Research Rap

Business Review (Federal Reserve Bank of Philadelphia), Summer 2006 | Go to article overview
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Research Rap


Abstracts of research papers produced by the economists at the Philadelphia Fed

THE EQUITY PREMIUM AND RETURN ON ASSETS

Recent empirical work documents a decline in the U.S. equity premium and a decline in the standard deviation of real output growth. The author investigates the link between aggregate risk and the asset returns in a dynamic production-based asset-pricing model. When calibrated to match asset return moments, the model implies that the post-1984 reduction in TFP shock volatility of 60 percent gives rise to a 40 percent decline in the equity premium. Lower macroeconomic risk post-1984 can account for a substantial fraction of the decline in the equity premium.

Working Paper 06-1, "Macroeconomic Volatility and the Equity Premium" Keith Sill, Federal Reserve Bank of Philadelphia

EXPLORING THE DYNAMICS OF PREDATORY LENDING

Regulators express growing concern over "predatory lending," which the authors take to mean lending that reduces the expected utility of borrowers - They present a rational model of consumer credit in which such lending is possible and identify the circumstances in which it arises with and without competition. Predatory lending is associated with imperfect competition, highly collateralized loans, and poorly informed borrowers. Under most circumstances competition among lenders eliminates predatory lending.

Working Paper 06-2, "Predatory Lending in a Rational World" Philip Bond, The Wharton School, University of Pennsylvania, and Visiting Scholar, Federal Reserve Bank of Philadelphia; David K. Musto, The Wharton School, University of Pennsylvania; and Bilge Yilmaz, The Wharton School, University of Pennsylvania

DEVELOPING EMPIRICALLY VIABLE MODELS

The time series fit of dynamic stochastic general equilibrium (DSGE) models often suffers from restrictions on the long-run dynamics that are at odds with the data. Relaxing these restrictions can close the gap between DSGE models and vector autoregressions. This paper modifies a simple stochastic growth model by incorporating permanent labor supply shocks that can generate a unit root in hours worked. Using Bayesian methods the authors estimate two versions of the DSGE model: the standard specification in which hours worked are stationary and the modified version with permanent labor supply shocks. They find that the data support the latter specification.

Working Paper 06-3, "Non-Stationary Hours in a DSGE Model" Yongsung Chang, Seoul National University; Taeyoung Doh, University of Pennsylvania; and Frank Schorfheide, University of Pennsylvania, CEPR and Visiting Scholar, Federal Reserve Bank of Philadelphia

POLICY ANALYSIS AND POTENTIALLY MISSPECIFIED MODELS

This paper proposes a novel method for conducting policy analysis with potentially misspecified dynamic stochastic general equilibrium (DSGE) models and applies it to a New Keynesian DSGE model along the lines of Christiano, Eichenbaum, and Evans (JPE 2005) and Smets and Wouters (JEEA 2003). The authors first quantify the degree of model misspecification and then illustrate its implications for the performance of different interest-rate feedback rules. The authors find that many of the prescriptions derived from the DSGE model are robust to model misspecification.

Working Paper 06-4, "Monetary Policy Analysis with Potentially Misspecified Models," Marco Del Negro, Federal Reserve Bank of Atlanta, and Frank Schorfheide, University of Pennsylvania, and Visiting Scholar, Federal Reserve Bank of Philadelphia

REVIEWING ESTIMATION AND EVALUATION TECHNIQUES IN DSGE MODELS

This paper reviews Bayesian methods that have been developed in recent years to estimate and evaluate dynamic stochastic general equilibrium (DSGE) models. The authors consider the estimation of linearized DSGE models, the evaluation of models based on Bayesian model checking, posterior odds comparisons, and comparisons to vector autoregressions, as well as the nonlinear estimation based on a second-order accurate model solution.

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