Working papers
- A Gibbs Sampler for Efficient Bayesian Inference in Sign-Identified SVARs
- On the Wisdom of Crowds (of Economists)
- Testing for Endogeneity: A Moment-Based Bayesian Approach
- Measuring Fairness in the US Mortgage Market
- Constructing Applicants from Loan-level Data: A Case Study of Mortgage Applications
- Capital-Based Corporate Tax Benefits: Endogenous Misallocation through Lobbying
Publications
- Inference Based on Time-Varying SVARs Identified with Sign Restrictions
- On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates
- Macroeconomic Forecasting and Variable Ordering in Multivariate Stochastic Volatility Models
- The Causal Effects of Lockdown Policies on Health and Macroeconomic Outcomes
- A Statistical Learning Approach to Land Valuation: Optimizing the Use of External Information
- Bayesian Estimation and Comparison of Conditional Moment Models
- DSGE-SVt: An Econometric Toolkit for High-Dimensional DSGE Models with SV and t Errors
- A New Approach to Identifying the Real Effects of Uncertainty Shocks
- Probability Forecast Combination via Entropy Regularized Wasserstein Distance
- Machine Learning for Regularized Survey Forecast Combination: Partially-Egalitarian Lasso and Its Derivatives
- Bayesian Estimation and Comparison of Moment Condition Models
- Metropolitan Land Values
- On the Comparison of Interval Forecasts
- Measuring International Uncertainty: the Case of Korea
- Real-Time Forecast Evaluation of DSGE Models with Stochastic Volatility
- Does Realized Volatility Help Bond Yield Density Prediction?
- Assessing Point Forecast Accuracy by Stochastic Error Distance
- Assessing Point Forecast Accuracy by Stochastic Loss Distance
Other Publications
- Breaking Down the Latest Fight Against Inflation
- Failure of Silicon Valley Bank Reduced Local Consumer Spending but Had Limited Effect on Aggregate Spending
- Measuring Disagreement in Probabilistic and Density Forecasts
- Tracking U.S. Real GDP Growth During the Pandemic
- Bayesian GMM
Ph.D. Dissertation, 2015