Capacity, capacity analysis, DEA, Resource /Energy Economics and Policy, Q2, Q22,

Wilen, James E.

English

Research Papers in Economics

79
Marine Resource Economics, Volume 22, pp. 79–82 0738-1360/00 $3.00 + .00
Printed in the U.S.A. All rights reserved Copyright © 2007 MRE Foundation, Inc.
Thoughts on Capacity Analysis: Is Capacity Analysis
Giving Policy Makers Information they Need?
JAMES E. WILEN
University of California, Davis
Key words   Capacity, capacity analysis, DEA.
JEL Classification Codes   Q2, Q22.
Introduction
A quick scan through the literature on the application of capacity analysis to fisher-
ies cannot help but impress a reader. Most obvious is how much recent intellectual
horsepower has been brought to the task. The work has attracted the best and the
brightest of both the fisheries economics and production economics professions. It
has received attention of economists who have been prominent for decades, as well
as a group of sophisticated young professionals. There have been numerous high-
level meetings and working groups convened by international agencies like the Food
and Agriculture Organization (FAO); regional groups within the European Union
(EU); and domestic governmental agencies, such as the U.S. National Marine Fish-
eries Service (NMFS) and Canada’s Department of Fisheries and Oceans (DFO).
There have also been numerous journal articles written applying methods to particu-
lar fisheries, volumes devoted to explaining concepts to policy makers and
professionals, and both peer reviewed and gray literature available to interested par-
ties. As someone who has not conducted any capacity analysis, I welcomed the
opportunity to read some of this literature and reflect on the question: Is capacity
analysis giving policy makers the information they need?
To address this question, we need to first revisit the policy context that origi-
nally generated recent interest in applying capacity analysis to fisheries. My read of
the origins of this work is that it was initiated in response to needs expressed by the
FAO and the EU to deal with the “overcapacity problem.” As a prominent early FAO
participant put it, “the existence of excessive fishing capacity is largely responsible
for the degradation of fishery resources, for the dissipation of food production po-
tential and for significant economic waste” (Greboval 2000). From this conceptual
perspective, it is not surprising that fishing capacity has captured the attention of
both the FAO and the EU. The FAO has placed new emphasis on measuring and re-
ducing excess capacity as part of its Code of Conduct for Responsible Fishing. The
EU similarly faces a number of Common Fisheries Policy (CFP) issues that require
agreeing upon transparent and coordinated capacity measurement methods in order
to phase out subsidies and reduce capacity.
Economists who have been involved in capacity analysis see its usefulness as
applying at two levels. One is at a reasonably aggregated level, so that, for example,
EU policy makers have a common measure to talk about the general level of overca-
James E. Wilen is a professor in the Department of Agricultural & Resource Economics, University of
California, Davis, Davis, CA 95616, email: wilen@primal.ucdavis.edu.Wilen 80
pacity. Does the EU have 50% too much capacity? 30%? Does Spain have more ex-
cess capacity than France? To answer these questions, it is obviously desirable to
have a few commonly agreed-upon measures of capacity with which to have discus-
sions regarding modifications to the CFP, and much of the recent methods
development is directed at that need. A second level is at the more disaggregated mi-
cro level, specifically a need to have vessel-specific measures for use in directed
capacity reduction programs and/or further regulations of capacity use. For example,
Kirkley and Squires (1999) suggest that “(input-based Data Envelopment Analysis
(DEA) measures) would allow determining the optimal vessel or fleet configuration
and actual vessels that should be decommissioned.”
My personal judgment about the above two potential uses of capacity analysis
in fisheries is that the first is possible and desirable, while the second may be desir-
able, but less likely to be achieved. It is a good idea to have some commonly
agreed-upon measures of excess capacity for the big picture part of the capacity
policy problem discussion. For example, if the EU wants to develop and finance a
decommissioning program, it would be useful to know which countries have the
most excess capacity and at least an order-of-magnitude estimate of the extent of
overcapacity. Policy makers need methods that can be used with different kinds of
data bases and that produce similar conclusions in order to avoid gaming in the
policy process. However, this application of capacity analysis seems best thought of
as a back-of-the-envelope task (e.g., to generate an ordinal ranking of countries with
the most severe problems) and not a task for which policy decisions hinge upon pre-
cise measurement. On the other hand, using micro-level analysis to identify which
specific vessels ought to be removed is a very precise objective, and one likely to be
