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dc.rights.licenseopenen_US
dc.contributor.authorABAY, K.A.
dc.contributor.authorABATE, G.T.
dc.contributor.authorBARRETT, C.B.
hal.structure.identifierGroupe de Recherche en Economie Théorique et Appliquée [GREThA]
dc.contributor.authorBERNARD, Tanguy
IDREF: 186182163
dc.date.accessioned2020-02-18T14:43:15Z
dc.date.available2020-02-18T14:43:15Z
dc.date.issued2019
dc.identifier.issn0304-3878en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/3500
dc.description.abstractEnWe show that non-classical measurement errors (NCME) on both sides of a regression can bias the parameter estimate of interest in either direction. Furthermore, if these NCME are correlated, correcting for either one alone can aggravate bias relative to ignoring mismeasurement in both variables, a ‘second best’ result with implications for a broad class of economic phenomena of policy interest. We then use a unique Ethiopian dataset of matched farmer self-reported and precise ground-based measures for both plot size and agricultural output to re-investigate the long-debated relationship between plot size and crop productivity. Both self-reported variables contain substantial NCME that are negatively correlated with the true variable values, and positively correlated with one another, consistent with prior studies. Eliminating both sources of NCME eliminates the estimated inverse size-productivity relationship. But correcting neither variable generates a parameter estimate not statistically significantly different from that generated using two improved measures, while correcting for just one source of NCME significantly aggravates the bias in the parameter estimate. Numerical simulations demonstrate that over a relatively large parameter space, expensive collection of objective measures of only one variable or correcting only one variable's NCME may be inadvisable when NCME are large and correlated. This has practical implications for survey design as well as for estimation using existing survey data.
dc.language.isoENen_US
dc.subject.enEthiopia
dc.subject.enagricultural policy
dc.subject.ensmallholder
dc.subject.enproductivity
dc.subject.enagricultural development
dc.subject.enAgricultural development
dc.subject.enagricultural performance
dc.subject.enBias
dc.subject.encomputer simulation
dc.subject.encorrelation
dc.subject.encrop production
dc.subject.enMeasurement
dc.subject.ennumerical model
dc.subject.enpolicy analysis
dc.subject.enSmallholder agriculture
dc.title.enCorrelated non-classical measurement errors, ‘Second best’ policy inference, and the inverse size-productivity relationship in agriculture
dc.typeArticle de revueen_US
dc.identifier.doi10.1016/j.jdeveco.2019.03.008
dc.subject.halEconomie et finance quantitative [q-fin]en_US
dc.subject.halÉconomie et finance quantitative [q-fin]
bordeaux.journalJournal of Development Economicsen_US
bordeaux.page171-184en_US
bordeaux.volume139en_US
bordeaux.hal.laboratoriesGroupe de Recherche en Economie Théorique et Appliquée (GREThA) - UMR 5113en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
hal.identifierhal-03033509
hal.version1
hal.date.transferred2020-12-01T12:50:30Z
hal.exporttrue
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