Bivariate Probit and Logit Models.pdf - Google Drive
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Page 2 of 4. 2. Bivariate Probit and Logit Models Example. We study the factors influencing the joint outcome of being i
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Bivariate Probit and Logit Models.pdf - Google Drive
Bivariate probit and logit models equations Coefficients and marginal effects
2
Bivariate probit model
Bivariate outcome examples Individual decision whether to work or not and whether to have children or not. Farmer decision of whether to use marketing contracts or not and whether to use environmental contracts or not. The bivariate models estimates decisions that are interrelated as opposed to independent. Bivariate probit model specification The bivariate probit model is a joint model for two binary outcomes. These outcomes may be correlated, with correlation . If the correlation turns out insignificant, then we can estimate two separate probit models, otherwise we have to use a bivariate probit model. The unobserved latent variables are presented as: y∗ y∗
′ ′
3
The bivariate probit model specifies the outcomes as: 1 y ∗ 0 y ∗
0 0
1 y ∗ 0 y ∗
0 0
Marginal effects and predicted values can be estimated similarly to those for the binary probit models. Marginal effects for the joint probability, say P(y1=1 and y2=1) are also available.
