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Predicting Medium-Term TFP Growth in the United States: Econometrics vs ‘Techno-Optimism’

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  • Crafts, Nicholas
  • Mills, Terence C.

Abstract

We analyse TFP growth in the US business sector using a basic unobserved component model where trend growth follows a random walk and the noise is a first order autoregression. This is fitted using a Kalman-filter methodology. We find that trend TFP growth has declined steadily from 1.5 to 1.0 per cent per year over the past 50 years. Nevertheless, recent trends are not a good guide to actual medium-term TFP growth. This exhibits substantial variations and is quite unpredictable. Techno-optimists should not give best to productivity pessimists simply because recent TFP growth has been weak.

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  • Crafts, Nicholas & Mills, Terence C., 2017. "Predicting Medium-Term TFP Growth in the United States: Econometrics vs ‘Techno-Optimism’," National Institute Economic Review, National Institute of Economic and Social Research, vol. 242, pages 60-67, November.
    • Handle: RePEc:cup:nierev:v:242:y:2017:i::p:r60-r67_15
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    Cited by:

    1. Yingying Lu & Yixiao Zhou, 2021. "A review on the economics of artificial intelligence," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 1045-1072, September.

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