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FORECASTING WOMEN, INFANTS, AND CHILDREN CASELOADS: A COMPARISON OF VECTOR AUTOREGRESSION AND AUTOREGRESSIVE INTEGRATED MOVING AVERAGE APPROACHES
Author(s) -
LAZARIU VICTORIA,
YU CHENGXUAN,
GUNDERSEN CRAIG
Publication year - 2011
Publication title -
contemporary economic policy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.454
H-Index - 49
eISSN - 1465-7287
pISSN - 1074-3529
DOI - 10.1111/j.1465-7287.2010.00203.x
Subject(s) - autoregressive integrated moving average , autoregressive model , vector autoregression , econometrics , economics , moving average , time series , statistics , mathematics
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)