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Local projections (LPs) are widely used for impulse response analysis, but Bayesian methods face challenges due to the absence of a likelihood function. Existing approaches rely on pseudo-likelihoods, which often result in poorly calibrated posteriors. We propose a quasi-Bayesian method based on the Laplace-type estimator, where a quasi-likelihood is constructed using a generalized method of moments criterion. This approach avoids strict distributional assumptions, ensures well-calibrated inferences, and supports simultaneous credible bands. Additionally, it can be naturally extended to the instrumental variable method. We validate our approach through Monte Carlo simulations.

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