The Price Responsiveness of Salmon Supply in the Short and Long Run

Transcription

1 Marne Resource Economcs, Volume 23, pp /00 $ Prnted n the U.S.A. All rghts reserved Copyrght 2008 MRE Foundaton, Inc. The Prce Responsveness of Salmon Supply n the Short and Long Run TRUDE B. ANDERSEN KRISTIN H. ROLL SIGBJØRN TVETERÅS Unversty of Stavanger Abstract Productvty growth and compettveness ndcate that salmon supply s prce responsve. However, n the short run supply s lkely to be constraned by the bologcal producton process, regulatons, and capacty constrants. In ths artcle, we estmate a restrcted proft functon for Norwegan salmon producers, whch allows us to examne the ndustry s short-run and long-run supply responsveness separately. Usng data spannng 1985 to 2004, we fnd that there s close to zero, own-prce supply responsveness n the short run. In the long run, ths changes substantally as supply becomes elastc. Ths result can contrbute to explanng the observed cyclcal proftablty n the salmon farmng ndustry. Key words Restrcted proft functon, supply, salmon farmng, proft cycles. JEL Classfcaton Codes D24, Q21, Q22. Introducton Snce the begnnng of the 1980s, the salmon ndustry has been characterzed by a hgh degree of technologcal nnovaton. Both publc and prvate R&D as well as on-farm learnng have contrbuted to the nnovatons, whch have resulted n the development of farmed salmon as one of the most successful aquaculture speces. Producton ncreased from vrtually nothng n the early 1980s to about 1.6 mllon tonnes by 2006, and farmed salmon s now traded and consumed globally. Together wth the ncreased producton of salmon, the general producton cost has decreased substantally, such that by 2004 real cost was only a quarter of the cost n the md- 1980s. The reduced producton costs have been mportant n several ways for makng the salmon ndustry more compettve, as a lower output prce has been vtal n generatng greater consumpton of salmon (Asche 1997). Despte the fact that the salmon ndustry has experenced substantal productvty growth that has led to a decreasng trend n prces, there seems to be substantal cycles n prces around ths long-run trend (Øglend and Skveland 2008). One mportant factor contrbutng to these cycles s that the short-run supply response s lkely to be constraned, meanng that the reacton of producers to hgh prces wll be delayed. In the long run, ths can lead to an overshootng supply response, de- Trude B. Anderson s a Ph.D. canddate and Krstn H. Roll and Sgbjorn Tveteras are assocate professors at the Unversty of Stavanger, 4036 Stavanger, Norway, emal: Trude.Thomassen@us.no, krstn.h.roll@us.no, and sgbjorn.tveteras.us.no, respectvely. 425

