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Keywords:Bayesian statistical decision theory 

Report
Correlated disturbances and U.S. business cycles

The dynamic stochastic general equilibrium (DSGE) models used to study business cycles typically assume that exogenous disturbances are independent first-order autoregressions. This paper relaxes this tight and arbitrary restriction by allowing for disturbances that have a rich contemporaneous and dynamic correlation structure. Our first contribution is a new Bayesian econometric method that uses conjugate conditionals to allow for feasible and quick estimation of DSGE models with correlated disturbances. Our second contribution is a reexamination of U.S. business cycles. We find that ...
Staff Reports , Paper 434

Report
Estimating the cross-sectional distribution of price stickiness from aggregate data

We estimate a multisector sticky-price model for the U.S. economy in which the degree of price stickiness is allowed to vary across sectors. For this purpose, we use a specification that allows us to extract information about the underlying cross-sectional distribution from aggregate data. Identification is possible because sectors play different roles in determining the response of aggregate variables to shocks at different frequencies: Sectors where prices are stickier are relatively more important in determining the low-frequency response. Estimating the model using only aggregate data on ...
Staff Reports , Paper 419

Report
Sectoral price facts in a sticky-price model

We develop a multi-sector sticky-price DSGE (dynamic stochastic general equilibrium) model that can endogenously deliver differential responses of prices to aggregate and sectoral shocks. Input-output production linkages induce across-sector pricing complementarities that contribute to a slow response of prices to aggregate shocks. In turn, input-market segmentation at the sectoral level induces within-sector pricing substitutability, which helps the model deliver a fast response of prices to sector-specific shocks. Estimating the factor-augmented vector autoregression specification of ...
Staff Reports , Paper 495

Report
Bayesian social learning, conformity, and stubbornness: evidence from the AP top 25

The recent nonexperimental literature on social learning focuses on showing that observational learning exists, that is, individuals do indeed draw inferences by observing the actions of others. We take this literature a step further by analyzing whether individuals are Bayesian social learners. We use data from the Associated Press (AP) U.S. College Football Poll, a weekly subjective ranking of the top twenty-five teams. The voters' aggregate rankings are available each week prior to when voters have to update their individual rankings, so voters can potentially learn from their peers. We ...
Staff Reports , Paper 453

Report
Belief updating among college students: evidence from experimental variation in information

We investigate how college students form and update their beliefs about future earnings using a unique ?information? experiment. We provide college students true information about the population distribution of earnings and observe how this information causes respondents to update their beliefs about their own future earnings. We show that college students are substantially misinformed about population earnings and logically revise their self-beliefs in response to the information we provide, with larger revisions when the information is more specific and is good news. We classify the ...
Staff Reports , Paper 516

Working Paper
A Bayesian evaluation of alternative models of trend inflation

The concept of trend inflation is important in making accurate inflation forecasts. However, there is little consensus on how the trend in inflation should be modeled. While some studies suggest a survey-based measure of long-run inflation expectations as a good empirical proxy for trend inflation, others have argued for a statistical exercise of decomposing inflation data into trend and cycle components. In this paper, we assess alternative models of trend inflation based on the accuracy of medium-term inflation forecasts. To incorporate recent evidence on the time-varying macroeconomic ...
Research Working Paper , Paper RWP 11-16

Working Paper
Sequential Monte Carlo sampling for DSGE models

We develop a sequential Monte Carlo (SMC) algorithm for estimating Bayesian dynamic stochastic general equilibrium (DSGE) models, wherein a particle approximation to the posterior is built iteratively through tempering the likelihood. Using three examples consisting of an artificial state-space model, the Smets and Wouters (2007) model, and Schmitt-Grohe and Uribe's (2012) news shock model we show that the SMC algorithm is better suited for multi-modal and irregular posterior distributions than the widely-used random walk Metropolis-Hastings algorithm. Unlike standard Markov chain Monte Carlo ...
Working Papers , Paper 12-27

Working Paper
Bayesian estimation of DSGE models

We survey Bayesian methods for estimating dynamic stochastic general equilibrium (DSGE) models in this article. We focus on New Keynesian (NK)DSGE models because of the interest shown in this class of models by economists in academic and policy-making institutions. This interest stems from the ability of this class of DSGE model to transmit real, nominal, and fiscal and monetary policy shocks into endogenous fluctuations at business cycle frequencies. Intuition about these propagation mechanisms is developed by reviewing the structure of a canonical NKDSGE model. Estimation and evaluation of ...
Working Papers , Paper 12-4

Working Paper
Identifying long-run risks: a bayesian mixed-frequency approach

We develop a nonlinear state-space model that captures the joint dynamics of consumption, dividend growth, and asset returns. Building on Bansal and Yaron (2004), our model consists of an economy containing a common predictable component for consumption and dividend growth and multiple stochastic volatility processes. The estimation is based on annual consumption data from 1929 to 1959, monthly consumption data after 1959, and monthly asset return data throughout. We maximize the span of the sample to recover the predictable component and use high-frequency data, whenever available, to ...
Working Papers , Paper 13-39

Working Paper
Estimating the parameters of a small open economy DSGE model: identifiability and inferential validity

This paper estimates the parameters of a stylized dynamic stochastic general equilibrium model using maximum likelihood and Bayesian methods, paying special attention to the issue of weak parameter identification. Given the model and the available data, the posterior estimates of the weakly identified parameters are very sensitive to the choice of priors. We provide a set of tools to diagnose weak identification, which include surface plots of the log-likelihood as a function of two parameters, heat plots of the log-likelihood as a function of three parameters, Monte Carlo simulations using ...
International Finance Discussion Papers , Paper 955

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