Nonparametric estimation of homogeneous function
Gautam Tripathi () and
No 2000,85, SFB 373 Discussion Papers from Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes
Consider the regression y = f(x) + e ' where E (e | x) = 0 and the exact functional form of f is unknown, although we do know that it is homogeneous of known degree r. Using a local linear approach we examine two ways of nonparametrically estimating f: (i) a direct or numeraire approach, and (ii) a projection based approach. We show that depending upon the nature of the conditional variance var (E | x), one approach may be asymptotically better than the other. Results of a small simulation experiment are presented to support our findings.
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Journal Article: NONPARAMETRIC ESTIMATION OF HOMOGENEOUS FUNCTIONS (2003)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:sfb373:200085
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