John Geweke

University of Technology, Sydney

Bayesian statisticsStatisticsBayesian probabilityMarkov chain Monte CarloSeries (mathematics)EconometricsGibbs samplingBayesian inferenceEconomicsFrequentist inferencePrior probabilityEconometric modelMonte Carlo methodInferenceApplied mathematicsMathematicsComputer sciencePosterior probabilityBayesian econometricsMedicineMarkov chain

211Publications

68H-index

18.8kCitations

Publications 172

#1John GewekeH-Index: 68

#2Garland DurhamH-Index: 9

#1Garland Durham (CPP: California State Polytechnic University, Pomona)H-Index: 9

#2John Geweke (UTS: University of Technology, Sydney)H-Index: 68

Last. Fallaw Sowell (CMU: Carnegie Mellon University)H-Index: 10

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#1Gianni Amisano (Federal Reserve System)H-Index: 16

#2John Geweke (UW: University of Washington)H-Index: 68

Prediction of macroeconomic aggregates is one of the primary functions of macroeconometric models, including dynamic factor models, dynamic stochastic general equilibrium models, and vector autoregressions. This study establishes methods that improve the predictions of these models, using a representative model from each class and a canonical 7-variable postwar US data set. It focuses on prediction over the period 1966 through 2011. It measures the quality of prediction by the probability densit...

Sequentially Adaptive Bayesian Learning for a Nonlinear Model of the Secular and Cyclical Behavior of US Real GDP

#1John Geweke (UTS: University of Technology, Sydney)H-Index: 68

There is a one-to-one mapping between the conventional time series parameters of a third-order autoregression and the more interpretable parameters of secular half-life, cyclical half-life and cycle period. The latter parameterization is better suited to interpretation of results using both Bayesian and maximum likelihood methods and to expression of a substantive prior distribution using Bayesian methods. The paper demonstrates how to approach both problems using the sequentially adaptive Bayes...

Comment on: Reflections on the Probability Space Induced by Moment Conditions with Implications for Bayesian Inference

#1John Geweke (UTS: University of Technology, Sydney)H-Index: 68

#1Hazel Bateman (UNSW: University of New South Wales)H-Index: 16

#2Christine Eckert (UTS: University of Technology, Sydney)H-Index: 12

Last. Susan Thorp (USYD: University of Sydney)H-Index: 19

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Efficient investment of personal savings depends on clear risk disclosures. We study the propensity of individuals to violate some implications of expected utility under alternative "mass-market" descriptions of investment risk, using a discrete choice experiment. We found violations in around 25% of choices, and substantial variation in rates of violation, depending on the mode of risk disclosure and participants’ characteristics. When risk is described as the frequency of returns below or abov...

A comment on Christoffersen, Jacobs, and Ornthanalai (2012), “Dynamic jump intensities and risk premiums: Evidence from S&P 500 returns and options”

#1Garland Durham (California Polytechnic State University)H-Index: 9

#2John Geweke (CSU: Colorado State University)H-Index: 68

Last. Pulak Ghosh (IIMB: Indian Institute of Management Bangalore)H-Index: 19

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Christoffersen, Jacobs, and Ornthanalai (2012) (CJO) propose an interesting and useful class of generalized autoregressive conditional heteroskedasticity (GARCH)-like models with dynamic jump intensity, and find evidence that the models not only fit returns data better than some commonly used benchmarks but also provide substantial improvements in option pricing performance. While such models pose difficulties for estimation and analysis, CJO propose an innovative approach to filtering intended ...

#1John Geweke (UTS: University of Technology, Sydney)H-Index: 68

#2Lea Petrella (Sapienza University of Rome)H-Index: 15

This paper shows that regular fractional polynomials can approximate regular cost, production and utility functions and their first two derivatives on closed compact subsets of the strictly positive orthant of Euclidean space arbitrarily well. These functions therefore can provide reliable approximations to demand functions and other economically relevant characteristics of tastes and technology. Using canonical cost function data, it shows that full Bayesian inference for these approximations c...

Public policy setting often involves quantitative choices with quantitative outcomes. Yet unqualified statements about the precise consequences of alternative choices characterize much of the policy analysis bearing on these decisions. Public Policy in an Uncertain World: Analysis and Decisions by Charles F. Manski characterizes and richly illustrates the nature of this unwarranted certitude. It details specific constructive alternatives on which the economics profession has achieved varying deg...

#1Bart D. Frischknecht (UTS: University of Technology, Sydney)H-Index: 8

#2Christine Eckert (UTS: University of Technology, Sydney)H-Index: 12

Last. Jordan J. Louviere (UTS: University of Technology, Sydney)H-Index: 102

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Abstract This paper demonstrates a method for estimating logit choice models for small sample data, including single individuals, that is computationally simpler and relies on weaker prior distributional assumptions compared to hierarchical Bayes estimation. Using Monte Carlo simulations and online discrete choice experiments, we show how this method is particularly well suited to estimating values of choice model parameters from small sample choice data, thus opening this area to the applicatio...

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