Nonparametric estimation of homothetic and homothetically separable functions

Arthur Lewbel and Oliver Linton

No CWP14/03, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract: For vectors x and w, let r(x,w) be a function that can be nonparametrically estimated consistently and asymptotically normally. We provide consistent, asymptotically normal estimators for the functions g and h, where r(x,w) = h[g(x),w], g is linearly homogeneous and h is monotonic in g. This framework encompasses homothetic and homothetically separable functions. Such models reduce the curse of dimensionality, provide a natural generalization of linear index models, and are widely used in utility, production, and cost function applications. Extensions to related functional forms include a generalized partly linear model with unknown link function. We provide simulation evidence on the small sample performance of our estimator, and we apply our method to a Chinese production dataset.

JEL-codes: C14 C21 D24 (search for similar items in EconPapers)
Pages: 17 pp.
Date: 2003-10-01
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Related works:
Working Paper: Nonparametric estimation of homothetic and homothetically separable functions (2003)
Working Paper: Nonparametric Estimation of Homothetic and Homothetically Separable Functions (2003)
Working Paper: Nonparametric estimation of homothetic and homothetically separable functions (2003)
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