Discontinuity Assignment Identification
RD estimates confirmed that direct learning gains for tutored students approached 1.00 standard deviation, while untutored peers above the rank cutoff showed no statistically significant indirect benefits.
Tag
econometrics
8 cards
Dynamic Selection Bias in Duration Models
Uncorrected raw Kaplan-Meier hazard rates provide only a lower bound on treatment efficacy due to dynamic selection, whereas MPH duration models correctly isolate true 20–40% exit rate increases.
Financial Outcome Winsorization
Winsorization bounded weekly remittance amounts (control mean 2,338.50 PhP), stabilizing regression estimates across full sample (p = 0.81) and low-baseline subsample (+174.94 PhP, p < 0.05) specifications.
Indirect Inference Structural Estimation
The structural parameters matched the reduced-form empirical moments (treatment exit rate, control exit rate, regional comparison exit rate, and vacancy response curves), validating structural policy simulation counterfactuals.
Intent-to-Treat (ITT) Estimation Framework
Estimated overall ITT remittance probability increase of +0.007 (p < 0.10) across all treatment-assigned migrants, preventing self-selection bias from confounding the experimental estimates.
Intention-to-Treat (ITT) Instrumentation
In Year 2 in Mumbai, 33% of schools assigned to receive a balsakhi tutor did not receive one due to administrative difficulties; 2SLS instrumentation successfully eliminated non-compliance bias to yield unbiased direct treatment estimates.
Kling Summary Index Aggregation
The Kling labeling index demonstrated a statistically significant treatment take-up effect (mean index = 1.233, t = 44.445, p < 0.001) and a statistically significant overall remittance increase in the low-baseline subsample (+0.027 index units, p < 0.01).
Pre-Experimental Out-of-Sample Predictive Profiling
The historical model successfully stratified the experimental sample into 1,688 high-employability ($\le 6$ months) and 2,475 low-employability ($> 6$ months) individuals, correctly identifying 87% of long-duration cases in baseline data without endogenous stratification bias.