# RUNLOG

- started (UTC): 2026-10-05T15:42:09Z
- HEAD: a1de37e78b4ee538d818dbb5204e473d47f6d001
- prereg-v1: 564594d225d27ee8ad345f70606c3175f11db929
- prereg-v1 tag object: 91c1480760dd41ab56c54890a8a003fc5f585dc9
- SHA-256 of `prereg-v1:docs/prereg-v1.sha256` (its exact bytes; this is the value OpenTimestamps stamps): bda29a49b8dfba6a4c0c7a1ff04752556d30d551b9a39bd7007416f2c77e441b
- repo (REPO.resolve()): /home/colin/Documents/Projects/whopays
- sys.argv: ["/home/colin/Documents/Projects/whopays/analysis/run.py", "--panel", "data/derived/panel.csv", "--units", "data/derived/units.csv"]
- main(argv): null
- python 3.14.4, numpy 2.5.3, pandas 3.0.6, scipy 1.18.1

## Input SHA-256 (written before any model was fitted)

- `data/derived/panel.csv`  c1c5cf56e5576949debab99fa46a56d7efae244dd780e4fa15ebf28c4dadb635
- `data/derived/units.csv`  fbc0f82dc96c7923a8aefdb59e76444f8063ebe1fd7386c14a3283d1dd4dad5d
- `data/derived/panel_extended.csv`  632b6bff3f0d211b2d7c55fd68477fbec660175f9227705854b7c437795544a0
- `data/derived/units_extended.csv`  eae549ab5b2a3ecbd3d315aeecb3ed71c044e8dd1982844abdf08fb4f5103b86
- `/home/colin/Documents/Projects/whopays/docs/appendix_C_power.csv`  13f19b0d82eea35d1ad100e3d037097b0a98ede67ab73269257bdea8989baa87
- `/home/colin/Documents/Projects/whopays/data/derived/fetch_manifest.csv`  805a300309eea2f574141b28a65bdb38f53746189e0af2d5edc3dddedc879cfe
- `/home/colin/Documents/Projects/whopays/data/derived/panel_provenance.json`  677e5a83ded637636de3f72aaf571ad3fef93e3049aeceadfbca903aedb7efae
- `/home/colin/Documents/Projects/whopays/data/raw/eia861m/sales_ult_cust_2015.xls`  a77235bba902b75d90f6914c48b2172146d8a47e6537fc1ce6f4107c28e2d0aa
- `/home/colin/Documents/Projects/whopays/data/raw/eia861m/sales_ult_cust_2016.xlsx`  2a42a8a975aa014ac713f49d28dd2ead0d48167bf84117713ab751b315954cd6
- `/home/colin/Documents/Projects/whopays/data/raw/eia861m/sales_ult_cust_2017.xlsx`  70f2427eb73f96524e3d759609d05b2e2c6d5a355e3104bb47880da20c0ab31a
- `/home/colin/Documents/Projects/whopays/data/raw/eia861m/sales_ult_cust_2018.xlsx`  42afd53bd5f4f8a8e9ad1d973add208e052af9b84c403d8b37e9447a7d31d683
- `/home/colin/Documents/Projects/whopays/data/raw/eia861m/sales_ult_cust_2019.xlsx`  39524378d0be24c64ca53e57938afa4136489cdc1c7280d57d4528406ac4b4d9
- `/home/colin/Documents/Projects/whopays/data/raw/eia861m/sales_ult_cust_2020.xlsx`  015da31d07fa6854d9115a127a04fd6f6589b1eb3acb13703ca9b835aed94d68
- `/home/colin/Documents/Projects/whopays/data/raw/eia861m/sales_ult_cust_2021.xlsx`  b8f9393eef44bb4896f6ad900161c4cf4bfe8abc89cbca8cef5669140c2f8e88
- `/home/colin/Documents/Projects/whopays/data/raw/eia861m/sales_ult_cust_2022.xlsx`  8f503dd5196ab6a99bfedb5282366f93837f2e6dcb0a94870bd9ed5d374dcb2e
- `/home/colin/Documents/Projects/whopays/data/raw/eia861m/sales_ult_cust_2023.xlsx`  c0e3144005cb66f3a796a80dec9321f48d6dd23b73cd16b1418ad5bb561c1eeb
- `/home/colin/Documents/Projects/whopays/data/raw/eia861m/sales_ult_cust_2024.xlsx`  bdcd1164b00dd70a09b83b753d45766ea2a92c5385feb30268217312c210379f
- `/home/colin/Documents/Projects/whopays/data/raw/eia861m/sales_ult_cust_2025.xlsx`  b43f08a1cdfb1f2d193fdb925b1180607b3734918fc74f7cf5a90087bb557f23
- `/home/colin/Documents/Projects/whopays/data/raw/eia861m/sales_ult_cust_2026.xlsx`  70fc58052e2f9bbc6c0dbde4a33f53c7ec39715cd825278af045a508fe55ef6f

