My current research focuses on building high-dimensional time-varying models useful for empirical macroeconomic analysis and forecasting. In particular, many of my current projects involve developing flexible large Bayesian VARs. For more information, please see here.

More generally, my research interests include inflation modeling, output gap estimation, Bayesian model comparison and efficient estimation of nonlinear state space models. For more information about my research on trend inflation models, see here.

MATLAB code and datasets used in some of my papers can be found below. The code is arranged by topics here.

US trend inflation estimates from various models can be downloaded here.

See also my Google Scholar citations and information about my coauthors.


Books


Working Papers

Refereed Journal Publications

  1. Large Order-Invariant Bayesian VARs with Stochastic Volatility
    Joshua Chan, Gary Koop and Xuewen Yu (2023)
    Journal of Business and Economic Statistics, forthcoming
    [ Journal Version | Working Paper | Code ]
  2. High-Dimensional Conditionally Gaussian State Space Models with Missing Data
    Joshua Chan, Aubrey Poon and Dan Zhu (2023)
    Journal of Econometrics, 236(1): 105468
    [ Journal Version | Working Paper | YouTube video ]
    (Previously circulated as Efficient Estimation of State-Space Mixed-Frequency VARs: A Precision-Based Approach)
  3. Comparing Stochastic Volatility Specifications for Large Bayesian VARs
    Joshua Chan (2023)
    Journal of Econometrics, 235(2): 1419-1446
    [ Journal Version | Working Paper | Code ]
  4. Large Hybrid Time-Varying Parameter VARs
    Joshua Chan (2023)
    Journal of Business and Economic Statistics, 41(3): 890-905
    [ Journal Version | Working Paper | Code ]
  5. An Unobserved Components Model of Total Factor Productivity and the Relative Price of Investment
    Joshua Chan and Edouard Wemy (2023)
    Macroeconomic Dynamics, 27(5): 1397-1423
    [ Journal Version | Working Paper ]
  6. Bayesian State Space Models in Macroeconometrics
    Joshua Chan and Rodney Strachan (2023)
    Journal of Economic Surveys, 37(1): 58-75
    [ Journal Version | Working Paper ]
  7. Corrigendum to: Large Bayesian Vector Autoregressions with Stochastic Volatility and Non-Conjugate Priors
    Andrea Carriero, Joshua Chan, Todd Clark and Massimiliano Marcellino (2022)
    Journal of Econometrics, 227(2): 506-512
    [ Journal Version | Working Paper | Code ]
  8. Asymmetric Conjugate Priors for Large Bayesian VARs
    Joshua Chan (2022)
    Quantitative Economics, 13(3): 1145-1169
    [ Journal Version | Working Paper | Code ]
    (An earlier version of the paper with a forecasting application and the associated code)
  9. An Automated Prior Robustness Analysis in Bayesian Model Comparison
    Joshua Chan, Liana Jacobi and Dan Zhu (2022)
    Journal of Applied Econometrics, 37(3): 583-602
    [ Journal Version | Working Paper | Code ]
  10. Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility
    Joshua Chan and Xuewen Yu (2022)
    Journal of Economic Dynamics and Control, 143, 104505
    [ Journal Version | Working Paper ]
  11. Choosing Between Identification Schemes in Noisy-News Models
    Joshua Chan, Eric Eisenstat and Gary Koop (2022)
    Studies in Nonlinar Dynamics and Econometrics, 26(1): 99-136
    [ Journal Version | Working Paper ]
    (Previous title: Quantifying the Effects of Noise Shocks: A Structural VARMA Approach)
  12. Minnesota-Type Adaptive Hierarchical Priors for Large Bayesian VARs
    Joshua Chan (2021)
    International Journal of Forecasting, 37(3): 1212-1226
    [ Journal Version | Working Paper | Code ]
  13. Speculative Bubbles in Present-Value Models: A Bayesian Markov-Switching State Space Approach
    Joshua Chan and Caterina Santi (2021)
    Journal of Economic Dynamics and Control, 127, 104101
    [ Journal Version | Working Paper ]
  14. Composite Likelihood Methods for Large Bayesian VARs with Stochastic Volatility
    Joshua Chan, Eric Eisenstat, Chenghan Hou and Gary Koop (2020)
    Journal of Applied Econometrics, 35(6): 692-711
    [ Journal Version | Working Paper | Online Appendix | Code ]
  15. Reducing the State Space Dimension in a Large TVP-VAR
    Joshua Chan, Eric Eisenstat and Rodney Strachan (2020)
    Journal of Econometrics, 218(1): 105-118
    [ Journal Version | Working Paper | Online Appendix | Code ]
