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Fishing rights and small communities: Alaska halibut IFQ transfer patterns
Ocean & Coastal Management 53 (2010) 518e523
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Ocean & Coastal Management journal homepage: www.elsevier.com/locate/ocecoaman
Fishing rights and small communities: Alaska halibut IFQ transfer patterns Courtney Carothers a, *, Daniel K. Lew b, c, 2, Jennifer Sepez b,1 a
School of Fisheries and Ocean Sciences, University of Alaska Fairbanks, 905 N. Koyukuk Drive, Fairbanks, AK 99775, USA Alaska Fisheries Science Center, National Marine Fisheries Service, F/AKC-2, 7600 Sand Point Way NE, Seattle, WA 98115, USA c Department of Environmental Science and Policy, University of California, One Shields Avenue, Davis, CA 95616, USA b
a r t i c l e i n f o
a b s t r a c t
Article history: Available online 28 April 2010
In the Alaska halibut individual fishing quota (IFQ) fishery, small remote fishing communities (SRFCs) have disproportionately lost fishing rights. Our analysis of quota market participation from 1995 to 1999 confirms that SRFC residents are more likely to sell than buy quota. Alaska Native heritage is another important predictor of quota market behavior. Residents of Alaska Native villages have an increased likelihood of selling quota. Loss of fisheries participation in small indigenous communities can be an unintended consequence of quota systems. Mitigation measures should take into account the social factors that can lead to such a redistribution of fishing rights in privatized access fisheries. Ó 2010 Elsevier Ltd. All rights reserved.
1. Introduction Fisheries management is increasingly framed in economic terms. An emerging prescription to the economic problem of fisheries (articulated in various ways, e.g., overfishing, race for fish, overcapitalization) is to remove excess labor and capital which dissipate resource rents through policies of enclosure. Restructuring fisheries management based on individual property rights and market-based allocation has been presented as so logical in fisheries management that it is often termed rationalization. Increasingly common, fisheries rationalization limits and commodifies the right to fish. Commodified fishing rights usually take the form of individual fishing or transferable quotas (IFQs or ITQs), or increasingly, catch shares, that allocate a certain percentage of an overall catch limit to individual or corporate quota holders. These rights are tradable to encourage economic efficiency and reduce overcapacity. While IFQ programs often achieve these stated economic goals, certain patterned social impacts (e.g., loss of jobs and bargaining power of crew and hired-captains, increased entry costs, and disproportionate losses of fishing rights from crewmembers, small vessels, and small communities) have made this type of fisheries management controversial [1e3]. In 1995, an IFQ program was implemented to manage the federal fixed gear commercial halibut and sablefish fisheries off
* Corresponding author. Tel.: þ1 907 474 5329; fax: þ1 907 474 7204. E-mail address: [email protected] (C. Carothers). 1 Tel.: þ1 206 526 6546; fax: þ1 206 526 6723. 2 Tel.: þ1 530 752 1746. 0964-5691/$ e see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.ocecoaman.2010.04.014
Alaska [4]. The IFQ program was designed to limit access to the fishery, reduce overcapacity, and address “conservation and management problems that are endemic to open access fisheries” [5, p. 23681]. Several restrictions were placed on quota share transfers to limit certain distributional outcomes of capacity reduction. To preserve the small-scale, owner-operator character of the halibut fishery, quota were linked to vessel size classes, limits were placed on corporate ownership and consolidation, and provisions requiring quota owners to be on board were established [6]. Despite these innovative regulations, transfers in the quota market have produced some unintended results. Notable among these is the disproportionate emigration of quota from small remote fishing communities in Alaska. In an attempt to redistribute quota share to these communities without altering the basic market-driven structure of transferability in the system, the North Pacific Fishery Management Council amended the IFQ program in June 2004 to enable small Gulf of Alaska communities with a documented history of participation in the halibut fishery to purchase quota collectively as communities. These communities are dependent on commercial fishing and thus are less likely to be resilient to economic change and may disproportionately absorb the negative impacts of redistribution under rationalized management system. To our knowledge, the Alaska halibut and sablefish fishery is the first tradable IFQ system to explicitly address community size as a factor in targeting mitigation of unintended socioeconomic impacts from IFQ-style management. Various claims and assumptions about effects of IFQ programs are often made without systematic testing. In this paper, we test whether the size of communities in which quota holders reside was
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a factor in the redistribution of halibut quota share in the Alaska fishery during the first several years of its implementation. Finding that it was, we examine communities of different sizes, and the buying and selling behavior of individual quota holders, to determine to what extent community size drives the unintended redistribution pattern. The data show it is only in the smallest communities (those with populations under 1500) that the pattern of quota loss is clearly evident. Residents of these communities are more likely to sell quota (and less likely to purchase quota) than residents of larger communities. Among the community characteristics that are likely drivers for the quota share emigration pattern observed, our analysis identifies Alaska Native cultural status as most significant. These findings support the claim that IFQ programs are likely to disproportionately impact smaller fishing communities and that this factor should be considered when predicting distributional impacts. They also suggest that community protection measures designed to mitigate the inequities of IFQ programs in Alaska and around the world may also wish to consider whether ethnic composition and cultural factors, in addition to community size, should serve as a guide for predicting likely impacts. 2. Data and definitions Using data collected and maintained by the National Marine Fisheries Service on halibut IFQ transactions and participants, we analyzed permanent halibut quota share transfers completed between 1995 and 19993 to assess whether halibut quota share is leaving small remote fishing communities (SRFCs) and evaluate the role SRFC residency plays in halibut quota share buying and selling behavior. Over the five-year study period, a total of 4817 permanent halibut quota share transfers were completed involving 2769 individual sellers and 2132 individual buyers. This paper limits the analysis to permanent transfers that involve a buyer and seller and does not include unusual transfers or leases.4 Beyond residency information, very little is known about the characteristics of buyers and sellers in the halibut IFQ market. The only individual-specific demographic information provided in the collected data is age. The mean age at the time of the transaction across all buyers, sellers, and years is 41.3 years. On average, buyers tend to be younger (39 years) than sellers (43.6 years). Income, gender, ethnicity, and other common demographic information are not collected from quota share transfers. We developed three operational definitions of small remote fishing communities (SRFCs) based on the following criteria: (a) population size, (b) designation as rural, (c) proximity to coastline, and (d) historical participation in the Alaska halibut fishery. In several recent policy discussions, these criteria were determined to be most relevant to defining SRFCs that have demonstrated quota share loss. Although there is uncertainty surrounding which maximum population size should delimit a “small community” in Alaska, three population sizes of 1500, 2500, and 7500 are commonly discussed [7,8]. We use these thresholds to create three SRFC groupings: small SRFCs (populations under 1500), medium SRFCs (populations between 1501 and 2500) and large SRFCs (populations between 2501 and 7501). In each of the size groupings, the same qualifying criteria are used to determine rural status (U.S.
3 More recent quota share transfer data are available, but inconsistencies prevented us from analyzing these data here. 4 Individual transfer participants that did not provide residency information were excluded (N ¼ 34). Four types of non-buying/non-selling transfers were excluded: leases of initial quota share (N ¼ 226), quota block sweep-ups (N ¼ 757), transfers resulting from financial rulings (N ¼ 36), and transfers to surviving heirs (N ¼ 26).
