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Based on panel data from 1991, 2000 and 2010 at the county level in China, this study analyzed the coupling characteristics and spatio-temporal patterns of agricultural labor changes and economic development under rapid urbanization using quantitative and GIS spatial analysis methods. Three primary conclusions were obtained. (1) During 1991-2010, China's agricultural labor at the county level showed a decreasing trend, down 4.91% from 1991 to 2000 and 15.50% from 2000 to 2010. In spatial distribution, agricultural labor force has evolved by decreasing eastward and increasing westward. (2) During 1991-2010, China's agricultural economy at the county level showed a sustained growth trend, with a total increase of 140.13%, but with clear regional differences. The proportion of agricultural output in national GDP gradually decreased, characterized by decreases in eastern China and increases in western China. (3) The coupling types of economic-labor elasticity coefficient are mainly growth in northwest China, for both the agricultural economy and labor, and are intensive in southeast China, with growth of the agricultural economy and reduction of agricultural labor. Regions with lagged, fading, and declining coupling types are generally coincident with the high incidence of poverty in China. However, different coupling types had a positive developing trend for 1991-2010. Finally, based on the coupling types and spatial distribution characteristics of economic-labor elasticity coefficients, some policy suggestions are proposed to promote the integration of the primary, secondary, and tertiary industries and the vitalization of rural economies. Keywords: agricultural labor change; agricultural economic development; economic-labor elasticity coefficient; spatio-temporal coupling; rural vitalization 2 The mechanisms driving agricultural labor changes and economic development This study establishes a theoretical framework to characterize the mechanisms driving agricultural labor changes and economic development. We use this framework to explore the

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