Non-compliance behavior and use of extraction rights for natural resources

Transcription

1 Non-compliance behavior and use of extraction rights for natural resources Florian Diekert 1 Yuanhao Li 2 Linda Nøstbakken 2 Andries Richter 3 2 Norwegian School of Economics 1 Heidelberg University 3 Wageningen University FishEcon Workshop, October / 23

2 Introduction Market-based instruments are widely used in resource conservation (fish, petroleum, water, timber, wildlife...) Individual quotas can limit aggregate resource use and define property rights incentivize optimal production inputs quota trading can enhance allocative efficiency 1 / 23

3 Introduction Market-based instruments are widely used in resource conservation (fish, petroleum, water, timber, wildlife...) Individual quotas can limit aggregate resource use and define property rights incentivize optimal production inputs quota trading can enhance allocative efficiency Strong enforcement of the underlying regulatory system is crucial 1 / 23

4 Research question This paper theoretically and empirically investigates how differences in individual preferences such as risk preferences intrinsic motivation to obey the law affect agents behavior in quota markets, and thus the allocative efficiency post trade. 2 / 23

5 Theoretical model I Assumptions and setup 1 A fisher operates in the fishery by choosing harvest, y, capital investment, K, quota investment, q, and catchability coefficient α 3 / 23

6 Theoretical model I Assumptions and setup 1 A fisher operates in the fishery by choosing harvest, y, capital investment, K, quota investment, q, and catchability coefficient α 2 Harvest revenue is αpy 3 / 23

7 Theoretical model I Assumptions and setup 1 A fisher operates in the fishery by choosing harvest, y, capital investment, K, quota investment, q, and catchability coefficient α 2 Harvest revenue is αpy α = 1: the fisher complies with harvest regulations 3 / 23

8 Theoretical model I Assumptions and setup 1 A fisher operates in the fishery by choosing harvest, y, capital investment, K, quota investment, q, and catchability coefficient α 2 Harvest revenue is αpy α = 1: the fisher complies with harvest regulations α > 1: the fisher violates harvest regulations (illegal gear/zone/season) 3 / 23

9 Theoretical model I Assumptions and setup 1 A fisher operates in the fishery by choosing harvest, y, capital investment, K, quota investment, q, and catchability coefficient α 2 Harvest revenue is αpy α = 1: the fisher complies with harvest regulations α > 1: the fisher violates harvest regulations (illegal gear/zone/season) α increases catchability at no extra costs 3 / 23

10 Theoretical model I Assumptions and setup 1 A fisher operates in the fishery by choosing harvest, y, capital investment, K, quota investment, q, and catchability coefficient α 2 Harvest revenue is αpy α = 1: the fisher complies with harvest regulations α > 1: the fisher violates harvest regulations (illegal gear/zone/season) α increases catchability at no extra costs α increases the penalty if violation is detected 3 / 23

11 Theoretical model I Assumptions and setup 1 A fisher operates in the fishery by choosing harvest, y, capital investment, K, quota investment, q, and catchability coefficient α 2 Harvest revenue is αpy α = 1: the fisher complies with harvest regulations α > 1: the fisher violates harvest regulations (illegal gear/zone/season) α increases catchability at no extra costs α increases the penalty if violation is detected 3 The marginal cost of using quota q is z 3 / 23

12 Theoretical model I Assumptions and setup 1 A fisher operates in the fishery by choosing harvest, y, capital investment, K, quota investment, q, and catchability coefficient α 2 Harvest revenue is αpy α = 1: the fisher complies with harvest regulations α > 1: the fisher violates harvest regulations (illegal gear/zone/season) α increases catchability at no extra costs α increases the penalty if violation is detected 3 The marginal cost of using quota q is z y = q: the fisher complies with quota regulations 3 / 23

13 Theoretical model I Assumptions and setup 1 A fisher operates in the fishery by choosing harvest, y, capital investment, K, quota investment, q, and catchability coefficient α 2 Harvest revenue is αpy α = 1: the fisher complies with harvest regulations α > 1: the fisher violates harvest regulations (illegal gear/zone/season) α increases catchability at no extra costs α increases the penalty if violation is detected 3 The marginal cost of using quota q is z y = q: the fisher complies with quota regulations y > q: the fisher violates quota regulations 3 / 23

