BoC paper offers monetary policy ‘decision synthesis’

Authors say model combination method helps capture complexities of decision-making

Bank of Canada, Ottawa
Bank of Canada, Ottawa
Photo: Matthew Liteplo Photography

Research published by the Bank of Canada proposes a means of combining econometric models to improve monetary policy decision-making.

Authors Tony Chernis, Gary Koop, Emily Tallman and Mike West say standard methods of combining models are too simplistic, and typically focus only on how well the model fits the data and forecasting one step ahead.

Their proposed alternative, based on “Bayesian predictive decision synthesis” (BPDS), enables models to be weighted not only on past performance but also

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