Total number of cases: 196 (Unweighted) Number of selected cases: 196 Number of unselected cases: 0 Number of selected cases: 196 Number rejected because of missing data: 0 Number of cases included in the analysis: 196 Dependent Variable Encoding: Original Internal Value Value 0 0 1 1 Dependent Variable.. YES Would have taken trips in 1991 if cost of all trips is $[cost] more? Beginning Block Number 0. Initial Log Likelihood Function -2 Log Likelihood 270.0583 * Constant is included in the model. Beginning Block Number 1. Method: Enter Variable(s) Entered on Step Number 1.. COST Increase in the total cost of taking trips Estimation terminated at iteration number 3 because parameter estimates changed by less than .001 -2 Log Likelihood 255.570 Goodness of Fit 196.083 Cox & Snell - R^2 .071 Nagelkerke - R^2 .095 Chi-Square df Significance Model 14.488 1 .0001 Block 14.488 1 .0001 Step 14.488 1 .0001 Classification Table for YES The Cut Value is .50 Predicted No Yes Percent Correct N I Y Observed +-------+-------+ No N I 26 I 63 I 29.21% +-------+-------+ Yes Y I 14 I 93 I 86.92% +-------+-------+ Overall 60.71% ---------------------- Variables in the Equation ----------------------- Variable B S.E. Wald df Sig R Exp(B) COST -.0019 .0005 13.4326 1 .0002 -.2058 .9981 Constant .9767 .2619 13.9103 1 .0002

Total number of cases: 196 (Unweighted) Number of selected cases: 196 Number of unselected cases: 0 Number of selected cases: 196 Number rejected because of missing data: 0 Number of cases included in the analysis: 196 Dependent Variable Encoding: Original Internal Value Value 0 0 1 1 Dependent Variable.. YES Would have taken trips in 1991 if cost of all trips is $[cost] more? Beginning Block Number 0. Initial Log Likelihood Function -2 Log Likelihood 270.0583 * Constant is included in the model. Beginning Block Number 1. Method: Enter Variable(s) Entered on Step Number 1.. COST Increase in the total cost of taking trips Estimation terminated at iteration number 3 because parameter estimates changed by less than .001 -2 Log Likelihood 255.570 Goodness of Fit 196.083 Cox & Snell - R^2 .071 Nagelkerke - R^2 .095 Chi-Square df Significance Model 14.488 1 .0001 Block 14.488 1 .0001 Step 14.488 1 .0001 Classification Table for YES The Cut Value is .50 Predicted No Yes Percent Correct N I Y Observed +-------+-------+ No N I 26 I 63 I 29.21% +-------+-------+ Yes Y I 14 I 93 I 86.92% +-------+-------+ Overall 60.71% ---------------------- Variables in the Equation ----------------------- Variable B S.E. Wald df Sig R Exp(B) COST -.0019 .0005 13.4326 1 .0002 -.2058 .9981 Constant .9767 .2619 13.9103 1 .0002 Beginning Block Number 2. Method: Enter Variable(s) Entered on Step Number 1.. CATCH About how many bass-trout did you catch in 1991 INCOME annual income (in thousands) Estimation terminated at iteration number 4 because parameter estimates changed by less than .001 -2 Log Likelihood 241.691 Goodness of Fit 200.974 Cox & Snell - R^2 .135 Nagelkerke - R^2 .180 Chi-Square df Significance Model 28.367 3 .0000 Block 13.879 2 .0010 Step 13.879 2 .0010 Classification Table for YES The Cut Value is .50 Predicted No Yes Percent Correct N I Y Observed +-------+-------+ No N I 53 I 36 I 59.55% +-------+-------+ Yes Y I 28 I 79 I 73.83% +-------+-------+ Overall 67.35% ---------------------- Variables in the Equation ----------------------- Variable B S.E. Wald df Sig R Exp(B) COST -.0020 .0005 13.3348 1 .0003 -.2106 .9980 CATCH .0057 .0023 6.0436 1 .0140 .1258 1.0057 INCOME .0166 .0085 3.7664 1 .0523 .0831 1.0167 Constant .1040 .4102 .0643 1 .7999

