This paper constructs a consistent model specification test based on the difference between the nonparametric kernel sum of squares of residuals and the sum of squares of residuals from a parametric null model. We establish the asymptotic normality of the proposed test statistic under the null...

This paper extends the linear stochastic frontier model proposed by D. J. Aigner, C. A. K. Lovell, and P. Schmidt (1977) to a semiparametric frontier model in which the functional form of the production frontier is unspecified and the distributions of the composite error terms are of known form....

Research in empirical health economics has found that the relationship between medical expenditures and age, income and other variables can be highly nonlinear. Moreover, men and women can have quite different medical expenditure patterns due to their differences in life expectancy. Thus it may...

By using nonparametric kernel estimation method and a central limit theorem for degenerate U-statistics of order higher than two, the authors develop several consistent model specification tests in the context of a nonparametric regression model. These include tests for omitted variables, tests...

Let <italic>F</italic> denote a distribution function defined on the probability space (Ω,null,<italic>P</italic>), which is absolutely continuous with respect to the Lebesgue measure in <italic>R</italic> with probability density function <italic>f</italic>. Let <italic>f</italic>₀(·,β) be a parametric density function that depends on an unknown <italic>p</italic> × 1 vector β. In this...

The focus of this paper is the nonparametric estimation of an instrumental regression function f defined by conditional moment restrictions that stem from a structural econometric model E[Y − f (Z) | W] = 0, and involve endogenous variables Y and Z and instruments W. The function f is the...