Hi,

I'm having trouble with a new instrumental variable. So I'm trying to find some causality, between how people think what their prices are and what they are. To get this causality I need some variables, and I've been directed to create some IV's, and have done many. So I believe that one of the driving factors are mortgage rates.

I tried this one below.
reghdfe SVoverLiquidTW log_fam_income age sex educ mstatus emp_status fam_members (misper_final = l2.misper_final), absorb(ZIP510 year) vce(cluster msa2 year)

And was told I was wrong, and that I should use an IV that is ela*libor. That is, the elasticity of prices(x)the interest rate of the market.

Does this mean my IV will have to look like: reghdfe SVoverLiquidTW log_fam_income age sex educ mstatus emp_status fam_members (ela*intrate), absorb(ZIP510 year) vce(cluster msa2 year)? Or have I just done an interaction variable?

I'm putting some of the code below but I believe it wont be very useful since i'm missing many values for the first 100 observations.
Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input float(SVoverLiquidTW log_fam_income age) byte(sex educ) float(int_rate elasticity10)
.  9.950609 48 1 0     . .
.  9.950609 48 1 0     . .
.  9.392662 57 1 0     . .
.  9.950609 48 1 0     . .
.  9.392662 57 1 0     . .
.  9.950609 48 1 0     . .
.  9.950609 48 1 0     . .
. 10.005592 49 1 0     . .
. 10.005592 49 1 0     . .
. 10.005592 49 1 0     . .
.  9.511111 58 1 0     . .
. 10.005592 49 1 0     . .
.  9.511111 58 1 0     . .
. 10.005592 49 1 0     . .
.  10.08581 50 1 0     . .
.  10.08581 50 1 0     . .
.   9.62905 59 1 0     . .
.  10.08581 50 1 0     . .
.  10.08581 50 1 0     . .
.   9.62905 59 1 0     . .
.  10.08581 50 1 0     . .
.  10.05406 50 1 0     . .
.  10.05406 50 1 0     . .
.  9.756436 60 1 0     . .
.  10.05406 50 1 0     . .
.  10.05406 50 1 0     . .
.  9.756436 60 1 0     . .
.  10.05406 50 1 0     . .
.  10.10234 52 1 0  7.38 .
.  10.10234 52 1 0  7.38 .
.  9.765604 60 1 0  7.38 .
.  10.10234 52 1 0  7.38 .
.  9.765604 60 1 0  7.38 .
.  10.10234 52 1 0  7.38 .
.  10.10234 52 1 0  7.38 .
.   8.88461 63 2 0  8.04 .
.  10.03012 53 1 0  8.04 .
.  10.03012 53 1 0  8.04 .
.  10.03012 53 1 0  8.04 .
.  10.03012 53 1 0  8.04 .
.   8.88461 63 2 0  8.04 .
.  10.03012 53 1 0  8.04 .
.  9.298168 64 2 0  9.19 .
. 10.210972 54 1 0  9.19 .
. 10.210972 54 1 0  9.19 .
.  9.298168 64 2 0  9.19 .
.   9.11603 24 1 0  9.19 .
.   9.11603 24 1 0  9.19 .
. 10.210972 54 1 0  9.19 .
.  9.480368 25 1 1  9.04 .
.  9.595603 26 1 1  9.04 .
.  10.37349 54 1 0  9.04 .
.  9.595603 26 1 1  9.04 .
.  10.37349 54 1 0  9.04 .
.  10.37349 54 1 0  9.04 .
.  9.480368 25 1 1  9.04 .
.  9.828603 27 1 1  8.86 .
. 10.388995 56 1 0  8.86 .
. 10.388995 56 1 0  8.86 .
.  9.585346 26 1 1  8.86 .
. 10.388995 56 1 0  8.86 .
.  9.585346 26 1 1  8.86 .
.  9.828603 27 1 1  8.86 .
.   9.62245 27 1 1  8.84 .
. 10.545341 57 1 0  8.84 .
. 10.545341 57 1 0  8.84 .
.  9.974319 28 1 1  8.84 .
. 10.545341 57 1 0  8.84 .
.   9.62245 27 1 1  8.84 .
.  9.974319 28 1 1  8.84 .
. 10.496815 57 1 0  9.63 .
.  9.384294 28 1 1  9.63 .
. 10.496815 57 1 0  9.63 .
.  10.25136 29 1 1  9.63 .
.  10.25136 29 1 1  9.63 .
. 10.496815 57 1 0  9.63 .
.  9.384294 28 1 1  9.63 .
. 10.499573 29 1 1 11.19 .
. 10.499573 29 1 1 11.19 .
.  9.480368 23 1 1 11.19 .
.  9.267477 30 1 1 11.19 .
.  9.480368 23 1 1 11.19 .
.  9.480368 23 1 1 11.19 .
.  9.267477 30 1 1 11.19 .
. 10.545341 30 1 1 13.77 .
. 10.663966 31 1 1 13.77 .
. 10.663966 31 1 1 13.77 .
.  9.517825 24 1 1 13.77 .
.  9.517825 24 1 1 13.77 .
. 10.545341 30 1 1 13.77 .
.  9.517825 24 1 1 13.77 .
. 9.2591305 25 1 1 16.63 .
. 9.2591305 25 1 1 16.63 .
. 9.2591305 25 1 1 16.63 .
. 10.738568 31 1 1 16.63 .
. 10.738568 31 1 1 16.63 .
.   10.4601 31 1 1 16.63 .
.   10.4601 31 1 1 16.63 .
. 10.897054 33 1 1 16.08 .
.  9.350102 26 1 1 16.08 .
end