Leaning and Technology Spillove: Poductivity Convegence in Nowegian Salmon Aquacultue Ragna Tveteås Stavange College & Foundation fo Reseach in Economics and Business Administation P.O. Box 2557 Ullandhaug, N-4004 Stavange, NORWAY Phone: 47 51 831640, Fax: 47 51 831550 E-mail: Ragna.Tveteas@os.his.no Shot pape vesion fo pesentation at the annual meeting of the Ameican Agicultual Economics Association in Nashville, Tennessee, August 1999 Peliminay vesion May 1999 Abstact An econometic analysis of poductivity convegence in Nowegian salmon aquacultue is undetaen. We also test fo the effects of leaning and extenal industy infastuctue capital. Empiical evidence fo eduction in poductivity diffeentials is found, but the estimated models also povide indications of moe pemanent diffeences in poductivity and thei undelying souces. Copyight 1998 by Ragna Tveteås. All ights eseved. Reades may tae vebatim copies of this document fo non-commecial puposes by any means, povided that this copyight notice appeas on all such copies. 1
1. Intoduction This pape povides an econometic analysis of poductivity convegence in the Nowegian salmon faming industy, which is a paticulaly inteesting case study fo seveal easons. Fist, it is a young industy whee lage scale poduction stated in the late 1970s and most fims wee established duing the 1980s. Second, it has expeienced majo changes in the poduction technology duing its shot lifetime due to innovations in e.g. poduction equipment, feed technology, salmon genetics, and medical teatment. 1 Thid, diffeent coastal egions enteed the industy at diffeent stages and faced diffeent technological and institutional oppotunities and obstacles when they enteed. Though poduction pactice fams accumulates nowledge, and olde fams ae expected to be moe efficient than new fams due to longe poduction expeience. Anothe facto is the ate of acquisition of new capital equipment by new and olde fams. New fams may use moe ecent technologies due to high eplacement costs fo physical capital. The effect of own poduction expeience may also be mitigated by nowledge spillove, if nowledge capital has a public goods popety in aquacultue. In this pape it is agued that inta-egional nowledge spilloves dominate inte-egional spilloves because, in addition to histoical diffeences and geogaphical baies, industy infastuctue such as fame oganizations and public extension sevices ae oganized at the egional level. These factos leads to highe costs associated with tansmitting nowledge acoss egions than within egions. Hence, they should act as an impediment to apid poductivity convegence acoss egions. Futhemoe, it has been asseted that spatial clusteing of poduces facilitates the development of a egional industy-specific infastuctue, which allows the fims to exploit extenal economies of scale. The degee of spatial clusteing should consequently be taen into account in models of poductivity convegence. The esults fom this analysis also has implications fo the public egulation of the industy, since the Nowegian govenment has egulated the egional distibution of salmon fams. Spatial egulation of poduction is pesent in many counties, fo example in the agicultual secto in the Euopean Union, as a cental element in egional income edistibution policies. One may as if this spatial egulation has lead to efficiency losses in salmon aquacultue. In the ealy yeas of the data peiod one obseved substantial diffeences in aveage poductivity between egions. Wee these diffeences, and hence efficiency losses, tansitoy o pemanent? Biophysical conditions may give ise to pemanent poductivity 2
diffeences. Howeve, thee may also have been moe tansitoy poductivity diffeentials in ealie yeas due to diffeences in poduction expeience and technology, which can be eliminated though leaning and eplacement of capital equipment. Finally, shaing of industy infastuctue capital may give ise to extenal economies of scale. The pesence of extenal effects suggests a ole fo govenment egulation, povided that egulatos have sufficient nowledge about the natue of the extenalities. We employ an unbalanced panel data set with a total of 2738 obsevations on 577 fams obseved duing the 1985-1995 peiod. The fams ae obseved fom one to eleven yeas. Infomation on the age of the fam, egional location, poduction level, input levels, costs and evenues ae included in the data set. Seveal econometic tanslog poduction model specifications ae estimated to test the hypotheses on poductivity convegence. An extension of the standad time tend model that allows fo egion-specific ates of technical change is estimated. We also estimate a moe flexible time dummy model that allows fo discontinuous egion-specific technical change. Finally, we estimate model specifications with intenal and extenal factos which can influence poductivity. Fam age is implemented to captue potential leaning-by-doing effects. The extenal factos we account fo is egional industy size (measued by employment), and fam density in the egion. We asset that the possibility fo shaing of industy infastuctue capital and exploiting extenal economies of scale is closely lined with these two egional industy indicatos. 