We develop and assess the performance of an econometric targeting model for a large scale humanitarian aid program providing unconditional cash and food assistance to refugees in Lebanon. We use regularized linear regression to derive a prediction model for household expenditure based on demographic and background characteristics; from administrative data that are routinely collected by humanitarian agencies. Standard metrics of prediction accuracy suggest this approach compares favorably to the commonly used “scorecard” Proxy Means Test, which requires a survey of the entire target population. We confirm these results through a blind validation test performed on a random sample collected after the model derivation.
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