Forecasting in long horizons using smoothed direct forecast. (8th February 2019)

• Record Type: Journal Article
• Authors: Baek, Yaein
• Is Part Of: Journal of forecasting. Volume 38:Number 4(2019)
• Page Start: 277
• Page End: 292
• Publication Date: 2019-02-08
• Subjects: forecasting -- forecast comparisons -- long horizon; Forecasting -- Periodicals; Forecasting -- Mathematical models -- Periodicals; 003.2
• DOI: 10.1002/for.2572
• Languages: English
• ISSNs: 0277-6693

Abstract

Abstract: This paper constructs a forecast method that obtains long‐horizon forecasts with improved performance through modification of the direct forecast approach. Direct forecasts are more robust to model misspecification compared to iterated forecasts, which makes them preferable in long horizons. However, direct forecast estimates tend to have jagged shapes across horizons. Our forecast method aims to "smooth out" erratic estimates across horizons while maintaining the robust aspect of direct forecasts through ridge regression, which is a restricted regression on the first differences of regression coefficients. The forecasts are compared to the conventional iterated and direct forecasts in two empirical applications: real oil prices and US macroeconomic series. In both applications, our method shows improvement over direct forecasts.