Nonparametric Identification of the Production Functions
نویسندگان
چکیده
A class of semi-recursive kernel plug-in estimates of functions depending on multivariate density functionals and their derivatives is considered. The approach enables to estimate the production function, marginal productivity and marginal rate of technical substitution of inputs. The piecewise smoothed approximations of these estimates are proposed. The main parts of the asymptotic mean square errors (AMSE) of the estimates are found. The results are generalized to the production functions with the lagged values of the output.
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