FORECASTING WOMEN, INFANTS, AND CHILDREN CASELOADS: A COMPARISON OF VECTOR AUTOREGRESSION AND AUTOREGRESSIVE INTEGRATED MOVING AVERAGE APPROACHES

Authors

  • VICTORIA LAZARIU,

    1. Lazariu: Research Scientist, New York State Department of Health, Albany, NY 12204. Phone 1-518-402-7109, Fax 1-518-408-0254, E-mail vgl01@health.state.ny.us
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  • CHENGXUAN YU,

    1. Yu: Research Scientist, New York State Department of Health, Albany, NY 12204. Phone 1-518-402-7109, Fax 1-518-408-0254, E-mail yxc04@health.state.ny.us
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  • CRAIG GUNDERSEN

    1. Gundersen: Associate Professor, Department of Agricultural and Consumer Economics, University of Illinois, Urbana, IL, 61801-3671. Phone 1-217-333-2857, Fax 1-217-333-5538, E-mail cggunder@illinois.edu
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    • Previous versions of this paper were presented at the 2005 Student Poster Day of School of Public Health, University at Albany; the USDA Northeastern Regional Office meeting; the New York State Department of Health SPEED Rounds; and the Albany Chapter meeting of the American Statistical Association. The authors wish to thank participants at those venues for their comments and Mary Lou Woelfel for her comments. Craig Gundersen gratefully acknowledges financial support for this project from the New York State Department of Health.


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 H7, C5)

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