A Model of Regulated Open Access Resource Use

More documents

Recommendations

Info

14 HOMANS AND WILEN TABLE II Parameter Estimates Ž . a Ž . a Ž . Ž . b Eq. 13 Eq. 14 Eqs. 16 and 15 Parameter Area 2 Area 3 Area 2 Area 3 Area 2 Area 3 c c 1a 1.3786 1.3119 Ž 24.01. Ž 31.51. b c 0.00119 c 0.00075 Ž 2.472. Ž 3.212. c c 12.329 c 16.417 Ž 2.990. Ž 2.807. d c 0.0897 d 0.0575 Ž 2.943. Ž 1.703. q c 0.00114 c 0.000975 Ž 24.984. Ž 30.895. c 0.0555 c 0.07848 Ž 8.4263. Ž 6.9705. f d 1.0318 2.0993 Ž 2.5569. Ž 1.8104. fW 0.79697 9.6556 d Ž 1.2154. Ž 3.4284. 0.96 0.92 Durbin’s h 6.21 5.76 D.W. 1.33 2.01 2 R 0.95 0.97 0.94 0.84 Hansen’s J 1.33 1.49 method OLS OLS NL3SLS a t-statistics in parentheses. b Asymptotic t-statistics in parentheses. c Significant at the 1% level. d Significant at the 5% level. biomass levels and the implied levels are 159 and 208 million pounds. The four parameter estimates can also be used to compute the safe biomass level implied by regulators’ choices of quota levels over this period. Using Eq. Ž 11. above, the levels of Xsafe implied by actual choices of harvest quota levels over the 19351977 period are 187 and 252 million pounds, respectively. Interestingly, the targeted or safe biomass levels implied by these equations are greater than the maximum sustainable yield biomass levels in both Areas 2 and 3, implying a conservative concern for stock safety. Results from the estimation of the industryregulator behavioral equations are also given in Table II. Parameter estimates are all of the correct sign and generally significant. Hansen’s J test of overidentifying restrictions 11 indicates that the model is not misspecified. 13 With respect to magnitudes, the parameter estimates are also reasonable and similar across regions. We would expect higher costs in 13 Hansen’s test is for estimators in the class of Generalized Method of Moments estimators, of which non-linear three stage least-squares is one. It is calculated as the value of the criterion function multiplied by the number of observations, and has a Chi-square distribution where the degrees of freedom are the number of instruments Ž. 8 less the number of free parameters Ž. 4 . Since Eq. Ž 16. is an implicit equation where the dependent variable is zero, there is no adequate goodness of fit measure available.
REGULATED OPEN ACCESS RESOURCE USE 15 FIG. 4. Quota rule targets. Area 3 due to its remoteness and this is the case for fixed costs. Fixed cost estimates suggest a twofold difference, with gear up cost estimates about $1,030 per unit of gear in Area 2 and $2,100 in Area 3. The War also had the expected effect of increasing the implicit opportunity cost of participating in the fishery. The implicit opportunity costs added by the hazards of war amount to an extra $790 per unit of gear in Area 2 and almost $9,700 in the Bering Sea. Variable costs are about $56 and $78 per gear set Ž skate soak. in Areas 2 and 3, respectively. This suggests that operating costs are lower in the more accessible region. 5. IMPLICATIONS AND ANALYSIS The predictions generated from this model of regulated open access are significantly different from those from the standard open access paradigm. In view of the fact that most fisheries are regulated rather than pure open access, we should also expect that they are closer to what we observe in real fisheries. In this section we compare the predictions of our new model with those that would be generated using the basic H. S. Gordon model of open access equilibrium. The issue to be examined is: what are the implications of Ž correctly, we would argue. including the regulatory sector in a model of a fishery? To examine this question we calculate the steady state for two alternatives, using parameter estimates described above. As discussed in the Introduction, the dominant paradigm in the renewable resource literature is the Gordon model of pure open access. We take this model to be represented by a zero rent condition together with a biological dynamics equation which describes how the species evolves. We thus assume instantaneous rent dissipation or fast dynamics for the entryexit of fishing capacity, and slow dynamics for the biology. Since we have also brought into the analysis the concept of a season length, a question arises as to what to assume about TŽ. t . We assume that the industry ends up fishing for a period equal to T max, which is the rent dissipating season length also. In Fig. 1, the industry reaches a temporary equilib-
Page 1 and 2: Ž . JOURNAL OF ENVIRONMENTAL ECONO
Page 3 and 4: REGULATED OPEN ACCESS RESOURCE USE
Page 13: REGULATED OPEN ACCESS RESOURCE USE
Page 21: REGULATED OPEN ACCESS RESOURCE USE

A Model of Regulated Open Access Resource Use

Create successful ePaper yourself

Delete template?

Save as template?