2. Discussion of Issues Related to Industy Infastuctue and Leaning In the empiical analysis we compae the pefomance of eight egions. These egions ae listed accoding to thei location on the noth-south axis, fom the southenmost county of Rogaland (R) to the nothenmost counties of Toms and Finnma (T&F). Thee ae seveal easons fo using a egional division fo the Nowegian salmon faming industy. Fist, egions have diffeent biophysical conditions. This applies paticulaly to the sea tempeatue and the wate exchange - two impotant deteminants of salmon gowth and motality. The aveage sea tempeatue is significantly lowe in the nothen counties than in the southen counties. The gowth ate of salmon inceases with sea tempeatue. On the othe hand, due to tidal cuents the wate exchange is highe in the nothen egions than in the southen egions, implying that the supply of clean wate and oxygen is highe in nothen egions. 1 See Dietichs (1995) fo a discussion of the pocess of technological change in the industy. 3
Industy-specific infastuctue is too a lage extent oganized in egional units. This is the case fo govenment agencies that monito and assist fish fams on disease teatment, envionmental issues (e.g. fam location) and othe mattes which affect fam pefomance. The fish fames own industy association has also been oganized in egional units. This oganization is involved in taining pogams and dissemination of nowledge to fish fames. Disease outbeas and algae blooms tend to be spatially coelated. Diseases ae usually fist tansmitted to neighboing fams, and the pobability of contagion is positively elated to the density of fams. The industy has expeienced that disease losses ae not evenly distibuted along the Nowegian coast, but has been concentated in cetain egions. Regions enteed the industy at diffeent stages, which means that thee ae cossegional diffeences in aveage fam age. If thee ae leaning-by-own-expeience effects pesent then age diffeences may lead to poductivity diffeences. Thee ae substantial diffeences in the size of the egional industies and the spatial concentation of poduction. This is impotant if thee is potential fo shaing industy infastuctue capital o extenal economies of scale. 23 Souces of extenal economies of scale ae indivisibilities o nonexclusiveness associated with tangible and nontangible capital inputs, such as physical industy infastuctue capital, R&D, nowledge spilloves (i.e. leaning fom othes), and specialized human capital. Fo the fim shaing of these types of capital leads to savings on mateials and labo inputs, and a educed need fo intenal investments in capital equipment. In this pape we ae concened about the effects of leaning on poductivity diffeentials. We use fam age to captue the effect of own leaning fom own poduction expeience. Howeve, the age vaiable may also account fo othe influences upon poductivity. If eplacement of old capital equipment is costly the fam age vaiable may also captue capital vintage effects. Fo this paticula industy thee is pobably also a negative elationship between fam age and the quality of the fam site, since olde fams tended to be located at moe shelteed sites which had lowe biopoductivity(johannessen et al.). Poduces may not only lean fom own poduction expeiences, but also fom othe poduces. The extent of extenal nowledge spilloves should be incease with fam density, 2 See Caballeo & Lyons (1990), Baltagi & Pinnoi (1995) Moison & Scwatz (1996), Moison & Siegel (1998) and Segoua (1998) fo discussions of these issues, and fo empiical testing of the contibution of public capital and extenal economies of scale. 3 Extenal economies of scale is pesent fo an industy with constant intenal (o pivate) economies of scale if a doubling of inputs by all fims togethe moe than doubles thei output. 4
