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Jel Classification:C15 

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
Self-employment and health care reform: evidence from Massachusetts

We study the e ect of the Massachusetts health care reform on the uninsured rate and the self-employment rate in the state. The reform required all individuals to obtain health insurance, required most employers to o er health insurance to their employees, formed a private marketplace that o ered subsidized health insurance options and ex- panded public insurance. We examine data from the Current Population Survey (CPS)for 1994-2012 and its Annual Social and Economic (ASEC) Supplement for 1996-2013. We show that the reform led to a dramatic reduction in the state's uninsured rate due to ...
Research Working Paper , Paper RWP 14-16

Working Paper
Real-Time Density Nowcasts of US Inflation: A Model-Combination Approach

We develop a flexible modeling framework to produce density nowcasts for US inflation at a trading-day frequency. Our framework: (1) combines individual density nowcasts from three classes of parsimonious mixed-frequency models; (2) adopts a novel flexible treatment in the use of the aggregation function; and (3) permits dynamic model averaging via the use of weights that are updated based on learning from past performance. Together these features provide density nowcasts that can accommodate non-Gaussian properties. We document the competitive properties of the nowcasts generated from our ...
Working Papers , Paper 202031

Working Paper
A staggered pricing approach to modeling speculative storage: implications for commodity price dynamics

This paper embeds a staggered price feature into the standard speculative storage model of Deaton and Laroque (1996). Intermediate goods inventory speculators are added as an additional source of intertemporal linkage, which helps us to replicate the stylized facts of the observed commodity price dynamics. Incorporating this type of friction into the model is motivated by its ability to increase price stickiness which, gives rise to a higher degree of persistence in the first two conditional moments of commodity prices. The structural parameters of our model are estimated by the simulated ...
FRB Atlanta Working Paper , Paper 2013-08

Journal Article
Asset Pricing Through the Lens of the Hansen-Jagannathan Bound

Stochastic discount factor (SDF) models are the dominant framework for modern asset pricing. The Hansen-Jagannathan bound is a characterization of the admissible set of SDFs, given a vector of asset returns.
Review , Volume 102 , Issue 3 , Pages 255-269

Report
Deconstructing the yield curve

We investigate the factor structure of the term structure of interest rates and argue that characterizing the minimal dimension of the data generating process is more challenging than currently appreciated. As a result, inference procedures for yield curve models that commit to a parsimoniously parameterized factor structure may be omitting important information about the underlying true factor space. To circumvent these difficulties, we introduce a novel nonparametric bootstrap that is robust to general forms of time and cross-sectional dependence and conditional heteroskedasticity of ...
Staff Reports , Paper 884

Working Paper
Easy Bootstrap-Like Estimation of Asymptotic Variances

The bootstrap is a convenient tool for calculating standard errors of the parameter estimates of complicated econometric models. Unfortunately, the bootstrap can be very time-consuming. In a recent paper, Honor and Hu (2017), we propose a ?Poor (Wo)man's Bootstrap? based on one-dimensional estimators. In this paper, we propose a modified, simpler method and illustrate its potential for estimating asymptotic variances.
Working Paper Series , Paper WP-2018-11

Working Paper
A Likelihood-Based Comparison of Macro Asset Pricing Models

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
exuber: Recursive Right-Tailed Unit Root Testing with R

This paper introduces the R package exuber for testing and date-stamping periods of mildly explosive dynamics (exuberance) in time series. The package computes test statistics for the supremum ADF test (SADF) of Phillips, Wu and Yu (2011), the generalized SADF (GSADF) of Phillips, Shi and Yu (2015a,b), and the panel GSADF proposed by Pavlidis, Yusupova, Paya, Peel, Martínez-García, Mack and Grossman (2016); generates finite-sample critical values based on Monte Carlo and bootstrap methods; and implements the corresponding date-stamping procedures. The recursive least-squares algorithm that ...
Globalization Institute Working Papers , Paper 383

Working Paper
A Class of Time-Varying Parameter Structural VARs for Inference under Exact or Set Identification

This paper develops a new class of structural vector autoregressions (SVARs) with time-varying parameters, which I call a drifting SVAR (DSVAR). The DSVAR is the first structural time-varying parameter model to allow for internally consistent probabilistic inference under exact?or set?identification, nesting the widely used SVAR framework as a special case. I prove that the DSVAR implies a reduced-form representation, from which structural inference can proceed similarly to the widely used two-step approach for SVARs: beginning with estimation of a reduced form and then choosing among ...
Working Papers (Old Series) , Paper 1811

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