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Table 1 Small remote fishing communities. Type of SRFC
Communities
Small SRFC
Akhiok, Akutan, Angoon, Atka, Chenega Bay, Chignik, Chignik Lagoon, Coffman Cove, Craig, Edna Bay, Elfin Cove, False Pass, Gustavus, Halibut Cove, Hoonah, Hydaburg, Hyder, Ivanof Bay,a Kake, Kasilof, King Cove, Klawock, Larsen Bay, Mekoryuk, Metlakatla, Meyers Chuck, Naknek, Nanwalek,a Naukati Bay, Nikolaevsk, Ninilchik, Old Harbor, Ouzinkie, Pelican, Perryville, Point Baker, Port Alexander, Port Graham, Port Lions, Port Protection,a Saint George Island, Saint Paul Island, Sand Point, Seldovia, Skagway, South Naknek, Tatitlek, Tenakee Springs, Thorne Bay, Toksook Bay, Tununak, Whale Pass, Whittier, Yakutat Cordova, Dillingham, Haines, Wrangell Kodiak, Petersburg, Unalaska
Medium SRFC Large SRFC
a Communities that have neither buying nor selling transactions during the study period.
Federal Subsistence Board declarations), proximity to the Alaska coastline (less than 10 miles), and historical fishing participation (at least one resident received an initial halibut quota share). For every community in Alaska, population estimates were compiled from Census data5 and distances from the Alaska coastline were calculated using GIS software. Population estimates based on the 1990 Census were used to be consistent with the current Federal Subsistence Board (FSB) lists of rural and urban areas at the time of analysis. Alaska communities with residents who received an initial allocation of halibut quota share were also identified. Using this information, a list of small SRFCs (54 communities), medium SRFCs (4 communities), and large SRFCs (3 communities) was generated (see Table 1). 3. Overall quota share trends from 1995 to 1999 The flow of quota into and out of communities is determined by both quota share buying and selling patterns and owner migration. The net gains and losses of quota share reported here only reflect the results of the quota share market, not the migration of owners. On average, buyers from larger SRFCs engaged in more buying transactions involving more quota share compared to those from smaller SRFCs. Residents of non-SRFCs in Alaska and communities outside of Alaska also had more average buying transactions for more average quota share than residents of small and medium SRFCs. Sellers from communities outside of Alaska had the largest number of selling transactions per seller. The average amount of quota sold by non-Alaskan sellers was about double the amount sold on average by sellers from small SRFCs (Tables 2 and 3). Quota share migration was assessed by examining the net flow of quota share into and out of these communities via sales transactions (again, as opposed to quota owner migration). Figure 1 shows the net change in halibut quota share by year for each of the three SRFC groups, non-SRFC Alaska communities, and communities outside Alaska. Among SRFCs, the trend towards quota share emigration from the smallest communities is most pronounced. These SRFCs consistently experienced a net loss of quota share in each of the years under investigation. The net flow of quota share out of these communities by transfer sale is greatest in 1996, the second full year of the IFQ program. In total, over 5.5 million quota share units of halibut (approximately 10% of annual catch limits) were transferred out of small SRFCs between 1995 and 1999.
5 We include only those communities that meet U.S. Census criteria for “place” or “census-designated place.”
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Table 2 Buyers and buy transactions. Community type
Small SRFC Medium SRFC Large SRFC Non-SRFC in Alaska Outside Alaska
No. buyers
No. transactions per buyer
Quota share per transaction (in quota share units)
Mean
Std. dev.
Min
Max
Mean
Std. dev.
Min
Max
283 157 388 827 459
1.72 1.85 2.32 2.14 2.94
2.72 2.69 2.84 2.52 6.11
1 1 1 1 1
35 30 33 33 83
24,316 31,105 45,747 33,430 40,079
28,322 47,811 63,925 42,609 61,230
56 44 10 18 10
251,063 423,365 762,603 371,640 760,699
No. sellers
No. transactions per seller
Table 3 Sellers and sell transactions. Community type
Small SRFC Medium SRFC Large SRFC Non-SRFC in Alaska Outside Alaska
497 153 400 1008 669
Quota share per transaction (in quota share units)
Mean
Std. dev.
Min
Max
Mean
Std. dev.
Min
Max
1.70 1.25 1.69 1.62 2.14
1.18 0.757 1.23 1.70 3.43
1 1 1 1 1
9 7 9 33 59
20,942 27,310 48,913 35,571 42,313
29,390 34,100 67,775 45,430 60,963
10 60 78 23 10
251,063 298,912 762,603 371,640 760,999
Table 4 Percent of total quota share transacted between communities. Buy community
Small SRFC Medium SRFC Large SRFC Other Alaska (non-SRFC) Outside Alaska Total
Sell community Small SRFC
Medium SRFC
Large SRFC
Other Alaska (non-SRFC)
Outside Alaska
Total
4.88% 1.01% 2.60% 4.42% 4.84% 17.75%
0.25% 2.14% 0.34% 0.80% 0.50% 4.02%
0.65% 0.29% 8.02% 2.74% 2.43% 14.14%
2.20% 1.40% 3.54% 21.22% 5.70% 34.07%
2.22% 1.24% 4.32% 7.54% 14.71% 30.02%
10.20% 6.08% 18.81% 36.73% 28.18% 100.00%
This quota emigration trend is not shared by the larger SRFCs, which as a group saw an overall net gain of quota share from the quota share market over the period. Medium SRFCs saw a positive balance of transfers each year of the study period. The group of large SRFCs experienced the largest gains in quota share, with a net gain of over 8 million quota share units of halibut, almost entirely due to an influx of purchased quota share by residents of Petersburg (4.5 million quota share units) and Kodiak (3.6 million quota share units). The other community classified as a large SRFC, Unalaska, saw a small net loss of quota share over the study period. In contrast to conventional wisdom, we found that communities outside of Alaska sold more quota share than they purchased each year between 1995 and 1999, totaling a loss of over 6.7 million units of quota share. Most of the quota share emigration from communities
outside of Alaska occurred in 1995 and 1996, the first two full years of the IFQ program, which is consistent with the significant restructuring of the fishery that occurred immediately following implementation of the IFQ program as less profitable fishermen exited the fishery. Table 4 lists the percent of total quota share transacted between each type of community over the study period. The largest percentages of quota share transacted were sold internally between non-SRFCs (21% of the total) and between communities outside Alaska (about 15% of the total). For transactions between residents of different community types, one trend clearly stands out. Residents of small SRFCs clearly sell more than they buy from all other community types over the period. Overall, residents of small SRFCs sold 74% more quota share than they purchased and sold more than they purchased from each of the other types of communities.
4. SRFC residency and quota share market behavior
Fig. 1. Net quota share changes by community type from 1995 to 1999.
The trends discussed above suggest residency plays a role in quota share market behavior. In this section, we explore to what extent SRFC residency affects the decision to buy or sell quota share using a logit statistical model to systematically investigate the differences between Alaska buyers and sellers. We focus on identifying whether residency in small remote fishing communities influences quota share market behavior separately from individualspecific characteristics and from other community effects. Specifically, we wish to control for individual age effects, community population size effects, and specific year (time) effects. The analysis is restricted to Alaska buyers and sellers since only Alaska communities are defined as SRFCs and our intent is to control, to the extent possible given data limitations, other factors that may influence the decision to buy or sell quota share.
