{"ID":23029921,"CreatedAt":"2026-09-17T05:12:50.116335254Z","UpdatedAt":"2026-09-17T05:12:50.116335254Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2609.18903","arxiv_id":"2609.18903","title":"Shrinkage Bayesian Causal Forest with Instrumental Variable","abstract":"Discovering interpretable subgroups whose complier effects deviate from the average is a central goal of instrumental variable analysis under imperfect compliance, yet existing tree-based methods degrade when most covariates are irrelevant to the effect. We propose Shrinkage Bayesian Causal Forest with Instrumental Variable (SBCF-IV) for discovering and estimating subgroups with heterogeneous Complier Average Causal Effects (CACE) in sparse high-dimensional settings. SBCF-IV places a sparsity-inducing Dirichlet prior on the splitting probabilities of the Bayesian Additive Regression Trees that estimate the conditional intention-to-treat and the complier share, concentrating posterior mass on the few covariates that moderate the complier effect and thereby regularizing effect estimation. The posterior split frequencies additionally enter a downstream CART as variable-level costs that steer the partition toward relevant moderators, providing an interpretable division of the covariate space. Monte Carlo experiments show that, as the share of irrelevant covariates grows, SBCF-IV recovers the true partition more reliably than its non-sparse predecessor BCF-IV at the tree and unit level, and retains nominal coverage where BCF-IV's intervals deteriorate. We apply the method to the Oregon Health Insurance Experiment and the 401(k) eligibility data.","short_abstract":"Discovering interpretable subgroups whose complier effects deviate from the average is a central goal of instrumental variable analysis under imperfect compliance, yet existing tree-based methods degrade when most covariates are irrelevant to the effect. We propose Shrinkage Bayesian Causal Forest with Instrumental Var...","url_abs":"https://arxiv.org/abs/2609.18903","url_pdf":"https://arxiv.org/pdf/2609.18903v1","authors":"[\"Lennard Maßmann\",\"Jens Klenke\"]","published":"2026-09-16T16:41:03Z","proceeding":"econ.EM","tasks":"[\"econ.EM\"]","methods":"[]","has_code":false}