2 426 Andersen, Roll, and Tveterås pressng prces to unproftable levels. Ths msalgnment between supply and demand has led to substantal varatons n ndustry proftablty. Several studes of salmon aquaculture have documented the large productvty growth and the subsequent lowerng of costs and output prces (Asche and Tveteras 1999, Tveteras 1999, Guttormsen 2002, Kumbhakar 2002, Tveteras and Heshmat 2002, Tveteras and Battese 2006, Asche 2008). However, few studes have analyzed how producton possbltes and relatve prces affect salmon producers supply responsveness. 1 In ths paper, we estmate a restrcted proft functon for Norwegan salmon producers, whch allows us to separate the ndustry s short- and long-run responsveness. The theoretcal framework for the restrcted or partal statc equlbrum approach was developed by Lau (1976), Mork (1978), and Brown and Chrstensen (1981). 2 By specfyng a restrcted proft functon nstead of usng the more commonly used cost functon, a more general representaton of the frm s producton technology s provded. In contrast to the full equlbrum models, the restrcted equlbrum model allows for partal adjustment of supply n the short run, and hence s able to separate short- from long-run effects. Ths dentfcaton of shortand long-run flexblty may help to explan why we observe cycles n ndustry proftablty. We estmate a restrcted translog proft functon based on a sample of over 500 Norwegan salmon farms durng a 20-year perod. In lne wth several earler studes, we assume that captal s fxed n the short run (Salvanes 1993, Kouka and Engle 1998, Guttormsen 2002, Tveteras 2002). Based on the estmated proft functon, short- and long-run elastctes are derved as shown by Squres (1987). Whle greater knowledge of the supply response n salmon farmng s nterestng n tself, t s also nterestng from the perspectve that the ndustry has faced dfferent sets of regulatons amed at lmtng producton (Bjørndal and Salvanes 1995, Knnucan and Myrland 2002). For nstance, the Norwegan salmon ndustry has faced mnmum mport prce restrctons from the European Unon as well as restrctons on captal and feed use by Norwegan authortes. Therefore, knowledge about the supply response and the nteracton between producton and nput factor use s of nterest n relaton to the mpact of the regulatons. The artcle proceeds as follows. The next secton elaborates on some of the ssues that constran short-run supply of farmed salmon, before we go on to dscuss the theoretcal model underlyng the restrcted proft functon. We then present the data used for emprcal analyss, followed by a presentaton and dscusson of the emprcal results. The artcle concludes wth some observatons regardng the model and results. Background Productvty growth and compettveness among salmon producers have been nstrumental n the development of salmon aquaculture. Fgure 1 shows how real producton costs have decreased snce the end of the 1980s, owng to productvty 1 Steen, Asche, and Salvanes (1997) estmated a short-run elastcty of about 1.0 and a long-run supply elastcty of about 1.5 for the Norwegan salmon ndustry usng annual aggregated data. Asche, Kumbhakar, and Tveteras (2007) reported a long-run supply elastcty of about 1.5 derved from a cost functon. 2 The approach has been appled by Schankerman and Nadr (1986), Kulatlaka (1985), Morrson (1985), Halvorsen and Smth (1986), and Hazlla and Kopp (1986) n the framework of a restrcted cost functon, and by Squres (1987) n the framework of a restrcted proft functon.

3 Prce Responsveness of Salmon Supply 427 Fgure 1. Average Producton Cost, Export Prce and Profts n Norwegan Salmon Aquaculture, growth. Prces have followed sut, as shown by the decreasng export prce of salmon n the fgure, ndcatng that a large part of the effcency gans have been transferred to consumers. The hgh degree of competton evdent from the prce reductons suggests that salmon supply s responsve to changes n the marketplace. In other words, to reman n the marketplace, salmon producers must be able to supply salmon at compettve prces. Another feature of the ndustry dsplayed n fgure 1 s shfts between prolonged perods of low and hgh profts. Ths s an ndcaton that salmon supply does not easly adjust n the short run. 3 Supply responsveness depends to a large degree on producton technology, but also on market structure. In an ndustry that s hghly concentrated and where some frms have market power, supply wll be less responsve than n a compettve market. Although consoldaton actvty has created a few very large companes, ndcatng that the ndustry s reachng a more mature stage n the lfe cycle, there are strong reasons to beleve that the Norwegan salmon ndustry remans compettve. There are stll many small- and medum-szed frms operatng. In 2005, there were 88 frms wth between one and nne lcenses each, eght frms wth lcenses, and nne frms wth more than 20 lcenses. Hence, even though the frm sze dstrbuton has become more skewed towards the largest frms, the number of producers stll suggests that we are dealng wth a compettve ndustry. For that reason, we argue that lmted short-run supply responsveness s manly caused by restrctons on technology, nput avalablty, and regulatons. To understand the supply responsveness of salmon producers, t s necessary to consder the bologcal producton process. Salmon producton s carred out n two 3 Ths cyclcal pattern became apparent after the md-1990s. In the early years of the Norwegan salmon ndustry, producers experenced wdespread dsease outbreaks, whch led to erratc changes n proftablty. The ntroducton of vaccnes at the begnnng of the 1990s reduced these problems and the supply of farmed salmon became more stable, followed by the emergence of proft cycles. Such cycles are common n many commodty markets.

