The results of analyzing experimental data using a parametric model may heavily depend on the chosen model. In this paper we propose procedures for the adequate selection of nonlinear regression models if the intended use of the model is among the following: prediction of future values of the...

A new likelihood-based panel cointegration test which allows a linear time trend in the data generating process is proposed. The test is an extension of the likelihood ratio type test with trend adjustment prior to testing to the panel data framework. Under the null hypothesis, the standardized...

We study the problem of estimating the mean of a normal distribution with known variance, when prior knowledge specifies that this mean lies in a bounded interval. The focus is on a minimax regret comparison of soft and hard threshold estimators, which have become very popular in the context of...

In regression analysis there is typically a large collection of competing models available from which we want to select an appropriate one. This paper is concerned with asymptotic properties of procedures for selecting linear models, which are based on certain data-dependent criteria such as...

We give an explicit PDE characterization for the solution of the problemof maximizing the utility of both terminal wealth and intertemporal consumption under model uncertainty. The underlying market model consists of a risky asset, whose volatility and long-term trend are driven by an external...

This paper explores implications of nominal rigidity characterized by a non-constanthazard function for aggregate dynamics. I derive the NKPC under an arbitrary hazardfunction and parameterize it with the Weibull duration model. The resulting Phillips curveinvolves lagged inflation and lagged...