14 Theoretical model I Assumptions and setup 1 A fisher operates in the fishery by choosing harvest, y, capital investment, K, quota investment, q, and catchability coefficient α 2 Harvest revenue is αpy α = 1: the fisher complies with harvest regulations α > 1: the fisher violates harvest regulations (illegal gear/zone/season) α increases catchability at no extra costs α increases the penalty if violation is detected 3 The marginal cost of using quota q is z y = q: the fisher complies with quota regulations y > q: the fisher violates quota regulations (y q) increases the penalty if violation is detected 3 / 23

15 Theoretical model II Assumptions and setup 4 Harvest cost is C(K, y) 4 / 23

16 Theoretical model II Assumptions and setup 4 Harvest cost is C(K, y) Given y, C( ) is a U-shaped curve w.r.t. K 4 / 23

17 Theoretical model II Assumptions and setup 4 Harvest cost is C(K, y) Given y, C( ) is a U-shaped curve w.r.t. K Given y, there is a cost-minimizing level of capital K = K (y) 4 / 23

18 Theoretical model II Assumptions and setup 4 Harvest cost is C(K, y) Given y, C( ) is a U-shaped curve w.r.t. K Given y, there is a cost-minimizing level of capital K = K (y) y and K are strategic complements 4 / 23

19 Theoretical model II Assumptions and setup 4 Harvest cost is C(K, y) Given y, C( ) is a U-shaped curve w.r.t. K Given y, there is a cost-minimizing level of capital K = K (y) y and K are strategic complements Cost of capital investment is I(K) 4 / 23

20 Theoretical model II Assumptions and setup 4 Harvest cost is C(K, y) Given y, C( ) is a U-shaped curve w.r.t. K Given y, there is a cost-minimizing level of capital K = K (y) y and K are strategic complements Cost of capital investment is I(K) 5 Exogenous probability π of detecting violations (inspection intensity) 4 / 23

21 Theoretical model II Assumptions and setup 4 Harvest cost is C(K, y) Given y, C( ) is a U-shaped curve w.r.t. K Given y, there is a cost-minimizing level of capital K = K (y) y and K are strategic complements Cost of capital investment is I(K) 5 Exogenous probability π of detecting violations (inspection intensity) 6 Fisher also receives a moral cost of violation M(y q, α 1) regardless of violation detection. 4 / 23

22 Theoretical model II Assumptions and setup 4 Harvest cost is C(K, y) Given y, C( ) is a U-shaped curve w.r.t. K Given y, there is a cost-minimizing level of capital K = K (y) y and K are strategic complements Cost of capital investment is I(K) 5 Exogenous probability π of detecting violations (inspection intensity) 6 Fisher also receives a moral cost of violation M(y q, α 1) regardless of violation detection. 7 Fisher chooses y, q, K and α to maximize expected utility 4 / 23

23 Theoretical model III Fisher chooses y, q, K and α to maximize expected utility ( ) max EU = (1 π)u αpy C(K, y) zq I(K) + q,α,y,k ( ) πu αpy C(K, y) zq I(K) β q (y q) β a (α 1) Subject to µm(y q, α 1) y q α 1 q 0 5 / 23

24 Model solution Solution to this model can be found in the following way Choose optimal harvest-violation, α 1, depending on revenue, expected punishment, moral cost and risk attitude Choose optimal harvest rate, y, which solves Optimal capital K (y) solves αp C y (K (y), y) z = 0 C K (K, y ) I (K) = 0 Demand for quota q y, depending on revenue, expected punishment, moral cost and risk attitude 6 / 23

25 Testable predictions/hypotheses 1 Agents with lower moral cost of harvest regulations are more likely to violate harvest regulations They can make higher profits by owning quota and capital Invest more in quota and capital 2 Agents with lower moral cost of quota regulations are more likely to violate quota regulations Invest less in quota, but not in harvest or capital 3 More risk-averse agents are less likely to violate Ambiguous effect on investment 7 / 23

