A method of deriving asymptotics for linear processes is introduced which uses an explicit algebraic decomposition of the linear filter. The method leads to substantial simplifications in the asymptotics and offers a unified approach to strong laws and central limit theory for linear processes....

This paper derives asymptotically optimal tests for testing problems in which a nuisance parameter exists under the alternative hypothesis but not under the null. The results of the paper are of interest, because the testing problem considered in non-standard and the classical asymptotic...

This paper provides an axiomatic model based on an extraneous random device generating objective probabilities for the derivation of expected utilities and subjective probabilities. Four basic axioms fully determine a real-valued utility function and a finitely additive subjective probability...

We provide methods of decomposing the variance of world national incomes into components in such a way as to indicate the most important risk-sharing opportunities, and, therefore, the most important missing international risk markets to establish. One method uses a total variance reduction...

A general model of a coalition production economy allowing set-up costs, indivisibilities, and non-convexities is developed. It is shown that for all sufficiently large replications, approximate cores of the economy are non-empty.

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 studies the finite sample distributions of estimators of the cointegrating vector of linear regression models with I(1) variables. Attention is concentrated on the least squares (OLS) and instrumental variables (IV) methods analyzed in other recent work (Phillips and Hansen (1988))....