Review of Economics & Finance Submitted on 27/03/2017 Article ID: Mackenzie D. Wood, and Jungho Baek

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1 Review of Economics & Finance Submied on 27/03/2017 Aricle ID: Mackenzie D. Wood, and Jungho Baek Facors Affecing Alaska s Salmon Permi Values: Evidence from Brisol Bay Drif Gillne Permis Mackenzie D. Wood Deparmen of Economics Universiy of Alaska Fairbanks mdwood2@alaska.edu Dr. Jungho Baek (Correspondence Auhor) Deparmen of Economics Universiy of Alaska Fairbanks Fairbanks, AK 99775, U.S.A. jbaek3@alaska.edu Absrac: The effecs of oal earnings, oal coss and mining exploraion on permi prices in Alaska are invesigaed using an auoregressive disribued lag (ARDL) approach o coinegraion. We ake specific accoun of regional and gear specific salmon fisheries ha is, Brisol Bay drif gillne permis in our modelling. We find ha here is a sable long-run relaionship among permi prices, oal earnings, and oal coss. I is also found ha, in boh he shor- and long-run, oal earnings have a posiive and significan relaionship wih permi prices, while oal coss have a negaive and significan relaionship. Alhough he mining exploraion in he region has a negaive and significan effec on permi prices in he shor-run, he effec does no seem o las in he long-run. Keywords: Alaska; ARDL model; Brisol Bay; Drif gillnes; Permi prices JEL Classificaions: C22, D46, L79, Q22 1. Inroducion Commercial salmon fisheries are no only a criical resource o Alaska s economy, bu o he U.S. marke as well. During he period, for example, he Alaskan salmon fisheries provided an annual average of 59,539 jobs wih oal labor income of $1.584 billion and accouned for almos 98% of U.S. salmon harvess wih annual harvess averaging around 800 million pounds valued a over $500 million (McDowell, 2015). To preven economic ren dissipaion in he salmon fisheries, he Alaska sae legislaure hus has adoped he so-called limied enry permi sysem for commercial salmon fisheries hrough he passage of he Limied Enry Ac since The sysem issues radeable permis for specific salmon fisheries corresponding o differen ypes of gear and geographical areas, and requires he permi holders o be presen on he vessel when fish are landed. However, he Alaskan salmon fisheries have been subjec o grea volailiy in permi values over he pas four decades. For example, saring in 1978 he value of a permi in 2014 dollars was nearly $152,000. They reached an allime high of $475,000 in 1989, bu fell sharply o a low of $26,000 in By 2014, he values of he permis had rebounded back o around $150,000. Therefore, i is crucial o ~ 63 ~

2 ISSNs: ; Academic Research Cenre of Canada examine facors ha conribue o he dynamic behavior of permi values appropriaely in order o undersand Alaska s commercial salmon fisheries accuraely. A number of sudies o dae have invesigaed he markes for limied enry permis in he Alaska salmon fisheries. Some examine he implicaions of he limied enry permis for commercial salmon fisheries in Alaska (Karpoff, 1982) and changes in local ownership of Alaskan salmon enry permis (Knapp, 2010). Ohers address he economic and non-economic effecs of he limied enry permis on he Alaskan salmon fisheries (e.g., Karpoff, 1985; Benshoof and Baek, 2014). Moreover, a couple of sudies have analyzed he key facors affecing he prices of limied enry permis (Karpoff, 1984; Hupper e al. 1996). They commonly find ha (expeced) oal earnings generaed by permi ownership and use are he mos significan facor in deermining he permi values, confirming asse pricing heory. However, an imporan poin overlooked by he wo researchers is ha if he seleced variables in heir models are nonsaionary, sandard OLS esimaion leads o he spurious regression problem, hereby raising doubs abou he validiy of he resuls. Furher, despie wide variaions in permi prices corresponding o gear ypes and/or fishing areas, he emphasis of he sudies has ypically been on Alaskan saewide salmon fisheries. In oher words, here is no curren research or modeling on regional/gear specific salmon fisheries in he Sae of Alaska. 