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Keywords:Bayesian estimation 

Working Paper
Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs

We present a general framework for Bayesian estimation and causality assessment in epidemiological models. The key to our approach is the use of sequential Monte Carlo methods to evaluate the likelihood of a generic epidemiological model. Once we have the likelihood, we specify priors and rely on a Markov chain Monte Carlo to sample from the posterior distribution. We show how to use the posterior simulation outputs as inputs for exercises in causality assessment. We apply our approach to Belgian data for the COVID-19 epidemic during 2020. Our estimated time-varying-parameters SIRD model ...
Working Papers , Paper 21-18

Working Paper
Financial Business Cycles

Using Bayesian methods, I estimate a DSGE model where a recession is initiated by losses suffered by banks and exacerbated by their inability to extend credit to the real sector. The event triggering the recession has the workings of a redistribution shock: a small sector of the economy -- borrowers who use their home as collateral -- defaults on their loans. When banks hold little equity in excess of regulatory requirements, the losses require them to react immediately, either by recapitalizing or by deleveraging. By deleveraging, banks transform the initial shock into a credit crunch, and, ...
International Finance Discussion Papers , Paper 1116

Working Paper
Forward Guidance with Bayesian Learning and Estimation

Considerable attention has been devoted to evaluating the macroeconomic effectiveness of the Federal Reserve's communications about future policy rates (forward guidance) in light of the U.S. economy's long spell at the zero lower bound (ZLB). In this paper, we study whether forward guidance represented a shift in the systematic description of monetary policy by estimating a New Keynesian model using Bayesian techniques. In doing so, we take into account the uncertainty that agents have about policy regimes using an incomplete information setup in which they update their beliefs using Bayes ...
Finance and Economics Discussion Series , Paper 2018-072

Working Paper
Bayesian Estimation of Time-Changed Default Intensity Models

We estimate a reduced-form model of credit risk that incorporates stochastic volatility in default intensity via stochastic time-change. Our Bayesian MCMC estimation method overcomes nonlinearity in the measurement equation and state-dependent volatility in the state equation. We implement on firm-level time-series of CDS spreads, and find strong in-sample evidence of stochastic volatility in this market. Relative to the widely-used CIR model for the default intensity, we find that stochastic time-change offers modest benefit in fitting the cross-section of CDS spreads at each point in time, ...
Finance and Economics Discussion Series , Paper 2015-2

Working Paper
Short-term Planning, Monetary Policy, and Macroeconomic Persistence

This paper uses aggregate data to estimate and evaluate a behavioral New Keynesian (NK) model in which households and firms plan over a finite horizon. The finite-horizon (FH) model outperforms rational expectations versions of the NK model commonly used in empirical applications as well as other behavioral NK models. The better fit of the FH model reflects that it can induce slow-moving trends in key endogenous variables which deliver substantial persistence in output and inflation dynamics. In the FH model, households and firms are forward-looking in thinking about events over their ...
Finance and Economics Discussion Series , Paper 2020-003

Working Paper
Optimal Monetary and Macroprudential Policies: Gains and Pitfalls in a Model of Financial Intermediation

We estimate a quantitative general equilibrium model with nominal rigidities and financial intermediation to examine the interaction of monetary and macroprudential stabilization policies. The estimation procedure uses credit spreads to help identify the role of financial shocks amenable to stabilization via monetary or macroprudential instruments. The estimated model implies that monetary policy should not respond strongly to the credit cycle and can only partially insulate the economy from the distortionary effects of financial frictions/shocks. A counter-cyclical macroprudential instrument ...
Finance and Economics Discussion Series , Paper 2015-78

Working Paper
Uncertainty Shocks, Monetary Policy and Long-Term Interest Rates

We study the relationship between monetary policy and long-term rates in a structural, general equilibrium model estimated on both macro and yields data from the United States. Regime shifts in the conditional variance of productivity shocks, or "uncertainty shocks", are an important model ingredient. First, they account for countercyclical movements in risk premia. Second, they induce changes in the demand for precautionary saving, which affects expected future real rates. Through changes in both risk-premia and expected future real rates, uncertainty shocks account for about 1/2 of the ...
Finance and Economics Discussion Series , Paper 2019-024

Working Paper
The Role of News about TFP in U.S. Recessions and Booms

We develop a general equilibrium model to study the historical contribution of TFP news to the U.S. business cycle. Hiring frictions provide incentives for firms to start hiring ahead of an anticipated improvement in technology. For plausibly calibrated hiring costs, employment gradually rises in response to positive TFP news shocks even under standard preferences. TFP news shocks are identified mainly by current and expected unemployment rates since periods in which average unemployment is relatively high (low) are also periods in which average TFP growth is slow (fast). We work out the ...
Working Paper Series , Paper WP-2018-6

Working Paper
The Causal Effects of Lockdown Policies on Health and Macroeconomic Outcomes

We assess the causal impact of epidemic-induced lockdowns on health and macroeconomic outcomes and measure the trade-off between containing the spread of an epidemic and economic activity. To do so, we estimate an epidemiological model with time-varying parameters and use its output as information for estimating SVARs and LPs that quantify the causal effects of nonpharmaceutical policy interventions. We apply our approach to Belgian data for the COVID-19 epidemic during 2020. We find that additional government mandated mobility curtailments would have reduced deaths at a very small cost in ...
Working Papers , Paper 22-18

Working Paper
A narrative approach to a fiscal DSGE model

This version: March 28, 2016 First version: February 2014 {{p}} Structural DSGE models are used both for analyzing policy and the sources of business cycles. Conclusions based on full structural models are, however, potentially affected by misspecification. A competing method is to use partially identified VARs based on narrative shocks. This paper asks whether both approaches agree. First, I show that, theoretically, the narrative VAR approach is valid in a class of DSGE models with Taylor-type policy rules. Second, I quantify whether the two approaches also agree empirically, that is, ...
Working Papers , Paper 16-11


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