Dear all,
I’m estimating a three-step model involving:
Problem:
When I bootstrap all equations together (selection and outcome equations), the standard errors for the structural equation (step 3) are very large, and all p-values are 1. This issue does not occur when I bootstrap each equation separately, or when I run the equations without bootstrapping.
Any suggestions or advice on how to handle this would be greatly appreciated!
Best regards,
I’m estimating a three-step model involving:
- Selection Equation: A probit model for working
- Outcome Equations: Two outcome equations for income and child human capital.
- Structural working Equation: The working decision is modeled as a function of predicted values from the outcome equations and their squared terms.
Code:
program define full3step_allcoefs, rclass * Step 1: probit W controls of the income and child equations IV, vce(cluster coun) * Generate IMR predict xb, xb gen imr = normalden(xb) / normal(xb) if W== 1 replace imr = -normalden(xb) / (1 - normal(xb)) if W== 0 * Step 2: Outcome Equations reg hh_inc controls if W== 1 predict hh_inc1 reg hh_inc controls if W== 0 predict hh_inc0 gen change_hhInc = hh_inc1 - hh_inc0 gen change_hhIncSQ = change_hhInc * change_hhInc * Child Human Capital Equations reg child_hc controls if W== 1 predict child_hc_1 reg child_hc controls if W== 0 predict child_hc_0 gen change_child_hc = child_hc_1 - child_hc_0 gen change_child_hcSQ = change_child_hc * change_child_hc * Step 3: Structural Equation probit W change_hhInc change_hhIncSQ change_child_hc change_child_hcSQ controls, vce(cluster coun) matrix b_struct = e(b) end * Run the bootstrap bootstrap, reps(1000) seed(12345) cluster(coun): full3step_allcoefs
When I bootstrap all equations together (selection and outcome equations), the standard errors for the structural equation (step 3) are very large, and all p-values are 1. This issue does not occur when I bootstrap each equation separately, or when I run the equations without bootstrapping.
- Why bootstrapping all equations together could lead to these issues, but bootstrapping each equation separately works fine?
- Would it be appropriate to bootstrap the selection and outcome equations together, but bootstrapping the structural migration equation separately (which uses predicted values from the outcome equations)? or would this lead to biases in the standard errors?
Any suggestions or advice on how to handle this would be greatly appreciated!
Best regards,
Comment