Pith Number

pith:THEJTLRN

pith:2026:THEJTLRNBGOVI25UE3GAVT6FP7

not attested not anchored not stored refs resolved

Quasi-Bayesian Local Projection Instrumental-Variables Method: Application to Renewable Energy and Electricity Prices

Masahiro Tanaka

A roughness-penalty prior smooths LP-IV impulse responses without changing their first-order asymptotics.

arxiv:2605.15966 v1 · 2026-05-15 · econ.EM · stat.ME

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{THEJTLRNBGOVI25UE3GAVT6FP7}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Simulations indicate that this regularization decreases root mean squared error compared to standard GMM, especially at medium and longer horizons. The approach maintains the key first-order features of traditional LP-IV methods, while enhancing stability in finite samples and allowing for joint inference through simultaneous bands.

C2weakest assumption

The roughness-penalty prior can be introduced without changing the first-order asymptotic distribution of the LP-IV estimator, so that the quasi-Bayesian procedure remains consistent for the same parameters as ordinary GMM-based LP-IV.

C3one line summary

A quasi-Bayesian LP-IV estimator is proposed that regularizes impulse responses via a roughness-penalty prior on the GMM objective, reducing finite-sample RMSE while preserving first-order asymptotics.

References

44 extracted · 44 resolved · 0 Pith anchors

[1] Barnichon, R. & Brownlees, C. (2019). Impulse response estimation by smooth local projections. Review of Economics and Statistics , 101(3), 522--530 2019

[2] Barnichon, R. & Matthes, C. (2018). Functional approximation of impulse responses. Journal of Monetary Economics , 99, 41--55 2018

[3] Bissiri, P. G., Holmes, C. C., & Walker, S. G. (2016). A general framework for updating belief distributions. Journal of the Royal Statistical Society Series B: Statistical Methodology , 78(5), 1103-- 2016

[4] Borenstein, S. (2002). The trouble with electricity markets: Understanding C alifornia's restructuring disaster. Journal of Economic Perspectives , 16(1), 191--211 2002

[5] Chernozhukov, V. & Hong, H. (2003). An MCMC Approach to Classical Estimation . Journal of Econometrics , 115(2), 293--346 2003

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-20T00:01:46.989854Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

99c899ae2d099d546bb426cc0acfc57fc136ef5e666ccce2a17a76c2ad79f800

Aliases

arxiv: 2605.15966 · arxiv_version: 2605.15966v1 · doi: 10.48550/arxiv.2605.15966 · pith_short_12: THEJTLRNBGOV · pith_short_16: THEJTLRNBGOVI25U · pith_short_8: THEJTLRN

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/THEJTLRNBGOVI25UE3GAVT6FP7 \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 99c899ae2d099d546bb426cc0acfc57fc136ef5e666ccce2a17a76c2ad79f800

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "e7ef258b113244bb96c33551d6ab919d958b55a4648848e30c6bf36af44410ed",
    "cross_cats_sorted": [
      "stat.ME"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "econ.EM",
    "submitted_at": "2026-05-15T13:56:37Z",
    "title_canon_sha256": "f39e57a0a495824bfd6e030fdd1596d27f6a9e6c2f92684979ec4c4db950c0d2"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.15966",
    "kind": "arxiv",
    "version": 1
  }
}