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- W4236098233 abstract "Semiparametric estimation methods are used to obtain estimators of the parameters of interest — typically the coefficients of an underlying regression function — in an econometric model, without a complete parametric specification of the conditional distribution of the dependent variable given the explanatory variables (regressors). A structural econometric model relates an observable dependent variable y to some observable regressors x; some unknown parameters β, and some unobservable ‘error term’ ε, through some functional y = g(x, β, ε); in this context, a semiparametric estimation problem does not restrict the distribution of ε (given the regressors) to belong to a parametric family determined by a finite number of unknown parameters, but instead imposes only broad restrictions on the distribution of e (for example, independence of ε and x, or symmetry of ε about zero given x) to obtain identification of β and construct consistent estimators of it." @default.
- W4236098233 created "2022-05-12" @default.
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- W4236098233 date "2010-01-01" @default.
- W4236098233 modified "2023-09-27" @default.
- W4236098233 title "Semiparametric Estimation" @default.
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- W4236098233 doi "https://doi.org/10.1057/9780230280816_30" @default.
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