Abstract
Although fishing is regarded as a risky production process, limited attention has been given to the impact of input factor use on production risk. Production risk is particularly important for fisher behavior and fisheries management when input factors are restricted, since input restrictions can influence production risk in addition to output levels. This paper investigates production risk by estimating production and risk functions for the main vessel groups in the Norwegian fishing fleet. The results indicate that production risk is present and that the effect of input use on production risk varies between vessel groups. Capital has a risk-reducing effect in the ocean fleet, but are risk-increasing in coastal fisheries. Fuel use is found to be a risk-increasing input for most of the vessel groups, while labor use is risk-reducing.
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Notes
The coastal fleet comprises vessels smaller than 28 m.
There are also other vessel groups of much less economic importance such as shrimp trawlers and reduction fisheries.
There were some adjustments in how the groups were defined in 1998 and 2003, mostly within what we define as the coastal groups.
The smallest coastal vessels in all fisheries do not have IFQs, but are regulated open access for all species.
Structural break tests indicate that none of these groups can be combined.
As it is mandatory to land all fish that is being brought onboard, this virtually ensure that most whitefish trips are multi-species.
The models were also estimated allowing for structural breaks on the slope parameters. However, the structural breaks captured by the time dummies seem to capture the structural shifts.
This is in line with most productivity studies of Norwegian fisheries which use three or four inputs.
The confidence intervals of the fuel elasticity coefficients for coastal vessels and trawlers do not overlap.
References
Alam MA, Guttormsen A, Roll KH (2019) Production risk and technical efficiency of tilapia aquaculture in Bangladesh. Mar Resour Econ 34:123–141. https://doi.org/10.1086/704129
Asche F, Roll KH (2018) Economic inefficiency in a revenue setting: the Norwegian whitefish fishery. Appl Econ 50:6112–6127. https://doi.org/10.1080/00036846.2018.1489502
Asche F, Tveterås R (1999) Modeling production risk with a two-step procedure. J Agric Resour Econ 24:424–439. https://doi.org/10.2307/40987031
Asche F, Bremnes H, Wessells CR (1999) Product aggregation, market integration, and relationships between prices: an application to world salmon markets. Am Agric Econ Assoc 81:568–581
Asche F, Gordon DV, Hannesson R (2002) Searching for price parity in the European whitefish market. Appl Econ 34:1017–1024. https://doi.org/10.1080/00036840110061965
Asche F, Gordon DV, Jensen CL (2007) Individual vessel quotas and increased fishing pressure on unregulated species. Land Econ 83:41–49. https://doi.org/10.2307/27647745
Asche F, Bjørndal T, Gordon DV (2009) Resource rent in individual quota fisheries. Land Econ 85:279–291. https://doi.org/10.4256/mio.2010.0010
Bronnmann J, Ankamah-Yeboah I, Nielsen M (2016) Market integration between farmed and wild fish: evidence from the whitefish market in Germany. Mar Resour Econ 31:421–432
Cojocaru AL, Asche F, Pincinato RBM, Straume H-M (2019) Where are the fish landed? An analysis of landing plants in Norway. Land Econ 95:246–257
Cunningham S, Bennear LS, Smith MD (2016) Spillovers in regional fisheries management: do catch shares cause leakage? Land Econ 92:344–362. https://doi.org/10.3368/le.92.2.344
Eggert H, Martinsson P (2004) Are commercial fishers risk-lovers? Land Econ 80:550–560. https://doi.org/10.2307/3655810
Eggert H, Tveterås R (2004) Stochastic production and heterogeneous risk preferences: commercial fishers’ gear choices. Am J Agric Econ 86:199–212. https://doi.org/10.1111/j.0092-5853.2004.00572.x
Gordon DV, Hannesson R (1996) On prices of fresh and frozen cod fish in European and U.S. markets. Mar Resour Econ 11:223–238. https://doi.org/10.1086/mre.11.4.42629167
Guttormsen AG, Roll KH (2011) Technical efficiency in a heterogeneous fishery: the case of Norwegian groundfish fisheries. Mar Resour Econ 26:293–307. https://doi.org/10.5950/0738-1360-26.4.293
Guttormsen AG, Roll KH (2014) Production risk in a subsistence agriculture. J Agric Educ Ext 20:133–145. https://doi.org/10.1080/1389224X.2013.775953
Hannesson R (2013) Norway’s experience with ITQs. Mar Policy 37:264–269. https://doi.org/10.1016/j.marpol.2012.05.008
Hannesson R (2017) Fish quota prices in Norway. Mar Resour Econ 32:109–117
Harper S, Bevacqua D, Chudnow R et al (2012) Fuelling the fisheries subsidy debate: agreements, loopholes and implications. Fish Res 113:143–146
Harvey AC (1976) Estimating regression models with multiplicative heteroscedasticity. Econometrica 44:461–465
Holland DS, Speir C, Agar J et al (2017) Impact of catch shares on diversification of fishers’ income and risk. Proc Natl Acad Sci 114:9302–9307. https://doi.org/10.1073/pnas.1702382114
