Open Access
Issue
Aquat. Living Resour.
Volume 37, 2024
Article Number 8
Number of page(s) 11
DOI https://doi.org/10.1051/alr/2024006
Published online 24 May 2024
  • Andersen JL. 2002. Using Different Inputs and Outputs to Estimate Technical Efficiency in Fisheries: An Application to Danish Seiners in the North Sea and Skagerrak. Working Paper N. 10/02. Frederiksberg C, Denmark. [Google Scholar]
  • Armelloni EN, Scanu M, Masnadi F, Coro G, Angelini S, Scarcella G. 2021. Data poor approach for the assessment of the main target species of rapido trawl fishery in Adriatic Sea. Front Mar Sci 8: 1–11. [Google Scholar]
  • Asche F, Guillen J. 2012. The importance of fishing method, gear and origin: the Spanish hake market. Mar Policy 36: 365–369. [Google Scholar]
  • Asche F, Hannesson R. 2002. Allocation of fish between markets and product forms. Mar Resour Econ 17: 225–238. [Google Scholar]
  • Battese GE, Coelli TJ. 1995. A model for technical inefficiency effects in a stochastic frontier production function for panel data. Empir Econ 20: 325–332. [Google Scholar]
  • Cardinale M, Osio GC, Scarcella G. 2017. Mediterranean Sea: a failure of the European fisheries management system. Front Mar Sci 44: 72 [Google Scholar]
  • Carpi P, Scarcella G, Cardinale M. 2017. The saga of the management of fisheries in the Adriatic Sea: History, flaws, difficulties, and successes toward the application of the common fisheries policy in the Mediterranean. Front Mar Sci 44, 423. doi: 10.3389/fmars.2017.00423 [Google Scholar]
  • Chatterjee S, Hadi AS. Regression by Example, John Wiley & Sons Inc, 2006. [Google Scholar]
  • COEWEB. 2023. Coeweb − statistiche del commercio estero, http://www.coeweb.istat.it/, accessed 17 October 2023. [Google Scholar]
  • Coglan L, Pascoe S. 2007. Implications of human capital enhancement in fisheries. Aquat Living Resour 20: 231–239. [CrossRef] [EDP Sciences] [Google Scholar]
  • Colwell JMN, Axelrod M, Roth B. 2019. Unintended consequences of a seasonal ban on fishing effort in Tamil Nadu & Puducherry, India. Fish Res 212: 72–80. [Google Scholar]
  • Costanigro M, Mccluskey JJ, Lusk JL. Hedonic Price Analysis in Food Markets, Oxford University Press, Oxford, 2011, pp. 152–180. [Google Scholar]
  • Dağtekin M, Uysal O, Candemir S, Genç Y. 2021. Productive efficiency of the pelagic trawl fisheries in the Southern Black Sea. Reg Stud Mar Sci 45: 101853. [Google Scholar]
  • Domina G. 2021. Invasive Aliens in Italy: enumeration, history, biology and their impact. Invasive Alien Species: Observations and Issues from Around the World, 1; 3: 190–214. [Google Scholar]
  • Drouineau H, Moullec F, Gascuel D, Laloë F, Lucas S, Bez N, Vermard Y. 2023. Food for thought from French scientists for a revised EU Common Fisheries Policy to protect marine ecosystems and enhance fisheries performance. Mar Policy 148: 105460. [Google Scholar]
  • European Commission. 2023a. Report from the Commission to the European Parliament and the Council. Implementation of Regulation (EU) No 1379/2013 on the common organisation of the markets in fishery and aquaculture products, Brussels. [Google Scholar]
  • European Commission. 2023b. Common Fisheries Policy − State of Play Accompanying the Document Communication from the Commission to the European Parliament and the Council the Common Fisheries Policy Today and Tomorrow: A Fisheries and Oceans Pact towards Sustainable, Science-Based, Brussels. [Google Scholar]
  • FAO. 2023. The State of Mediterranean and Black Sea Fisheries 2023- Special edition, Rome, https://doi.org/10.4060/cc8888en [Google Scholar]
  • Fousekis P, Klonaris S. 2003. Technical efficiency determinants for fisheries: a study of trammel netters in Greece. Fish Res 63: 85–95. [Google Scholar]
  • Gómez S, Maynou F. 2020. Economic, sociocultural and ecological dimensions of fishing capacity in NW mediterranean fisheries. Ocean Coast Manag 197: 105323. [Google Scholar]
  • Greene WH. 2023 Econometric Analysis, Pearson Education. [Google Scholar]
