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Labor productivity forecasts based on a Beveridge–Nelson filter: Is there statistical evidence for a slowdown?
Institution:1. School of Business, Macau University of Science and Technology, Avenida Wai Long Taipa, Macau, China;2. School of Economics, Singapore Management University, 90 Stamford Road, Singapore 178903, Singapore
Abstract:In this paper, I assess the evidence for a structural break in labor productivity growth in the years before the Great Recession with the use of out-of-sample forecasting exercises for the years 2010 to 2019 and the recently developed Beveridge–Nelson filter. Models based on a Beveridge–Nelson filter with no structural breaks outperform those allowing for a structural break, and there is statistically significant evidence that they outperform the random walk, though all models were too optimistic about labor productivity growth. Recently developed statistical tests do point to the presence of a structural break before the Great Recession, but uncertainty about the data-generating process for labor productivity growth or the timing and magnitude of the break may be too great to be helpful in forecast preparation.
Keywords:Out-of-sample forecasts  Beveridge–Nelson filter  Labor productivity  Random walk
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