Inflation Forecasting
RBI paper says combining models leads to more accurate inflation forecasting
This story was originally published at 20:01 IST on 25 June 2025
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NEW DELHI – Using a combination of statistical, machine learning, and deep learning methods helps to improve accuracy in inflation forecasting, a Reserve Bank of India staff paper released Wednesday said.
The study tried to develop a methodology for forecasting headline CPI inflation and CPI excluding food and fuel inflation for India using various statistical, machine learning, and deep learning models. These models were also combined using a performance-weighted forecasts combination approach.
The results showed that performance-weighted forecasts for headline and core inflation were on a par with or better than simple average forecasts for all model classes and across horizons, as per the paper. "The results indicate a clear advantage in using all model classes together, with a guarantee that the forecast accuracy never deteriorates while combining forecasts from all classes of models and getting better in most cases," according to the paper authored by Renjith Mohan, Saquib Hasan, Sayoni Roy, Suvendu Sarkar, and Joice John.
While traditional models of inflation forecasting are useful for their stability and interpretability, machine learning and deep learning models offer more accurate forecasts. "However, its inability to provide a coherent interpretation remains a concern," the authors of the paper said. A combination of models to forecast inflation provides confidence bands, enabling policymakers to assess risks and make more informed decisions, they said. End
Reported by Shubham Rana
Edited by Rajeev Pai
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