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Macroeconomic forecasting with mixed data sampling frequencies: Evidence from a small open economy

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  • Albert K. Tsui
  • Cheng Yang Xu
  • Zhaoyong Zhang

Abstract

The aim of this study was to forecast the Singapore gross domestic product (GDP) growth rate by employing the mixed‐data sampling (MIDAS) approach using mixed and high‐frequency financial market data from Singapore, and to examine whether the high‐frequency financial variables could better predict the macroeconomic variables. We adopt different time‐aggregating methods to handle the high‐frequency data in order to match the sampling rate of lower‐frequency data in our regression models. Our results showed that MIDAS regression using high‐frequency stock return data produced a better forecast of GDP growth rate than the other models, and the best forecasting performance was achieved by using weekly stock returns. The forecasting result was further improved by performing intra‐period forecasting.

Suggested Citation

  • Albert K. Tsui & Cheng Yang Xu & Zhaoyong Zhang, 2018. "Macroeconomic forecasting with mixed data sampling frequencies: Evidence from a small open economy," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(6), pages 666-675, September.
    • Handle: RePEc:wly:jforec:v:37:y:2018:i:6:p:666-675
    DOI: 10.1002/for.2528
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    Cited by:

    1. Hwee Kwan Chow & Yijie Fei & Daniel Han, 2023. "Forecasting GDP with many predictors in a small open economy: forecast or information pooling?," Empirical Economics, Springer, vol. 65(2), pages 805-829, August.
    2. Rong Fu & Luze Xie & Tao Liu & Juan Huang & Binbin Zheng, 2022. "Chinese Economic Growth Projections Based on Mixed Data of Carbon Emissions under the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(24), pages 1-16, December.
    3. Andrianady, Josué R. & Rajaonarison, Njakanasandratra R. & Razanajatovo, Yves H., 2023. "Estimating Madagascar economic growth using the Mixed Data Sampling (MIDAS) approach," MPRA Paper 118267, University Library of Munich, Germany.
    4. Joseph Zhi Bin Ling & Albert K. Tsui & Zhaoyong Zhang, 2021. "Trading Macro-Cycles of Foreign Exchange Markets Using Hybrid Models," Sustainability, MDPI, vol. 13(17), pages 1-20, September.
    5. Mahmut Gunay, 2020. "Nowcasting Turkish GDP with MIDAS: Role of Functional Form of the Lag Polynomial," Working Papers 2002, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.

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