asking too much of the methods. This is particularly the case given both the state of
our data and our understanding of production systems in fisheries.
In my opinion, there are several important reasons why it is unlikely that micro-
level capacity analysis will be useful to help design specific decommissioning
schemes, or to help with any task that requires vessel-specific precision. These rea-
sons have more to do with the state of production analysis as applied to fisheries
than to specific capacity methods, such as DEA methods. First, fishing production
processes are not adequately captured by simple adaptations of conventional produc-
tion analysis. Conventional production analysis, after all, was developed to study
agricultural production systems. A typical agricultural production function estimates
output per season as a function of inputs applied (water, fertilizer, management in-
puts, soil characteristics, degree days) and these kinds of systems tend to work
because there are clear physical relationships and processes connecting outputs and
inputs. But much of the fishing production process involves (often strategic) use of
space and time in ways that seem too subtle to be captured by simple output/input
relationships. Second, micro-level based capacity analysis relies on maintained be-
havioral hypotheses that do not hold in fisheries. While farmers may be
atomistically competitive cost minimizers (or profit maximizers), fishermen are of-
ten engaged in strategic, coordinated behavior that depends upon their neighbors’
actions. Information groups, group fishing, pooling, and other kinds of non-atomis-
tic and strategic behavior are at odds with simplifying behavioral assumptions that
are, in some cases, necessary foundations of empirical analysis. Third, and perhaps
most important, an implicit assumption of analysis that estimates production rela-
tionships based on current technology is that optimum capacity and ideally
configured fleets will be simply scaled-down versions of technology that is in use;
e.g., fewer boats and smaller vessels with similar designs. However, many rational-
ization programs have witnessed changes in incentives so different than under those
regulated open/restricted access, that often the technology in place before rational-
ization is not evident afterwards. For example, much of New Zealand’s nearshoreCapacity Analysis 81
red snapper was prosecuted with mixed species trawl gear before ITQs; whereas af-
ter ITQs, longlines were used in order to produce high-quality live fish for the
Japanese sashimi market. In other words, characterizing the optimal fleet (a precon-
dition for determining which boats should be decommissioned) is generally a much
more subtle exercise than estimating production relationships over existing activities
and tweaking those to simulate rationalization. In some cases, the technology by
which one estimates capacity relationships might not even exist under a regime that
generates incentives to optimize rents.
The potentially critical role of the skipper is another important issue that re-
duces the likely ability of even sophisticated micro-level capacity analysis to say
anything useful about which vessels ought to be removed. Many studies have shown
that much of the heterogeneity we see in fishing production functions is attributable
to the skipper rather than unobserved vessel characteristics (Hilborn and Ledbetter
1985; Squires and Kirkley 1999; Kirkley, Squires, and Strand 1998). If this is true,
the link between typical capacity analysis and ranking candidates for removal re-
quires more thinking. While there has been a considerable amount of high-quality
empirical effort aimed at understanding this link, there has been less work on the
policy implications of the findings. If the skippers’ skills are responsible for varia-
tions in efficiency, what are the implications for capacity reduction? Should we
remove the most productive skippers? Should (or is it even political or legally fea-
sible) they be required to permanently exit? How do we target those we think should
be removed (Vishwanathan et al. 2001)? Does the transferability of skills to tasks
outside the fishery matter to decommissioning? What about opportunity costs of
skippers?
Reflections
In summary, my opinion is that having simple aggregate measures of capacity at the
country- or fishery-specific level is worth a modest amount of effort and thought,
and it is likely to be of use to international, intra-governmental, and national regula-
tory agencies. Coming to some agreement over acceptable measures, and
recognizing strengths and weaknesses of various options, is worth some transactions
costs and research effort. Much of this conceptual work, comparison of methods,
and assessment of strengths and weaknesses has been done and is admirably summa-
rized in a series of reports and journal articles (Kirkley and Squires 1999;
Felthoven, Hyatt, and Terry 2002; Kirkley, Morrison-Paul, and Squires 2002;
Felthoven and Morrison-Paul 2004). Some of this work is finding its way into high-
level policy discussions of capacity and capacity management, as it should be.
However, I am more skeptical of economists’ ability to generate robust, micro-level,