  16. Stochastic Volatility Models with ARMA Innovations: An Application to G7 Inflation Forecasts
    Bo Zhang, Joshua Chan and Jamie Cross (2020)
    International Journal of Forecasting, 36(4): 1318-1328
    [ Journal Version | Working Paper | Online Appendix ]
  17. Efficient Selection of Hyperparameters in Large Bayesian VARs Using Automatic Differentiation
    Joshua Chan, Liana Jacobi and Dan Zhu (2020)
    Journal of Forecasting, 39(6): 934-943
    [ Journal Version | Working Paper | Code ]
  18. Large Bayesian VARs: A Flexible Kronecker Error Covariance Structure
    Joshua Chan (2020)
    Journal of Business and Economic Statistics, 38(1), 68-79
    [ Journal Version | Working Paper | Code ]
  19. Robust Estimation and Inference for Importance Sampling Estimators with Infinite Variance
    Joshua Chan, Chenghan Hou and Thomas Yang (2020)
    Advances in Econometrics, 41, 255-285
    [ Journal Version | Working Paper ]
  20. Identifying Noise Shocks
    Luca Benati, Joshua Chan, Eric Eisenstat and Gary Koop (2020)
    Journal of Economic Dynamics and Control, 111, 103780
    [ Journal Version | Working Paper | Online Appendix ]
  21. An Alternate Parameterization for Bayesian Nonparametric / Semiparametric Regression
    Justin Tobias and Joshua Chan (2019)
    Advances in Econometrics, 40B, 47-64
    [ Journal Version | Working Paper ]
  22. How Sensitive Are VAR Forecasts to Prior Hyperparameters? An Automated Sensitivity Analysis
    Joshua Chan, Liana Jacobi and Dan Zhu (2019)
    Advances in Econometrics, 40A, 229-248
    [ Journal Version | Working Paper | Code ]
  23. A Regime Switching Skew-normal Model of Contagion
    Joshua Chan, Renée Fry-McKibbin and Cody Hsiao (2019)
    Studies in Nonlinear Dynamics and Econometrics, 23(1): 20170001
    [ Journal Version | Working Paper | Code ]
  24. Measuring Inflation Expectations Uncertainty Using High-Frequency Data
    Joshua Chan and Yong Song (2018)
    Journal of Money, Credit and Banking, 50(6), 1139-1166
    [ Journal Version | Working Paper | Code ]
  25. Invariant Inference and Efficient Computation in the Static Factor Model
    Joshua Chan, Roberto Leon-Gonzalez and Rodney Strachan (2018)
    Journal of the American Statistical Association, 113, 819-828
    [ Journal Version | Working Paper | Code ]
  26. Comparing Hybrid Time-Varying Parameter VARs
    Joshua Chan and Eric Eisenstat (2018)
    Economics Letters, 171, 1-5 (lead article)
    [ Journal Version | Working Paper | Code ]
  27. Bayesian Model Comparison for Time-Varying Parameter VARs with Stochastic Volatility
    Joshua Chan and Eric Eisenstat (2018)
    Journal of Applied Econometrics, 33(4), 509-532
    [ Journal Version | Working Paper | Code ]
  28. Specification Tests for Time-Varying Parameter Models with Stochastic Volatility
    Joshua Chan (2018)
    Econometric Reviews, 37(8), 807-823 (lead article)
    [ Journal Version | Working Paper | Code | Trend Inflation Estimates ]
  29. A New Model of Inflation, Trend Inflation, and Long-Run Inflation Expectations
    Joshua Chan, Todd Clark and Gary Koop (2018)
    Journal of Money, Credit and Banking, 50(1), 5-53 (lead article)
    [ Journal Version | Working Paper | Code | Trend Inflation Estimates ]
  30. Efficient Estimation of Bayesian VARMAs with Time-Varying Coefficients
    Joshua Chan and Eric Eisenstat (2017)
    Journal of Applied Econometrics, 32(7), 1277-1297
    [ Journal Version | Working Paper | Code ]
  31. Nonparametric Estimation in Economics: Bayesian and Frequentist Approaches
    Joshua Chan, Daniel Henderson, Christopher Parmeter, Justin Tobias (2017)
    WIREs Computational Statistics, 9(6), e1406
    [ Journal Version | Working Paper ]
  32. A Bayesian Model Comparison for Trend-Cycle Decompositions of Output
    Angelia Grant and Joshua Chan (2017)
    Journal of Money, Credit and Banking, 49(2-3), 525-552
    [ Journal Version | Working Paper | Code ]
  33. Reconciling Output Gaps: Unobserved Components Model and Hodrick-Prescott Filter
    Angelia Grant and Joshua Chan (2017)
    Journal of Economic Dynamics and Control, 75, 114-121
    [ Journal Version | Working Paper | Code ]
  34. The Stochastic Volatility in Mean Model with Time-Varying Parameters: An Application to Inflation Modeling
    Joshua Chan (2017)
    Journal of Business and Economic Statistics, 35(1), 17-28
    [ Journal Version | Working Paper | Code ]
  35. Large Bayesian VARMAs
