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Matteo Barigozzi

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Matteo Barigozzi & Giuseppe Cavaliere & Graziano Moramarco, 2022. "Factor Network Autoregressions," Papers 2208.02925, arXiv.org, revised Feb 2024.

    Mentioned in:

    1. Factor Network Autoregressions
      by Francis Diebold in No Hesitations on 2022-09-18 22:10:00
  2. Matteo Barigozzi & Christian Brownlees, 2013. "Nets: Network Estimation for Time Series," Working Papers 723, Barcelona School of Economics.

    Mentioned in:

    1. NBER/NSF Time-Series Conference: Retrospect and Prospect
      by Francis Diebold in No Hesitations on 2013-10-25 18:14:00
    2. Network Estimation for Time Series
      by Francis Diebold in No Hesitations on 2013-10-16 16:41:00

Working papers

  1. Matteo Barigozzi & Marc Hallin, 2024. "The Dynamic, the Static, and the Weak factor models and the analysis of high-dimensional time series," Papers 2407.10653, arXiv.org.

    Cited by:

    1. Ignacio Garr'on & C. Vladimir Rodr'iguez-Caballero & Esther Ruiz, 2024. "International vulnerability of inflation," Papers 2410.20628, arXiv.org, revised Oct 2024.

  2. Matteo Barigozzi & Filippo Pellegrino, 2023. "Multidimensional dynamic factor models," Papers 2301.12499, arXiv.org.

    Cited by:

    1. Matteo Barigozzi, 2023. "Quasi Maximum Likelihood Estimation of High-Dimensional Factor Models: A Critical Review," Papers 2303.11777, arXiv.org, revised May 2024.

  3. Matteo Barigozzi & Giuseppe Cavaliere & Graziano Moramarco, 2022. "Factor Network Autoregressions," Papers 2208.02925, arXiv.org, revised Feb 2024.

    Cited by:

    1. Marko Mlikota, 2022. "Cross-Sectional Dynamics Under Network Structure: Theory and Macroeconomic Applications," Papers 2211.13610, arXiv.org, revised Sep 2024.
    2. Andrea Bastianin & Chiara Casoli & Marzio Galeotti, 2023. "The connectedness of Energy Transition Metals," Working Papers 2023.11, Fondazione Eni Enrico Mattei.
    3. Francis X. Diebold & Kamil Yilmaz, 2022. "On the Past, Present, and Future of the Diebold-Yilmaz Approach to Dynamic Network Connectedness," Papers 2211.04184, arXiv.org, revised Jan 2023.

  4. Matteo Barigozzi & Daniele Massacci, 2022. "Modelling Large Dimensional Datasets with Markov Switching Factor Models," Papers 2210.09828, arXiv.org, revised Dec 2024.

    Cited by:

    1. Matteo Barigozzi, 2022. "On Estimation and Inference of Large Approximate Dynamic Factor Models via the Principal Component Analysis," Papers 2211.01921, arXiv.org, revised Jul 2023.

  5. Matteo Barigozzi & Marc Hallin & Matteo Luciani & Paolo Zaffaroni, 2021. "Inferential Theory for Generalized Dynamic Factor Models," Working Papers ECARES 2021-20, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Philipp Gersing, 2024. "A Distributed Lag Approach to the Generalised Dynamic Factor Model (GDFM)," Papers 2410.20885, arXiv.org.
    2. Matteo Barigozzi & Marc Hallin, 2024. "The Dynamic, the Static, and the Weak factor models and the analysis of high-dimensional time series," Papers 2407.10653, arXiv.org.
    3. Philipp Gersing, 2024. "On the Existence of One-Sided Representations in the Generalised Dynamic Factor Model," Papers 2410.18159, arXiv.org.

  6. Barigozzi, Matteo & Hallin, Marc & Soccorsi, Stefano, 2019. "Identification of global and local shocks in international financial markets via general dynamic factor models," LSE Research Online Documents on Economics 86932, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Riccardo Borghi & Eric Hillebrand & Jakob Mikkelsen & Giovanni Urga, 2018. "The dynamics of factor loadings in the cross-section of returns," CREATES Research Papers 2018-38, Department of Economics and Business Economics, Aarhus University.
    2. Niţoi, Mihai & Pochea, Maria Miruna, 2022. "The nexus between bank connectedness and investors’ sentiment," Finance Research Letters, Elsevier, vol. 44(C).
    3. Carlos Cesar Trucios-Maza & João H. G Mazzeu & Luis K. Hotta & Pedro L. Valls Pereira & Marc Hallin, 2019. "On the robustness of the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting," Working Papers ECARES 2019-32, ULB -- Universite Libre de Bruxelles.
    4. Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
    5. Matteo Barigozzi & Marc Hallin & Stefano Soccorsi, 2019. "Time-Varying General Dynamic Factor Models and the Measurement of Financial Connectedness," Working Papers ECARES 2019-09, ULB -- Universite Libre de Bruxelles.
    6. Lucchetti, Riccardo & Venetis, Ioannis A., 2020. "A replication of "A quasi-maximum likelihood approach for large, approximate dynamic factor models" (Review of Economics and Statistics, 2012)," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 14, pages 1-14.
    7. Barigozzi, Matteo & Hallin, Marc, 2020. "Generalized dynamic factor models and volatilities: Consistency, rates, and prediction intervals," Journal of Econometrics, Elsevier, vol. 216(1), pages 4-34.
    8. Thomas Lux & Duc Thi Luu & Boyan Yanovski, 2020. "An analysis of systemic risk in worldwide economic sentiment indices," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 47(4), pages 909-928, November.
    9. Trucíos Maza, Carlos César & Mazzeu, João H. G. & Hotta, Luiz Koodi & Pereira, Pedro L. Valls & Hallin, Marc, 2020. "Robustness and the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting," Textos para discussão 521, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).

  7. Matteo Barigozzi & Matteo Luciani, 2019. "Quasi Maximum Likelihood Estimation of Non-Stationary Large Approximate Dynamic Factor Models," Papers 1910.09841, arXiv.org.

    Cited by:

    1. Lippi, Marco & Deistler, Manfred & Anderson, Brian, 2023. "High-Dimensional Dynamic Factor Models: A Selective Survey and Lines of Future Research," Econometrics and Statistics, Elsevier, vol. 26(C), pages 3-16.
    2. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    3. Matteo Barigozzi, 2023. "Quasi Maximum Likelihood Estimation of High-Dimensional Factor Models: A Critical Review," Papers 2303.11777, arXiv.org, revised May 2024.
    4. Matteo Barigozzi & Daniele Massacci, 2022. "Modelling Large Dimensional Datasets with Markov Switching Factor Models," Papers 2210.09828, arXiv.org, revised Dec 2024.
    5. Matteo Barigozzi & Angelo Cuzzola & Marco Grazzi & Daniele Moschella, 2021. "Factoring in the micro: a transaction-level dynamic factor approach to the decomposition of export volatility," LEM Papers Series 2021/22, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    6. Paolo Andreini & Cosimo Izzo & Giovanni Ricco, 2020. "Deep Dynamic Factor Models," Papers 2007.11887, arXiv.org, revised May 2023.
    7. Lucchetti, Riccardo & Venetis, Ioannis A., 2020. "A replication of "A quasi-maximum likelihood approach for large, approximate dynamic factor models" (Review of Economics and Statistics, 2012)," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 14, pages 1-14.
    8. Hie Joo Ahn & Matteo Luciani, 2021. "Relative prices and pure inflation since the mid-1990s," Finance and Economics Discussion Series 2021-069, Board of Governors of the Federal Reserve System (U.S.).
    9. Fresoli, Diego & Poncela, Pilar & Ruiz, Esther, 2023. "Ignoring cross-correlated idiosyncratic components when extracting factors in dynamic factor models," Economics Letters, Elsevier, vol. 230(C).
    10. Matteo Barigozzi & Marc Hallin & Matteo Luciani & Paolo Zaffaroni, 2021. "Inferential Theory for Generalized Dynamic Factor Models," Working Papers ECARES 2021-20, ULB -- Universite Libre de Bruxelles.
    11. Luke Hartigan & Michelle Wright, 2021. "Financial Conditions and Downside Risk to Economic Activity in Australia," RBA Research Discussion Papers rdp2021-03, Reserve Bank of Australia.
    12. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
    13. Serena Ng & Susannah Scanlan, 2023. "Constructing High Frequency Economic Indicators by Imputation," Papers 2303.01863, arXiv.org, revised Oct 2023.
    14. Poncela, Pilar & Ruiz, Esther, 2020. "A comment on the dynamic factor model with dynamic factors," Economics Discussion Papers 2020-7, Kiel Institute for the World Economy (IfW Kiel).
    15. Matteo Barigozzi, 2023. "Asymptotic equivalence of Principal Components and Quasi Maximum Likelihood estimators in Large Approximate Factor Models," Papers 2307.09864, arXiv.org, revised Jun 2024.

  8. Matteo Barigozzi & Matteo Luciani, 2019. "Quasi Maximum Likelihood Estimation and Inference of Large Approximate Dynamic Factor Models via the EM algorithm," Papers 1910.03821, arXiv.org, revised Sep 2024.

    Cited by:

    1. Danilo Cascaldi-Garcia & Matteo Luciani & Michele Modugno, 2024. "Lessons from nowcasting GDP across the world," Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 8, pages 187-217, Edward Elgar Publishing.
    2. Filippo Pellegrino, 2021. "Factor-augmented tree ensembles," Papers 2111.14000, arXiv.org, revised Jun 2023.
    3. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    4. Linton, O. B. & Tang, H. & Wu, J., 2022. "A Structural Dynamic Factor Model for Daily Global Stock Market Returns," Janeway Institute Working Papers camjip:2214, Faculty of Economics, University of Cambridge.
    5. Junfan Mao & Zhigen Gao & Bing-Yi Jing & Jianhua Guo, 2024. "On the statistical analysis of high-dimensional factor models," Statistical Papers, Springer, vol. 65(8), pages 4991-5019, October.
    6. Diego Fresoli & Pilar Poncela & Esther Ruiz, 2024. "Dealing with idiosyncratic cross-correlation when constructing confidence regions for PC factors," Papers 2407.06883, arXiv.org.
    7. Hie Joo Ahn & Matteo Luciani, 2021. "Relative prices and pure inflation since the mid-1990s," Finance and Economics Discussion Series 2021-069, Board of Governors of the Federal Reserve System (U.S.).
    8. Linton, O. B. & Tang, H. & Wu, J., 2022. "A Structural Dynamic Factor Model for Daily Global Stock Market Returns," Cambridge Working Papers in Economics 2237, Faculty of Economics, University of Cambridge.
    9. Poncela, Pilar & Ruiz, Esther, 2020. "A comment on the dynamic factor model with dynamic factors," Economics Discussion Papers 2020-7, Kiel Institute for the World Economy (IfW Kiel).

  9. Barigozzi, M. & Hallin, M. & Soccorsi, S. & Von Sachs, R., 2019. "Time-Varying General Dynamic Factor Models and the Measurement of Financial Connectedness," LIDAM Discussion Papers ISBA 2019024, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Longo, Luigi & Riccaboni, Massimo & Rungi, Armando, 2022. "A neural network ensemble approach for GDP forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    2. Baruník, Jozef & Ellington, Michael, 2024. "Persistence in financial connectedness and systemic risk," European Journal of Operational Research, Elsevier, vol. 314(1), pages 393-407.
    3. Ellington, Michael, 2022. "Fat tails, serial dependence, and implied volatility index connections," European Journal of Operational Research, Elsevier, vol. 299(2), pages 768-779.
    4. Rigana, Katerina & Wit, Ernst-Jan Camiel & Cook, Samantha, 2023. "A new way of measuring effects of financial crisis on contagion in currency markets," International Review of Financial Analysis, Elsevier, vol. 90(C).
    5. Katerina Rigana & Ernst-Jan Camiel Wit & Samantha Cook, 2021. "Using Network-based Causal Inference to Detect the Sources of Contagion in the Currency Market," Papers 2112.13127, arXiv.org.
    6. Ouyang, Zisheng & Zhou, Xuewei & Lu, Min & Liu, Ke, 2024. "Imported financial risk in global stock markets: Evidence from the interconnected network," Research in International Business and Finance, Elsevier, vol. 69(C).
    7. Rajae Azrak & Guy Mélard, 2022. "Autoregressive Models with Time-Dependent Coefficients—A Comparison between Several Approaches," Stats, MDPI, vol. 5(3), pages 1-21, August.
    8. Vidal-Llana, Xenxo & Uribe, Jorge M. & Guillén, Montserrat, 2023. "European stock market volatility connectedness: The role of country and sector membership," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    9. Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2024. "Forecasting Growth-at-Risk of the United States: Housing Price versus Housing Sentiment or Attention," Working Papers 202401, University of Pretoria, Department of Economics.
    10. Baruník, Jozef & Bevilacqua, Mattia & Faff, Robert, 2024. "Dynamic industry uncertainty networks and the business cycle," Journal of Economic Dynamics and Control, Elsevier, vol. 159(C).
    11. Matteo Barigozzi & Marc Hallin & Matteo Luciani & Paolo Zaffaroni, 2021. "Inferential Theory for Generalized Dynamic Factor Models," Working Papers ECARES 2021-20, ULB -- Universite Libre de Bruxelles.
    12. Jianqing Fan & Ricardo Masini & Marcelo C. Medeiros, 2021. "Bridging factor and sparse models," Papers 2102.11341, arXiv.org, revised Sep 2022.
    13. Marc Hallin, 2022. "Manfred Deistler and the General Dynamic Factor Model Approach to the Analysis of High-Dimensional Time Series," Working Papers ECARES 2022-30, ULB -- Universite Libre de Bruxelles.
    14. Erik Kole & Dick van Dijk, 2022. "Moments, Shocks and Spillovers in Markov-switching VAR Models," Tinbergen Institute Discussion Papers 21-080/III, Tinbergen Institute, revised 11 Jan 2022.
    15. Marina Yu. Malkina, 2024. "Financial Contagion of the Commodity Markets from the Stock Market during Pandemic and New Sanctions Shocks," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 23(2), pages 452-475.
    16. Jonas Krampe & Luca Margaritella, 2024. "Global bank network connectedness revisited: What is common, idiosyncratic and when?," Papers 2402.02482, arXiv.org.
    17. Marc Hallin, 2022. "Manfred Deistler and the General-Dynamic-Factor-Model Approach to the Statistical Analysis of High-Dimensional Time Series," Econometrics, MDPI, vol. 10(4), pages 1-9, December.
    18. Han Liu & Yongjing Wang & Haiyan Song & Ying Liu, 2023. "Measuring tourism demand nowcasting performance using a monotonicity test," Tourism Economics, , vol. 29(5), pages 1302-1327, August.
    19. Eric Hillebrand & Jakob Mikkelsen & Lars Spreng & Giovanni Urga, 2020. "Exchange Rates and Macroeconomic Fundamentals: Evidence of Instabilities from Time-Varying Factor Loadings," CREATES Research Papers 2020-19, Department of Economics and Business Economics, Aarhus University.

  10. Barigozzi, Matteo, 2018. "On the stability of euro area money demand and its implications for monetary policy," LSE Research Online Documents on Economics 87283, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Stephen M. Miller & Luis F. Martins & Rangan Gupta, 2014. "A Time-Varying Approach of the US Welfare Cost of Inflation," Working papers 2014-11, University of Connecticut, Department of Economics.
    2. Raouf Boucekkine & Mohammed Laksaci & Mohamed Touati-Tliba, 2021. "Long-run stability of money demand and monetary policy: the case of Algeria," Working Papers halshs-03120699, HAL.
    3. Jung, Alexander & Carcel Villanova, Hector, 2020. "The empirical properties of euro area M3, 1980-2017," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 37-49.
    4. William A. Barnett & Marcelle Chauvet & Danilo Leiva‐Leon & Liting Su, 2024. "The Credit‐Card‐Services Augmented Divisia Monetary Aggregates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 56(5), pages 1163-1202, August.
    5. Conti, Antonio M., 2021. "Resurrecting the Phillips Curve in Low-Inflation Times," Economic Modelling, Elsevier, vol. 96(C), pages 172-195.

