In the present paper we propose a new method, the Penalized Adaptive Method (PAM), for a data driven detection of structure changes in sparse linear models. The method is able to allocate the longest homogeneous intervals over the data sample and simultaneously choose the most proper variables...

There are many economic parameters that depend on nonparametric first steps. Examples include games, dynamic discrete choice, average consumer surplus, and treatment effects. Often estimators of these parameters are asymptotically equivalent to a sample average of an object referred to as the...

The estimation of the holding periods of financial products has to be done in a dynamic process in which the size of the observation time interval influences the result. Small intervals will produce smaller average holding periods than bigger ones. The approach developed in this paper offers the...

There are many economic parameters that depend on nonparametric first steps. Examples include games, dynamic discrete choice, average exact consumer surplus, and treatment effects. Often estimators of these parameters are asymptotically equivalent to a sample average of an object referred to as...

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...

Having in view some algebraical properties of the Student Test statistics, in this paper a new indicator is proposed in order to evaluate the quality of estimation in case of a linear regression with three explanatory variables, when OLS method is used. The respective indicator, named Synthesis...

Soft regression is a regression technique based on fuzzy information processing and heuristic information processing methods. However, following the practical use of the method, it was found that two aspects of the calculations pertaining to the relative weights of explanatory variables could be...

A regression model is considered where earnings are explained by schooling and ability. It is assumed that schooling is measured with error and that there are no data on ability. Regressing earnings on observed schooling then yields an estimate of the return to schooling that is subject to...

In this paper, I examine the properties of the class of generalized empirical likelihood estimators of moment-condition models. These nonparametric likelihood estimators satisfy exactly the moment conditions and automatically remove any bias due to a lack of centering. Moreover, the bias of the...

In this paper we show how the assumption that higher moments do not depend on the regressors can be exploited in a GMM framework, and we provide very simple estimators that are equivalent to GMM estimators. These simple estimators can be calculated by linear regressions which have been augmented...