Sampling Schemes for Policy Analyses Using Computer Simulation Experiments

dc.contributor.author Carriquiry, Alicia
dc.contributor.author Breidt, F. Jay
dc.contributor.author Carriquiry, Alicia
dc.contributor.author Lakshminarayan, P.
dc.contributor.department Center for Agricultural and Rural Development
dc.date 2018-02-16T12:50:14.000
dc.date.accessioned 2020-06-30T01:02:44Z
dc.date.available 2020-06-30T01:02:44Z
dc.date.embargo 2015-06-12
dc.date.issued 1997-11-01
dc.description.abstract <p>Evaluating the environmental and Economic impacts of agricultural policies is not a simple task. A systematic approach to evaluation would include the effect of policy-dependent factors (such as tillage practices, crop rotations, and chemical use) as well as the effect of policy independent covariates (such as weather, topography, and soil attributes) on response variables (such as amount of soil eroded or chemical leached into the groundwater). For comparison purposes, the effects of these input combinations on the response variable would have to be assessed under competing policy scenarios. Because the number of input combinations is high in most problems, and because policies to be evaluated are often not in use at the time of the study, practitioners have resorted to simulation experiments to generate data. But generating data from simulation models is often costly and time consuming; thus, the number of input combinations in a study may be limiting even in simulation experiments. In this paper, we discuss the problem of designing computer simulation experiments that require generating data for just a fraction of the possible input combinations. We propose an approach that is based on subsampling the 1992 National Resources Inventory (NRI) points. We illustrate the procedure by assessing soil erosion in a situation where there are "observed" data (reported by the Natural Resources Conservation Service (NRCS)) for comparison. Estimates for soil erosion obtained using the procedure we propose are in good agreement with NRCS reported values.</p>
dc.identifier archive/lib.dr.iastate.edu/card_workingpapers/169/
dc.identifier.articleid 1211
dc.identifier.contextkey 7212324
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath card_workingpapers/169
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/12486
dc.source.bitstream archive/lib.dr.iastate.edu/card_workingpapers/169/97wp184.pdf|||Fri Jan 14 21:07:36 UTC 2022
dc.subject.disciplines Agricultural and Resource Economics
dc.subject.disciplines Agricultural Economics
dc.subject.disciplines Biometry
dc.subject.disciplines Economics
dc.subject.disciplines Environmental Policy
dc.subject.keywords Statistics
dc.title Sampling Schemes for Policy Analyses Using Computer Simulation Experiments
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication 6ddd5891-2ad0-4a93-89e5-8c35c28b0de4
relation.isOrgUnitOfPublication 1a6be5f1-4f64-4e48-bb66-03bbcc25c76d
File
Original bundle
Now showing 1 - 1 of 1
Name:
97wp184.pdf
Size:
358.04 KB
Format:
Adobe Portable Document Format
Description:
Collections