vessel-specific capacity analysis that is useful for the task of identifying which ves-
sels ought to be decommissioned. Instead, it seems much more sensible to leave that
decision to the marketplace, with voluntary buyback auctions, etc. I am not con-
vinced that the simple production-function based analysis that underpins DEA and
other similar methods is rich enough to capture the subtle nuances of actual fisheries
production processes. Moreover, the typical data available are not rich enough or
even focused on the right variables to help lead the way to results that economists
would find unanimity over. At the same time, a useful outcome that has emerged out
of the surge of effort in capacity analysis is a push to develop better micro-level data
and micro-level analysis in fisheries management agencies.
When all is said and done, however, perhaps the biggest problem with focusing
so much effort on capacity analysis is that it distracts attention from the real prob-
lem, which is not excess capacity, but perverse incentives associated with insecureWilen 82
property rights. It is misleading to suggest that the existence of excessive fishing ca-
pacity is responsible for the degradation of fishery resources, because excess
capacity is a symptom and not a fundamental cause of the problem. Much of the
dithering that we have witnessed as fisheries have declined is arguably due to this
mistaken characterization, by fisheries scientists and policy makers, of the “fisheries
problem” (Wilen 2006). My own normative judgment is that economists who oper-
ate in and have access to the policy process should be hammering home the real
important message that we economists have to offer, and that is that all fisheries
problems are caused by insecure access rights, and we will make no headway in
solving global and regional problems until those problems are fixed. It does not ad-
vance the cause to buy into the false belief that we can fix the problem by removing
excess capacity. Past debacles have shown repeatedly that buybacks do not work, di-
rect capacity removal is ineffective and expensive, and it is impossible to engineer
optimal fleet configurations by command and control.
References
Felthoven, R., T. Hiatt, and J.M. Terry. 2002. Measuring Fishing Capacity and Utili-
zation Using Commonly Available Data: An Application to Alaska Fisheries.
Marine Fisheries Review Fall:29–39.
Felthoven, R., and C. Morrison-Paul. 2004. Multi-output, Nonfrontier Primal Mea-
sures of Capacity and Capacity Utilization. American Journal of Agricultural
Economics 86(3):619–33.
Greboval, D. 2000. The FOA International Plan of Action for the Management of
Fishing Capacity. Proceedings of the 10th Biennial Conference of the Institute of
Fisheries Economics and Trade, pp. 1–7. Corvallis, OR.
Hilborn, R., and M. Ledbetter. 1985. Determinants of Catching Power in the British
Columbia Purse Seine Fleet. Canadian Journal of Fisheries and Aquatic Sci-
ence 42(1):51–6.
Kirkley, J., C. Morrison-Paul, and D. Squires. 2002. Capacity and Capacity Utiliza-
tion in Fishing Industries: Definition, Measurement, and a Comparison of
Approaches. Environmental and Resource Economics 3:1–27.
Kirkley, J., and D. Squires. 1999. Measuring Capacity and Capacity Utilization in
Fisheries. Managing Fishing Capacity: Selected Papers on Underlying Con-
cepts and Issues, D. Greboval, ed. Rome: FAO.
Kirkley, J., D. Squires, and I. Strand. 1998. Characterizing Managerial Skill and
Technical Efficiency in a Fishery. Journal of Production Analysis 9:145–60.
Squires, D., and J. Kirkley. 1999. Skipper Skill and Panel Data in Fishing Industries.
Canadian Journal of Fisheries and Aquatic Science 56:2001–18.
Viswanathan, K.K., I.H. Omar, Y. Jeon, J. Kirkley, D. Squires, and I. Susilowati.
2001. Fishing Skill in Developing Country Fisheries: The Kedah, Malaysia
Trawl Fishery. Marine Resource Economics 16(4):293–314.
Wilen, J. 2006. Why Fisheries Management Fails: Treating Symptoms Rather than
Causes. Bulletin of Marine Science 78:529–46.

Capacity and Capacity Utilization in Fishing Industries: Definition, Measurement, and a Comparison of Approaches. Environmental and Resource Economics 3:1–27.

Characterizing Managerial Skill and Technical Efficiency in a Fishery.

Determinants of Catching Power in the British Columbia Purse Seine Fleet.

Fishing Skill in Developing Country Fisheries: The Kedah, Malaysia Trawl Fishery.

Measuring Capacity and Capacity Utilization in Fisheries. Managing Fishing Capacity: Selected Papers on Underlying Concepts and Issues,

Measuring Fishing Capacity and Utilization Using Commonly Available Data: An Application to Alaska Fisheries. Marine Fisheries Review Fall:29–39.

Multi-output, Nonfrontier Primal Measures of Capacity and Capacity Utilization.

Skipper Skill and Panel Data in Fishing Industries.

The FOA International Plan of Action for the Management of Fishing Capacity.

Why Fisheries Management Fails: Treating Symptoms Rather than Causes.

Thoughts on Capacity Analysis: Is Capacity Analysis Giving Policy Makers Information they Need?

Thoughts on Capacity Analysis: Is Capacity Analysis Giving Policy Makers Information they Need?

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