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Assessing the regime-switching role of risk mitigation measures on agricultural vulnerability: A threshold analysis

  • Technical University of Munich
  • Rheinische Friedrich-Wilhelms-Universität Bonn

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Vulnerability to agrometeorological disasters threatens agricultural production and food security, which calls for urgent risk mitigation measures. Previous studies have widely focused on constructing composite indices of agricultural vulnerability and projecting agricultural losses under changing climate. Only a few authors have delved into the patterns of mitigation practices in reducing agricultural vulnerability and enhancing the functioning of agricultural systems. To fill this research gap, our study assesses the spatial-temporal characteristics of agricultural vulnerability with respect to meteorological disasters (including droughts, floods, hail, low temperatures, and frost) from 2000 to 2021 across 31 regions (including 22 provinces, 4 direct-administered municipalities, and 5 autonomous regions) in China. Identifying a dynamic trend of agricultural vulnerability and making use of a regime-switching framework, a Markov regime-switching model is employed to examine the changing regimes underlying the link between agricultural vulnerability and crop yields. More importantly, regime-switching roles of four different mitigation practices (i.e., irrigation, reservoir capacity, soil loss control, and drainage systems) in moderating agricultural vulnerability are evaluated using panel threshold regressions. Our results show that: 1) The link between agricultural vulnerability and crop yields differs across regions, and regime-switching phenomena behind this link can be detected. 2) Irrigation systems, water reservoirs, and soil loss control can be effective tools for mitigating agricultural vulnerability. 3) With the above three measures, detrimental impacts of agricultural vulnerability on agricultural production can be reduced significantly when certain thresholds are hit. 4) Non-linear relationships between mitigation measures and crop yields require authorities to pay considerable attention to determining the effective scales of mitigation measures. Overall, this paper shall contribute to understanding the moderating role of risk mitigation measures in alleviating agricultural vulnerability and increasing crop yields, thereby providing insights into designing strategies and policies for sustainable agricultural production.

Original languageEnglish
Article number108360
JournalEcological Economics
Volume227
DOIs
StatePublished - Jan 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 2 - Zero Hunger
    SDG 2 Zero Hunger
  2. SDG 6 - Clean Water and Sanitation
    SDG 6 Clean Water and Sanitation
  3. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth
  4. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities
  5. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production
  6. SDG 17 - Partnerships for the Goals
    SDG 17 Partnerships for the Goals

Keywords

  • Agricultural vulnerability
  • Markov regime-switching model
  • Mitigation measures
  • Panel threshold regression
  • Regime-switching framework
  • Spatial-temporal heterogeneity

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