    Joshua Chan, Eric Eisenstat and Gary Koop (2016)
    Journal of Econometrics, 192(2), 374-390
    [ Journal Version | Working Paper | Appendix | Code ]
  36. On the Observed-Data Deviance Information Criterion for Volatility Modeling
    Joshua Chan and Angelia Grant (2016)
    Journal of Financial Econometrics, 14(4), 772-802
    [ Journal Version | Working Paper | Code ]
    (Previous title: Issues in Comparing Stochastic Volatility Models Using the Deviance Information Criterion)
  37. Stochastic Model Specification Search for Time-Varying Parameter VARs
    Eric Eisenstat, Joshua Chan and Rodney Strachan (2016)
    Econometric Reviews, 35(8-10), 1638-1665
    [ Journal Version | Working Paper | Code ]
  38. Fast Computation of the Deviance Information Criterion for Latent Variable Models
    Joshua Chan and Angelia Grant (2016)
    Computational Statistics and Data Analysis, 100, 847-859
    [ Journal Version | Working Paper | Code ]
  39. A Bounded Model of Time Variation in Trend Inflation, NAIRU and the Phillips Curve
    Joshua Chan, Gary Koop and Simon Potter (2016)
    Journal of Applied Econometrics, 31(3), 551-565
    [ Journal Version | Working Paper | Appendix | Code | Trend Inflation Estimates ]
  40. Modeling Energy Price Dynamics: GARCH versus Stochastic Volatility
    Joshua Chan and Angelia Grant (2016)
    Energy Economics, 54, 182-189
    [ Journal Version | Working Paper | Code ]
  41. Priors and Posterior Computation in Linear Endogenous Variables Models with Imperfect Instruments
    Joshua Chan and Justin Tobias (2015)
    Journal of Applied Econometrics, 30(4), 650-674
    [ Journal Version | Working Paper | Code ]
  42. Pitfalls of Estimating the Marginal Likelihood Using the Modified Harmonic Mean
    Joshua Chan and Angelia Grant (2015)
    Economics Letters, 131, 29-33
    [ Journal Version | Working Paper ]
  43. Marginal Likelihood Estimation with the Cross-Entropy Method
    Joshua Chan and Eric Eisenstat (2015)
    Econometric Reviews, 34(3), 256-285 (lead article)
    [ Journal Version | Working Paper | Code ]
  44. Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables
    Joshua Chan and Gary Koop (2014)
    Computational Statistics and Data Analysis, 76, 186-193
    [ Journal Version | Working Paper ]
  45. Moving Average Stochastic Volatility Models with Application to Inflation Forecast
    Joshua Chan (2013)
    Journal of Econometrics, 176(2), 162-172
    [ Journal Version | Working Paper | Code ]
  46. A New Model of Trend Inflation
    Joshua Chan, Gary Koop and Simon Potter (2013)
    Journal of Business and Economic Statistics, 31(1), 94-106
    [ Journal Version | Working Paper | Appendix | Code | Trend Inflation Estimates ]
  47. Time Varying Dimension Models
    Joshua Chan, Gary Koop, Roberto Leon-Gonzalez and Rodney Strachan (2012)
    Journal of Business and Economic Statistics, 30(3), 358-367
    [ Journal Version | Working Paper | Appendix ]
  48. Improved Cross-Entropy Method for Estimation
    Joshua Chan and Dirk Kroese (2012)
    Statistics and Computing, 22(5), 1031-1040
    [ Journal Version | Working Paper | Code ]
  49. A Comparison of Cross-Entropy and Variance Minimization Strategies
    Joshua Chan, Peter Glynn and Dirk Kroese (2011)
    Journal of Applied Probability, 48A, 183-194
    [ Journal Version | Working Paper ]
  50. Rare-event Probability Estimation with Conditional Monte Carlo
    Joshua Chan and Dirk Kroese (2011)
    Annals of Operations Research, 189, 43-61
    [ Journal Version | Working Paper]
  51. Efficient Estimation of Large Portfolio Loss Probabilities in t-copula Models
    Joshua Chan and Dirk Kroese (2010)
    European Journal of Operational Research, 205, 361-367
    [ Journal Version | Working Paper ]
  52. MCMC Estimation of Restricted Covariance Matrix
    Joshua Chan and Ivan Jeliazkov (2009)
    Journal of Computational and Graphical Statistics, 18, 457-480
    [ Journal Version | Working Paper | Code ]
  53. Efficient Simulation and Integrated Likelihood Estimation in State Space Models
    Joshua Chan and Ivan Jeliazkov (2009)
    International Journal of Mathematical Modelling and Numerical Optimisation, 1, 101-120
    [ Journal Version | Working Paper | Code ]
  54. Replication of the Results in 'Learning about Heterogeneity in Returns to Schooling'
    Joshua Chan (2005)
    Journal of Applied Econometrics, 20, 439-443
    [ Journal Version ]

