Agricultural Insurance Effects on the Resilience of Agricultural Industry in China
Description
Research Hypothesis and Methodology This study hypothesizes that agricultural insurance significantly enhances the resilience of the agricultural industry chain (RAIC). We constructed the RAIC index using the entropy weight method (EWM) based on 15 indicators, including the effective irrigation rate. Notably, indicators 4-7 negatively impacted resilience, while others exhibited positive effects. Subsequent empirical analysis examines the relationship between RAIC and agricultural insurance development (DAI) alongside control variables. Data Sources： National Bureau of Statistics of China (Official Portal) China Industrial Statistical Yearbook (2011-2022) China Rural Statistical Yearbook (2011-2022) China Insurance Statistical Yearbook (2011-2022) Provincial Statistical Yearbooks (30 provinces) (Balanced Panel: N = 360 ，T = 12 years) Core Variables 'RAIC': Resilience of Agricultural Industry Chain;'DAI':Development of Agricultural Insurance
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Steps to reproduce
This study compiles data from the National Bureau of Statistics of China, China Industrial Statistical Yearbook, China Rural Statistical Yearbook, China Insurance Statistical Yearbook, and provincial statistical yearbooks (N = 360 , 2011-2022). The Agricultural Industry Chain Resilience (RAIC) index was constructed using the Entropy Weight Method (EWM), with variables 4-7 treated as negative indicators and the remaining variables as positive indicators. Subsequently, a two-way fixed effects model was implemented in Stata 18.0 to empirically examine the relationship between RAIC and agricultural insurance development (DAI), controlling for county and year fixed effects to address unobserved heterogeneity.
Institutions
- Southwest University