A consistent model specification test with mixed discrete and continuous data

By Cheng Hsiao, Qi Li, Jeffrey S. Racine. 2007

215 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/23003eb099dc0435849cd0345c2cf7bae8d34470

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Management Science and Operations Research

1. Ping Yu
2. Daniel J. Henderson
3. Ozkan Eren
4. Thanasis Stengos
5. C. Criado
6. Simone Valente
7. Jeffrey S. Racine
8. J. Porter

In Statistics and Probability

1. Jeffrey S. Racine
2. Ping Yu
3. T. Hayfield
4. Qi Li
5. Daniel J. Henderson
6. Ozkan Eren
7. Thanasis Stengos
8. J. Porter

Citations in the corpus

• The Impact of Homework on Student Achievement (2008, methodology): “To assess the correct estimation strategy, we utilize the Hsiao et al. (2007) specification test for mixed categorical and continuous data.”
• Specification Test for Panel Data Models with Interactive Fixed Effects (2014, unknown): “The parametric residual contains no useful information about the regression function when the linear model is correctly specified; it does otherwise.”
• An updated review of Goodness-of-Fit tests for regression models (2013, background): “A recent extension to the case where covariates may have a discrete component can be seen in Hsiao et al. (2007).”
• What can we learn from benefit transfer errors? Evidence from 20 years of research on convergent validity (2013, methodology): “A consistent kernel test [15] rejects the null hypothesis that the WLS model is correctly specified against the nonparametric alternative.”
• SMOOTH VARYING-COEFFICIENT ESTIMATION AND INFERENCE FOR QUALITATIVE AND QUANTITATIVE DATA (2010, methodology): “The proof of Theorem 4.1 is similar to the proof of Theorem 2.1 of Hsiao, Li, and Racine (2007).”
• Regression discontinuity designs with unknown discontinuity points: Testing and estimation (2015, methodology): “40 In classical speci cation tests, Hsiao et al (2007) is the only exception.”
• Growth and pollution convergence: Theory and evidence (2011, methodology): “40-3 to apply Hsiao et al. (2007)’s misspecification test.”
• Testing the Significance of Categorical Predictor Variables in Nonparametric Regression Models (2006, methodology): “also applied a consistent nonparametric test for correct specication of the parametric model (see Hsiao, Li, and Racine (2003) ).”
• Nonparametric Econometrics: The np Package (2008, methodology): “One might next test the null hypothesis that this parametric linear model is correctly specied using the consistent model specication test described in Hsiao et al. (2007) that admits both categorical and continuous data (we have overridden the default search tolerances for this example as the obj”