Agric. Econ. - Czech, 2020, 66(12):550-561 | DOI: 10.17221/85/2020-AGRICECON
A spatiotemporal analysis of comparative advantage in tea production in ChinaCase Study
- 1 Anxi College of Tea Science, Fujian Agriculture and Forestry University, Fuzhou, China
- 2 School of Economics and Management, Fuzhou University, Fuzhou, China
- 3 Department of Economics, Swedish University of Agricultural Sciences, Uppsala, Sweden
- 4 Department of Economics and Rural Development, Arish University, Al-Arish, Egypt
Tea is one of the most important cash crops and widely consumed beverages worldwide and plays a significant role in rural development, poverty reduction, and food security in many developing countries. Nevertheless, very few empirical studies have analysed the comparative advantage of the tea industry in developing countries. Taking Fujian Province, China, as the object of a case study, we carried out a spatiotemporal analysis of the determinants of the tea industry's revealed comparative advantage (RCA) during the period 2010-2018. The empirical analysis relied on a calculation of RCA and an estimation of a geographically and temporally weighted regression (GTWR) using data from 67 counties in Fujian. The results confirmed that the effect and significance of RCA determinants vary considerably across different spatial areas and over time. With the exception of 'disposable income', all other determinants had a positive and statistically significant effect on a region's RCA in the tea industry. Specifically, the results indicated that regional specialisation had the strongest positive effect on tea competitiveness. Local governments' sectoral strategies and institutional policies were essential elements in building and maintaining regional tea competitiveness. Infrastructure development, which traditionally went hand-in-hand with urbanisation processes, had a significant impact on tea competitiveness. These findings imply that competitiveness of the tea sector can be improved by adopting local polices that support producers and processors through fiscal investment, technology provision, and capacity building as well as measures to improve rural road infrastructure and link small farmers to other actors along tea supply chains.
Keywords: geographically and temporally weighted regression; regional specialisation; revealed comparative advantage; spatial analysis; temporal analysis
Published: December 31, 2020 Show citation
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