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Predicting the Probability of a Recession with Nonlinear Autoregressive Leading Indicator Models

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  • Anderson, H.M.
  • Vahid, F.

Abstract

We develop nonlinear leading indicator models for GDP growth, with the interest rate spread and growth in M2 as leading indicators. Since policy makers are typically interested in whether or not a recession is imminent, we evaluate these models according to their ability to predict the probability of a recession. Using data for the United States, we find that conditional on the spread, the marginal contribution of M2 growth in predicting recessions is negligible.

Suggested Citation

  • Anderson, H.M. & Vahid, F., 2000. "Predicting the Probability of a Recession with Nonlinear Autoregressive Leading Indicator Models," Monash Econometrics and Business Statistics Working Papers 3/00, Monash University, Department of Econometrics and Business Statistics.
  • Handle: RePEc:msh:ebswps:2000-3
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    File URL: http://www.buseco.monash.edu.au/ebs/pubs/wpapers/2000/wp3-00.pdf
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    References listed on IDEAS

    as
    1. de Boer, P. M. C. & Harkema, R., 1986. "Maximum likelihood estimation of sum-constrained linear models with insufficient observations," Economics Letters, Elsevier, vol. 20(4), pages 325-329.
    2. Fry, Jane M. & Fry, Tim R. L. & McLaren, Keith R., 1996. "The stochastic specification of demand share equations: Restricting budget shares to the unit simplex," Journal of Econometrics, Elsevier, vol. 73(2), pages 377-385, August.
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    More about this item

    Keywords

    Event probabilities; Leading Indicators; Nonlinear Models;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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