Application of distributed lag and autocorrelated error models to short-run demand analysis

dc.contributor.author Ladd, George
dc.contributor.author Martin, James
dc.contributor.department Extension and Experiment Station Publications
dc.date 2018-02-18T14:07:55.000
dc.date.accessioned 2020-06-30T06:59:36Z
dc.date.available 2020-06-30T06:59:36Z
dc.date.embargo 2017-06-21
dc.date.issued 2017-06-21
dc.description.abstract <p>The objective of the research reported here was to investigate the usefulness of distributed lag economic models and autocorrelated error statistical models for analysis of monthly and quarterly food demand. Distributed lags are a way of incorporating dynamic considerations into econometric models of consumer demand. In the distributed lag model used here, current consumption is the dependent variable, and lagged consumption is one explanatory variable. Testing the significance of the coefficient of lagged consumption tests the hypothesis of a lag in consumer adjustment to conditions affecting demand.</p> <p>The presence of autocorrelated errors can have serious effects on least squares (L.S.) estimates of coefficients. Autocorrelated errors may frequently occur in equations fitted to monthly and quarterly data. Therefore, equations were estimated by autoregressive least squares (A.L.S.) as well as by least squares. A.L.S.-1 assumes the errors u<sub>t</sub> to follow a first order autoregressive scheme, u<sub>t</sub> = β<sub>1</sub>u<sub>t-1</sub> + e<sub>t</sub>. It provides simultaneous estimates of β<sub>1</sub> and of the coefficients in the demand equation. A.L.S.-2 assumes the errors to be generated by a second order autoregressive process, u<sub>t</sub> = β<sub>1</sub>u<sub>t-1</sub> + β<sub>2</sub>u<sub>t-2</sub> + e<sub>t</sub>. It provides simultaneous estimates of β<sub>1</sub>, β<sub>2</sub> and the coefficients in the demand equation.</p>
dc.identifier archive/lib.dr.iastate.edu/researchbulletin/vol35/iss526/1/
dc.identifier.articleid 1540
dc.identifier.contextkey 10331045
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath researchbulletin/vol35/iss526/1
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/62865
dc.source.bitstream archive/lib.dr.iastate.edu/researchbulletin/vol35/iss526/1/Agricultural_Research_Bulletin_v035_b526.pdf|||Fri Jan 14 17:43:32 UTC 2022
dc.subject.disciplines Agriculture
dc.subject.disciplines Economics
dc.subject.disciplines Sociology
dc.title Application of distributed lag and autocorrelated error models to short-run demand analysis
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isJournalIssueOfPublication 2246edaa-e785-4a10-b71d-8aaa4cf2ca37
relation.isOrgUnitOfPublication 302bd0e8-f82f-406a-88b5-c8f956b5f77b
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