Estimation of productivity growth, technical progress, and efficiency changes in the Korean offshore fisheries

Kim, Do-Hoon; Seo, Ju-Nam; Kim, Hyung-Seok; Lee, Kyounghoon

doi:10.1007/s12562-012-0488-2

Cited by 5 publications

(3 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Ritzau et al (2014) estimate that catchability increases by 3.2% per year due to technological developments. Kim et al (2012) estimate an average 6% drop in the total factor productivity of 12 Korean offshore fisheries over the 1997-2009 period, the change ranging from a 16.6% drop of the trawl fishery and a 4.8% increase of the long line fishery. 13 See Wilberg et al (2009) for a survey of the use of a time-varying catchability parameter.…”

Section: Data and Measurement Of Effortmentioning

confidence: 99%

Minimum information management and price‐abundance relationships in a fishery

Marvasti

Dakhlia

2021

Canadian J Agri Economics

View full text Add to dashboard Cite

We explore the information content of dockside prices and fishing costs in the estimation of stock abundance. Our approach is two-pronged: we first examine whether the implied biomass, that is, the biomass that is consistent with a simple microeconomic model calibrated with observed prices and costs, offers an approximation of actual stock assessments-both agree over the first 20 years of observation, but diverge over the last five. In a second approach, we use annual data in Vector Autoregressive (VAR), Bayesian VAR (B-VAR), and Vector Error Correction (VEC) frameworks and add monthly data in a mixed-frequency data analysis including Mixed-Frequency Bayesian VAR (MF-BVAR) and Mixed-Data Sampling (MIDAS) frameworks for log-differenced time series. Parameter uncertainties are addressed through Bayesian regression and forecasting methods. We find a statistically significant correlation between biometric estimates and changes in a price-based indicator that is robust to the inclusion of confounding factors. We conclude that the combination of price data and per-trip landings, when interpreted with care, can serve as a complementary, but comparatively affordable and timely, source of information for stock assessments.

show abstract

Section: Data and Measurement Of Effortmentioning

confidence: 99%

Minimum information management and price‐abundance relationships in a fishery

Marvasti

Dakhlia

2021

Canadian J Agri Economics

View full text Add to dashboard Cite

show abstract

“…However, the latest data of fish stock of demersal fish in west coast could not be obtain since the last survey made by DOF was around 1997-1998. Hence, the alternative way did by Kim et al (2012), Haggarty and King (2006), Pascoe et al (2004), which they used catch per unit of effort, CPUE as symbolizing the biodynamics of fish stocks affecting the fish landings. This CPUE refers to the total catch per effort expended to catch fish using the existing assets or energy (i.e., vessels, fishing period, engine size etc.).…”

Section: Determination Of Inputs and Outputsmentioning

confidence: 99%

Efficiency and Capacity of Trawlers in West Coast Peninsular Malaysia

2024

JQMA

View full text Add to dashboard Cite

This study discusses the efficiency, capacity and capacity utilization of fish trawlers of various zones in the west coast of Peninsular Malaysia in 2011. Data for this study were obtained from the Department of Fisheries Malaysia. An input-oriented Data Envelopment Analysis (DEA) model assuming the constant return to scale (CRS) technology was used to measure the technical efficiency and an output-oriented DEA model based on variable returns to scale (VRS) was implemented for the efficiency of capacity and capacity utilization. The study found that nearly 80% of trawlers fishing on the West Coast of Peninsular Malaysia is efficient and have an average 0.90 capacity utilization. Only fish trawlers in Perlis C2 Zone, B Zone and C Zone in Kedah were inefficient and has excess capacity to be reduced respectively by 58%, 29% and 38%. Overall current capacity can be increased by 6.14% if the excess capacity have been overcome.

show abstract

“…The research on the development of fishery science and technology mainly involved the measurement of total factor productivity, the calculation of economic contribution rate and the calculation of technological innovation efficiency. Wang et al [13] explored the impact of fishery science and technology development on improving fishery total factor productivity by using econometric model, and proposed to adjust the direction and focus of fishery science and technology transformation; Yu et al [14] used the Cobb Douglas production function and the solo residual method to calculated the contribution rate of fishery scientific and technological progress to fishery economy; Kim et al [15] constructed the Malmquist productivity index to estimate the changes of productivity growth and technological progress of offshore fisheries in South Korea in total factor productivity; Apreku et al [16] combined Nerlovian and directional distance function methods to decompose the profit efficiency of fishery into technical efficiency and distribution efficiency, and explored the contribution of profit efficiency to fishery production; Zheng et al [17] measured the total factor productivity of fishery economy in Chinese mainland and Taiwan coastal areas, and pointed out that the improvement in technological innovation efficiency and technological progress would promote the total factor productivity of fisheries.…”

Section: Literature Reviewmentioning

confidence: 99%

Spatial–Temporal Evolution and Sustainable Type Division of Fishery Science and Technology Innovation Efficiency in China

Zhu

Han

2022

Sustainability

View full text Add to dashboard Cite

Science and technology innovation is an important driving force to promote the development of fishery industry, and is very important to improve the quality of fishery development. In this study, the Super-SBM model was used to evaluate the fishery science and technology innovation efficiency of 30 provinces and cities in China (excluding Hong Kong, Macao, Taiwan and Tibet) from 2011 to 2020. Combined with the kernel density estimation, the spatial and temporal differentiation characteristics were analyzed. Then, from the two dimensions of investment scale and innovation efficiency, the sustainable development types of fishery science and technology innovation were classified. The results show the following: (1) From the perspective of efficiency change, the overall efficiency of fishery science and technology innovation in China increased first and then decreased during 2011–2020, but the overall efficiency level was low, and the efficiency difference between regions gradually widened, and the eastern coastal regions became the development core of fishery science and technology innovation. (2) From the perspective of spatial differentiation characteristics, there was a large gap between the coastal and inland areas in China. The high-efficiency areas were mainly concentrated in the coastal provinces and cities, such as Guangdong, Jiangsu, Shandong, Shanghai and Tianjin, showing a decreasing trend from east to west. (3) From the perspective of investment scale and innovation efficiency, the study regions can be divided into four types: leading area, breakthrough area, catch-up area and backward area. This paper mainly calculates the efficiency of fishery science and technology innovation in various regions, and divides the type areas of fishery science and technology innovation and development. According to the advantages and problems of different types of areas, different development strategies and correction measures are proposed, which can effectively improve the efficiency of resource utilization, avoid resource waste and realize the sustainable development of fishery.

show abstract

Estimation of productivity growth, technical progress, and efficiency changes in the Korean offshore fisheries

Cited by 5 publications

References 8 publications

Minimum information management and price‐abundance relationships in a fishery

Minimum information management and price‐abundance relationships in a fishery

Efficiency and Capacity of Trawlers in West Coast Peninsular Malaysia

Spatial–Temporal Evolution and Sustainable Type Division of Fishery Science and Technology Innovation Efficiency in China

Contact Info

Product

Resources

About