Improving the Efficiency of Probit Estimators
Bibliographic Data
| ID | 19318149 |
|---|---|
| Authors | Andrew Chesher (0000-0001-9646-3955, corresponding author) |
| Year | 1984 |
| Volume | 66 |
| Issue | 3 |
| Pages | 523 |
| Publication date | 1984-08-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | The Review of Economics and Statistics (JOURNAL) |
| Journal identifiers | ISSN: 0034-6535 • E-ISSN: 1530-9142 |
| Publisher | JSTOR (PUBLISHER) |
| DOI | 10.2307/1925015 |
| OpenAlex | W2165331727 |
| Language | EN |
| Citations received | 1 |
| References cited | 3 |
The efficiency with which coefficients in probit models are estimated is improved by exploiting data on continuous ancillary variates.In this paper the resulting gains in efficiency are examined and illustrative calculations are provided.Extra precision is achieved at the cost of making an extra assumption but this assumption can be tested.It is shown that fully efficient maximum likelihood estimation of the probit model with a continuous ancillary variate can be achieved by a simple two step procedure involving an ordinary least squares and a probit estimation
Econometrics · Economics · Estimator · Multivariate probit model · Ordered probit · Probit · Probit model · Statistics · Financial Risk and Volatility Modeling · Mathematics · Spatial and Panel Data Analysis · Statistical Distribution Estimation and Applications
| Citations per year | 0.03 |
|---|---|
| Citation span | 1987 - 1987 (1) |
| Highly cited | No |