 Nonparametric Estimation of Nonadditive Random FunctionsEconometrica, 2003, vol. 71, issue 5, 1339-1375 Abstract: We present estimators for nonparametric functions that are nonadditive in unobservable random terms. The distributions of the unobservable random terms are assumed to be unknown. We show that when a nonadditive, nonparametric function is strictly monotone in an unobservable random term, and it satisfies some other properties that may be implied by economic theory, such as homogeneity of degree one or separability, the function and the distribution of the unobservable random term are identified. We also present convenient normalizations, to use when the properties of the function, other than strict monotonicity in the unobservable random term, are unknown. The estimators for the nonparametric function and for the distribution of the unobservable random term are shown to be consistent and asymptotically normal. We extend the results to functions that depend on a multivariate random term. The results of a limited simulation study are presented. Copyright The Econometric Society 2003. Date: 2003 There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ecm:emetrp:v:71:y:2003:i:5:p:1339-1375 Ordering information: This journal article can be ordered from Access Statistics for this article Econometrica is currently edited by Guido Imbens More articles in Econometrica from Econometric Society Contact information at EDIRC. |
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