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An individual’s decision to buy or sell quota share is assumed to depend upon the attributes of the individual.6 The data upon which this analysis is based are limited to the individual-specific information collected, which is age and residency information. Age may play a significant role in determining whether a person buys or sells quota. Younger persons are more likely to participate in the fishery and purchase halibut quota for that purpose or as an investment. Yet, younger individuals often have less access to capital to purchase quota share compared with older individuals. Older individuals may wish to sell quota because they no longer wish or are able to participate in the fishery, or wish to liquidate their holdings for retirement or other opportunities. To incorporate the role of age in the buy-sell decision, individuals who buy or sell in different years are treated as separate observations. This allows us to control for the effect of age on these decisions. Data are pooled over the five-year study period. The resulting dataset has 4639 cases. Where an individual lives may also play a role in the decision to buy or sell. Residency may be a proxy for other unobserved factors that influence quota purchases or sales. For instance, in communities with strong fishing traditions, there may be pressure to retain or obtain halibut quota to maintain traditional practices. Other socioeconomic factors likely affect quota share market participation. In low-income communities, the need for readily available cash gained by quota share sale is likely to be greater than in more affluent communities. Limited access to capital also decreases the likelihood of purchasing quota. Many of the smallest SRFCs in Alaska are predominantly Alaska Native communities, with cultural and economic characteristics that affect residents’ quota buying and selling behavior. To investigate the relative importance of SRFC residency on buying and selling decisions while controlling for other individual characteristics, we assume the probability of selling (Pr[sell]) and probability of buying (Pr[buy] ¼ 1 Pr[sell]) depend upon the individual’s age, the population size of the individual’s community, and whether or not the individual lives in an SRFC. Population size is included to account for population effects that are independent of SRFC residency. The deterministic portion of Pr[sell] is specified as a linearly additive function with the following covariates: the individual’s age (in years) and age squared, the population size of the individual’s community (in 10,000s) and population size squared, a cross-effect term to capture interactions between population size and age, and dummy variables that indicate whether or not an individual lives in a small SRFC, medium-sized SRFC, or large SRFC. To capture time effects, dummy variables that represent each of the first four years of the program are also included. The logit estimation results for this SRFC-based model are presented in Table 5. Overall, the parameter values are as expected and indicate that an individual’s age, the size of the individual’s community, and SRFC residency are statistically significant explainers of the difference between Alaska buyers and sellers. Also listed in Table 5 are the marginal effects of these explanatory variables (calculated as a mean over the sample), which measure the effect on the probability of selling (Pr[sell]) with a one unit
6 Transaction-specific variables, such as the price paid, amount of quota share transacted, and other market condition information (e.g., expectations of stock abundance, other economic opportunities), are excluded from the analysis. Since the model looks for differences between buyers and sellers and the data consists of information on both the seller and buyer in each transaction, estimation of the effect of transaction-specific variables on probabilities of buying and selling is precluded. As a result, the analysis is confined to variables that are specific to individuals. Estimation of formal economic models of quota share demand and supply are beyond the scope of the present analysis. For an analysis of this type, see [9].
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Table 5 Small remote fishing community-based logit results and marginal effects on probability of selling quota share. Parameter
Estimate
Constant Age Age squared Small SRFC dummy Medium SRFC dummy Large SRFC dummy Population size Population size squared Population size age 1995 year dummy 1996 year dummy 1997 year dummy 1998 year dummy Maximized log-likelihood value LR test statistic for overall significance
0.6573** (3.117) 0.003886 (0.4765) 0.0004311** (4.311) 0.3427** (3.556) 0.3457** (2.829) 0.1791** (2.177) 0.05531 (1.0575) 0.003851** (2.029) 0.001181** (4.055) 0.1153 (1.131) 0.1926* (1.912) 0.1430 (1.318) 0.08210 (0.6599) 3075.17
Marginal effect on Pr[sell] 0.006930** 0.08056** 0.08218** 0.04273** 0.02043**
0.02720 0.04538* 0.03372 0.01937
280.69
For parameter estimates, asymptotic t-values are in parentheses. * and ** denote statistical significance at the 10% and 5% levels, respectively. The marginal effect of a variable is the change in the Pr[sell] with a one unit change in the variable holding all other things constant. Reported marginal effects are calculated as means over the sample. Significance of a marginal effect is based on whether the simulated confidence interval includes zero or not. Sample size is 4639.
change in the variable of interest (or the presence or absence of a characteristic in the case of a dummy variable). These results suggest one is more likely to sell as one gets older and also when one is from a larger community, all else being the same.7 The only significant time effect indicates that in 1996, the second year of the program, one was more likely to sell than buy, which may be indicative of Alaska quota share holders selling small-quantity quota share holdings during the initial years of the program. Even when age effects of the individual, population size effects of the individual’s community, and time effects are accounted for, there are still differences between buyers and sellers attributable to residency in small, medium, and large SRFCs. The effects appear to go in opposite directions for residents of small versus medium or large SRFCs, which reinforce the idea that quota share emigration trends are likely sensitive to how one defines SRFCs. Moreover, the SRFC residency effects on the probability of selling halibut quota share appear to be significant, and are roughly an order of magnitude greater than the effects due to age. 5. Characteristics of SRFCs and quota share market behavior In the previous section, the SRFC-based logit statistical model was used to identify whether residency in an SRFC could help explain the differences between buyers and sellers of quota share in the halibut quota share market while controlling for several other factors.8 In this section, we step away from the SRFC construct to identify the characteristics of SRFCs that may help explain why residency in these communities makes a difference in quota share market behavior. To do this, we explicitly incorporate several of the criteria used to develop our SRFC definitions, as well as additional community data, into the logit specification. Thus, the community characteristics-based logit model is identical to the SRFC-based
7 The population size effect is not surprising given that the population size effects of SRFCs are already accounted for in the coefficients for those variables. 8 It does not account for economic factors related to quota share market and fishery conditions. Demographic information, such as gender, ethnicity, and income, would be valuable to include, but such data were not collected, or generally available, from individual market participants.
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logit model except there are no SRFC dummy variables, and in their place are additional community variables (dummy variables for whether the community is considered rural, for communities within 10 miles of the coast, and for whether any residents of the community received an initial quota share issuance).9 In addition to community characteristics that were used to construct the SRFC definitions, other community factors that are correlated with these communities could possibly explain why residency in SRFCs are indicative of market behavior. Among these factors, one stands out as especially important: Alaska Native heritage. Many of the small SRFCs identified here are Alaska Native communities. Forty-eight percent of small SRFCs have a majority of Alaska Native residents (26 communities), 55% have a quarter or more (30 communities), and 67% have at least 10% or more of the population that identifies as Alaska Native (36 communities). On average, about 42% of the populations of small SRFCs identify as Alaska Native (median ¼ 43%), compared to 20% of other non-small SRFC Alaskan communities (median ¼ 5.7%). Only seven non-small SRFC Alaskan communities included in this analysis have a majority of residents that identify as Alaska Native. Some analysts predicted that Alaska Native villages would be differentially impacted by the implementation of the IFQ program [10]. The limitation and commoditization of fishing access rights began on a large scale in Alaska with the limited entry management of salmon in the 1970s. While keeping fishing rights in Alaska was a motivating factor for limiting entry [11], analyses show a migration trend of salmon permits away from rural Native villages in Alaska [12e14]. A complex set of historical, cultural, socioeconomic, and geographic characteristics of Alaska Native villages is believed to drive this trend [3]. Data on the ethnicity of individual transfer participants is not collected. To account for this factor in the community characteristics-based model, we include in the specification the percentage of the individual’s community that identifies as Alaska Native drawn from US Census data. The results of the community characteristics-based logit model are summarized in Table 6. Without the different-sized SRFCs represented in the model, the population size marginal effect reversesdresidents of smaller Alaska communities are more likely to sell than buy. Age effects are similar to the SRFC-based logit model, and time effects are not significant. Among the community characteristics that are used to define an SRFC, only rural classification appears to have an effect in explaining differences between buyers and sellers. Individuals from communities classified as rural are less likely to sell than buy holding everything else constant.10 Interestingly, proximity to the coast and whether the community was originally issued quota share do not appear to be significant factors that distinguish buyers and sellers. However, individuals from communities with larger percentages of Alaska Native residents are more likely to sell than buy, which provides evidence for why quota holders in small SRFCs, which have high percentages of Alaska Native residents, tended to sell more quota share than they buy.
