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Found 3 papers, 2 papers with code
Monitoring the Economy in Real Time: Trends and Gaps in Real Activity and Prices
We propose two specifications of a real-time mixed-frequency semi-structural time series model for evaluating the output potential, output gap, Phillips curve, and Okun's law for the US.
Deep Dynamic Factor Models
A novel deep neural network framework -- that we refer to as Deep Dynamic Factor Model (D$^2$FM) --, is able to encode the information available, from hundreds of macroeconomic and financial time-series into a handful of unobserved latent states.
A Model of the Fed's View on Inflation
We develop a medium-size semi-structural time series model of inflation dynamics that is consistent with the view - often expressed by central banks - that three components are important: a trend anchored by long-run expectations, a Phillips curve and temporary fluctuations in energy prices.
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