Hi all,
I have a panel dataset on syndicated loans. This means that I have data on specific loans made to firms, where there are multiple lenders/banks for a given loan. The panel has a three dimensional structure, with firm-bank-quarter observations. The total loan amount to a given firm is allocated to banks based on the variable "bankallocation". This variable is essentially a percentage that indicates which part of the total loan a specific bank has contributed (i.e. it can only take values from 0-100). In other words, the loan volume is the bank’s allocation times the total loan amount. The problem with this "bankallocation" variable is that the majority of the observations have missing values for this variable in my dataset. This means that I cannot calculate the loan volume for each bank in a given loan syndicate. This problem has been addressed in previous research, namely by Schwert (2018) in his Journal of Finance paper. He estimates missing values of this variable using a Tobit regression. The following quote from the paper explains his approach:
"When the bank’s allocation is missing in the data, it is estimated as the fitted value from a Tobit regression of bank allocation on log loan amount, the ratio of loan amount to lender assets, the ratio of loan amount to borrower assets, the number of lead arrangers, the number of participants, and quarter fixed effects."
I have been trying to find a way to imitate this approach using the same dataset. However, I ran into some issues. Given that the "bankallocation" variable can only take values from 0-100 (because it is a percentage, which should total 100 for a given loan), setting the lower and upper limit to 0 and 100 respecitvely makes sense. However, the added difficulty is that the sum of all "bankallocation" values should sum up to 100 for each loan, or at least not exceed 100. How could I accomplish this in Stata?
In addition, how can I estimate a quarter fixed effects Tobit regression in Stata?
Any help and advice is much appreciated.
Regards, Ali
I have a panel dataset on syndicated loans. This means that I have data on specific loans made to firms, where there are multiple lenders/banks for a given loan. The panel has a three dimensional structure, with firm-bank-quarter observations. The total loan amount to a given firm is allocated to banks based on the variable "bankallocation". This variable is essentially a percentage that indicates which part of the total loan a specific bank has contributed (i.e. it can only take values from 0-100). In other words, the loan volume is the bank’s allocation times the total loan amount. The problem with this "bankallocation" variable is that the majority of the observations have missing values for this variable in my dataset. This means that I cannot calculate the loan volume for each bank in a given loan syndicate. This problem has been addressed in previous research, namely by Schwert (2018) in his Journal of Finance paper. He estimates missing values of this variable using a Tobit regression. The following quote from the paper explains his approach:
"When the bank’s allocation is missing in the data, it is estimated as the fitted value from a Tobit regression of bank allocation on log loan amount, the ratio of loan amount to lender assets, the ratio of loan amount to borrower assets, the number of lead arrangers, the number of participants, and quarter fixed effects."
I have been trying to find a way to imitate this approach using the same dataset. However, I ran into some issues. Given that the "bankallocation" variable can only take values from 0-100 (because it is a percentage, which should total 100 for a given loan), setting the lower and upper limit to 0 and 100 respecitvely makes sense. However, the added difficulty is that the sum of all "bankallocation" values should sum up to 100 for each loan, or at least not exceed 100. How could I accomplish this in Stata?
In addition, how can I estimate a quarter fixed effects Tobit regression in Stata?
Any help and advice is much appreciated.
Regards, Ali
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