Macroeconomists construct impulse responses using many competing time series models and different statistical paradigms (Bayesian or frequentist). We adapt optimal linear prediction pools to efficiently combine impulse response estimators for the effects of the same economic shock from this vast class of possible models. We thus alleviate the need to choose one specific model, obtaining weights that are typically positive for more than one model. Three Monte Carlo simulations and two monetary shock empirical applications illustrate how the weights leverage the strengths of each model by (i) trading off properties of each model depending on variable, horizon, and application and (ii) accounting for the full predictive distribution rather than being restricted to specific moments.

We study how international linkages and nominal price rigidities jointly shape the dynamics of inflation and output across multiple large economies. We describe how these features produce a global system of Phillips curves explicitly connected by multilateral trade relationships. In equilibrium, disturbances abroad propagate to domestic variables not only directly, through pairwise trade between countries, but also indirectly through third-country effects arising from the network structure of trade. The combined propagation mechanisms imply that country-specific shocks alone explain almost 90 percent of the observed average pairwise comovement in output growth between countries. These idiosyncratic shocks also explain more than 1/2 the cross-country comovement in inflation, and between output and inflation. We estimate that a European inflationary shock results in significant U.S. inflation accompanied by lower output, and that these responses transpire almost entirely from the network effects of trade. In addition, a tightening of U.S. monetary policy generates a percentage decline in output globally that is comparable to 1/2 the domestic response.

We highlight a reason for the vast range of estimates for the effect of demographics on interest rates: the magnitudes are not well-identified without often omitted data on capital and life-cycle consumption. Using nonparametric prior sensitivity analysis for an overlapping generations model estimated through Bayesian methods, we show small changes in the prior for the discount rate, intertemporal elasticity of substitution, and depreciation rate can shift posterior quantiles for the effects of demographics by up to 1.5 percentage points. Capital-output ratio data substantially tighten estimates of the depreciation rate but not the discount rate. Life-cycle consumption informs all three parameters.