In this paper, I apply univariate and vector autoregressive (VAR) models to forecast inflation in Vietnam. To … properties of inflation in Vietnam. Then, I compute the pseudo out-of-sample root mean square error (RMSE) as a measure of … forecasting models from among the different candidates. I find that VAR_m2 is the best monthly model to forecast inflation in …

-based algorithms. We assess the usefulness of these new models in an inflation forecasting exercise across all G7 economies. We find …

algorithms. We assess the usefulness of these new models in an inflation forecasting exercise across all G7 economies. We find …

This paper sheds light on the questions whether it is possible to generate an accurate forecast of the real price of … oil and how it can be improved using forecast combinations. For this reason, my work will investigate the out …

applications on nowcasting U.S. GDP growth, investment growth and GDP deflator inflation confirm this ranking. Moreover, in both …

applications on nowcasting U.S. GDP growth, investment growth and GDP deflator inflation confirm this ranking. Moreover, in both …

Inflation is defined as an increase in the general price level of goods and services within a period of time. For any … economic agent to formulate policy, it must taken into consideration inflation and the aim of this study is to use ARIMA model … to predict inflation in Ghana. In order to fulfill this objective, monthly inflation variable was used to build the …

while ARIMA model gives the most accurate forecast of twelve-month inflation in EU countries. The Holt-Winters (additive and … models give the most accurate forecast of inflation future values. In the countries of the Western Balkans the targeting …-of-sample forecast. The key finding of this paper is that NNAR models give the most accurate forecast for the Western Balkans countries …

economic emergencies. This paper aims to forecast the short to medium-term incidence of COVID-19 epidemic through the medium of …