# F4-conf-01: Treatment effects and their uncertainty taken from two published results tables

## Question
The task is to copy specified point estimates, uncertainty measures and counts exactly as printed from two arXiv extracts, and to give each one a locator:
- **DCR study** (arxiv-2609.27732v1): staggered DiD on Swiss drug consumption room openings, Tables 6 and 7.
- **RESEA study** (arxiv-2606.14621v1): randomised trial in Rhode Island, Table 2.

Two quantities that the sources do not print are derived, with the convention stated:
- a 95% CI for the Table 6 5 km ATT, computed from its SE;
- an SE for the RESEA wage ATE, computed from its CI.

The task also asks us to identify which requested quantity is not reported at all. Nothing is re-estimated.

## Data and exclusions
We read `data/README.md` (10 lines), `arxiv-2609.27732v1.txt` (134 lines) and `arxiv-2606.14621v1.txt` (58 lines). Only these extracts were used. Table A19 (DCR) and Table 3 (RESEA) were read for consistency checks only, because every key names Table 6, 7 or 2.

## Method
`out/analysis.py` finds the table rows by their labels and the columns by their headers, then parses the printed numbers and prints each line it matched.
- **Stars** are stripped from estimates and recorded separately.
- **DCR standard errors** come from the parenthesised line under each coefficient row.
- **RESEA ATE cells** are split into the estimate, the p-value and the CI bounds.
- **Formatting of printed numbers.** Thousands separators are dropped (17,250 → 17250; $2,141 → 2141). JSON cannot store trailing zeros, so printed `0.210` appears as `0.21` and `-0.340` as `-0.34`. The numeric values are identical to the printed ones.

## Results
| key | value | source |
|---|---|---|
| dcr_att_5km / se | -0.431** / (0.210) | Table 6, ATT, 5 km |
| dcr_att_3km / se | -0.283 / (0.279) | Table 6, ATT, 3 km |
| dcr_obs_5km | 17,250 | Table 6, Observations, 5 km |
| dcr_narcotics_att_3km / se | 0.549*** / (0.187) | Table 7, Narcotics, 3 km |
| dcr_fatal_att_1km / se | -1.207*** / (0.137) | Table 7, Drug-related (fatal), 1 km |
| dcr_hiv_att_5km / se | -0.340 / (0.294) | Table 7, HIV, 5 km |
| dcr_hiv_att_5km_p_value | **null**: not reported (stars only) | Table 7 |
| dcr_hiv_att_5km_significant_10pct | false (no star) | Table 7 |
| dcr_att_5km CI (derived) | [-0.8426, -0.0194] | from Table 6 |
| ri_wage_ate | $1,153; 95% CI [166, 2,141] | Table 2, Wage, ATE |
| ri_wage_ate_se_reported | false | Table 2 |
| ri_wage_ate_se_derived | 503.83 | from Table 2 CI |
| ri_control_mean_wage | $33,043 | Table 2, Wage, Control |
| ri_reemployment_ate_pp | 1.47 pp | Table 2, Reemployment, ATE |
| ri_weeks_ui_ate | -1.99 weeks; 95% CI [-2.24, -1.75] | Table 2, Weeks on UI, ATE |

The full locator strings are in `results.json` under `locators`.

## Uncertainty
- **DCR study (Tables 6 and 7).** The uncertainty is printed as **standard errors** (clustered at the MedStat region level, in parentheses) plus significance stars. No exact p-values or CIs are printed.
- **RESEA study (Table 2).** The uncertainty is printed as **95% confidence intervals** and two-sided p-values. No standard errors are printed.

How the derived quantities were computed:
- **DCR 95% CI.** -0.431 ± 1.96 × 0.210 = [-0.8426, -0.0194].
  - This uses a normal approximation with critical value 1.96.
  - The extract does not say which critical value the paper uses (it could be a bootstrap or t critical value). Using 2.0 instead would give [-0.851, -0.011].
  - The interval excludes zero, which matches the ** (p<0.05) star.
- **RESEA wage SE.** (2141 − 166) / (2 × 1.96) = 503.83.
  - This assumes the printed interval is a symmetric Wald interval with a normal critical value of 1.96.
  - The assumption is supported in two ways. The half-widths are 987 and 988. The implied z of 2.288 gives a normal two-sided p of 0.0221, against a printed p of 0.022.
  - Using 2.0 instead would give an SE of about 493.75.

## Limitations and open issues
- **Two conflicting SEs for the 5 km ATT.** Table A19 prints an SE of (0.218) for the same CS-DR 5 km ATT of -0.431, whereas Table 6 prints (0.210). We used Table 6, as the key names it.
- **Control-region count does not match the observation count.** Tables 6 and 7 say there are 608 never-treated control regions; the A19 note says 640. The printed Observations (16,175 / 16,875 / 17,250) equal (treated + 640) × 25 exactly. With 608 controls the counts would be 15,375 / 16,075 / 16,450. The observation counts are reported as printed.
- **Narrative text does not match the tables in places:**
  - The abstract says fatal hospitalisations fall by 35%. Table 7's -0.354 at 5 km implies a fall of 29.8%, and Section 6.1 says about 30%.
  - The text calls the HIV estimates "close to zero", but the 5 km point estimate is -0.340. It is insignificant, not near zero.
- **Weeks-on-UI CI sign.** The RESEA prose gives this CI as magnitudes ([1.75, 2.24] weeks). We used the signed Table 2 bounds [-2.24, -1.75].
- **Rendering and layout.** The RESEA extract has a rendering defect ("p ¡ 0.001"). Its Tables 2 and 3 were re-set by the extract editor, so we rely on the editor's statement that the values are verbatim. We could not check them against the original PDF.
- **Missing p-value.** The exact p-value for the HIV 5 km ATT is not printed, so it is reported as null. A normal-approximation p could be computed from the estimate and SE, but that would be a derived value, not a printed one.