• Saurabh Ghosh Reserve Bank of India
  • Abhishek Ranjan Reserve Bank of India
Keywords: GDP, Nowcasting, Random forest, Neural network


The growth rate of real Gross Domestic Product (GDP), as measured by the National Statistical Office of India, is an important metric for monetary policy making. Because GDP is released with a significant lag, particularly for the emerging market economies, this article presents various methodologies for nowcasting and forecasting GDP, using both traditional time series and machine learning methods. Further, considering the
importance of forward-looking information, our nowcasting model incorporates financial market data and an economic uncertainty index, in addition to high-frequency traditional macroeconomic indicators. Our findings suggest an improvement in the performance of nowcasting using a hybrid of machine learning and conventional time series methods.


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How to Cite
Ghosh, S., & Ranjan, A. (2023). A MACHINE LEARNING APPROACH TO GDP NOWCASTING: AN EMERGING MARKET EXPERIENCE. Buletin Ekonomi Moneter Dan Perbankan, 26, 33-54. https://doi.org/10.59091/bemp.v26i0.2454