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average treatment effects, based on forecasting counterfactuals using a short time series of pre-treatment data. We show that … counterfactuals. Basing the forecasts on a model can introduce misspecification bias and does not necessarily improve performance even …
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We estimate a large Bayesian time-varying parameter vector autoregressive (TVP-VAR) model of daily stock return volatilities for 35 U.S. and European financial institutions. Based on that model we extract a connectedness index in the spirit of Diebold and Yilmaz (2014) (DYCI). We show that the...
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We develop a simple estimation procedure for general equilibrium (GE) comparative static analysis of gravity models. Non-linear solvers of estimated models are replaced by (constrained) regressions. Applied economists can more readily generate results, with more intuition about the working of...
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We propose a framework for estimation and inference about the parameters of an economic model and predictions based on it, when the model may be misspecified. We rely on a local asymptotic approach where the degree of misspecification is indexed by the sample size. We derive formulas to...
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