1 In his aricle, herefore, we ake one sep furher and aemp o examine he facors affecing he prices of limied enry permis in he conex of regional and gear specific salmon fisheries in Alaska using enhanced mehods and an updaed daase. Special aenion has been given o he assessmen of he shor- and long-run effecs of such facors as gross earnings and operaing coss on he values of Brisol Bay drif gillne permis. Brisol Bay, locaed in souhwesern Alaska, accouns for nearly one-hird of all Alaska s salmon harves earnings ($156 million in 2016) and produces he larges sockeye salmon fishery in he world. 2 In addiion, drif gillnes are used o cach nearly 80% of Brisol Bay sockeye salmon. For he analysis, we employ an auoregressive disribued lag (ARDL) approach o coinegraion developed by Pesaran e al. (2001). The ARDL approach can be applicable o he level of variables wihou esing wheher hey are saionary or nonsaionary and uses an errorcorrecion forma o esimae boh he shor- and long-run dynamics wih a single sep; hence, i is well suied o deal wih his line of research. The remaining secions presen an overview of Alaska s limied enry permi sysem, empirical mehod, daa, empirical findings and concluding remarks. This paper is organized as follows. Secion 2 describes he limied enry permi sysem in Alaska ha his research analyzes. Secion 3 describes he model and mehods used o invesigae he facors deermining he values of Brisol Bay drif gillne permis. Secion 4 describes he daa uilized in he analysis. Secion 5 reviews he empirical resuls. Finally, secion 6 presens our conclusions and discusses limiaions and policy implicaions. 1 In fac, Hupper e al. (1996) use wo gear ypes such as purse seine and drif gillne in heir models and conclude ha esimaing he wo gear ypes separaely would be more desirable in order o draw robus conclusions. However, hey employ Alaskan saewide salmon fisheries daa for he analysis. 2 As he second mos abundan species commercially caugh in Alaska, sockeye salmon is known as he mos valuable salmon species. ~ 64 ~

3 Review of Economics & Finance, Volume 10, Issue 4 2. Limied Enry Permi Sysem in Alaska Alaska creaed he Commercial Fisheries Enry Commission (CFEC) in 1973 and adoped a limied enry managemen sysem for commercial salmon fisheries hrough he passage of he Limied Enry Ac in Eigh geographic areas (Souheas, Yakua, Prince William Sound, Cook Inle, Kodiak, Chignik, Alaska Peninsula, and Brisol Bay) are fished using five differen ypes of gear (purse seine, beach seine, drif gill ne, se gill ne, and power roll). These limied enry permis were originally issued for free o individuals based on he degree of economic dependence upon he fishery, including he percenage of income derived from he fishery, reliance on alernaive occupaions, availabiliy of alernaive occupaions, invesmen in vessels and gear; (and) (2) exen of pas paricipaion in he fishery, including he number of years of paricipaion in he fishery, and he consisency of paricipaion during each year (Alaska Saues, Sec ). Only individuals may own hese permis, he owner mus be presen on he vessel while hey are fishing, and permis may no be leased (Knapp, 2010). The Limied Enry Ac allows for wo ypes of permi ransfers: permanen and emergency. Permanen ransfers occur when here is a change in he holder of he permi, and emergency ransfers allow for he permi o be fished by someone oher han he holder if he permi holder: is prevened from fishing due o illness, deah, disabiliy, required miliary or governmen service, or oher unavoidable hardship of a emporary, unexpeced and unforeseen naure. In order o permanenly ransfer a permi o someone else, he permi holder mus file a Noice of Inen o Permanenly