This paper revisits Wald's (1947) sequential experimentation paradigm, now assuming that an impatient decision maker can run variable-size experiments each period at some increasing and strictly convex cost before finally choosing an irreversible action. We translate this natural discrete time...

The present paper introduces new sign tests for testing for conditionally symmetric martingale-difference assumptions as well as for testing that conditional distributions of two (arbitrary) martingale-difference sequences are the same. Our analysis is based on the results that demonstrate that...

Beverage consumption occurs many times a day in response to a variety of needs that change throughout the day. In making their choices, consumers self-regulate their consumption by managing short run needs (e.g., hydration and mood pickup) with long-term goals (e.g., health). Using unique...

This paper offers a general approach to time series modeling that attempts to reconcile classical and methods. The central idea put forward to achieve reconciliation is that the Bayesian approach relies implicitly a frame of reference for the data generating mechanism that is quite different...

Recent time series methods are applied to the problem of forecasting New Zealand's real GDP. Model selection is conducted within autoregressive (AR) and vector autoregressive (VAR) classes, allowing for evolution in the form of the models over time. The selections are performed using the Schwarz...

This paper analyzes the behavior of posterior distributions under the Jeffreys prior in a simultaneous equations model. The case under study is that of a general limited information setup with n + 1 endogenous variables. The Jeffreys prior is shown to give rise to a marginal posterior density...

In his paper "To Criticize the Critics" (1991), Peter Phillips discusses Bayesian methodology for time series models. The main point that Uhlig and I set out to make, however, was that careful consideration of the implications of the likelihood principle suggests that much of the recent work...

The Kalman filter is sued to derive updating equations for the Bayesian data density in discrete time linear regression models with stochastic regressors. The implied "Bayes model" has time varying parameters and conditionally heterogeneous error variances. A sigma-finite "Bayes model" measure...

This paper reports an empirical application of new Baynesian methodology to Australian data on consumption, income, liquid assets and inflation. The methods involve the use of objective model based reference priors and objective posterior odds test criteria. The paper provides an overview of...

This paper provides detailed responses to the following 8 discussants of my paper "To Criticize the Critics: An Objective Bayesian Analysis of Stochastic Trends": Gary Koop and Mark Steel; Edward Leamer; In-Moo Kim and G.S. Maddala Dale J. Poirier; Peter C. Schotman and Herman K. van Dijk; James...