which is implemented in one of the model specifications. Finally, poduces may lean fom othe agents which is a pat of the industy infastuctue. In the case of salmon faming feed manufactues, veteinaians, salmon fingeling poduces and eseaches may be souces of nowledge on diffeent aspects of the poduction pocess. 3. Empiical Model Specifications In this pape we estimate poduction functions to test fo convegence and the effects of diffeent industy chaacteistics on poductivity. 4 In one class of models the specification of technical change is an extension of Conwell, Schmidt & Sicles' (CSS) specification. 5 We denote this class CSSE models: ln y it = α t α ln x α D t, it α t 2 j j, it, it D t α ln x 2 α t 3 ln x D t 3 h α ln x t, it t ( FC, RC;α,α ) y is salmon output, x is input ( = capital, fish, feed, labo, mateials), t is a time tend vaiable (t = 1 in 1985), and D is egion-specific effects (egion-dummies), = (R, H, SF, MR, ST, NT, N, T&F). Subscipts i and t denotes fam and time, espectively. A tem h(fc, RC) is also added, whee FC is a (vecto of) fam chaacteistics and RC is egion chaacteistics which influences poductivity. The technical change specification in the CSS model is a special case of the above model with the tems involving the thid-ode time tend vaiable excluded (i.e. α t = 0,t). The above model can be divided into fou pats. Fist, the egion-specific effect ( α ) which gives ise to pemanent output diffeences. Second, the pue input level effect (i.e. α ln x, it α ln x it x j, ln, ). Thid, the input-biased technical change effect (i.e. α t ln x, it j it t ) which is influenced both by the input levels and the time peiod. Fouth, the egion-specific technical change effect (i.e. α Dt α Dt 2 α Dt 3 ). When we FC RC t t 2 t 3 compae two egions and s fom time peiod t to t1 elative output will be influenced both by elative changes in output levels x and x s and the egion-specific technical change effects. The following time-dummy model povides a moe flexible specification of technical change than the CSS time-tend model (heeafte denoted TD):, 4 Salvanes (1989; 1993) and Bjøndal and Salvanes estimate cost functions fo the Nowegian salmon industy. 5 Howeve, Conwell, Schmidt and Sicles specified a poduction fontie model with a half-nomal andom tem in addition to the usual white noise eo tem. 5
= ln yit ln x, it j ln x j, it ln x, it t t ln x, it Dt α α D D h t t t α ( FC, RC;α,α ) FC RC whee D t is time-specific effects (time-dummies), t = 1985,, 1995. The above model allows discontinuous shifts in technical change between yeas within a egion. This seems plausible, since it is difficult to povide a pioi suppot fo the smooth technical pogess function implied by the time tend model. To captue the effects of fam-specific effects due to biophysical chaacteistics and quality of human capital an extension of the CSSE model specification with andom famspecific effects added was also estimated (denoted CSSE-RE). 6 Fam age (AGE) is included in one model specification (denoted CSSE-AGE). Due to fams' leaning-by-own-expeience a positive elationship is expected between age and poductivity. Howeve, as mentioned ealie, thee may also be capital vintage and fam site effects woing in the opposite diection. To account fo density dependent extenal effects between fams the numbe of fams pe squae ilomete of sea aea (FSR) in the egion is included in one of the model specifications (denoted CSSE-FSR). The poximity of fams can influence poductivity in seveal espects. High fam density should enhance nowledge tansmission. It should also lead to a moe efficient use of industy capital equipment, such as vessels fo tanspotation of live fish, slaughte- and pocessing facilities. Hence, investments in capital equipment is expected to decline fo each individual fam due to inceased possibility fo shaing. This implies that thee ae extenal economies of scale associated with an incease in the numbe of fams in a egion. On the othe hand, fish disease extenalities between fams is expected to incease with highe fam density, leading to lowe expected poductivity. Total egional industy employment (RL) is also included in one specification (denoted CSSE-RL). This vaiable may captue extenal economies of scale o the availability of industy-specific capital. It can be viewed as a poxy fo human (intangible) capital in the egional industy, but is pobably also coelated with the egional industy's physical capital. White noise eo tems ae added to all models. Heteosedasticity is adjusted fo by means of White s (1980) pocedue. α, 6 See e.g. Bege & Blastad (1989) and Johannessen fo documentation of the poduce heteogeneity in salmon faming. Suveys of a lage numbe of fam sites have shown that thee ae consideable diffeences in the biophysical poductivity. 6
