Hi all,
I want to estimate the effects of personal characteristics on the turnedown ratio of loan applicants.
The dependent variable is the loan turndown ratio, lets say, varies between 0 and 1. If the applicant gets the desired loan amount she applies, the turndown ratio will be 0; and if she is totally turned down, the turndown ratio will be 1. However, if she gets some loan but not as much as she desires, the turndown ratio might vary within 0 and 1.
To test the effects, I tried several ways,
1. Using "intreg" to treat the sample as censored at two bounds: 0 and 1
2. Simply using OLS to estimate the full sample (I want to keep the information of the observations when the turndown ratio is 1 and 0).
3. Estimating the sub sample with the turndown ratio equals 0 and 1, using a probit model. (In this case, the sub sample looks like a truncated one, but do I have a better choose of model?)
In general, I feel uncomfortable with my tests, because option 1 losses the information when the turndown ration is 1 and 0. Option 2 looks to generate biased estimates, so does Option 3.
So, what should I do then especially when I want to keep as much as information as I can? Thank you.
Best,
Xiaoqiang Cheng
Xiaoqiang Cheng
University of Leuven
Tel +32 16 326853
Fax +32 16 326796
Mail Xiaoqiang Cheng
Center for Economic Studies
University of Leuven
Naamsestraat 69
Leuven, Belgium
B3000
Url www.econ.kuleuven.be/xiaoqiang.cheng
Disclaimer: http://www.kuleuven.be/cwis/email_disclaimer.htm
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