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As some sections are influenced by im- poundments, and therefore have slow moving water, other sections are true riv- erine environments. Each of the six river sections is considered a separate recre- ational site. Since flow data are available only for section 3, empirical results are derived only for this section. River section 3 spans the North Fork of the Feather River between Rock Creek Dam and Rock Creek power house. The TCM model specified in this study presents trips per capita as a function of the travel expenses from a particular coun- ty of origin to the recreational site plus other monetary parameters, such as the av- erage household income for the area of or- igin, and a quality variable, such as fish catch. The model can be specified, in time series form, as: TRIPS;,/POP;, = Bo • TRVCOST,," INC;,BZ - CREEL B3 + u;,, (3) where: i = 1, ... , 57 is the number of counties in California, excluding Imperial County, from which no visitations originated over the five-year period of the study. t = years from 1981 to 1985. TRVCOST;, is the cost of traveling from county i to river section 3 in time t. INC;, is average household income in county i in time t. CREEL, is the aggregate number of fish kept by anglers at river section 3 in year t. We chose to model fishing quality as to- tal number of fish kept rather than catch per angler day primarily because we be- lieve, and other fishing research has shown (Sorg et al. 1985:5), that aggregate catch may be a better approximation of how an- glers form their perception of a river's fish- ing quality. That is, anglers form their per- ceptions, concerning total fish catch, by word of mouth rather than catch per unit. The variable labeled TRVCOST is a func- tion of round trip distance to the site, vari- able vehicle expenses such as fuel and re- pair costs per mile, the average number of passengers per automobile, and the op- portunity cost of travel in terms of a frac- tion of the wage rate. TRVCOST is speci- fied as follows: TRVCOST;, _ ((rtdist * fuel and repair costs per mile)/2.5 passengers) + (rtdist,,/40 mph) * ('/z * wage rate). Data on fuel and repair costs for each of the five years were obtained from Hertz Corporation surveys (Hertz News 1981- 1986). To develop relative prices over the period of the study, the nominal dollar fig- ures were converted to real 1985 dollars. The cost per mile in 1985 was 17 cents. The secondary data require valuing trav- el time by the "fraction of wage rate" ap- proach suggested by Cesario (1976) rather than more recent primary data approaches suggested by Bockstael et al. (1987). The value of time was calculated as one-half the County specific wage rates in each of the five years (California Department of Finance 1986). The nonlinear equation (3) is mathe- matically equivalent to the nonlinear in the variables double-log form. Model (3) is a constant elasticity model with a hom- oscedastic dependent variable. With a homoscedastic dependent variable the ad- ditive error term in equation (3) is accept- able (Judge et al. 1985). A nonlinear form is desirable for several reasons. In general, taking the log of trips per capita has been found to reduce het- eroscedasticity (Vaughan et al. 1982; Strong 1983). Also, the problem of a negative pre- diction of trips that can occur with a linear model is avoided with certain specifica- tions that are nonlinear in the variables or coefficients. Since the dependent variable contains some zero observations, equation (3) must be estimated in lieu of the semi- or double- log forms. To exclude counties with zero trips at some time t from the sample is equivalent to excluding relevant infor- mation from the sample and would add a truncation bias to the coefficients (Smith and Desvousges 1985). Ideally, equation (3) should have a vari- able for price of substitute sites as there are a few substitute stream fishing areas on the west side of the Sierra Nevada Mountains; however, a substitute variable is not in- cluded in this analysis. As Caulkins et al. I NJ 26 Rivers • Volume 1, Number 1 January 1990