Marginal rate of substitution for different sociodemographic groups
Posted: 31 Mar 2024, 17:54
Dear Prof. Hess.
I recently estimated a mixed logit model and calculated two different Marginal Rate of Substitution (MRS) indicators for the entire sample in the following way:
randcoeff[["b_tt"]] = -exp( mu_log_b_tt + sigma_log_b_tt * draws_tt )
randcoeff[["b_info"]] = exp(mu_log_b_info + sigma_log_b_info * draws_info)
randcoeff[["b_money"]] = exp(mu_log_b_money + sigma_log_b_money * draws_money)
1) Value of Risk Reduction (VRR) = (unconditionals[["b_info"]]/unconditionals[["b_tt"]])
(mean(VRR)); (sd(VRR))
2) Willingness to Accept (WTA) = (unconditionals[["b_tt"]]/unconditionals[["b_money"]])
(mean(WTA)); (sd(WTA))
Now, I aim to calculate these indicators for different socio-demographic groups using the below code:
VRR_ageL35 = (unconditionals[["b_info"]]/unconditionals[["b_tt"]]* (database$age == 1|database$age==2|database$age ==3))
(mean(VRR_ageL35)); (sd(VRR_ageL35))
WTA_ageL35 = ((unconditionals[["b_tt"]]/unconditionals[["b_money"]]) * (database$age == 1|database$age==2|database$age ==3))
(mean(WTA_ageL35)); (sd(WTA_ageL35))
The questions are the following:
A) Is the way I'm using to calculate MRS for different socio-demographic groups correct? If it is correct way, then my next question is:
B) Behaviorally, the values of VRR and WTA should have inverse relation, i.e. the socio-demogrpahic group that has higher value for VRR should have lower value for WTA, but unfortunately it is not the case in the results. What could be the reason for this?
Thank you for your kind support.
Regards,
K
I recently estimated a mixed logit model and calculated two different Marginal Rate of Substitution (MRS) indicators for the entire sample in the following way:
randcoeff[["b_tt"]] = -exp( mu_log_b_tt + sigma_log_b_tt * draws_tt )
randcoeff[["b_info"]] = exp(mu_log_b_info + sigma_log_b_info * draws_info)
randcoeff[["b_money"]] = exp(mu_log_b_money + sigma_log_b_money * draws_money)
1) Value of Risk Reduction (VRR) = (unconditionals[["b_info"]]/unconditionals[["b_tt"]])
(mean(VRR)); (sd(VRR))
2) Willingness to Accept (WTA) = (unconditionals[["b_tt"]]/unconditionals[["b_money"]])
(mean(WTA)); (sd(WTA))
Now, I aim to calculate these indicators for different socio-demographic groups using the below code:
VRR_ageL35 = (unconditionals[["b_info"]]/unconditionals[["b_tt"]]* (database$age == 1|database$age==2|database$age ==3))
(mean(VRR_ageL35)); (sd(VRR_ageL35))
WTA_ageL35 = ((unconditionals[["b_tt"]]/unconditionals[["b_money"]]) * (database$age == 1|database$age==2|database$age ==3))
(mean(WTA_ageL35)); (sd(WTA_ageL35))
The questions are the following:
A) Is the way I'm using to calculate MRS for different socio-demographic groups correct? If it is correct way, then my next question is:
B) Behaviorally, the values of VRR and WTA should have inverse relation, i.e. the socio-demogrpahic group that has higher value for VRR should have lower value for WTA, but unfortunately it is not the case in the results. What could be the reason for this?
Thank you for your kind support.
Regards,
K