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Working Paper
Bayesian Estimation and Comparison of Conditional Moment Models
Simoni, Anna; Shin, Minchul; Chib, Siddhartha (2019-12-09)
We provide a Bayesian analysis of models in which the unknown distribution of the outcomes is speci?ed up to a set of conditional moment restrictions. This analysis is based on the nonparametric exponentially tilted empirical likelihood (ETEL) function, which is constructed to satisfy a sequence of unconditional moments, obtained from the conditional moments by an increasing (in sample size) vector of approximating functions (such as tensor splines based on the splines of each conditioning variable). The posterior distribution is shown to satisfy the Bernstein-von Mises theorem, subject to a ...
Working Papers , Paper 19-51

Working Paper
Sticky Information Versus Sticky Prices Revisited: A Bayesian VAR-GMM Approach
Kurozumi, Takushi; Oishi, Ryohei; Van Zandweghe, Willem (2022-11-16)
Several Phillips curves based on sticky information and sticky prices are estimated and compared using Bayesian VAR-GMM. This method derives expectations in each Phillips curve from a VAR and estimates the Phillips curve parameters and the VAR coefficients simultaneously. Quasi-marginal likelihood-based model comparison selects a dual stickiness Phillips curve in which, each period, some prices remain unchanged, consistent with micro evidence. Moreover, sticky information is a more plausible source of inflation inertia in the Phillips curve than other sources proposed in previous studies. ...
Working Papers , Paper 22-34

Working Paper
A Likelihood-Based Comparison of Macro Asset Pricing Models
Chen, Andrew Y.; Wasyk, Rebecca; Winkler, Fabian (2017-03)
We estimate asset pricing models with multiple risks: long-run growth, long-run volatility, habit, and a residual. The Bayesian estimation accounts for the entire likelihood of consumption, dividends, and the price-dividend ratio. We find that the residual represents at least 80% of the variance of the price-dividend ratio. Moreover, the residual tracks most recognizable features of stock market history such as the 1990's boom and bust. Long run risks and habit contribute primarily in crises. The dominance of the residual comes from the low correlation between asset prices and consumption ...
Finance and Economics Discussion Series , Paper 2017-024

Working Paper
Monetary policy, trend inflation, and the Great Moderation: an alternative interpretation: comment based on system estimation
Kurozumi, Takushi; Hirose, Yasuo; Van Zandweghe, Willem (2015-12-01)
What caused the U.S. economy's shift from the Great Inflation era to the Great Moderation era? {{p}} A large literature shows that the shift was achieved by the change in monetary policy from a passive to an active response to inflation. However, Coibion and Gorodnichenko (2011) attribute the shift to a fall in trend inflation along with the policy change, based on a solely estimated Taylor rule and a calibrated staggered-price model. We estimate the Taylor rule and the staggered-price model jointly and demonstrate that the change in monetary policy responses to inflation and other variables ...
Research Working Paper , Paper RWP 15-17

Working Paper
News-driven uncertainty fluctuations
Song, Dongho; Tang, Jenny (2018-01-01)
We embed a news shock, a noisy indicator of the future state, in a two-state Markov-switching growth model. Our framework, combined with parameter learning, features rich history-dependent uncertainty dynamics. We show that bad news that arrives during a prolonged economic boom can trigger a ?Minsky moment??a sudden collapse in asset values. The effect is greatly amplified when agents have a preference for early resolution of uncertainty. We leverage survey recession probability forecasts to solve a sequential learning problem and estimate the full posterior distribution of model primitives. ...
Working Papers , Paper 18-3

Working Paper
A New Way to Quantify the Effect of Uncertainty
Throckmorton, Nathaniel A.; Richter, Alexander W. (2017-05-04)
This paper develops a new way to quantify the effect of uncertainty and other higher-order moments. First, we estimate a nonlinear model using Bayesian methods with data on uncertainty, in addition to common macro time series. This key step allows us to decompose the exogenous and endogenous sources of uncertainty, calculate the effect of volatility following the cost of business cycles literature, and generate data-driven policy functions for any higherorder moment. Second, we use the Euler equation to analytically decompose consumption into several terms--expected consumption, the ex-ante ...
Working Papers , Paper 1705

Working Paper
Signaling Effects of Monetary Policy
Melosi, Leonardo (2016-09-16)
We develop a dynamic general equilibrium model in which the policy rate signals the central bank?s view about macroeconomic developments to price setters. The model is estimated with likelihood methods on a U.S. data set that includes the Survey of Professional Forecasters as a measure of price setters? inflation expectations. This model improves upon existing perfect information models in explaining why, in the data, inflation expectations respond with delays to monetary impulses and remain disanchored for years. In the 1970s, U.S. monetary policy is found to signal persistent inflationary ...
Working Paper Series , Paper WP-2016-14

Working Paper
Estimating (Markov-Switching) VAR Models without Gibbs Sampling: A Sequential Monte Carlo Approach
Herbst, Edward P.; Bognanni, Mark (2014-11-12)
Vector autoregressions with Markov-switching parameters (MS-VARs) offer dramatically better data fit than their constant-parameter predecessors. However, computational complications, as well as negative results about the importance of switching in parameters other than shock variances, have caused MS-VARs to see only sparse usage. For our first contribution, we document the effectiveness of Sequential Monte Carlo (SMC) algorithms at estimating MSVAR posteriors. Relative to multi-step, model-specific MCMC routines, SMC has the advantages of being simpler to implement, readily parallelizable, ...
Working Papers (Old Series) , Paper 1427

Working Paper
Business Cycles Across Space and Time
Owyang, Michael T.; Francis, Neville; Soques, Daniel (2021-05-05)
We study the comovement of international business cycles in a time series clustering model with regime-switching. We extend the framework of Hamilton and Owyang (2012) to include time-varying transition probabilities to determine what drives similarities in business cycle turning points. We find four groups, or "clusters", of countries which experience idiosyncratic recessions relative to the global cycle. Additionally, we find the primary indicators of international recessions to be fluctuations in equity markets and geopolitical uncertainty. In out-of-sample forecasting exercises, we find ...
Working Papers , Paper 2019-010

Report
On the Validity of Classical and Bayesian DSGE-Based Inference
Petrova, Katerina (2024-01-01)
This paper studies large sample classical and Bayesian inference in a prototypical linear DSGE model and demonstrates that inference on the structural parameters based on a Gaussian likelihood is unaffected by departures from Gaussianity of the structural shocks. This surprising result is due to a cancellation in the asymptotic variance resulting into a generalized information equality for the block corresponding to the structural parameters. The underlying reason for the cancellation is the certainty equivalence property of the linear rational expectation model.The main implication of this ...
Staff Reports , Paper 1084

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