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Details about Mengheng Li

E-mail:
Homepage:https://menghengli.net/
Workplace:Economics Discipline Group, Business School, University of Technology Sydney, (more information at EDIRC)

Access statistics for papers by Mengheng Li.

Last updated 2020-07-14. Update your information in the RePEc Author Service.

Short-id: pli1187


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Working Papers

2019

  1. The multivariate simultaneous unobserved components model and identification via heteroskedasticity
    Working Paper Series, Economics Discipline Group, UTS Business School, University of Technology, Sydney Downloads

2018

  1. Are long-run output growth rates falling?
    Working Paper Series, Department of Economics, University of Utah, University of Utah, Department of Economics Downloads View citations (2)
    See also Journal Article in Metroeconomica (2020)
  2. Forecasting economic time series using score-driven dynamic models with mixed-data sampling
    Tinbergen Institute Discussion Papers, Tinbergen Institute Downloads View citations (1)
    See also Journal Article in International Journal of Forecasting (2019)
  3. Leverage, asymmetry and heavy tails in the high-dimensional factor stochastic volatility model
    Working Paper Series, Economics Discipline Group, UTS Business School, University of Technology, Sydney Downloads
  4. Looking for the stars: Estimating the natural rate of interest
    Working Paper Series, Economics Discipline Group, UTS Business School, University of Technology, Sydney Downloads
  5. Unobserved Components with Stochastic Volatility in U.S. Inflation: Estimation and Signal Extraction
    Tinbergen Institute Discussion Papers, Tinbergen Institute Downloads View citations (1)

Journal Articles

2020

  1. Are long‐run output growth rates falling?
    Metroeconomica, 2020, 71, (1), 204-234 Downloads
    See also Working Paper (2018)
  2. Long-term forecasting of El Niño events via dynamic factor simulations
    Journal of Econometrics, 2020, 214, (1), 46-66 Downloads

2019

  1. Forecasting economic time series using score-driven dynamic models with mixed-data sampling
    International Journal of Forecasting, 2019, 35, (4), 1735-1747 Downloads
    See also Working Paper (2018)
 
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