1. Long term forecasting of El Niño events via dynamic factor simulations, by M. Li, S.J. Koopman, R. Lit, and D. Petrova, Journal of Econometrics, Volumn 209, forthcoming. Latest working paper;

2. Forecasting economic time series using score-driven models with mixed-data sampling, by P. Gorgi, S.J. Koopman and M. Li, International Journal of Forecasting, Volume 34, forthcoming. Latest working paper;

Working papers

1. Unobserved components and stochastic volatility in U.S. Inflation: Estimation and signal extraction, by M. Li and S.J. Koopman, R&R Journal of Applied EconometricsPaper; Tinbergen Institute Discussion Paper: TI2018-027/III.

2. Are long-run output growth rates falling? by M. Li and I. Mendieta-Muñoz, Paper; University of Utah, Department of Economics Working Paper Series: 2018-02.

3. Leverage, asymmetry and heavy tails in the high-dimensional factor stochastic volatility model, by M. Li and M. Scharth, Paper; UTS Business School Economics Discipline Group Working Paper Series: 2018-49.

4. Look for the stars: Estimating the natural rate of interest, by M. Li and I. Hindrayanto, Paper;

Work in progress

1. Identify long-run non-neutrality of aggregate demand shocks via heteroskedasticity, by M. Li and I. Mendieta-Muñoz.

2. Univariate treatment of multivariate latent stationary processes when they are superimposed, by M. Li

3. Volatility in commonality or commonality in volatility? by M. Li and S. Wang

4. Understand (the failure of) uncovered interest rate parity in a data-rich environment, by M. Li and B. Fu.