New semiparametric estimator for nonlinear IRFs achieves root-T consistency and asymptotic normality via doubly robust moments and cross-fitting for time series.
Manuscript, arXiv:1903.01637 , year=
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Hamiltonian Causal Models reconcile causal interventions in dynamical systems with non-equilibrium thermodynamics by treating entropy production as a path-wise causal witness.
QBHM estimator matches standard GMM asymptotics for strongly identified parameters and is a Bayes rule under squared loss in weak-GMM limit experiments induced by the hierarchy.
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Semiparametric Local Projections
New semiparametric estimator for nonlinear IRFs achieves root-T consistency and asymptotic normality via doubly robust moments and cross-fitting for time series.
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Reconciling Causality and Non-Equilibrium Thermodynamics with Hamiltonian Causal Models
Hamiltonian Causal Models reconcile causal interventions in dynamical systems with non-equilibrium thermodynamics by treating entropy production as a path-wise causal witness.
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Quasi-Bayesian Hierarchical Models
QBHM estimator matches standard GMM asymptotics for strongly identified parameters and is a Bayes rule under squared loss in weak-GMM limit experiments induced by the hierarchy.