The California Rockfish Conservation Area: Climate Fluctuations and Groundfish Trawlers at Moss Landing Harbor

1. The California Rockfish Conservation Area:Climate Fluctuations and Groundfish Trawlers at Moss Landing Harbor UW Climate Impacts Group Seminar November 14, 2002 Michael Dalton California State University, Monterey Bay

2. Motivation for current work • Rebuilding stocks of bocaccio, canary, darkblotched, widow, yelloweye rockfish ... • Spatial regulations may protect overfished stocks and allow fishing opportunities • Issues related to effects of displaced fishing effort • Bioeconomic models with climate links could inform policy

3. CIG Vision Statement 2001-2005 • Provide fishery managers tools to improve management of … economically and ecologically important fisheries • Improve regional natural resource management decisions, including new climate information • Reduce vulnerability of agricultural production to climatic variability and climate change • Provide decision-making tools including geographical information systems for quantitative policy analysis (Integrated Assessment?)

4. Economics and global change • Two sides of ecological economics • Ecosystem valuation • Human behavior • Human behavior has two key elements • Economic activity drives global change • People respond to economic incentives (e.g. policy) and adapt to change • Coupled ecological-economic (bioeconomic) models are a framework for understanding behavior and its effects, and a tool for valuation • However climatic variability is usually missing

5. Global warming and agriculture • Economics literature has focused on average temperatures • Climatic variability literature suggests extremes and higher-order effects also important • “Welfare bias from omitting climatic variability…” (Dalton, 1997)

6. Climatic variability and information • Type of forward-looking behavior important for predicting responses and measuring effects • Recursive or adaptive expectations • Perfect foresight • Rational expectations • “Making Climate Forecasts Matter” (NRC, 1999) • Value of climate information depends on type of expectations • Need to develop and test structural models for climate sensitive sectors • Testing different behavioral assumptions is important for policy analysis • Little testing has been done for climate models

7. Estimating and testing economic models • Testing models for policy analysis familiar problem to macroeconomists • Lucas and Sargent: We observe an agent, or collection of agents, behaving through time; we wish to use these observations to infer how this behavior would have differed had the agent's environment been altered in some specified way • They conclude: the problem of identifying a structural model from a collection of economic time-series must be solved

8. Climatic variability and fisheries • Mantua et al. BAMS (1997) article life-changing: atmosphere and ocean • Familiar time-series methods (ARIMA etc.) • Static treatment of economic decisions • “El Nino, Expectations, and Fishing Effort in Monterey Bay” (Dalton, 2001)

9. Climate fluctuations and bioeconomic dynamics Sea surface temperature • ENSO affects abundance • Effects and feedbacks • fishing effort • landings • ex vessel prices • Uncertainty is another feedback • future ENSO • future abundance • future ex vessel prices • Expectations can affect current fishing effort Abundance Fishing Effort Landings Ex vessel prices

10. El Nino and Monterey Bay fisheries • Time-series analysis of fish ticket data for Monterey Bay ports • Albacore • Chinook • Sablefish • Squid • Empirical strategy • Vector autoregressions • Develop, estimate, and test structural fisheries model

11. Methods for Monterey Bay • Vector of fishing effort (number of vessels), ex vessel prices, and sea surface temperatures for each fishery • Vector autoregression (VAR): linear regression of current values on lagged values of each variable • Structural fisheries model: Fishermen have rational expectations and maximize expected discounted value of profits • Compare likelihood values to test structural model

12. Results for Monterey Bay • VAR analysis shows significant effects of SST on fishing effort and ex vessel prices for albacore, chinook, sablefish, and squid • Rational expectations hypothesis accepted for albacore, chinook, and sablefish • Fisheries model gives structural relationships between climate, abundance, ex vessel prices, and fishing effort • Model shows ENSO has positive effects on abundance of albacore and negative effects on chinook and sablefish

13. Climate fluctuations and spatial management • Goal of bioeconomic models to inform management • Recent management actions are spatial • Marine reserve size and location • 2003 West Coast groundfish regulations • Follow similar empirical strategy with spatial and dynamic structural fisheries model • Spatial and temporal interactions enrich and complicate analysis • Computational “curse of dimensionality” • Case study: Moss Landing groundfish trawlers and California Rockfish Conservation Area

14. PacFIN Data and GIS analysis • California PacFIN trawler logbook and ticket data • 1981-2001, north of Point Conception • GIS by port and DFG fishing blocks • Query GIS for Moss Landing data on tow hours, catch, and ex vessel prices

15. IRI SST and DFG bathymetry data

16. California Rockfish Conservation Area (CRCA) • CRCA • Inshore zone >3nm and <50-60fm • Offshore zone >150fm Pt. Reyes south, >250fm north • Area 1: DFG blocks inside CRCA • Area 2: DFG blocks outside CRCA

17. Data for vector autoregression (VAR) analysis • Compile time series data for Moss Landing • Total tow hours for blocks inside and outside CRCA, 1981-2001 • Cumulative ex vessel prices for DTS species at Moss Landing • Nov-March Average sea surface temperatures (SST) for ENSO index • Quadrivariate (four variable) VAR • Data are deviations from means • Data are covariance stationary • Second-order restrictions appropriate

21. Orthogonalized impulse response functions simulate 1997-98 ENSO • Increase in effort inside CRCA • Decrease outside • Inshore movement of effort from ENSO • Modest increase in ex vessel prices