## Binding to the freeze

- REAL run: the four inputs are byte-identical to the frozen inputs
- `data/derived/panel.csv` <- data/derived/panel.csv: identical to the frozen line
- `data/derived/units.csv` <- data/derived/units.csv: identical to the frozen line
- `data/derived/panel_extended.csv` <- data/derived/panel_extended.csv: identical to the frozen line
- `data/derived/units_extended.csv` <- data/derived/units_extended.csv: identical to the frozen line

## Frozen files SHA-256 (each equals the line frozen in the tag; any mismatch would have refused the run)

- `analysis/__init__.py`  16ea2907ea796838e07c65afc94b9b0cf2ed4fd9ed1b65fa1ddce67034743ff5
- `analysis/checks.py`  e562341cc99c7c6a07387a8200527d36b0dd0c6150acdd0774842156ec307f3f
- `analysis/model.py`  2c62ea3b2fde38873199d5ebe597c46bfbd22d2ba8abefec5f04755912c9dd37
- `analysis/run.py`  7ed64fa07d9c97a54870b6c0537bf5c528339ae6090afd3092e3884adf79cea4
- `data/derived/exposure_pjm_2023.csv`  f5479342421711679da024028a4f8b866a669fd634d9310e86de642d80fe502b
- `data/derived/exposure_pjm_2024.csv`  2682fc5779ff732f39352570ed8ad0683b1fa289ab69bfd5e4a80c15325962ad
- `data/derived/panel.csv`  c1c5cf56e5576949debab99fa46a56d7efae244dd780e4fa15ebf28c4dadb635
- `data/derived/panel_extended.csv`  632b6bff3f0d211b2d7c55fd68477fbec660175f9227705854b7c437795544a0
- `data/derived/units.csv`  fbc0f82dc96c7923a8aefdb59e76444f8063ebe1fd7386c14a3283d1dd4dad5d
- `data/derived/units_extended.csv`  eae549ab5b2a3ecbd3d315aeecb3ed71c044e8dd1982844abdf08fb4f5103b86
- `data/raw/eia861m/sales_ult_cust_2015.xls`  a77235bba902b75d90f6914c48b2172146d8a47e6537fc1ce6f4107c28e2d0aa
- `data/raw/eia861m/sales_ult_cust_2016.xlsx`  2a42a8a975aa014ac713f49d28dd2ead0d48167bf84117713ab751b315954cd6
- `data/raw/eia861m/sales_ult_cust_2017.xlsx`  70f2427eb73f96524e3d759609d05b2e2c6d5a355e3104bb47880da20c0ab31a
- `data/raw/eia861m/sales_ult_cust_2018.xlsx`  42afd53bd5f4f8a8e9ad1d973add208e052af9b84c403d8b37e9447a7d31d683
- `data/raw/eia861m/sales_ult_cust_2019.xlsx`  39524378d0be24c64ca53e57938afa4136489cdc1c7280d57d4528406ac4b4d9
- `data/raw/eia861m/sales_ult_cust_2020.xlsx`  015da31d07fa6854d9115a127a04fd6f6589b1eb3acb13703ca9b835aed94d68
- `data/raw/eia861m/sales_ult_cust_2021.xlsx`  b8f9393eef44bb4896f6ad900161c4cf4bfe8abc89cbca8cef5669140c2f8e88
- `data/raw/eia861m/sales_ult_cust_2022.xlsx`  8f503dd5196ab6a99bfedb5282366f93837f2e6dcb0a94870bd9ed5d374dcb2e
- `data/raw/eia861m/sales_ult_cust_2023.xlsx`  c0e3144005cb66f3a796a80dec9321f48d6dd23b73cd16b1418ad5bb561c1eeb
- `data/raw/eia861m/sales_ult_cust_2024.xlsx`  bdcd1164b00dd70a09b83b753d45766ea2a92c5385feb30268217312c210379f
- `data/raw/eia861m/sales_ult_cust_2025.xlsx`  b43f08a1cdfb1f2d193fdb925b1180607b3734918fc74f7cf5a90087bb557f23