Total number of cases: 196 (Unweighted) Number of selected cases: 196 Number of unselected cases: 0 Number of selected cases: 196 Number rejected because of missing data: 0 Number of cases included in the analysis: 196 Dependent Variable Encoding: Original Internal Value Value 0 0 1 1 Dependent Variable.. YES Would have taken trips in 1991 if cost of all trips is $[cost] more? Beginning Block Number 0. Initial Log Likelihood Function -2 Log Likelihood 270.0583 * Constant is included in the model. Beginning Block Number 1. Method: Enter Variable(s) Entered on Step Number 1.. COST Increase in the total cost of taking trips CATCH About how many bass-trout did you catch in 1991 INCOME annual income (in thousands) Estimation terminated at iteration number 4 because parameter estimates changed by less than .001 -2 Log Likelihood 241.691 Goodness of Fit 200.974 Cox & Snell - R^2 .135 Nagelkerke - R^2 .180 Chi-Square df Significance Model 28.367 3 .0000 Block 28.367 3 .0000 Step 28.367 3 .0000 Classification Table for YES The Cut Value is .50 Predicted No Yes Percent Correct N I Y Observed +-------+-------+ No N I 53 I 36 I 59.55% +-------+-------+ Yes Y I 28 I 79 I 73.83% +-------+-------+ Overall 67.35% ---------------------- Variables in the Equation ----------------------- Variable B S.E. Wald df Sig R Exp(B) COST -.0020 .0005 13.3348 1 .0003 -.2049 .9980 CATCH .0057 .0023 6.0436 1 .0140 .1224 1.0057 INCOME .0166 .0085 3.7664 1 .0523 .0809 1.0167 Constant .1040 .4102 .0643 1 .7999 Beginning Block Number 2. Method: Enter Variable(s) Entered on Step Number 1.. EDUCATIO Years of completed schooling MARRIED Marital Status SEX Sex of respondent AGE Age of Respondent EMPLOYED Has a job-business Estimation terminated at iteration number 4 because Log Likelihood decreased by less than .01 percent. -2 Log Likelihood 230.301 Goodness of Fit 197.233 Cox & Snell - R^2 .184 Nagelkerke - R^2 .245 Chi-Square df Significance Model 39.758 8 .0000 Block 11.390 5 .0442 Step 11.390 5 .0442 Classification Table for YES The Cut Value is .50 Predicted No Yes Percent Correct N I Y Observed +-------+-------+ No N I 52 I 37 I 58.43% +-------+-------+ Yes Y I 25 I 82 I 76.64% +-------+-------+ Overall 68.37% ---------------------- Variables in the Equation ----------------------- Variable B S.E. Wald df Sig R Exp(B) COST -.0018 .0006 10.0119 1 .0016 -.1821 .9982 CATCH .0059 .0023 6.6256 1 .0101 .1383 1.0059 INCOME .0153 .0099 2.3922 1 .1219 .0403 1.0155 EDUCATIO -.0760 .0620 1.5017 1 .2204 .0000 .9268 MARRIED .3666 .4012 .8349 1 .3609 .0000 1.4428 SEX .9826 .4753 4.2743 1 .0387 .0970 2.6715 AGE -.0045 .0156 .0817 1 .7750 .0000 .9956 EMPLOYED 1.3769 .5973 5.3145 1 .0211 .1171 3.9625 Constant -.4473 1.1585 .1491 1 .6994

