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Labor productivity forecasts based on a Beveridge–Nelson filter: Is there statistical evidence for a slowdown?

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  • Biolsi, Christopher

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.

Suggested Citation

  • Biolsi, Christopher, 2021. "Labor productivity forecasts based on a Beveridge–Nelson filter: Is there statistical evidence for a slowdown?," Journal of Macroeconomics, Elsevier, vol. 69(C).
    • Handle: RePEc:eee:jmacro:v:69:y:2021:i:c:s0164070421000276
    DOI: 10.1016/j.jmacro.2021.103321
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    More about this item

    Keywords

    Out-of-sample forecasts; Beveridge–Nelson filter; Labor productivity; Random walk;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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