Spatiotemporal dynamics and policy impact on farmer suicides in Maharashtra, India

Abstract

Maharashtra has long faced a severe agricultural crisis, with a high number of farmer suicides, making it crucial to evaluate how government agricultural policies affect farmer suicides. This study investigated the influence of the Pradhan Mantri Fasal Bima Yojana (PMFBY), a crop insurance scheme, on patterns of farmer suicides across the state. Data for this study is acquired from the "Crime in Maharashtra" and the "Pradhan Mantri Fasal Bima Yojana (PMFBY) scheme" report spanning 2017-2021. This study focuses on analyzing the spatiotemporal trends to identify suicide-prone regions and assess whether the PMFBY has mitigated this distress. Further, this study employs statistical techniques to highlight key factors influencing suicides in these clustered regions. The findings suggest a notable reduction in suicide occurrences following the implementation of PMFBY, especially in high-risk districts. The study highlights that the districts of Aurangabad, Nagpur, and Amravati divisions emerged as significant clusters during the period from 2017 to 2019, and predicted rainfall, insurance units, gender-specific distribution, and agricultural land as positively influencing in mitigating the occurrence of farmer suicides within these clustered regions. Overall, this research underscores a notable reduction in the occurrence of both concentrated and dispersed regions before and after the introduction of the PMFBY. This study offers insights to policymakers for designing more targeted interventions aimed at reducing agrarian distress, improving farmer well-being, and offering valuable insights to improve suicide prevention initiatives in Maharashtra's districts and more broadly across India.

Keywords: Farmer’s suicide; Logistic regression; Public health; Relative risk; Spatiotemporal analysis; Suicide prevention.

Fig. 1

Study region (District of Maharashtra State, India) (Acquired from Google images, https://wheremaps.com/india/maharastra/maharashtra-district-map.html).

Fig. 2

Constraints provided in the PMFBY scheme’s raw dataset.

Fig. 3

Spatiotemporal analysis workflow of the study.

Fig. 4

Logistic regression modelling workflow of the study.

Fig. 5

Distribution of farmers’ suicides from 2017 to 2021 (Created by Microsoft Excel, Version 2411, https://www.microsoft.com/en-in/microsoft-365/excel).

Fig. 6

Phase-wise rainfall distribution (Created by Microsoft Excel, Version 2411, https://www.microsoft.com/en-in/microsoft-365/excel).

Fig. 7

Phase-wise insurance units distribution (Created by Microsoft Excel, Version 2411, https://www.microsoft.com/en-in/microsoft-365/excel).

Fig. 8

Suicide cluster of different temporal window sizes under consideration (Created by Microsoft Excel, Version 2411, https://www.microsoft.com/en-in/microsoft-365/excel).

Fig. 9

Phase-wise farmer’s suicide cluster in the state of Maharashtra, India (Created by Map data: OSM Datawrapper, https://www.datawrapper.de/).

Fig. 10

Phase-wise confusion matrix of clustered and non-clustered regions (Created by Python 3.10.9, https://www.python.org).

Fig. 11

Phase-wise variable coefficients of logistic regression modeling (Created by Python 3.10.9, https://www.python.org).