On Forecasting Economic Time Series Data: A Comparative Study

Kuldeep Kumar, Dilbagh S. Gill

Research output: Contribution to journalArticleResearchpeer-review


Since the appearance of the book by Box and Jenkins in 1970, the use of autoregressive integrated moving average model has become widespread in analysing and forecasting economic time series data. Sims (1980) proposed a vector auto regressive model (V AR) approach as an alternative to the conventional strategy for constructing macro-economic model. Trevor and Thorp (1988) emphasised that estimating a V ARmodel using non-stationary data may result in unstable econometric relationships and suggested using Bayesian VAR model to accommodate non-stationarity. ill this paper we have compared the forecasting performance of these models using Australian macro-economic time series data.
Original languageEnglish
Pages (from-to)265-272
Number of pages8
JournalJournal of Information and Optimization Sciences
Issue number2
Publication statusPublished - 1998


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