Forecasting women, infants, and children caseloads: A comparison of vector autoregression and autoregressive integrated moving average approaches

Victoria Lazariu, Chengxuan Yu, Craig Gundersen

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Pages (from-to)46-55
Number of pages10
JournalContemporary Economic Policy
Volume29
Issue number1
DOIs
StatePublished - Jan 1 2011

ASJC Scopus subject areas

  • Business, Management and Accounting(all)
  • Economics and Econometrics
  • Public Administration

Fingerprint Dive into the research topics of 'Forecasting women, infants, and children caseloads: A comparison of vector autoregression and autoregressive integrated moving average approaches'. Together they form a unique fingerprint.

  • Cite this