Targeting the Poor Secondary Students for Stipend: Identifying the Gap between Policy and Implementation
Well-designed and efficient poverty-based targeting methods are necessary for effectively identifying the poor households in poverty eradicating programs. This study investigates the ex-post implementation process and performance of two common targeting approaches - Proxy Means Test (PMT) and Community-Based Targeting (CBT)- to target the poor beneficiaries in a conditional cash transfer program in Bangladesh. Each method's effectiveness and implementation status was assessed using the Bangladesh Integrated Household Survey (BIHS) third round (2018-19) data in Bangladesh. Firstly, we used the probit regression model to check whether the targeting in practice follows the PMT and CBT's set of eligibility criteria. Then, we added the consumption-based poverty indicators (alternative poverty measure) and other control variables to find the other factors that might predict the selection. Secondly, we test the targeting performance using two popular targeting efficiency indicators (i.e., erroneous exclusion of the poor and erroneous inclusion of non-poor). This paper finds that although the PMT mostly followed implementation guidelines, it had high exclusion error and low coverage. In contrast, the CBT performed poorly executing the pre-defined poverty selection criteria, and the stipend selection committee used their local knowledge to identify the beneficiaries. The study also reveals that the mother's years of education and the concrete road in the community play a vital role in reducing exclusion error and increasing inclusion error under CBT. In line with other literature on this program, there were many anomalies in the selection process, and authorities should make practical implementation steps to realize the programs' full potential.
Conditional Cash Transfer
Proxy Means Testing (PMT)
Community-Based Targeting (CBT)
Master Degree Project