4. Empiical Results 7 The lagest fams ae found in egion H (see Table 2 fo full egion names), whee the sample aveage salmon output is 534 tonnes, while the smallest fams ae located in egion NT, with an aveage poduction of 355 tonnes. The aveage age of the sample fams is 9.6 yeas. The longest aveage poduction expeience in the sample is found in the egions ST (12.6 yeas), MR and H (both 11.2 yeas), while the fams in the nothenmost egions of T&F and N have the shotest aveage poduction expeience (6.6 and 7.9 yeas, espectively). Region H has the highest employment - thee times highe than egion R, which has the smallest employment (1151.72 and 342.23 thousand man-hous, espectively). Thee ae lage coss-egional vaiations in fam density, as measued by the numbe of fams pe squae m of sea aea. In the high-density egion H thee ae 0.035 fams pe squae m, while the lowdensity egions N and T&F have only 0.005 and 0.004 fams pe sq.m, espectively. This means that the fam density in egion H is almost nine times highe than in N and T&F. Deived elasticities fom the estimated models ae pesented in Table 1. In all models fish feed (F) tuns out to be the most impotant input as measued by the feed elasticity, which anges fom 0.48 to 0.51 acoss the models. Fish input (I) is the second most impotant input in tems of output elasticity, which anges fom 0.304 to 0.311. Labo (L), mateials (M), and paticulaly capital (K) ae much less impotant. The output elasticity with espect to these inputs is geneally aound o less than 1/10 of the feed elasticity.the mean etuns to scale (RTS) is vey simila acoss models; it anges fom 0.92 to 0.93. This implies that the mean fam in the panel opeated at a sufficiently lage scale to exhaust economies of scale. The fist model to be estimated is the CSS poduction function. Accoding to both t- atios and joint tests the use of egion-specific technical change paametes is appopiate. The standad poduction function specification with pooled intecept and technical change is fimly ejected at conventional significance levels by a lielihood-atio test, with an estimated test statistic of 101.40 (21 degees of feedom). A poduction function with heteogeneous intecepts but pooled technical change paametes is also ejected with an L-R test statistic of 57.32 (14 df). Next, the extended CSS model (CSSE) was estimated. The addition of thid-ode egion-specific technical change paametes tuns out to be appopiate. An L-R test of the 7 Due to space estictions seveal tables in the full pape vesion is not pesented hee, but available fom the autho upon equest. 7
CSSE vesus the esticted CSS model povides a test statistic of 60.48 (8 df), thus ejecting the esticted model at conventional significance levels. To account fo fam-specific effects the CSSE model was extended to include a andom fam-specific eo component (model CSSE-RE). The estimates of the obsevation- and fimspecific vaiance in the CSSE-RE model ae σ 2 u = 0.4146 and σ 2 η = 0.0947, espectively. Fom Table 2 one can see that the inclusion of a andom effect lead to some changes in elasticity estimates, although not damatic. Next, we examine the estimated CSSE-AGE model, whee a fist- and second-ode logaithmic tansfomation of fam age is added to the CSSE model. An L-R test of CSSE- AGE vesus CSSE suppots the extension of the model, with a test statistic of 2(806.10-814.64)=17.08 (2 df). The inclusion of an age effect in the model only lead to small changes in the elasticity estimates. Howeve, the paamete estimates associated with the age tems did not povide suppot fo a positive leaning effect on poductivity, as both tems had negative signs. The elasticity of output with espect to fam age is -0.023 fo the sample mean fam. This leads to the conclusion that negative capital vintage and fam site effects discussed in the pevious section dominate the leaning effect. We then tun to the models with egional chaacteistics included. Fist we examine the model with total egional salmon industy employment tems added (CSSE-RL). This extension of the model is also suppoted by an L-R test, with a test statistic of 2(806.10-826.91)=41.62 (2 df). Accoding to the estimated model industy size has a significant positive impact on poductivity. Fo the sample aveage fam the elasticity of output with espect to egional industy employment is 0.299 (!). Regional fam density also has a significant impact