  11. Barigozzi, Matteo & Cho, Haeran & Fryzlewicz, Piotr, 2018. "Simultaneous multiple change-point and factor analysis for high-dimensional time series," LSE Research Online Documents on Economics 88110, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Zhou, Ruichao & Wu, Jianhong, 2023. "Determining the number of change-points in high-dimensional factor models by cross-validation with matrix completion," Economics Letters, Elsevier, vol. 232(C).
    2. Jiangtao Duan & Jushan Bai & Xu Han, 2021. "Quasi-maximum likelihood estimation of break point in high-dimensional factor models," Papers 2102.12666, arXiv.org, revised Mar 2021.
    3. Matteo Barigozzi & Lorenzo Trapani, 2017. "Sequential testing for structural stability in approximate factor models," Papers 1708.02786, arXiv.org, revised Mar 2020.
    4. Barigozzi, Matteo & Cho, Haeran & Fryzlewicz, Piotr, 2018. "Simultaneous multiple change-point and factor analysis for high-dimensional time series," Journal of Econometrics, Elsevier, vol. 206(1), pages 187-225.
    5. Matteo Barigozzi & Daniele Massacci, 2022. "Modelling Large Dimensional Datasets with Markov Switching Factor Models," Papers 2210.09828, arXiv.org, revised Dec 2024.
    6. Matteo Barigozzi & Marc Hallin & Stefano Soccorsi, 2019. "Time-Varying General Dynamic Factor Models and the Measurement of Financial Connectedness," Working Papers ECARES 2019-09, ULB -- Universite Libre de Bruxelles.
    7. Thomas Despois & Catherine Doz, 2021. "Identifying and interpreting the factors in factor models via sparsity: Different approaches," Working Papers halshs-02235543, HAL.
    8. Cho, Haeran & Kirch, Claudia, 2024. "Data segmentation algorithms: Univariate mean change and beyond," Econometrics and Statistics, Elsevier, vol. 30(C), pages 76-95.
    9. Ma, Chenchen & Tu, Yundong, 2023. "Shrinkage estimation of multiple threshold factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1876-1892.
    10. Anastasiou, Andreas & Cribben, Ivor & Fryzlewicz, Piotr, 2022. "Cross-covariance isolate detect: a new change-point method for estimating dynamic functional connectivity," LSE Research Online Documents on Economics 112148, London School of Economics and Political Science, LSE Library.
    11. Zhang, Lyuou & Zhou, Wen & Wang, Haonan, 2021. "A semiparametric latent factor model for large scale temporal data with heteroscedasticity," Journal of Multivariate Analysis, Elsevier, vol. 186(C).
    12. Jushan Bai & Jiangtao Duan & Xu Han, 2022. "Likelihood ratio test for structural changes in factor models," Papers 2206.08052, arXiv.org, revised Dec 2023.
    13. Li, Degui, 2024. "Estimation of Large Dynamic Covariance Matrices: A Selective Review," Econometrics and Statistics, Elsevier, vol. 29(C), pages 16-30.
    14. Cho, Haeran & Korkas, Karolos K., 2022. "High-dimensional GARCH process segmentation with an application to Value-at-Risk," Econometrics and Statistics, Elsevier, vol. 23(C), pages 187-203.
    15. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    16. Matteo Barigozzi, 2022. "On Estimation and Inference of Large Approximate Dynamic Factor Models via the Principal Component Analysis," Papers 2211.01921, arXiv.org, revised Jul 2023.
    17. Wang, Lu & Wu, Jianhong, 2022. "Estimation of high-dimensional factor models with multiple structural changes," Economic Modelling, Elsevier, vol. 108(C).
    18. Wang, Hanchao & Peng, Bin & Li, Degui & Leng, Chenlei, 2021. "Nonparametric estimation of large covariance matrices with conditional sparsity," Journal of Econometrics, Elsevier, vol. 223(1), pages 53-72.
    19. Fernandez, Julian, 2020. "Exchange Rate Uncertainty and the Interest Rate Parity," MPRA Paper 116010, University Library of Munich, Germany, revised 2022.
    20. Mengjia Yu & Xiaohui Chen, 2021. "Finite sample change point inference and identification for high‐dimensional mean vectors," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(2), pages 247-270, April.
    21. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.
    22. Qing Yang & Yu-Ning Li & Yi Zhang, 2020. "Change point detection for nonparametric regression under strongly mixing process," Statistical Papers, Springer, vol. 61(4), pages 1465-1506, August.
    23. Matteo Barigozzi & Matteo Luciani, 2019. "Quasi Maximum Likelihood Estimation and Inference of Large Approximate Dynamic Factor Models via the EM algorithm," Papers 1910.03821, arXiv.org, revised Sep 2024.
    24. Alessandro Casini & Pierre Perron, 2021. "Change-Point Analysis of Time Series with Evolutionary Spectra," Papers 2106.02031, arXiv.org, revised Aug 2024.
    25. Xialu Liu & Elynn Y. Chen, 2022. "Identification and estimation of threshold matrix‐variate factor models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(3), pages 1383-1417, September.
    26. Cui, Junfeng & Wang, Guanghui & Zou, Changliang & Wang, Zhaojun, 2023. "Change-point testing for parallel data sets with FDR control," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    27. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
    28. Ma, Chenchen & Tu, Yundong, 2023. "Group fused Lasso for large factor models with multiple structural breaks," Journal of Econometrics, Elsevier, vol. 233(1), pages 132-154.
    29. Christis Katsouris, 2023. "Break-Point Date Estimation for Nonstationary Autoregressive and Predictive Regression Models," Papers 2308.13915, arXiv.org.
    30. Thomas Despois & Catherine Doz, 2021. "Identifying and interpreting the factors in factor models via sparsity: Different approaches," PSE Working Papers halshs-02235543, HAL.
    31. Eric Hillebrand & Jakob Mikkelsen & Lars Spreng & Giovanni Urga, 2020. "Exchange Rates and Macroeconomic Fundamentals: Evidence of Instabilities from Time-Varying Factor Loadings," CREATES Research Papers 2020-19, Department of Economics and Business Economics, Aarhus University.

  12. Matteo Barigozzi & Lorenzo Trapani, 2018. "Determining the dimension of factor structures in non-stationary large datasets," Papers 1806.03647, arXiv.org.

    Cited by:

    1. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    2. Lorenzo Trapani & Emily Whitehouse, 2020. "Sequential monitoring for cointegrating regressions," Papers 2003.12182, arXiv.org.

  13. Matteo Barigozzi & Matteo Luciani, 2018. "Do National Account Statistics Underestimate US Real Output Growth?," FEDS Notes 2018-01-09-1, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Kenneth E. Poole & Allison Forbes & Nichelle Williams, 2023. "Applied Regional Economic Research Can Improve Development Strategies and Drive Better Outcomes," Economic Development Quarterly, , vol. 37(1), pages 85-95, February.
    2. Zheng Liu & Mark M. Spiegel & Eric Tallman, 2018. "Is GDP Overstating Economic Activity?," FRBSF Economic Letter, Federal Reserve Bank of San Francisco.

  14. Matteo Barigozzi & Marc Hallin, 2018. "Generalized Dynamic Factor Models and Volatilities: Consistency, rates, and prediction intervals," Papers 1811.10045, arXiv.org, revised Jul 2019.

    Cited by:

    1. Hallin, Marc & Trucíos, Carlos, 2023. "Forecasting value-at-risk and expected shortfall in large portfolios: A general dynamic factor model approach," Econometrics and Statistics, Elsevier, vol. 27(C), pages 1-15.
    2. Trucíos Maza, Carlos César & Mazzeu, João H. G. & Hallin, Marc & Hotta, Luiz Koodi & Pereira, Pedro L. Valls & Zevallos, Mauricio, 2019. "Forecasting conditional covariance matrices in high-dimensional time series: a general dynamic factor approach," Textos para discussão 505, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    3. Carlos Cesar Trucios-Maza & João H. G Mazzeu & Luis K. Hotta & Pedro L. Valls Pereira & Marc Hallin, 2019. "On the robustness of the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting," Working Papers ECARES 2019-32, ULB -- Universite Libre de Bruxelles.
    4. Matteo Barigozzi, 2023. "Quasi Maximum Likelihood Estimation of High-Dimensional Factor Models: A Critical Review," Papers 2303.11777, arXiv.org, revised May 2024.
    5. Liao, Gaoke & Li, Yanling & Wang, Mengxin, 2024. "Contagion network of idiosyncratic volatility: Does corporate environmental responsibility matter?," Energy Economics, Elsevier, vol. 129(C).
    6. Matteo Barigozzi & Marc Hallin, 2024. "The Dynamic, the Static, and the Weak factor models and the analysis of high-dimensional time series," Papers 2407.10653, arXiv.org.
    7. Matteo Barigozzi & Marc Hallin & Matteo Luciani & Paolo Zaffaroni, 2021. "Inferential Theory for Generalized Dynamic Factor Models," Working Papers ECARES 2021-20, ULB -- Universite Libre de Bruxelles.
    8. Marc Hallin & Carlos Trucíos, 2020. "Forecasting Value-at-Risk and Expected Shortfall in Large Portfolios: a General Dynamic Factor Approach," Working Papers ECARES 2020-50, ULB -- Universite Libre de Bruxelles.
    9. Gunawan, David & Kohn, Robert & Nott, David, 2021. "Variational Bayes approximation of factor stochastic volatility models," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1355-1375.
    10. Nummi, Patrik & Viitasaari, Lauri, 2024. "Necessary and sufficient conditions for continuity of hypercontractive processes and fields," Statistics & Probability Letters, Elsevier, vol. 208(C).
    11. Jianqing Fan & Ricardo Masini & Marcelo C. Medeiros, 2021. "Bridging factor and sparse models," Papers 2102.11341, arXiv.org, revised Sep 2022.
    12. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.
    13. Trucíos Maza, Carlos César & Mazzeu, João H. G. & Hotta, Luiz Koodi & Pereira, Pedro L. Valls & Hallin, Marc, 2020. "Robustness and the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting," Textos para discussão 521, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    14. Marc Hallin, 2022. "Manfred Deistler and the General-Dynamic-Factor-Model Approach to the Statistical Analysis of High-Dimensional Time Series," Econometrics, MDPI, vol. 10(4), pages 1-9, December.
    15. Matteo Barigozzi, 2023. "Asymptotic equivalence of Principal Components and Quasi Maximum Likelihood estimators in Large Approximate Factor Models," Papers 2307.09864, arXiv.org, revised Jun 2024.

  15. Campi, Mercedes & Dueñas, Marco & Barigozzi, Matteo & Fagiolo, Giorgio, 2018. "Intellectual property rights, imitation, and development. The effect on cross-border mergers and acquisitions," LSE Research Online Documents on Economics 90203, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Mercedes Campi & Alessandro Nuvolari, 2020. "Intellectual property rights and agricultural development: evidence from a worldwide index of IPRS in agriculture (1961-2018)," Documentos de trabajo del Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET) 2020-51, Universidad de Buenos Aires, Facultad de Ciencias Económicas, Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET).
    2. Bazel-Shoham, Ofra & Lee, Sang Mook & Ahammad, Mohammad Faisal & Tarba, Shlomo Y. & Alon, Ilan, 2023. "IP protection and ownership in cross-border acquisitions," International Business Review, Elsevier, vol. 32(3).
    3. Yan Yan & Jiatao Li & Jingjing Zhang, 2022. "Protecting intellectual property in foreign subsidiaries: An internal network defense perspective," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 53(9), pages 1924-1944, December.
    4. Gnangnon, Sèna Kimm, 2023. "Aid for Trade flows, Patent Rights Protection and Total Factor Productivity," EconStor Preprints 274650, ZBW - Leibniz Information Centre for Economics.

  16. Matteo Barigozzi & Lorenzo Trapani, 2017. "Sequential testing for structural stability in approximate factor models," Papers 1708.02786, arXiv.org, revised Mar 2020.

    Cited by:

    1. Matteo Barigozzi & Daniele Massacci, 2022. "Modelling Large Dimensional Datasets with Markov Switching Factor Models," Papers 2210.09828, arXiv.org, revised Dec 2024.
    2. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.
    3. Lorenzo Trapani & Emily Whitehouse, 2020. "Sequential monitoring for cointegrating regressions," Papers 2003.12182, arXiv.org.
    4. Xin-Bing Kong & Yong-Xin Liu & Long Yu & Peng Zhao, 2022. "Matrix Quantile Factor Model," Papers 2208.08693, arXiv.org, revised Aug 2024.

  17. Dueñas, Marco & Mastrandrea, Rossana & Barigozzi, Matteo & Fagiolo, Giorgio, 2017. "Spatio-temporal patterns of the international merger and acquisition network," LSE Research Online Documents on Economics 84092, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Campi, Mercedes & Dueñas, Marco & Barigozzi, Matteo & Fagiolo, Giorgio, 2018. "Intellectual property rights, imitation, and development. The effect on cross-border mergers and acquisitions," LSE Research Online Documents on Economics 90203, London School of Economics and Political Science, LSE Library.
    2. Brózda-Wilamek Dominika, 2023. "The global cross-border mergers and acquisitions network between 1990 and 2021," International Journal of Management and Economics, Warsaw School of Economics, Collegium of World Economy, vol. 59(4), pages 333-348, December.
    3. A. Baronchelli & T.E. Uberti, 2018. "Exports and FDI: comparing networks in the new millennium," Working Paper CRENoS 201813, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.

  18. Matteo Barigozzi & Matteo Luciani, 2017. "Common Factors, Trends, and Cycles in Large Datasets," Finance and Economics Discussion Series 2017-111, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Corona, Francisco & Poncela, Pilar, 2017. "Estimating non-stationary common factors : Implications for risk sharing," DES - Working Papers. Statistics and Econometrics. WS 24585, Universidad Carlos III de Madrid. Departamento de Estadística.

  19. Barigozzi, Matteo & Hallin, Marc, 2017. "A network analysis of the volatility of high-dimensionalfinancial series," LSE Research Online Documents on Economics 67456, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Zheng, Tingguo & Zhang, Hongyin & Ye, Shiqi, 2024. "Monetary policies on green financial markets: Evidence from a multi-moment connectedness network," Energy Economics, Elsevier, vol. 136(C).
    2. Niţoi, Mihai & Pochea, Maria Miruna, 2022. "The nexus between bank connectedness and investors’ sentiment," Finance Research Letters, Elsevier, vol. 44(C).
    3. Ahelegbey, Daniel Felix & Giudici, Paolo & Hashem, Shatha Qamhieh, 2021. "Network VAR models to measure financial contagion," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    4. Matteo Barigozzi & Christian T. Brownlees, 2013. "Nets: Network estimation for time series," Economics Working Papers 1391, Department of Economics and Business, Universitat Pompeu Fabra.
    5. Barigozzi, Matteo & Cho, Haeran & Fryzlewicz, Piotr, 2018. "Simultaneous multiple change-point and factor analysis for high-dimensional time series," Journal of Econometrics, Elsevier, vol. 206(1), pages 187-225.
    6. Jonas Krampe & Luca Margaritella, 2021. "Factor Models with Sparse VAR Idiosyncratic Components," Papers 2112.07149, arXiv.org, revised May 2022.
    7. Christian Gross & Pierre L. Siklos, 2018. "Analyzing Credit Risk Transmission to the Non-Financial Sector in Europe: A Network Approach," CQE Working Papers 7218, Center for Quantitative Economics (CQE), University of Muenster.
    8. Geraci, Marco Valerio & Gnabo, Jean-Yves, 2018. "Measuring Interconnectedness between Financial Institutions with Bayesian Time-Varying Vector Autoregressions," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(3), pages 1371-1390, June.
    9. Liao, Gaoke & Li, Yanling & Wang, Mengxin, 2024. "Contagion network of idiosyncratic volatility: Does corporate environmental responsibility matter?," Energy Economics, Elsevier, vol. 129(C).
    10. Rigana, Katerina & Wit, Ernst-Jan Camiel & Cook, Samantha, 2023. "A new way of measuring effects of financial crisis on contagion in currency markets," International Review of Financial Analysis, Elsevier, vol. 90(C).
    11. Hai-Chuan Xu & Fredj Jawadi & Jie Zhou & Wei-Xing Zhou, 2023. "Quantifying interconnectedness and centrality ranking among financial institutions with TVP-VAR framework," Empirical Economics, Springer, vol. 65(1), pages 93-110, July.
    12. Katerina Rigana & Ernst-Jan Camiel Wit & Samantha Cook, 2021. "Using Network-based Causal Inference to Detect the Sources of Contagion in the Currency Market," Papers 2112.13127, arXiv.org.
    13. Matteo Barigozzi & Marc Hallin & Stefano Soccorsi, 2019. "Time-Varying General Dynamic Factor Models and the Measurement of Financial Connectedness," Working Papers ECARES 2019-09, ULB -- Universite Libre de Bruxelles.
    14. Chen, Chuanglian & Zhou, Lichao & Sun, Chuanwang & Lin, Yuting, 2024. "Does oil future increase the network systemic risk of financial institutions in China?," Applied Energy, Elsevier, vol. 364(C).
    15. Raffaele Mattera & Philipp Otto, 2023. "Network log-ARCH models for forecasting stock market volatility," Papers 2303.11064, arXiv.org.
    16. Kumar, Sudarshan & Bansal, Avijit & Chakrabarti, Anindya S., 2019. "Ripples on financial networks," IIMA Working Papers WP 2019-10-01, Indian Institute of Management Ahmedabad, Research and Publication Department.
    17. Krampe, J. & Paparoditis, E. & Trenkler, C., 2023. "Structural inference in sparse high-dimensional vector autoregressions," Journal of Econometrics, Elsevier, vol. 234(1), pages 276-300.
    18. Miao, Ke & Phillips, Peter C.B. & Su, Liangjun, 2023. "High-dimensional VARs with common factors," Journal of Econometrics, Elsevier, vol. 233(1), pages 155-183.
    19. Etesami, Jalal & Habibnia, Ali & Kiyavash, Negar, 2017. "Econometric modeling of systemic risk: going beyond pairwise comparison and allowing for nonlinearity," LSE Research Online Documents on Economics 70769, London School of Economics and Political Science, LSE Library.
    20. Ge, Shuyi & Li, Shaoran & Linton, Oliver, 2023. "News-implied linkages and local dependency in the equity market," Journal of Econometrics, Elsevier, vol. 235(2), pages 779-815.
    21. Luca Barbaglia & Christophe Croux & Ines Wilms, 2017. "Volatility Spillovers and Heavy Tails: A Large t-Vector AutoRegressive Approach," Papers 1708.02073, arXiv.org.
    22. Ge, S., 2020. "Text-Based Linkages and Local Risk Spillovers in the Equity Market," Cambridge Working Papers in Economics 20115, Faculty of Economics, University of Cambridge.
    23. Yaya Su & Zhehao Huang & Benjamin M. Drakeford, 2019. "Monetary Policy, Industry Heterogeneity and Systemic Risk—Based on a High Dimensional Network Analysis," Sustainability, MDPI, vol. 11(22), pages 1-15, November.
    24. Tingguo Zheng & Hongyin Zhang & Shiqi Ye, 2024. "Monetary Policies on Green Financial Markets: Evidence from a Multi-Moment Connectedness Network," Papers 2405.02575, arXiv.org, revised Oct 2024.
    25. Jianqing Fan & Ricardo Masini & Marcelo C. Medeiros, 2021. "Bridging factor and sparse models," Papers 2102.11341, arXiv.org, revised Sep 2022.
    26. Dominik Bertsche & Ralf Brüggemann & Christian Kascha, 2023. "Directed graphs and variable selection in large vector autoregressive models," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(2), pages 223-246, March.
    27. Yong Tang & Jason Jie Xiong & Zi-Yang Jia & Yi-Cheng Zhang, 2018. "Complexities in Financial Network Topological Dynamics: Modeling of Emerging and Developed Stock Markets," Complexity, Hindawi, vol. 2018, pages 1-31, November.
    28. Herculano, Miguel C. & Lütkebohmert, Eva, 2023. "Investor sentiment and global economic conditions," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 134-152.
    29. Christis Katsouris, 2023. "Statistical Estimation for Covariance Structures with Tail Estimates using Nodewise Quantile Predictive Regression Models," Papers 2305.11282, arXiv.org, revised Jul 2023.
    30. Sudarshan Kumar & Tiziana Di Matteo & Anindya S. Chakrabarti, 2020. "Disentangling shock diffusion on complex networks: Identification through graph planarity," Papers 2001.01518, arXiv.org.
    31. Groß, Christian, 2019. "Analyzing credit risk transmission to the non-financial sector in Europe: a network approach," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203645, Verein für Socialpolitik / German Economic Association.
    32. Jonas Krampe & Luca Margaritella, 2024. "Global bank network connectedness revisited: What is common, idiosyncratic and when?," Papers 2402.02482, arXiv.org.
    33. Naeem, Muhammad Abubakr & Anwer, Zaheer & Khan, Ashraf & Paltrinieri, Andrea, 2024. "Do market conditions affect interconnectedness pattern of socially responsible equities?," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 611-630.
    34. Matteo Barigozzi & Marc Hallin & Stefano Soccorsi, 2017. "Identification of Global and National Shocks in International Financial Markets via General Dynamic Factor Models," Working Papers ECARES ECARES 2017-10, ULB -- Universite Libre de Bruxelles.
    35. Daniel Felix Ahelegbey & Luis Carvalho & Eric D. Kolaczyk, 2020. "A Bayesian Covariance Graph And Latent Position Model For Multivariate Financial Time Series," DEM Working Papers Series 181, University of Pavia, Department of Economics and Management.
    36. Tian, Sihua & Li, Shaofang & Gu, Qinen, 2023. "Measurement and contagion modelling of systemic risk in China's financial sectors: Evidence for functional data analysis and complex network," International Review of Financial Analysis, Elsevier, vol. 90(C).
    37. Pagnottoni, Paolo, 2023. "Superhighways and roads of multivariate time series shock transmission: Application to cryptocurrency, carbon emission and energy prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    38. Baek, Changryong & Gates, Katheleen M. & Leinwand, Benjamin & Pipiras, Vladas, 2021. "Two sample tests for high-dimensional autocovariances," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).

