that can conduct the computations on the fly, or a reliable internet connection for processing in the cloud, would be required. Enumerator training is another implementation aspect that would require adjustment as the targeting survey questions need to be ordered by their stepwise regression sequence rather than the standard of thematic grouping. A final IT-related issue is that the social registry information collected with a TrESt or early stopping approach would collect jagged optional question data, so that survey designers would need to include all variables required for analytical or monitoring purposes in the core questionnaire.

Although the simulations presented here suggest scope for reducing survey costs while potentially reducing exclusion errors, this paper is only deskbased proof of concept. Indonesia has already achieved good targeting outcomes through years of investment in improving targeting processes and implementation. Continued improvements in design could further strengthen targeting outcomes at no additional cost, but piloting would be advisable to verify that the method is practical, that the results hold in the field, and also to collect additional data. For Indonesia, a simple PMT trial that collects the survey metadata to estimate realistic survey times would provide key budgetary inputs. Similarly, information on travel times between households would be important to calibrate time savings, particularly in rural districts and island locations where shorter questionnaires may only yield negligible savings. Detailed cost estimation along the lines of Fujii and van der Weide [2020] on the cost-effectiveness of double sampling would be advisable if implementation were to be considered.

One way to improve accuracy may be to draw on alternative data sources, such as the exploration of internet and phone expenditure for Indonesia’s PMT by Pinxten [2021]. Such data can potentially support better classification, shorter questionnaires, or both. Similarly, alternative data preparation tailored to the early stopping approach may offer significant benefits in terms of accuracy or question numbers. On the other hand, the shortened questionnaire raises the risk of misreporting, as it concentrates both predictive power and enumerator attention on a few high-impact variables. A restriction to verifiable variables may mitigate this risk, but monitoring of response patterns would remain important to identify emerging subterfuge.

Beyond a more detailed assessment of financial and logistical aspects, additional applications with data from other countries would be helpful in assessing whether the early stopping algorithm can be a useful tool in other settings. The distributional impact in terms of unequal outcomes for different groups is another important aspect that would warrant further exploration. Appendix B outlines an illustrative group-level analysis which suggests that outcomes for pensioner households are similar for early stopping when compared with a standard PMT. Further reassurance would be gained by verification of estimation consistency for a full range of relevant vulnerable groups, as well as by a more extensive exploration of targeting fairness 30