AGNELLO: ECONOMIC VALUE OF FISHING SUCCESS 



Table 1 . — Survey questions used in the estimations. 



From intercept survey 



16. Including today's trip, about how many times would you say you have fished from [this 



(specify exact mode) in the last 12 months?/a (specify exact boat mode) leaving from 



this launching area in the last 12 months?] 

 18. To the nearest highway mile, about how far is it from your home to this fishing location? 



29. May I look at the fish that you caught that you're taking with you? Enter species codes 

 and number kept. Did you land any (specify common name) that you're not taking with 

 you? 



30. How many additional (specify common name) did you land? 



From telephone survey 



23. How satisfied were you with your fishing trip on ( Month/Day )? Would you say you were 



bZ, aZ 



Ci, Vi 



ified in the above discussion,' 

 fishing success measured by the total 

 number of fish Icept (Table 1, question 

 29), 



previous year's income of the respond- 

 ent (Table 1, question 28), and 

 vector products of additive and multi- 

 plicative dummy variables and param- 

 eters allowing pooling across species to 

 be tested using a covariance model 

 (Kmenta 1986), 



independent, identically distributed 

 random errors. 



The log linear specification is used since it provides 

 a better fit over linear and semilog models in terms 

 of t-statistics and the equation F-statistics. Recent 

 studies estimating travel cost models have also 

 found that log models provide better fits to the data. 

 The choice of functional form has received much at- 

 tention in the literature. Discussions of some of the 

 issues including utility consistency, benefit sensi- 

 ti'vity, and transformed parameter biases can be 



'Dollar valuations are obtained by assuming a driving cost of 

 $0.16 per mile. This figure reflects a rescaling to 1987 dollars of 

 estimates appearing in "Cost of Owning and Operating Automo- 

 biles and Vans 1984," U.S. Department of Transportation, and in- 

 cludes only variable driving costs averaged over several vehicle 

 types. 



found in Bockstael et al. (1986), Stynes et al. (1986), 

 and Ziemer et al. (1980). 



Whether Equation (3) or Equation (4) is the appro- 

 priate model depends on the individual angler's 

 choice process. If we assume that trip frequency (Q) 

 is chosen after the site and thus travel cost (i.e., 

 distance) is specified. Equation (3) is appropriate. 

 If, on the other hand, anglers choose travel distance 

 or cost (P) by choosing a recreational site after the 

 frequency of visitation (i.e., the number of trips per 

 year, Q) is determined, then Equation (4) is appro- 

 priate. Most likely both Q and P are endogenous to 

 an individual angler so that ideally a multiequation 

 model should be estimated that would include many 

 competing sites as well as determinants of residen- 

 tial location choice. Unfortunately our data do not 

 allow us to employ such a model.* 



In our empirical analysis Equations (3) and (4) are 

 estimated as single equation models and compared. 

 Although Equation (3) is standard in the literature 



'Fishing success (S) also could be treated as an endogenous vari- 

 able related to angler skill, experience, equipment, and the fish 

 stock. An additional equation would be added to the model if one 

 wished to "explain" S. The empirical approach would be affected 

 depending on whether the model were simultaneous or recursive 

 in nature. To the extent that fishing success (S) is related to travel 

 frequency, Q (a proxy for experience), and travel cost, P, the model 

 should be estimated as a simultaneous equation system. Unfor- 

 tunately, additional variables required to adequately identify such 

 a system are not available. 



227 



