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Nonparametric Estimation of Nonadditive Random Functions
Open accessAbstract
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.
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Cited by
Recent Developments in the Econometrics of Program Evaluation
Imbens, G. W., & Wooldridge, J. M. (2009) · Journal of Economic Literature · doi:10.1257/jel.47.1.5 · Cited by 4,926
Identification and Inference in Nonlinear Difference-in-Differences Models
Athey, S., & Imbens, G. W. (2006) · Econometrica · doi:10.1111/j.1468-0262.2006.00668.x · Cited by 1,084
1. The Scientific Model of Causality
Heckman, J. J. (2005) · Sociological Methodology · doi:10.1111/j.0081-1750.2006.00164.x · Cited by 401
Abbring, J. H., & Heckman, J. J. (2007) · Handbook of Econometrics · doi:10.1016/s1573-4412(07)06072-2 · Cited by 122
Metadata
- Authors
- Matzkin, R. L.
- Venue
- Econometrica
- Publisher
- The Econometric Society
- Published
- 2003-09
- Volume
- 71
- Issue
- 5
- Pages
- 1339-1375
- ISSN
- 0012-9682 (ISSN-L)
- 1468-0262
- OpenAlex
- W1989711934
- Cited by
- 386
- References
- 46
- FWCI
- 10.43
- Type
- journal article
- Language
- en
- Open access
- green
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