Skip to main content

Arima Models

  • Reference work entry
  • First Online:
Book cover The New Palgrave Dictionary of Economics
  • 69 Accesses

Abstract

Autoregressive integrated moving-average (ARIMA) models are models which can be fitted to a single time series and used to make predictions of future observations. They owe their popularity primarily to the work of Box and Jenkins (1970), who defined the class of ARIMA and seasonal ARIMA models and provided a methodology for selecting a suitable model from that class.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 6,499.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 8,499.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Box, G.E.P., and G.M. Jenkins. 1970. Time series analysis: Forecasting and control. San Francisco: Holden-Day.

    Google Scholar 

  • Engle, R.F. 1978. Estimating structural models of seasonality. In Seasonal analysis of economic time series, ed. A. Zellner, 281–308. Washington, DC: Bureau of the Census.

    Google Scholar 

  • Harrison, P.J. 1967. Exponential smoothing and short-term sales forecasting. Management Science 13: 821–842.

    Article  Google Scholar 

  • Harvey, A.C. 1985. Trends and cycles in macroeconomic time series. Journal of Business and Economic Statistics 3: 216–227.

    Google Scholar 

  • Harvey, A.C., and P.H.J. Todd. 1983. Forecasting economic time series with structural and Box–Jenkins models: A case study (with discussion). Journal of Business and Economic Statistics 1: 229–315.

    Google Scholar 

  • Jenkins, G.M. 1982. Some practical aspects of forecasting in organisations. Journal of Forecasting 1: 3–21.

    Article  Google Scholar 

  • Kitagawa, G. 1981. A nonstationary time series model and its fitting by a recursive filter. Journal of Time Series Analysis 2: 103–116.

    Article  Google Scholar 

  • Muth, J.F. 1960. Optimal properties of exponentially weighted forecasts. Journal of the American Statistical Association 55: 299–306.

    Article  Google Scholar 

  • Nerlove, M., and S. Wage. 1964. On the optimality of adaptive forecasting. Management Science 10: 207–224.

    Article  Google Scholar 

  • Theil, H., and S. Wage. 1964. Some observations on adaptive forecasting. Management Science 10: 198–206.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Copyright information

© 2018 Macmillan Publishers Ltd.

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Harvey, A.C. (2018). Arima Models. In: The New Palgrave Dictionary of Economics. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-349-95189-5_533

Download citation

Publish with us

Policies and ethics