Transfer form and wai he 60 day waiing period; he permi holder and he ransferee hen mus complee he Reques for Permanen Transfer of Enry Permi form (CFEC, 2012b). This 60 day waiing period was creaed by he legislaure so ha permi holders would have ime o consider heir long erm needs before permanenly ransferring heir permi. Limied enry permis mus be renewed annually once issued, and failure o renew for a period of wo years resuls in forfeiure. Also, he Alaska Legislaure has reserved he righ o modify or revoke a limied enry permi wihou providing compensaion or hrough buyback programs (Weiss, 1992). Permis ha have been forfeied are removed from he fishery and are no reissued o oher fishermen (CFEC, 2012a). 3. The Model and he Mehod To invesigae he facors deermining he values of Brisol Bay drif gillne permis, following previous sudies (i.e., Karpoff, 1984; Hupper e al., 1996), we also rely on an asse pricing model developed by Hirschleifer (1980). In is simples form his model can be saed as: P f ( R, C, Z) where P is he price of a permi; R is he expeced oal earnings (revenue); C is he expeced oal coss; and Z is oher shif facors affecing he price of a permi. Equaion can be specified in a log-level form as follows: ln P C DUM u (2) 0 1 ln R 2 ln ~ 65 ~ where lnp is he naural log of he price of permis; lnr is he naural log of he average oal earnings; lnc is he naural log of he average gasoline price as a proxy for coss; DUM is a dummy variable capuring he effec of he Pebble Mine exploraion on permi prices; and u is he error erm. Pebble Mine is a mineral exploraion projec invesigaing a very large porphyry copper, gold and molybdenum mineral deposi in Brisol Bay. However,

4 ISSNs: ; Academic Research Cenre of Canada since he mine is locaed in he headwaers of he fishery, many local fisherman have voiced heir concern over he mine and he possibiliy of he negaive impacs i has on he fishery in he fuure. The decision for DUM o ake on he value of 1 for he years is decided based upon Norhern Dynasy Minerals Ld. saring exploraion in 2002, discovering Pebble Eas deposi in 2005, forming he Pebble Parnership wih Anglo American plc in 2007, developers releasing preliminary assessmen and environmenal daa in 2011, and he Pebble Parnership coming o an end in 2013 leaving Norhern Dynasy looking for new invesors. Since an increase in expeced oal earnings generally leads o an increase in permi prices, i is expeced ha β 1 >0. To he exen ha a rise in expeced oal coss resuls in a decrease in permi prices hrough reducion in fishing aciviies and hence demand for permis, i is expeced ha β 2 <0. Finally, if he Pebble Mine exploraion has a negaive effec on he fishery and permi prices, i is expeced ha β 3 <0. Equaion (2) is now reformulaed as follows o illusrae he ARDL modeling approach: ln P 0 n i1 ln P i1 ln P 0 1 i n i0 ln R 1 ln R 1 i2 i ln C 2 1 n i0 ln C i3 i DUM (3) All variables here are as previously defined wih ε being he error erm. Unlike a sandard error-correcion model ha includes he lagged error-correcion erm (ec -1 ) from Equaion (3), he ARDL model includes he linear combinaion of lagged level variables (lnp -1, lnr -1, and lnc -1 ) as he error-correcion erm. Pesaran e al. (2001) recommend using he F-es o evaluae wheher or no he hree lagged level variables in Equaion (3) are joinly significan. For his, he upper and lower asympoic criical values provided by Pesaran e al. (2001) can be uilized o es he null hypohesis ha here is no coinegraion (H 0 : θ 0 = θ 1 = θ 2 =0) agains he alernaive ha here is (H 1 : θ 0 θ 1 θ 2 0). Once he F-es provides a coinegraing relaionship, he long-run coefficien esimaes are derived by he esimaes of θ 1 and θ 2 normalized on θ 0. The shor-run dynamic effecs are represened by he esimaes of coefficiens following he sigma symbols. 