pith:SK5JTIP6
Estimating Dynamic Marginal Policy Effects under Sequential Unconfoundedness
Dynamic marginal policy effects can be identified via tractable reduced-form expressions and estimated with a doubly robust estimator under sequential unconfoundedness.
arxiv:2604.05639 v2 · 2026-04-07 · stat.ME
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Claims
Dynamic marginal policy effects can be identified via tractable reduced-form expressions and estimated under sequential unconfoundedness with a doubly robust estimator that does not require full dynamic state information and avoids the exponential curse of horizon.
The sequential unconfoundedness assumption holds, allowing identification of dynamic MPEs from observed data without full state information.
Develops tractable reduced-form identification and a doubly robust estimator for dynamic marginal policy effects that avoids full state observation and exponential horizon curse.
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Receipt and verification
| First computed | 2026-05-20T00:00:37.741030Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
92ba99a1fea90a7bacbefe7207e885dcb20aef954a0efa8e829116654e4e62cd
Aliases
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/SK5JTIP6VEFHXLF67ZZAP2EF3S \
| 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: 92ba99a1fea90a7bacbefe7207e885dcb20aef954a0efa8e829116654e4e62cd
Canonical record JSON
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