from the Centre for Monitoring Indian Economy (2014-2016).

This research makes several significant contributions to understanding rural economic resilience in the context of weather variability. As climate change intensifies the frequency and severity of weather shocks, understanding their comprehensive economic impacts becomes crucial for policy design. The study’s findings on how weather variations affect both farm and non-farm sectors provide valuable insights for developing integrated rural development policies, particularly important for regions like Rajasthan where agricultural vulnerability to climate variability is high (Auffhammer and Carleton, 2018). By quantifying the relationships between agricultural conditions and non-farm enterprise performance, it provides evidence-based guidance for designing interventions that can enhance rural economic resilience, addressing a critical gap identified by Pingali et al. (2019) regarding the need for policies that support both agricultural adaptation and rural economic diversification.

New insights are added locally: The current study supports the existing literature on the interdependence of the rural economy with evidence on the specific channels for and magnitude of agricultural-nonagricultural linkages affected by weather shocks. Most notably, past studies ascribed this commonality to weather variables in general. The current study moves forward by examining potentially-weather dependent relationships, such as those related to agricultural economics and climate adaptation strategies. In addition, significant methodological contributions are made through the linking of multiple data sources to produce a nuanced understanding of rural economic development under climate conditions. These insights hold potential for informing climate adaptation strategies in rural economies, filling a “critical gap” identified by Barrett et al. (2017) in the need for combination strategies relying on evidence that relate solely to agricultural activities but also to climate developments in sectors engaged in non-grain-related activities. The ultimate translated goal supports the need to inform policymakers of the need to rethink the clear economic interdependence of rural activity with climactic realities.

# **2 Data and Summary Statistics**

This paper combines data from three sources: namely data on non-farm enterprises based on a nationally representative enterprise survey; agricultural statistics and rainfall data from the district-level ICRISAT database; and household consumption data from a nationally representative household survey. Additional district-level covariates are sourced from the Census of India and representative household employment surveys.

## **2.1 Agricultural Productivity Data**

We obtain data on district-level farm productivity and rainfall from the district-level database maintained by the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT). This database contains extensive crop-wise data on acreage and output for 14 crops at the district-level, in addition to data on fertilizer usage, cultivable land, irrigation and monthly precipitation. While the data is available for a 26 year period between 1990 and 2015, we use 4