Test Data Fixtures

hrs_edid_validation.csv

Source: Dobkin, C., Finkelstein, A., Kluender, R., & Notowidigdo, M. J. (2018). "The Economic Consequences of Hospital Admissions." American Economic Review, 108(2), 308-352. Replication kit: https://www.openicpsr.org/openicpsr/project/116186/version/V1/view

Sample selection: Follows Sun & Abraham (2021), as used by Chen, Sant'Anna & Xie (2025) Section 6:

1. Read HRS_long.dta from the Dobkin et al. replication kit
2. Keep waves 7-11, retain only individuals present in all 5 waves
3. Filter to ever-hospitalized individuals with first_hosp >= 8
4. Filter to ages 50-59 at hospitalization (age_hosp)
5. Drop wave 11 (no valid comparison group)
6. Recode first_hosp == 11 as never-treated (inf)

Expected counts:

Column	Values
Total individuals	656
Waves	7, 8, 9, 10
Rows	2,624
G=8	252
G=9	176
G=10	163
G=inf	65

Columns: unit (hhidpn), time (wave), outcome (oop_spend, 2005 dollars), first_treat (first_hosp)

Regeneration: Requires the Dobkin et al. replication kit (.gitignored as replication_data/).

import pandas as pd, numpy as np
df = pd.read_stata("replication_data/116186-V1/Replication-Kit/HRS/Data/HRS_long.dta")
sub = df[df["wave"].isin([7, 8, 9, 10, 11])]
balanced = sub.groupby("hhidpn")["wave"].nunique()
sub = sub[sub["hhidpn"].isin(balanced[balanced == 5].index)]
sub = sub[sub["hhidpn"].isin(sub[sub["first_hosp"].notna()]["hhidpn"].unique())]
fh = sub.groupby("hhidpn")["first_hosp"].first()
sub = sub[sub["hhidpn"].isin(fh[fh >= 8].index)]
ages = sub.groupby("hhidpn")["age_hosp"].first()
sub = sub[sub["hhidpn"].isin(ages[(ages >= 50) & (ages <= 59)].index)]
sub = sub[sub["wave"] <= 10]
sub["first_treat"] = sub["first_hosp"].apply(lambda x: np.inf if x == 11 else int(x))
out = sub[["hhidpn", "wave", "oop_spend", "first_treat"]].copy()
out.columns = ["unit", "time", "outcome", "first_treat"]
out["unit"] = out["unit"].astype(int)
out["time"] = out["time"].astype(int)
out.sort_values(["unit", "time"]).reset_index(drop=True).to_csv(
    "tests/data/hrs_edid_validation.csv", index=False
)