6. Discussion Fishery managers and analysts have recognized the problem of net transfer of Alaska halibut quota shares out of small remote fishing communities. Our analysis of the data between 1995 and
9 Models with population size thresholds were estimated, but because of the correlation with the continuous population size variable, population size was modeled in its continuous form in the models presented. 10 In the absence of SRFC dummies, this should not be too surprising given the large number of rural communities in Alaska that are non-SRFCs.
Table 6 Community criteria-based logit results and marginal effects on probability of selling quota share. Parameter
Estimate
Constant Age Age squared Population size Population size squared Population size Age Alaska Native Percentage Initial quota share dummy Distance (within 10 miles of coast) dummy Rural community dummy 1995 year dummy 1996 year dummy 1997 year dummy 1998 year dummy Maximized log-likelihood value LR test statistic for overall significance
1.934** (2.225) 0.003533 (0.4341) 0.006763** 0.0004208** (4.218) 0.09416* (1.874) 0.02754** 0.005312** (2.935) 0.001164** (4.001) 0.01538** (8.322) 0.003595** 1.377 (1.604) 0.2900 0.09808 (0.6520) 0.02287 0.2678** (3.469) 0.09140 (0.8933) 0.1538 (1.519) 0.1215 (1.119) 0.06616 (0.5309) 3056.34 318.34
Marginal effect on Pr[sell]
0.06218** 0.02138 0.03597 0.02842 0.01548
For parameter estimates, asymptotic t-values are in parentheses. * and ** denote statistical significance at the 10% and 5% levels, respectively. The marginal effect of a variable is the change in the Pr[sell] with a one unit change in the variable. Reported marginal effects are calculated as means over the sample. Significance of a marginal effect is based on whether the simulated confidence interval includes 0 or not. Sample size is 4639.
1999 confirms that this concern is based on genuine quota losses from these communities and offers statistically-based evidence that the size of SRFCs matters. These results also indicate that in addition to small community size, Alaska Native cultural affiliation is an important factor that is linked to quota share market behavior. Reducing the number of participants in a fishery by a marketbased system which allows those that exit to receive a pay-out funded by remaining or entering participants seems an obvious improvement over chaotic one-day fishing seasons or governmentfunded buybacks. Individuals are compensated for their exit without burdening taxpayers, while those who remain in the fishery have a longer season and a better potential earning outlook. But, to the extent that these exiters are disproportionately located in small communities or indigenous communities, social and economic impacts (including negative multiplier effects) will be differentially concentrated. So the consequence of solving one collective action problem (too many participants in a fishery) creates another (disproportionate quota loss from small or indigenous communities). Recognizing that the transferability of halibut and sablefish quota was creating distributional inequities, the North Pacific Fishery Management Council (hereafter, the Council) implemented the “Community Purchase Program” for 42 fishing communities in the Gulf of Alaska. The Council set the population threshold for eligibility at 1500 (along with other criteria). The program communities align fairly closely to the small SRFCs discussed in this paper.11 Our analysis suggests the Council targeted the appropriately-sized Gulf of Alaska communities by limiting the new program to the smallest of the SRFCs. Developing models of community-based ownership of fishing quota may be a primary
11 Several communities (Chignik Lake, Hollis, Karluk, Kasaan, and Tyonek,) are part of the Community Purchase Program, but are not classified as small SRFCs. These communities did not have residents that received an initial halibut quota share allocation and therefore did not meet our criteria for SRFC inclusion. In addition, there are seventeen communities that are classified as small SRFCs that are not eligible for the Community Purchase Program. This program was restricted to Gulf of Alaska communities and communities that are not linked to larger communities via a highway network.
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solution to addressing the kinds of quota share emigration trends described in this paper [3,15]. The findings presented in this paper contribute to an understanding of a broader range of distributive impacts of fisheries access privatization around the globe. The Council imposed restrictions on halibut quota market trading to limit extensive consolidation and corporate ownership witnessed in some other IFQ fisheries; however, the emigration of quota from SRFCs, while unintended, was a predictable outcome of the limitation and commoditization of halibut fishing rights. Often for a suite of reasons, fishermen residing in small remote communities are among the most “inefficient” harvesters. Many fishermen in SRFCs have exited halibut fishing. As the privatization of fisheries access continues to gain favor in an international context, a diverse range of fisheries in various social contexts will become restructured to provide for increased economic efficiencies. Analyzing the overall distribution of fishing rights (both initially and as a result of market trading) is a key piece to understanding the social impacts of privatized access fishing on communities of people and place. Particularly when the stated goals of privatized access policies are to encourage efficiency and reduce overcapitalization it is critical to predict the impacts of “inefficient exiters.” To the extent that these exiters are disproportionately located in small, remote fishing communities (in this particular case, indigenous communities), a wider set of socioeconomic and cultural issues surface as managers and analysts debate the benefits and costs of implementing such programs. Acknowledgements The authors would like to thank Jessica Gharrett at the National Marine Fisheries Service for her patience and responsiveness with our many questions and data inquiries, Susan Abbott-Jamieson for early support of this research, Dave Colpo at the Pacific States Marine Fisheries Commission, Eugene Hunn at the University of Washington, and Angie Grieg of the Alaska Fisheries Science Center for her assistance with GIS. We also thank Ron Felthoven (AFSC), Nicole Kimball (NPFMC), Suzanne Russell (NWFSC), and participants at the 2006 IIFET meetings for providing useful comments
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that have improved this paper. All potential errors are our own. The opinions expressed in this article are those of the authors and do not necessarily reflect those of the National Marine Fisheries Service. References [1] National Research Council. Sharing the fish: toward a national policy on individual fishing quotas. Washington, D.C.: National Academy Press; 1999. 422 pp. [2] McCay B. ITQs and community: an essay on environmental governance. Agricultural and Resource Economics Review 2004;33(2):162e70. [3] Lowe, M, Carothers C, editors. Enclosing the fisheries: people, places and power. Symposium 68. Bethesda, Maryland: American Fisheries Society Press; 2008. [4] US Department of Commerce, National Oceanic and Atmospheric Administration. Limited access management of fisheries of Alaska, final rule. Federal Register 58(215):59,375e413. [5] US Department of Commerce, National Oceanic and Atmospheric Administration. Community purchase, final rule. Federal Register 69(84):23,681e94. [6] Dawson R. Vertical integration in the post-IFQ halibut fishery. Marine Policy 2006;30(4):341e6. [7] Gulf of Alaska rationalization introductory paper. Anchorage, AK: North Pacific Fisheries Management Council. Available from:; 2004 [accessed 3/11/2006]. [8] North Pacific Fishery Management Council. Gulf of Alaska community provisions. Anchorage, AK: NPFMC. Available from: ; 2005 [accessed 02/13/2006]. [9] Newell R, Sanchirico J, Kerr S. Fishing quota markets. Journal of Environmental Economics and Management 2005;49:437e62. [10] Langdon S. Communities and quota: alternatives in North Pacific fisheries. Pacific States Marine Fisheries Commission, Semiahmoo, WA, Unpublished; 1999. [11] Homan F. Limited entry in Alaska’s commercial fisheries. In: Cullenberg P, editor. Alaska’s fishing communities: harvesting the future. Fairbanks: Alaska Sea Grant; 2007. p. 31e4. [12] Langdon S. Transfer patterns in Alaskan limited entry fisheries. Final report prepared for the Limited Entry Study Group of the Alaska State Legislature, Juneau, AK; 1980. 153 pp. [13] Kamali N. Alaska natives and limited fisheries of Alaska: a study of changes in the distribution of permit ownership amongst Alaska Natives, 1975e1983. Report 84-8. Juneau: Alaska Commercial Fisheries Entry Commission; 1984. [14] Tide C, Free-Sloan N, Iverson K. Changes in the distribution of Alaska’s commercial fisheries entry permits, 1975 to 2003. Report 04-IN-EXEC. Juneau: Alaska Commercial Fisheries Entry Commission; 2004. [15] Wingard JD. Community transferable quotas: internalizing externalities and minimizing social impacts of fisheries management. Human Organization 2000;59(1):48e57.
