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Jel Classification:C13 

Working Paper
GDP Trend-cycle Decompositions Using State-level Data

This paper develops a method for decomposing GDP into trend and cycle exploiting the cross-sectional variation of state-level real GDP and unemployment rate data. The model assumes that there are common output and unemployment rate trend and cycle components, and that each state?s output and unemployment rate are subject to idiosyncratic trend and cycle perturbations. The model is estimated with Bayesian methods using quarterly data from 2005:Q1 to 2016:Q1 for the 50 states and the District of Columbia. Results show that the U.S. output gap reached about -8% during the Great Recession and is ...
Finance and Economics Discussion Series , Paper 2017-051

Working Paper
When Can Trend-Cycle Decompositions Be Trusted?

In this paper, we examine the results of GDP trend-cycle decompositions from the estimation of bivariate unobserved components models that allow for correlated trend and cycle innovations. Three competing variables are considered in the bivariate setup along with GDP: the unemployment rate, the inflation rate, and gross domestic income. We find that the unemployment rate is the best variable to accompany GDP in the bivariate setup to obtain accurate estimates of its trend-cycle correlation coefficient and the cycle. We show that the key feature of unemployment that allows for precise ...
Finance and Economics Discussion Series , Paper 2016-099

Working Paper
Financial Frictions, Financial Shocks, and Aggregate Volatility

I revisit the Great Inflation and the Great Moderation for nominal and real variables. I document an immoderation in corporate balance sheet variables so that the Great Moderation is best described as a period of divergent patterns in volatilities for real, nominal and financial variables. A model with time-varying financial frictions and financial shocks allowing for structural breaks in the size of shocks and the institutional framework is estimated. The paper shows that (i) while the Great Inflation was driven by bad luck, the Great Moderation was mostly due to better institutions; (ii) ...
Finance and Economics Discussion Series , Paper 2014-84

Working Paper
Generating Options-Implied Probability Densities to Understand Oil Market Events

We investigate the informational content of options-implied probability density functions (PDFs) for the future price of oil. Using a semiparametric variant of the methodology in Breeden and Litzenberger (1978), we investigate the fit and smoothness of distributions derived from alternative PDF estimation methods, and develop a set of robust summary statistics. Using PDFs estimated around episodes of high geopolitical tensions, oil supply disruptions, and macroeconomic data releases, we explore the extent to which oil price movements are expected or unexpected, and whether agents believe ...
International Finance Discussion Papers , Paper 1122

Working Paper
When Simplicity Offers a Benefit, Not a Cost: Closed-Form Estimation of the GARCH(1,1) Model that Enhances the Efficiency of Quasi-Maximum Likelihood

Simple, multi-step estimators are developed for the popular GARCH(1,1) model, where these estimators are either available entirely in closed form or dependent upon a preliminary estimate from, for example, quasi-maximum likelihood. Identification sources to asymmetry in the model's innovations, casting skewness as an instrument in a linear, two-stage least squares estimator. Properties of regular variation coupled with point process theory establish the distributional limits of these estimators as stable, though highly non-Gaussian, with slow convergence rates relative to the ??n-case. Moment ...
Finance and Economics Discussion Series , Paper 2019-030

Working Paper
Closed-Form Estimation of Finite-Order ARCH Models: Asymptotic Theory and Finite-Sample Performance

Strong consistency and weak distributional convergence to highly non-Gaussian limits are established for closed-form, two stage least squares (TSLS) estimators for a class of ARCH(p) models. Conditions for these results include (relatively) mild moment existence criteria that are supported empirically by many (high frequency) financial returns. These conditions are not shared by competing closed-form estimators like OLS. Identification of these TSLS estimators depends on asymmetry, either in the model's rescaled errors or in the conditional variance function. Monte Carlo studies reveal TSLS ...
Finance and Economics Discussion Series , Paper 2016-083

Working Paper
An Output Gap Measure for the Euro Area : Exploiting Country-Level and Cross-Sectional Data Heterogeneity

This paper proposes a methodology to estimate the euro-area output gap by taking advantage of two types of data heterogeneity. On the one hand, the method uses information on real GDP, inflation, and the unemployment rate for each member state; on the other hand, it jointly considers this information for all the euro-area countries to extract an area-wide output gap measure. The setup is an unobserved components model that theorizes a common cycle across euro-area economies in addition to country-specific cyclical components. I estimate the model with Bayesian methods using data for the 19 ...
Finance and Economics Discussion Series , Paper 2018-040

Working Paper
Financial Frictions, Financial Shocks, and Aggregate Volatility

The Great Moderation in the U.S. economy was accompanied by a widespread increase in the volatility of financial variables. We explore the sources of the divergent patterns in volatilities by estimating a model with time-varying financial rigidities subject to structural breaks in the size of the exogenous processes and two institutional characteristics: the coefficients in the monetary policy rule and the severity of the financial rigidity at the steady state. To do so, we generalize the estimation methodology developed by Curdia and Finocchiaro (2013). Institutional changes are key in ...
Finance and Economics Discussion Series , Paper 2018-054

Working Paper
Too Good to Be True? Fallacies in Evaluating Risk Factor Models

This paper is concerned with statistical inference and model evaluation in possibly misspecified and unidentified linear asset-pricing models estimated by maximum likelihood and one-step generalized method of moments. Strikingly, when spurious factors (that is, factors that are uncorrelated with the returns on the test assets) are present, the models exhibit perfect fit, as measured by the squared correlation between the model's fitted expected returns and the average realized returns. Furthermore, factors that are spurious are selected with high probability, while factors that are useful are ...
FRB Atlanta Working Paper , Paper 2017-9

Working Paper
Asymptotic variance approximations for invariant estimators in uncertain asset-pricing models

This paper derives explicit expressions for the asymptotic variances of the maximum likelihood and continuously updated GMM estimators under potentially misspecified models. The proposed misspecification-robust variance estimators allow the researcher to conduct valid inference on the model parameters even when the model is rejected by the data. Although the results for the maximum likelihood estimator are only applicable to linear asset-pricing models, the asymptotic distribution of the continuously updated GMM estimator is derived for general, possibly nonlinear, models. The large ...
FRB Atlanta Working Paper , Paper 2015-9


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