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Discussion Paper
Measuring and Managing COVID-19 Model Risk
Jensen, Mark J. (2020-06-18)
One of the many lessons learned from the financial crisis is the increased awareness of model risk. In this article, I apply the best practices of model risk management found in SR 11-7 (which offers regulatory guidance on the best practices for managing model risk) to COVID-19 models. In particular, I investigate the Institute of Health Metrics and Evaluation's (IHME) model to see if it has been effectively challenged with a critical assessment of its conceptual soundness, ongoing monitoring, and outcomes analysis.
Policy Hub* , Paper 2020-07

Discussion Paper
Measuring and Managing COVID-19 Model Risk
Jensen, Mark J. (2020-06-18)
One of the many lessons learned from the financial crisis is the increased awareness of model risk. In this article, I apply the best practices of model risk management found in SR 11-7 (which offers regulatory guidance on the best practices for managing model risk) to COVID-19 models. In particular, I investigate the Institute of Health Metrics and Evaluation’s (IHME) model to see if it has been effectively challenged with a critical assessment of its conceptual soundness, ongoing monitoring, and outcomes analysis.
Policy Hub* , Paper 2020-7

Journal Article
Measuring and Managing COVID-19 Model Risk
Jensen, Mark J. (2020-06-18)
One of the many lessons learned from the financial crisis is the increased awareness of model risk. In this article, I apply the best practices of model risk management found in SR 11-7 (which offers regulatory guidance on the best practices for managing model risk) to COVID-19 models. In particular, I investigate the Institute of Health Metrics and Evaluation's (IHME) model to see if it has been effectively challenged with a critical assessment of its conceptual soundness, ongoing monitoring, and outcomes analysis.
Policy Hub , Volume 2020 , Issue 7 , Pages 12

Report
Identifying and Evaluating Sample Selection Bias in Consumer Payment Surveys
Hitczenko, Marcin (2015-11-23)
This paper develops a two-stage statistical analysis to identify and assess the effect of a sample selection bias associated with an individual’s household role. The methodology is applied to the 2012 Survey of Consumer Payment Choice. Survey responses to a series of questions about the respondent’s role in household finances are combined and adjusted for response error to estimate a latent variable that represents each individual’s share of household responsibility. The distribution of this variable among survey respondents suggests that the sampling procedure favors household members ...
Consumer Payments Research Data Reports , Paper 2015-07

Working Paper
Risk, Return, and Volatility Feedback: A Bayesian Nonparametric Analysis
Maheu, John M.; Jensen, Mark J. (2014-06-01)
The relationship between risk and return is one of the most studied topics in finance. The majority of the literature is based on a linear, parametric relationship between expected returns and conditional volatility. This paper models the contemporaneous relationship between market excess returns and contemporaneous log-realized variances nonparametrically with an infinite mixture representation of their joint distribution. The conditional distribution of excess returns given log-realized variance will also have an infinite mixture representation but with probabilities and arguments depending ...
FRB Atlanta Working Paper , Paper 2014-6

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
The Usefulness of the Median CPI in Bayesian VARs Used for Macroeconomic Forecasting and Policy
Meyer, Brent; Zaman, Saeed (2016-11-01)
In this paper we investigate the forecasting performance of the median Consumer Price Index (CPI) in a variety of Bayesian vector autoregressions (BVARs) that are often used for monetary policy. Until now, the use of trimmed-mean price statistics in forecasting inflation has often been relegated to simple univariate or Phillips curve approaches, thus limiting their usefulness in applications that require consistent forecasts of multiple macro variables. We find that inclusion of an extreme trimmed-mean measure?the median CPI?improves the forecasts of both core and headline inflation (CPI and ...
FRB Atlanta Working Paper , Paper 2016-13

Working Paper
Inference Based on SVARs Identified with Sign and Zero Restrictions: Theory and Applications
Rubio-Ramirez, Juan F.; Waggoner, Daniel F.; Arias, Jonas E. (2014-02-01)
In this paper, we develop algorithms to independently draw from a family of conjugate posterior distributions over the structural parameterization when sign and zero restrictions are used to identify SVARs. We call this family of conjugate posterior distributions normal-generalized-normal. Our algorithms draw from a conjugate uniform-normal-inverse-Wishart posterior over the orthogonal reduced-form parameterization and transform the draws into the structural parameterization; this transformation induces a normal-generalized-normal posterior distribution over the structural parameterization. ...
FRB Atlanta Working Paper , Paper 2014-1

Working Paper
Robust estimation of nonstationary, fractionally integrated, autoregressive, stochastic volatility
Jensen, Mark J. (2015-11-01)
Empirical volatility studies have discovered nonstationary, long-memory dynamics in the volatility of the stock market and foreign exchange rates. This highly persistent, infinite variance?but still mean reverting?behavior is commonly found with nonparametric estimates of the fractional differencing parameter d, for financial volatility. In this paper, a fully parametric Bayesian estimator, robust to nonstationarity, is designed for the fractionally integrated, autoregressive, stochastic volatility (SV-FIAR) model. Joint estimates of the autoregressive and fractional differencing parameters ...
FRB Atlanta Working Paper , Paper 2015-12

Working Paper
Fitting a distribution to survey data for the half-life of deviations from PPP
Fisher, Mark (2015-12-15)
This note presents a nonparametric Bayesian approach to fitting a distribution to the survey data provided in Kilian and Zha (2002) regarding the prior for the half-life of deviations from purchasing power parity (PPP). A point mass at infinity is included. The unknown density is represented as an average of shape-restricted Bernstein polynomials, each of which has been skewed according to a preliminary parametric fit. A sparsity prior is adopted for regularization.
FRB Atlanta Working Paper , Paper 2015-15

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