4 428 Andersen, Roll, and Tveterås phases. The frst s a freshwater phase, where the ova are hatched and the smolts are reared n tanks or n cages n freshwater lakes. Ths takes around months. The second phase nvolves growng the smolts n cages n seawater untl they reach market sze, whch may take between 10 and 18 months. In practce, when the producton of a cohort has commenced, there s lttle room for adjustments n producton untl the next cohort s ntroduced. Because of the bologcal producton cycle, the short-run response to prce sgnals from the market s lkely to be lmted. Therefore, one would expect the supply to be substantally more flexble and therefore more elastc n the long run, as farmers can then adjust to the new economc sgnals. Regulaton s another factor that restrcts short-run supply. In most countres wth salmon aquaculture, governments have mposed regulatons on producton technology and farmng actvty. Ths s the case for Norwegan salmon producers. Intally, the ndustry was regulated as a result of envronmental concerns and because of concerns about populaton dsperson, as the Norwegan government has a vested nterest n mantanng employment and settlement n rural areas. Farmng lcenses have been one of the man tools used to regulate the ndustry. Although each lcense s a permt to produce, t also restrcts producton possbltes by lmtng fsh densty, locaton, producton volume, depth of cages n the sea, amount of feed, etc. Intally, there were also ownershp regulatons statng that a salmon producer could own only one lcense, but ths restrcton was removed n the 1990s. Ownershp regulatons can explan why there are stll many small- and medum-szed salmon producers operatng n Norway despte over a decade of consoldaton actvtes. If producton capacty depends crtcally on some fxed factors, there wll be lmted opportuntes to respond to ncreasng prces n the short run. Both producton and marketng of farmed salmon are assocated wth sunk costs n the form of nvestment n educaton and tranng of personnel, captal equpment, market research, and advertsements. As the level of nvestment s chosen based on the nformaton avalable before producton begns, t may later turn out to be suboptmal compared wth the realzed output level and market prces. Furthermore, f captal clearly defnes producton capacty and t s beng fully utlzed, there wll be lmted opportunty to respond to ncreasng prces n the short run. Ths s n lne wth other studes, whch have found that captal represents a consderable capacty restrcton n aquaculture producton (Salvanes 1993, Kouka and Engle 1998, Guttormsen 2002, Tveteras 2002). The Model Followng Squres (1987), the most general form of the restrcted proft functon can be specfed as HR (p; z), where HR s the restrcted proft, defned as total revenue mnus total varable cost; p s a vector of postve nput and output prces; and z s a vector of quas-fxed nputs. The functon s restrcted n the sense that frms are assumed to be n a statc equlbrum wth respect to a subset of varable nputs, condtonal upon the exstng levels of the quas-fxed factors. At the observed level of quas-fxed factors, total proft can be wrtten as the sum of the restrcted proft functon less the expendture for the quas-fxed factors, or HT (p, p z, z) = HR (p; z) p z z, where HT s total short-run proft, and p z s the market prce of the quas-fxed factors. The total short-run proft functon descrbes the technology and proft of a temporary equlbrum, where departure from full equlbrum arses as a result of frms employng non-optmal levels of quas-fxed

