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Get the Lowdown: The International Side of the Fall in the U.S. Natural Rate of Interest
Much consideration has been given among scholars and policymakers to the decline in the U.S. natural rate of interest since the 2007 – 09 global financial crisis. In this paper, I investigate its determinants and drivers through the lens of the workhorse two-country New Keynesian model that captures the trade and technological interconnectedness of the U.S. with the rest of the world economy. Using Bayesian techniques, I bring the set of binding log-linearized equilibrium conditions from this model to the data, but augmented with survey-based forecasts in order to align the solution with ...
Understanding Heterogeneous Agent New Keynesian Models: Insights from a PRANK
In recent years there has been a lot of interest in the effect of income inequality (heterogeneity) on the economy, from both academics and policymakers. Researchers have developed Heterogeneous Agent New Keynesian (HANK) models that incorporate heterogeneity and uninsurable idiosyncratic risk into the New Keynesian models that have become a cornerstone of monetary policy analysis. This research has argued that heterogeneity and idiosyncratic risk change many features of New Keynesian models – the transmission of conventional monetary policy, the forward guidance puzzle, fiscal multipliers, ...
Understanding HANK: insights from a PRANK
We show analytically that whether incomplete markets resolve New Keynesian ?paradoxes? depends primarily on the cyclicality of income risk, rather than marginal propensity to consume (MPC) heterogeneity. Incomplete markets reduce the effectiveness of forward guidance and multipliers in a liquidity trap only with procyclical risk. Countercyclical risk amplifies these ?puzzles.? Procyclical risk permits determinacy under a peg; countercyclical risk generates indeterminacy even under the Taylor principle. MPC heterogeneity leaves determinacy and paradoxes qualitatively unaffected, but can change ...
Efficient VAR Discretization
The standard approach to discretizing VARs uses tensor grids. However, when the VAR components exhibit significant unconditional correlations or when there are more than a few variables, this approach creates large inefficiencies because some discretized states will be visited with only vanishingly small probability. I propose pruning these low-probability states, thereby constructing an efficient grid. I investigate how much an efficient grid improves accuracy in the context of an AR(2) model and a small-scale New Keynesian model featuring four shocks. In both contexts, the efficient grid ...