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Real-Time Forecast of DSGE Models with Time-Varying Volatility in GARCH Form

Author

Listed:
  • Sergey Ivashchenko

    (The North-Western Main Branch of the Bank of Russia; The Institute of Regional Economy Studies (Russian Academy of Sciences); The Financial Research Institute)

  • Semih Emre Cekin

    (Department of Economics, Turkish-German University, Istanbul, Turkey)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

  • Chien-Chiang Lee

    (School of Economics and Management, Nanchang University, Nanchang, China)

Abstract

Recent research shows that time-varying volatility plays a crucial role in nonlinear modeling. Contributing to this literature, we suggest a DSGE-GARCH approach that allows for straight-forward computation of DSGE models with time-varying volatility. As an application of our approach, we examine the forecasting performance of the DSGE-GARCH model using Eurozone real-time data. Our findings suggest that the DSGE-GARCH approach is superior in out-of-sample forecasting performance in comparison to various other benchmarks for the forecast of inflation rates, output growth and interest rates, especially in the short term. Comparing our approach to the widely used stochastic volatility specification using in-sample forecasts, we also show that the DSGE-GARCH is superior in in-sample forecast quality and computational effciency. In addition to these results, our approach reveals interesting properties and dynamics of time-varying correlations (conditional correlations).

Suggested Citation

  • Sergey Ivashchenko & Semih Emre Cekin & Rangan Gupta & Chien-Chiang Lee, 2022. "Real-Time Forecast of DSGE Models with Time-Varying Volatility in GARCH Form," Working Papers 202204, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202204
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    DSGE; forecasting; GARCH; stochastic volatility; conditional correlations;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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