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Working Paper
Fed-Driven Systemic Tail Risk: High-Frequency Measurement, Evidence and Implications
Yang, Xiye; Neely, Christopher J.; Erdemlioglu, Deniz (2025-05-27)
We develop a framework to measure market-wide (systemic) tail risk in the cross-section of asset returns. Using high-frequency data on individual U.S. stocks and sector-specific ETF portfolios, we estimate time-varying jump intensities and multi-asset tail risk around Fed policy announcements. While most FOMC announcements generate systemic left-tail risk, there is no evidence that macro announcements have a similar effect. The magnitude of the tail risk induced by Fed policy announcements varies over the business cycle, peaks during the global financial crisis and remains high during phases ...
Working Papers , Paper 2023-016

Working Paper
Sample Selection Models Without Exclusion Restrictions: Parameter Heterogeneity and Partial Identification
Honore, Bo E.; Hu, Luojia (2021-07)
This paper studies semiparametric versions of the classical sample selection model (Heckman (1976, 1979)) without exclusion restrictions. We extend the analysis in Honoré and Hu (2020) by allowing for parameter heterogeneity and derive implications of this model. We also consider models that allow for heteroskedasticity and briefly discuss other extensions. The key ideas are illustrated in a simple wage regression for females. We find that the derived implications of a semiparametric version of Heckman's classical sample selection model are consistent with the data for women with no college ...
Working Paper Series , Paper WP 2022-33

Working Paper
Betting the House
Taylor, Alan M.; Schularick, Moritz; Jordà, Òscar (2014-12)
Is there a link between loose monetary conditions, credit growth, house price booms, and financial instability? This paper analyzes the role of interest rates and credit in driving house price booms and busts with data spanning 140 years of modern economic history in the advanced economies. We exploit the implications of the macroeconomic policy trilemma to identify exogenous variation in monetary conditions: countries with fixed exchange regimes often see fluctuations in short-term interest rates unrelated to home economic conditions. We use novel instrumental variable local projection ...
Working Paper Series , Paper 2014-28

Working Paper
Measuring Transaction Costs in the Absence of Timestamps
Zikes, Filip (2017-04-06)
This paper develops measures of transaction costs in the absence of transaction timestamps and information about who initiates transactions, which are data limitations that often arise in studies of over-the-counter markets. I propose new measures of the effective spread and study the performance of all estimators analytically, in simulations, and present an empirical illustration with small-cap stocks for the 2005-2014 period. My theoretical, simulation, and empirical results provide new insights into measuring transaction costs and may help guide future empirical work.
Finance and Economics Discussion Series , Paper 2017-045

Working Paper
Bayesian Inference and Prediction of a Multiple-Change-Point Panel Model with Nonparametric Priors
Jensen, Mark J.; Fisher, Mark (2018-02-01)
Change point models using hierarchical priors share in the information of each regime when estimating the parameter values of a regime. Because of this sharing, hierarchical priors have been very successful when estimating the parameter values of short-lived regimes and predicting the out-of-sample behavior of the regime parameters. However, the hierarchical priors have been parametric. Their parametric nature leads to global shrinkage that biases the estimates of the parameter coefficient of extraordinary regimes toward the value of the average regime. To overcome this shrinkage, we model ...
FRB Atlanta Working Paper , Paper 2018-2

Working Paper
Selection Without Exclusion
Hu, Luojia; Honore, Bo E. (2018-07-02)
It is well understood that classical sample selection models are not semiparametrically identified without exclusion restrictions. Lee (2009) developed bounds for the parameters in a model that nests the semiparametric sample selection model. These bounds can be wide. In this paper, we investigate bounds that impose the full structure of a sample selection model with errors that are independent of the explanatory variables but have unknown distribution. We find that the additional structure in the classical sample selection model can significantly reduce the identified set for the parameters ...
Working Paper Series , Paper WP-2018-10

Working Paper
Estimation of the discontinuous leverage effect: Evidence from the NASDAQ order book
Winkelmann, Lars; Bibinger, Markus; Neely, Christopher J. (2017-04-26)
An extensive empirical literature documents a generally negative correlation, named the ?leverage effect,? between asset returns and changes of volatility. It is more challenging to establish such a return-volatility relationship for jumps in high-frequency data. We propose new nonparametric methods to assess and test for a discontinuous leverage effect ? i.e. a relation between contemporaneous jumps in prices and volatility ? in high-frequency data with market microstructure noise. We present local tests and estimators for price jumps and volatility jumps. Five years of transaction data from ...
Working Papers , Paper 2017-12

Working Paper
The Taylor rule and forecast intervals for exchange rates
Wang, Jian; http://fedora:8080/fcrepo/rest/objects/authors/ (2008)
This paper attacks the Meese-Rogoff (exchange rate disconnect) puzzle from a different perspective: out-of-sample interval forecasting. Most studies in the literature focus on point forecasts. In this paper, we apply Robust Semi-parametric (RS) interval forecasting to a group of Taylor rule models. Forecast intervals for twelve OECD exchange rates are generated and modified tests of Giacomini and White (2006) are conducted to compare the performance of Taylor rule models and the random walk. Our contribution is twofold.> ; First, we find that in general, Taylor rule models generate tighter ...
Globalization Institute Working Papers , Paper 22

Report
Nonlinear Binscatter Methods
Cattaneo, Matias D.; Crump, Richard K.; Feng, Yingjie; Farrell, Max H. (2024-08-01)
Binscatters are a powerful tool for empirical work in the social, behavioral, and biomedical sciences. Available tools rely on least squares estimation of the conditional mean. We introduce novel binscatter methods based on nonlinear, possibly nonsmooth M-estimation, covering generalized linear, robust, and quantile regression models. We provide theoretical results and practical tools, including optimal bin selection, confidence bands, and statistical tests regarding functional form or shape restrictions. We demonstrate our methods by studying the relationship of income and (lack of) health ...
Staff Reports , Paper 1110

Working Paper
Systemic Tail Risk: High-Frequency Measurement, Evidence and Implications
Yang, Xiye; Neely, Christopher J.; Erdemlioglu, Deniz (2023-07-20)
We develop a new framework to measure market-wide (systemic) tail risk in the cross-section of high-frequency stock returns. We estimate the time-varying jump intensities of asset prices and introduce a testing approach that identifies multi-asset tail risk based on the release times of scheduled news announcements. Using high-frequency data on individual U.S. stocks and sector-specific ETF portfolios, we find that most of the FOMC announcements create systemic left tail risk, but there is no evidence that macro announcements do so. The magnitude of the tail risk induced by Fed news varies ...
Working Papers , Paper 2023-016

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