@techreport{oai:grips.repo.nii.ac.jp:00001824,
 author = {LE, Ha Thu and LEON-GONZALEZ, Roberto},
 note = {http://www.grips.ac.jp/list/jp/facultyinfo/leon_gonzalez_roberto/, Forecasting macroeconomic variables in the rapidly changing macroeconomic environments faced by developing and emerging countries is an important task for central banks and policy-makers, yet often presents a number of challenges. In addition to the structural changes in the economy, the time-series data are usually available only for a small 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, and compares its forecasting performance with a wide range of other time-series methods. Some results are noteworthy. First, the number and composition of the optimal predictor set changed, indicating changes in the economic relationships over time. Second, DMA frequently produces more accurate forecasts than other forecasting methods for both the inflation and the economic growth rate of Vietnam., JEL Classification Codes: E31, E37, O40, C11, C53},
 title = {Forecasting Macroeconomic Variables in Emerging Economies: An Application to Vietnam}
}