Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-11-25T11:25:00.807Z Has data issue: false hasContentIssue false
  • English
  • Français

Forecasting Item Movement with Scan Data: Box-Jenkins Results

Published online by Cambridge University Press:  10 May 2017

David B. Eastwood ,
Morgan D. Gray  and
John R. Brooker
David B. Eastwood
Affiliation:
Department of Agricultural Economics and Rural Sociology, Agricultural Experiment Station, The University of Tennessee, Knoxville, TN
Morgan D. Gray
Affiliation:
Department of Agricultural Economics and Rural Sociology, Agricultural Experiment Station, The University of Tennessee, Knoxville, TN
John R. Brooker
Affiliation:
Department of Agricultural Economics and Rural Sociology, Agricultural Experiment Station, The University of Tennessee, Knoxville, TN
Get access

Abstract

Preliminary forecasts using the Box-Jenkins methodology for supermarket scan data for ground beef and roast item movement are described. The functional form and the accuracy of the forecasts vary by product. Results suggest that further analyses incorporating price and advertising may increase the accuracy of the forecasts.

Type
Articles
Information
Northeastern Journal of Agricultural and Resource Economics , Volume 20 , Issue 1 , April 1991 , pp. 42 - 51
Copyright
Copyright © 1991 Northeastern Agricultural and Resource Economics Association 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

The authors wish to thank Dr. Daniel L. McLemore for his helpful comments on the research. However, responsibility for the paper rests with the authors.

References

Capps, O. Jr., “The Ultimate Source for Demand Analysis?” Working Paper. Texas A&M University, 1987.Google Scholar
Capps, O. Jr., “Utilizing Scanner Data to Estimate Retail Demand Functions for Meat Products.” American Journal of Agricultural Economics 71 (1989):750–60.Google Scholar
Capps, O. Jr., and Nayga, R. M. “Demand for Fresh Beef Products in Supermarkets: A Trial with Scanner Data.” Paper presented at the Southern Agricultural Economics Association Annual Meeting, 5 February 1990. Forecasting Item Movement with Scan Data 51Google Scholar
Eastwood, D. B. “Organizing Scan Data for Market Research.” Journal of Food Distribution Research June 1990:45–52.Google Scholar
Eastwood, D. B., Gray, M. D., and Brooker, J. R. “State-oriented Shelf Labels: A Preliminary Analysis of Their Effects on Food Purchases.” Proceedings of the 36th Annual Conference of the American Council on Consumer Interests, edited by Carsky, M. 36 (1990):293–98.Google Scholar
Granger, C. S. J., and Newbold, P. Forecasting Economic Time Series. New York: Academic Press, 1986.Google Scholar
Jensen, H. H., and Schroeter, J. R. “Estimating Retail Beef Demand Using Household Scanner Data.” Paper presented at the AAEA Annual Meetings, 1989.Google Scholar
Nazem, S. M. Applied Time Series Analysis for Business and Economic Forecasting. New York: Marcel Dekker, Inc., 1988.Google Scholar
McLaughlin, E., and Lesser, W. “Experimental Price Variability and Consumer Response: Tracking Potato Sales with Scanners.” Working Paper. Cornell University, 1986.Google Scholar
Supermarket Business. Selected Issues.Google Scholar
Theil, H. Applied Economic Forecasting. New York: North-Holland, 1971.Google Scholar