5 Prce Responsveness of Salmon Supply 429 factors. Long-run equlbrum s acheved by optmally adjustng the quas-fxed nputs untl total profts are maxmzed. Consequently, the defnton of the long run s only a construct to dstngush the temporary short-run equlbrum from the desred long-run equlbrum where total profts are maxmzed wthout pror assumpton of exogenous factors. 4 Because the long-run proft s a specal case of HT, the long-run proft functon can be derved from the total short-run proft functon, usng the full statc equlbrum condton. The condton states that n optmum, the market prce of the quas-fxed factor, p z, s equal to the shadow prce of the quas-fxed factors, HR z (whch s the frst partal dervatve of the restrcted equlbrum proft functon wth respect to the quas-fxed factors). Ths condton can be expressed formally as: p z = HR z (p, z * ), where z * s the optmal level of the quas-fxed factors. Hence, long-run equlbrum mples equalty between the shadow value of the quas-fxed factor and ts market prce. A devaton between p z and HR z (p, z * ) reflects the dfference between the short- and long-run (margnal) proft functons and represents the potental to obtan greater profts n the long run by adjustng the quas-fxed nput levels. When HR z (p, z * ) > p z, the valuaton of an ncremental unt of the quas-fxed factor s hgher than the market rental prce, and a hgher proft s attanable by ncreasng the level of the quas-fxed factor. Alternatvely, when HR z (p, z * ) < p z, the margnal unt of the quas-fxed factor has a low valuaton relatve to ts market value, and t s possble to ncrease profts by reducng the level of the quas-fxed factor. Only when HR z (p, z * ) = p z s there no ncentve for the frm to change the level of the quas-fxed factor, as the equalty mples full equlbrum and long-run proft maxmzaton. For a partcular proft functon, t s possble to solve ths equalty for z * and, by substtutng z * nto HT, to obtan the long-run proft functon: H (p, p z,) = HR (p, z * ) p z z *. Hence, the long-run proft, H, s derved by maxmzng HT wth respect to the quas-fxed nputs, whle holdng output and varable nputs at ther restrcted proft-maxmzng levels. As the restrcted equlbrum approach does not explctly specfy the adjustment cost of the quas-fxed factors, there are no detals about the adjustment path and the frm s nter-temporal behavor n the model. 5 Detaled nformaton on how long t takes for the quas-fxed factor to reach optmum, what ntertemporal path t takes, and what crtera are used n determnng ths adjustment path s not provded (Kulatlaka 1985). However, what can be establshed are the dfferences between the short-run and long-run elastctes, whch accordngly can be used to ndcate substtuton and transformaton possbltes. To estmate the model, we specfy a translog functonal form for the restrcted proft functon. The translog specfcaton s part of a group of flexble functonal forms, whch allows for a complete specfcaton of substtuton patterns among varable and quas-fxed factors. Gven panel data and only one quas-fxed factor, the translog restrcted proft functon becomes: 4 If no dfference can be found between the observed and optmal long-run levels of the quas-fxed factors, the HT model becomes dentcal to the H model (Kulatlaka 1985). A number of testng procedures for the dvergence between observed and optmal z are possble. Bootstrap and jackknfe procedures can be used. Kulatlaka (1985) appled the delta method to form a test for departure between the actual and optmal long-run level of quas-fxed factors. 5 By usng the dynamc equlbrum approach rather than the statc equlbrum approach, the cost of adjustng the quas-fxed factor can be recognzed explctly. The frms are assumed to be contnuously n a dynamc equlbrum, and the approach offers nsghts nto the ntertemporal factor substtuton possbltes. Berndt, Morrson, and Watkns (Chapter 12, 1981) provded a bref revew of an emprcal applcaton based on ths approach.

6 430 Andersen, Roll, and Tveterås ln HR = β ln D + β ln p β ln p ln p (1) r r r + βz ln z βzz ln z2 + βz ln p ln z + β t β t2 + β ln pt + β ln zt, t tt t zt where and j represent nputs and outputs, respectvely; t s a tme trend, ncluded to control for technologcal changes; and D r denotes regon-specfc dummy varables ncluded to account for dfferences n bophyscal factors among the sample farms. The correspondng revenue and cost-share equatons gven by Hotellng s lemma are: j j j S HR = ln ln p = β + β ln p + β ln z + β t, (2) j j z t whch are postve for outputs and negatve for nputs. Restrctons of symmetry and lnear homogenety n prces are drectly mposed through the parameter restrctons: j j j j z j β = β j, β = 1, β = β = β = β = 0. The restrcted proft functon (1) wll be jontly estmated wth the restrcted revenue and cost-share equatons (2), from whch the supply and demand elastctes wll be derved. Partal statc equlbrum own- and cross-prce elastcty can be computed as ε = (β + S 2 S )/S and ε j = (β j + S S j )/S, respectvely. These elastctes are vald only for the level of the quas-fxed factors at whch they are evaluated and do not provde any nformaton on substtuton possbltes among quas-fxed and varable factors. On the other hand, by usng the theoretcal relatonshp between the dervatves of HR and H, frst establshed by Lau (1976) and dscussed further by Brown and Chrstensen (1981), full equlbrum long-run, own-, and cross-prce elastctes of supply and demand can be derved as follows: t ε = 2 2 ( β + S S ) ( βz + SS z ) S S ( β + S S ), 2 zz z z (3) ε j = ( βj + SS j ) ( βz + SS z )( βjz + SS j z ), S S ( β + S2 S ) zz z z (4) ε zz = Sz ( β + S S ), 2 zz z z (5) ε z = Sz( βz + SS z) S ( β + S S ), 2 zz z z (6)

