joel - 2012

This paper is concerned with inference about an unidentified linear functional, L(g), where the function g satisfies the relation Y=g(x) + U; E(U/W) = 0. In this relation, Y is the dependent variable, X is a possibly endogenous explanatory variable, W is an instrument for X, and U is an...

Persistent link: https://www.econbiz.de/10009554348