This study analyses the impact of irrigation infrastructure and climate variability on rice and wheat yields across 22 districts of Haryana using a panel dataset from 2014-15 to 2022-23, collected from the Department of Economic and Statistical Affairs, Government of Haryana; additionally, data on climate variables such as rainfall, temperature, and relative humidity were collected from the NASA Power Data Access Viewer (DAV). The study integrates agricultural infrastructure, irrigated area by tubewells, canal system, total fertilizer use, area under crop, and climate variables such as temperature, rainfall, and relative humidity. Descriptive statistics were used to summarize the data for both crops, wheat and rice. Diagnostic tests such as the variance inflation factor (VIF), Breusch-Pagan LM test, and Hausman test were performed. The Hausman test was applied to select between random effects and fixed effects methods; the Hausman test failed to reject the null hypothesis, which means that random effects are preferred over fixed effects. So, the main model of the current research for analysis is random effects. Further, the Pesaran CD test was performed and the null hypothesis was rejected, suggesting the presence of cross-sectional dependence among districts. Therefore, the analysis uses Fixed Effects Regression (Driscoll-Kraay SE) for both crops to check robustness. The results illustrate that climatic factors have more influence on wheat production, while rice productivity is primarily associated with cultivated area and input utilization. The analysis recommends that a better future policy should be focused on climate-responsive water management rather than continuing to expand irrigation sources.
No takes yet. Share an insight, caveat, or question.
Singh et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: