I would like to Regress the likelihood that collateral are pledged on firm variables, loan contract variables and my test variables.
I have in mind to Control for time variant Variation by using time Dummies and to Control for the heterogeneity of Banks by Setting them as Panel variable. However, I would like to compare the normal probit model with the Panel probit model that use random effects per Default and the logit fixed effects model so that I justify my choice by the same comparisons as I did it for my other Analysis, where I used the loan rate as dependent variable (thus I could compare the fixed and the random effects model with the ols Regression by using Regress and xtreg command) Is this Approach for the justification of my model choice useful? This is my dataset:
input float Collateraldummy int Age long Totalassets byte Numberofemployees float Corporationdummy long Grossprofit double(Profitability Leverage) long Loansize byte(Maturity g1 g2 g3) double Duration byte Housebank str6 Loantype
1 8 1500000 28 1 1600000 .0625 .95 475000 10 0 0 1 0 0 "Credit"
0 8 1500000 28 1 1600000 .0625 .95 475000 10 0 0 1 0 0 "Credit"
1 6 500000 15 1 800000 .0875 .5 150000 10 0 0 1 5.75 1 "Credit"
1 6 500000 15 1 800000 .0875 .5 30000 1 0 0 1 5.75 1 "LC"
1 6 500000 15 1 800000 .0875 .5 20000 1 0 0 1 6 1 "LC"
1 23 387000 10 0 815000 .0343558282208589 .72 80000 1 0 1 0 10 1 "LC"
1 24 415000 10 0 830000 .05060240963855422 .77 80000 1 0 1 0 11 1 "LC"
1 25 400000 10 0 850000 .03529411764705882 .9 120000 1 0 1 0 12 1 "LC"
0 24 415000 10 0 830000 .05060240963855422 .77 60000 6 0 1 0 1 0 "Credit"
1 15 800000 25 1 3500000 .03428571428571429 .2 100000 1 0 0 1 4.666666666666667 0 "LC"
1 15 800000 25 1 3500000 .03428571428571429 .2 620000 20 0 0 1 0 0 "Credit"
1 15 800000 25 1 3500000 .03428571428571429 .2 230000 3 0 0 1 5 0 "LC"
0 7 130000 8 0 300000 .23333333333333334 .4 50000 10 1 0 0 4.75 1 "Credit"
0 1 60000 3 0 190000 0 0 20000 10 1 0 0 0 1 "Credit"
0 7 130000 8 0 300000 .23333333333333334 .4 15000 3 1 0 0 3 0 "LC"
1 20 450000 12 1 800000 .08125 .26 50000 10 0 1 0 10.083333333333334 0 "Credit"
1 18 462000 12 1 830000 .0819277108433735 .32 125000 5 0 1 0 8 0 "Credit"
1 19 438000 12 1 755000 .07549668874172186 .3 100000 5 0 1 0 0 0 "Credit"
1 20 450000 12 1 800000 .08125 .26 15000 1 0 1 0 10 0 "LC"
1 19 438000 12 1 755000 .07549668874172186 .3 15000 1 0 1 0 9 0 "LC"
1 18 462000 12 1 830000 .0819277108433735 .32 15000 1 0 1 0 8 0 "LC"
1 19 438000 12 1 755000 .07549668874172186 .3 120000 1 0 1 0 10 0 "LC"
1 18 462000 12 1 830000 .0819277108433735 .32 120000 1 0 1 0 9 0 "LC"
0 20 450000 12 1 800000 .08125 .26 10000 1 0 1 0 10.583333333333334 0 "LC"
1 15 320000 10 1 1000000 .08 .55 70000 6 1 0 0 7 0 "Credit"
1 15 320000 10 1 1000000 .08 .55 100000 5 1 0 0 5.166666666666667 0 "Credit"
1 10 277000 12 1 800000 .09375 .6 150000 4 1 0 0 5.083333333333333 1 "Credit"
1 18 720000 25 1 1800000 .11388888888888889 .45 350000 3 1 0 0 12 1 "Credit"
0 20 695000 25 1 2000000 .105 .45 300000 6 1 0 0 14 1 "Credit"
1 3 248000 3 1 500000 .11 .44 30000 4 0 1 0 0 0 "Credit"
1 4 250000 3 1 600000 .08333333333333333 .5 50000 5 0 1 0 1.33 0 "Credit"
0 3 248000 3 1 500000 .11 .44 8000 1 0 1 0 0 0 "LC"
0 4 250000 3 1 600000 .08333333333333333 .5 8000 1 0 1 0 1 0 "LC"
0 4 250000 3 1 600000 .08333333333333333 .5 10000 3 0 1 0 1.083 0 "LC"
1 2 462000 25 1 1750000 .022857142857142857 .45 100000 1 0 1 0 0 0 "LC"
1 3 450000 29 1 1900000 .027105263157894736 .5 200000 3 0 1 0 .5833333333333334 0 "LC"
1 3 450000 29 1 1900000 .027105263157894736 .5 100000 1 0 1 0 1 0 "LC"
1 2 462000 25 1 1750000 .022857142857142857 .45 250000 5 0 1 0 0 0 "Credit"
1 4 440000 29 1 2000000 .025 .5 200000 5 0 1 0 1.4166666666666667 0 "Credit"
