<u>Table 2: Precautionary Planting and Risk Aversion</u>

||(1)|(2)|(3)|(4)|(5)|
|---|---|---|---|---|---|
|log(borewell plot area)|0.573***|0.560***|0.544***|0.545***|0.545***|
||(0.0155)|(0.0149)|(0.0146)|(0.0144)|(0.0145)|
|log(mean well fow)||0.692***|0.763***|0.770***|0.762***|
|||(0.110)|(0.110)|(0.111)|(0.110)|
|log(pipe width)||0.463***|0.441***|0.439***|0.440***|
|||(0.0366)|(0.0405)|(0.0406)|(0.0405)|
|log(_CV_)|-0.709***|-0.311***|-0.249***|-0.226**|-0.213***|
||(0.0256)|(0.0459)|(0.0468)|(0.0882)|(0.0749)|
|_RISK_<sup>1</sup>||||-0.0146<br>(0.0231)||
|log(_CV_)_× RISK_<sup>1</sup>||||-0.00309||
|||||(0.0118)||
|_RISK_<sup>2</sup>|||||-0.144|
||||||(0.176)|
|log(_CV_)_× RISK_<sup>2</sup>|||||-0.0537<br>(0.0925)|
|_R_<sup>2</sup>|0.599|0.634|0.645|0.645|0.645|
|Controls|No|No|Yes|Yes|Yes|

_Notes:_ Robust standard errors in parentheses adjusted for clustering on borewell (*** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1). Sample size is 2,411 borewells. Dependent variable in all regressions is log(total irrigated area by borewell); CV is the coefficient of variation of end-of-season well flow; _RISK_<sup>1</sup> is a self-assessed ranking of risk tolerance; _RISK_<sup>2</sup> is an index of marginal willingness-to-pay for risk based on Binswanger lotteries. Unreported controls are as follows: pump horse-power, log of well depth, number of other borewells within 100 meters, dummy for presence of recharge source.

our six districts, principally paddy, banana, sugarcane, and mulberry) and irrigated-dry or ID crops (e.g., groundnut, maize, cotton, chillies), distinguished by the much greater water requirements of the former. Since a field that, planted to ID crops, would take 3 days to irrigate would take a week to irrigate under wet crops, we use the equivalence 1 acre wet = <u>7</u><sup>IDtocomputetotalareairrigatedbyaborewell.25</sup> 3<sup>acre</sup> We investigate the effect of uncertainty on _rabi_ area irrigated by a borewell conditional on the plot area of that borewell. For 27% of the borewells, irrigated area is less than reference plot area (also expressed in dry-equivalent acres), indicating that part of the borewell’s plot

> 25We carry this efficiency units assumption over to our structural estimation. To appreciate the simplification thereby achieved, consider the implications of separate wet and ID crop technologies. In the first place, conditional on area choices of each crop type, farmers would presumably allocate groundwater ex-post across crops in response to the realized _w_ . This gives rise to one additional optimality condition _for each state of nature_ . Second, there would be two cultivated area choices, and farmers are observed opting for mixed wet-ID cropping as well as for monoculture of either type. To rationalize the data, our empirical model would need two structural error terms (instead of just the one ultimately assumed) and would have to account for the two types of corner solutions in cropped area. Third, for any form of groundwater transfer, each cell of the 3 _×_ 3 matrix of wet-ID-mixed cropping decisions of borewell owner and groundwater recipient would have to be compared to determine the optimal arrangement and the bivariate distribution of the structural error terms partitioned accordingly. As the composite-crop model already captures the fundamental trade-off between ex-ante and ex-post efficiency, we believe that a dual-crop model offers little in the way of additional insight relative to this enormous increase in computational burden.

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