26 Data Online survey and economic experiment 1 Incentivized experiments to elicit Risk preference Loss preference Time preference 2 Socioeconomic background 3 Fishery specific questions Background, type of fishery, ownership Non-compliance violations of formal and informal rules Stated past investment decisions Conducted in spring 2014 Response rate 10%: 164 vessel owners Representative sample Entire Norwegian coast Small and large boats All age groups, 98.4% male 8 / 23

27 Experiment payoffs (Exp. 1) Situations Lottery A Lottery B Expected payoff diff. High (0.3) Low (0.7) High (0.1) Low (0.9) (A-B) / 23

28 Experiment payoffs (Exp. 2) Situations Lottery A Lottery B Expected payoff diff. High (0.9) Low (0.1) High (0.7) Low (0.3) (A-B) / 23

29 Experiment payoffs (Exp. 3) Situations Lottery A Lottery B Expected payoff diff High (0.5) Low (0.5) High (0.5) Low (0.5) (A-B) / 23

30 Estimating parameters U(x, y; p) = { π(p)x r + {1 π(p)}y r, for x > y > 0 π(p)x r λ[1 π(p)]( y) r, for x > 0 > y where π(p) = exp[ ( ln(p)) α ] 12 / 23

31 Survey questions about non-compliance Fishermen answered the following questions about a range of formal and informal violations: 1 Can the violation be justified? 2 What is the main reason for you to comply? 3 How does your compliance behavior compare to that of the average fisherman 13 / 23

32 % of respondents ear/zone/time Q1. Can the violation be justified? Summary statistics Min. size Discards Unrep. sales Under-report Never Sometimes Usually / 23

33 Q2. Why comply with regulations? Summary statistics by violation type (in %) Formal Should Stock dev., punishmt follow law future inc. Unfair Reputation Other Gear/zone/time Min. size Discards Unrep. Sales Under report / 23

34 % of respondents Q3. Non-compliance relative to average? Summary statistics Discards Unrep. sales Min. size Less than About average More than / 23

35 Investment decisions Number of investments made ( ), by individuals N of inv. Quota Vessel Total / 23

36 Results Correlation between investments and moral cost to violate: negative binomial regression N quota inv N vessel inv Justify Harvest Violation (0.472) (0.379) Justify Quota Violation (0.360) (0.190) Risk tolerance (0.267) (0.183) Observations Pseudo R Prob > χ Control variables: discount rate, loss aversion, income, age, geographic location Robust standard errors in parentheses p < 0.1, p < 0.05, p < / 23

37 Results Correlation between investments and self-reported violation: negative binomial regression N quota inv N vessel inv Harvest violation (0.288) (0.196) Quota violation (0.288) (0.212) Risk tolerance (0.259) (0.178) Observations Pseudo R Prob > χ Control variables: discount rate, loss aversion, income, age, geographic location Robust standard errors in parentheses p < 0.1, p < 0.05, p < / 23

38 Results Correlation between self-reported violation and moral motivation: probit model Fish violate Qutoa violate Justify violation (0.388) (0.279) Reason: follow law (0.277) (0.211) Risk tolerance (0.208) (0.193) Loss aversion (0.0354) (0.0332) Observations Pseudo R Prob > χ Control variables: income, age, geographic location Robust standard errors in parentheses p < 0.1, p < 0.05, p < / 23

39 Concluding remarks We find correlations between fishers moral motivations to comply with regulations, frequencies of violations and investment behavior Fishers with lower moral cost of harvest regulations are more likely to violate harvest regulations and invest more in quota Fishers with lower moral cost of quota regulations are more likely to violate quota regulations and invest less in quota We did not find statistically significant correlation between moral motivations/violation and capital investment Fishers whose main reason to comply is one should follow the law are less likely to violate 21 / 23

40 What can we learn Less compliant agents have higher demand for quota. Hence, the long-run equilibrium may be represented by a larger portion of less compliant agents. An adverse selection problem because the resource manager cannot observe agents types Cannot be induced from behavior in the quota market either because quota and harvest violations have opposite effects Market price of quota may incorporate non-compliance behavior in addition to resource rent, which may be affected by the efficacy of enforcement of the regulatory system Possible solutions Increase the intensity of inspection can be costly Change agents intrinsic motivation to comply(?) 22 / 23

41 Thank you! 23 / 23

42 Appendix 23 / 23

43 Geographic distribution of fishermen in the sample and in the population 23 / 23