22. Response to a temporary effort reduction in the CRCA equal to total tow hours in 2001 • Reduction inside CRCA followed by rapid return to mean • Increase outside with oscillations • Modest increase in ex vessel prices

23. Granger causality tests • Multivariate test rejects excluding effort outside CRCA from the VAR at 5% significance level • Effort outside CRCA could be Granger causing: • Ex vessel prices • Fishing effort inside CRCA • SST (fishermen’s expectations) • Bioeconomic model here allows 3 only • Bivariate tests inconclusive • T-statistics from VAR support 3

24. Bioeconomic Model components • Two area model with stochastic dynamics • Net RPUE A t depends on • Effort H t in the area (crowding externality) • Abundance N t in the area (dynamic externality) • Ex vessel prices P t at the port • A t = f 0 + f 1 H t + f 2 N t + f 3 P t

25. Bioeconomic Model components • Abundance N t depends on • Effort H t in the area (fishing mortality) • Lagged abundance N t - 1 • Stochastic recruitment or migration X t • N t = g 0 + g 1 H t + g 2 N t - 1 - g 1 g 2 H t - 1 + X t • Stochastic recruitment depends on • Sea surface temperature St • random factor Y t • X t = τ St + Y t

26. Bioeconomic model components • SST and Y tare first order Markov processes • S t = ρ St - 1 + εs t • Y t = λ Yt - 1 + εy t • Ex vessel prices have a first-order form • P t = φ1 Pt - 1 + φ2 St - 1 + εp t • The εk t are least-squares residuals with finite variance and zero conditional mean

27. Fisherman’s problem • Dynamic and spatial adjustment costs • Each fisherman has discount factor 0 < β < 1 and chooses random vectors of fishing effort h t to maximize an expected present value of profits: E Σ t β t( A t h t – ( h t - h t – 1 )´R ( h t - h t – 1 ) )

28. Model solution and regression equations • Solution given by stochastic Euler equations and transversality conditions • Solving the fisherman’s problem involves many tedious steps of algebra • Highlights are • Factoring characteristic matrix polynomial • Wiener-Kolmogorov prediction formula • Construction of orthogonal forecast errors • End result: system of four regression equations that incorporate parameter restrictions of rational expectations hypothesis

29. Maximum likelihood estimates

30. Likelihood ratio tests of bioeconomic model • Bioeconomic model tested against less restricted third-order VAR alternative • First test statistic has asymptotic chi-squared distribution • Second test statistic modified for small sample bias • Neither test rejects bioeconomic model at 5% significance level

31. Conclusions • VAR analysis shows significant differences inside and outside CRCA • Inshore movement from ENSO • Effort displacement from CRCA • Bioeconomic model gives reasonable results • RPUE inside CRCA more sensitive to vessel crowding • RPUE inside CRCA more sensitive to changes in ex vessel prices • Adjustment costs greater outside CRCA • Stock/SST effects support VAR results

32. Next steps for data and model development • Historical regulatory data including trip limits for DTS species from SAFE documents • Species detail from stock assessments, rebuilding analyses, etc. to identify additional parameters and estimate bycatch • Relax model assumptions to predict effort shifts • Adjustment costs • Stock recruitment and migration • Address effort and ex vessel prices

33. Acknowledgements • National Marine Fisheries Service, Division of Statistics and Economics • California Seagrant • William Daspit (PSMFC/PacFIN), • Rita Curtis (NMFS), Church Grimes (NMFS), Pat Iampietro (CSUMB), Carrie Pomeroy (UCSC), Rick Starr (CSG), Cindy Thomson (NMFS), Charlie Wahle (NOAA MPA Center), Gina Wade (CDFG), Nancy Wright (CDFG)

34. Community effects and integrated assessment • Structural models for climate sensitive sectors do not measure full social effects of climate variability • Multiplier effects are often present in economic systems • For example, Post 9/11 decline in demand for air travel • Effects cascade through hospitality and entertainment sectors

35. Input-output analysis • Input-output (IO) analysis is one way to derive multipliers • IO table embedded in larger Social Accounting Matrix (SAM) • SAM multipliers often used for policy analysis • West Coast Fisheries Economics Assessment Model • Regional and national sources of IO data available • IO analysis by itself is static and restrictive • No substitutability of inputs • Use of multipliers often inappropriate

36. Computable general equilibrium models • Accepted method for Integrated Assessment is to calibrate dynamic simulation models with SAMs • Dynamic computable general equilibrium models are routinely used to analyze costs and benefits of alternative climate change policies • Production sectors can be disaggregated to highlight climate sensitive industries • Ongoing work with the Population-Environment-Technology (PET) model

37. Population Environment Technology Model Carbon Emissions Households capital & labor consumption & savings K & L C & I Intermediate goods producers oil&gas coal electricity refined petroleum materials (everything else) Final goods producers hi energy consumption lo energy consumption investment government exports & imports E & M

38. US costs and permit prices with Kyoto • no permit trade=400$/ton • with permit trade=100$/ton • with ed. & permits=75$/ton • LR costs of ed. policies >direct=10-15$/ton >net=2-3$/ton • CDM with carbon credits for primary education is cost effective in LR • Ed. policies ineffective for SR goals of Kyoto

39. Future Population Environment Technology Model Climate Households capital & labor consumption & savings K & L C & I Intermediate goods producers agriculture fisheries forests energy everything else Final goods producers tourism and recreation other consumption investment government exports & imports E & M