Total number of cases: 196 (Unweighted) Number of selected cases: 196 Number of unselected cases: 0 Number of selected cases: 196 Number rejected because of missing data: 0 Number of cases included in the analysis: 196 Dependent Variable Encoding: Original Internal Value Value 0 0 1 1 Dependent Variable.. YES Would have taken trips in 1991 if cost of all trips is $[cost] more? Beginning Block Number 0. Initial Log Likelihood Function -2 Log Likelihood 270.0583 * Constant is included in the model. Beginning Block Number 1. Method: Enter Variable(s) Entered on Step Number 1.. COST Increase in the total cost of taking trips CATCH About how many bass-trout did you catch in 1991 INCOME annual income (in thousands) EMPLOYED Has a job-business EDUCATIO Years of completed schooling MARRIED Marital Status SEX Sex of respondent AGE Age of Respondent Estimation terminated at iteration number 4 because Log Likelihood decreased by less than .01 percent. -2 Log Likelihood 230.301 Goodness of Fit 197.233 Cox & Snell - R^2 .184 Nagelkerke - R^2 .245 Chi-Square df Significance Model 39.758 8 .0000 Block 39.758 8 .0000 Step 39.758 8 .0000 Classification Table for YES The Cut Value is .50 Predicted No Yes Percent Correct N I Y Observed +-------+-------+ No N I 52 I 37 I 58.43% +-------+-------+ Yes Y I 25 I 82 I 76.64% +-------+-------+ Overall 68.37% ----------------- Variables in the Equation ------------------ Variable B S.E. Wald df Sig R COST -.0018 .0006 10.0119 1 .0016 -.1722 CATCH .0059 .0023 6.6256 1 .0101 .1309 INCOME .0153 .0099 2.3922 1 .1219 .0381 EMPLOYED 1.3769 .5973 5.3145 1 .0211 .1108 EDUCATIO -.0760 .0620 1.5017 1 .2204 .0000 MARRIED .3666 .4012 .8349 1 .3609 .0000 SEX .9826 .4753 4.2743 1 .0387 .0918 AGE -.0045 .0156 .0817 1 .7750 .0000 Constant -.4473 1.1585 .1491 1 .6994 95% CI for Exp(B) Variable Exp(B) Lower Upper COST .9982 .9971 .9993 CATCH 1.0059 1.0014 1.0104 INCOME 1.0155 .9959 1.0354 EMPLOYED 3.9625 1.2291 12.7751 EDUCATIO .9268 .8207 1.0466 MARRIED 1.4428 .6572 3.1675 SEX 2.6715 1.0524 6.7816 AGE .9956 .9656 1.0264

Total number of cases: 196 (Unweighted) Number of selected cases: 108 Number of unselected cases: 88 Number of selected cases: 108 Number rejected because of missing data: 0 Number of cases included in the analysis: 108 Dependent Variable Encoding: Original Internal Value Value 0 0 1 1 Dependent Variable.. YES Would have taken trips in 1991 if cost of all trips is $[cost] more? Beginning Block Number 0. Initial Log Likelihood Function -2 Log Likelihood 149.71979 * Constant is included in the model. Beginning Block Number 1. Method: Enter Variable(s) Entered on Step Number 1.. COST Increase in the total cost of taking trips CATCH About how many bass-trout did you catch in 1991 INCOME annual income (in thousands) EMPLOYED Has a job-business EDUCATIO Years of completed schooling MARRIED Marital Status SEX Sex of respondent AGE Age of Respondent Estimation terminated at iteration number 4 because Log Likelihood decreased by less than .01 percent. -2 Log Likelihood 122.848 Goodness of Fit 106.283 Cox & Snell - R^2 .220 Nagelkerke - R^2 .294 Chi-Square df Significance Model 26.872 8 .0007 Block 26.872 8 .0007 Step 26.872 8 .0007 Classification Table for YES The Cut Value is .50 Selected cases NC EQ 1 Predicted No Yes Percent Correct N I Y Observed +-------+-------+ No N I 36 I 18 I 66.67% +-------+-------+ Yes Y I 17 I 37 I 68.52% +-------+-------+ Overall 67.59% Classification