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Jel Classification:C13 

Working Paper
Shrinkage estimation of high-dimensional factor models with structural instabilities

In high-dimensional factor models, both the factor loadings and the number of factors may change over time. This paper proposes a shrinkage estimator that detects and disentangles these instabilities. The new method simultaneously and consistently estimates the number of pre- and post-break factors, which liberates researchers from sequential testing and achieves uniform control of the family-wise model selection errors over an increasing number of variables. The shrinkage estimator only requires the calculation of principal components and the solution of a convex optimization problem, which ...
Working Papers , Paper 14-4

Working Paper
Measuring Uncertainty and Its Impact on the Economy

We propose a new framework for measuring uncertainty and its effects on the economy, based on a large VAR model with errors whose stochastic volatility is driven by two common unobservable factors, representing aggregate macroeconomic and financial uncertainty. The uncertainty measures can also influence the levels of the variables so that, contrary to most existing measures, ours reflect changes in both the conditional mean and volatility of the variables, and their impact on the economy can be assessed within the same framework. Moreover, identification of the uncertainty shocks is ...
Working Papers (Old Series) , Paper 1622

Working Paper
Bayesian estimation of NOEM models: identification and inference in small samples

This paper studies the (potential) weak identification of these relationships in the context of a fully specified structural model using Bayesian estimation techniques. We trace the problems to sample size, rather than misspecification bias. We conclude that standard macroeconomic time series with a coverage of less than forty years are subject to potentially serious identification issues, and also to model selection errors. We recommend estimation with simulated data prior to bringing the model to the actual data as a way of detecting parameters that are susceptible to weak identification in ...
Globalization Institute Working Papers , Paper 105

Working Paper
Impacts of Monetary Stimulus on Credit Allocation and Macroeconomy: Evidence from China

We develop a new empirical framework to identify and estimate the effects of monetary stimulus on the real economy. The framework is applied to the Chinese economy when monetary policy in normal times was switched to an extraordinarily expansionary regime to combat the impact of the 2008 financial crisis. We show that this unprecedented monetary stimulus accounted for as high as a 4 percent increase of real gross domestic product (GDP) growth rate by the end of 2009. Monetary transmission to the real economy was through bank credit allocated disproportionately to financing investment in real ...
FRB Atlanta Working Paper , Paper 2016-9

Working Paper
Backtesting Systemic Risk Measures During Historical Bank Runs

The measurement of systemic risk is at the forefront of economists and policymakers concerns in the wake of the 2008 financial crisis. What exactly are we measuring and do any of the proposed measures perform well outside the context of the recent financial crisis? One way to address these questions is to take backtesting seriously and evaluate how useful the recently proposed measures are when applied to historical crises. Ideally, one would like to look at the pre-FDIC era for a broad enough sample of financial panics to confidently assess the robustness of systemic risk measures but ...
Working Paper Series , Paper WP-2015-9

Working Paper
A Bias-Corrected Method of Moments Approach to Estimation of Dynamic Short-T Panels

This paper contributes to the GMM literature by introducing the idea of self-instrumenting target variables instead of searching for instruments that are uncorrelated with the errors, in cases where the correlation between the target variables and the errors can be derived. The advantage of the proposed approach lies in the fact that, by construction, the instruments have maximum correlation with the target variables and the problem of weak instrument is thus avoided. The proposed approach can be applied to estimation of a variety of models such as spatial and dynamic panel data models. In ...
Globalization Institute Working Papers , Paper 327

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

Report
Nonparametric pricing of multivariate contingent claims

In this paper, I derive and implement a nonparametric, arbitrage-free technique for multivariate contingent claim (MVCC) pricing. Using results from the method of copulas, I show that the multivariate risk-neutral density can be written as a product of marginal risk-neutral densities and a risk-neutral dependence function. I then develop a pricing technique using nonparametrically estimated marginal risk-neutral densities (based on options data) and a nonparametric dependence function (based on historical return data). By using nonparametric estimation, I avoid the pricing biases that result ...
Staff Reports , Paper 162

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
Simultaneous Spatial Panel Data Models with Common Shocks

I consider a simultaneous spatial panel data model, jointly modeling three effects: simultaneous effects, spatial effects and common shock effects. This joint modeling and consideration of cross-sectional heteroskedasticity result in a large number of incidental parameters. I propose two estimation approaches, a quasi-maximum likelihood (QML) method and an iterative generalized principal components (IGPC) method. I develop full inferential theories for the estimation approaches and study the trade-off between the model specifications and their respective asymptotic properties. I further ...
Supervisory Research and Analysis Working Papers , Paper RPA 17-3

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