Book Chapters

  1. Bayesian Econometric Methods
    Joshua Chan and Justin Tobias (2021)
    In: A. Flores-Lagunes and K. Zimmermann (Eds.), Methods and Data, Handbook in Labor, Human Resources and Population Economics, Springer Nature
  2. Large Bayesian Vector Autoregressions
    Joshua Chan (2020)
    In: P. Fuleky (Eds), Macroeconomic Forecasting in the Era of Big Data, 95-125, Springer, Cham (Code)
  3. Estimation of Stochastic Volatility Models with Heavy Tails and Serial Dependence
    Joshua Chan and Cody Hsiao (2014)
    In: I. Jeliazkov and X.-S. Yang (Eds.), Bayesian Inference in the Social Sciences, 159-180, John Wiley & Sons, Hoboken, New Jersey (Code)
  4. Monte Carlo Methods for Portfolio Credit Risk
    Tim Brereton, Joshua Chan and Dirk Kroese (2013)
    In: H. Scheule and D. Rosch (Eds.), Credit Portfolio Securitizations and Derivatives, 127-152, John Wiley & Sons, New York

Refereed Conference Proceedings

  1. Fitting Mixture Importance Sampling Distributions via Improved Cross-Entropy
    Tim Brereton, Joshua Chan and Dirk Kroese (2011)
    Proceedings of the 2011 Winter Simulation Conference, 422-428
  2. Randomized Methods for Solving the Winner Determination Problem in Combinatorial Auctions
    Joshua Chan and Dirk Kroese (2008)
    Proceedings of the 2008 Winter Simulation Conference, 1344-1349