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We construct networks based on the co-movement of these components.Analysis of these networks allows us to identify time periods of increased risk concentration in the banking sector and determine which firms pose high systemic risk.In this paper, we propose a procedure based on mixed-frequency models and network analysis to help address both of these policy concerns.We decompose firm-specific stock returns into two components: one that is explained by observed covariates (or fitted values), the other unexplained (or residuals).This paper develops a New Keynesian model with a time-varying natural rate of interest (r-star) and a zero lower bound (ZLB) on the nominal interest rate.The representative agent contemplates the possibility of an occasionally binding ZLB that is driven by switching between two local equilibria, labeled the "targeted" and "deflation" regimes, respectively.
The aggregate consumption multiplier is 0.4, which implies an output multiplier higher than one.Qualitatively, we find that evidence is largely consistent with the theoretical predictions in the target equilibrium and find no evidence in favor of the liquidity trap equilibrium. During episodes in which bank lending from advanced to emerging economies is booming, the relationship between the federal funds rate and cross-border bank lending is positive and mostly driven by the macro fundamentals component, which is consistent with a search-for-yield behavior by internationally-active banks.Quantitatively, while the lower bound has a sizable effect on the distribution of future interest rates, its impact on forecast densities for inflation is relatively modest. In contrast, during episodes of stagnant growth in bank lending from advanced to emerging economies, the relationship between the federal funds rate and bank lending is negative, mainly due to the monetary policy stance component of the federal funds rate.Sustained periods when the real interest rate remains below the central bank's estimate of r-star can induce the agent to place a substantially higher weight on the deflation forecast rules, causing the deflation equilibrium to occasionally become fully realized.
I solve for the time series of stochastic shocks and endogenous forecast rule weights that allow the model to exactly replicate the observed time paths of the U. output gap, quarterly inflation, and the federal funds rate since 1988.We use a stylized model economy where the policy instrument is subject to a lower bound to motivate the empirical analysis.Two equilibria emerge: In the “target equilibrium,” policy is unconstrained most or all of the time, whereas in the “liquidity trap equilibrium,” policy is mostly or always constrained.What is the aggregate real rate of return in the economy?