The paper concerns the fixed-width confidence intervals for location based on M- estimators in the location model. A robust three-stage procedure is proposed and its asymptotic properties are studied. The performance of the procedure depends on some tuning parameters. Their effect on the...

Robust learning experiments confront participants with structurally different decision environments which they encounter, furthermore, repeatedly. Since the decision format does not depend on the rules (of game), forward looking deliberation (the shadow of the future) can be detected by...

This paper analyzes the performance of heteroskedasticity-and-autocorrelation-consistent (HAC) covariance matrix estimators in which the residuals are prewhitened using a vector autoregressive (VAR) filter. We highlight the pitfalls of using an arbitrarily fixed lag order for the VAR filter, and...

This paper examines monetary policy in Rudebusch and Svensson's (1999) two equation macroeconomic model when the policymaker recognizes that the model is an approximation and is uncertain about the quality of that approximation. It is argued that the minimax approach of robust control provides a...

In geostatistics, spatial data will be analysed that often come from irregularly distributed sampling locations. Interest is in modelling the data, i.e. estimating distributional parameters and then to predict the phenomenon under study at unobserved sites within the corresponding sampling...

In this paper we consider the asymptotic distribution of S -estimators in the nonlinear regression model with long-memory error terms. S - estimators are robust estimates with a high breakdown point and good asymptotic properties in the i.i.d case. They are constructed for linear regression. In...

The method for estimation and testing for cointegration put forward by Johansen assumes that the data are described by a vector autoregressive process. In this article we extend the data generating process to autoregressive moving average models without unit roots in the MA polynomial. We first...

Deviations from the center within a robust neighborhood may naturally be considered an infinite dimensional nuisance parameter. Thus, in principle, the semiparametric method may be tried, which is to compute the scores function for the main parameter minus its orthogonal projection on the closed...

This paper presents an approximate affinely adjustable robust counterpart for conic quadratic constraints. The theory is applied to obtain robust solutions to the problems of subway route design with implementation errors and a supply chain management with uncertain demands. Comparison of the...