1 7 360000 9 1 415000 .18795180722891566 .25 15000 1 0 1 0 5 1 "LC"
1 8 350000 9 1 435000 .18620689655172415 .25 25000 1 0 1 0 6 1 "LC"
1 9 345000 9 1 430000 .18604651162790697 .3 15000 1 0 1 0 7 1 "LC"
1 45 1000000 14 0 1450000 .07931034482758621 .6 350000 7 1 0 0 15 1 "Credit"
0 50 1050000 15 0 1500000 .06666666666666667 .7 300000 10 1 0 0 20 1 "Credit"
1 45 1000000 14 0 1450000 .07931034482758621 .6 150000 1 1 0 0 15 1 "LC"
1 46 970000 15 0 1400000 .06785714285714285 .7 150000 1 1 0 0 16.5 1 "LC"
1 47 960000 15 0 1475000 .06779661016949153 .7 150000 1 1 0 0 17.75 1 "LC"
1 7 350000 3 0 400000 .125 .5 20000 1 0 1 0 7 1 "LC"
1 7 350000 3 0 400000 .125 .5 15000 5 0 1 0 7 1 "Credit"
0 25 500000 25 1 1100000 .18181818181818182 .8 150000 10 0 1 0 15 1 "Credit"
0 25 500000 25 1 1100000 .18181818181818182 .8 400000 15 0 1 0 15 1 "Credit"
0 25 500000 25 1 1100000 .18181818181818182 .8 50000 1 0 1 0 15 1 "LC"
0 40 620000 25 0 2000000 .15 .2 150000 10 0 1 0 20 1 "Credit"
0 40 620000 25 0 2000000 .15 .2 50000 1 0 1 0 20 1 "LC"
0 35 380000 12 1 1500000 .06666666666666667 .3 25000 5 0 1 0 15 1 "Credit"
1 4 400000 7 0 950000 .1368421052631579 .25 300000 5 0 1 0 3 1 "Credit"
0 7 425000 9 0 1000000 .123 .2 250000 7 0 1 0 6 1 "Credit"
1 4 400000 7 0 950000 .1368421052631579 .25 50000 1 0 1 0 3 1 "LC"
1 5 415000 8 0 975000 .14358974358974358 .2 80000 1 0 1 0 4.333333333333333 1 "LC"
1 6 410000 9 0 935000 .13368983957219252 .2 80000 1 0 1 0 5.333333333333333 1 "LC"
1 7 425000 9 0 1000000 .123 .2 80000 1 0 1 0 6 1 "LC"
1 102 370000 6 0 427000 .14285714285714285 .42 80000 5 0 1 0 23 1 "Credit"
1 102 370000 6 0 427000 .14285714285714285 .42 30000 1 0 1 0 8 0 "LC"
1 103 375000 6 0 430000 .13953488372093023 .45 45000 1 0 1 0 8.75 0 "LC"
0 102 370000 6 0 427000 .14285714285714285 .42 80000 5 0 1 0 0 0 "Credit"
0 17 3500000 28 1 2875000 .05495652173913043 .38 500000 10 0 0 1 14 1 "Credit"
0 22 3625000 30 1 3000000 .05 .4 400000 7 0 0 1 4 0 "Credit"
1 22 3625000 30 1 3000000 .05 .4 60000 2 0 0 1 5 0 "LC"
1 22 3625000 30 1 3000000 .05 .4 50000 2 0 0 1 .16666666666666666 0 "LC"
0 18 3100000 15 1 2600000 .06538461538461539 .5 150000 3 0 0 1 5 0 "Credit"
0 18 3100000 15 1 2600000 .06538461538461539 .5 130000 4 0 0 1 4 0 "Credit"
0 18 3100000 15 1 2600000 .06538461538461539 .5 50000 2 0 0 1 4 0 "LC"
1 26 2650000 35 1 2300000 .09 .21 300000 5 0 0 1 22 1 "Credit"
1 27 2710000 35 1 2425000 .09278350515463918 .28 250000 7 0 0 1 23 1 "Credit"
0 29 2665000 33 1 2400000 .0875 .25 50000 9 0 0 1 25.25 1 "Credit"
0 30 2700000 33 1 2350000 .08297872340425531 .25 80000 10 0 0 1 26.333333333333332 1 "Credit"
1 27 2710000 34 1 2425000 .09278350515463918 .28 80000 1 0 0 1 23.166666666666668 1 "LC"
1 17 1980000 26 1 1650000 .0893939393939394 .26 325000 10 0 1 0 16 1 "Credit"
0 19 2050000 26 1 1700000 .08941176470588236 .31 150000 8 0 1 0 18.333333333333332 1 "Credit"
0 20 1930000 26 1 1750000 .08857142857142856 .33 220000 5 0 1 0 19.166666666666668 1 "Credit"
0 19 2050000 26 1 1700000 .08941176470588236 .31 80000 1 0 1 0 18.166666666666668 1 "LC"
end
and the Code:
Code:
probit Collateraldummy Age Totalassets Numberofemployees Corporationdummy Grossprofit Profitability Leverage Loansize Maturity g1 g3 Duration Housebank if Loantype!="Crédit"
Code:
 which yield to an R squared of 100% that I cannot explain. Also to use clustered Standard error, what variable do I have to use for the vce command

 xtprobit Collateraldummy Age Totalassets Numberofemployees Corporationdummy Grossprofit Profitability Leverage Loansize Maturity g1 g3 Duration Housebank if Loantype!="Credit"
for which model the iterations do not come to an end. Could you please tell me the reason?
Thanks in Advance for your help.