Nonparametric Regression Tests Based on Least Squares
- 1 December 1992
- journal article
- research article
- Published by Cambridge University Press (CUP) in Econometric Theory
- Vol. 8 (4) , 435-451
- https://doi.org/10.1017/s0266466600013153
Abstract
This paper proposes tests on semiparametric models based on the sum of squared residuals from a least-squares procedure. Smoothness conditions are imposed on the nonparametric portion of the model to obtain asymptotic normality of the sum of squared residuals. The approach yields tests of specification, significance, smoothness and concavity and allows for heteroskedastic residuals.Keywords
This publication has 21 references indexed in Scilit:
- Non-parametric analysis of optimizing behavior with measurement errorJournal of Econometrics, 1985
- Non-parametric hypothesis testing procedures and applications to demand analysisJournal of Econometrics, 1985
- Convergence of Stochastic ProcessesPublished by Springer Nature ,1984
- École d'Été de Probabilités de Saint-Flour XII - 1982Published by Springer Nature ,1984
- A limit distribution of the square error deviation of nonparametric estimators of the regression functionProbability Theory and Related Fields, 1983
- Unbiased determination of production technologiesJournal of Econometrics, 1982
- Consistent model specification testsJournal of Econometrics, 1982
- Consequences and Detection of Misspecified Nonlinear Regression ModelsJournal of the American Statistical Association, 1981
- How small can one make the derivatives of an interpolating function?Journal of Approximation Theory, 1975
- Einige Ungleichungen Für Zweimal Differentiierbare FunktionenProceedings of the London Mathematical Society, 1914