6. The following regression equation describes contingent valuation estimates of
ID: 3200268 • Letter: 6
Question
6. The following regression equation describes contingent valuation estimates of willingness to pay user access fees on Coopers Rock State Forest (CRSF) in West A. Based on economic theory, what sign would you expect for each variable coefficient? B. Interpret each coefficient. Which variables have statistically significant coefficients? C. Do the results conform to economic theory? D. Would you add the education variable to this model? why or why not? wTP User Access Fees on Coopers Rock State Forest Variable Name Definition Mean Respondent Demographics AGE Age in years 39.90 EDUCATION Highest level of education, coded 1 4.61 (8th grade or less to 6 uate school 42.40 INCOME Level of household income ($000) 0.38 Location ofresidence LOCATION Out-of state 1, In-state 0 0.93 Caucasian Other 0 RACE Recreational Behavior Day of interview DAY weekend-1, weekday 0 0.08 Mountain biking as main activity at MTBIKE CRSF 1, otherwise zero 0.48 Previous experience with user access fees, PAID vessel, no 0 2.88 Number of visits to CRSF in the previous VISITS year, coded l (once) to 10 (more than 50) Attitudinal 0.54. Response to question about fairness of FAIR charging fees at state parks or dExplanation / Answer
Reg eq is
WTP=2.211+1.101 FAIR-0.00722INCOME-0.0340AGE+1.071RACE+0.761 LOCATION-0.901 PAID-0.124 VISITS
+0.719 DAY+1.414 MTBIKE
+ sign ---> means as WTPincreases the taken independent varaiable like FAIR ,RACE,LOCATION, DAY ,MTBIKE increases and as WTP decreases the taken independent varaiable like FAIR ,RACE,LOCATION, DAY ,MTBIKE decreases.
-sign means--->means as WTPincreases the taken independent variable like INCOME,AGE,PAID,VISTS decreases and as WTPdecreases the taken independent variable like INCOME,AGE,PAID,VISTS increases.
The standard deviation of the estimate of a regression coefficient measures how precisely the model estimates the coefficient's unknown value. The standard error of the coefficient is always positive.
Use the standard error of the coefficient to measure the precision of the estimate of the coefficient. The smaller the standard error, the more precise the estimate. Dividing the coefficient by its standard error calculates a t-value. If the p-value associated with this t-statistic is less than your alpha level, you conclude that the coefficient is significantly different from zero.
u can add education variable as
R 2 value increased from 0.1862 to 0.1967
After adding Education variable:
WTP=2.211+1.101 FAIR-0.00722INCOME-0.0340AGE+1.071RACE+0.761 LOCATION-0.901 PAID-0.124 VISITS
+0.719 DAY+1.414 MTBIKE+0.2381 EDUCATION
variable coefficient standard error t value degrees of freedom p value(two tail) level of significance(assumed =0.05) constant 2.2119 0.8023 2.756949 148 0.006568 The result is significant at p < .05. FAIR 1.1019 0.3619 3.044764 148 0.002764. The result is significant at p < .05. INCOME -0.00722 0.0051 -1.41569 148 0.159169. The result is not significant at p < .05. AGE -0.034 0.0166 -2.04819 148 0.042328. The result is significant at p < .05. RACE 1.071 0.6205 1.726027 148 0.086434 The result is not significant at p < .05 LOCATION 0.762 0.385 1.979221 148 0.049672. The result is significant at p < .05. PAID -0.901 0.3559 -2.53161 148 0.012385. The result is significant at p < .05 VISITS -0.124 0.0817 -1.51775 148 0.131148. The result is not significant at p < .05. DAY 0.719 0.3344 2.15012 148 .03318. The result is significant at p < .05. MTBIKE 1.414 0.7372 1.918068 148 .057037. The result is not significant at p < .05. t value=coeff/std error fair,age,location,paid,day are significant variable coefficient standard error t value degrees of freedom p value(two tail) level of significance(assumed =0.05) constant 2.2119 0.8023 2.756949 148 0.006568 The result is significant at p < .05. FAIR 1.1019 0.3619 3.044764 148 0.002764. The result is significant at p < .05. INCOME -0.00722 0.0051 -1.41569 148 0.159169. The result is not significant at p < .05. AGE -0.034 0.0166 -2.04819 148 0.042328. The result is significant at p < .05. RACE 1.071 0.6205 1.726027 148 0.086434 The result is not significant at p < .05 LOCATION 0.762 0.385 1.979221 148 0.049672. The result is significant at p < .05. PAID -0.901 0.3559 -2.53161 148 0.012385. The result is significant at p < .05 VISITS -0.124 0.0817 -1.51775 148 0.131148. The result is not significant at p < .05. DAY 0.719 0.3344 2.15012 148 .03318. The result is significant at p < .05. MTBIKE 1.414 0.7372 1.918068 148 .057037. The result is not significant at p < .05. t value=coeff/std error fair,age,location,paid,day are significantRelated Questions
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