Contents lists available at ScienceDirect
Ocean & Coastal Management journal homepage: www.elsevier.com/locate/ocecoaman
Fishing rights and small communities: Alaska halibut IFQ transfer patterns Courtney Carothers a, *, Daniel K. Lew b, c, 2, Jennifer Sepez b,1 a
School of Fisheries and Ocean Sciences, University of Alaska Fairbanks, 905 N. Koyukuk Drive, Fairbanks, AK 99775, USA Alaska Fisheries Science Center, National Marine Fisheries Service, F/AKC-2, 7600 Sand Point Way NE, Seattle, WA 98115, USA c Department of Environmental Science and Policy, University of California, One Shields Avenue, Davis, CA 95616, USA b
a r t i c l e i n f o
a b s t r a c t
Article history: Available online 28 April 2010
In the Alaska halibut individual fishing quota (IFQ) fishery, small remote fishing communities (SRFCs) have disproportionately lost fishing rights. Our analysis of quota market participation from 1995 to 1999 confirms that SRFC residents are more likely to sell than buy quota. Alaska Native heritage is another important predictor of quota market behavior. Residents of Alaska Native villages have an increased likelihood of selling quota. Loss of fisheries participation in small indigenous communities can be an unintended consequence of quota systems. Mitigation measures should take into account the social factors that can lead to such a redistribution of fishing rights in privatized access fisheries. Ó 2010 Elsevier Ltd. All rights reserved.
1. Introduction Fisheries management is increasingly framed in economic terms. An emerging prescription to the economic problem of fisheries (articulated in various ways, e.g., overfishing, race for fish, overcapitalization) is to remove excess labor and capital which dissipate resource rents through policies of enclosure. Restructuring fisheries management based on individual property rights and market-based allocation has been presented as so logical in fisheries management that it is often termed rationalization. Increasingly common, fisheries rationalization limits and commodifies the right to fish. Commodified fishing rights usually take the form of individual fishing or transferable quotas (IFQs or ITQs), or increasingly, catch shares, that allocate a certain percentage of an overall catch limit to individual or corporate quota holders. These rights are tradable to encourage economic efficiency and reduce overcapacity. While IFQ programs often achieve these stated economic goals, certain patterned social impacts (e.g., loss of jobs and bargaining power of crew and hired-captains, increased entry costs, and disproportionate losses of fishing rights from crewmembers, small vessels, and small communities) have made this type of fisheries management controversial [1e3]. In 1995, an IFQ program was implemented to manage the federal fixed gear commercial halibut and sablefish fisheries off
* Corresponding author. Tel.: þ1 907 474 5329; fax: þ1 907 474 7204. E-mail address: [email protected] (C. Carothers). 1 Tel.: þ1 206 526 6546; fax: þ1 206 526 6723. 2 Tel.: þ1 530 752 1746. 0964-5691/$ e see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.ocecoaman.2010.04.014
Alaska [4]. The IFQ program was designed to limit access to the fishery, reduce overcapacity, and address “conservation and management problems that are endemic to open access fisheries” [5, p. 23681]. Several restrictions were placed on quota share transfers to limit certain distributional outcomes of capacity reduction. To preserve the small-scale, owner-operator character of the halibut fishery, quota were linked to vessel size classes, limits were placed on corporate ownership and consolidation, and provisions requiring quota owners to be on board were established [6]. Despite these innovative regulations, transfers in the quota market have produced some unintended results. Notable among these is the disproportionate emigration of quota from small remote fishing communities in Alaska. In an attempt to redistribute quota share to these communities without altering the basic market-driven structure of transferability in the system, the North Pacific Fishery Management Council amended the IFQ program in June 2004 to enable small Gulf of Alaska communities with a documented history of participation in the halibut fishery to purchase quota collectively as communities. These communities are dependent on commercial fishing and thus are less likely to be resilient to economic change and may disproportionately absorb the negative impacts of redistribution under rationalized management system. To our knowledge, the Alaska halibut and sablefish fishery is the first tradable IFQ system to explicitly address community size as a factor in targeting mitigation of unintended socioeconomic impacts from IFQ-style management. Various claims and assumptions about effects of IFQ programs are often made without systematic testing. In this paper, we test whether the size of communities in which quota holders reside was
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a factor in the redistribution of halibut quota share in the Alaska fishery during the first several years of its implementation. Finding that it was, we examine communities of different sizes, and the buying and selling behavior of individual quota holders, to determine to what extent community size drives the unintended redistribution pattern. The data show it is only in the smallest communities (those with populations under 1500) that the pattern of quota loss is clearly evident. Residents of these communities are more likely to sell quota (and less likely to purchase quota) than residents of larger communities. Among the community characteristics that are likely drivers for the quota share emigration pattern observed, our analysis identifies Alaska Native cultural status as most significant. These findings support the claim that IFQ programs are likely to disproportionately impact smaller fishing communities and that this factor should be considered when predicting distributional impacts. They also suggest that community protection measures designed to mitigate the inequities of IFQ programs in Alaska and around the world may also wish to consider whether ethnic composition and cultural factors, in addition to community size, should serve as a guide for predicting likely impacts. 2. Data and definitions Using data collected and maintained by the National Marine Fisheries Service on halibut IFQ transactions and participants, we analyzed permanent halibut quota share transfers completed between 1995 and 19993 to assess whether halibut quota share is leaving small remote fishing communities (SRFCs) and evaluate the role SRFC residency plays in halibut quota share buying and selling behavior. Over the five-year study period, a total of 4817 permanent halibut quota share transfers were completed involving 2769 individual sellers and 2132 individual buyers. This paper limits the analysis to permanent transfers that involve a buyer and seller and does not include unusual transfers or leases.4 Beyond residency information, very little is known about the characteristics of buyers and sellers in the halibut IFQ market. The only individual-specific demographic information provided in the collected data is age. The mean age at the time of the transaction across all buyers, sellers, and years is 41.3 years. On average, buyers tend to be younger (39 years) than sellers (43.6 years). Income, gender, ethnicity, and other common demographic information are not collected from quota share transfers. We developed three operational definitions of small remote fishing communities (SRFCs) based on the following criteria: (a) population size, (b) designation as rural, (c) proximity to coastline, and (d) historical participation in the Alaska halibut fishery. In several recent policy discussions, these criteria were determined to be most relevant to defining SRFCs that have demonstrated quota share loss. Although there is uncertainty surrounding which maximum population size should delimit a “small community” in Alaska, three population sizes of 1500, 2500, and 7500 are commonly discussed [7,8]. We use these thresholds to create three SRFC groupings: small SRFCs (populations under 1500), medium SRFCs (populations between 1501 and 2500) and large SRFCs (populations between 2501 and 7501). In each of the size groupings, the same qualifying criteria are used to determine rural status (U.S.
