Photo of Edward P. Herbst

Edward P. Herbst

Education

  • Ph.D., Economics, University of Pennsylvania, 2011
  • B.A., Mathematics & Economics, Rutgers University, 2006
Current Research Topics
  • Estimation of Dynamic Models
  • Density Forecast Evaluation
  • Principal Economist

    Board of Governors of the Federal Reserve System

    2016 - present
  • Senior Economist

    Board of Governors of the Federal Reserve System

    2015 - 2016
  • Economist

    Board of Governors of the Federal Reserve System

    2011 - 2015
  • Hebden, James, Edward P. Herbst, Jenny Tang, Giorgio Topa, and Fabian Winkler (2020). "How Robust Are Makeup Strategies to Key Alternative Assumptions?" Finance and Economics Discussion Series 2020-069. Board of Governors of the Federal Reserve System (U.S.).
  • Cai, Michael, Marco Del Negro, Edward Herbst, Ethan Matlin, Reca Sarfati, and Frank Schorfheide (2020). "Online Estimation of DSGE Models," Finance and Economics Discussion Series 2020-023. Board of Governors of the Federal Reserve System (U.S.).
  • Herbst, Edward P., and Benjamin K. Johannsen (2020). "Bias in Local Projections," Finance and Economics Discussion Series 2020-010. Board of Governors of the Federal Reserve System (U.S.).
  • Gust, Christopher, Edward Herbst, and David López-Salido (2018). "Forward Guidance with Bayesian Learning and Estimation," Finance and Economics Discussion Series 2018-072. Board of Governors of the Federal Reserve System (U.S.)
  • Caldara, Dario, and Edward Herbst (2019). "Monetary Policy, Real Activity, and Credit Spreads: Evidence from Bayesian Proxy SVARs," American Economic Journal: Macroeconomics, vol. 11, no. 1, pp. 157-192.
  • Herbst, Edward, and Frank Schorfheide (2019). "Tempered Particle Filtering," Journal of Econometrics, vol. 210, no. 1, pp. 26-44.
  • Bognanni, Mark, and Edward Herbst (2018). "A Sequential Monte Carlo Approach to Inference in Multiple-Equation Markov-Switching Models," Journal of Applied Econometrics, vol. 33, no. 1, pp. 126-140.
  • Gust, Christopher, Edward Herbst, David López-Salido, and Matthew E. Smith (2017). "The Empirical Implications of the Interest-Rate Lower Bound," American Economic Review, vol. 107, no. 7, pp. 1971-2006.
  • Herbst, Edward P., and Frank Schorfheide (2016). "Bayesian Estimation of DSGE Models." Princeton, N.J.: Princeton University Press.
  • Chung, Hess, Edward Herbst, and Michael T. Kiley (2015). "Effective Monetary Policy Strategies in New Keynesian Models: A Reexamination," in Parker, Jonathan A., and Michael Woodford NBER Macroeconomics Annual 2014, University of Chicago Press, vol. 29, no. 1, pp. 289-344.
  • Herbst, Edward (2015). "Using the 'Chandrasekhar Recursions' for Likelihood Evaluation of DSGE Models," Computational Economics, vol. 45, no. 4, pp. 693-705.
  • Herbst, Edward, and Frank Schorfheide (2014). "Sequential Monte Carlo Sampling for DSGE Models," Journal of Applied Econometrics, vol. 29, no. 7, pp. 1073-1098.
  • Herbst, Edward, and Frank Schorfheide (2012). "Evaluating DSGE Model Forecasts of Comovements," Journal of Econometrics, vol. 171, no. 2, pp. 152-166.
  • Herbst, Edward, and Frank Schorfheide (2017). "Tempered Particle Filtering," NBER Working Paper, no. 23448. National Bureau of Economic Research.
  • Caldara, Dario, and Edward Herbst (2016). "Monetary Policy, Real Activity, and Credit Spreads: Evidence from Bayesian Proxy SVARs," Finance and Economics Discussion Series 2016-049. Board of Governors of the Federal Reserve System (U.S.).
  • Herbst, Edward, and Frank Schorfheide (2016). "Tempered Particle Filtering," Finance and Economics Discussion Series 2016-072. Board of Governors of the Federal Reserve System (U.S.).
  • Gust, Christopher J., Edward P. Herbst, J. David López-Salido, and Matthew E. Smith (2012). "The Empirical Implications of the Interest-Rate Lower Bound," Finance and Economics Discussion Series 2012-83r2. Board of Governors of the Federal Reserve System (U.S.).
  • Bognanni, Mark, and Edward P. Herbst (2015). "Estimating (Markov-Switching) VAR Models without Gibbs Sampling: A Sequential Monte Carlo Approach," Finance and Economics Discussion Series 2015-116. Board of Governors of the Federal Reserve System (U.S.).
  • Herbst, Edward P., and Frank Schorfheide (2013). "Sequential Monte Carlo Sampling for DSGE Models," Finance and Economics Discussion Series 2013-43. Board of Governors of the Federal Reserve System (U.S.).
  • Herbst, Edward (2012). "Using the Chandrasekhar Recursions for Likelihood Evaluation of DSGE Models," Finance and Economics Discussion Series 2012-35. Board of Governors of the Federal Reserve System (U.S.).
  • Herbst, Edward, and Frank Schorfheide (2012). "Evaluating DSGE Model Forecasts of Comovements," Finance and Economics Discussion Series 2012-11. Board of Governors of the Federal Reserve System (U.S.).
  • Herbst, Edward, and Frank Schorfheide (2012). "Sequential Monte Carlo Sampling for DSGE Models," Working Papers 12-27. Federal Reserve Bank of Philadelphia.
  • Herbst, Edward, and Frank Schorfheide (2011). "Evaluating DSGE Model Forecasts of Comovements," Working Papers 11-5. Federal Reserve Bank of Philadelphia.
  • Bognanni, Mark, and Edward Herbst (2014). "Estimating (Markov-Switching) VAR Models without Gibbs Sampling: A Sequential Monte Carlo Approach," Working Paper, no. 14-27. Federal Reserve Bank of Cleveland.
  • Chung, Hess, Edward Herbst, and Michael T. Kiley (2014). "Effective Monetary Policy Strategies in New Keynesian Models: A Re-Examination," NBER Working Paper 20611. National Bureau of Economic Research.
  • Herbst, Edward P. (2011). "Essays on Bayesian Macroeconometrics," Ph.D. dissertation, University of Pennsylvania.
  • discussion

    October 2011

    NBER/Federal Reserve Bank of Philadelphia Workshop on DSGE Models

    Discussion of Smith: Estimating Nonlinear Economic Models Using Surrogate Transitions

  • conference

    June 2011

    Canadian Economic Association Annual Meeting

    Evaluating Predictions of Comovements

  • conference

    April 2011

    Society for Bayesian Inference in Econometrics and Statistics 2011 Meeting

    Gradient and Hessian-based MCMC for Macro Models

  • seminar

    January 2011

    Board of Governors of the Federal Reserve System

    Gradient and Hessian-based MCMC for Macro Models

Referee
  • International Economic Review
  • International Journal of Forecasting
  • Journal of Money, Credit, and Banking
  • Review of Economics and Statistics
Professional Affiliation
  • American Economic Association
  • International Society for Bayesian Analysis
Last update: September 14, 2020