| Autor: |
Chinwe Adaugo Uzokwe, Joel Chiadikobi Nwaubani, Adanma Ngozi Ohia, Peace Opara, Christiana Uzoma Ezechukwu, Uchechi Mgbafor Ezeji |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
European Journal of Business and Management Research. 5 |
| ISSN: |
2507-1076 |
| DOI: |
10.24018/ejbmr.2020.5.6.554 |
| Popis: |
In fisheries production, aquaculture sector is characterised as a "blue revolution" as it is the fastest developing food industry in the world. Fish farming and aquaculture products are constantly gaining ground than ever before on our daily dishes. Fishes are a great source of affordable protein which the human body needs in regular and specific quantities and also it serves as a major pharmaceutical ingredient such as fish oil soap, body cream and perfume. Moreover, fishes are now being used as raw materials for fillets, canning for eateries and fish feeds. Statisticians and Nutrition/Dietician experts predict that much of the vital protein food necessary to nourish an increasing global population of which pathetically, many are underfed even today will come from marine (saltwater) fisheries. With a total production of 52 million tons in 2017, aquaculture is seen by many as the only solution to replenish the vacuum created in fishes due to an increase in consumption and overfishing. Aquaculture is important because it offers an alternative to overburdening and depleting marine fishery stocks. Currently the depletion rate of European fish stocks is 88%. This study considers the use of a logarithmic linear model to analyse fisheries and aquaculture products in EU26. We consider using data from the European Market Observatory for fisheries and aquaculture, estimated on actual base year from 2006-2017. The analysis of association table (ANOAS) is given to ascertain the percentage of the data which is covered by each model. We investigate and estimate the association model with the best fit and in conclusion, find out that the Row-Column Effects Association Model (RC) of the multivariate model (M=8) has the best fit among all, covering almost 91% of the total data observed. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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