Mirko Armillotta

I am a Research Associate at the Department of Econometrics and Data Science, Vrije Universiteit Amsterdam. Prior to my current position, I had a PostDoc position at the University of Cyprus and a visiting research period at Lancaster University. I received the Ph.D. and M.Sc. in Statistical Sciences from the University of Bologna. I have been awarded with the Award for the Best Ph.D. thesis in Statistics 2022 by the Italian Statistical Society. I also hold a Marie Skłodowska-Curie Individual Fellowship financed by the European Commission.

Research interests: Discrete-valued time series, Econometrics, Forecasting economic variables, Network time series, Observation-driven models, Time Series Analysis.

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Email: m.armillotta@vu.nl

Research

Published Articles and Book Chapters

• Armillotta M., Tsagris M., and Fokianos K. (2024)   Inference for Network Count Time Series with the R Package PNAR.   The R Journal, forthcoming.
• Armillotta M., Fokianos K., and Guizzardi A. (2024)   Unveiling Venice's hotels competition networks from dynamic pricing digital market.   Journal of the Royal Statistical Society Series A: Statistics in Society, 187(1): 130-157.
• Armillotta M., Fokianos K. (2023)   Nonlinear Network Autoregression.   The Annals of Statistics, 51(6): 2526-2552.   [Open access version]
• Armillotta M., Fokianos K. (2023)   Count Network Autoregression.   Journal of Time Series Analysis, jtsa.12728.
• Armillotta M. (2023)   Two-stage weighted least squares estimator of multivariate conditional mean observation-driven time series models.   Book of short Papers SIS 2023, Pearson, pp. 770-775.
• Armillotta M., Luati A. and Lupparelli M. (2023)   An overview of ARMA-like models for count and binary data.   Trends and Challenges in Categorical Data Analysis, Springer, 2023, pp. 233-274.
• Armillotta M., Fokianos K., and Krikidis I. (2023)   Bootstrapping Network Autoregressive Models for Testing Linearity.   Data Science in Applications, Springer, 2023, pp. 99-116.
• Armillotta M., Luati A. and Lupparelli M. (2022)   Observation-driven models for discrete-valued time series.   Electronic Journal of Statistics 16(1): 1393-1433.
• Armillotta M., Fokianos K. and Krikidis I. (2022)   Generalized Linear Models Network Autoregression.   Network Science, Springer, 2022, pp. 112-125.
• Armillotta M., Luati A. and Lupparelli M. (2020)   Observation-driven models for storm counts.   Book of short Papers SIS 2020, Pearson, 2020, pp. 863-868.
• Armillotta M., Luati A. and Lupparelli M. (2019)   Stationarity of a general class of observation driven models for discrete valued processes.   Book of short Papers SIS 2019, Pearson, 2019, pp. 31-39.

Working Papers

• Armillotta M. (2023)   Two-stage weighted least squares estimator of multivariate discrete-valued observation-driven models, under review.
• Armillotta M., Gorgi P. (2023)   Pseudo-variance quasi-maximum likelihood estimation of semi-parametric time series models, under review.

Software

• Tsagris M., Armillotta M. and Fokianos K.   R Package PNAR: Poisson Network Autoregressive Models.  

Curriculum Vitae

Current Position

• 2022 - present, Research Associate, Department Econometrics & Data Science, Vrije Universiteit Amsterdam.
• 2023 - present, Candidate Fellow, Tinbergen Institute.

Past Positions

• 2020 - 2022, Postdoctoral Researcher, Department of Mathematics & Statistics, University of Cyprus.
• Feb 2020 - May 2020, Visiting Researcher, Department of Mathematics & Statistics, Lancaster University.
• 2017 - 2019, Teaching tutor, Department of Statistics and Department of Economics, University of Bologna.

Education

• 2017 - 2021, Ph.D. in Statistical Sciences, University of Bologna.   
  Dissertation title: Essays on discrete valued time series models.
  
• 2015 - 2017, M.A. (cum laude) in Statistics, Economics and Business, University of Bologna.
  
• 2012 - 2015, B.Sc. (cum laude) in Statistical Sciences, University of Bologna.

Teaching

• 2023 - present, Statistics PM. Teacher and Course coordinator, Vrije Universiteit Amsterdam (English).
• 2022 - 2023, Econometrics II. Teacher, Vrije Universiteit Amsterdam (English).

Awards & Fellowships

• Marie Skłodowska-Curie Individual Fellowship financed by the European Commission (4/2023-present).
• Award for the Best Ph.D. thesis in Statistics 2022, awarded by the Italian Statistical Society.

Download CV here