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The Million Farmers School (MFS) program—also known as Kisan Pathshala was launched to impart training to the farmers by the government of the state of Uttar Pradesh (India) in December 2017. This study estimates the impact of training on agricultural knowledge of the farmers.

The study is based on household survey conducted in Uttar Pradesh (UP), India, during March–May 2019. The authors employed matching methods, the two-stage least square (2SLS)-residual and endogenous switching regression approaches to control for selection bias and endogeneity.

The results suggest that knowledge outcomes are significantly better among participants vis-à-vis non-participants. The results are robust to different model specifications. Further, the benefits are observed across different regions and social groups.

The MFS program can go a long way in enhancing agricultural know-how and the farmers' economic well-being, bringing a transformative change in the agricultural landscape of UP.

This study is based on a field survey data and analyzes various aspects of the program's impact, design and implementation, and offers implementation advice for greater efficacy in future.

Laser land leveling (LLL) is a climate-smart technology that improves water use efficiency and reduces risk in crop cultivation due to weather variability. Hence, this technology is useful for cultivating water-intensive crops in a sustainable way. Given this background, the state government of Karnataka initiated to promote LLL in drought-prone districts and selected Raichur district for implementation. Moreover, farmers in this district had observed drought situation during monsoon paddy growing season in 2018. Therefore, this study attempts to investigate the importance of LLL technology for paddy cultivation under drought conditions.

A primary survey with 604 farmer households had been conducted in Raichur in 2018. Among them, 50% are adopters of LLL who have been selected purposively and rest 50% are non-adopters who have grown paddy in the adjacent or nearest plot of the laser-leveled plot. The adoption and causal impact of LLL has been estimated using propensity score matching, coarsened exact matching and endogenous switching regression methods.

The result reveals a positive and significant impact of LLL on paddy yield and net returns to the farmers. The results indicate an increment of 12 and 16% in rice yield and net income, respectively, for LLL adopters in comparison to the non-adopters of LLL.

The major limitation of the study is that it does not adopt the method of experimental study due to certain limitations; hence, the authors employed a quasi-experimental method to look at the possible impact of adoption of LL.

There have been various agronomic studies focusing on the ex-ante assessment of the LLL. This study is an ex-post assessment of the technology on the crop yield and farmers' income in a dry semi-arid region of India, which, according to the authors, is the first in this approach.