Original collectionUnder development

Under development — library extension. This report is part of the expanded-library work, not the original collection. Source preparation, methods and results are subject to revision.

Provisional eligibility assessment — under development. Deep DiD follow-up: The source uses Post x Treatment with household, calendar month and event-time effects. The stack construction retains controls shocked more than 24 months later; absorbing status is within the chosen health-shock window, not a lifetime state. Preserve stack IDs, reused controls and household inference. This working assessment is not fully vetted and may change. See the report below for its recorded replication or assessment status. Provisional eligibility log

Propagation and Insurance in Village Networks

Cynthia Kinnan; Krislert Samphantharak; Robert Townsend; Diego Vera-Cossio (2023) · American Economic Review

import sys
from pathlib import Path

ROOT = next(
    p for p in [Path.cwd(), *Path.cwd().parents]
    if (p / "scripts/tranche50_report.py").exists()
)
sys.path.insert(0, str(ROOT / "scripts"))
from tranche50_report import report

report("aeraej-15", tranche="tranche150")

Cynthia Kinnan; Krislert Samphantharak; Robert Townsend; Diego Vera-Cossio (2023). American Economic Review. Table 2 Panel A.

Collection index · Results JSON · QMD · Reproduction code

Template assessment

The household-dyad source uses PostXclose, the shock-period indicator times inverse network distance, with dyad-related effects and two-way clustering. The continuous network spillover coefficient is not a binary adoption ATT.

No comparison point or homogeneity-test decision is assigned to this paper.