on poductivity, accoding to the estimated model (CSSE-FSR). Two fam density tems ae added to the CSSE model in this specification, ln FSR and (ln FSR) 2. The L-R test suppots the inclusion of the fam density tems with a test statistic of 2(806.10-817.58)= 22.96 (2 df). The elasticity of output with espect to fam density is 0.152 fo the sample mean fam. Howeve, the effect is ambiguous, since the second ode fam density tem ((ln FSR) 2 ) has a negative coefficient. This may indicate that fo low values an incease in fam density is beneficial fo fam poductivity, possibly due to inceased shaing of capital equipment, human capital and nowledge, while fo highe values a futhe incease in fam density is hamful due to negative disease extenality effects. 8
Next, we estimated a model with egion-specific time dummies (model TD) to allow fo highe flexibility in the ate of technical change. Accoding to both estimated t-atios and joint tests this specification is appopiate. A Wald test fimly ejects identical time-specific effects acoss egions with a test statistic of 328.4 (80 df) and p-value of 0.000. Fam age was also added to the time dummy model in one specification (TD-AGE). As fo the CSSE model we find a significant negative age effect, thus einfocing the above conclusions. Figue 1 plots the pedicted output by egion ove the 1985-1995 time peiod fo fams employing sample mean input levels based on the TD model estimates. We see that the flexible TD specification is able to captue the volatility of poductivity gowth in Nowegian salmon faming. Fo example. the egion Sø-Tøndelag (ST) expeienced an outbea of the fish disease Fuunculosis in 1985-86, which lead to huge losses. Fom the figue one can see that this is captued by the TD model. Accoding to figue 1 poductivity seems to convege fom 1985-86 to the middle of the data peiod. But theeafte poductivity diffeentials seem to have stabilized o possibly diveged again. To analyze this issue futhe we examine the elative poductivity estimates in table 2. Accoding to the estimates based on the TD model the standad deviation of poductivity was 5.94 in the fist data yea, 1985. Relative poductivity diffeentials peaed in 1986, with a standad deviation of 10.52. Theeafte elative poductivity diffeences declined, although not monotonously, and eached a minimum in 1991. Since then the elative poductivity diffeentials seem to have stabilized at lowe levels than in the fist half of the data peiod. 5. Summay and Conclusions This pape has examined whethe poductivity conveged acoss egions in Nowegian salmon aquacultue fom 1985 to 1995. Seveal competing pimal models of technical change wee estimated. Accoding to the most cedible model poductivity diffeentials have declined duing the data peiod. Howeve, thee ae still substantial diffeences in poductivity as the mean fam in the least poductive egion (Rogaland) was 10 % less poductive than the mean fam in the most poductive egion (Nod-Tøndelag) in 1995. One cannot find a consistent poductivity patten along the noth-south axis, as the southenmost egion is the least poductive, followed by the two nothenmost egions in 1995. 9
We do not find a positive elationship between poduction expeience as measued by fam age and poductivity. On the contay, olde fams seems to be less poductive, suggesting that negative capital vintage and site effects dominate positive leaning effects. Hence, it seems lie fams which enteed the industy at late stages wee not seveely disadvantaged due to lac of own poduction expeience, but compensated fo this by leaning fom othe industy agents and investing in the newest technologies. Evidence is found fo the contibution of industy-specific infastuctue capital to fam poductivity. The size of the egional industy and fam density both have a significant positive effect. Howeve, the empiical esults suggest that fo fam density negative fish disease extenalities may dominate with high densities. The Nowegian govenment has influenced the egional distibution of salmon fams though its egulations. This pape has shown that egional location of fams may influence the industy s maginal cost cuve. Thee exists is a potential fo spatial edistibution of fams that can lead to a downwad shift in the industy s supply cuve. Howeve, based on the findings hee one should also tae into account density-dependent effects of elocation and effects on egional extenal economies of scale. Accoding to ou esults shifting poduction between two egions will affect the poductivity in both egions, but in opposite