Baseline Remittance Level Heterogeneity

Picture this

Imagine offering a fuel discount voucher to two drivers: one who rarely drives due to high fuel costs, and another who already drives every single day [15, 17]. The driver who rarely drove increases their trips significantly when given the discount, whereas the daily driver makes no additional trips because their driving behavior was already at capacity [17].

What the evidence says

Among migrants with below-median baseline remittances, labeling access significantly increased the probability of remitting (+1.0 percentage point, p < 0.01), weekly remittance frequency (+0.012 transfers, p < 0.01), winsorized weekly amount (+174.94 PhP, p < 0.05), and log weekly remittance amount (+0.083, p < 0.01), while showing no statistically significant effect on high-baseline remitters [19, 20].

Who was studied

2,408 low-baseline remitters (below median pre-treatment remittances) and 2,043 high-baseline remitters (above median) out of 4,451 analyzed migrant workers in the United Arab Emirates [19, 20].

How

Ordinary least-squares (OLS) panel regression with individual and week fixed effects across subsamples split by baseline remittance volume during weeks 1–5 [17, 19-21].

What to do

Segment financial policy evaluations by pre-treatment transaction volume to detect intervention impacts specific to under-performing user segments [15, 17, 22].

From the source

"The estimated treatment coefficients indicate a consistent positive effect of labeling on all remitting dimensions when the sample included migrants that were sending below the median in the first 6-9 weeks before the labeling feature was activated in Padalapp [17]."

A Field Experiment among Filipino Migrant Workers in the UAE

Tags

• treatment heterogeneity
• baseline remittances
• rct