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A nowcasting model of industrial production using alternative data and machine learning approaches

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  • Furukawa, Kakuho
  • Hisano, Ryohei
  • Minoura, Yukio
  • Yagi, Tomoyuki

Abstract

Recent years have seen a growing trend to utilize "alternative data" in addition to traditional statistical data in order to understand and assess economic conditions in real time. In this paper, we construct a nowcasting model for the Indices of Industrial Production (IIP), which measure production activity in the manufacturing sector in Japan. The model has the following characteristics: First, it uses alternative data (mobility data and electricity demand data) that is available in real-time and can nowcast the IIP one to two months before their official release. Second, the model employs machine learning techniques to improve the nowcasting accuracy by endogenously changing the mixing ratio of nowcast values based on traditional economic statistics (the Indices of Industrial Production Forecast) and nowcast values based on alternative data, depending on the economic situation. The estimation results show that by applying machine learning techniques to alternative data, production activity can be nowcasted with high accuracy, including when it went through large fluctuations during the spread of the COVID-19 pandemic.

Suggested Citation

  • Furukawa, Kakuho & Hisano, Ryohei & Minoura, Yukio & Yagi, Tomoyuki, 2024. "A nowcasting model of industrial production using alternative data and machine learning approaches," Japan and the World Economy, Elsevier, vol. 71(C).
  • Handle: RePEc:eee:japwor:v:71:y:2024:i:c:s0922142524000343
    DOI: 10.1016/j.japwor.2024.101271
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    References listed on IDEAS

    as
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    8. Matsumura, Kohei & Oh, Yusuke & Sugo, Tomohiro & Takahashi, Koji, 2024. "Nowcasting economic activity with mobility data," Journal of the Japanese and International Economies, Elsevier, vol. 73(C).
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Industrial production; Mobility data; Electricity data; Nowcasting; Machine learning; COVID-19;
    All these keywords.

    JEL classification:

    • C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

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