- `data/raw/eia861m/sales_ult_cust_2026.xlsx`  70fc58052e2f9bbc6c0dbde4a33f53c7ec39715cd825278af045a508fe55ef6f
- `data/raw/eia923/annual_generation_state.xls`  17873cccfb86208563b98493619699fa090a43fd93e5d1376e53ac59d7093141
- `data/raw/eia_gas/henry_hub_monthly.xls`  b5af6a6b5810893a334878da1686a89f8eb7d6d7cf49658eba458ff573cfe6e2
- `data/raw/eia_gas/ng_electric_power_price_bystate.xls`  17055d59eece15affd26c019f2c1098c79884d58f7fa413600ae89742317a255
- `docs/PREREGISTRATION.md`  2a3cd989847458174dbeae74113ec32561373f67516142af41af62d4f24dc500
- `docs/appendix_A2_merger_effects.csv`  323c5cf0eec76fcdc1801efbc4b9a14ac35a3e79354447a03df716e41aa75b17
- `docs/appendix_A2_mergers.csv`  e0b7ed853954d605de710510d4eb534ef89c52509a1d5d07a9ce93687f7e5e7f
- `docs/appendix_A3_extended.csv`  d61b004efdbea7905d99d183df5c9694768f9727043b870f06dca0f6190a0b9b
- `docs/appendix_A_sample.csv`  025d07e46e0facc4f24ddfcf13801b97a3e421a74f65b07e06d6f8c4be08e264
- `docs/appendix_B2_gas_share.csv`  53b992b14619f375c102bd2fdfbb57ae80dc75576d15b800eb70ee7ef7612b1a
- `docs/appendix_B_exposure.csv`  66b9e3857af277cd6c1c69c6c056e9dc1486701fb2515dc3f6c578f3c83f07a2
- `docs/appendix_C_power.csv`  13f19b0d82eea35d1ad100e3d037097b0a98ede67ab73269257bdea8989baa87
- `pipeline/__init__.py`  8208e6b2f55ac1640ea3770202abed01b9e89819a08de8e3c9c49f32c4a8363f
- `pipeline/appendices.py`  11a57b161af2f9cb53551e72b4803e7afd2acc8f43bef34b4f369ad2ba7ce3c7
- `pipeline/construct.py`  266a82cd021b98c801e0c3248669c41ca1ef09323d17d7ddff639e4a368ae6b6
- `pipeline/exposure.py`  ff1b016892632764b9e0cc42fae89cc11f76bf12473d4406d6ccef8bb5379442
- `pipeline/fetch.py`  ac4979600c64cf7e1d31d6b4be3fa8a555f1c598423a12bb357ae68e8869e1b0
- `pipeline/freeze.py`  13c42a55fd3b594c5584681fd53993a0d6a5554066a635cff67d2f77d268919e
- `pipeline/mergers.py`  99c3f87c6af8010891fe8874511708700f51308ae7b8fdc800510ce62e5acc80
- `pipeline/panel.py`  d90d5e22926adbe8414372551df2c04c1a6adf95cde3fa502faaaabe6f6a1ac7
- `pipeline/pjm.py`  efb5596da7e238350297728c3a13c0eb882cd55e5cd6e27158bd299f61adb58a
- `pipeline/pjm_zones.py`  8ad711b79c215f43845a1fc0814e2ee995375bc59c001f53341535b2340fe27b
- `pipeline/power.py`  dd053bcd4ff160a52995e78d0dc8a9621633e577cd4ec934645b00b290d6b583
- `pipeline/region_map.py`  277e22db8fd9263c5abb6167b6e0add37fad5a4c1cce379bf14ee74cc63b473e
- `pipeline/sample.py`  41de84601267925c2110fada554b1badb8da9336aa93d33699b48c40cc9d9f55
- `pipeline/validate.py`  57366f668ba76e7663244d2c8827ddba6735d5fc104013122b024f1cd24fb3de

## Result

- decision row 6: So far, we don't see fast-growing business demand pushing household bills above similar areas.
- beta -0.01736, RI p 0.4011 (smallest possible 0.0001), draws 9999
- full output: results.json (sha256 ba0cff0a1a7b7c21fb96ec504b221384f24b83ca473d568f79308df926992caf)