Nonparametric specification testing via the trinity of tests

Abhimanyu Gupta

Economics Discussion Papers from University of Essex, Department of Economics

Abstract: Tests are developed for inference on a parameter vector whose dimension grows slowly with sample size. The statistics are based on the Lagrange Multiplier, Wald and (pseudo) Likelihood Ratio principles, admit standard normal asymptotic distributions under the null and are straightforward to compute. They are shown to be consistent and possessing non-trivial power against local alternatives. The settings considered include multiple linear regression, panel data models with fixed effects and spatial autoregressions. When a nonparametric regression function is estimated by series, we use our statistics to propose specification tests, and in semiparametric adaptive estimation we provide a test for correct error distribution specification. These tests are nonparametric but handled in practice with parametric techniques. A Monte Carlo study suggests that our tests perform well in finite samples. Two empirical examples use them to test for correct shape of an electricity distribution cost function and linearity and equality of Engel curves.

Date: 2015-10-22
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://repository.essex.ac.uk/23824/ original version (application/pdf)

Related works:
Journal Article: Nonparametric specification testing via the trinity of tests (2018)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:esx:essedp:23824

Ordering information: This working paper can be ordered from
Discussion Papers Administrator, Department of Economics, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, U.K.

Access Statistics for this paper

More papers in Economics Discussion Papers from University of Essex, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Essex Economics Web Manager ().