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Food Stamp Certification Periods and Payment Accuracy: State Experience During 1997-2001

  • by Gregory Mills, Don Laliberty, Christopher Rodger and J. William Levedahl
  • 11/12/2004
  • EFAN-04012

Overview

Quality control (QC) reviews of Food Stamp Program (FSP) cases show that error rates across States range from less than 5 percent to more than 25 percent when both overpayment and underpayment error are combined. This study uses QC data for 1997-2001 and a Markov probability framework to characterize year-to-year national and State error rates into variations due to errors occurring with first-month cases (those approved at initial certification); ongoing cases (those subject to the interim action process); and expiring cases (those subject to the recertification process). This information can be used in planning corrective actions by focusing attention on phases of the administrative process that are more responsible for errors. This study also explores the effect on payment accuracy and FSP participation of more frequent recertification of food stamp cases. A motivating concern is that the use of short certification periods (3 months or less) as a strategy to reduce case error may unintentionally reduce program participation.

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  • Entire report

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  • Abstract, Acknowledgments, Contents, Executive Summary

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  • Chapter One: Background and Objectives

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  • Chapter Two: Modeling Program Participation and Error

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  • Chapter Three: Deriving the Transition Matrix

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  • Chapter Four: National Trends in Program Participation and Error Rates

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  • Chapter Five: State-by-State Error Patterns

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  • Chapter Six: Effects of More Frequent Recertification

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  • Bibliography

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  • Appendix A: Distribution of Food Stamp Households by Length of Certification Period

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  • Appendix B: Procedures For Deriving The Transition Matrix

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  • Appendix C: National Estimates of Cell Counts and Transition Probabilities

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  • Appendix D: State-by-State Estimates of Cell Counts and Transition Probabilities

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  • Appendix E: Discrete Time Markov Chains

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