In this paper we provide a convenient econometric framework for the analy-sis of nonlinear dependence in financial applications. We introduce models withconstrained nonparametric dependence, which specify the conditional distrib-ution or the copula in terms of a one-dimensional functional...

We study the asymptotic properties of a Tikhonov Regularized (TiR) estimator of a functional parameter based on a minimum distance principle for nonparametric conditional moment restrictions. The estimator is computationally tractable and takes a closed form in the linear case. We derive its...

How do people learn? We assess, in a distribution-free manner, subjects' learning and choice rules in dynamic two-armed bandit (probabilistic reversal learning) experiments. To aid in identification and estimation, we use auxiliary measures of subjects' beliefs, in the form of their...

This paper extends the nonparametric method to estimate labor supply developed by Blomquist and Newey (2002) to handle cases in which there are individuals who do not work. The method is then applied to married women in Sweden from 1973 to 1999. For 1999, I find an aggregate uncompensated wage...

This paper evaluates the tax reforms carried out in Sweden between 1980 and 1991. We use a recently developed nonparametric labor supply function to account for the behavorial responses of the taxed individuals. We decompose the tax reform to study how the separate components influence hours of...

The basic idea in this paper is that labor supply can be viewed as a function of the entire budget set, so that one way to account non-parametrically for a nonlinear budget set is to estimate a nonparametric regression where the variable in the regression is the budget set. In the special case...

This paper focuses on the robust Effcient Method of Moments (EMM) estimation of a general parametric stationary process and proposes a broad framework for constructing robust EMM statistics in this context. This extends the application field of robust statistics to very general time series...

In the current paper, the finite-sample stability of various implementations of the KPSS test is studied. The implementations considered differ in how the so-called long-run variance is estimated under the null hypothesis. More specifically, the effects that the choice of kernel, the value of...

Consider an observed binary regressor D and an unobserved binary variable D*, both of which affect some other variable Y. This paper considers nonparametric identification and estimation of the effect of D on Y , conditioning on D* = 0. For example, suppose Y is a person's wage, the unobserved D...

This paper investigates the bias and the Bahadur representation of a local polynomial estimator of the conditional quantile function and its derivatives. The bias and Bahadur remainder term are studied uniformly with respect to the quantile level, the covariates and the smoothing parameter. The...