Table for YES The Cut Value is .50 Unselected cases NC NE 1 Predicted No Yes Percent Correct N I Y Observed +-------+-------+ No N I 21 I 14 I 60.00% +-------+-------+ Yes Y I 20 I 33 I 62.26% +-------+-------+ Overall 61.36% ----------------- Variables in the Equation ------------------ Variable B S.E. Wald df Sig R COST -.0021 .0008 6.4549 1 .0111 -.1725 CATCH .0051 .0027 3.5632 1 .0591 .1022 INCOME .0154 .0132 1.3629 1 .2430 .0000 EMPLOYED 1.9155 .8994 4.5357 1 .0332 .1301 EDUCATIO -.0873 .0873 .9991 1 .3175 .0000 MARRIED .2419 .5380 .2023 1 .6529 .0000 SEX 1.0829 .6624 2.6730 1 .1021 .0670 AGE .0195 .0221 .7774 1 .3779 .0000 Constant -1.6041 1.5765 1.0353 1 .3089 95% CI for Exp(B) Variable Exp(B) Lower Upper COST .9979 .9963 .9995 CATCH 1.0051 .9998 1.0104 INCOME 1.0156 .9896 1.0423 EMPLOYED 6.7903 1.1650 39.5787 EDUCATIO .9164 .7722 1.0875 MARRIED 1.2737 .4438 3.6560 SEX 2.9532 .8063 10.8168 AGE 1.0196 .9765 1.0647

Total number of cases: 196 (Unweighted) Number of selected cases: 88 Number of unselected cases: 108 Number of selected cases: 88 Number rejected because of missing data: 0 Number of cases included in the analysis: 88 Dependent Variable Encoding: Original Internal Value Value 0 0 1 1 Dependent Variable.. YES Would have taken trips in 1991 if cost of all trips is $[cost] more? Beginning Block Number 0. Initial Log Likelihood Function -2 Log Likelihood 118.28597 * Constant is included in the model. Beginning Block Number 1. Method: Enter Variable(s) Entered on Step Number 1.. COST Increase in the total cost of taking trips CATCH About how many bass-trout did you catch in 1991 INCOME annual income (in thousands) EMPLOYED Has a job-business EDUCATIO Years of completed schooling MARRIED Marital Status SEX Sex of respondent AGE Age of Respondent Estimation terminated at iteration number 4 because Log Likelihood decreased by less than .01 percent. -2 Log Likelihood 101.644 Goodness of Fit 87.096 Cox & Snell - R^2 .172 Nagelkerke - R^2 .233 Chi-Square df Significance Model 16.641 8 .0341 Block 16.641 8 .0341 Step 16.641 8 .0341 Classification Table for YES The Cut Value is .50 Selected cases NC EQ 0 Predicted No Yes Percent Correct N I Y Observed +-------+-------+ No N I 17 I 18 I 48.57% +-------+-------+ Yes Y I 8 I 45 I 84.91% +-------+-------+ Overall 70.45% Classification Table for YES The Cut Value is .50 Unselected cases NC NE 0 Predicted No Yes Percent Correct N I Y Observed +-------+-------+ No N I 24 I 30 I 44.44% +-------+-------+ Yes Y I 5 I 49 I 90.74% +-------+-------+ Overall 67.59% ----------------- Variables in the Equation ------------------ Variable B S.E. Wald df Sig R COST -.0018 .0009 4.3435 1 .0372 -.1408 CATCH .0076 .0043 3.1321 1 .0768 .0978 INCOME .0062 .0165 .1432 1 .7051 .0000 EMPLOYED .9334 .8417 1.2297 1 .2675 .0000 EDUCATIO -.0651 .0958 .4610 1 .4972 .0000 MARRIED .4865 .6659 .5338 1 .4650 .0000 SEX .7256 .7191 1.0182 1 .3130 .0000 AGE -.0348 .0247 1.9863 1 .1587 .0000 Constant 1.4162 1.9127 .5482 1 .4591 95% CI for Exp(B) Variable Exp(B) Lower Upper COST .9982 .9965 .9999 CATCH 1.0076 .9992 1.0160 INCOME 1.0062 .9743 1.0392 EMPLOYED 2.5431 .4885 13.2385 EDUCATIO .9370 .7766 1.1306 MARRIED 1.6267 .4410 5.9997 SEX 2.0660 .5047 8.4577 AGE .9658 .9202 1.0137