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Bayesian Variable Selection for Nowcasting Economic Time Series

In: Economic Analysis of the Digital Economy

Author

Listed:
  • Steven L. Scott
  • Hal R. Varian
Abstract
We consider the problem of short-term time series forecasting (nowcasting) when there are more possible predictors than observations. Our approach combines three Bayesian techniques: Kalman filtering, spike-and-slab regression, and model averaging. We illustrate this approach using search engine query data as predictors for consumer sentiment and gun sales.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Steven L. Scott & Hal R. Varian, 2015. "Bayesian Variable Selection for Nowcasting Economic Time Series," NBER Chapters, in: Economic Analysis of the Digital Economy, pages 119-135, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberch:12995
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    References listed on IDEAS

    as
    1. Yan Carrière‐Swallow & Felipe Labbé, 2013. "Nowcasting with Google Trends in an Emerging Market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(4), pages 289-298, July.
    2. Concha Artola & Enrique Galán, 2012. "Tracking the future on the web: construction of leading indicators using internet searches," Occasional Papers 1203, Banco de España.
    3. Jennifer L. Castle & Xiaochuan Qin & W. Robert Reed, 2009. "How To Pick The Best Regression Equation: A Review And Comparison Of Model Selection Algorithms," Working Papers in Economics 09/13, University of Canterbury, Department of Economics and Finance.
    4. Castle Jennifer L. & Doornik Jurgen A & Hendry David F., 2011. "Evaluating Automatic Model Selection," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-33, February.
    5. David C. Wyld, 2010. "ASecond Lifefor organizations?: managing in the new, virtual world," Management Research Review, Emerald Group Publishing Limited, vol. 33(6), pages 529-562, May.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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