4. Daa The average price of acual sales ransacions for permis are used as a proxy for permi values and are acquired from he Commercial Fisheries Enry Commission (CFEC) via he Alaska Deparmen of Fish and Game (ADF&G). The oal average earnings for all permanen permi holders are used as a proxy for he expeced oal earnings and are colleced from he CFEC. Since he rise and fall of fuel prices affecs fishing aciviies, gasoline prices are used as a proxy for he expeced operaing coss and are aken from he U.S. Energy Informaion Adminisraion (EIA). 3 All he variables are deflaed o 2014 dollars using he Consumer Price Index (CPI) aken from he U.S. Bureau of Labor Saisics (BLS). Finally, since permi values are no recorded unil 1978, our daase is compiled from 1978 o I should be admied ha here are a number of inpus ha conribue o oal coss wih wages paid o he deckhands, food prices, mainenance coss, and insurance raes all being examples. Due o unavailabiliy of hose daa, however, average gas prices are used as a proxy for inpu coss in our model; hus, our findings should be viewed wih cauion. ~ 66 ~

5 Review of Economics & Finance, Volume 10, Issue 4 5. Empirical Resuls Alhough he ARDL mehod does no require he variables in Equaion (3) o all be of he same order of inegraion, i crashes in he cases where I(2) variables are involved. Before esimaing he model, herefore, he presence of a uni roo in he seleced variables is esed using an augmened Dickey Fuller (ADF) es. Table 1 repors he resuls of he ADF es for a uni roo in each of he hree variables. Since he es saisics for he levels (firs differences) are above (below) -3.5(-3.18) a he 5% (10%) significance level, we canno (can) rejec he null hypohesis of a uni roo for any of he hree variables. This indicaes ha each series in Equaion (3) is I variable, ensuring ha he ARDL mehod can be safely applied o he curren research. Table 1. Resuls of ADF uni roo ess (period: ) Variable Level Firs difference Decision lnp ** I lnr ** (2) (2) I lnc ** I Noes: ** and * indicae rejecion of he null hypohesis a he 5% and 10% levels, respecively. The 5% and 10% criical values for he ADF, including a consan and rend, are -3.5 and -3.18, respecively. Numbers inside parenheses are lag lenghs, which are seleced by he Schwarz Informaion Crierion (AIC). In he ARDL approach, he shor- and long-run esimaed coefficiens of he individual series are saisically meaningful only if hey are coinegraed. Therefore, he model is esed o deermine he exisence of coinegraion relaionship among he hree variables using he F-es. For his, afer imposing a maximum of wo lags, Akaike s Informaion Crierion (AIC) is used o selec he opimum lags in Equaion (3). Since he compued F-saisic of far exceeds he 5% upper bound criical value of 6.021, we can rejec he null hypohesis ha he hree variables are no coinegraed. Therefore, i is likely ha any deviaion among he hree variables is no expeced o coninue and will have a endency o reurn o is rend pah in he long-run. Table 2. Esimaed long-run coefficiens of he price permi model of Brisol Bay (period: ) Noes: ***, ** and * denoe significance a he 1%, 5%, and 10% levels, respecively. In parenheses are -saisics. We now move on o discuss he resuls of he shor- and long-run coefficien esimaes of he permi price model of Brisol Bay. Tables 2 and 3 repor our key findings, where he permi value is used as he dependen variable. The ~ 67 ~ Variable lnr lnc DUM Consan Coefficien *** (7.725) ** (-1.968) (-0.455) (-1.520)

