Purchase - $38.00

Forecasting Women, Infants, and Children Caseloads: A Comparison of Vector Autoregression and Autoregressive Integrated Moving Average Approaches

10 Pages Posted: 12 Jan 2011  

Victoria Lazariu

affiliation not provided to SSRN

Chengxuan Yu

affiliation not provided to SSRN

Craig Gundersen

U.S. Department of Agriculture (USDA); Iowa State University

Date Written: January 10, 2011

Abstract

Under the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), each state receives a fixed federal grant for the operation of WIC in the upcoming federal fiscal year. Accurate forecasting is vital because states have to bear the expenses of any underestimation of WIC expenditures. Using monthly data from 1997 through 2005, this paper examined the performance of two competing models, autoregressive integrated moving average (ARIMA) and vector autoregression (VAR), in forecasting New York WIC caseloads for women, infants, and children. VAR model predicted over $120,000 less per month in forecast errors in comparison to the ARIMA model.

JEL Classification: H7, C5

Suggested Citation

Lazariu, Victoria and Yu, Chengxuan and Gundersen, Craig, Forecasting Women, Infants, and Children Caseloads: A Comparison of Vector Autoregression and Autoregressive Integrated Moving Average Approaches (January 10, 2011). Contemporary Economic Policy, Vol. 29, No. 1, pp. 46-55, 2011. Available at SSRN: https://ssrn.com/abstract=1738112 or http://dx.doi.org/10.1111/j.1465-7287.2010.00203.x

Victoria Lazariu (Contact Author)

affiliation not provided to SSRN ( email )

Chengxuan Yu

affiliation not provided to SSRN ( email )

Craig Gundersen

U.S. Department of Agriculture (USDA) ( email )

1301 New York Ave. NW
Washington, DC 20250
United States

Iowa State University ( email )

Ames, IA 50011
United States

Paper statistics

Downloads
1
Abstract Views
248