Testing the Significance of Categorical Predictor Variables in Nonparametric Regression Models
By Jeffrey S. Racine, Jeffrey D. Hart, Qi Li. 2006
172 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/2f225e561afac8c63e4711586ef6dfcba19cfb47
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Jaren C. Pope
- N. Kuminoff
- Kristof De Witte
- Christopher F. Parmeter
- Mika Kortelainen
- T. Hayfield
- Kevin J. Boyle
- Jeffrey S. Racine
In Sociology and Political Science
- N. Kuminoff
- Jaren C. Pope
- Kristof De Witte
- Mika Kortelainen
- T. Hayfield
- Kevin J. Boyle
- Christopher F. Parmeter
- Jeffrey S. Racine
Citations in the corpus
- What explains the performance of students in a heterogeneous environment? Conditional efficiency estimation with continuous and discrete environmental variables (2013, methodology): “Simar and Wilson, 2007). It is important to give more justification for our approach based on the estimated dependent variable. Related to this we want to emphasize that the framework does not suffer from similar inference problems as the two-stage models based on the traditional and deterministic F”
- What can we learn from benefit transfer errors? Evidence from 20 years of research on convergent validity (2013, methodology): “This test is analogous to a t-test in linear regression [28].”
- Nonparametric Econometrics: The np Package (2008, methodology): “There exist nonparametric counterparts to these tests that were proposed by Racine (1997), and extended to admit categorical variables by Racine et al. (2006) Having conducted this test we observe that, as was the case for the linear parametric model, the explanatory variable age is significant at…”