Multinomial Probit with Time-Series Data
Unifying State Dependence and Serial Correlation Models
Bibliographic Data
| ID | 4139562 |
|---|---|
| Authors | Carlos F Daganzo (University of California, Berkeley), Yosef Sheffi (Massachusetts Institute of Technology) |
| Year | 1982 |
| Volume | 14 |
| Issue | 10 |
| Pages | 1377-1388 |
| Publication date | 1982-10-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Environment and Planning A Economy and Space (JOURNAL) |
| Journal identifiers | ISSN: 0308-518X • E-ISSN: 1472-3409 |
| Publisher | SAGE Publications Inc (PUBLISHER) |
| DOI | 10.1068/a141377 |
| OpenAlex | W1994075928 |
| Language | EN |
| Citations received | 4 |
| References cited | 3 |
This paper develops a general method for treating discrete data sets containing individuals that have made more than one choice under varying stimuli. The multinomial probit model is shown to possess properties that make it very attractive for this application, as with it, it is possible to develop an estimation process that uses all the information in the data, and is both relatively inexpensive and consistent with utility maximization. The method, which is a generalization of Heckman's binary model, can include taste variations and more than two alternatives
Binary data · Binary number · Econometrics · Expectation–maximization algorithm · Generalization · Mathematical optimization · Maximization · Maximum likelihood · Multinomial distribution · Multinomial probit · Multivariate probit model · Probit · Probit model · Statistics · Computer Science · Economic and Environmental Valuation · Mathematics · Multi-Criteria Decision Making · Transportation Planning and Optimization
| Citations per year | 0.1 |
|---|---|
| Citation span | 1985 - 2010 (26) |
| Highly cited | No |