Herbert Zhao

Professor, Department of Economics

Photo of Herbert  Zhao

Contact Info

Phone:
410-704-2338
Office:
Stephens Hall, 101-G



Education

Ph D, Economics, University at Albany, State University of New York, 2014

Areas of Expertise

Economic and Financial Forecasting

Survey Analytics and Predictive Analytics

Macro and Financial Econometrics

Selected Publications and Presentations

  • Could Diffusion Indexes Have Forecasted the Great Depression?,
    Publisher: John Wiley & Sons Ltd, March, 2025
  • Uncertainty of Household Inflation Expectations: Reconciling Point and Density Forecasts,
    Publisher: Elsevier, January (1st Quarter/Winter), 2024
  • Internal Consistency of Household Inflation Expectations:Point Forecasts vs. Density Forecasts,
    Publisher: International Journal of Forecasting, September, 2023
  • Uncertainty and Disagreement of Inflation Expectations: Evidence from Household-Level Qualitative Survey Responses,
    Publisher: Journal of Forecasting, June, 2022
  • The Nordhaus Test with Many Zeros,
    Publisher: Economics Letters, August, 2020
  • Nowcasting in Real Time Using Popularity Priors,
    Publisher: International Journal of Forecasting, June, 2020
  • Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set,
    Publisher: Journal of Business Cycle Research , May, 2020
  • The Robustness of Forecast Combination in Unstable Environments: A Monte Carlo Study of Advanced Algorithms,
    Publisher: Empirical Economics, April (2nd Quarter/Spring), 2020
  • Updates to Household Inflation Expectations: Signal or Noise?,
    Publisher: Economics Letters, August, 2019
  • Inflation expectations in India: Learning from household tendency surveys,
    Publisher: International Journal of Forecasting, July (3rd Quarter/Summer), 2019
  • International propagation of shocks: A dynamic factor model using survey forecasts,
    Publisher: International Journal of Forecasting, July (3rd Quarter/Summer), 2019
  • Business Cycle Synchronization: A Bayesian Model of Survey Forecasts,
    Publisher: American Statistical Association: JSM Proceedings, Business and Economic Statistics Section, December, 2017
  • On-line Learning and Forecast Combination in Unbalanced Panels,
    Publisher: Econometric Reviews, January (1st Quarter/Winter), 2017
  • Forecasting Consumption: The Role of Consumer Confidence in Real Time with Many Predictors,
    Publisher: Journal of Applied Econometrics, December, 2016
  • Determinants of Consumer Sentiment Over Business Cycles: Evidence from the U.S. Surveys of Consumers,
    Publisher: Journal of Business Cycle Research, September, 2016
  • Quantifying survey expectations: A critical review and generalization of the Carlson–Parkin method,
    Publisher: International Journal of Forecasting, February, 2015
  • Testing the value of probability forecasts for calibrated combining,
    Publisher: International Journal of Forecasting, February, 2015
  • Modeling Hedge Fund Returns: Selection, Non-linearity and Managerial Efficiency,
    Publisher: Managerial and Decision Economics, February, 2014
  • The yield spread puzzle and the information content of SPF forecasts,
    Publisher: Economics Letters, January (1st Quarter/Winter), 2013
  • On Estimating the Failure Probability of Hedge Funds,
    Publisher: Research in Finance, , 2011

Grants & Contracts

  • Learning from Professional Forecasters’ Mistakes
    Sponsor: CBE Faculty Development & Research Committee, 2026
  • Do Consumers Use Economic Theory to Form Their Expectations? Should They?
    Sponsor: CBE Faculty Development & Research Committee, 2025
  • Could Diffusion Indexes Have Forecasted the Great Depression?
    Sponsor: CBE Faculty Development and Research Committee, 2022
  • Agree to Disagree about an Uncertain Future? Learning from Consumers’ Experiences and Household Surveys
    Sponsor: CBE Faculty Development and Research Committee, 2019
  • Identification and Time Series Properties of the Breakeven Points of the Purchasing Managers' Index (PMI) and Its Components
    Sponsor: Towson University Faculty Development and Research Committee, 2019
  • Constructing a “Big Data”-Based Composite Coincident Indicator: A Quantification Approach
    Sponsor: Towson Academy of Scholars, 2016
  • Real-Time Monitoring of Macroeconomic Uncertainty: Combining Official Statistics, Professional Forecasts, and Economic News
    Sponsor: CBE Faculty Development and Research Committee, 2015
  • SAS-IIF Grant to Support Research on Principles of Forecasting
    Sponsor: International Institute of Forecasters, 2014