Forecasting macroeconomic variables in emerging economies

Le Ha Thu and Roberto Leon-Gonzalez

Journal of Asian Economics, 2021, vol. 77, issue C

Abstract: Forecasting macroeconomic variables in rapidly changing emerging economies presents a number of challenges. In addition to structural changes, the time-series data are usually available only for a short number of periods, and predictors are available in different lengths and frequencies. Dynamic model averaging (DMA), by allowing the forecasting model to change dynamically over time, permits the use of predictors with different lengths and frequencies for the purpose of forecasting in a rapidly changing economy. This study uses DMA to forecast inflation and growth in Vietnam, Thailand, Philippines, Sri Lanka and Ghana. We compare its forecasting performance with a wide range of other time-series methods. We find that the size and composition of the optimal predictor set changed, indicating changes in the economic relationships over time. We also find that DMA frequently produces more accurate forecasts than other forecasting methods for both inflation and economic growth in the countries studied.

Keywords: Bayesian; Dynamic model averaging; Forecasting macroeconomic variables; Vietnam (search for similar items in EconPapers)
JEL-codes: C11 C53 E31 E37 O40 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:asieco:v:77:y:2021:i:c:s1049007821001329

DOI: 10.1016/j.asieco.2021.101403

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