  20. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2016. "Non-Stationary Dynamic Factor Models for Large Datasets," Finance and Economics Discussion Series 2016-024, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Di Iorio, Francesca & Fachin, Stefano, 2021. "Evaluating restricted common factor models for non-stationary data," Econometrics and Statistics, Elsevier, vol. 17(C), pages 64-75.
    2. Alessi, Lucia & Kerssenfischer, Mark, 2016. "The response of asset prices to monetary policy shocks: stronger than thought," Working Paper Series 1967, European Central Bank.
    3. Theodore Panagiotidis & Panagiotis Printzis, 2019. "What is the Investment Loss due to Uncertainty?," GreeSE – Hellenic Observatory Papers on Greece and Southeast Europe 138, Hellenic Observatory, LSE.
    4. Cristina Conflitti and Matteo Luciani, 2019. "Oil Price Pass-through into Core Inflation," The Energy Journal, International Association for Energy Economics, vol. 0(Number 6).
    5. Panagiotidis, Theodore & Printzis, Panagiotis, 2021. "Investment and uncertainty: Are large firms different from small ones?," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 302-317.
    6. Jongrim Ha & M. Ayhan Kose & Franziska Ohnsorge, 2021. "One-stop source: A global database of inflation," CAMA Working Papers 2021-59, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    7. Corona, Francisco & Poncela, Pilar, 2017. "Estimating non-stationary common factors : Implications for risk sharing," DES - Working Papers. Statistics and Econometrics. WS 24585, Universidad Carlos III de Madrid. Departamento de Estadística.
    8. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2016. "Dynamic Factor Models, Cointegration, and Error Correction Mechanisms," Finance and Economics Discussion Series 2016-018, Board of Governors of the Federal Reserve System (U.S.).
    9. Hsiang-Hsi Liu & Chien-Kuo Tseng, 2022. "Common Components in Co-integrated System and Its Estimation and Application: Evidence from Five Stock Markets in Asia-Pacific Chinese Region," Bulletin of Applied Economics, Risk Market Journals, vol. 9(2), pages 101-121.
    10. Dalibor Stevanovic & Rachidi Kotchoni & Maxime Leroux, 2017. "Forecasting economic activity in data-rich environment," CIRANO Working Papers 2017s-05, CIRANO.
    11. Cimadomo, Jacopo & Giannone, Domenico & Lenza, Michele & Monti, Francesca & Sokol, Andrej, 2022. "Nowcasting with large Bayesian vector autoregressions," Journal of Econometrics, Elsevier, vol. 231(2), pages 500-519.
    12. Smeekes, Stephan & Wijler, Etiënne, 2016. "Macroeconomic Forecasting Using Penalized Regression Methods," Research Memorandum 039, Maastricht University, Graduate School of Business and Economics (GSBE).
    13. Francisco Corona & Graciela González-Farías & Pedro Orraca, 2017. "A dynamic factor model for the Mexican economy: are common trends useful when predicting economic activity?," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 26(1), pages 1-35, December.
    14. Martina Hengge & Seton Leonard, 2017. "Factor Models for Non-Stationary Series: Estimates of Monthly U.S. GDP," IHEID Working Papers 13-2017, Economics Section, The Graduate Institute of International Studies.
    15. Matteo Barigozzi & Matteo Luciani, 2017. "Common Factors, Trends, and Cycles in Large Datasets," Finance and Economics Discussion Series 2017-111, Board of Governors of the Federal Reserve System (U.S.).
    16. Ergemen, Yunus Emre, 2023. "Parametric estimation of long memory in factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1483-1499.

  21. Barigozzi, Matteo & Moneta, Alessio, 2016. "Identifying the independent sources of consumption variation," LSE Research Online Documents on Economics 60979, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Christophe Faugère, 2021. "Connectalism: A new paradigm for human choice," Systems Research and Behavioral Science, Wiley Blackwell, vol. 38(6), pages 866-889, November.
    2. Matteo Barigozzi, 2023. "Quasi Maximum Likelihood Estimation of High-Dimensional Factor Models: A Critical Review," Papers 2303.11777, arXiv.org, revised May 2024.
    3. Tommaso Ciarli & Andre Lorentz & Marco Valente & Mario Savona, 2017. "Structural Changes and Growth Regimes," SPRU Working Paper Series 2017-12, SPRU - Science Policy Research Unit, University of Sussex Business School.
    4. Liqiong Chen & Antonio F. Galvao & Suyong Song, 2021. "Quantile Regression with Generated Regressors," Econometrics, MDPI, vol. 9(2), pages 1-35, April.

  22. Matteo Barigozzi & Marc Hallin, 2015. "Networks, Dynamic Factors, and the Volatility Analysis of High-Dimensional Financial Series," Papers 1510.05118, arXiv.org, revised Jul 2016.

    Cited by:

    1. Affinito, Massimiliano & Franco Pozzolo, Alberto, 2017. "The interbank network across the global financial crisis: Evidence from Italy," Journal of Banking & Finance, Elsevier, vol. 80(C), pages 90-107.
    2. Barigozzi, Matteo & Hallin, Marc, 2020. "Generalized dynamic factor models and volatilities: Consistency, rates, and prediction intervals," Journal of Econometrics, Elsevier, vol. 216(1), pages 4-34.

  23. Matteo Barigozzi & Marc Hallin, 2015. "Generalized Dynamic Factor Models and Volatilities: Estimation and Forecasting," Working Papers ECARES ECARES 2015-22, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Trucíos Maza, Carlos César & Mazzeu, João H. G. & Hallin, Marc & Hotta, Luiz Koodi & Pereira, Pedro L. Valls & Zevallos, Mauricio, 2019. "Forecasting conditional covariance matrices in high-dimensional time series: a general dynamic factor approach," Textos para discussão 505, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    2. Trucíos Maza, Carlos César & Hotta, Luiz Koodi & Pereira, Pedro L. Valls, 2018. "On the robustness of the principal volatility components," Textos para discussão 474, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    3. Carlos Cesar Trucios-Maza & João H. G Mazzeu & Luis K. Hotta & Pedro L. Valls Pereira & Marc Hallin, 2019. "On the robustness of the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting," Working Papers ECARES 2019-32, ULB -- Universite Libre de Bruxelles.
    4. Cipollini, Fabrizio & Gallo, Giampiero M., 2019. "Modeling Euro STOXX 50 volatility with common and market-specific components," Econometrics and Statistics, Elsevier, vol. 11(C), pages 22-42.
    5. Matteo Barigozzi & Marc Hallin, 2024. "The Dynamic, the Static, and the Weak factor models and the analysis of high-dimensional time series," Papers 2407.10653, arXiv.org.
    6. Duc Thi Luu, 2022. "Portfolio Correlations in the Bank-Firm Credit Market of Japan," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 529-569, August.
    7. Bontempi, Maria Elena & Mammi, Irene, 2012. "A strategy to reduce the count of moment conditions in panel data GMM," MPRA Paper 40720, University Library of Munich, Germany.
    8. Kumar, Sudarshan & Bansal, Avijit & Chakrabarti, Anindya S., 2019. "Ripples on financial networks," IIMA Working Papers WP 2019-10-01, Indian Institute of Management Ahmedabad, Research and Publication Department.
    9. Lucchetti, Riccardo & Venetis, Ioannis A., 2020. "A replication of "A quasi-maximum likelihood approach for large, approximate dynamic factor models" (Review of Economics and Statistics, 2012)," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 14, pages 1-14.
    10. Jari Miettinen & Markus Matilainen & Klaus Nordhausen & Sara Taskinen, 2020. "Extracting Conditionally Heteroskedastic Components using Independent Component Analysis," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(2), pages 293-311, March.
    11. Xinyu Song, 2019. "Large Volatility Matrix Prediction with High-Frequency Data," Papers 1907.01196, arXiv.org, revised Sep 2019.
    12. Valentina Aprigliano & Lorenzo Bencivelli, 2013. "Ita-coin: a new coincident indicator for the Italian economy," Temi di discussione (Economic working papers) 935, Bank of Italy, Economic Research and International Relations Area.
    13. Matteo Barigozzi & Marc Hallin & Matteo Luciani & Paolo Zaffaroni, 2021. "Inferential Theory for Generalized Dynamic Factor Models," Working Papers ECARES 2021-20, ULB -- Universite Libre de Bruxelles.
    14. Ma, Yan-Ran & Zhang, Dayong & Ji, Qiang & Pan, Jiaofeng, 2019. "Spillovers between oil and stock returns in the US energy sector: Does idiosyncratic information matter?," Energy Economics, Elsevier, vol. 81(C), pages 536-544.
    15. Kris Boudt & Dries Cornilly & Tim Verdonck, 2019. "Nearest Comoment Estimation With Unobserved Factors," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 19/970, Ghent University, Faculty of Economics and Business Administration.
    16. Xisong Jin & Francisco Nadal De Simone, 2012. "An Early-warning and Dynamic Forecasting Framework of Default Probabilities for the Macroprudential Policy Indicators Arsenal," BCL working papers 75, Central Bank of Luxembourg.
    17. Barigozzi, Matteo & Hallin, Marc, 2020. "Generalized dynamic factor models and volatilities: Consistency, rates, and prediction intervals," Journal of Econometrics, Elsevier, vol. 216(1), pages 4-34.
    18. Jianqing Fan & Ricardo Masini & Marcelo C. Medeiros, 2021. "Bridging factor and sparse models," Papers 2102.11341, arXiv.org, revised Sep 2022.
    19. Andreou, Elena & Ghysels, Eric, 2021. "Predicting the VIX and the volatility risk premium: The role of short-run funding spreads Volatility Factors," Journal of Econometrics, Elsevier, vol. 220(2), pages 366-398.
    20. Tingting Lan & Liuguo Shao & Hua Zhang & Caijun Yuan, 2023. "The impact of pandemic on dynamic volatility spillover network of international stock markets," Empirical Economics, Springer, vol. 65(5), pages 2115-2144, November.
    21. Marc Hallin, 2022. "Manfred Deistler and the General Dynamic Factor Model Approach to the Analysis of High-Dimensional Time Series," Working Papers ECARES 2022-30, ULB -- Universite Libre de Bruxelles.
    22. Osman Dou{g}an & Raffaele Mattera & Philipp Otto & Suleyman Tac{s}p{i}nar, 2024. "A Dynamic Spatiotemporal and Network ARCH Model with Common Factors," Papers 2410.16526, arXiv.org.
    23. Matteo Barigozzi & Marc Hallin, 2015. "Networks, Dynamic Factors, and the Volatility Analysis of High-Dimensional Financial Series," Papers 1510.05118, arXiv.org, revised Jul 2016.
    24. Sudarshan Kumar & Tiziana Di Matteo & Anindya S. Chakrabarti, 2020. "Disentangling shock diffusion on complex networks: Identification through graph planarity," Papers 2001.01518, arXiv.org.
    25. Gaoke Liao & Peng Hou & Xiaoyan Shen & Khaldoon Albitar, 2021. "The impact of economic policy uncertainty on stock returns: The role of corporate environmental responsibility engagement," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4386-4392, July.
    26. Trucíos Maza, Carlos César & Mazzeu, João H. G. & Hotta, Luiz Koodi & Pereira, Pedro L. Valls & Hallin, Marc, 2020. "Robustness and the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting," Textos para discussão 521, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    27. Matteo Barigozzi & Marc Hallin & Stefano Soccorsi, 2017. "Identification of Global and National Shocks in International Financial Markets via General Dynamic Factor Models," Working Papers ECARES ECARES 2017-10, ULB -- Universite Libre de Bruxelles.
    28. Marc Hallin, 2022. "Manfred Deistler and the General-Dynamic-Factor-Model Approach to the Statistical Analysis of High-Dimensional Time Series," Econometrics, MDPI, vol. 10(4), pages 1-9, December.
    29. Krupskii, Pavel & Joe, Harry, 2020. "Flexible copula models with dynamic dependence and application to financial data," Econometrics and Statistics, Elsevier, vol. 16(C), pages 148-167.
    30. Gong, Xiao-Li & Liu, Xi-Hua & Xiong, Xiong & Zhang, Wei, 2020. "Research on China's financial systemic risk contagion under jump and heavy-tailed risk," International Review of Financial Analysis, Elsevier, vol. 72(C).
    31. Kim, Donggyu & Fan, Jianqing, 2019. "Factor GARCH-Itô models for high-frequency data with application to large volatility matrix prediction," Journal of Econometrics, Elsevier, vol. 208(2), pages 395-417.
    32. Lübbers, Johannes & Posch, Peter N., 2016. "Commodities' common factor: An empirical assessment of the markets' drivers," Journal of Commodity Markets, Elsevier, vol. 4(1), pages 28-40.

  24. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2014. "Dynamic Factor Models, Cointegration and Error Correction Mechanisms," Working Papers ECARES ECARES 2014-14, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2016. "Non-Stationary Dynamic Factor Models for Large Datasets," Finance and Economics Discussion Series 2016-024, Board of Governors of the Federal Reserve System (U.S.).
    2. Corona, Francisco & Poncela, Pilar, 2017. "Estimating non-stationary common factors : Implications for risk sharing," DES - Working Papers. Statistics and Econometrics. WS 24585, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Soccorsi, Stefano, 2016. "Measuring nonfundamentalness for structural VARs," Journal of Economic Dynamics and Control, Elsevier, vol. 71(C), pages 86-101.
    4. Smeekes, Stephan & Wijler, Etiënne, 2016. "Macroeconomic Forecasting Using Penalized Regression Methods," Research Memorandum 039, Maastricht University, Graduate School of Business and Economics (GSBE).
    5. Martina Hengge & Seton Leonard, 2017. "Factor Models for Non-Stationary Series: Estimates of Monthly U.S. GDP," IHEID Working Papers 13-2017, Economics Section, The Graduate Institute of International Studies.
    6. Carlo A. Favero & Alessandro Melone, 2019. "Asset Pricing vs Asset Expected Returning in Factor Models," Working Papers 651, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    7. Matteo Barigozzi & Matteo Luciani, 2017. "Common Factors, Trends, and Cycles in Large Datasets," Finance and Economics Discussion Series 2017-111, Board of Governors of the Federal Reserve System (U.S.).

