pith:R7DSHWQU
Causal State-Dependent Local Projections
State-dependent local projections recover causal impulse responses under a linearity condition that holds in many models.
arxiv:2605.05404 v2 · 2026-05-06 · econ.EM
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\pithnumber{R7DSHWQU2SVHKVZ7SOV7LTYBTU}
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Claims
We show that this interpretation obtains under the sufficient condition that the conditional mean is linear in the aggregate shock at each horizon, and that this condition holds in a broad class of canonical micro-macro environments, including first-order perturbation solutions of heterogeneous-agent models and macro-finance models.
The sufficient condition that the conditional mean is linear in the aggregate shock at each horizon (and that this linearity holds in the relevant class of models).
State-dependent local projections recover causal responses when the conditional mean is linear in the shock, a new sieve nonparametric estimator restores this interpretation with valid inference, and empirical application shows material changes in heterogeneous firm investment responses to monetary
Receipt and verification
| First computed | 2026-05-20T00:03:14.260361Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
8fc723da14d4aa75573f93abf5cf019d08d262e9d834ccd1f987380e7a38f5fe
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/R7DSHWQU2SVHKVZ7SOV7LTYBTU \
| 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: 8fc723da14d4aa75573f93abf5cf019d08d262e9d834ccd1f987380e7a38f5fe
Canonical record JSON
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