7 Prce Responsveness of Salmon Supply 431 ε z = ( βz + SS z ) ( β + S S ), 2 zz z z (7) where S z lnhr/ lnz = p z z/hr by Hotellng s lemma. The frst term of equatons (3) and (4) s dentcal to the partal statc equlbrum own- and cross-prce elastctes. Consequently, these terms reflect the short-run prce responsveness, where varable nputs and outputs are chosen condtonal on the short-run level of quas-fxed factors. As these condtonal elastctes do not allow for the effects of changes n the quas-fxed factor, ths has to be accounted for n the long run by appendng the changes n demand for the quas-fxed factor to the drect short-run mpact. The second term of equatons (3) and (4) represents the long-run mpact of the quas-fxed factor. Expresson (3) can also be used to demonstrate the Le Chateler prncple. The prncple states that the own-prce elastcty of varable factors decreases n absolute value wth the number of factors that are quas-fxed. Owng to concavty of the restrcted proft functon n the quas-fxed factors, the second term n (3) s negatve for outputs and postve for nputs. Therefore, the restrcted own-prce short-run elastctes are smaller than the unrestrcted long-run elastctes, whch s consstent wth the prncple. Equatons (5) (7) are pure long-run elastctes as the quas-fxed factor s adjustable only n the long run. Equaton (5) represents the own-prce elastcty of the quas-fxed factor, whereas (6) and (7) represent the cross-prce elastctes, or substtuton possbltes, between varable and quas-fxed factors. The system of equatons s estmated usng the generalzed least square technque, whch s equvalent to maxmum lkelhood. Before estmaton, a classcal addtve dsturbance term s appended to the restrcted proft functon and each of the share equatons. As the cost shares sum to unty, one of the proft shares s dropped before estmaton and ts parameters are dentfed through lnear homogenety and symmetry restrctons. The results are nvarant to the choce of equaton dropped. Data The dataset s provded by the Norwegan Drectorate of Fsheres, whch has collected data annually snce 1982 on Norwegan salmon farms producton and proftablty. As all Norwegan salmon farms are oblged by law to report ther annual accounts along wth several frm characterstcs, the dataset s farly extensve. 6 All sze groups and regons along the Norwegan coast are covered n the sample, and more than 50% of the total Norwegan salmon producton s ncluded n most of the sample years. Roughly 80 varables are reported for each farm, ncludng age of the farm, regonal locaton, producton level, nput level, cost, and revenues. Unbalanced panel data wth farm level observatons for the perod are avalable for our research. 7 The data are unbalanced because the same farms are not systematcally reported year after year. The observaton tme span vares from one to 20 years among the ndvdual farms, wth the average farm beng observed for 6.1 years. In total, the dataset conssts of 3,580 observatons, dstrbuted among 6 Before a frm s ncluded n the fnal dataset, ts returned report s subjected to a qualty assessment process, where farms are ncluded f they have been n producton for two precedng years, were n full operaton for the entre perod, and have returned annual accounts of suffcent qualty. 7 The sample years 1982 and 1983 were dropped from the analyss because of dfferences n cost categores.

