The Impact of Insurance Provision on Household Production and Financial Decisions

Jing Cai (2016) · American Economic Journal: Economic Policy

Published

October 10, 2026

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-33")

Jing Cai (2016). American Economic Journal: Economic Policy. Table 4.

Collection index · Results JSON · QMD · Reproduction code

Source specification

The comparison adds household fixed effects to the source year-effects model, retaining household size, schooling and age.

Source coefficient	Template on source sample	Source N	Template source-sample N
0.83978	0.83958	31183	31183

The source and comparison coefficients use different specifications or aggregation targets, as stated above; they are not an exact-replication comparison.

Role	Column
Outcome	area_tob
Treatment	inter1
Unit	hhno
Time	year
Cluster	county

3 retained control columns. hhsize; educ_scale; age

Estimates below divide the outcome by its source-sample standard deviation, 3.39404. Static TWFE is the treatment coefficient. Dynamic TWFE, BJS and Sun–Abraham average supported post-treatment cells by observation count. CS-DID additionally reports an equal-event-time average.

Analysis sample and treatment timing

Observations	Units	Treated	Control units	Cohorts	Clusters
31183	3466	1259	2207	1	12

Adoption is the first observed treated period. Initially treated units and units without an observed minus-one baseline are excluded. Post-adoption untreated rows are excluded for switching policies. The plot shows at most 100 seeded-sample units; estimation uses the full eligible sample. Empty cells remain missing.

y__d: 100 of 3466 units shown (seed 20261008). All eligible units enter estimation. Purple: untreated; yellow: treated; white: unobserved.

Estimates

Estimator	Estimate (SD)	SE	95% lower	95% upper	Target	Status
Static TWFE	0.24737	0.11629	-0.0085775	0.50331	Coefficient	estimated
Dynamic TWFE	0.22727	0.11073	-0.016435	0.47098	Treated cells	estimated
BJS / did2s	0.24744	0.1115	0.002039	0.49284	Treated cells	estimated
Sun–Abraham	0.22727	0.11073	-0.016435	0.47098	Treated cells	estimated
CS-DID (equal event-time)	0.24853	0.08991	0.072312	0.42475	Equal post-event times	estimated
CS-DID (treated cells)	0.24853	0.08991	0.072312	0.42475	Treated cells	estimated
SDID	nan	nan	nan	nan	Treated cells	unsupported
Matrix completion	nan	nan	nan	nan	Treated cells	unsupported
Horizontal ridge	nan	nan	nan	nan	Treated cells	unsupported
Multisynth (cohort-averaged)	nan	nan	nan	nan	Treated cells	unsupported
Multisynth (individual)	nan	nan	nan	nan	Treated cells	unsupported

Intervals use the configured clusters and the estimator’s available inference. Hollow points have no computed interval; no new refit-bootstrap batch is run.

Estimator	Reason
SDID	sdid: this adapter does not implement covariate adjustment; controls retained.
Matrix completion	matrix-completion: this adapter does not implement covariate adjustment; controls retained.
Horizontal ridge	horizontal-ridge: this adapter does not implement covariate adjustment; controls retained.
Multisynth (cohort-averaged)	multisynth-cohort: this adapter does not implement covariate adjustment; controls retained.
Multisynth (individual)	multisynth-individual: this adapter does not implement covariate adjustment; controls retained.

Event studies

Cohort homogeneity

The imported TestingInEventStudies deviations design tests positive-event-time cohort deviations jointly. This is the homoskedastic nested-model F-test; the estimator confidence intervals above use clustered inference.

**y__d: homogeneity test not identified.** Only one treated cohort remains on the common supported sample.

Fitting settings and checks

Specification	Estimator	Settings	Pooling
y__d	CS-DID	{“est_method”: “dr”, “covariate_basis”: “cell-specific rank-reduced column space”, “control_group”: “notyettreated”, “xformla”: “y ~ 1 + x0 + x1 + x2”, “panel”: true, “effective_panel”: false, “allow_unbalanced_panel”: true, “weights_name”: “weight”, “fix_weights”: null, “base_period”: “universal”, “clustervar”: “cluster”, “aggregate”: “dynamic”, “faster_mode”: true}	{}
y__d	SDID	{}	{}
y__d	Matrix completion	{}	{}
y__d	Horizontal ridge	{}	{}
y__d	Multisynth (cohort-averaged)	{}	{}
y__d	Multisynth (individual)	{}	{}

{
  "did2s_vs_direct_imputation_max_post_difference": 3.1282485808692417e-07,
  "package_aggregate_vs_estimable_cell_weights": null
}