On Forecasting Economic Time Series: A Comparative Study

Kuldeep Kumar, Dilbagh Gill

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Since the appearance of the book by Box and Jenkins in 1970, the use of auto regressive integrated moving average model has become widespread in analyzing and forecasting economic time series data. Sims (1980) proposed a vector auto regressive model (VAR) model approach as an alternative to the conventional strategy for constructing macro- economic model. Trevor and Thorp (1988) emphasized that estimating a V AR model using non-stationary data may result in unstable econometric relationships and suggested using Bayesian V AR model to accommodate non- stationarity. In this paper we have compared the forecasting performance of these models using Australian macro- economic time series data.
Original languageEnglish
Pages (from-to)143-150
Number of pages8
JournalIndian Journal of Economics
Volume81
Issue number321
Publication statusPublished - Oct 2000

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Economic forecasting
Comparative study
Time series data
Integrated
Macroeconomic models
Vector autoregressive model
Macroeconomics
Nonstationarity
Forecasting performance
Econometric relationships
Moving average

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Kumar, Kuldeep ; Gill, Dilbagh. / On Forecasting Economic Time Series: A Comparative Study. In: Indian Journal of Economics. 2000 ; Vol. 81, No. 321. pp. 143-150.
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On Forecasting Economic Time Series: A Comparative Study. / Kumar, Kuldeep; Gill, Dilbagh.

In: Indian Journal of Economics, Vol. 81, No. 321, 10.2000, p. 143-150.

Research output: Contribution to journalArticleResearchpeer-review

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