6 ISSNs: ; Academic Research Cenre of Canada esimaed effec of he earning variable on permi prices is posiive and highly significan in boh he shor-and long-run, suggesing ha improved earnings resul in higher permi prices. In he long-run (shor-run), for example, wih a 1% increase in earnings we can expec o see an increase in permi prices by 1.352% (0.516%). The esimaed effec of he cos variable on permi prices is negaive and significan in he shor- and long-run, indicaing ha as coss increase he profi margin ends o decrease which in urn reduces demand for permis and prices. In he long-run (shor-run), for example, wih a 1% increase in coss we can expec o see a decrease in permi prices by 0.576% (0.346%). These findings could be viewed as one piece of evidence supporing ha radiional asse pricing heory holds for permi values in Brisol Bay in boh he shor- and long-run: herefore, changes in ne earnings, which represen revenues less coss, generally deermine he flucuaions in permi values. Finally, he dummy variable represening he Pebble Mine exploraion is negaive in he shor- and long-run - bu insignificanly so for he long-run and highly significan for he shor-run. Apparenly, here is evidence ha heavy mining exploraion occurred in he region negaively affec permi prices in he shor-run, bu does no las in he long-run. Table 3. Esimaed shor-run coefficiens of he price permi model of Brisol Bay (period: ) Variable lnr lnc DUM Coefficiens *** (5.448) * (-1.913) ** (-1.995) Noes: ***, ** and * denoe significance a he 1%, 5% and 10% levels, respecively. In parenheses are -saisics. Brackes in diagnosic ess are p-values. RESET indicaes regression specificaion error es, which uses Ramsey's RESET es based on he square of he fied values ec *** -1 (-4.783) I is imporan o menion ha he errorcorrecion erm (ec -1 ) obained from he Serial correlaion [0.261] linear combinaion of lagged variables in Equaion (3) are negaive and highly RESET [0.138] significan, confirming ha here is a significan long-run relaionship among he Normaliy variables (Kremers e al., 1992). The [0.815] significan coefficien on he error-correcion Heeroskedasiciy erm being indicaes ha when permi [0.901] values in he previous year deviae from he equilibrium, he permi marke ends o adjus by approximaely 60.1% in he following year. ~ 68 ~

7 Review of Economics & Finance, Volume 10, Issue 4 Figure 1. Plos of CUSUM ( ) Figure 2. Plos of CUSUMSQ ( ) Finally, a series of diagnosics ess show ha our ARDL model seems o be wellspecified, passing such ess as serial correlaion, regression specificaion error es (RESET), heeroscedasiciy, and non-normaliy. In addiion, he cumulaive sum (CUSUM) and cumulaive sum of squares (CUSUMSQ) show ha he plos lie beween he 5% criical bounds a all poins, providing he sabiliy of he shor- and long-run coefficien esimaes for he period (Figures 1 and 2). ~ 69 ~

8 ISSNs: ; Academic Research Cenre of Canada 6. Concluding Remarks Alaska adoped a limied enry permi sysem for commercial salmon fishing in These permis have been subjec o grea volailiy in price over he las four decades. In his shor paper, herefore, we aim o empirically examine he facors ha conribue o he dynamic behavior of he permi values. The primary conribuion of he paper is o address he issue in he conex of regional and gear specific salmon fisheries in Alaska ha is, Brisol Bay drif gillne permis - using an enhanced mehod ha is, an auoregressive disribued lag (ARDL) approach o coinegraion. Evidence is found ha here is a sable coinegraion relaionship among he variables of ineres which poins o a long-run relaionship beween permi prices, oal earnings, and oal coss. I is also found ha oal earnings have a posiive and significan relaionship wih permi prices, and oal coss have a negaive and significan relaionship in boh he shor- and long-run. Finally, i is found ha he mining exploraion in he region has no significan long erm effec. As of early May 2017 i has been repored ha he US EPA and Norhern Dynasy are close o seling liigaion over he Pebble Mine. A sake is an Obama-era Proposed Deerminaion ha, if finalized, would place resricions on he mine (Associaed Press, 2017). Wih a new adminisraion and a shif in EPA leadership i is possible he mine will become a high prioriy again in he near fuure. If he mining aciviy does indeed negaively impac permi prices in he shor-run like our analysis shows, policy could be