Assessing the relationship between air pollution, agricultural insurance, and agricultural green total factor productivity: evidence from China

Environ Sci Pollut Res Int. 2022 Nov;29(52):78381-78395. doi: 10.1007/s11356-022-21287-7. Epub 2022 Jun 11.

Abstract

As a favorite means to promote the development of green agriculture, agricultural insurance can not only encourage farmers to adopt green production technology and improve production efficiency, but also achieve the purpose of reducing the input of chemicals to protect the environment. This article aims to study the dynamic relationship between agricultural insurance, air pollution, and agricultural green total factor productivity using the panel vector auto-regressive method (PVAR) and panel data of 30 provinces in China from 2005 to 2018. The empirical results show that there is a significant cross-sectional dependence and the co-integration relationship between agricultural insurance, air pollution, and agricultural green total factor productivity. The increase in agricultural insurance can improve agricultural green total factor productivity and aggravate air pollution to a certain extent. However, serious air pollution does not improve agricultural green total factor productivity. Panel Granger causality test results show that agricultural insurance has a one-way causal relationship with green total factor productivity and air pollution, and so does air pollution with agricultural green total factor productivity. In addition, impulse response results show that increasing agricultural insurance or reducing air pollution can improve agricultural green total factor productivity. These conclusions have long-term practical implications for both agricultural policymakers and environmental managers.

Keywords: Agricultural green total factor productivity; Agricultural insurance; Air pollution; China; Panel vector auto-regressive method.

MeSH terms

  • Agriculture / methods
  • Air Pollution*
  • China
  • Cross-Sectional Studies
  • Insurance*