Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This article evaluates the impacts of a controlled irrigation technique in rice production called alternate wetting and drying (AWD). Propensity score matching (PSM) and regression-based approaches applied to farm-level survey data are used to achieve the objective of the study. The PSM and regression-based approach accounts for the potential bias due to selection problems from observable variables. Results of the impact analysis using both empirical approaches indicate that AWD, particularly the "Safe AWD" variant, reduces the hours of irrigation use (by about 38%), without a statistically significant reduction in yields and profits. This reduction in irrigation time translates to corresponding savings in the amount of irrigation water and pumping energy used. However, further analysis of the impact estimates suggests that the potential magnitude of the selection bias based on unobservable variables may still be able to eliminate the measured impact from the PSM and regression-based techniques that only control for selection based on observable variables. Hence, the current impact results have to be interpreted with caution and further data collection is needed to construct a panel data that would allow one to account for selection problems due to unobservable variables and, consequently, better estimate the AWD impact.