Modeling Selectivity in Count-Data Models

By H. Ophem. 2000

56 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Marketing, Transportation

View Paper: https://www.semanticscholar.org/paper/67c61c34dade90b09ddc991965adffd823fb8b5d

How researchers see this paper

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

In Artificial Intelligence

1. Margarita Genius
2. Pravin K. Trivedi
3. David M. Zimmer
4. William H. Greene
5. E. Strazzera

In Marketing

1. Margarita Genius
2. Pravin K. Trivedi
3. David M. Zimmer
4. William H. Greene
5. E. Strazzera
6. David A. Hensher
7. Stephane Hess
8. John M. Rose

In Transportation

1. Margarita Genius
2. Pravin K. Trivedi
3. David M. Zimmer
4. William H. Greene
5. E. Strazzera
6. Stephane Hess
7. David A. Hensher
8. Riccardo Scarpa

Citations in the corpus

• Applying the copula approach to sample selection modelling (2008, result): “We also show results for the Lee copula, since it is fairly well-known in the econometrics literature: recent applications include van Ophem ( 2000 ) and Heckman et al .”
• Copula Modeling: An Introduction for Practitioners (2007, background): “Several texts have modeled sample selection using bivariate latent variable distributions that can be interpreted as specific examples of copula functions even though the term copula or copula properties are not explicitly used; see Lee (1983), Prieger (2002) and van Ophem (1999, 2000).”
• Fixed and Random Effects in Nonlinear Models (2001, methodology): “(A related approach based on embedding bivariate heterogeneity in a model is investigated by Lee (1983) and van Ophem (1999, 2000).”