  25. Matteo Barigozzi & Marc Hallin, 2014. "Generalized Dynamic Factor Models and Volatilities. Recovering the Market Volatility Shocks," Working Papers ECARES ECARES 2014-52, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Hallin, Marc & Trucíos, Carlos, 2023. "Forecasting value-at-risk and expected shortfall in large portfolios: A general dynamic factor model approach," Econometrics and Statistics, Elsevier, vol. 27(C), pages 1-15.
    2. Liu, Yixuan & Kirch, Claudia & Lee, Jeong Eun & Meyer, Renate, 2024. "A nonparametrically corrected likelihood for Bayesian spectral analysis of multivariate time series," Computational Statistics & Data Analysis, Elsevier, vol. 199(C).
    3. Bouri, Elie & Gabauer, David & Gupta, Rangan & Tiwari, Aviral Kumar, 2021. "Volatility connectedness of major cryptocurrencies: The role of investor happiness," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
    4. Trucíos Maza, Carlos César & Mazzeu, João H. G. & Hallin, Marc & Hotta, Luiz Koodi & Pereira, Pedro L. Valls & Zevallos, Mauricio, 2019. "Forecasting conditional covariance matrices in high-dimensional time series: a general dynamic factor approach," Textos para discussão 505, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    5. Ma, Yan-Ran & Ji, Qiang & Wu, Fei & Pan, Jiaofeng, 2021. "Financialization, idiosyncratic information and commodity co-movements," Energy Economics, Elsevier, vol. 94(C).
    6. Chen, Liang & Dolado, Juan J. & Gonzalo, Jesús, 2020. "Quantile Factor Models," IZA Discussion Papers 13870, Institute of Labor Economics (IZA).
    7. Trucíos Maza, Carlos César & Hotta, Luiz Koodi & Pereira, Pedro L. Valls, 2018. "On the robustness of the principal volatility components," Textos para discussão 474, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    8. Carlos Cesar Trucios-Maza & João H. G Mazzeu & Luis K. Hotta & Pedro L. Valls Pereira & Marc Hallin, 2019. "On the robustness of the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting," Working Papers ECARES 2019-32, ULB -- Universite Libre de Bruxelles.
    9. Matteo Barigozzi & Christian T. Brownlees, 2013. "Nets: Network estimation for time series," Economics Working Papers 1391, Department of Economics and Business, Universitat Pompeu Fabra.
    10. Cipollini, Fabrizio & Gallo, Giampiero M., 2019. "Modeling Euro STOXX 50 volatility with common and market-specific components," Econometrics and Statistics, Elsevier, vol. 11(C), pages 22-42.
    11. Ergemen, Yunus Emre & Rodríguez-Caballero, C. Vladimir, 2023. "Estimation of a dynamic multi-level factor model with possible long-range dependence," International Journal of Forecasting, Elsevier, vol. 39(1), pages 405-430.
    12. Ruofan Yu & Rong Chen & Han Xiao & Yuefeng Han, 2024. "Dynamic Matrix Factor Models for High Dimensional Time Series," Papers 2407.05624, arXiv.org.
    13. Yunus Emre Ergemen, 2022. "Parametric Estimation of Long Memory in Factor Models," CREATES Research Papers 2022-10, Department of Economics and Business Economics, Aarhus University.
    14. Pourkhanali, Armin & Tafakori, Laleh & Bee, Marco, 2023. "Forecasting Value-at-Risk using functional volatility incorporating an exogenous effect," International Review of Financial Analysis, Elsevier, vol. 89(C).
    15. Lucchetti, Riccardo & Venetis, Ioannis A., 2020. "A replication of "A quasi-maximum likelihood approach for large, approximate dynamic factor models" (Review of Economics and Statistics, 2012)," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 14, pages 1-14.
    16. Jari Miettinen & Markus Matilainen & Klaus Nordhausen & Sara Taskinen, 2020. "Extracting Conditionally Heteroskedastic Components using Independent Component Analysis," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(2), pages 293-311, March.
    17. Kwangmin Jung & Donggyu Kim & Seunghyeon Yu, 2021. "Next Generation Models for Portfolio Risk Management: An Approach Using Financial Big Data," Papers 2102.12783, arXiv.org, revised Feb 2022.
    18. Matteo Barigozzi & Marc Hallin, 2015. "Generalized Dynamic Factor Models and Volatilities: Estimation and Forecasting," Working Papers ECARES ECARES 2015-22, ULB -- Universite Libre de Bruxelles.
    19. Xinyu Song, 2019. "Large Volatility Matrix Prediction with High-Frequency Data," Papers 1907.01196, arXiv.org, revised Sep 2019.
    20. Ma, Yan-Ran & Zhang, Dayong & Ji, Qiang & Pan, Jiaofeng, 2019. "Spillovers between oil and stock returns in the US energy sector: Does idiosyncratic information matter?," Energy Economics, Elsevier, vol. 81(C), pages 536-544.
    21. Kris Boudt & Dries Cornilly & Tim Verdonck, 2019. "Nearest Comoment Estimation With Unobserved Factors," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 19/970, Ghent University, Faculty of Economics and Business Administration.
    22. Barigozzi, Matteo & Hallin, Marc, 2020. "Generalized dynamic factor models and volatilities: Consistency, rates, and prediction intervals," Journal of Econometrics, Elsevier, vol. 216(1), pages 4-34.
    23. Jianqing Fan & Ricardo Masini & Marcelo C. Medeiros, 2021. "Bridging factor and sparse models," Papers 2102.11341, arXiv.org, revised Sep 2022.
    24. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.
    25. Demetrescu, Matei & Hacıoğlu Hoke, Sinem, 2019. "Predictive regressions under asymmetric loss: Factor augmentation and model selection," International Journal of Forecasting, Elsevier, vol. 35(1), pages 80-99.
    26. Barigozzi, Matteo & Hallin, Marc, 2017. "A network analysis of the volatility of high-dimensionalfinancial series," LSE Research Online Documents on Economics 67456, London School of Economics and Political Science, LSE Library.
    27. Marc Hallin, 2022. "Manfred Deistler and the General Dynamic Factor Model Approach to the Analysis of High-Dimensional Time Series," Working Papers ECARES 2022-30, ULB -- Universite Libre de Bruxelles.
    28. Osman Dou{g}an & Raffaele Mattera & Philipp Otto & Suleyman Tac{s}p{i}nar, 2024. "A Dynamic Spatiotemporal and Network ARCH Model with Common Factors," Papers 2410.16526, arXiv.org.
    29. Matteo Barigozzi & Marc Hallin, 2015. "Networks, Dynamic Factors, and the Volatility Analysis of High-Dimensional Financial Series," Papers 1510.05118, arXiv.org, revised Jul 2016.
    30. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2021. "Uncertainty and Forecastability of Regional Output Growth in the United Kingdom: Evidence from Machine Learning," Working Papers 202111, University of Pretoria, Department of Economics.
    31. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2022. "Uncertainty and forecastability of regional output growth in the UK: Evidence from machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1049-1064, September.
    32. Trucíos Maza, Carlos César & Mazzeu, João H. G. & Hotta, Luiz Koodi & Pereira, Pedro L. Valls & Hallin, Marc, 2020. "Robustness and the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting," Textos para discussão 521, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    33. Matteo Barigozzi & Marc Hallin & Stefano Soccorsi, 2017. "Identification of Global and National Shocks in International Financial Markets via General Dynamic Factor Models," Working Papers ECARES ECARES 2017-10, ULB -- Universite Libre de Bruxelles.
    34. Marc Hallin, 2022. "Manfred Deistler and the General-Dynamic-Factor-Model Approach to the Statistical Analysis of High-Dimensional Time Series," Econometrics, MDPI, vol. 10(4), pages 1-9, December.
    35. Gong, Xiao-Li & Liu, Xi-Hua & Xiong, Xiong & Zhang, Wei, 2020. "Research on China's financial systemic risk contagion under jump and heavy-tailed risk," International Review of Financial Analysis, Elsevier, vol. 72(C).
    36. Kim, Donggyu & Fan, Jianqing, 2019. "Factor GARCH-Itô models for high-frequency data with application to large volatility matrix prediction," Journal of Econometrics, Elsevier, vol. 208(2), pages 395-417.
    37. Karmous, Aida & Boubaker, Heni & Belkacem, Lotfi, 2019. "A dynamic factor model with stylized facts to forecast volatility for an optimal portfolio," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    38. Lübbers, Johannes & Posch, Peter N., 2016. "Commodities' common factor: An empirical assessment of the markets' drivers," Journal of Commodity Markets, Elsevier, vol. 4(1), pages 28-40.
    39. Ergemen, Yunus Emre, 2023. "Parametric estimation of long memory in factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1483-1499.

  26. Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2014. "Disentangling Systematic and Idiosyncratic Dynamics in Panels of Volatility Measures," Econometrics Working Papers Archive 2014_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.

    Cited by:

    1. Harry Vander Elst, 2015. "FloGARCH : Realizing long memory and asymmetries in returns volatility," Working Paper Research 280, National Bank of Belgium.
    2. Cipollini, Fabrizio & Gallo, Giampiero M. & Otranto, Edoardo, 2021. "Realized volatility forecasting: Robustness to measurement errors," International Journal of Forecasting, Elsevier, vol. 37(1), pages 44-57.
    3. Alessandra Amendola & Vincenzo Candila & Fabrizio Cipollini & Giampiero M. Gallo, 2020. "Doubly Multiplicative Error Models with Long- and Short-run Components," Papers 2006.03458, arXiv.org.
    4. Matteo Barigozzi & Marc Hallin, 2014. "Generalized Dynamic Factor Models and Volatilities. Recovering the Market Volatility Shocks," Working Papers ECARES ECARES 2014-52, ULB -- Universite Libre de Bruxelles.
    5. KALNINA, Ilze & TEWOU, Kokouvi, 2015. "Cross-sectional dependence in idiosyncratic volatility," Cahiers de recherche 2015-04, Universite de Montreal, Departement de sciences economiques.
    6. Marko Mlikota, 2022. "Cross-Sectional Dynamics Under Network Structure: Theory and Macroeconomic Applications," Papers 2211.13610, arXiv.org, revised Sep 2024.
    7. Zhang, Xingmin & Zhang, Shuai & Lu, Liping, 2022. "The banking instability and climate change: Evidence from China," Energy Economics, Elsevier, vol. 106(C).
    8. Matteo Barigozzi & Christian T. Brownlees, 2013. "Nets: Network estimation for time series," Economics Working Papers 1391, Department of Economics and Business, Universitat Pompeu Fabra.
    9. Cipollini, Fabrizio & Gallo, Giampiero M., 2019. "Modeling Euro STOXX 50 volatility with common and market-specific components," Econometrics and Statistics, Elsevier, vol. 11(C), pages 22-42.
    10. Duc Thi Luu, 2022. "Portfolio Correlations in the Bank-Firm Credit Market of Japan," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 529-569, August.
    11. Philip L. H. Yu & W. K. Li & F. C. Ng, 2017. "The Generalized Conditional Autoregressive Wishart Model for Multivariate Realized Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 513-527, October.
    12. Alketa Bejko & Etleva Peta & Belinda Xarba, 2015. "The Evaluation of the Drafting Process of Regional’s Development Strategies in Albania. the Research on Gjirokastra’s Region," European Journal of Interdisciplinary Studies Articles, Revistia Research and Publishing, vol. 1, ejis_v1_i.
    13. Pietro Coretto & Michele La Rocca & Giuseppe Storti, 2020. "Improving Many Volatility Forecasts Using Cross-Sectional Volatility Clusters," JRFM, MDPI, vol. 13(4), pages 1-23, March.
    14. Bernard Herskovic & Bryan Kelly & Hanno Lustig & Stijn Van Nieuwerburgh, 2013. "Firm Volatility in Granular Networks," NBER Working Papers 19466, National Bureau of Economic Research, Inc.
    15. Matteo Barigozzi & Marc Hallin, 2015. "Generalized Dynamic Factor Models and Volatilities: Estimation and Forecasting," Working Papers ECARES ECARES 2015-22, ULB -- Universite Libre de Bruxelles.
    16. Jozef Barun'ik & Tobias Kley, 2015. "Quantile Coherency: A General Measure for Dependence between Cyclical Economic Variables," Papers 1510.06946, arXiv.org, revised Dec 2018.
    17. Giampiero M. Gallo & Edoardo Otranto, 2018. "Combining sharp and smooth transitions in volatility dynamics: a fuzzy regime approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(3), pages 549-573, April.
    18. Fabrizio Cipollini & Giampiero M. Gallo, 2021. "Multiplicative Error Models: 20 years on," Papers 2107.05923, arXiv.org.
    19. Paul G. Egan & Anthony J. Leddin, 2016. "Examining Monetary Policy Transmission in the People's Republic of China–Structural Change Models with a Monetary Policy Index," Asian Development Review, MIT Press, vol. 33(1), pages 74-110, March.
    20. Matteo Barigozzi & Marc Hallin, 2015. "Networks, Dynamic Factors, and the Volatility Analysis of High-Dimensional Financial Series," Papers 1510.05118, arXiv.org, revised Jul 2016.
    21. Matteo Barigozzi & Marc Hallin & Stefano Soccorsi, 2017. "Identification of Global and National Shocks in International Financial Markets via General Dynamic Factor Models," Working Papers ECARES ECARES 2017-10, ULB -- Universite Libre de Bruxelles.
    22. Francisco Blasques & Enzo D'Innocenzo & Siem Jan Koopman, 2021. "Common and Idiosyncratic Conditional Volatility Factors: Theory and Empirical Evidence," Tinbergen Institute Discussion Papers 21-057/III, Tinbergen Institute.
    23. Le, Trung Hai & Do, Hung Xuan & Nguyen, Duc Khuong & Sensoy, Ahmet, 2021. "Covid-19 pandemic and tail-dependency networks of financial assets," Finance Research Letters, Elsevier, vol. 38(C).

  27. Matteo Barigozzi & Christian Brownlees, 2013. "Nets: Network Estimation for Time Series," Working Papers 723, Barcelona School of Economics.

    Cited by:

    1. Gomez-Gonzalez, Jose E. & Uribe, Jorge M. & Valencia, Oscar, 2022. "Risk Spillovers between Global Corporations and Latin American Sovereigns: Global Factors Matter," IDB Publications (Working Papers) 12236, Inter-American Development Bank.
    2. Liao, Yin & Pan, Zheyao, 2022. "Extreme risk connectedness among global major financial institutions: Links to globalization and emerging market fear," Pacific-Basin Finance Journal, Elsevier, vol. 76(C).
    3. Billio, Monica & Caporin, Massimiliano & Panzica, Roberto & Pelizzon, Loriana, 2023. "The impact of network connectivity on factor exposures, asset pricing, and portfolio diversification," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 196-223.
    4. Mert Demirer & Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2018. "Estimating global bank network connectedness," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(1), pages 1-15, January.
    5. Matteo Iacopini & Luca Rossini, 2019. "Bayesian nonparametric graphical models for time-varying parameters VAR," Papers 1906.02140, arXiv.org.
    6. Abbassi, Puriya & Brownlees, Christian & Hans, Christina & Podlich, Natalia, 2016. "Credit risk interconnectedness: What does the market really know?," Discussion Papers 09/2016, Deutsche Bundesbank.
    7. Ben Craig & Martín Saldías, 2016. "Spatial Dependence and Data-Driven Networks of International Banks," IMF Working Papers 2016/184, International Monetary Fund.
    8. Boyao Wu & Difang Huang & Muzi Chen, 2024. "Estimating Contagion Mechanism in Global Equity Market with Time-Zone Effect," Papers 2404.04335, arXiv.org.
    9. Mengting Li & Qifa Xu & Cuixia Jiang & Yezheng Liu, 2024. "The role of long‐ and short‐run correlation networks in international portfolio selection," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(3), pages 3147-3176, July.
    10. Xu, Qifa & Li, Mengting & Jiang, Cuixia, 2021. "Network-augmented time-varying parametric portfolio selection: Evidence from the Chinese stock market," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    11. Paolo Giudici & Laura Parisi, 2015. "Modeling Systemic Risk with Correlated Stochastic Processes," DEM Working Papers Series 110, University of Pavia, Department of Economics and Management.
    12. Rodolfo C. Moura & Márcio P. Laurini, 2021. "Spillovers and jumps in global markets: A comparative analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5997-6013, October.
    13. Alin Marius Andries & Steven Ongena & Nicu Sprincean & Radu Tunaru, 2020. "Risk Spillovers and Interconnectedness between Systemically Important Institutions," Swiss Finance Institute Research Paper Series 20-40, Swiss Finance Institute.
    14. M. Hakan Eratalay; Evgenii V. Vladimirov, 2018. "Mapping The Stocks In Micex: Who Is Central To The Moscow Stock Exchange?," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 111, Faculty of Economics and Business Administration, University of Tartu (Estonia).
    15. Badics, Milan Csaba & Huszar, Zsuzsa R. & Kotro, Balazs B., 2023. "The impact of crisis periods and monetary decisions of the Fed and the ECB on the sovereign yield curve network," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    16. René Böheim & Philipp Stöllinger, 2020. "Decomposition of the Gender Wage Gap using the LASSO Estimator," Economics working papers 2020-03, Department of Economics, Johannes Kepler University Linz, Austria.
    17. Sun, Jiaojiao & Zhang, Chen & Zhu, Jing & Zhao, Jingsong, 2024. "Risk spillover mechanism among commercial banks and FinTech institutions throughout public health emergencies," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
    18. Carlo Campajola & Fabrizio Lillo & Daniele Tantari, 2019. "Unveiling the relation between herding and liquidity with trader lead-lag networks," Papers 1909.10807, arXiv.org, revised Mar 2020.
    19. Foglia, Matteo & Angelini, Eliana, 2020. "From me to you: Measuring connectedness between Eurozone financial institutions," Research in International Business and Finance, Elsevier, vol. 54(C).
    20. P. Giudici & A. Spelta, 2016. "Graphical Network Models for International Financial Flows," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 128-138, January.
    21. Monica Billio & Roberto Casarin & Luca Rossini, 2016. "Bayesian nonparametric sparse VAR models," Papers 1608.02740, arXiv.org, revised Oct 2018.
    22. Ariana Paola Cortés Ángel & Mustafa Hakan Eratalay, 2022. "Deep diving into the S&P Europe 350 index network and its reaction to COVID-19," Journal of Computational Social Science, Springer, vol. 5(2), pages 1343-1408, November.
    23. Andrea Bastianin & Chiara Casoli & Marzio Galeotti, 2023. "The connectedness of Energy Transition Metals," Working Papers 2023.11, Fondazione Eni Enrico Mattei.
    24. Zhang, Xingmin & Zhang, Shuai & Lu, Liping, 2022. "The banking instability and climate change: Evidence from China," Energy Economics, Elsevier, vol. 106(C).
    25. Natalia Bailey & Sean Holly & M. Hashem Pesaran, 2016. "A Two‐Stage Approach to Spatio‐Temporal Analysis with Strong and Weak Cross‐Sectional Dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 249-280, January.
    26. Paolo Giudici & Laura Parisi, 2016. "Bail in or Bail out? The Atlante example from a systemic risk perspective," DEM Working Papers Series 124, University of Pavia, Department of Economics and Management.
    27. Jonas Krampe & Luca Margaritella, 2021. "Factor Models with Sparse VAR Idiosyncratic Components," Papers 2112.07149, arXiv.org, revised May 2022.
    28. Daniel Felix Ahelegbey & Paolo Giudici, 2020. "NetVIX - A Network Volatility Index of Financial Markets," DEM Working Papers Series 192, University of Pavia, Department of Economics and Management.
    29. Agosto, Arianna & Ahelegbey, Daniel Felix & Giudici, Paolo, 2020. "Tree Networks to assess Financial Contagion," MPRA Paper 107066, University Library of Munich, Germany.
    30. Kamil Yilmaz, 2018. "Bank Volatility Connectedness in South East Asia," Koç University-TUSIAD Economic Research Forum Working Papers 1807, Koc University-TUSIAD Economic Research Forum.
    31. Hai-Chuan Xu & Fredj Jawadi & Jie Zhou & Wei-Xing Zhou, 2023. "Quantifying interconnectedness and centrality ranking among financial institutions with TVP-VAR framework," Empirical Economics, Springer, vol. 65(1), pages 93-110, July.
    32. Mikhail Stolbov & Daniil Parfenov, 2023. "Credit risk linkages in the international banking network, 2000–2019," Risk Management, Palgrave Macmillan, vol. 25(3), pages 1-38, September.
    33. Matteo Barigozzi & Marc Hallin & Stefano Soccorsi, 2019. "Time-Varying General Dynamic Factor Models and the Measurement of Financial Connectedness," Working Papers ECARES 2019-09, ULB -- Universite Libre de Bruxelles.
    34. Sullivan HUE & Yannick LUCOTTE & Sessi TOKPAVI, 2018. "Measuring Network Systemic Risk Contributions: A Leave-one-out Approach," LEO Working Papers / DR LEO 2608, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    35. Zitian Gao & Yihao Xiao, 2024. "Enhancing Startup Success Predictions in Venture Capital: A GraphRAG Augmented Multivariate Time Series Method," Papers 2408.09420, arXiv.org, revised Dec 2024.
    36. Muñoz Mendoza, Jorge A. & Veloso Ramos, Carmen L. & Delgado Fuentealba, Carlos L. & Araya Gómez, Iván E. & Sepúlveda Yelpo, Sandra M. & Cornejo Saavedra, Edinson E., 2024. "Connectedness in the global banking market network: Implications for risk management and financial policy," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    37. Ahelegbey, Daniel Felix & Billio, Monica & Casarin, Roberto, 2024. "Modeling Turning Points in the Global Equity Market," Econometrics and Statistics, Elsevier, vol. 30(C), pages 60-75.
    38. Vidal-Llana, Xenxo & Uribe, Jorge M. & Guillén, Montserrat, 2023. "European stock market volatility connectedness: The role of country and sector membership," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    39. Niels Gillmann & Ostap Okhrin, 2023. "Adaptive local VAR for dynamic economic policy uncertainty spillover," Papers 2302.02808, arXiv.org.
    40. Sullivan HUE & Yannick LUCOTTE & Sessi TOKPAVI, 2018. "Measuring network systemic risk contributions: A leave-one-out approach," LEO Working Papers / DR LEO 2708, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    41. Yu Chen & Jie Hu & Weiping Zhang, 2020. "Too Connected to Fail? Evidence from a Chinese Financial Risk Spillover Network," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 28(6), pages 78-100, November.
    42. Dahlqvist, Carl-Henrik & Gnabo, Jean-Yves, 2018. "Effective network inference through multivariate information transfer estimation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 376-394.
    43. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto, 2019. "Estimation and model-based combination of causality networks among large US banks and insurance companies," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 1-21.
    44. Marcelo C. Medeiros & Eduardo F. Mendes, 2015. "l1-Regularization of High-Dimensional Time-Series Models with Flexible Innovations," Textos para discussão 636, Department of Economics PUC-Rio (Brazil).
    45. Chuliá, Helena & Muñoz-Mendoza, Jorge A. & Uribe, Jorge M., 2023. "Energy firms in emerging markets: Systemic risk and diversification opportunities," Emerging Markets Review, Elsevier, vol. 56(C).
    46. Kamil Yilmaz, 2014. "Volatility Connectedness of Bank Stocks Across the Atlantic," Koç University-TUSIAD Economic Research Forum Working Papers 1402, Koc University-TUSIAD Economic Research Forum.
    47. I�aki Aldasoro & Ignazio Angeloni, 2015. "Input-output-based measures of systemic importance," Quantitative Finance, Taylor & Francis Journals, vol. 15(4), pages 589-606, April.
    48. Krampe, J. & Paparoditis, E. & Trenkler, C., 2023. "Structural inference in sparse high-dimensional vector autoregressions," Journal of Econometrics, Elsevier, vol. 234(1), pages 276-300.
    49. Boyao Wu & Difang Huang & Muzi Chen, 2023. "Estimating contagion mechanism in global equity market with time‐zone effect," Financial Management, Financial Management Association International, vol. 52(3), pages 543-572, September.
    50. Miao, Ke & Phillips, Peter C.B. & Su, Liangjun, 2023. "High-dimensional VARs with common factors," Journal of Econometrics, Elsevier, vol. 233(1), pages 155-183.
    51. Ge, Shuyi & Li, Shaoran & Linton, Oliver, 2023. "News-implied linkages and local dependency in the equity market," Journal of Econometrics, Elsevier, vol. 235(2), pages 779-815.
    52. Ivan Alves & Stijn Ferrari & Pietro Franchini & Jean-Cyprien Heam & Pavol Jurca & Sam Langfield & Sebastiano Laviola & Franka Liedorp & Antonio Sánchez & Santiago Tavolaro & Guillaume Vuillemey, 2013. "The structure and resilience of the European interbank market," ESRB Occasional Paper Series 03, European Systemic Risk Board.
    53. Medeiros, Marcelo C. & Mendes, Eduardo F., 2016. "ℓ1-regularization of high-dimensional time-series models with non-Gaussian and heteroskedastic errors," Journal of Econometrics, Elsevier, vol. 191(1), pages 255-271.
    54. Paolo Giudici & Laura Parisi, 2016. "CoRisk: measuring systemic risk through default probability contagion," DEM Working Papers Series 116, University of Pavia, Department of Economics and Management.
    55. Siva R Venna & Satya Katragadda & Vijay Raghavan & Raju Gottumukkala, 2021. "River Stage Forecasting using Enhanced Partial Correlation Graph," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(12), pages 4111-4126, September.
    56. Ge, S., 2020. "Text-Based Linkages and Local Risk Spillovers in the Equity Market," Cambridge Working Papers in Economics 20115, Faculty of Economics, University of Cambridge.
    57. Sessi Tokpavi, 2013. "Testing for the Systemically Important Financial Institutions: a Conditional Approach," EconomiX Working Papers 2013-27, University of Paris Nanterre, EconomiX.
    58. Jianqing Fan & Ricardo Masini & Marcelo C. Medeiros, 2021. "Bridging factor and sparse models," Papers 2102.11341, arXiv.org, revised Sep 2022.
    59. Daniel Felix Ahelegbey & Paolo Giudici, 2020. "Market Risk, Connectedness and Turbulence: A Comparison of 21st Century Financial Crises," DEM Working Papers Series 188, University of Pavia, Department of Economics and Management.
    60. Foglia, Matteo & Addi, Abdelhamid & Wang, Gang-Jin & Angelini, Eliana, 2022. "Bearish Vs Bullish risk network: A Eurozone financial system analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    61. Dominik Bertsche & Ralf Brüggemann & Christian Kascha, 2023. "Directed graphs and variable selection in large vector autoregressive models," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(2), pages 223-246, March.
    62. Alain Hecq & Marie Ternes & Ines Wilms, 2021. "Hierarchical Regularizers for Mixed-Frequency Vector Autoregressions," Papers 2102.11780, arXiv.org, revised Mar 2022.
    63. Mengting Li & Qifa Xu & Cuixia Jiang & Qinna Zhao, 2023. "The role of tail network topological characteristic in portfolio selection: A TNA‐PMC model," International Review of Finance, International Review of Finance Ltd., vol. 23(1), pages 37-57, March.
    64. Bettendorf, Timo & Heinlein, Reinhold, 2019. "Connectedness between G10 currencies: Searching for the causal structure," Discussion Papers 06/2019, Deutsche Bundesbank.
    65. Ouyang, Zisheng & Zhou, Xuewei & Wang, Gang-jin & Liu, Shuwen & Lu, Min, 2024. "Multilayer networks in the frequency domain: Measuring volatility connectedness among Chinese financial institutions," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 909-928.
    66. Emanuele De Meo & Giacomo Tizzanini, 2021. "GDP‐network CoVaR: A tool for assessing growth‐at‐risk," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 50(2), July.
    67. Paola Cerchiello & Paolo Giudici, 2014. "Conditional graphical models for systemic risk measurement," DEM Working Papers Series 087, University of Pavia, Department of Economics and Management.
    68. Mustafa Hakan Eratalay & Ariana Paola Cortés Ángel, 2022. "The Impact of ESG Ratings on the Systemic Risk of European Blue-Chip Firms," JRFM, MDPI, vol. 15(4), pages 1-41, March.
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    72. Brownlees, Christian & Hans, Christina & Nualart, Eulalia, 2021. "Bank credit risk networks: Evidence from the Eurozone," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 585-599.
    73. Daniela Scidá, 2023. "Structural VAR and financial networks: A minimum distance approach to spatial modeling," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(1), pages 49-68, January.
    74. Chuliá, Helena & Estévez, Marc & Uribe, Jorge M., 2023. "Systemic political risk," Economic Modelling, Elsevier, vol. 125(C).
    75. Anufriev, Mikhail & Panchenko, Valentyn, 2015. "Connecting the dots: Econometric methods for uncovering networks with an application to the Australian financial institutions," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 241-255.
    76. Muñoz Mendoza, Jorge A. & Ferreira, Guillermo & Márquez Sanders, Vicente A., 2023. "Liquidity spillovers in the global stock markets: Lessons for risk management," Global Finance Journal, Elsevier, vol. 58(C).
    77. Jonas Krampe & Luca Margaritella, 2024. "Global bank network connectedness revisited: What is common, idiosyncratic and when?," Papers 2402.02482, arXiv.org.
    78. Guðmundsson, Guðmundur Stefán & Brownlees, Christian, 2021. "Detecting groups in large vector autoregressions," Journal of Econometrics, Elsevier, vol. 225(1), pages 2-26.
    79. Daniel Felix Ahelegbey & Luis Carvalho & Eric D. Kolaczyk, 2020. "A Bayesian Covariance Graph And Latent Position Model For Multivariate Financial Time Series," DEM Working Papers Series 181, University of Pavia, Department of Economics and Management.
    80. Christian Brownlees & Eulàlia Nualart & Yucheng Sun, 2018. "Realized networks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 986-1006, November.
    81. Dallakyan, Aramayis & Kim, Rakheon & Pourahmadi, Mohsen, 2022. "Time series graphical lasso and sparse VAR estimation," Computational Statistics & Data Analysis, Elsevier, vol. 176(C).
    82. Paolo Giudici & Peter Sarlin & Alessandro Spelta, 2016. "The multivariate nature of systemic risk: direct and common exposures," DEM Working Papers Series 118, University of Pavia, Department of Economics and Management.
    83. Chabé-Ferret, Sylvain & Reynaud, Arnaud & Tène, Eva, 2021. "Water Quality, Policy Diffusion Effects and Farmers’ Behavior," TSE Working Papers 21-1229, Toulouse School of Economics (TSE).

  28. Barigozzi, Matteo & Conti, Antonio & Luciani, Matteo, 2012. "Do Euro area countries respond asymmetrically to the common monetary policy?," LSE Research Online Documents on Economics 43344, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Corsetti, G. & Duarte, J. B. & Mann, S., 2018. "One Money, Many Markets - A Factor Model Approach to Monetary Policy in the Euro Area with High-Frequency Identification," Cambridge Working Papers in Economics 1816, Faculty of Economics, University of Cambridge.
    2. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2016. "Non-Stationary Dynamic Factor Models for Large Datasets," Finance and Economics Discussion Series 2016-024, Board of Governors of the Federal Reserve System (U.S.).
    3. Christophe Blot & Jerôme Creel & Bruno Ducoudré & Xavier Timeau, 2015. "Back to fiscal consolidation in Europe and its dual tradeoff : now of later, through spending cuts or tax hikes," Documents de Travail de l'OFCE 2015-11, Observatoire Francais des Conjonctures Economiques (OFCE).
    4. Kerssenfischer, Mark, 2017. "The effects of US monetary policy shocks: Applying external instrument identification to a dynamic factor model," Discussion Papers 08/2017, Deutsche Bundesbank.
    5. Bagnai, Alberto & Granville, Brigitte & Mongeau Ospina, Christian A., 2017. "Withdrawal of Italy from the euro area: Stochastic simulations of a structural macroeconometric model," Economic Modelling, Elsevier, vol. 64(C), pages 524-538.
    6. Potjagailo, Galina & Wolters, Maik H, 2020. "Global financial cycles since 1880," Bank of England working papers 867, Bank of England.
    7. Badinger, Harald & Schiman, Stefan, 2020. "Measuring Monetary Policy with Residual Sign Restrictions at Known Shock Dates," Department of Economics Working Paper Series 300, WU Vienna University of Economics and Business.
    8. Martin Mandler & Michael Scharnagl & Ute Volz, 2022. "Heterogeneity in Euro Area Monetary Policy Transmission: Results from a Large Multicountry BVAR Model," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(2-3), pages 627-649, March.
    9. Jackson, Laura E. & Owyang, Michael T. & Zubairy, Sarah, 2018. "Debt and stabilization policy: Evidence from a Euro Area FAVAR," Journal of Economic Dynamics and Control, Elsevier, vol. 93(C), pages 67-91.
    10. Georgiadis, Georgios & Jančoková, Martina, 2017. "Financial globalisation, monetary policy spillovers and macro-modelling: tales from 1001 shocks," Working Paper Series 2082, European Central Bank.
    11. Gabe de Bondt, 2017. "Confidence and monetary policy transmission," EcoMod2017 10197, EcoMod.
    12. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2016. "Dynamic Factor Models, Cointegration, and Error Correction Mechanisms," Finance and Economics Discussion Series 2016-018, Board of Governors of the Federal Reserve System (U.S.).
    13. Mattia Guerini & Duc Thi Luu & Mauro Napoletano, 2019. "Synchronization Patterns in the European Union," GREDEG Working Papers 2019-30, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    14. Giancarlo Corsetti & Joao B. Duarte & Samuel Mann, 2018. "One Money, Many Markets," Discussion Papers 1805, Centre for Macroeconomics (CFM).
    15. Stefano Neri & Tiziano Ropele, 2015. "The macroeconomic effects of the sovereign debt crisis in the euro area," Temi di discussione (Economic working papers) 1007, Bank of Italy, Economic Research and International Relations Area.
    16. Mario Forni & Luca Gambetti & marco Lippi & Luca Sala, 2020. "Common Components Structural VARs," Center for Economic Research (RECent) 147, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    17. Roy, Ripon & Bashar, Omar H.N.M. & Bhattacharya, Prasad Sankar, 2023. "The cross-industry effects of monetary policy: New evidence from Bangladesh," Economic Modelling, Elsevier, vol. 127(C).
    18. Akbari Dehbaghi, Simin & Arman, Seyed Aziz & Ahangari, Majid, 2020. "The Impact of Domestic and Foreign Monetary Policy on Iran\'s economy: Global Modeling," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 15(2), pages 151-180, April.
    19. Jung, Alexander & Carcel Villanova, Hector, 2020. "The empirical properties of euro area M3, 1980-2017," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 37-49.
    20. Florian Huber & Michael Pfarrhofer & Philipp Piribauer, 2020. "A multi‐country dynamic factor model with stochastic volatility for euro area business cycle analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 911-926, September.
    21. Matteo Barigozzi & Claudio Lissona & Lorenzo Tonni, 2024. "Large datasets for the Euro Area and its member countries and the dynamic effects of the common monetary policy," Papers 2410.05082, arXiv.org.
    22. Andrea Colabella, 2019. "Do the ECB’s monetary policies benefit emerging market economies? A GVAR analysis on the crisis and post-crisis period," Temi di discussione (Economic working papers) 1207, Bank of Italy, Economic Research and International Relations Area.
    23. Destefanis, Sergio & Fragetta, Matteo & Gasteiger, Emanuel, 2021. "Does one size fit all in the Euro Area? Some counterfactual evidence," ECON WPS - Working Papers in Economic Theory and Policy 05/2019, TU Wien, Institute of Statistics and Mathematical Methods in Economics, Economics Research Unit, revised 2021.
    24. Marco Flaccadoro, 2022. "Exchange rate pass-through in small, open, commodity-exporting economies: lessons from Canada," Temi di discussione (Economic working papers) 1368, Bank of Italy, Economic Research and International Relations Area.
    25. Pestova, Anna, 2020. "“Credit view” on monetary policy in Russia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 57, pages 72-88.
    26. Michael Pfarrhofer & Anna Stelzer, 2019. "High-frequency and heteroskedasticity identification in multicountry models: Revisiting spillovers of monetary shocks," Papers 1912.03158, arXiv.org, revised Dec 2024.
    27. Christophe Blot & Marion Cochard & Jérôme Creel & Bruno Ducoudre & Danielle Schweisguth & Xavier Timbeau, 2014. "Fiscal Consolidation, Public Debt and Output Dynamics in the Euro Area: lessons from a simple model with time-varying fiscal multipliers," Post-Print hal-03429902, HAL.
    28. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2020. "Cointegration and Error Correction Mechanisms for Singular Stochastic Vectors," Econometrics, MDPI, vol. 8(1), pages 1-23, February.
    29. Christophe Blot & Jérôme Creel & Paul Hubert & Fabien Labondance, 2016. "The impact of ECB policies on Euro area investment," SciencePo Working papers Main hal-03459319, HAL.
    30. Karim Triki, 2016. "Expenditure-based Consolidation: Experiences and Outcomes – Workshop proceedings," European Economy - Discussion Papers 026, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    31. Potjagailo, Galina, 2016. "Spillover effects from euro area monetary policy across the EU: A factor-augmented VAR approach," Kiel Working Papers 2033, Kiel Institute for the World Economy (IfW Kiel).
    32. von Borstel, Julia & Eickmeier, Sandra & Krippner, Leo, 2015. "The interest rate pass-through in the euro area during the sovereign debt crisis," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113035, Verein für Socialpolitik / German Economic Association.
    33. Max Hanisch, 2017. "US Monetary Policy and the Euro Area," Discussion Papers of DIW Berlin 1701, DIW Berlin, German Institute for Economic Research.
    34. Hristov, Nikolay & Huelsewig, Oliver & Siemsen, Thomas & Wollmershaeuser, Timo, 2019. "Restoring euro area monetary transmission: Which role for government bond rates?," Munich Reprints in Economics 78269, University of Munich, Department of Economics.
    35. Norhana Endut & James Morley & Pao-Lin Tien, 2015. "The Changing Transmission Mechanism of U.S. Monetary Policy," Discussion Papers 2015-03, School of Economics, The University of New South Wales.
    36. Juho Koistinen & Bernd Funovits, 2022. "Estimation of Impulse-Response Functions with Dynamic Factor Models: A New Parametrization," Papers 2202.00310, arXiv.org, revised Feb 2022.
    37. Zhu, Bing & Betzinger, Michael & Sebastian, Steffen, 2017. "Housing market stability, mortgage market structure, and monetary policy: Evidence from the euro area," Journal of Housing Economics, Elsevier, vol. 37(C), pages 1-21.
    38. Alberto Caruso, 2016. "The Impact of Macroeconomic News on the Euro-Dollar Exchange Rate," Working Papers ECARES ECARES 2016-32, ULB -- Universite Libre de Bruxelles.
    39. Corsetti, Giancarlo & Duarte, Joao B. & Mann, Samuel, 2020. "One Money, Many Markets: Monetary Transmission and Housing Financing in the Euro Area," CEPR Discussion Papers 14968, C.E.P.R. Discussion Papers.
    40. Cavallo, Antonella & Ribba, Antonio, 2015. "Common macroeconomic shocks and business cycle fluctuations in Euro area countries," International Review of Economics & Finance, Elsevier, vol. 38(C), pages 377-392.
    41. Thomas Lux & Duc Thi Luu & Boyan Yanovski, 2020. "An analysis of systemic risk in worldwide economic sentiment indices," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 47(4), pages 909-928, November.
    42. Ayla OguÅŸ Binatli & Niloufer Sohrabji, 2019. "Monetary Policy Transmission in the Euro Zone," Athens Journal of Business & Economics, Athens Institute for Education and Research (ATINER), vol. 5(1), pages 79-92, January.
    43. Conti, Antonio M., 2021. "Resurrecting the Phillips Curve in Low-Inflation Times," Economic Modelling, Elsevier, vol. 96(C), pages 172-195.
    44. Hanisch, Max, 2019. "US monetary policy and the euro area," Journal of Banking & Finance, Elsevier, vol. 100(C), pages 77-96.
    45. Xing, Xiaoyun & Wang, Mingsong & Wang, Yougui & Stanley, H. Eugene, 2020. "Credit creation under multiple banking regulations: The impact of balance sheet diversity on money supply," Economic Modelling, Elsevier, vol. 91(C), pages 720-735.
    46. Simona Hašková & Marek Vochozka, 2018. "Duality in Cyclical Trends in European Union Confirmed," SAGE Open, , vol. 8(1), pages 21582440177, January.
    47. Lukas Berend & Jan Pruser, 2024. "The Transmission of Monetary Policy via Common Cycles in the Euro Area," Papers 2410.05741, arXiv.org, revised Nov 2024.
    48. Hanisch, Max & Kempa, Bernd, 2017. "The international transmission channels of US supply and demand shocks: Evidence from a non-stationary dynamic factor model for the G7 countries," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 70-88.
    49. Theron Shumba & Sophia Mukorera, 2023. "Monetary Policy Implications on Macroeconomic Performance in the Common Monetary Area: A Panel-SVAR Framework," Economies, MDPI, vol. 11(5), pages 1-18, May.
    50. Petrovska Magdalena & Tonovska Jasna & Nikolov Miso & Sulejmani Artan, 2022. "Evaluating Monetary Policy Effectiveness in North Macedonia: Evidence from a Bayesian Favar Framework," South East European Journal of Economics and Business, Sciendo, vol. 17(2), pages 67-82, December.
    51. Emter, Lorenz & Setzer, Ralph & Zorell, Nico & Moura, Afonso S., 2024. "Monetary policy and growth-at-risk: the role of institutional quality," Working Paper Series 2989, European Central Bank.
    52. Potjagailo, Galina, 2017. "Spillover effects from Euro area monetary policy across Europe: A factor-augmented VAR approach," Journal of International Money and Finance, Elsevier, vol. 72(C), pages 127-147.
    53. Hanisch, Max, 2017. "The effectiveness of conventional and unconventional monetary policy: Evidence from a structural dynamic factor model for Japan," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 110-134.
    54. Neri, Stefano & Nobili, Andrea & Conti, Antonio M., 2017. "Low inflation and monetary policy in the euro area," Working Paper Series 2005, European Central Bank.
    55. Barigozzi, Matteo & Lippi, Marco & Luciani, Matteo, 2021. "Large-dimensional Dynamic Factor Models: Estimation of Impulse–Response Functions with I(1) cointegrated factors," Journal of Econometrics, Elsevier, vol. 221(2), pages 455-482.
    56. Ute Volz & Martin Mandler & Michael Scharnagl, 2016. "Heterogeneity in Euro Area Monetary Policy Transmission: Results from a large Multi-Country BVAR," EcoMod2016 9609, EcoMod.
    57. Krokida, Styliani-Iris & Makrychoriti, Panagiota & Spyrou, Spyros, 2020. "Monetary policy and herd behavior: International evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 170(C), pages 386-417.
    58. Andrea Colabella, 2021. "Do ECB's Monetary Policies Benefit EMEs? A GVAR Analysis on the Global Financial and Sovereign Debt Crises and Postcrises Period," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(2), pages 472-494, April.
    59. Matteo Farnè & Angelos T. Vouldis, 2021. "Banks’ business models in the euro area: a cluster analysis in high dimensions," Annals of Operations Research, Springer, vol. 305(1), pages 23-57, October.
    60. Geiger, Martin & Gründler, Daniel & Scharler, Johann, 2023. "Monetary policy shocks and consumer expectations in the euro area," Journal of International Economics, Elsevier, vol. 140(C).

  29. Matteo Barigozzi & Alessio Moneta, 2011. "The Rank of a System of Engel Curves. How Many Common Factors?," Papers on Economics and Evolution 2011-01, Philipps University Marburg, Department of Geography.

    Cited by:

    1. Andreas Chai, 2017. "Tackling Keynes’ question: a look back on 15 years of Learning To Consume," Journal of Evolutionary Economics, Springer, vol. 27(2), pages 251-271, April.

  30. Matteo Barigozzi & Antonio M. Conti & Matteo Luciani, 2011. "Measuring Euro Area Monetary Policy Transmission in a Structural Dynamic Factor Model," European Economy - Economic Papers 2008 - 2015 441, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.

    Cited by:

    1. Catherine Prettner & Klaus Prettner, 2012. "After Two Decades of Integration: How Interdependent are Eastern European Economies and the Euro Area?," Department of Economics Working Papers wuwp138, Vienna University of Economics and Business, Department of Economics.
    2. Konstantins Benkovskis & Andrejs Bessonovs & Martin Feldkircher & Julia Wörz, 2011. "The Transmission of Euro Area Monetary Shocks to the Czech Republic, Poland and Hungary: Evidence from a FAVAR Model," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 3, pages 8-36.
    3. Bhattacharya, Rudrani & Tripathi, Shruti & Chowdhury, Sahana Roy, 2019. "Financial structure, institutional quality and monetary policy transmission: A Meta-Analysis," Working Papers 19/274, National Institute of Public Finance and Policy.
    4. Prettner, Catherine & Prettner, Klaus, 2014. "How interdependent are Eastern European economies and the Euro area?," University of Göttingen Working Papers in Economics 187, University of Goettingen, Department of Economics.
    5. Efrem Castelnuovo, 2016. "Monetary policy shocks and Cholesky VARs: an assessment for the Euro area," Empirical Economics, Springer, vol. 50(2), pages 383-414, March.

  31. Matteo Barigozzi & Antonio Conti, 2010. "On the Sources of Euro Area Money Demand Stability. A Time-Varying Cointegration Analysis," Working Papers ECARES ECARES 2010-022, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. De Santis, Roberto A. & Favero, Carlo A. & Roffia, Barbara, 2008. "Euro area money demand and international portfolio allocation: a contribution to assessing risks to price stability," Working Paper Series 926, European Central Bank.
    2. Ralph Setzer & Guntram B. Wolff, 2009. "Money demand in the euro area: new insights from disaggregated data," European Economy - Economic Papers 2008 - 2015 373, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    3. Chen-Huan Shieh & Shou-Hsiang Liu & Chung-Ching Lee, 2017. "How Stable is the Money Demand in Taiwan?," International Journal of Economics and Financial Research, Academic Research Publishing Group, vol. 3(5), pages 54-64, 05-2017.

  32. Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2010. "Disentangling Systematic and Idiosyncratic Risk for Large Panels of Assets," Econometrics Working Papers Archive wp2010_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Herskovic, Bernard & Kelly, Bryan & Lustig, Hanno & Van Nieuwerburgh, Stijn, 2016. "The common factor in idiosyncratic volatility: Quantitative asset pricing implications," Journal of Financial Economics, Elsevier, vol. 119(2), pages 249-283.
    2. Fady Barsoum, 2013. "The Effects of Monetary Policy Shocks on a Panel of Stock Market Volatilities: A Factor-Augmented Bayesian VAR Approach," Working Paper Series of the Department of Economics, University of Konstanz 2013-15, Department of Economics, University of Konstanz.
    3. Bollerslev, Tim & Todorov, Viktor & Li, Sophia Zhengzi, 2013. "Jump tails, extreme dependencies, and the distribution of stock returns," Journal of Econometrics, Elsevier, vol. 172(2), pages 307-324.
    4. Matteo Luciani & David Veredas, 2012. "A model for vast panels of volatilities," Working Papers 1230, Banco de España.
    5. Bernard Herskovic & Bryan Kelly & Hanno Lustig & Stijn Van Nieuwerburgh, 2013. "Firm Volatility in Granular Networks," NBER Working Papers 19466, National Bureau of Economic Research, Inc.

  33. Matteo Barigozzi & Giorgio Fagiolo & Giuseppe Mangioni, 2010. "Identifying the Community Structure of the International-Trade Multi Network," LEM Papers Series 2010/15, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

    Cited by:

    1. Yuichi Ikeda & Hiroshi Iyetomi, 2018. "Trade Network Reconstruction and Simulation with Changes in Trade Policy," Papers 1806.00605, arXiv.org.
    2. Sun, Mei & Li, Juan & Gao, Cuixia & Han, Dun, 2017. "Identifying regime shifts in the US electricity market based on price fluctuations," Applied Energy, Elsevier, vol. 194(C), pages 658-666.
    3. Michela Chessa & Arnaud Persenda & Dominique Torre, 2023. "Brexit and Canadadvent: An application of graphs and hypergraphs to recent international trade agreements," Post-Print hal-04194464, HAL.
    4. Rodrigo Mesa-Arango & Badri Narayanan & Satish V. Ukkusuri, 2019. "The Impact of International Crises on Maritime Transportation Based Global Value Chains," Networks and Spatial Economics, Springer, vol. 19(2), pages 381-408, June.
    5. Ehsan Ardjmand & William A. Young II & Najat E. Almasarwah, 2021. "Detecting Community Structures Within Complex Networks Using a Discrete Unconscious Search Algorithm," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 12(2), pages 15-32, April.
    6. Nicole Palan & Nadia Simoes & Nuno Crespo, 2021. "Measuring fifty years of trade globalisation," The World Economy, Wiley Blackwell, vol. 44(6), pages 1859-1884, June.
    7. Giorgio Fagiolo & Tiziano Squartini & Diego Garlaschelli, 2011. "Null Models of Economic Networks: The Case of the World Trade Web," LEM Papers Series 2011/26, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    8. Hao, Xiaoqing & An, Haizhong & Jiang, Meihui & Sun, Xiaoqi, 2024. "Supply shock propagation in the multi-layer network of global steel product chain: Additive effect of trade and production," Resources Policy, Elsevier, vol. 89(C).
    9. Zhong, Weiqiong & An, Haizhong & Shen, Lei & Fang, Wei & Gao, Xiangyun & Dong, Di, 2017. "The roles of countries in the international fossil fuel trade: An emergy and network analysis," Energy Policy, Elsevier, vol. 100(C), pages 365-376.
    10. Nobi, Ashadun & Lee, Tae Ho & Lee, Jae Woo, 2020. "Structure of trade flow networks for world commodities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    11. Yuichi Ikeda & Hiroshi Iyetomi, 2018. "Trade network reconstruction and simulation with changes in trade policy," Evolutionary and Institutional Economics Review, Springer, vol. 15(2), pages 495-513, December.
    12. Fu, Xin & Yang, Yu & Dong, Wen & Wang, Changjian & Liu, Yi, 2017. "Spatial structure, inequality and trading community of renewable energy networks: A comparative study of solar and hydro energy product trades," Energy Policy, Elsevier, vol. 106(C), pages 22-31.
    13. Hoppe, K. & Rodgers, G.J., 2015. "A microscopic study of the fitness-dependent topology of the world trade network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 64-74.
    14. Stefania Vitali & Stefano Battiston, 2013. "The Community Structure of the Global Corporate Network," Papers 1301.2363, arXiv.org.
    15. Adelaide Baronchelli & Teodora Erika Uberti, 2021. "International Economic Integration: Comparing Exports and FDI Networks in the New Millennium," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 13(11), pages 1-30, November.
    16. Paolo Bartesaghi & Gian Paolo Clemente & Rosanna Grassi, 2020. "Community structure in the World Trade Network based on communicability distances," Papers 2001.06356, arXiv.org, revised Jul 2020.
    17. IKEDA Yuichi & AOYAMA Hideaki & IYETOMI Hiroshi & MIZUNO Takayuki & OHNISHI Takaaki & SAKAMOTO Yohei & WATANABE Tsutomu, 2016. "Econophysics Point of View of Trade Liberalization: Community dynamics, synchronization, and controllability as example of collective motions," Discussion papers 16026, Research Institute of Economy, Trade and Industry (RIETI).
    18. Takayuki Mizuno & Takaaki Ohnishi & Tsutomu Watanabe, 2015. "Structure of global buyer-supplier networks and its implications for conflict minerals regulations," UTokyo Price Project Working Paper Series 053, University of Tokyo, Graduate School of Economics.
    19. Gao, Cuixia & Sun, Mei & Shen, Bo, 2015. "Features and evolution of international fossil energy trade relationships: A weighted multilayer network analysis," Applied Energy, Elsevier, vol. 156(C), pages 542-554.
    20. Suhua Ou & Qingshan Yang & Jian Liu, 2024. "The global production pattern of the semiconductor industry: an empirical research based on trade network," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
    21. Jalili, Mahdi, 2017. "Spike phase synchronization in multiplex cortical neural networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 325-333.
    22. Kyle F Davis & Paolo D'Odorico & Francesco Laio & Luca Ridolfi, 2013. "Global Spatio-Temporal Patterns in Human Migration: A Complex Network Perspective," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-8, January.
    23. Fraňková, Eva & Fousek, Jan & Kala, Lukáš & Labohý, Jan, 2014. "Transaction network analysis for studying Local Exchange Trading Systems (LETS): Research potentials and limitations," Ecological Economics, Elsevier, vol. 107(C), pages 266-275.
    24. Lovrić, Marko & Da Re, Riccardo & Vidale, Enrico & Pettenella, Davide & Mavsar, Robert, 2018. "Social network analysis as a tool for the analysis of international trade of wood and non-wood forest products," Forest Policy and Economics, Elsevier, vol. 86(C), pages 45-66.
    25. Xia, Qifan & Du, Debin & Cao, Wanpeng & Li, Xiya, 2023. "Who is the core? Reveal the heterogeneity of global rare earth trade structure from the perspective of industrial chain," Resources Policy, Elsevier, vol. 82(C).
    26. Yang, Yu & Poon, Jessie P.H. & Liu, Yi & Bagchi-Sen, Sharmistha, 2015. "Small and flat worlds: A complex network analysis of international trade in crude oil," Energy, Elsevier, vol. 93(P1), pages 534-543.
    27. Nicolò Musmeci & Vincenzo Nicosia & Tomaso Aste & Tiziana Di Matteo & Vito Latora, 2017. "The Multiplex Dependency Structure of Financial Markets," Complexity, Hindawi, vol. 2017, pages 1-13, September.
    28. Hao, Xiaoqing & An, Haizhong, 2022. "Comparative study on transmission mechanism of supply shortage risk in the international trade of iron ore, pig iron and crude steel," Resources Policy, Elsevier, vol. 79(C).
    29. Juan de Lucio & Raúl Mínguez & Asier Minondo & Francisco Requena, 2014. "Networks and the Dynamics of Firms' Export Portfolio: Evidence for Mexico," Working Papers 2014003, The University of Sheffield, Department of Economics.
    30. Takayuki Mizuno & Takaaki Ohnishi & Tsutomu Watanabe, 2015. "Structure of global buyer-supplier networks and its implications for conflict minerals regulations," CARF F-Series CARF-F-362, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    31. Zhu, Bo & Liu, Jiahao & Lin, Renda & Chevallier, Julien, 2021. "Cross-border systemic risk spillovers in the global oil system: Does the oil trade pattern matter?," Energy Economics, Elsevier, vol. 101(C).
    32. A. Baronchelli & T.E. Uberti, 2018. "Exports and FDI: comparing networks in the new millennium," Working Paper CRENoS 201813, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    33. Russo, Margherita & Alboni, Fabrizio & Sanginés, Jorge Carreto & De Domenico, Manlio & Mangioni, Giuseppe & Righi, Simone & Simonazzi, Annamaria, 2023. "Regionalisation and cross-region integration. Twin dynamics in the automotive international trade networks," Structural Change and Economic Dynamics, Elsevier, vol. 67(C), pages 98-114.
    34. Julian Maluck & Reik V Donner, 2015. "A Network of Networks Perspective on Global Trade," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-24, July.
    35. Zhong, Weiqiong & An, Haizhong & Gao, Xiangyun & Sun, Xiaoqi, 2014. "The evolution of communities in the international oil trade network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 42-52.
    36. Yuichi Ikeda, 2020. "An Interacting Agent Model of Economic Crisis," Papers 2001.11843, arXiv.org.
    37. Marco Dueñas & Giorgio Fagiolo, 2013. "Modeling the International-Trade Network: a gravity approach," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 155-178, April.
    38. Yujing Wang & Fu Ren & Ruoxin Zhu & Qingyun Du, 2020. "An Exploratory Analysis of Networked and Spatial Characteristics of International Natural Resource Trades (2000–2016)," Sustainability, MDPI, vol. 12(18), pages 1-34, September.
    39. Matteo Barigozzi & Marc Hallin, 2015. "Networks, Dynamic Factors, and the Volatility Analysis of High-Dimensional Financial Series," Papers 1510.05118, arXiv.org, revised Jul 2016.
    40. Carlo Piccardi, 2011. "Finding and Testing Network Communities by Lumped Markov Chains," PLOS ONE, Public Library of Science, vol. 6(11), pages 1-13, November.
    41. Jayles, Bertrand & Cheong, Siew Ann & Herrmann, Hans J., 2022. "Modeling the resilience of social networks to lockdowns regarding the dynamics of meetings," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 602(C).
    42. Wu, Jianshe & Li, Xiaoxiao & Jiao, Licheng & Wang, Xiaohua & Sun, Bo, 2013. "Minimum spanning trees for community detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2265-2277.
    43. Marco Grassia & Giuseppe Mangioni & Stefano Schiavo & Silvio Traverso, 2020. "(Unintended) Consequences of export restrictions on medical goods during the Covid-19 pandemic," Papers 2007.11941, arXiv.org.
    44. John J Bartholdi & Pisit Jarumaneeroj & Amar Ramudhin, 2016. "A new connectivity index for container ports," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 18(3), pages 231-249, September.
    45. Paolo Bartesaghi & Gian Paolo Clemente & Rosanna Grassi, 2022. "Community structure in the World Trade Network based on communicability distances," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(2), pages 405-441, April.
    46. Ali Kharrazi & Brian D. Fath & Harald Katzmair, 2016. "Advancing Empirical Approaches to the Concept of Resilience: A Critical Examination of Panarchy, Ecological Information, and Statistical Evidence," Sustainability, MDPI, vol. 8(9), pages 1-17, September.
    47. Sun, Qingru & Gao, Xiangyun & Zhong, Weiqiong & Liu, Nairong, 2017. "The stability of the international oil trade network from short-term and long-term perspectives," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 345-356.
    48. Takayuki Mizuno & Takaaki Ohnishi & Tsutomu Watanabe, 2015. "Structure of global buyer-supplier networks and its implications for conflict minerals regulations," Papers 1505.02274, arXiv.org.
    49. Qing Guan & Haizhong An & Xiaoqing Hao & Xiaoliang Jia, 2016. "The Impact of Countries’ Roles on the International Photovoltaic Trade Pattern: The Complex Networks Analysis," Sustainability, MDPI, vol. 8(4), pages 1-16, March.
    50. Xu, Helian & Cheng, Long, 2019. "The study of the influence of common humanistic relations on international services trade-from the perspective of multi-networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 642-651.
    51. Zhong, Weiqiong & An, Haizhong & Shen, Lei & Dai, Tao & Fang, Wei & Gao, Xiangyun & Dong, Di, 2017. "Global pattern of the international fossil fuel trade: The evolution of communities," Energy, Elsevier, vol. 123(C), pages 260-270.
    52. Khomami, Mohammad Mehdi Daliri & Meybodi, Mohammad Reza & Rezvanian, Alireza, 2024. "Exploring social networks through stochastic multilayer graph modeling," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    53. Li, Yuke & Wu, Tianhao & Marshall, Nicholas & Steinerberger, Stefan, 2017. "Extracting geography from trade data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 205-212.
    54. Alessandro Chessa & Irene Crimaldi & Massimo Riccaboni & Luca Trapin, 2014. "Cluster Analysis of Weighted Bipartite Networks: A New Copula-Based Approach," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-12, October.
    55. Carlo Piccardi & Lucia Tajoli, 2015. "Are Preferential Agreements Significant for the World Trade Structure? A Network Community Analysis," Kyklos, Wiley Blackwell, vol. 68(2), pages 220-239, May.
    56. LI, Yang & Luo, Jingqiu & Jiang, Yongmu, 2021. "Policy uncertainty spillovers and financial risk contagion in the Asia-Pacific network," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
    57. Rosanna Grassi & Paolo Bartesaghi & Stefano Benati & Gian Paolo Clemente, 2021. "Multi-Attribute Community Detection in International Trade Network," Networks and Spatial Economics, Springer, vol. 21(3), pages 707-733, September.
    58. Liu, Linqing & Shen, Mengyun & Sun, Da & Yan, Xiaofei & Hu, Shi, 2022. "Preferential attachment, R&D expenditure and the evolution of international trade networks from the perspective of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).

  34. Alessi, Lucia & Barigozzi, Matteo & Capasso, Marco, 2009. "Estimation and forecasting in large datasets with conditionally heteroskedastic dynamic common factors," Working Paper Series 1115, European Central Bank.

    Cited by:

    1. Hallin, Marc & Trucíos, Carlos, 2023. "Forecasting value-at-risk and expected shortfall in large portfolios: A general dynamic factor model approach," Econometrics and Statistics, Elsevier, vol. 27(C), pages 1-15.
    2. Trucíos Maza, Carlos César & Mazzeu, João H. G. & Hallin, Marc & Hotta, Luiz Koodi & Pereira, Pedro L. Valls & Zevallos, Mauricio, 2019. "Forecasting conditional covariance matrices in high-dimensional time series: a general dynamic factor approach," Textos para discussão 505, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    3. Claudio Morana, 2010. "Heteroskedastic Factor Vector Autoregressive Estimation of Persistent and Non Persistent Processes Subject to Structural Breaks," ICER Working Papers - Applied Mathematics Series 36-2010, ICER - International Centre for Economic Research.
    4. Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2014. "Disentangling Systematic and Idiosyncratic Dynamics in Panels of Volatility Measures," Econometrics Working Papers Archive 2014_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
    5. Aramonte, Sirio & Giudice Rodriguez, Marius del & Wu, Jason, 2013. "Dynamic factor Value-at-Risk for large heteroskedastic portfolios," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4299-4309.
    6. Carlos Cesar Trucios-Maza & João H. G Mazzeu & Luis K. Hotta & Pedro L. Valls Pereira & Marc Hallin, 2019. "On the robustness of the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting," Working Papers ECARES 2019-32, ULB -- Universite Libre de Bruxelles.
    7. Chevallier, Julien, 2011. "Macroeconomics, finance, commodities: Interactions with carbon markets in a data-rich model," Economic Modelling, Elsevier, vol. 28(1), pages 557-567.
    8. Alketa Bejko & Etleva Peta & Belinda Xarba, 2015. "The Evaluation of the Drafting Process of Regional’s Development Strategies in Albania. the Research on Gjirokastra’s Region," European Journal of Interdisciplinary Studies Articles, Revistia Research and Publishing, vol. 1, ejis_v1_i.
    9. Matteo Luciani & David Veredas, 2012. "A model for vast panels of volatilities," Working Papers 1230, Banco de España.
    10. Matteo Barigozzi & Marc Hallin, 2015. "Generalized Dynamic Factor Models and Volatilities: Estimation and Forecasting," Working Papers ECARES ECARES 2015-22, ULB -- Universite Libre de Bruxelles.
    11. Marc Hallin & Carlos Trucíos, 2020. "Forecasting Value-at-Risk and Expected Shortfall in Large Portfolios: a General Dynamic Factor Approach," Working Papers ECARES 2020-50, ULB -- Universite Libre de Bruxelles.
    12. Hallin, Marc & Mathias, Charles & Pirotte, Hugues & Veredas, David, 2011. "Market liquidity as dynamic factors," Journal of Econometrics, Elsevier, vol. 163(1), pages 42-50, July.
    13. Trucíos Maza, Carlos César & Mazzeu, João H. G. & Hotta, Luiz Koodi & Pereira, Pedro L. Valls & Hallin, Marc, 2020. "Robustness and the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting," Textos para discussão 521, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).

  35. Barigozzi, Matteo & Alessi, Lucia & Capasso, Marco & Fagiolo, Giorgio, 2009. "The distribution of households consumption-expenditure budget shares," Working Paper Series 1061, European Central Bank.

    Cited by:

    1. Kaldasch, Joachim, 2012. "Evolutionary model of the personal income distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5628-5642.
    2. Stefano Marchetti & Caterina Giusti & Monica Pratesi, 2016. "The use of Twitter data to improve small area estimates of households’ share of food consumption expenditure in Italy [Die Nutzung von Twitter Daten um die Small Area Schätzungen vom Ausgabenanteil," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 10(2), pages 79-93, October.
    3. Ioannis Kostakis & Dimitrios Paparas & Anna Saiti & Stamatina Papadaki, 2020. "Food Consumption within Greek Households: Further Evidence from a National Representative Sample," Economies, MDPI, vol. 8(1), pages 1-18, February.
    4. Yu, Jian & Shi, Xunpeng & Cheong, Tsun Se, 2021. "Distribution dynamics of China's household consumption upgrading," Structural Change and Economic Dynamics, Elsevier, vol. 58(C), pages 193-203.
    5. Mien, Toh Siaw & Said, Rusmawati, 2018. "A Cross-sectional Household Analysis of Household Consumption Patterns: An Indirect Approach to Identify the Possible Factors of Personal Bankruptcy," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 52(3), pages 231-246.
    6. Voytenkov, Valentin & Demidova, Olga, 2023. "Impact of COVID-19 on household consumption in Russia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 72, pages 73-99.
    7. Iwona Bak & Beata Szczecinska, 2021. "Economic Aspects of Population Aging. Modeling Senior Household Ependiture," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 3), pages 50-67.

  36. Matteo Barigozzi & Giorgio Fagiolo & Diego Garlaschelli, 2009. "Multinetwork of international trade: A commodity-specific analysis," Papers 0908.1879, arXiv.org, revised Jun 2010.

    Cited by:

    1. Marco Duenas & Giorgio Fagiolo, 2013. "Global Trade Imbalances: A Network Approach," LEM Papers Series 2013/12, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    2. Yuichi Ikeda & Hiroshi Iyetomi, 2018. "Trade Network Reconstruction and Simulation with Changes in Trade Policy," Papers 1806.00605, arXiv.org.
    3. Michael Lebacher & Paul W. Thurner & Göran Kauermann, 2021. "Censored regression for modelling small arms trade volumes and its ‘Forensic’ use for exploring unreported trades," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 909-933, August.
    4. Aldasoro, Iñaki & Alves, Iván, 2015. "Multiplex interbank networks and systemic importance: An application to European data," SAFE Working Paper Series 102, Leibniz Institute for Financial Research SAFE.
    5. Arcagni, Alberto & Cerqueti, Roy & Grassi, Rosanna, 2024. "Higher-order assortativity for directed weighted networks and Markov chains," European Journal of Operational Research, Elsevier, vol. 316(1), pages 215-227.
    6. Wang, Bi & Su, Qin & Chin, Kwai Sang, 2021. "Vulnerability assessment of China–Europe Railway Express multimodal transport network under cascading failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 584(C).
    7. Franco Ruzzenenti & Andreas Joseph & Elisa Ticci & Pietro Vozzella & Giampaolo Gabbi, 2015. "Interactions between financial and environmental networks in OECD countries," Papers 1501.04992, arXiv.org, revised Apr 2015.
    8. Roland Lantner & Didier Lebert, 2013. "Dominance, dependence and interdependence in linear structures. A theoretical model and an application to the international trade flows," Post-Print halshs-00825477, HAL.
    9. Rodrigo Mesa-Arango & Badri Narayanan & Satish V. Ukkusuri, 2019. "The Impact of International Crises on Maritime Transportation Based Global Value Chains," Networks and Spatial Economics, Springer, vol. 19(2), pages 381-408, June.
    10. Rosanna Grassi & Paolo Bartesaghi & Gian Paolo Clemente & Duc Thi Luu, 2021. "The multilayer architecture of the global input-output network and its properties," Papers 2109.02946, arXiv.org, revised Nov 2022.
    11. Gianfranco Giulioni & Edmondo Di Giuseppe & Massimiliano Pasqui & Piero Toscano & Francesco Miglietta, 2018. "Investigating Wheat Price with a Multi-Agent Model," Papers 1807.10537, arXiv.org.
    12. Fourel, V. & Héam, J-C. & Salakhova, D. & Tavolaro, S., 2013. "Domino Effects when Banks Hoard Liquidity: The French network," Working papers 432, Banque de France.
    13. Shi, Qing & Sun, Xiaoqi & Xu, Man & Wang, Mengjiao, 2022. "The multiplex network structure of global cobalt industry chain," Resources Policy, Elsevier, vol. 76(C).
    14. Giorgio Fagiolo & Tiziano Squartini & Diego Garlaschelli, 2011. "Null Models of Economic Networks: The Case of the World Trade Web," LEM Papers Series 2011/26, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    15. Pietro Vozzella & Franco Ruzzenenti & Giampaolo Gabbi, 2019. "Energy and Environmental Flows: Do Most Financialised Countries within the Mediterranean Area Export Unsustainability?," Sustainability, MDPI, vol. 11(13), pages 1-15, July.
    16. Leonardo Ermann & Dima L. Shepelyansky, 2015. "Google matrix analysis of the multiproduct world trade network," Papers 1501.03371, arXiv.org.
    17. Paolo Bartesaghi & Gian Paolo Clemente & Rosanna Grassi, 2022. "Clustering coefficients as measures of the complex interactions in a directed weighted multilayer network," Papers 2206.06309, arXiv.org, revised Dec 2022.
    18. Nobi, Ashadun & Lee, Tae Ho & Lee, Jae Woo, 2020. "Structure of trade flow networks for world commodities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    19. Angela Abbate & Luca De Benedictis & Giorgio Fagiolo & Lucia Tajoli, 2012. "The International Trade Network in Space and Time," LEM Papers Series 2012/17, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    20. C'elestin Coquid'e & Jos'e Lages & Dima L. Shepelyansky, 2020. "Crisis contagion in the world trade network," Papers 2002.07100, arXiv.org.
    21. Zhuo-Ming Ren & An Zeng & Yi-Cheng Zhang, 2020. "Bridging nestedness and economic complexity in multilayer world trade networks," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-8, December.
    22. Yuichi Ikeda & Hiroshi Iyetomi, 2018. "Trade network reconstruction and simulation with changes in trade policy," Evolutionary and Institutional Economics Review, Springer, vol. 15(2), pages 495-513, December.
    23. Deepika Srivastava & M. Rahul, 2024. "Network analysis of trade and FDI," SN Business & Economics, Springer, vol. 4(1), pages 1-27, January.
    24. Hu, Xiaoqian & Wang, Chao & Lim, Ming K. & Chen, Wei-Qiang, 2020. "Characteristics of the global copper raw materials and scrap trade systems and the policy impacts of China's import ban," Ecological Economics, Elsevier, vol. 172(C).
    25. Hoppe, K. & Rodgers, G.J., 2015. "A microscopic study of the fitness-dependent topology of the world trade network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 64-74.
    26. Luca Salvatici & Silvia Nenci, 2017. "New features, forgotten costs and counterfactual gains of the international trading system," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 44(4), pages 592-633.
    27. C'elestin Coquid'e & Jos'e Lages & Dima L. Shepelyansky, 2023. "Prospects of BRICS currency dominance in international trade," Papers 2305.00585, arXiv.org.
    28. Vittorio Carlei & Francesca Affortunato & Alessandro Marra & Marco Brogi, 2019. "Does centrality of importing countries affect export prices in the global trade?," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(1), pages 529-551, January.
    29. De Benedictis, L. & Nenci, S. & Santoni, G. & Tajoli, L. & Vicarelli, C., 2013. "Network Analysis of World Trade using the BACI-CEPII dataset," Working papers 471, Banque de France.
    30. Matteo Barigozzi & Giorgio Fagiolo & Giuseppe Mangioni, 2010. "Identifying the Community Structure of the International-Trade Multi Network," LEM Papers Series 2010/15, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    31. Adelaide Baronchelli & Teodora Erika Uberti, 2021. "International Economic Integration: Comparing Exports and FDI Networks in the New Millennium," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 13(11), pages 1-30, November.
    32. Zhu, Nina & Wang, Yuqing & Yang, Shuwen & Lyu, Lixing & Gong, Kunyao & Huang, Xinyue & Huang, Siyi, 2024. "Structure characteristics and formation mechanism of the RCEP manufacturing trade network: An ERGM analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 635(C).
    33. Gao, Cuixia & Sun, Mei & Shen, Bo, 2015. "Features and evolution of international fossil energy trade relationships: A weighted multilayer network analysis," Applied Energy, Elsevier, vol. 156(C), pages 542-554.
    34. Kyu-Min Lee & Kwang-Il Goh, 2016. "Strength of weak layers in cascading failures on multiplex networks: case of the international trade network," Papers 1603.05181, arXiv.org, revised May 2016.
    35. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    36. Hong, Liu & Yan, Yongze & Ouyang, Min & Tian, Hui & He, Xiaozheng, 2017. "Vulnerability effects of passengers' intermodal transfer distance preference and subway expansion on complementary urban public transportation systems," Reliability Engineering and System Safety, Elsevier, vol. 158(C), pages 58-72.
    37. Hao Xu & Niu Niu & Dongmei Li & Chengjie Wang, 2024. "A Dynamic Evolutionary Analysis of the Vulnerability of Global Food Trade Networks," Sustainability, MDPI, vol. 16(10), pages 1-17, May.
    38. Peiteng Shi & Jiang Zhang & Bo Yang & Jingfei Luo, 2014. "Hierarchicality of Trade Flow Networks Reveals Complexity of Products," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-10, June.
    39. Lovrić, Marko & Da Re, Riccardo & Vidale, Enrico & Pettenella, Davide & Mavsar, Robert, 2018. "Social network analysis as a tool for the analysis of international trade of wood and non-wood forest products," Forest Policy and Economics, Elsevier, vol. 86(C), pages 45-66.
    40. V. Kandiah & H. Escaith & D. L. Shepelyansky, 2015. "Contagion effects in the world network of economic activities," Papers 1507.03278, arXiv.org.
    41. Di Vece, Marzio & Garlaschelli, Diego & Squartini, Tiziano, 2023. "Reconciling econometrics with continuous maximum-entropy network models," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    42. Yang, Yu & Poon, Jessie P.H. & Liu, Yi & Bagchi-Sen, Sharmistha, 2015. "Small and flat worlds: A complex network analysis of international trade in crude oil," Energy, Elsevier, vol. 93(P1), pages 534-543.
    43. V. Kandiah & H. Escaith & D. L. Shepelyansky, 2015. "Google matrix of the world network of economic activities," Papers 1504.06773, arXiv.org.
    44. Li, Liqiang & Liu, Jing, 2020. "The aggregation of multiplex networks based on the similarity of networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    45. Jakob Grazzini & Alessandro Spelta, 2015. "An empirical analysis of the global input-output network and its evolution," DISCE - Working Papers del Dipartimento di Economia e Finanza def031, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    46. A. Baronchelli & T.E. Uberti, 2018. "Exports and FDI: comparing networks in the new millennium," Working Paper CRENoS 201813, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    47. Julian Maluck & Reik V Donner, 2015. "A Network of Networks Perspective on Global Trade," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-24, July.
    48. Zhang, Xiaohang & Cui, Huiyuan & Zhu, Ji & Du, Yu & Wang, Qi & Shi, Wenhua, 2017. "Measuring the dissimilarity of multiplex networks: An empirical study of international trade networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 380-394.
    49. Barigozzi, Matteo & Hallin, Marc, 2017. "A network analysis of the volatility of high-dimensionalfinancial series," LSE Research Online Documents on Economics 67456, London School of Economics and Political Science, LSE Library.
    50. Zhong, Weiqiong & An, Haizhong & Gao, Xiangyun & Sun, Xiaoqi, 2014. "The evolution of communities in the international oil trade network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 42-52.
    51. Martinčić-Ipšić, Sanda & Margan, Domagoj & Meštrović, Ana, 2016. "Multilayer network of language: A unified framework for structural analysis of linguistic subsystems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 117-128.
    52. Yuichi Ikeda, 2020. "An Interacting Agent Model of Economic Crisis," Papers 2001.11843, arXiv.org.
    53. Arvis, Jean-Francois, 2013. "How many dimensions do we trade in ? product space geometry and latent comparative advantage," Policy Research Working Paper Series 6478, The World Bank.
    54. Shen, Xinran & Lovrić, Marko, 2022. "Structural determinants of global trade in graphic paper and pulp products," Forest Policy and Economics, Elsevier, vol. 134(C).
    55. C'elestin Coquid'e & Leonardo Ermann & Jos'e Lages & D. L. Shepelyansky, 2019. "Influence of petroleum and gas trade on EU economies from the reduced Google matrix analysis of UN COMTRADE data," Papers 1903.01820, arXiv.org.
    56. Marco Dueñas & Giorgio Fagiolo, 2013. "Modeling the International-Trade Network: a gravity approach," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 155-178, April.
    57. Bartesaghi, Paolo & Clemente, Gian Paolo & Grassi, Rosanna, 2023. "Clustering coefficients as measures of the complex interactions in a directed weighted multilayer network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).
    58. Matteo Barigozzi & Marc Hallin, 2015. "Networks, Dynamic Factors, and the Volatility Analysis of High-Dimensional Financial Series," Papers 1510.05118, arXiv.org, revised Jul 2016.
    59. N. Foti & S. Pauls & Daniel N. Rockmore, 2011. "Stability of the World Trade Web over Time - An Extinction Analysis," Papers 1104.4380, arXiv.org, revised May 2011.
    60. Knoll, Susanne & Padula, Antonio Domingos & Crespolini dos Santos, Mariane & Pumi, Guilherme & Zhou, Shudong & Zhong, Funing & Jardim Barcellos, Julio Otavio, 2018. "Information flow in the Sino-Brazilian beef trade," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 21(1).
    61. Peiteng Shi & Jiang Zhang & Bo Yang & Jingfei Luo, 2014. "Hierarchicality of Trade Flow Networks Reveals Complexity of Products," Papers 1401.3103, arXiv.org.
    62. Marlies Hanna Schütz & Nicole Palan, 2016. "Restructuring of the international clothing and textile trade network: the role of Italy and Portugal," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 5(1), pages 1-29, December.
    63. Giudici, Paolo & Huang, Bihong & Spelta, Alessandro, 2018. "Trade Networks and Economic Fluctuations in Asia," ADBI Working Papers 832, Asian Development Bank Institute.
    64. Gianfranco Giulioni & Edmondo Di Giuseppe & Piero Toscano & Francesco Miglietta & Massimiliano Pasqui, 2019. "A Novel Computational Model of the Wheat Global Market with an Application to the 2010 Russian Federation Case," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 22(3), pages 1-4.
    65. Ma, Yu & Wang, Minxi & Li, Xin, 2022. "Analysis of the characteristics and stability of the global complex nickel ore trade network," Resources Policy, Elsevier, vol. 79(C).
    66. Luu, Duc Thi & Lux, Thomas, 2018. "Multilayer overlaps and correlations in the bank-firm credit network of Spain," Economics Working Papers 2018-04, Christian-Albrechts-University of Kiel, Department of Economics.
    67. Mario Maggioni & Teodora Uberti, 2011. "Networks and geography in the economics of knowledge flows," Quality & Quantity: International Journal of Methodology, Springer, vol. 45(5), pages 1031-1051, August.
    68. Michael Lebacher & Paul W. Thurner & Göran Kauermann, 2021. "A dynamic separable network model with actor heterogeneity: An application to global weapons transfers," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 201-226, January.
    69. Khomami, Mohammad Mehdi Daliri & Meybodi, Mohammad Reza & Rezvanian, Alireza, 2024. "Exploring social networks through stochastic multilayer graph modeling," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
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    72. Roland Lantner & Didier Lebert, 2013. "Dominance, dependence and interdependence in linear structures. A theoretical model and an application to the international trade flows," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00825477, HAL.
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    74. Roland Lantner & Didier Lebert, 2013. "Dominance, dependence and interdependence in linear structures. A theoretical model and an application to the international trade flows," Documents de travail du Centre d'Economie de la Sorbonne 13043, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
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    77. Mika J. Straka & Guido Caldarelli & Tiziano Squartini & Fabio Saracco, 2017. "From Ecology to Finance (and Back?): Recent Advancements in the Analysis of Bipartite Networks," Papers 1710.10143, arXiv.org.
    78. Jeroen van Lidth de Jeude & Riccardo Di Clemente & Guido Caldarelli & Fabio Saracco & Tiziano Squartini, 2019. "Reconstructing Mesoscale Network Structures," Complexity, Hindawi, vol. 2019, pages 1-13, January.