3 More recent quota share transfer data are available, but inconsistencies prevented us from analyzing these data here. 4 Individual transfer participants that did not provide residency information were excluded (N ¼ 34). Four types of non-buying/non-selling transfers were excluded: leases of initial quota share (N ¼ 226), quota block sweep-ups (N ¼ 757), transfers resulting from financial rulings (N ¼ 36), and transfers to surviving heirs (N ¼ 26).
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Table 1 Small remote fishing communities. Type of SRFC
Communities
Small SRFC
Akhiok, Akutan, Angoon, Atka, Chenega Bay, Chignik, Chignik Lagoon, Coffman Cove, Craig, Edna Bay, Elfin Cove, False Pass, Gustavus, Halibut Cove, Hoonah, Hydaburg, Hyder, Ivanof Bay,a Kake, Kasilof, King Cove, Klawock, Larsen Bay, Mekoryuk, Metlakatla, Meyers Chuck, Naknek, Nanwalek,a Naukati Bay, Nikolaevsk, Ninilchik, Old Harbor, Ouzinkie, Pelican, Perryville, Point Baker, Port Alexander, Port Graham, Port Lions, Port Protection,a Saint George Island, Saint Paul Island, Sand Point, Seldovia, Skagway, South Naknek, Tatitlek, Tenakee Springs, Thorne Bay, Toksook Bay, Tununak, Whale Pass, Whittier, Yakutat Cordova, Dillingham, Haines, Wrangell Kodiak, Petersburg, Unalaska
Medium SRFC Large SRFC
a Communities that have neither buying nor selling transactions during the study period.
Federal Subsistence Board declarations), proximity to the Alaska coastline (less than 10 miles), and historical fishing participation (at least one resident received an initial halibut quota share). For every community in Alaska, population estimates were compiled from Census data5 and distances from the Alaska coastline were calculated using GIS software. Population estimates based on the 1990 Census were used to be consistent with the current Federal Subsistence Board (FSB) lists of rural and urban areas at the time of analysis. Alaska communities with residents who received an initial allocation of halibut quota share were also identified. Using this information, a list of small SRFCs (54 communities), medium SRFCs (4 communities), and large SRFCs (3 communities) was generated (see Table 1). 3. Overall quota share trends from 1995 to 1999 The flow of quota into and out of communities is determined by both quota share buying and selling patterns and owner migration. The net gains and losses of quota share reported here only reflect the results of the quota share market, not the migration of owners. On average, buyers from larger SRFCs engaged in more buying transactions involving more quota share compared to those from smaller SRFCs. Residents of non-SRFCs in Alaska and communities outside of Alaska also had more average buying transactions for more average quota share than residents of small and medium SRFCs. Sellers from communities outside of Alaska had the largest number of selling transactions per seller. The average amount of quota sold by non-Alaskan sellers was about double the amount sold on average by sellers from small SRFCs (Tables 2 and 3). Quota share migration was assessed by examining the net flow of quota share into and out of these communities via sales transactions (again, as opposed to quota owner migration). Figure 1 shows the net change in halibut quota share by year for each of the three SRFC groups, non-SRFC Alaska communities, and communities outside Alaska. Among SRFCs, the trend towards quota share emigration from the smallest communities is most pronounced. These SRFCs consistently experienced a net loss of quota share in each of the years under investigation. The net flow of quota share out of these communities by transfer sale is greatest in 1996, the second full year of the IFQ program. In total, over 5.5 million quota share units of halibut (approximately 10% of annual catch limits) were transferred out of small SRFCs between 1995 and 1999.
5 We include only those communities that meet U.S. Census criteria for “place” or “census-designated place.”
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Table 2 Buyers and buy transactions. Community type
Small SRFC Medium SRFC Large SRFC Non-SRFC in Alaska Outside Alaska
No. buyers
No. transactions per buyer
Quota share per transaction (in quota share units)
Mean
Std. dev.
Min
Max
Mean
Std. dev.
Min
Max
283 157 388 827 459
1.72 1.85 2.32 2.14 2.94
2.72 2.69 2.84 2.52 6.11
1 1 1 1 1
35 30 33 33 83
24,316 31,105 45,747 33,430 40,079
28,322 47,811 63,925 42,609 61,230
56 44 10 18 10
251,063 423,365 762,603 371,640 760,699
No. sellers
No. transactions per seller
Table 3 Sellers and sell transactions. Community type
Small SRFC Medium SRFC Large SRFC Non-SRFC in Alaska Outside Alaska
497 153 400 1008 669
Quota share per transaction (in quota share units)
Mean
Std. dev.
Min
Max
Mean
Std. dev.
Min
Max
1.70 1.25 1.69 1.62 2.14
1.18 0.757 1.23 1.70 3.43
1 1 1 1 1
9 7 9 33 59
20,942 27,310 48,913 35,571 42,313
29,390 34,100 67,775 45,430 60,963
10 60 78 23 10
251,063 298,912 762,603 371,640 760,999
Table 4 Percent of total quota share transacted between communities. Buy community
Small SRFC Medium SRFC Large SRFC Other Alaska (non-SRFC) Outside Alaska Total
Sell community Small SRFC
Medium SRFC
Large SRFC
Other Alaska (non-SRFC)
Outside Alaska
Total
4.88% 1.01% 2.60% 4.42% 4.84% 17.75%
0.25% 2.14% 0.34% 0.80% 0.50% 4.02%
0.65% 0.29% 8.02% 2.74% 2.43% 14.14%
2.20% 1.40% 3.54% 21.22% 5.70% 34.07%
2.22% 1.24% 4.32% 7.54% 14.71% 30.02%
10.20% 6.08% 18.81% 36.73% 28.18% 100.00%
This quota emigration trend is not shared by the larger SRFCs, which as a group saw an overall net gain of quota share from the quota share market over the period. Medium SRFCs saw a positive balance of transfers each year of the study period. The group of large SRFCs experienced the largest gains in quota share, with a net gain of over 8 million quota share units of halibut, almost entirely due to an influx of purchased quota share by residents of Petersburg (4.5 million quota share units) and Kodiak (3.6 million quota share units). The other community classified as a large SRFC, Unalaska, saw a small net loss of quota share over the study period. In contrast to conventional wisdom, we found that communities outside of Alaska sold more quota share than they purchased each year between 1995 and 1999, totaling a loss of over 6.7 million units of quota share. Most of the quota share emigration from communities
outside of Alaska occurred in 1995 and 1996, the first two full years of the IFQ program, which is consistent with the significant restructuring of the fishery that occurred immediately following implementation of the IFQ program as less profitable fishermen exited the fishery. Table 4 lists the percent of total quota share transacted between each type of community over the study period. The largest percentages of quota share transacted were sold internally between non-SRFCs (21% of the total) and between communities outside Alaska (about 15% of the total). For transactions between residents of different community types, one trend clearly stands out. Residents of small SRFCs clearly sell more than they buy from all other community types over the period. Overall, residents of small SRFCs sold 74% more quota share than they purchased and sold more than they purchased from each of the other types of communities.
4. SRFC residency and quota share market behavior
Fig. 1. Net quota share changes by community type from 1995 to 1999.
The trends discussed above suggest residency plays a role in quota share market behavior. In this section, we explore to what extent SRFC residency affects the decision to buy or sell quota share using a logit statistical model to systematically investigate the differences between Alaska buyers and sellers. We focus on identifying whether residency in small remote fishing communities influences quota share market behavior separately from individualspecific characteristics and from other community effects. Specifically, we wish to control for individual age effects, community population size effects, and specific year (time) effects. The analysis is restricted to Alaska buyers and sellers since only Alaska communities are defined as SRFCs and our intent is to control, to the extent possible given data limitations, other factors that may influence the decision to buy or sell quota share.
