A MACHINE LEARNING APPROACH TO GDP NOWCASTING: AN EMERGING MARKET EXPERIENCE
Abstract
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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References
Aastveit, K., & Trovik, T. (2012). Nowcasting Norwegian GDP: The Role of Asset Prices in a Small Open Economy. Empirical Economics, 42, 95–119.
Angelini, E., Camba-Mendez, G., Giannone, D., Reichlin, L., & Rünstler, G. (2011). Short-term Forecasts of Euro Area GDP Growth. The Econometrics Journal, 14, C25–C44.
Baffigi, A., Golinelli, R., & Parigi, G. (2004). Bridge Models to Forecast the Euro Area GDP. International Journal of Forecasting, 20, 447-460.
Baker, S. R., Bloom, N., & Davis, S. J. (2015). Measuring Economic Policy Uncertainty. Working Paper 21633, National Bureau of Economic Research, October 2015.
Banbura, M., Giannone, D., Modugnoand, M., & Reichlin, L. (2013). Nowcasting and the Real-time Data Flow. Handbook of Economic Forecasting, 2A, 195–237.
Banbura, M., Giannone, D., & Reichlin, L. (2010). Nowcasting. European Central Bank Working Paper No. 1275.
Barhoumi, K., Darné, O., Ferrara, L., and Pluyaud, B., (2011). Monthly GDP Forecasting Using Bridge Models: Comparison from the Supply and Demand Sides for the French Economy. Bulletin of Economic Research, 64, 53–70.
Barnett, W. A., Chauvet, M., & Leiva-Leon D. (2016). Real-time Nowcasting of Nominal GDP with Structural Breaks. Journal of Econometrics, 19, 312-324.
Bhadury, S., Ghosh, S., & Kumar, P. (2021). Constructing a Coincident Economic Indicator for India: How Well does It Track Gross Domestic Product? Asian Development Review, 38, 237–277.
Bhattacharya, R., Pandey, R., & Veronese, G. (2011) Tracking India Growth in Real Time. Working Papers 11/90, National Institute of Public Finance and Policy, July 2011.
Bragoli, D., & Fosten, J. (2018). Nowcasting Indian GDP. Oxford Bulletin of Economics and Statistics, 80, 259-282.
Bragoli, D., Metelli, L., & Modugno, M. (2014). The Importance of Updating: Evidence from a Brazilian Nowcasting Model. ERN: Other Econometrics: Applied Econometric Modeling in Forecasting (Topic).
Cepni, O., Guney, I. E., & Swanson, N. R. (2019). Nowcasting and Forecasting GDP in Emerging Markets Using Global Financial and Macroeconomic Diffusion Indexes. International Journal of Forecasting, 35, 555–572.
D’Agostino, A., Gambetti, L., & Giannone, D. (2013). Macroeconomic Forecasting and Structural Change. Journal of Applied Econometrics, 28, 82–101.
Dahlhaus, T., Guénette, J., & Vasishtha, G. (2015). Nowcasting BRIC+M in Real Time. Staff Working Papers 15-38, Bank of Canada.
Fama, E. F., & French, K. R. (1987). Commodity Futures Prices: Some Evidence on Forecast Power Premiums and the Theory of Storage. Journal of Business, 60, 55–73.
Gardner Jr, E. S. (1985). Exponential Smoothing: The State of the Art. Journal of Forecasting, 4, 1–28.
Giannone, D., Miranda, S., Modugno, M., & Reichlin, L. (2014). Nowcasting China. Mimeo.
Giannone, D., Reichlin, L., & Small, D. (2008). Nowcasting: The Real-time Informational Content of Macroeconomic Data. Journal of Monetary Economics, 55, 665–676.
Harvey, A., & Peters, S. (1990). Estimation Procedures for Structural Time Series Models. Journal of Forecasting, 9, 89–108.
Hastie, T., & Tibshirani, R. (1987). Generalized Additive Models: Some Applications. Journal of the American Statistical Association, 82, 371–386.
Hyndman, R. J., & Khandakar, Y. (2008). Automatic Time Series Forecasting: The Forecast Package for R. Journal of Statistical Software, 27, 1–22.
Iyer, T., & Sen Gupta, A. (2019). Nowcasting Economic Growth in India: The Role of Rainfall. Asian Development Bank Economics Working Paper, October: 593.
Lahiri, K., & Monokroussos, G. (2011). Nowcasting US GDP: The Role of ISM Business Surveys. SUNY at Albany Discussion Papers 11-01.
Luciani, M., Pundit, M., Ramayandi, A., & Veronese, G. (2015). Nowcasting Indonesia. Asian Development Bank Economics Working Paper, December: 471.
Marcellino, M., & Schumacher, C. (2010). Factor MIDAS for Nowcasting and Forecasting with Ragged-edge Data: A Model Comparison for German GDP. Oxford Bulletin of Economics and Statistics, 72, 518–550.
Matheson, T. (2010). An Analysis of the Informational Content of New Zealand Data Releases: The Importance of Business Opinion Surveys. Economic Modelling, 27, 304–314.
Richardson, A., Mulder, T. V. F., & Vehbi, T. (2021). Nowcasting GDP Using Machine Learning Algorithms: A real time assessment. International Journal of Forecasting, 37, 941-948.
Stock, J., & Watson, M. (1989). New Indexes of Coincident and Leading Economic Indicators. Macroeconomics Annual, National Bureau of Economic Research, 4, 351–409.
Tang, B., Yemba, B., & Chang, D. (2020). Divisia Monetary Aggregates and US GDP Nowcasting. Applied Economics, 52, 3538-3554.
Taylor, S. J., & Letham, B. (2017). Forecasting at Scale. PeerJ Preprints 5 3190v2.
Zhemkov, M. (2021). Nowcasting Russian GDP Using Forecast Combination Approach. International Economics, 168, 10–24.
Zuur, A. F., Fryer, R. J., Jolliffe, I. T., Dekker, R., & Beukema, J. J. (2003). Estimating Common Trends in Multivariate Time Series Using Dynamic Factor Analysis. Environmetrics, 14, 665–685.
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