8 432 Andersen, Roll, and Tveterås Table 1 Summary Statstcs of the Data Feed Labor Salmon Feed Labor HR Revenue Cost Cost Prce Prce Prce Captal Mean 6,664,222 12,878,090 5,160,891 1,053, ,752,981 St. Dev. 9,584,776 17,656,183 7,739,879 1,148, ,237, farms. Summary statstcs are presented n table 1. To estmate the model defned by equatons (1) and (2), we make use of data on output prces, varable nput prces for feed and labor, and a captal stock varable. In addton, a tme trend and regon-specfc dummy varables were added to control for technologcal change and dfferences n bophyscal factors. All varable and quas-fxed nputs ncluded n the model are mplctly assumed to be weakly separable from other possble nputs n the producton process. The varables were defned as follows. Output prce s constructed by dvdng sales revenue by the total quantty of fsh sold. The feed prce s defned as the annual expenses on feed dvded by the quantty used. As we dd not have quantty data for the years , a feed quantty ndex was calculated as the product of the output and the feed converson rato for ths perod (Salvanes 1989). The labor prce s obtaned by dvdng annual labor expenses by hours worked at the farm by owner and workers. Prevous studes have found nput fxtes to be present n Norwegan salmon producton (Salvanes 1993, Tveteras 2002). Consequently, captal s measured n physcal quanttes, where captal equpment such as pens, buldngs, feedng equpment, etc., s represented by the actual replacement value. 8 Emprcal Results Table 2 reports the estmated technology parameters from the translog restrcted proft functon and the related share equatons for feed and labor. 9 Subscrpts f, l, and y represent feed, labor, and the salmon prce, respectvely; z symbolzes captal; and t s a tme trend where 1985 = 1. The D r parameters represent the regon-specfc dummy varables, where the subscrpt specfes the regons Rogaland and Vest- Agder (R), Hordaland (H), Sogn og Fjordane (SF), Møre og Romsdal (MR), Sør-Trøndalag (ST), Nord-Trøndelag (NT), Nordland (N), Troms (T), and Fnmark (F). The regons are lsted accordng to ther locaton south to north, from the southernmost regon of Vest-Agder and Rogaland to the northernmost regon of Fnmark. An R 2 of suggests the proft functon has reasonable explanatory power. Nearly all varables are statstcally sgnfcant, ncludng the trend terms, whch ndcate that t s mportant to account for technologcal change. As expected, the technologcal change s non-neutral. 8 Followng prevous productvty and supply studes n aquaculture, we have treated captal as quasfxed n the short run (Salvanes 1993, Kouka and Engle 1998, Guttormsen 2002, Tveteras 2002). Other nputs, n partcular fngerlngs, could also have served as a quas-fxed factor n the estmaton. Although ths could have been nterestng to nvestgate, there are some data ssues regardng quanttes for fngerlngs that can ntroduce serous measurement errors. Consequently, we have not followed ths route. 9 The share equaton for output was dropped to avod sngularty.

9 Prce Responsveness of Salmon Supply 433 Table 2 Parameter Estmates of the Restrcted Proft System Parameter Estmate Standard Error β f * β l * β y * β ff * β fl * β fy * β ll * β ly * β yy * β z * β zz * β fz β lz β yz β t * β tt * β ft * β lt * β yt * β zt D R * D H * D SF * D MR * D ST * D NT * D N * D T * D F * * Denotes sgnfcance at the 5% level. Wth the estmated parameters from the translog proft functon, we can calculate the sample mean prce elastctes of derved demand and supply usng equatons (3) to (7). The short-run elastctes reported n table 3 are calculated based on the frst term of the rght-hand sde expresson of equatons (3) and (4). The long-run elastctes presented n table 4 are calculated usng the entre expressons n equatons (3) to (7). The own-prce elastcty of supply n table 3 ndcates that the producers ablty to respond to changes n output prces n the short run s neglgble. A 1% ncrease n the output sales prce wll nduce only about a 0.05% ncrease n supply. Hence, n the short run, salmon producers are unable to respond to changes n output prces. In the short run, supply s also unresponsve to changes n nput prces. As expected, there s a postve relatonshp between the sales prce and the use of varable nputs n producton, where nput demand seems qute responsve to changes n output prces. When salmon prce ncreases by 1%, the quanttes of feed and labor ncrease by 0.5% and 1.6%, respectvely. The own-prce elastctes are negatve for both feed and labor, mplyng downward-slopng nput demand schedules.

