Representing the differences between female and male commute behavior in residential location choice models

By M. Sermons, Frank S. Koppelman. 2001

200 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Sociology and Political Science, Transportation

View Paper: https://www.semanticscholar.org/paper/374042754336cf87a335b001718f3c45b049a6a2

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

1. Chandra R. Bhat
2. C. Angelo Guevara
3. Moshe E. Ben-Akiva
4. R. Pendyala
5. Ipek N. Sener
6. Kara M. Kockelman
7. Jessica Y. Guo
8. Jason D. Lemp

In Sociology and Political Science

1. C. Angelo Guevara
2. Chandra R. Bhat

In Transportation

1. Chandra R. Bhat
2. C. Angelo Guevara
3. Moshe E. Ben-Akiva
4. R. Pendyala
5. Ipek N. Sener
6. Kara M. Kockelman
7. Jessica Y. Guo
8. Jason D. Lemp

Citations in the corpus

• Numerical Analysis of Effect of Sampling of Alternatives in Discrete Choice Models (2004, background): “Several researchers have exploited this result for estimations in different empirical contexts (8-12).”
• Correcting for endogeneity due to omitted attributes in discrete-choice models: the multiple indicator solution (2016, unknown): “Staiger and Stock (1997) showed that when the IVs are only weakly correlated with the endogenous variable, the correction of endogeneity may even result in larger finite sample bias than the one obtained with the uncorrected model.”
• STRATEGIC SAMPLING FOR LARGE CHOICE SETS IN ESTIMATION AND APPLICATION (2012, background): “(See, e.g., Pozsgay and Bhat 2001, Sermons and Koppelman 2001, Nerella and Bhat 2004, among many others.)”
• A MIXED SPATIALLY CORRELATED LOGIT MODEL: FORMULATION AND APPLICATION TO RESIDENTIAL CHOICE MODELING (2004, background): “The housing cost and school quality variables were, rather surprisingly, not statistically significant (see Sermons and Koppelman, 2001 for a similar result in their study of residential location in the San Francisco Bay Metropolitan area).”
• Accommodating Spatial Correlation Across Choice Alternatives in Discrete Choice Models: Application to Modeling Residential Location Choice Behavior (2011, background): “Bowman (1998), Sermons and Koppelman (1998, 2001) , Bhat and Guo (2004), Miyamoto et al.”
• Endogeneity in Residential Location Choice Models (2006, background): “Variables a, b, c, and d were considered iid uniform (1, 2) for each household and alternative.”