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An individual’s decision to buy or sell quota share is assumed to depend upon the attributes of the individual.6 The data upon which this analysis is based are limited to the individual-specific information collected, which is age and residency information. Age may play a significant role in determining whether a person buys or sells quota. Younger persons are more likely to participate in the fishery and purchase halibut quota for that purpose or as an investment. Yet, younger individuals often have less access to capital to purchase quota share compared with older individuals. Older individuals may wish to sell quota because they no longer wish or are able to participate in the fishery, or wish to liquidate their holdings for retirement or other opportunities. To incorporate the role of age in the buy-sell decision, individuals who buy or sell in different years are treated as separate observations. This allows us to control for the effect of age on these decisions. Data are pooled over the five-year study period. The resulting dataset has 4639 cases. Where an individual lives may also play a role in the decision to buy or sell. Residency may be a proxy for other unobserved factors that influence quota purchases or sales. For instance, in communities with strong fishing traditions, there may be pressure to retain or obtain halibut quota to maintain traditional practices. Other socioeconomic factors likely affect quota share market participation. In low-income communities, the need for readily available cash gained by quota share sale is likely to be greater than in more affluent communities. Limited access to capital also decreases the likelihood of purchasing quota. Many of the smallest SRFCs in Alaska are predominantly Alaska Native communities, with cultural and economic characteristics that affect residents’ quota buying and selling behavior. To investigate the relative importance of SRFC residency on buying and selling decisions while controlling for other individual characteristics, we assume the probability of selling (Pr[sell]) and probability of buying (Pr[buy] ¼ 1 Pr[sell]) depend upon the individual’s age, the population size of the individual’s community, and whether or not the individual lives in an SRFC. Population size is included to account for population effects that are independent of SRFC residency. The deterministic portion of Pr[sell] is specified as a linearly additive function with the following covariates: the individual’s age (in years) and age squared, the population size of the individual’s community (in 10,000s) and population size squared, a cross-effect term to capture interactions between population size and age, and dummy variables that indicate whether or not an individual lives in a small SRFC, medium-sized SRFC, or large SRFC. To capture time effects, dummy variables that represent each of the first four years of the program are also included. The logit estimation results for this SRFC-based model are presented in Table 5. Overall, the parameter values are as expected and indicate that an individual’s age, the size of the individual’s community, and SRFC residency are statistically significant explainers of the difference between Alaska buyers and sellers. Also listed in Table 5 are the marginal effects of these explanatory variables (calculated as a mean over the sample), which measure the effect on the probability of selling (Pr[sell]) with a one unit
6 Transaction-specific variables, such as the price paid, amount of quota share transacted, and other market condition information (e.g., expectations of stock abundance, other economic opportunities), are excluded from the analysis. Since the model looks for differences between buyers and sellers and the data consists of information on both the seller and buyer in each transaction, estimation of the effect of transaction-specific variables on probabilities of buying and selling is precluded. As a result, the analysis is confined to variables that are specific to individuals. Estimation of formal economic models of quota share demand and supply are beyond the scope of the present analysis. For an analysis of this type, see [9].
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Table 5 Small remote fishing community-based logit results and marginal effects on probability of selling quota share. Parameter
Estimate
Constant Age Age squared Small SRFC dummy Medium SRFC dummy Large SRFC dummy Population size Population size squared Population size age 1995 year dummy 1996 year dummy 1997 year dummy 1998 year dummy Maximized log-likelihood value LR test statistic for overall significance
0.6573** (3.117) 0.003886 (0.4765) 0.0004311** (4.311) 0.3427** (3.556) 0.3457** (2.829) 0.1791** (2.177) 0.05531 (1.0575) 0.003851** (2.029) 0.001181** (4.055) 0.1153 (1.131) 0.1926* (1.912) 0.1430 (1.318) 0.08210 (0.6599) 3075.17
Marginal effect on Pr[sell] 0.006930** 0.08056** 0.08218** 0.04273** 0.02043**
0.02720 0.04538* 0.03372 0.01937
280.69
For parameter estimates, asymptotic t-values are in parentheses. * and ** denote statistical significance at the 10% and 5% levels, respectively. The marginal effect of a variable is the change in the Pr[sell] with a one unit change in the variable holding all other things constant. Reported marginal effects are calculated as means over the sample. Significance of a marginal effect is based on whether the simulated confidence interval includes zero or not. Sample size is 4639.
change in the variable of interest (or the presence or absence of a characteristic in the case of a dummy variable). These results suggest one is more likely to sell as one gets older and also when one is from a larger community, all else being the same.7 The only significant time effect indicates that in 1996, the second year of the program, one was more likely to sell than buy, which may be indicative of Alaska quota share holders selling small-quantity quota share holdings during the initial years of the program. Even when age effects of the individual, population size effects of the individual’s community, and time effects are accounted for, there are still differences between buyers and sellers attributable to residency in small, medium, and large SRFCs. The effects appear to go in opposite directions for residents of small versus medium or large SRFCs, which reinforce the idea that quota share emigration trends are likely sensitive to how one defines SRFCs. Moreover, the SRFC residency effects on the probability of selling halibut quota share appear to be significant, and are roughly an order of magnitude greater than the effects due to age. 5. Characteristics of SRFCs and quota share market behavior In the previous section, the SRFC-based logit statistical model was used to identify whether residency in an SRFC could help explain the differences between buyers and sellers of quota share in the halibut quota share market while controlling for several other factors.8 In this section, we step away from the SRFC construct to identify the characteristics of SRFCs that may help explain why residency in these communities makes a difference in quota share market behavior. To do this, we explicitly incorporate several of the criteria used to develop our SRFC definitions, as well as additional community data, into the logit specification. Thus, the community characteristics-based logit model is identical to the SRFC-based
7 The population size effect is not surprising given that the population size effects of SRFCs are already accounted for in the coefficients for those variables. 8 It does not account for economic factors related to quota share market and fishery conditions. Demographic information, such as gender, ethnicity, and income, would be valuable to include, but such data were not collected, or generally available, from individual market participants.
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C. Carothers et al. / Ocean & Coastal Management 53 (2010) 518e523
logit model except there are no SRFC dummy variables, and in their place are additional community variables (dummy variables for whether the community is considered rural, for communities within 10 miles of the coast, and for whether any residents of the community received an initial quota share issuance).9 In addition to community characteristics that were used to construct the SRFC definitions, other community factors that are correlated with these communities could possibly explain why residency in SRFCs are indicative of market behavior. Among these factors, one stands out as especially important: Alaska Native heritage. Many of the small SRFCs identified here are Alaska Native communities. Forty-eight percent of small SRFCs have a majority of Alaska Native residents (26 communities), 55% have a quarter or more (30 communities), and 67% have at least 10% or more of the population that identifies as Alaska Native (36 communities). On average, about 42% of the populations of small SRFCs identify as Alaska Native (median ¼ 43%), compared to 20% of other non-small SRFC Alaskan communities (median ¼ 5.7%). Only seven non-small SRFC Alaskan communities included in this analysis have a majority of residents that identify as Alaska Native. Some analysts predicted that Alaska Native villages would be differentially impacted by the implementation of the IFQ program [10]. The limitation and commoditization of fishing access rights began on a large scale in Alaska with the limited entry management of salmon in the 1970s. While keeping fishing rights in Alaska was a motivating factor for limiting entry [11], analyses show a migration trend of salmon permits away from rural Native villages in Alaska [12e14]. A complex set of historical, cultural, socioeconomic, and geographic characteristics of Alaska Native villages is believed to drive this trend [3]. Data on the ethnicity of individual transfer participants is not collected. To account for this factor in the community characteristics-based model, we include in the specification the percentage of the individual’s community that identifies as Alaska Native drawn from US Census data. The results of the community characteristics-based logit model are summarized in Table 6. Without the different-sized SRFCs represented in the model, the population size marginal effect reversesdresidents of smaller Alaska communities are more likely to sell than buy. Age effects are similar to the SRFC-based logit model, and time effects are not significant. Among the community characteristics that are used to define an SRFC, only rural classification appears to have an effect in explaining differences between buyers and sellers. Individuals from communities classified as rural are less likely to sell than buy holding everything else constant.10 Interestingly, proximity to the coast and whether the community was originally issued quota share do not appear to be significant factors that distinguish buyers and sellers. However, individuals from communities with larger percentages of Alaska Native residents are more likely to sell than buy, which provides evidence for why quota holders in small SRFCs, which have high percentages of Alaska Native residents, tended to sell more quota share than they buy.
