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Codes



SOME CODES RELATED TO MY WORK
(click on the title to download)


Determining the number of static factors in approximate factor models       Matlab
Reference:
L. Alessi, M. Barigozzi, M. Capasso
Improved penalization for determining the number of factors in approximate static factor models
Statistics and Probability Letters, 2010, 80, 1806–1813


Structural dynamic factor model for the euro area       Matlab
Reference:
M. Barigozzi, A. Conti, M. Luciani
Do euro area countries respond asymmetrically to the common monetary policy?
Oxford Bulletin of Economics and Statistics, 2014, 76, 693–714


nets       R package
Reference:
M. Barigozzi, C. Brownlees
NETS: Network estimation for time series
Journal of Applied Econometrics, 2019, 34, 347-364


Dynamic factor models and volatilties       Matlab
References:
M. Barigozzi, M. Hallin
Generalized dynamic factor models and volatilities: recovering the market volaitility shocks
Econometrics Journal, 2016, 19, C33–C60
M. Barigozzi, M. Hallin
Generalized dynamic factor models and volatilities: estimation and forecasting
Journal of Econometrics, 2017, 201, 307–321
M. Barigozzi, M. Hallin
Generalized dynamic factor models and volatilities: consistency, rates, and prediction intervals
Journal of Econometrics, 2020, 116, 4-34


Factors and networks for volatilties       Matlab
Reference:
M. Barigozzi, M. Hallin
A network analysis of the volatility of high-dimensional financial series
Journal of the Royal Statistical Society - series C, 2017, 66(3), 581–605


Non-stationary dynamic factor models       Matlab
Reference:
M. Barigozzi, M. Lippi, M. Luciani
Large-dimensional dynamic factor models: estimation of impulse-response functions with I(1) cointegrated factors
Journal of Econometrics, 2020, available online


factorcpt       R package
Reference:
M. Barigozzi, H. Cho, P. Fryzlewicz
Simultaneous multiple change–point and factor analysis for high-dimensional time series
Journal of Econometrics, 2018, 206, 187-225


Factors and international financial markets       Matlab
Reference: M. Barigozzi, M. Hallin, S. Soccorsi
Identification of global and local shocks in international financial markets via general dynamic factor models
Journal of Financial Econometrics, 2019, 17, 462-494


Locally stationary general dynamic factor model       Matlab
Reference: M. Barigozzi, M. Hallin, S. Soccorsi, R. von Sachs
Time-varying general dynamic factor models and the measurement of financial connectedness
Journal of Econometrics, 2020, available online


Measuring output gap       Matlab
Reference: M. Barigozzi, M. Luciani
Measuring the output gap using large datasets




OTHER CODES
(click on the title to download)


Generalized Dynamic Factor Model       Matlab
written by M. Barigozzi, M. Forni, R. Liška, M. Luciani

References:
M. Forni, M. Hallin, M. Lippi, L. Reichlin (2000) The Generalized Dynamic Factor Model: Identification and estimation
The Review of Economics and Statistics, 82, 540-554
M. Forni, M. Hallin, M. Lippi, L. Reichlin (2005) The Generalized Dynamic Factor Model: One-sided estimation and forecasting
Journal of the American Statistical Association, 100, 830-840
M. Forni, M. Hallin, M. Lippi, P. Zaffaroni (2017) Dynamic Factor Models with infinite-dimensional factor space: Asymptotic analysis
Journal of Econometrics, 199, 74-92
M. Hallin, R. Liška (2007) Determining the number of factors in the General Dynamic Factor Model
Journal of the American Statistical Association, 102, 603-617