||(0.0624)|(0.0788)|
|---|---|---|
|The proportion of land that is upland|-0.0175|0.115**|
||(0.0509)|(0.0466)|
|**Caste Category**(Base = General)|||
|_Scheduled Caste (SC)_|-0.106|-0.0624|
||(0.107)|(0.0833)|
|_Scheduled Tribe (ST)_|0.00369|-0.0339|
||(0.0695)|(0.0392)|
|_Other Backward Classes (OBC)_|-0.0371|0.0203|
||(0.0659)|(0.0445)|
|Gender of Respondent = Male|-0.0824|-0.0318|
||(0.0608)|(0.0416)|
|Age of Respondent (In years)|0.00417**|0.000284|
||(0.00193)|(0.00152)|
|Literacy of Respondent (Can read and write)|0.0412|0.0288|
||(0.0253)|(0.0248)|
|Experience of farming in the family (in years)|-0.00265|0.000573|
||(0.00247)|(0.00194)|
|Farming is the main source of family income|0.0181|-0.0156|
||(0.0321)|(0.0271)|
|Member of the JOHAR Producer Group (PG) in the village|(0.00411)<br>0.0948|(0.00453)<br>0.0623|
|Block FE|(0.0617)|(0.0419)|
|Observations|757|757|
|R-squared|0.406|0.215|

Note: Robust standard errors in parentheses clustered at village level *** p<0.01, ** p<0.05, * p<0.1 The coefficients in the table above are based on an OLS estimation that analyses the difference in high value crop cultivation (cultivation of fruits and vegetables) between JOHAR beneficiary farmers vs control (non-beneficiary) farmers. Column 1 reports results from a Linear Probability Estimation where the dependent variable is the probability of cultivating an HV crop by a farmer across the three cropping seasons. Column 2 reports OLS results where the dependent variable is the area under HV crop cultivation per acre of land owned by the farmer. In each regression, we control for the number of months a JOHAR system has been operational (less than or more than 18 months) as well as the access of a farmer to a diesel pump, electric pump, or a pond/canal vs a farmer with no source of irrigation. In Column 1 we control for the total land holding of a farmer in acres. We also control for whether a JOHAR farmer used a supplementary source of irrigation and whether the pump used was a solar or diesel pump. Finally, we control for other demographic characteristics such as household size, migration, upland plot proportion, use of fertilizers, pesticides, weedicides and farmyard manure, use of hybrid seeds, caste category of family, gender, age and literacy of the respondent, the experience of farming in the family and whether farming is the main source of income, membership of the JOHAR Producer Group. We also include block fixed effects to account for unobserved time invariant difference across blocks and the distance to the closest fruit/vegetable market in the village.

# _5.5 The gross value of agricultural output in the Rabi season_

Better access to irrigation can increase the gross value of agricultural output by expanding the area cropped, by raising crop yields, and by facilitating a change in the cropping pattern towards more water-intensive, higher-value crops. In this sub-section, we compare the gross value of crop output in the Rabi season of JCLIS beneficiaries with non-beneficiaries in the same block. The gross value of agricultural output, therefore, combines all three effects: the effect on the cropped area, crop yields, and choice of what crops to grow. We focus on the Rabi season because our analysis shows that irrigation is redundant in the Kharif season when the rainfall is normal like it was in Jharkhand in 2020, and there was very little area under cultivation in the summer season even in JCLIS command areas (only 6-7% of the total cultivable land) due to limited availability of water and other issues.

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