Isaksen JR, Hermansen Ø, Flaaten O (2015) Stubborn fuel tax concessions: the case of fisheries in Norway. Mar Policy 52:85–92
Isik M, Khanna M (2003) Stochastic technology, risk preferences, and adoption of site-specific technologies. Am J Agric Econ 85:305–317
Just RE, Pope RD (1978) Stochastic specification of production functions and economic implications. J Econom 7:67–86
Just RE, Pope RD (1979) Production function estimation and related risk considerations. Am J Agric Econ 61:276–284. https://doi.org/10.2307/1239732
Kasperski S, Holland DS (2013) Income diversification and risk for fishermen. Proc Natl Acad Sci 110:2076–2081. https://doi.org/10.1073/pnas.1212278110
Khan A, Guttormsen A, Roll KH (2018) Production risk of pangas (Pangasius hypophthalmus) fish farming. Aquac Econ Manag 22:192–208. https://doi.org/10.1080/13657305.2017.1284941
Kroetz K, Sanchirico JN, Lew DK (2015) Efficiency costs of social objectives in tradable permit programs. J Assoc Environ Resour Econ 2:339–366. https://doi.org/10.1086/681646
Kumbhakar SC (2001) Risk preferences under price uncertainties and production risk. Commun Stat Theory Methods 30:1715–1735. https://doi.org/10.1081/STA-100105694
Kumbhakar SC (2002a) Specification and estimation of production risk, risk preferences and technical efficiency. Am J Agric Econ 84:8–22. https://doi.org/10.2307/1245020
Kumbhakar SC (2002b) Risk preference and productivity measurement under output price uncertainty. Empir Econ 27:461–472. https://doi.org/10.1007/s001810100091
Kumbhakar SC, Tsionas EG (2010) Estimation of production risk and risk preference function: a nonparametric approach. Ann Oper Res 176:369–378. https://doi.org/10.1007/s10479-008-0472-5
Kumbhakar SC, Tveterås R (2003) Risk preferences, production risk and firm heterogeneity. Scand J Econ 105:275–293. https://doi.org/10.1111/1467-9442.t01-1-00009
Lewbel A (1996) Aggregation without separability: a generalized composite commodity theorem. Am Econ Rev 86:524–543
Lien G, Kumbhakar SC, Hardaker JB (2017) Accounting for risk in productivity analysis: an application to Norwegian dairy farming. J Product Anal 47:247–257. https://doi.org/10.1007/s11123-016-0482-2
Munro G, Sumaila UR (2002) The impact of subsidies upon fisheries management and sustainability: the case of the North Atlantic. Fish Fish 3:233–250
Nøstbakken L (2006) Cost structure and capacity in the Norwegian pelagic fisheries. Appl Econ 38:1877–1887. https://doi.org/10.1080/00036840500427197
Ogundari K, Akinbogun OO (2010) Modeling technical efficiency with production risk: a study of fish farms in Nigeria. Mar Resour Econ 25:295–308
Sarker MAA, Arshad FM, Alam MF, Mohamed ZA, Khan MA (2016) Stochastic modeling of production risk and technical efficiency of Thai koi (Anabas testudineus) farming in Northern Bangladesh. Aquac Econ Manag 20:165–184. https://doi.org/10.1080/13657305.2016.1156189
Schau EM, Ellingsen H, Endal A, Aanondsen SA (2009) Energy consumption in the Norwegian fisheries. J Clean Prod 17:325–334. https://doi.org/10.1016/j.jclepro.2008.08.015
Sethi SA (2010) Risk management for fisheries. Fish Fish 11:341–365. https://doi.org/10.1111/j.1467-2979.2010.00363.x
Smith MD, Wilen JE (2005) Heterogeneous and correlated risk preferences in commercial fishermen: the perfect storm dilemma. J Risk Uncertain 31:53–71. https://doi.org/10.1007/s11166-005-2930-7
Standal D, Asche F (2018) Hesitant reforms: the Norwegian approach towards ITQ’s. Mar Policy 88:58–63. https://doi.org/10.1016/j.marpol.2017.11.005
Standal D, Sønvisen SA, Asche F (2016) Fishing in deep waters: the development of a deep-sea fishing coastal fleet in Norway. Mar Policy 63:1–7. https://doi.org/10.1016/j.marpol.2015.09.017
Sumaila UR, Lam V, Le Manach F et al (2016) Global fisheries subsidies: an updated estimate. Mar Policy 69:189–193. https://doi.org/10.1016/j.marpol.2015.12.026
Tveterås R (1999) Production risk and productivity growth: some findings for Norwegian salmon aquaculture. J Product Anal 12:161–179. https://doi.org/10.1023/A:1007863314751
Tveterås S, Asche F, Bellemare MF et al (2012) Fish is food—the FAO’s fish price index. PLoS ONE 7:1–13. https://doi.org/10.1371/journal.pone.0036731
Tveteras R, Flaten O, Lien G (2011) Production risk in multi-output industries: estimates from norwegian dairy farms. Appl Econ 43:4403–4414. https://doi.org/10.1080/00036846.2010.491461
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Financial support from the Norwegian Research Council (RCN: 233813 and 294804) and the Brazilian National Council for Scientific and Technological Development (CNPq: 202649/2011-3) is acknowledged. Any opinions and shortcomings in this paper are the responsibility of the authors and not these institutions.
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Asche, F., Cojocaru, A.L., Pincinato, R.B.M. et al. Production Risk in the Norwegian Fisheries. Environ Resource Econ 75, 137–149 (2020). https://doi.org/10.1007/s10640-019-00391-2
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DOI: https://doi.org/10.1007/s10640-019-00391-2