Evaluation of factors influencing Asian continent ocean health status using a semi-parametric production function

Nguyen, Kim Anh; Jolly, Curtis M.; Nguelifack, Brice M.

doi:10.1016/j.ocecoaman.2018.03.021

Cited by 2 publications

(3 citation statements)

References 18 publications

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“…This model and that of Nguyen, Jolly, and Nguelifack (2018a) showed that Biodiversity had the highest partial elasticity (0.43) and potential impact on OHI. While the partial elasticity suggests biodiversity as the main driver to improve the health of African ocean waters, the low IF indicates that other interacting variables such as Coastal Protection, Carbon Storage and Wild Fish Caught are also important in modulating the effects of Biodiversity to foster ocean health improvement.…”

Section: Methodsmentioning

confidence: 80%

“…Tourism and recreation and natural products had the highest influence factors, and therefore, the largest impacts on OHI compared to other factors considered. Nguyen, Jolly, and Nguelifack (2018a), using a semiparametric function, noted that similar variables influenced Asian OHI. Their model found that Coastal Protection had a relative influence at 19.21%, and in second place was Tourism and Recreation with 17.04%.…”

Section: Methodsmentioning

confidence: 99%

“…One method of dealing with data that is not normally distributed is to use semiparametric models, which do not require normal distribution of the data (Nguyen, Jolly, and Nguelifack, 2018a). Semiparametric models are sensitive to outlying observations, so the generated estimates are unreliable when study data includes outliers (Chen et al, 2014).…”

Section: Stage 1: Wilcoxon Rank Correlation Modelmentioning

confidence: 99%

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African Ocean Health Production Function: Policy Implications

Nguyen

Nguelifack

Nguyen

et al. 2023

Journal of Coastal Research

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Nguyen, K.A.T.; Nguelifack, B.M.; Nguyen, T.A.T., and Jolly, C.M., 2023. African ocean health production function: Policy implications. Journal of Coastal Research, 39(3), 519–530. Charlotte (North Carolina), ISSN 0749-0208.The study used a two-stage production function, rank regression in the first stage, and probit and ordinary least squares regression in the second stage, to evaluate the effect of socio-economic, environmental, physical, and demographic factors on ocean health. The rank regression analysis coefficients were evaluated using a “t” test. Biodiversity, Tourism, Recreation, Fish Production, Livelihoods, and Sense of Place were all significant at p-value <.01, while carbon storage was significant at p-value <0.05. Artisanal Fisheries were significant at p-value <0.1. The variable Biodiversity had the highest elasticity (.43). A 1.0% increase in biodiversity is likely to increase the Ocean Health Index (OHI) score by 0.43%, while 1.0% increases in sense of place and coastal livelihoods will increase the OHI by 0.14% and 0.13%, respectively. The relative influence result suggests that the most important variables are Tourism and Recreation (27.6%), Natural Products (20.6%), Food Production (14.1%), Carbon Storage (11.0%), and Coastal Protection (4.8%). The probit model showed that human development index influenced ocean health. Development policies may consider the inclusion of changes in Tourism and Recreation, Fish Provision, and Carbon Storage to improve African ocean health.

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Section: Methodsmentioning

confidence: 80%

Section: Methodsmentioning

confidence: 99%