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Why Has the U.S. Economy Stagnated since the Great Recession?

The Review of Economics and Statistics 2022 104(2), 246-258 open access
Abstract Since the Great Recession in 2007–2009, U.S. real GDP has failed to return to its previously projected path, a phenomenon widely associated with secular stagnation. We investigate whether this stagnation was due to hysteresis effects from the Great Recession, a persistent negative output gap following the recession, or slower trend growth for other reasons. To do so, we develop a new Markov-switching time series model of output growth that accommodates two different types of recessions: those that permanently alter the level of real GDP and those with only temporary effects. We also account for structural change in trend growth. Estimates from our model suggest that the Great Recession generated a large, persistent negative output gap rather than any substantial hysteresis effects, with the economy eventually recovering to a lower trend path that appears to be due to a reduction in productivity growth that began prior to the onset of the Great Recession.

Intuitive and Reliable Estimates of the Output Gap from a Beveridge-Nelson Filter

The Review of Economics and Statistics 2018 100(3), 550-566 open access
Abstract The Beveridge-Nelson decomposition based on autoregressive models produces estimates of the output gap that are strongly at odds with widely held beliefs about transitory movements in economic activity. This is due to parameter estimates implying a high signal-to-noise ratio in terms of the variance of trend shocks as a fraction of the overall forecast error variance. When we impose a lower signal-to-noise ratio, the resulting Beveridge-Nelson filter produces a more intuitive estimate of the output gap that is large in amplitude and highly persistent, and it typically increases in expansions and decreases in recessions. Notably, our approach is also reliable in the sense of being subject to smaller revisions and predicting future output growth and inflation better than other trend-cycle decompositions that impose a low signal-to-noise ratio.