Abstract: Inference in the inequality constrained normal linear regression model is approached as a problem in Bayesian inference, using a prior that is the product of a conventional uninformative distribution and an indicator function representing the inequality constraints. The posterior distribution is calculated using Monte Carlo numerical integration, which leads directly to the evaluation of expected values of functions of interest. This approach is compared with others that have been proposed. Three empirical examples illustrate the utility of the proposed methods using an inexpensive 32-bit microcomputer.
Abstract: Structural and stochastic neutrality have refutable implications for aggregate economic time series only in conjunction with other maintained hypotheses. Simple and commonly employed maintained hypotheses lead to restrictions on measures of feedback and their decomposition by frequency. These restrictions also suggest an empirical interpretation of the notional long and short runs. It is found that a century of annual U.S. data, and postwar monthly data, consistently support structural superneutrality of money with respect to output and the real rate of return and consistently reject its superneutrality with respect to velocity. A quantitative characterization of the long run is suggested.
Abstract: Methods for exact Bayesian inference under a uniform diffuse prior are set forth for the continuous time homogeneous Markov chain model. It is shown how the exact posterior distribution of any function of interest may be computed using Monte Carlo integration. The solution handles the problems of embeddability in a very natural way, and provides (to our knowledge) the only solution that systematically takes this problem into account. The methods are illustrated using several sets of data.
Abstract: The axiomatic derivation of mobility indices for first-order Markov chain models in discrete time is extended to continuous-time models. Many of the logical inconsistencies among axioms noted in the literature for the discrete time models do not arise for continuous time models. It is shown how mobility indices in continuous time Markov chains may be estimated from observations at two points in time. Specific attention is given to the case in which the states are fractiles, and an empirical example is presented.
Geweke, J. 1986, 'Modeling Conditional Variance', Econometric Reviews, vol. 5, no. 1, pp. 57-61.
Geweke, J. 1986, 'Fixed Investment in the American Business Cycle', The American Business Cycle: Continuity and Change, National Bureau of Economic Research, New York.
This paper systematically presents a knowledge-based geological prospecting system which is intended to provide consultation on geological mapping for the aerogeophysical prospecting interpreters. The system accepts the data of an aeromagnetic survey and an aeroradioactive survey, then it uses these data to identify magnetic anomalies and radioactive anomalies, to enclose the boundaries of the anomalous bodies, and finally to distinguish the lithologies of the anomalous bodies. Meanwhile, the system gives a confidence measure for each conclusion and answers the questions about the consultation. The capability of this system to provide the consultation relies on the knowledge the system has possessed. The knowledge has been offered by a panel of aerogeophysical prospecting domain experts.