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Jel Classification:C11 

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Estimating Macroeconomic Models of Financial Crises: An Endogenous Regime-Switching Approach

We estimate a workhorse dynamic stochastic general equilibrium (DSGE) model with an occasionally binding borrowing constraint. First, we propose a new specification of the occasionally binding constraint, where the transition between the unconstrained and constrained states is a stochastic function of the leverage level and the constraint multiplier. This specification maps into an endogenous regime-switching model. Second, we develop a general perturbation method for the solution of such a model. Third, we estimate the model with Bayesian methods to fit Mexico’s business cycle and ...
Staff Reports , Paper 944

Working Paper
Measuring Uncertainty and Its Effects in the COVID-19 Era

We measure the effects of the COVID-19 outbreak on macroeconomic and financial uncertainty, and we assess the consequences of the latter for key economic variables. We use a large, heteroskedastic vector autoregression (VAR) in which the error volatilities share two common factors, interpreted as macro and financial uncertainty, in addition to idiosyncratic components. Macro and financial uncertainty are allowed to contemporaneously affect the macroeconomy and financial conditions, with changes in the common component of the volatilities providing contemporaneous identifying information on ...
Working Papers , Paper 202032

Working Paper
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 ...
Globalization Institute Working Papers , Paper 403

Report
Identifying and evaluating sample selection bias in consumer payment surveys

Making meaningful inferences based on survey data depends on the ability to recognize and adjust for discrepancies between the survey respondents and the target population; this partly involves understanding how survey samples differ with respect to heterogeneous clusters of the population. Ex post adjustments for unbiased population parameter estimates are usually based on easily measured variables with known distributions in the target population, like age, gender, or income. This paper focuses on identifying and assessing the effect of an overlooked source of heterogeneity and potential ...
Research Data Report , Paper 15-7

Report
Safety, liquidity, and the natural rate of interest

Why are interest rates so low in the Unites States? We find that they are low primarily because the premium for safety and liquidity has increased since the late 1990s, and to a lesser extent because economic growth has slowed. We reach this conclusion using two complementary perspectives: a flexible time-series model of trends in Treasury and corporate yields, inflation, and long-term survey expectations, and a medium-scale dynamic stochastic general equilibrium (DSGE) model. We discuss the implications of this finding for the natural rate of interest.
Staff Reports , Paper 812

Report
Which bank is the \\"central\\" bank? an application of Markov theory to the Canadian Large Value Transfer System

Recently, economists have argued that a bank's importance within the financial system depends not only on its individual characteristics but also on its position within the banking network. A bank is deemed to be "central" if, based on our network analysis, it is predicted to hold the most liquidity. In this paper, we use a method similar to Google's PageRank procedure to rank banks in the Canadian Large Value Transfer System (LVTS). In doing so, we obtain estimates of the payment processing speeds for the individual banks. These differences in processing speeds are essential for ...
Staff Reports , Paper 356

Report
Time-Varying Structural Vector Autoregressions and Monetary Policy: a Corrigendum

This note corrects a mistake in the estimation algorithm of the time-varying structural vector autoregression model of Primiceri (2005) and shows how to correctly apply the procedure of Kim, Shephard, and Chib (1998) to the estimation of VAR, DSGE, factor, and unobserved components models with stochastic volatility. Relative to Primiceri (2005), the main difference in the new algorithm is the ordering of the various Markov Chain Monte Carlo steps, with each individual step remaining the same.
Staff Reports , Paper 619

Report
Online Estimation of DSGE Models

This paper illustrates the usefulness of sequential Monte Carlo (SMC) methods in approximating DSGE model posterior distributions. We show how the tempering schedule can be chosen adaptively, explore the benefits of an SMC variant we call generalized tempering for ?online? estimation, and provide examples of multimodal posteriors that are well captured by SMC methods. We then use the online estimation of the DSGE model to compute pseudo-out-of-sample density forecasts of DSGE models with and without financial frictions and document the benefits of conditioning DSGE model forecasts on nowcasts ...
Staff Reports , Paper 893

Report
DSGE forecasts of the lost recovery

The years following the Great Recession were challenging for forecasters. Unlike other deep downturns, this recession was not followed by a swift recovery, but generated a sizable and persistent output gap that was not accompanied by deflation as a traditional Phillips curve relationship would have predicted. Moreover, the zero lower bound and unconventional monetary policy generated an unprecedented policy environment. We document the real real-time forecasting performance of the New York Fed dynamic stochastic general equilibrium (DSGE) model during this period and explain the results using ...
Staff Reports , Paper 844

Report
Economic predictions with big data: the illusion of sparsity

We compare sparse and dense representations of predictive models in macroeconomics, microeconomics, and finance. To deal with a large number of possible predictors, we specify a prior that allows for both variable selection and shrinkage. The posterior distribution does not typically concentrate on a single sparse or dense model, but on a wide set of models. A clearer pattern of sparsity can only emerge when models of very low dimension are strongly favored a priori.
Staff Reports , Paper 847

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Clark, Todd E. 9 items

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