edits to draft documents

analysis/draft_appendix.md

@@ -9,24 +9,26 @@ The analysis combines inspection and violation administrative records (2015-2025
 
 ### A2. Core variables
 
-| Variable | Definition |
+| Measure | Definition |
 | :--- | :--- |
-| `log_days_to_enf` | Log of district-year mean days from violation discovery to enforcement action |
-| `resolution_rate` | Share of violations compliant on re-inspection |
-| `compliance_rate` | Share of inspections marked compliant |
-| `violations_per_inspection` | Total violations divided by inspections |
-| `post_2019` | Indicator for years >= 2019 |
-| `post_trend` | Piecewise linear trend after policy (`max(year-2018,0)`) |
-| `offshore_jurisdiction` | Indicator for districts 02/03/04 |
-| `high_capacity` | District above median pre-policy inspection volume |
-| `low_baseline_compliance` | District below median pre-policy compliance |
-| `high_eji` | District above median EJ score |
-| `high_rural` | District above median RUCA |
-| `border_competition` | Operationalized border-proximity indicator |
-| `primary_basin` | Dominant basin category |
+| Enforcement delay (logged) | Log of district-year mean days from violation discovery to enforcement action |
+| Resolution on re-inspection | Share of violations compliant on re-inspection |
+| Inspection compliance rate | Share of inspections marked compliant |
+| Violations per inspection | Total violations divided by inspections |
+| Post-policy period indicator | Indicator for years >= 2019 |
+| Post-policy trend term | Piecewise linear trend after policy (`max(year-2018,0)`) |
+| Offshore jurisdiction indicator | Indicator for districts 02/03/04 |
+| High-capacity indicator | District above median pre-policy inspection volume |
+| Low-baseline-compliance indicator | District below median pre-policy compliance |
+| High-EJ indicator | District above median EJ score |
+| High-rurality indicator | District above median RUCA |
+| Border-proximity indicator | Operationalized border-proximity indicator |
+| Dominant basin category | Dominant basin category |
 
 ## Appendix B. Econometric Specifications
 
+The specification sequence follows the main text: a common-shock interrupted panel for H1, district-specific post-policy heterogeneity for H2, an offshore moderator for H5, and a global spatial autocorrelation diagnostic for H4. Because all districts are exposed in the same policy year, heterogeneity is modeled through district-by-post interactions rather than staggered-adoption treatment-timing estimators.
+
 ### B1. Interrupted panel (all districts; H1)
 
 \[
@@ -47,14 +49,18 @@ Y_{dt}=\alpha_d + \gamma_t + \sum_d \theta_d (\text{District}_d\times \text{Post
 
 All models report district-clustered standard errors.
 
+### B4. Spatial diagnostic (H4)
+
+H4 is tested using permutation-based global Moran's I on estimated district treatment effects.
+
 ## Appendix C. Main Run Outputs
 
 ### C1. H1 (all-district timing outcome)
 
-| Parameter | Coefficient | P-value |
+| Effect term | Coefficient | P-value |
 | :--- | ---: | ---: |
-| `post_2019` | 0.1514 | 0.3294 |
-| `post_trend` | -0.3603 | 0.0010 |
+| Immediate post-2019 level shift | 0.1514 | 0.3294 |
+| Post-2019 annual trend shift | -0.3603 | 0.0010 |
 
 Interpretation: no significant immediate level shift; significant post-policy acceleration slope.
 Substantively, this table supports the main-text conclusion that the policy effect is best characterized as gradual acceleration through the enforcement pipeline rather than a single break at policy adoption.
@@ -93,9 +99,9 @@ These estimates indicate that offshore jurisdictions diverge from non-offshore d
 
 ### C4. H5 offshore moderator (conditional model)
 
-| Parameter | Coefficient | P-value |
+| Effect term | Coefficient | P-value |
 | :--- | ---: | ---: |
-| `post_2019:offshore_jurisdiction` | 0.3819 | <0.001 |
+| Offshore-by-post-policy differential | 0.3819 | <0.001 |
 
 See **Figure 4** in the main text (`district_treatment_effects_map_psj.png`) for the geographic distribution of district treatment effects.
 Read alongside C3, this pooled interaction should be interpreted as an average offshore differential in the post period after district heterogeneity is already modeled, not as a claim that offshore status is the dominant driver of all district variation.
@@ -132,7 +138,7 @@ The sign and magnitude of Moran’s I are both small, indicating no evidence tha
 
 ### E1. Placebo policy years (all-district interrupted model)
 
-| Placebo year | Coefficient (`post`) | P-value |
+| Placebo year | Estimated level shift | P-value |
 | :--- | ---: | ---: |
 | 2017 | 0.6565 | 0.0020 |
 | 2021 | -0.0245 | 0.9191 |
@@ -141,7 +147,7 @@ The significant 2017 placebo estimate suggests that single-cut timing designs ca
 
 ### E2. Alternative outcomes (all-district interrupted model)
 
-| Outcome | `post` coef (p) | `post_trend` coef (p) |
+| Outcome | Immediate post-policy level effect (p) | Post-policy trend effect (p) |
 | :--- | :--- | :--- |
 | Resolution rate | 4.3721 (0.2104) | -2.9371 (0.1424) |
 | Compliance rate | -0.1311 (0.9316) | -0.5562 (0.1870) |
@@ -151,7 +157,7 @@ This table shows that timing acceleration does not mechanically translate into i
 
 ### E3. Sample restrictions (all-district interrupted model)
 
-| Restriction | `post_2019` coef (p) | `post_trend` coef (p) |
+| Restriction | Immediate post-policy level effect (p) | Post-policy trend effect (p) |
 | :--- | :--- | :--- |
 | Full sample | 0.1514 (0.3294) | -0.3603 (0.0010) |
 | Exclude extreme districts | 0.1917 (0.1930) | -0.2972 (0.0133) |
@@ -162,7 +168,7 @@ Across restrictions, the post-trend estimate remains negative and generally sign
 
 ### E4. Specification sensitivity
 
-| Specification | `post` effect | `post_trend` effect |
+| Specification | Immediate post-policy level effect | Post-policy trend effect |
 | :--- | :--- | :--- |
 | Linear interrupted | -41.9298 (p=0.3104) | -67.0420 (p=0.0100) |
 | Winsorized interrupted | 0.2137 (p=0.1021) | -0.3147 (p=0.0016) |