10 434 Andersen, Roll, and Tveterås Table 3 Short-run Supply and Derved Demand Elastctes Output Prce Feed Prce Labor Prce Salmon Feed Labor Table 4 Long-run Supply and Derved Demand Elastctes Output Prce Feed Prce Labor Prce Captal Prce * Salmon Feed Labor Captal * Captal prce s a component of the captal s proft share, S Z, whch s the bass for calculaton of the elastctes. Although captal prce s not explctly accounted for, t can be derved from Hotellng s Lemma as shown n the dscusson of the model. The results change sgnfcantly when we allow adjustments n the amount of captal. When all nputs can be adjusted, the own-prce of salmon supply s 1.4. Ths suggests that salmon producton s much more prce-responsve n the long run. These results support prevous fndngs that suggested captal s a major capacty restrcton n aquaculture producton (Salvanes 1993, Kouka and Engle 1998, Guttormsen 2002, Tveteras 2002). The cross-prce elastctes suggest that n the long run, an ncrease n output prce ncreases the use of varable nputs. Furthermore, we note that supply s more responsve to nput prces n the long run. Feed prce, n partcular, becomes a restrcton on output, as a 1% ncrease n feed prce wll reduce supply by 0.8%. Ths suggests that the ntroducton of feed quotas, whch have been appled n Norway, s a relatvely effectve tool when one wshes to lmt producton. Also note that nput demand for feed reacts wth almost the same magntude to a change n output prce as output supply, whch emphaszes the relatonshp between feed usage and output. We may nterpret ths n accordance wth a fxed-proporton technology as suggested by Guttormsen (2002). Table 5 presents estmates that measure the dfferences n the effcency and bophyscal factors among the sample regons. The estmates are derved relatve to the most effcent regon, namely Hordaland (H), whch has been normalzed to one. The ratos of these coeffcent estmates provde a drect measure of the relatve dfferences among regons and are calculated as TE = D /D H, where 0 < 1 H. The estmates reveal that producton levels are lower n the northern regons. The colder sea temperatures n the north make t reasonable to assume that the bologcal producton process wll be slower, leadng to lower productvty. As llustrated n table 5, the most northern regon s operatng at only about 75% of the level of the most effectve regon, whch s located much farther south.

11 Prce Responsveness of Salmon Supply 435 Table 5 Regonal Dfferences n Effcency and Bophyscal Factors TE Estmate p-value TE R * TE H TE SF TE MR * TE ST * TE NT * TE N TE T * TE F * * Denotes sgnfcant dfferences between actual and optmal effcency at the 5% level. Concludng Remarks There s a rch lterature on productvty growth n salmon aquaculture, but few studes have addressed supply responsveness. Ths s of nterest because of the technologcal nnovatons that have nfluenced the producton process n salmon farmng. In ths artcle, we estmated a restrcted proft functon for Norwegan salmon farms for the perod 1985 to Based on the restrcted proft functon, we derved both demand and supply elastctes, takng nto account the dfferences n factor adjustments n the short and long run. In accordance wth our pror belefs, the results ndcated that salmon producers have lmted possbltes to respond to prce changes n the short run. The supply elastcty of salmon s close to zero, mplyng that there s no mmedate response to output prce changes. Furthermore, both feed and labor own-prce elastctes are nelastc n the short run. In the long run, the supply elastcty ncreases to 1.4, ndcatng that producton has become flexble. Prce responsveness also ncreases relatve to nput prces, n partcular for feed prce, where the own-prce elastcty ncreases from 0.5 to 1.2. Wth lmted short-run responsveness, there wll be a lag n the adjustment of output to the optmum level, gven exogenous prces. The delayed response may cause an overshootng n producton n the long run, whch wll depress prces, causng a fall n profts. Ths recurrng pattern goes a long way towards explanng the cyclcal varatons around the proft trend. Consequently, the observed volatlty n ndustry profts mght be explaned by the combnaton of hgh responsveness n the long run and lmted responsveness n the short run. If the ndustry remans compettve, wth many producers, t s lkely that profts wll contnue to be volatle, as ndvdual producers wll have lmted ncentves to restrct supply when prces are hgh. References Asche, F Trade Dsputes and Productvty Gans: The Curse of Farmed Salmon Producton? Marne Resource Economcs 12(1): _ Farmng the Sea. Marne Resource Economcs 23(4):

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13 Prce Responsveness of Salmon Supply 437 Steen, F., F. Asche, and K.G. Salvanes The Supply of Salmon n the EU: A Norwegan Aggregated Supply Curve. Foundaton for Research n Economcs and Busness Admnstraton, SNF Workng Paper 53/97, Centre for Fsheres Economcs, Bergen, Norway. Tveteras, R Producton Rsk and Productvty Growth: Some Fndngs for Norwegan Salmon Aquaculture. Journal of Productvty Analyss 12: _ Industral Agglomeraton and Producton Cost n Norwegan Salmon Aquaculture. Marne Resource Economcs 17(1):1 22. Tveteras, R., and G.E. Battese Agglomeraton Externaltes, Productvty and Techncal Ineffcency. Journal of Regonal Scence 46: Tveteras, R., and A. Heshmat Patterns of Productvty Growth n the Norwegan Salmon Farmng Industry. Internatonal Revew of Economcs and Busness 49(3):