diections. Although govenment egulation may have lead to an aveage poductivity which is lowe than the potential, deegulation may not necessaily lead to an efficient spatial distibution of poduction. With a lage numbe of independent fams extenal economies of scale and disease extenalities will not be fully intenalized by pivate decision maes, leading to inefficient outcomes. Hence, thee is a ole fo govenment egulation which taes these extenalities into account. This pape has povided new evidence on poductivity convegence and the effects of leaning and industy infastuctue on poductivity in Nowegian salmon aquacultue. Futue analyses should aim to decompose and measue futhe the effects of biophysical diffeences, fam-specific factos and egional industy infastuctue on poductivity diffeentials. 10
Table 1. Estimated Elasticities* Model CSS CSSE CSSE-AGE CSSE-RA CSSE-FSR CSS-RL TD TD-AGE Mean St.Dev Mean St.Dev Mean St.Dev Mean St.Dev Mean St.Dev Mean St.Dev Mean St.Dev Mean St.Dev E L 0.047 0.052 0.054 0.051 0.055 0.052 0.064 0.057 0.057 0.052 0.055 0.051 0.055 0.068 0.055 0.069 E F 0.510 0.095 0.504 0.095 0.499 0.094 0.480 0.086 0.503 0.094 0.500 0.094 0.498 0.106 0.493 0.104 E I 0.310 0.056 0.311 0.057 0.310 0.056 0.304 0.057 0.305 0.057 0.308 0.056 0.304 0.076 0.304 0.075 E K 0.023 0.020 0.021 0.021 0.026 0.022 0.026 0.024 0.023 0.020 0.023 0.020 0.022 0.027 0.027 0.028 E M 0.044 0.038 0.042 0.040 0.043 0.039 0.049 0.043 0.042 0.040 0.043 0.041 0.044 0.046 0.045 0.046 RTS 0.934 0.056 0.932 0.056 0.934 0.056 0.923 0.055 0.929 0.056 0.929 0.055 0.922 0.047 0.924 0.047 TC** 0.025 0.037 0.037 0.048 0.039 0.048 0.040 0.050 0.030 0.053 0.022 0.048 0.051 0.096 0.052 0.095 TC_PURE** 0.041 0.041 0.054 0.053 0.056 0.052 0.057 0.054 0.047 0.058 0.039 0.052 0.045 0.084 0.047 0.083 TC_NONUT** -0.017 0.019-0.017 0.019-0.017 0.019-0.018 0.019-0.016 0.019-0.017 0.019 0.006 0.065 0.006 0.064 TFP 0.023 0.054 0.031 0.065 0.033 0.065 0.032 0.067 0.028 0.067 0.023 0.061 0.044 0.107 0.046 0.106 * E = Elasticity of output with espect to input ( = F, I, K, L, M), RTS = Retuns To Scale, TC = ate of Technical Change, TC_PUR = ate of input-neutal technical change, TC_NONUT = ate of input-neutal technical change, TFP = ate of Total Facto Poductivity gowth. ** Technical change estimates include 1985 fo the CSS and CSSE models, but not fo the TD models. Table 2. Estimated Poductivity of Each Region Relative to Most Poductive Region 1985-95*, ** CSSE model estimates TD model estimates Yea R H SF MR ST NT N T&F Mean St.dev. R H SF MR ST NT N T&F Mean St.dev. 1985 100.00 94.48 95.75 94.72 81.73 86.87 94.23 79.58 90.92 6.83 95.60 93.37 100.00 93.54 87.95 85.28 95.19 80.50 91.43 5.94 1986 100.00 94.01 93.43 92.11 81.20 87.62 90.78 71.19 89.79 6.45 100.00 89.76 80.35 85.15 63.27 81.84 83.93 70.44 81.84 10.52 1987 100.00 94.11 93.24 91.04 82.25 88.88 90.27 81.11 90.11 5.80 100.00 97.76 90.14 89.81 87.06 80.82 85.42 81.05 89.01 6.58 1988 100.00 94.72 94.64 91.20 84.56 90.61 91.91 84.76 91.55 4.84 100.00 95.18 94.36 93.83 83.87 86.39 89.80 74.14 89.70 7.60 1989 100.00 95.81 97.16 92.32 87.86 92.76 95.04 89.60 93.82 3.73 97.37 95.02 100.00 90.78 86.00 94.01 94.91 94.10 94.02 3.93 1990 99.69 97.03 100.00 93.90 91.58 94.99 98.72 94.66 96.32 2.83 94.30 87.13 100.00 90.35 87.24 91.87 98.96 94.02 92.98 4.52 1991 96.55 95.83 100.00 93.23 92.91 94.74 99.56 96.58 96.18 2.45 97.85 96.74 97.23 97.24 93.03 92.20 100.00 96.83 96.39 2.39 1992 93.94 95.38 99.90 93.17 94.47 95.08 100.00 97.53 96.18 2.48 89.06 91.26 89.90 88.74 90.93 85.05 95.69 100.00 91.33 4.30 1993 92.52 96.36 99.91 94.20 96.59 96.69 100.00 97.39 96.71 2.38 91.50 96.10 100.00 87.97 91.23 97.72 92.51 88.51 93.19 4.06 1994 92.68 99.22 99.93 96.50 99.33 100.00 99.21 95.78 97.83 2.44 93.09 100.00 96.25 95.70 98.63 97.01 96.06 89.74 95.81 2.99 1995 89.83 99.01 94.56 95.04 97.34 100.00 92.17 87.48 94.43 4.11 89.99 98.27 96.58 94.75 98.20 100.00 95.86 93.12 95.85 3.00 * Fo each yea the pedicted output of the sample mean fam of each egion is divided by the output of the sample mean fam in the egion with the highest poductivity. ** Full egion names: R=Rogaland, H=Hodaland, SF=Sogn og Fjodane, MR= Møe og Romsdal, ST=Sø-Tøndelag, NT=Nod-Tøndelag, N=Nodland, T&F=Toms & Finnma. 11
1.4 1.3 1.2 1.1 1 0.9 0.8 R H SF MR ST NT N T&F 0.7 0.6 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 Figue 1. Pedicted Output fom Time Dummy Model (TD) by Region 1985-95 fo Fam Employing Sample Mean Input Levels 12
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