NDLI: Measuring the Inspectorate: Point and Interval Estimates for Performance Indicators

Content Provider	Springer Nature Link
Author	Decrouez, Geoffrey Robinson, Andrew
Copyright Year	2016
Abstract	Border-based regulatory inspectorates, such as quarantine and customs organizations, intervene at national and state borders to ensure compliance of activities to relevant policies. Performance indicators can be used to help assess and compare the activities for the risk of non-compliance, and also to assess the inspectorate’s ability to detect and rectify non-compliance. We document a suite of three performance indicators that target inspectorate intervention at and before the border, and provide protocols for collecting the necessary data to compute point estimates of the indicators. For obtaining interval estimates, we then discuss mathematical models that account for the sources of uncertainty that are present during data collection. We cover three distinct setups, namely, the importation of certain classes of air cargo in Australia, both historically and under current policies, and passengers arriving at an international airport. The methodology developed here using the terminology of quarantine inspections can be applied in more general settings. Under the model which best describes the way data are collected, we provide confidence bounds for the performance indicators, with coverage close to the nominal level. The methodology is then illustrated on real and fabricated data.
Starting Page	382
Ending Page	401
Page Count	20
File Format	PDF
ISSN	10857117
Journal	Journal of Agricultural, Biological, and Environmental Statistics
Volume Number	21
Issue Number	2
e-ISSN	15372693
Language	English
Publisher	Springer US
Publisher Date	2016-03-24
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Raking Iterative proportional fitting Performance indicators Confidence intervals Inspectorates Statistics for Life Sciences, Medicine, Health Sciences Agriculture Environmental Monitoring/Analysis Biostatistics
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Statistics and Probability Environmental Science Agricultural and Biological Sciences Statistics, Probability and Uncertainty

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