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Bayesian Forecasting of US Growth using Basic Time Varying Parameter Models and Expectations Data

Author

Listed:
  • Nalan Basturk

    (Maastricht University, the Netherlands)

  • Pinar Ceyhan

    (Erasmus University Rotterdam)

  • Herman K. van Dijk

    (Erasmus University Rotterdam, VU University Amsterdam, the Netherlands)

Abstract

Time varying patterns in US growth are analyzed using various univariate model structures, starting from a naive model structure where all features change every period to a model where the slow variation in the conditional mean and changes in the conditional variance are specified together with their interaction, including survey data on expected growth in order to strengthen the information in the model. Use is made of a simulation based Bayesian inferential method to determine the forecasting performance of the various model specifications. The extension of a basic growth model with a constant mean to models including time variation in the mean and variance requires careful investigation of possible identification issues of the parameters and existence conditions of the posterior under a diffuse prior. The use of diffuse priors leads to a focus on the likelihood fu nction and it enables a researcher and policy adviser to evaluate the scientific information contained in model and data. Empirical results indicate that incorporating time variation in mean growth rates as well as in volatility are important in order to improve for the predictive performances of growth models. Furthermore, using data information on growth expectations is important for forecasting growth in specific periods, such as the the recession periods around 2000s and around 2008.

Suggested Citation

  • Nalan Basturk & Pinar Ceyhan & Herman K. van Dijk, 2014. "Bayesian Forecasting of US Growth using Basic Time Varying Parameter Models and Expectations Data," Tinbergen Institute Discussion Papers 14-119/III, Tinbergen Institute, revised 14 Sep 2014.
  • Handle: RePEc:tin:wpaper:20140119
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    File URL: https://papers.tinbergen.nl/14119.pdf
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Growth; Time varying parameters; Expectations data;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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