16,862 research outputs found
Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting
We develop the methodology and a detailed case study in use of a class of
Bayesian predictive synthesis (BPS) models for multivariate time series
forecasting. This extends the recently introduced foundational framework of BPS
to the multivariate setting, with detailed application in the topical and
challenging context of multi-step macroeconomic forecasting in a monetary
policy setting. BPS evaluates-- sequentially and adaptively over time-- varying
forecast biases and facets of miscalibration of individual forecast densities,
and-- critically-- of time-varying inter-dependencies among them over multiple
series. We develop new BPS methodology for a specific subclass of the dynamic
multivariate latent factor models implied by BPS theory. Structured dynamic
latent factor BPS is here motivated by the application context-- sequential
forecasting of multiple US macroeconomic time series with forecasts generated
from several traditional econometric time series models. The case study
highlights the potential of BPS to improve of forecasts of multiple series at
multiple forecast horizons, and its use in learning dynamic relationships among
forecasting models or agents
Learning from Experts
The survey is concerned with the issue of information transmission from experts to non-experts. Two main approaches to the use of experts can be traced. According to the game-theoretic approach expertise is a case of asymmetric information between the expert, who is the better informed agent, and the non-expert, who is either a decision-maker or an evaluator of the expert’s performance. According to the Bayesian decision-theoretic approach the expert is the agent who announces his probabilistic opinion, and the non-expert has to incorporate that opinion into his beliefs in a consistent way, despite his poor understanding of the expert’s substantive knowledge. The two approaches ground the relationships between experts and non-experts on such different premises that their results are very poorly connected.Expert, Information Transmission, Learning
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