  • Greenville J, Hartmann J, MacAulay TG. 2006. Technical efficiency in input-controlled fisheries: The NSW ocean prawn trawl fishery. Mar Resour Econ 21: 159–179. [Google Scholar]
  • Grilli F, Accoroni S, Acri F, Bernardi Aubry F, Bergami C, Cabrini M, Cozzi S. 2020. Seasonal and interannual trends of oceanographic parameters over 40 yr in the northern Adriatic Sea in relation to nutrient loadings using the EMODnet chemistry data portal. Water 12: 2280. [Google Scholar]
  • Guillen J, Maynou F. 2015. Characterisation of fish species based on ex-vessel prices and its management implications: an application to the Spanish Mediterranean. Fish Res 167: 22–29. [Google Scholar]
  • Herrero I, Pascoe S. 2003. Value versus Volume in the Catch of the Spanish South-Atlantic Trawl Fishery. J Agric Econ 54: 325–341. [Google Scholar]
  • Jaffry S, Taylor G, Pascoe S. 2005. An Inverse Demand System for Fish Species in Spain. Working Paper. No. 2. CEMARE University of Portsmouth, Portsmouth, UK. [Google Scholar]
  • Kiyama S, Yamazaki S. 2018. The impact of stock collapse on small-scale fishers’ behavior: evidence from Japan. Can J Fish Aquat Sci 75: 2241–2254. [Google Scholar]
  • Kodde DA, Palm FC. 1986. Wald criteria for jointly testing equality and inequality restrictions. Econometrica 54: 1243–1248. [Google Scholar]
  • Krigbaum MJ, Anderson CM. 2021. Increasing value through gear flexibility: a case study of US west coast sablefish. Can J Fish Aquat Sci 78: 1130–1145. [Google Scholar]
  • Kristofersson D, Rickertsen K. 2004. Efficient estimation of hedonic inverse input demand systems. Am J Agric Econ 86: 1127–1137. [CrossRef] [Google Scholar]
  • Long RD, Charles A, Stephenson RL. 2015. Key principles of marine ecosystem-based management. Mar Policy 57: 53–60. [Google Scholar]
  • Malvarosa L, Basilone G, Carbonara P, Carpentieri P, Cozzolino M, Follesa MC, Scarcella G. 2023. Data availability and participatory approach: the right mix for enhancing Mediterranean fisheries’ sustainability. Front Mar Sci 10: 1155762. [Google Scholar]
  • Manea E, Di Carlo D, Depellegrin D, Agardy T, Gissi E. 2019. Multidimensional assessment of supporting ecosystem services for marine spatial planning of the Adriatic Sea. Ecol Indic 101: 821–837. [Google Scholar]
  • Menegon S, Fadini A, Perini L, Sarretta A, Depellegrin D, De Maio E, Barbanti A. 2023. A geoportal of data and tools for supporting Maritime Spatial Planning in the Adriatic-Ionian Region. Environ Model Softw 160: 105585. [Google Scholar]
  • Ministero dell’agricoltura, della sovranità alimentare e delle foreste (MASAF). 2023. Decreto Ministeriale n. 208415 del 18/04/2023. Disposizioni in materia di interruzione temporanea obbligatoria delle attività di pesca esercitate mediante l’utilizzo di attrezzi trainati ‘reti a strascico a divergenti (OTB)’, ‘reti gemelle a divergenti (OTT)’ e/o ‘sfogliare − rapidi (TBB)’ − Annualità 2023. [Google Scholar]
  • Mulazzani L, Camanzi L, Bonezzi A, Malorgio G. 2018. Individual transferable effort quotas for Italian fisheries? A preliminary analysis. Mar Policy 91: 14–21. [Google Scholar]
  • Newey WK, West KD. 1987. Hypothesis testing with efficient method of moments estimation. Int Econ Rev 28: 777–787. [Google Scholar]
  • Nielsen M. Calculations of Danish Prices of Unprocessed Seafood. SJFI Working Paper No. 9. Danish Re search Institute of Food Economics,Frederiksberg, Denmark, 2000. [Google Scholar]
  • NISEA. 2022a. Impatto Economico Dell ’ Incremento Del Costo Del Gasolio Sulla Flotta Peschereccia Italiana, 2022a. http://www.nisea.eu/dir/wp-content/uploads/2022/03/Bollettino-Nisea_22_1.pdf. [Google Scholar]
  • NISEA. 2022b. Rapporto Sull’andamento Economico Della Flotta Italiana per Regione, https://www.nisea.eu/dir/wp-content/uploads/2022/10/Rapporto-Nisea-2022. pdf [Google Scholar]
  • Ogundari K, Akinbogun OO. 2010. Modeling technical efficiency with production risk: a study of fish farms in Nigeria. Mar Resour Econ 25: 295–308. [Google Scholar]