6. Discussion Fishery managers and analysts have recognized the problem of net transfer of Alaska halibut quota shares out of small remote fishing communities. Our analysis of the data between 1995 and
9 Models with population size thresholds were estimated, but because of the correlation with the continuous population size variable, population size was modeled in its continuous form in the models presented. 10 In the absence of SRFC dummies, this should not be too surprising given the large number of rural communities in Alaska that are non-SRFCs.
Table 6 Community criteria-based logit results and marginal effects on probability of selling quota share. Parameter
Estimate
Constant Age Age squared Population size Population size squared Population size Age Alaska Native Percentage Initial quota share dummy Distance (within 10 miles of coast) dummy Rural community dummy 1995 year dummy 1996 year dummy 1997 year dummy 1998 year dummy Maximized log-likelihood value LR test statistic for overall significance
1.934** (2.225) 0.003533 (0.4341) 0.006763** 0.0004208** (4.218) 0.09416* (1.874) 0.02754** 0.005312** (2.935) 0.001164** (4.001) 0.01538** (8.322) 0.003595** 1.377 (1.604) 0.2900 0.09808 (0.6520) 0.02287 0.2678** (3.469) 0.09140 (0.8933) 0.1538 (1.519) 0.1215 (1.119) 0.06616 (0.5309) 3056.34 318.34
Marginal effect on Pr[sell]
0.06218** 0.02138 0.03597 0.02842 0.01548
For parameter estimates, asymptotic t-values are in parentheses. * and ** denote statistical significance at the 10% and 5% levels, respectively. The marginal effect of a variable is the change in the Pr[sell] with a one unit change in the variable. Reported marginal effects are calculated as means over the sample. Significance of a marginal effect is based on whether the simulated confidence interval includes 0 or not. Sample size is 4639.
1999 confirms that this concern is based on genuine quota losses from these communities and offers statistically-based evidence that the size of SRFCs matters. These results also indicate that in addition to small community size, Alaska Native cultural affiliation is an important factor that is linked to quota share market behavior. Reducing the number of participants in a fishery by a marketbased system which allows those that exit to receive a pay-out funded by remaining or entering participants seems an obvious improvement over chaotic one-day fishing seasons or governmentfunded buybacks. Individuals are compensated for their exit without burdening taxpayers, while those who remain in the fishery have a longer season and a better potential earning outlook. But, to the extent that these exiters are disproportionately located in small communities or indigenous communities, social and economic impacts (including negative multiplier effects) will be differentially concentrated. So the consequence of solving one collective action problem (too many participants in a fishery) creates another (disproportionate quota loss from small or indigenous communities). Recognizing that the transferability of halibut and sablefish quota was creating distributional inequities, the North Pacific Fishery Management Council (hereafter, the Council) implemented the “Community Purchase Program” for 42 fishing communities in the Gulf of Alaska. The Council set the population threshold for eligibility at 1500 (along with other criteria). The program communities align fairly closely to the small SRFCs discussed in this paper.11 Our analysis suggests the Council targeted the appropriately-sized Gulf of Alaska communities by limiting the new program to the smallest of the SRFCs. Developing models of community-based ownership of fishing quota may be a primary
11 Several communities (Chignik Lake, Hollis, Karluk, Kasaan, and Tyonek,) are part of the Community Purchase Program, but are not classified as small SRFCs. These communities did not have residents that received an initial halibut quota share allocation and therefore did not meet our criteria for SRFC inclusion. In addition, there are seventeen communities that are classified as small SRFCs that are not eligible for the Community Purchase Program. This program was restricted to Gulf of Alaska communities and communities that are not linked to larger communities via a highway network.
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solution to addressing the kinds of quota share emigration trends described in this paper [3,15]. The findings presented in this paper contribute to an understanding of a broader range of distributive impacts of fisheries access privatization around the globe. The Council imposed restrictions on halibut quota market trading to limit extensive consolidation and corporate ownership witnessed in some other IFQ fisheries; however, the emigration of quota from SRFCs, while unintended, was a predictable outcome of the limitation and commoditization of halibut fishing rights. Often for a suite of reasons, fishermen residing in small remote communities are among the most “inefficient” harvesters. Many fishermen in SRFCs have exited halibut fishing. As the privatization of fisheries access continues to gain favor in an international context, a diverse range of fisheries in various social contexts will become restructured to provide for increased economic efficiencies. Analyzing the overall distribution of fishing rights (both initially and as a result of market trading) is a key piece to understanding the social impacts of privatized access fishing on communities of people and place. Particularly when the stated goals of privatized access policies are to encourage efficiency and reduce overcapitalization it is critical to predict the impacts of “inefficient exiters.” To the extent that these exiters are disproportionately located in small, remote fishing communities (in this particular case, indigenous communities), a wider set of socioeconomic and cultural issues surface as managers and analysts debate the benefits and costs of implementing such programs. Acknowledgements The authors would like to thank Jessica Gharrett at the National Marine Fisheries Service for her patience and responsiveness with our many questions and data inquiries, Susan Abbott-Jamieson for early support of this research, Dave Colpo at the Pacific States Marine Fisheries Commission, Eugene Hunn at the University of Washington, and Angie Grieg of the Alaska Fisheries Science Center for her assistance with GIS. We also thank Ron Felthoven (AFSC), Nicole Kimball (NPFMC), Suzanne Russell (NWFSC), and participants at the 2006 IIFET meetings for providing useful comments
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that have improved this paper. All potential errors are our own. The opinions expressed in this article are those of the authors and do not necessarily reflect those of the National Marine Fisheries Service. References [1] National Research Council. Sharing the fish: toward a national policy on individual fishing quotas. Washington, D.C.: National Academy Press; 1999. 422 pp. [2] McCay B. ITQs and community: an essay on environmental governance. Agricultural and Resource Economics Review 2004;33(2):162e70. [3] Lowe, M, Carothers C, editors. Enclosing the fisheries: people, places and power. Symposium 68. Bethesda, Maryland: American Fisheries Society Press; 2008. [4] US Department of Commerce, National Oceanic and Atmospheric Administration. Limited access management of fisheries of Alaska, final rule. Federal Register 58(215):59,375e413. [5] US Department of Commerce, National Oceanic and Atmospheric Administration. Community purchase, final rule. Federal Register 69(84):23,681e94. [6] Dawson R. Vertical integration in the post-IFQ halibut fishery. Marine Policy 2006;30(4):341e6. [7] Gulf of Alaska rationalization introductory paper. Anchorage, AK: North Pacific Fisheries Management Council. Available from: