School of Economics

 

profile image for Dr Stefano Grassi

Dr Stefano Grassi

Lecturer in Economics

School of Economics, Keynes College, D1.05

Stefano is Director of Studies and Chief Examiner for Stage 2

About

Stefano Grassi is a Lecturer in Economics at the School of Economics of the University of Kent, based in Canterbury. He also has an affiliation with CREATES (Center of Research in Econometrics Analysis in Time Series) and is a member of the Macroeconomics, Growth and History Centre (MaGHiC).

Stefano's research interests are time series econometrics, state space models, Bayesian analysis and computational econometrics.

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Publications

Stefano's publications can also be found on RePEc and ResearchGate.

Also view these in the Kent Academic Repository

Article
Grassi, S. et al. (2016). The R package MitISEM: Efficient and Robust Simulation Procedures for Bayesian Inference. Journal of Statistical Software.
Grassi, S., Nonejad, N. and Santucci de Magistris, P. (2016). Forecasting with the Standardized Self-Perturbed Kalman Filter. Journal of Applied Econometrics [Online] 32:318-341. Available at: http://dx.doi.org/10.1002/jae.2522.
Bastürk, N. et al. (2016). Parallelization Experience with Four Canonical Econometric Models using ParMitISEM. Econometrics 4:1-20.
Grassi, S. and Santucci de Magistris, P. (2015). It's all about volatility of volatility: evidence from a two-factor stochastic volatility model. Journal of Empirical Finance [Online] 30:62-78. Available at: http://dx.doi.org/10.1016/j.jempfin.2014.11.007.
Proietti, T. and Grassi, S. (2015). Stochastic trends and seasonality in economic time series: new evidence from Bayesian stochastic model specification search. Empirical Economics [Online] 48:983-1011. Available at: http://dx.doi.org/10.1007/s00181-014-0821-y.
Grassi, S. et al. (2015). EuroMInd-C: a Disaggregate Monthly Indicator of Economic Activity for the Euro Area and member countries. International Journal of Forecasting [Online] 31:712-738. Available at: http://dx.doi.org/10.1016/j.ijforecast.2014.08.015.
Casarin, R. et al. (2015). Parallel Sequential Monte Carlo for Efficient Density Combination: The DeCo MATLAB Toolbox. Journal of Statistical Software [Online]. Available at: http://dx.doi.org/10.18637/jss.v068.i03.
Grassi, S., Nicolosi, M. and Stanghellini, E. (2014). Item Response Models to measure Corporate Social Responsibility. Applied Financial Economics [Online] 24:1449-1464. Available at: http://dx.doi.org/10.1080/09603107.2014.925070.
Grassi, S. and Proietti, T. (2014). Characterising Economic Trends by Bayesian Stochastic Model Specification Search. Computational Statistics and Data Analysis [Online] 71:359-374. Available at: http://dx.doi.org/10.1016/j.csda.2013.02.024.
Grassi, S. and de Magistris, P. (2014). When Long Memory Meets the Kalman Filter: A Comparative Study. Computational Statistics and Data Analysis [Online] 76:301-319. Available at: http://dx.doi.org/10.1016/j.csda.2012.10.018.
Grassi, S. and Dziubinski, M. (2013). Heterogeneous Computing In Economics: A Simplified Approach. Heterogeneous Computing In Economics: A Simplified Approach [Online] 43:485-495. Available at: http://dx.doi.org/10.1007/s10614-013-9362-2.
Grassi, S., Hillebrand, E. and Ventosa-Santaularia, D. (2013). The statistical relation of sea-level and temperature revisited. Dynamics of Atmospheres and Oceans [Online] 64:1-9. Available at: http://dx.doi.org/10.1016/j.dynatmoce.2013.07.001.
Grassi, S. and Proietti, T. (2010). Has the Volatility of U.S. Inflation Changed and How? Journal of Time Series Econometrics [Online] 2:1941-1928. Available at: http://dx.doi.org/10.2202/1941-1928.1050.
Book section
Grassi, S. and Proietti, T. (2012). Bayesian stochastic model specification search for seasonal and calendar effects. in: Economic Time Series: Modeling and Seasonality. Chapman and Hall/CRC Press. Available at: http://dx.doi.org/10.1201/b11823-25.
Total publications in KAR: 14 [See all in KAR]

 

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Research

Research interests

Time series econometrics, state space models, Bayesian analysis and computational econometrics.

Stefano's RePEc page is http://econpapers.repec.org/RAS/pgr438.htm

Working Papers

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Consultation hours

  • Mon 15.00-16.00
  • Tue 09.00-10.00
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PhD supervision

Current research themes within which Stefano Grassi can consider supervising PhD students, include:

  • Time series econometrics
  • State space models
  • Bayesian analysis 
  • Computational econometrics.

Projects need to have a substantial methodological and empirical content.

Current PhD students

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Administrative roles

  • Director of Studies and Chief Examiner for Stage 2
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School of Economics, Keynes College, University of Kent, Canterbury, Kent, CT2 7NP

Undergraduate enquiries: +44 (0) 1227 827497, Postgraduate enquiries: +44 (0) 1227 827440 or email us

Last Updated: 02/03/2017