  • Pascoe S, Coglan L. 2002. The contribution of unmeasurable inputs to fisheries production: an analysis of technical efficiency of fishing vessels in the english channel. Am J Agric Econ 84: 585–597. [CrossRef] [Google Scholar]
  • Pascoe S, Hassaszahed P, Anderson J, Korsbrekke K. 2003. Economic versus physical input measures in the analysis of technical efficiency in fisheries. Appl Econ 35: 1699–1710. [CrossRef] [Google Scholar]
  • Pascoe S, Tingley D. Capacity and technical efficiency estimation in fisheries: parametric and non-parametric techniques, in: Handbook of Operations Research in Natural Resources, Springer, 2007, pp. 273–294. [Google Scholar]
  • Pascoe S, Robinson C. 1998. Input controls, input substitution and profit maximisation in the English Channel beam trawl fishery. J Agric Econ 49: 16–33. [Google Scholar]
  • Pranovi F, Raicevich S, Franceschini G, Torricelli P, Giovanardi O. 2001. Discard analysis and damage to non-target species in the ‘Rapido’ trawl fishery. Mar Biol 139: 863–875. [Google Scholar]
  • Pranovi F, Anelli Monti M, Caccin A, Brigolin D, Zucchetta M. 2015. Permanent Trawl Fishery closures in the Mediterranean Sea: an effective management strategy? Mar Policy 60: 272–279. [Google Scholar]
  • Prellezo R, Villasante S. 2023. Economic and social impacts of the landing obligation of the European Common Fisheries Policy: a review. Mar Policy 148: 105437. [Google Scholar]
  • Roheim CA, Asche F, Santos JI. 2011. The elusive price premium for ecolabelled products: evidence from seafood in the UK market. J Agric Econ 62: 655–668. [Google Scholar]
  • Rosen S. 1974. Hedonic prices and implicit markets: product differentiation in pure competition. J Pol Econ 82: 34–55. [Google Scholar]
  • Russo E, Anelli Monti M, Mangano CM, Raffaetà A, Sarà G, Silvestri C, Pranovi F. 2020. Temporal and spatial patterns of trawl fishing activities in the Adriatic Sea (Central Mediterranean Sea, GSA17). Ocean Coast Manag 192: 105231. [Google Scholar]
  • Russo T, Bitetto I, Carbonara P, Carlucci R, D’Andrea L, Facchini MT, Cataudella S. 2017. A holistic approach to fishery management: evidence and insights from a central mediterranean case study (Western Ionian Sea). Front Mar Sci 4: 193. [Google Scholar]
  • Sala A, Damalas D, Labanchi L, Martinsohn J, Moro F, Sabatella R, Notti E. 2022. Energy audit and carbon footprint in trawl fisheries. Sci Data 9: 428. [Google Scholar]
  • Sánchez Lizaso JL, Sola I, Guijarro-García E, Bellido JM, Franquesa R. 2020. A new management framework for western mediterranean demersal fisheries. Mar Policy 112: 103772. [Google Scholar]
  • Sangün L, Güney OI, Berk A. 2018. Economic efficiency performance of small-scale fisheries in the East Mediterranean coast of Turkey. New Medit 17: 71–80. [Google Scholar]
  • Squires D, Kirkley J. 1999. Skipper skill and panel data in fishing industries. Can J Fish Aquat Sci 56: 2011–2018. [Google Scholar]
  • STECF. 2022. The Annual Economic Report on the EU Fishing Fleet (STECF 22-06), Luxembourg, 2022, https://doi.org/10.2760/120462. [Google Scholar]
  • Strafella P, Fabi G, Spagnolo A, Grati F, Polidori P, Punzo E, Scarcella G. 2015. Spatial pattern and weight of seabed marine litter in the northern and central Adriatic Sea. Mar Pollut Bull 91: 120–127. [Google Scholar]
  • Van Nguyen Q, Pascoe S, Coglan L. 2019. Implications of regional economic conditions on the distribution of technical efficiency: examples from coastal trawl vessels in Vietnam. Mar Policy 102: 51–60. [Google Scholar]
  • Vinuya FD. 2010. Technical efficiency of shrimp fishery in South Carolina, USA. Appl Econ Lett 17: 1–5. [CrossRef] [Google Scholar]
  • Yang C, Lou X, Matsui T, Zhang J. 2017. Evaluating the technical efficiencies of fishing vessels to achieve effective management of overexploited fisheries. Mitig Adapt Strateg Glob Chang 22: 1149–1162. [Google Scholar]

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