Hi everyone,
I need to determine the marginal effects of interaction terms after the -ivprobit command. Here is my code:
* ivprobit fminorsucc (csr1 csr1_capint2 csr1_bBindex1 csr1_volt = csr1iv2 c.csr1iv2#c.capint2 c.csr1iv2#c.bBindex1 c.csr1iv2#c.volt) capint2 bBindex1 volt i.indid ydum10-ydum18 dismissal outsider0 pceofminor2 interim ceopay1seq madjemp avaslack dratio eBindex lambda hsstatus2 madjfirmage madjroe , vce(cluster compid) nolog
The endogenous variable is csr1. The instrumental variable is csr1iv2. I also include interaction terms: csr1_capint2, csr1_bBindex1, and csr1_volt. My issue is that -ivprobit- does not allow me to use interaction operators on the endogenous variable list.
Consequently, I have the following questions:
1) Would margins command still provide accurate marginal effects in this case? If not, how should I address this issue?
2) I have also tried the approach specified by Wiersema & Bowen (2009), which provides the code to calculate the true interaction terms using the formula in Ai & Norton (2003). However, after ivprobit, the standard errors is not accurate. Specifically, I tried to calculate marginal effects of csr1 in the model without interaction terms using both Wiersema & Bowen(2009) approach and -margins- command. The marginal effect is the same, but the Wiersema & Bowen( 2009) approach gives me insignificant results, while the -margin- command gave me significant results. Is there any other way to calculate the true interaction effect after -ivprobit-?
Thank you very much for your consideration and guidance.
References:
Ai, C., & Norton, E. C. (2003). Interaction terms in logit and probit models. Economics letters, 80(1), 123-129.
Wiersema, M. F., & Bowen, H. P. (2009). The use of limited dependent variable techniques in strategy research: Issues and methods. Strategic Management Journal, 30(6), 679-692.
I need to determine the marginal effects of interaction terms after the -ivprobit command. Here is my code:
* ivprobit fminorsucc (csr1 csr1_capint2 csr1_bBindex1 csr1_volt = csr1iv2 c.csr1iv2#c.capint2 c.csr1iv2#c.bBindex1 c.csr1iv2#c.volt) capint2 bBindex1 volt i.indid ydum10-ydum18 dismissal outsider0 pceofminor2 interim ceopay1seq madjemp avaslack dratio eBindex lambda hsstatus2 madjfirmage madjroe , vce(cluster compid) nolog
The endogenous variable is csr1. The instrumental variable is csr1iv2. I also include interaction terms: csr1_capint2, csr1_bBindex1, and csr1_volt. My issue is that -ivprobit- does not allow me to use interaction operators on the endogenous variable list.
Consequently, I have the following questions:
1) Would margins command still provide accurate marginal effects in this case? If not, how should I address this issue?
2) I have also tried the approach specified by Wiersema & Bowen (2009), which provides the code to calculate the true interaction terms using the formula in Ai & Norton (2003). However, after ivprobit, the standard errors is not accurate. Specifically, I tried to calculate marginal effects of csr1 in the model without interaction terms using both Wiersema & Bowen(2009) approach and -margins- command. The marginal effect is the same, but the Wiersema & Bowen( 2009) approach gives me insignificant results, while the -margin- command gave me significant results. Is there any other way to calculate the true interaction effect after -ivprobit-?
Thank you very much for your consideration and guidance.
References:
Ai, C., & Norton, E. C. (2003). Interaction terms in logit and probit models. Economics letters, 80(1), 123-129.
Wiersema, M. F., & Bowen, H. P. (2009). The use of limited dependent variable techniques in strategy research: Issues and methods. Strategic Management Journal, 30(6), 679-692.