Ghee-Thean Lim’s scientific contributions

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Publications (2)


Assessing total factor productivity change in the aquaculture industry in China: A Färe-Primont productivity index and panel quantile regression
  • Article

January 2025

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27 Reads

Aquaculture

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Ghee-Thean Lim

Given the limited resources and growing demand for aquatic products, China's aquaculture industry must increase its output. Improving the total factor productivity (TFP) change is an importance step toward long-term sustainable development of the aquaculture industry. The study aims to examine the productivity change, particularly TFP change and its components, and to identify the factors influencing TFP change in China's aquaculture industry during 2010–2018. The Färe-Primont productivity index (FPI) is employed to assess the TFP change in the aquaculture industry. Subsequently, a novel introduced model - fixed effects panel quantile regression via the method of moments is used to analyze the heterogeneous effects of the influencing factors, namely, capture fishery ratio, extension workers, disaster losses, and real gross domestic product (GDP), on TFP change and efficiency change (ECH). The results show that the TFP grew by an average of 1.35 % during the period studied, driven mainly by a 3.63 % improvement in ECH, despite a decline of 1.86 % in technical change. Notably, inland provinces such as Chongqing, Shaanxi, Guizhou, and Yunnan predominantly exhibit higher TFP change than the coastal provinces. The results also demonstrated that socio-economic factors exerted differential impacts on the TFP change and the ECH of the aquaculture industry. The real GDP has positively influenced TFP change, exhibiting a downward trend across quantiles whereas the extension workers has positively contribution in TFP change only at lower quantiles (0.10–0.50). Moreover, the disaster losses exert a positive impact on TFP change only at higher quantiles (0.50–0.90). The real GDP was significantly improved ECH at all quantiles, while the disaster losses have a negative impact on ECH across all the quantiles except for the 0.10 quantile level. These findings highlight several policy implications. First, the aquaculture industry should train more technical workforce and facilitate cross-departmental rotations for these personnel. Second, less economically developed provinces need to adopt a better scientific management practice and improve the allocation of resources in aquaculture operations. Lastly, regions prone to natural disasters should develop more robust systems for disaster preparedness and response systems to minimize productivity losses.


Figure 1. Shaanxi livestock growth rate Source: National Bureau of Statistics of China (2021)
Figure 2. Technical efficiency score in the Shaanxi livestock industry Source: Authors' work
SOCIAL SCIENCES & HUMANITIES Assessing Determinants of Technical Efficiency in Livestock Production: A Case Study from Shaanxi, China
  • Article
  • Full-text available

September 2024

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5 Reads

Pertanika Journal of Social Science and Humanities

The demand for livestock products is rising, and China is actively encouraging farmers to increase their livestock production to meet this growing demand. At Shaanxi Province's livestock industry's current production output and growth rate, it appears unfeasible to meet the government's production target for 2025. Inefficiencies within livestock production can significantly impede the development of this industry. Therefore, this research employs the Data Envelopment Analysis (DEA) technique, considering Constant Returns to Scale (CRS) and Variable Returns to Scale (VRS) assumptions, to assess the technical efficiency of the livestock industry in Shaanxi Province. The data utilised are secondary data from 2010 to 2019. The findings reveal that the Shaanxi livestock industry has an average technical efficiency of 0.84 (CRS) and 0.92 (VRS), suggesting that there is room for further production growth with the current inputs, breeding scales and technology. Although dairy cows, cattle and goats have achieved full technical efficiency. Technical and scale inefficiencies still exist in hog and layer farming practices, which can be improved to increase production. Notably, hog farming demonstrated the lowest technical efficiency, scoring 0.68. The results of factors affecting inefficiency suggest that increasing spending on disease prevention and raising the selling price can both improve technical efficiency. Additionally, reducing death loss has the potential to improve technical efficiency. Thus, the government is expected to promote farm consolidation and expansion while actively advocating for establishing livestock production cooperatives.

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