inroduced in order o compensae he fishermen over a deermined period of ime in order o offse he negaive effec. The cos proxy of gasoline price was found o have a negaive and significan effec and policy could be developed in order o subsidize fuel coss when permi prices are above a level deermined o be unaainable by hisorical permi fishermen. Finally wih earnings being shown o have a posiive relaionship wih permi prices policy could be inroduced in order o help keep salmon prices seady o allow for more consan earnings and permi prices o avoid he dips and peaks we observe in he pas. There are wo main caveas o our analysis. Firs, we used gas prices alone as a proxy for coss o he permi holder while here are oher facors a hand such as shares paid o deckhands, food prices, mainenance coss, and insurance coss. Wih limied cos daa our findings mus be viewed wih cauion. Second, our indicaor variable represening Pebble Mine exploraion covers a vas period including he years Over his period here is a srucural break in he daa ha may be explained by facors oher han Pebble Mine ha we have no accouned for. Fuure research could be done uilizing ADF&G Fish Ticke cos daa or an index of coss in order o more accuraely esimae coss in he fishery. More research also need o be done on wha else occurred in he Pebble Mine indicaor ime period and wha exacly caused he break in he daa before we can definiively commen on he impacs of he mine on he permi marke. Acknowledgemen: The auhors hank anonymous referees for heir helpful commens. This research was suppored in par by he publicaion award of he office of he Vice Chancellor for Research (VCR) a Universiy of Alaska Fairbanks. ~ 70 ~

9 References Review of Economics & Finance, Volume 10, Issue 4 [1] Associaed Press (2017, May 5). Aorneys indicae agreemen close in Alaska Pebble Mine lawsui. [Online] Available a: hp:// (Rerieved on May 11, 2017). [2] Benshoof, C., Baek, J. (2014). Poliics, environmen, and fisheries: empirical evidence from Pacific salmon fisheries. Naural Resource Modeling, 27(3): [3] Commercial Fisheries Enrance Commission (CFEC) (2012a). Commercial Fishing Permis. [Online] Rerieved from hps:// Commercial_Fishing_Permis.pdf. [4] Commercial Fisheries Enrance Commission (CFEC) (2012b). Permi Transfers. [Online] Rerieved from hps:// [5] Hirschleifer, J. (1980). Price Theory and Applicaions, New Jersey: Prenice-Hall. [6] Hupper, D.D., Ellis, G.M., and Noble, B.N. (1996). Do permi prices reflec he discouned value of fishing? Evidence from Alaska s commercial salmon fisheries. Canadian Journal of Fisheries and Aquaic Science, 53(4): [7] Karpoff, J.M. (1982). Enry limiaion and he marke for limied enry permis in he Alaska salmon fisheries. Ann Arbor: Universiy Microfilms Inernaional. [8] Karpoff, J.M. (1984). Low-ineres loan and he markes for limied enry permis in he Alaska salmon fisheries. Land Economics, 60: [9] Karpoff, J.M. (1985). Non-pecuniary benefis in commercial fishing: empirical findings from he Alaska salmon fisheries. Economic Inquiry, 23: [10] Knapp, G. (2010). Local permi ownership in Alaska salmon fisheries. IIFET 2010 Monpellier Proceedings. [Online] Rerieved from hp://ir.library.oregonsae.edu/xmlui/ bisream/handle/1957/39100/430.pdf?sequence=1. [11] Kremers, J.J.M., Ericson, N.R., and Dolado, J.J. (1992). The power of coinegraion ess. Oxford Bullein of Economics and Saisics, 54(3): [12] McDowell Group (2015). The economic value of Alaska s seafood indusry. [Online] Rerieved from hp://ebooks.alaskaseafood.org/asmi_seafood_impacs_dec2015/pub Daa/source/ASMI%20Alaska%20Seafood%20Impacs%20Final%20Dec2015%20-%20 low%20res.pdf. [13] Pesaran, H.M., Shin, Y., and Smih, R.J. (2001). Bounds esing approaches o he analysis of level relaionships. Journal of Applied Economerics, 16(3): [14] Weiss, J.D. (1992). A axing issue: are limied enry fishing permi propery?. Alaska Law Review, 9: ~ 71 ~