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Compliance Checks The Probable Implications of Probability William DeJong, PhD Boston University School of Public Health Youth Alcohol Prevention Center.

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Presentation on theme: "Compliance Checks The Probable Implications of Probability William DeJong, PhD Boston University School of Public Health Youth Alcohol Prevention Center."— Presentation transcript:

1 Compliance Checks The Probable Implications of Probability William DeJong, PhD Boston University School of Public Health Youth Alcohol Prevention Center Responsible Retailing Forum Responsible Retailing Research April 19, 2006

2 Key Points ! Frequent non-compliance is a fact of life, even for retailers with relatively high rates of clerk compliance with the law! ? Given that, what is a reasonable standard of performance to which retailers can be held?

3 Probability for Event Sequences The probability that a sequence of events will occur is equal to the product of their individual probabilities Example: What is the probability of tossing a coin and getting “tails” twice? –0.50 x 0.50 = 0.25 OR 1/2 x 1/2 = 1/4 Example: What is the probability of tossing a coin and getting “tails” and then tossing a die and getting “6”? –0.50 x 0.167 = 0.083 OR 1/2 x 1/6 = 1/12

4 Mystery Shops  Set p = probability that a clerk will check ID for an individual mystery shop  1- p = probability that a clerk will NOT check ID for an individual mystery shop

5 Sequence of Mystery Shops  Probability that a clerk will check ID for all of the mystery shops:  2 visits: p x p  3 visits: p x p x p  4 visits: 1- (p 4 ) ... and so on  Probability that a clerk will NOT check ID for at least one mystery shop:  2 visits: 1- (p x p)  3 visits: 1- (p x p x p)  4 visits: 1- (p 4 ) ... and so on

6 Probability: Clerk Will Check ID for All Mystery Shop Inspections Number of MS 1 (p)2 (p 2 )3 (p 3 )4 (p 4 )5 (p 5 ) p =.60.60.36.22.13.08 p =.80.80.64.51.41.33 p =.90.90.81.73.66.59 p =.95.95.90.86.81.77

7 Probability: Clerk Will NOT Check ID for at Least One Mystery Shop Inspection Number of MS 1 (1-p)2 (1-p 2 )3 (1-p 3 )4 (1-p 4 )5 (1-p 5 ) p =.60.40.64.78.87.92 p =.80.20.36.49.59.67 p =.90.10.19.27.34.41 p =.95.05.10.14.19.23

8 Reality Check With clerk compliance at 90%, then the probability of at least 1 out of 5 MS inspections showing non-compliance is.41. Imagine a community (Utopia) where every alcohol retailer could bring the staff up to 90% compliance. With 5 MS inspections each, 41% of the retailers would be found in violation of the law at least once.

9 Do the Math Let’s do 10 mystery shop inspections: Retailer’s compliance rate = 90% –Probability of at least one MS inspection showing non-compliance = 65%! Retailer’s compliance rate = 95% –Probability of at least one MS inspection showing non-compliance = 40%!

10 Conclusion Frequent non-compliance is a fact of life, even for retailers with high rates of clerk compliance with the law

11 The Difficulty of Detecting Relatively Low Compliance Rates Compliance rate = 70% –Probability of detection 1 visit = 30% 2 visits = 51% Compliance rate = 80% –Probability of detection 1 visit = 20% 2 visits = 36%

12 Policy Implications Fact: Even with near universal compliance, there is a substantial probability of non- compliance over multiple inspections. –What constitutes a “reasonable” response to a first offense?

13 Policy Implications Fact: The greater the number of MS inspections, the greater the probability of non-universal compliance. –What is a reasonable number of MS inspections to conduct within a given time frame? –What is a reasonable number of non- compliance findings before harsher sanctions (license suspension or revocation) are applied?


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