A reasonable result from a complex simulation does not imply validity of the underlying formulations: robustness checks are essential. We analyze the disturbance scheme for solder joint lifetime prediction from this viewpoint and results suggest it may not provide the previously reported...

We consider robust serial correlation tests in autoregressive models with exogenous variables (ARX). Since the least squares estimators are not robust when outliers are present, a new family of estimators is introduced, called residual autocovariances for ARX (RA-ARX). They provide resistant...

Robust control theory is a tool for assessing decision rules when a decision maker distrusts either the specification of transition laws or the distribution of hidden state variables or both. Specification doubts inspire the decision maker to want a decision rule to work well for a ∅ of models...

This paper explores Knightian model uncertainty about dynamic misspecification as a possible explanation of the considerable difference between estimated interest rate rules and optimal feedback descriptions of monetary policy. In the literature on robust control, Knightian uncertainty about a...

We propose a framework for estimation and inference when the model may be misspecified. We rely on a local asymptotic approach where the degree of misspecification is indexed by the sample size. We construct estimators whose mean squared error is minimax in a neighborhood of the reference model,...

We propose a method for forecasting individual outcomes and estimating random effects in linear panel data models and value-added models when the panel has a short time dimension. The method is robust, trivial to implement and requires minimal assumptions. The idea is to take a weighted average...