Deficit/ Surplus, Unemployment Rate, Inflation and others. We forecast the macroeconomic variables post 2012 using ARIMA … deficit. ARIMA models indicate that with the continuance of present government’s policies, budgetary deficit is estimated to …

average (ARIMA), and multivariate models, i.e., vector autoregressive (VAR), vector error correction model (VECM), and state … likelihood estimation (MLE) for (ARIMA) models, and by seemingly unrelated regression for (VAR) and (VECM) models, during the …

statistical methods, i.e., simple regressions, Autoregressive Integrated Moving Average forecasting models (ARIMA), and linear and …

criteria, and then forecast. I compare the out-of-sample performance of a large number of autoregressive integrated moving … average (ARIMA) models with some variations, chosen by three commonly used information criteria for model building: Akaike …, Schwarz, and Hannan-Quinn. I perform this exercise to identify how to achieve the smallest root mean squared forecast error …

-average (ARIMA) models for time series data was used. A time series was a set of observations ordered according to the time that were …

factors such as GDP, exchange rate, inflation, capital markets and fiscal deficit. We forecast some of the major economic … variables using ARIMA modeling and present a picture of the Indian economy in the coming years. The findings indicate that …

models (Exponential Smoothing, ARIMA and GARCH) based on multi-step ahead forecast mean squared errors. We investigate … whether combining forecasts from different methods and from different origins and horizons could improve forecast accuracy. We …

average (ARIMA) time series models for forecasting Pakistan’s inflation. A framework for ARIMA forecasting is drawn up. On the … basis of insample and out-of-sample forecast it can be concluded that the model has sufficient predictive powers and the … findings are well in line with those of other studies. Further, in this study, the main focus is to forecast the monthly …

, the random walk produces wider prediction intervals. This picture changes when we forecast ARIMA (0,2,1) values for θ …In this paper we show that the random walk model with drift behaves like an ARIMA (0,2,1) when its parameter θ is … greater but close to –1. Using the random walk for predicting future values of an ARIMA (0,2,1) process, we find out that when …