We consider testing for correct specification of a nonparametric instrumental variable regression. In this ill-posed inverse problem setting, the test statistic is based on the empirical minimum distance criterion corresponding to the conditional moment restriction evaluated with a Tikhonov...

This article introduces and investigates the properties of a new bootstrap method for time-series data, the kernel block bootstrap. The bootstrap method, although akin to, offers an improvement over the tapered block bootstrap of Paparoditis and Politis (2001), admitting kernels with unbounded...

We provide stylized facts on the evolving shape dynamics of the US personal income distribution from 1962 to 2000. Based on adaptive kernel density estimation, we propose an adaptive bootstrap test for multimodality. Our results indicate that multimodality has been a predominant feature of the...

This paper is concerned with tests of restrictions on the sample path of conditional quantile processes. These tests are tantamount to assessments of lack of fit for models of conditional quantile functions or more generally as tests of how certain covariates affect the distribution of an...

We propose a flexible framework that allows for the relationship between housing prices and their determinants to vary over time. Our model incorporates housing-specific characteristics and macroeconomic variables, while accounting for a gradual global trend that reflects the unobserved external...

Consumption based equivalence scales are estimated by applying the extended partially linear model (EPLM) to the 1998 Income and Consumption Survey (EVS) of Germany. The chosen flexible semiparametric specification is able to capture a large variety of functional forms of household expenditure...

Consumption based equivalence scales are estimated by applying the extended partially linear model (EPLM) to the 1998 Income and Consumption Survey (EVS) carried out in Germany. In this model the equivalence scales are identified by virtue of nonlinearities in household demand. Therefore, the...

A new heteroskedastic hedonic regression model is suggested which takes into account time-varying volatility and is applied to a blue chips art market. A nonparametric local likelihood estimator is proposed, and this is more precise than the often used dummy variables method. The empirical...

In this paper, we study a general class of semiparametric optimization estimators of a vector-valued parameter. The criterion function depends on two types of infinite-dimensional nuisance parameters: a conditional expectation function that has been estimated nonparametrically using generated...

We analyze the properties of non- and semiparametric estimation procedures involving nonparametric regression with generated covariates. Such estimators appear in numerous econometric applications, including nonparametric estimation of simultaneous equation models, sample selection models,...