  37. Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2009. "A Robust Criterion for Determining the Number of Factors in Approximate Factor Models," Working Papers ECARES 2009_023, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Juan José Echavarría & Andrés gonzález & Enrique López & Norberto Rodríguez, 2012. "Choques internacionales reales y financieros y su impacto sobre la economía colombiana," Borradores de Economia 9884, Banco de la Republica.
    2. Jiang, Yu & Guo, Yongji & Zhang, Yihao, 2017. "Forecasting China's GDP growth using dynamic factors and mixed-frequency data," Economic Modelling, Elsevier, vol. 66(C), pages 132-138.
    3. Fernando Tenjo Galarza & Enrique López E. & Diego H. Rodríguez H., 2012. "El canal de préstamos de la política monetaria en Colombia. Un enfoque FAVAR," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 30(69), pages 195-256, December.
    4. Fernando Tenjo Galarza & Enrique López E. & Diego H. Rodríguez H., 2011. "El canal de préstamos de la política monetaria en Colombia. Un enfoque FAVAR," Borradores de Economia 9198, Banco de la Republica.
    5. Xisong Jin & Francisco Nadal De Simone, 2015. "Investment funds? vulnerabilities: A tail-risk dynamic CIMDO approach," BCL working papers 95, Central Bank of Luxembourg.
    6. Jin, Xisong & Nadal De Simone, Francisco, 2014. "A framework for tracking changes in the intensity of investment funds' systemic risk," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 343-368.
    7. Xisong Jin & Francisco Nadal De Simone, 2013. "Banking Systemic Vulnerabilities: A Tail-risk Dynamic CIMDO Approach," BCL working papers 82, Central Bank of Luxembourg.
    8. Xisong Jin & Francisco Nadal De Simone, 2017. "Systemic Financial Sector and Sovereign Risks," BCL working papers 109, Central Bank of Luxembourg.
    9. Travaglini, Guido, 2011. "Principal Components and Factor Analysis. A Comparative Study," MPRA Paper 35486, University Library of Munich, Germany.
    10. Xisong Jin & Francisco Nadal De Simone, 2016. "Tracking Changes in the Intensity of Financial Sector's Systemic Risk," BCL working papers 102, Central Bank of Luxembourg.
    11. Xisong Jin, 2018. "How much does book value data tell us about systemic risk and its interactions with the macroeconomy? A Luxembourg empirical evaluation," BCL working papers 118, Central Bank of Luxembourg.

  38. Matteo Barigozzi & Biagio Speciale, 2009. "Immigrant’s legal status, permanence in the destination country and the distribution of consumption expenditure," Working Papers ECARES 2009_019, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Adamopoulou, Effrosyni & Kaya, Ezgi, 2019. "Not Just a Work Permit: EU Citizenship and the Consumption Behavior of Documented and Undocumented Immigrants," IZA Discussion Papers 12642, Institute of Labor Economics (IZA).

  39. Alessi, Lucia & Barigozzi, Matteo & Capasso, Marco, 2008. "A robust criterion for determining the number of static factors in approximate factor models," Working Paper Series 903, European Central Bank.

    Cited by:

    1. Juan José Echavarría & Andrés gonzález & Enrique López & Norberto Rodríguez, 2012. "Choques internacionales reales y financieros y su impacto sobre la economía colombiana," Borradores de Economia 9884, Banco de la Republica.
    2. Alain Kabundi & Tumisang Loate & Nicola Viegi, 2020. "Spillovers of the Conventional and Unconventional Monetary Policy from the US to South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 88(4), pages 435-471, December.
    3. Jin, Xisong & Nadal De Simone, Francisco, 2020. "Monetary policy and systemic risk-taking in the Euro area investment fund industry: A structural factor-augmented vector autoregression analysis," Journal of Financial Stability, Elsevier, vol. 49(C).
    4. GUO-FITOUSSI, Liang, 2013. "A Comparison of the Finite Sample Properties of Selection Rules of Factor Numbers in Large Datasets," MPRA Paper 50005, University Library of Munich, Germany.
    5. Gao, Quansheng & Hu, Chengjun, 2009. "Dynamic mortality factor model with conditional heteroskedasticity," Insurance: Mathematics and Economics, Elsevier, vol. 45(3), pages 410-423, December.
    6. Christian Menden & Christian R. Proaño, 2017. "Dissecting the financial cycle with dynamic factor models," IMK Working Paper 183-2017, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    7. Fernando Tenjo Galarza & Enrique López E. & Diego H. Rodríguez H., 2012. "El canal de préstamos de la política monetaria en Colombia. Un enfoque FAVAR," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 30(69), pages 195-256, December.
    8. Matteo Luciani, 2015. "Monetary Policy and the Housing Market: A Structural Factor Analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(2), pages 199-218, March.
    9. Matteo Barigozzi & Marco Capasso, 2007. "A Multivariate Perspective for Modeling and Forecasting Inflation's Conditional Mean and Variance," LEM Papers Series 2007/21, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    10. Le, Vu & Wang, Qing, 2014. "Robust thresholding for Diffusion Index forecast," Economics Letters, Elsevier, vol. 125(1), pages 52-56.
    11. Alain Kabundi & Francisco Nadal De Simone, 2011. "France in the global economy: a structural approximate dynamic factor model analysis," Empirical Economics, Springer, vol. 41(2), pages 311-342, October.
    12. Fernando Tenjo Galarza & Enrique López E. & Diego H. Rodríguez H., 2011. "El canal de préstamos de la política monetaria en Colombia. Un enfoque FAVAR," Borradores de Economia 9198, Banco de la Republica.
    13. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André, 2012. "Dynamic factor models with macro, frailty and industry effects for US default counts: the credit crisis of 2008," Working Paper Series 1459, European Central Bank.
    14. Xisong Jin & Francisco Nadal De Simone, 2012. "An Early-warning and Dynamic Forecasting Framework of Default Probabilities for the Macroprudential Policy Indicators Arsenal," BCL working papers 75, Central Bank of Luxembourg.
    15. Dzhamilya Abuzyarova & Veronika Belousova & Zhaklin Krayushkina & Yulia Lonshcikova & Ekaterina Nikiforova & Nikolay Chichkanov, 2019. "The Role of Human Capital in Science, Technology and Innovation," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 13(2), pages 107-119.
    16. Mohan Subbiah & Frank J Fabozzi, 2016. "Equity style allocation: A nonparametric approach," Journal of Asset Management, Palgrave Macmillan, vol. 17(3), pages 141-164, May.
    17. Pallara, Kevin, 2016. "The dynamic effects of government spending: a FAVAR approach," MPRA Paper 92283, University Library of Munich, Germany.
    18. Vedolin, Andrea, 2012. "Uncertainty and leveraged Lucas Trees: the cross section of equilibrium volatility risk premia," LSE Research Online Documents on Economics 43091, London School of Economics and Political Science, LSE Library.
    19. Ali Babikir & Henry Mwambi, 2016. "Evaluating the combined forecasts of the dynamic factor model and the artificial neural network model using linear and nonlinear combining methods," Empirical Economics, Springer, vol. 51(4), pages 1541-1556, December.

  40. Alessi, Lucia & Barigozzi, Matteo & Capasso, Marco, 2008. "A review of nonfundamentalness and identification in structural VAR models," Working Paper Series 922, European Central Bank.

    Cited by:

    1. Paul Beaudry & Franck Portier, 2014. "News Driven Business Cycles: Insights and Challenges," 2014 Meeting Papers 289, Society for Economic Dynamics.
    2. Giorgio Fagiolo & Andrea Roventini, 2012. "Macroeconomic Policy in DSGE and Agent-Based Models," Working Papers 07/2012, University of Verona, Department of Economics.
    3. Lanne, Markku & Saikkonen, Pentti, 2013. "Noncausal Vector Autoregression," Econometric Theory, Cambridge University Press, vol. 29(3), pages 447-481, June.
    4. G. Fagiolo & A. Roventini, 2009. "On the Scientific Status of Economic Policy: A Tale of Alternative Paradigms," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 6.
    5. Helmut Lütkepohl, 2012. "Fundamental Problems with Nonfundamental Shocks," Discussion Papers of DIW Berlin 1230, DIW Berlin, German Institute for Economic Research.
    6. Gianluca Cubadda & Francesco Giancaterini & Alain Hecq & Joann Jasiak, 2024. "Optimization of the Generalized Covariance Estimator in Noncausal Processes," CEIS Research Paper 574, Tor Vergata University, CEIS, revised 23 Apr 2024.
    7. Féve, Patrick & Jidoud, Ahmat, 2012. "Identifying News Shocks from SVARs," Journal of Macroeconomics, Elsevier, vol. 34(4), pages 919-932.
    8. Valter Di Giacinto & Giacinto Micucci & Pasqualino Montanaro, 2010. "Dynamic Macroeconomic Effects of Public Capital: Evidence from Regional Italian Data," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 69(1), pages 29-66, April.
    9. Johannes Hermanus Kemp, 2020. "Empirical estimates of fiscal multipliers for South Africa," WIDER Working Paper Series wp-2020-91, World Institute for Development Economic Research (UNU-WIDER).

  41. Giorgio Fagiolo & Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2007. "On the distributional properties of household consumption expenditures. The case of Italy," LEM Papers Series 2007/24, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

    Cited by:

    1. Barigozzi, Matteo & Alessi, Lucia & Capasso, Marco & Fagiolo, Giorgio, 2009. "The distribution of households consumption-expenditure budget shares," Working Paper Series 1061, European Central Bank.
    2. Chatterjee, Arnab & Chakrabarti, Anindya S. & Ghosh, Asim & Chakraborti, Anirban & Nandi, Tushar K., 2016. "Invariant features of spatial inequality in consumption: The case of India," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 169-181.
    3. Matteo Barigozzi & Biagio Speciale, 2011. "Immigrants' legal status, permanence in the destination country and the distribution of consumption expenditure," Post-Print hal-04514056, HAL.
    4. Mundt, Philipp & Oh, Ilfan, 2019. "Asymmetric competition, risk, and return distribution," Economics Letters, Elsevier, vol. 179(C), pages 29-32.
    5. Scharfenaker, Ellis, 2020. "Implications of quantal response statistical equilibrium," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    6. Schulz, Jan & Mayerhoffer, Daniel M., 2021. "A network approach to consumption," BERG Working Paper Series 173, Bamberg University, Bamberg Economic Research Group.
    7. Barigozzi, Matteo & Moneta, Alessio, 2016. "Identifying the independent sources of consumption variation," LSE Research Online Documents on Economics 60979, London School of Economics and Political Science, LSE Library.
    8. Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2019. "Exploiting ergodicity in forecasts of corporate profitability," BERG Working Paper Series 147, Bamberg University, Bamberg Economic Research Group.
    9. Matteo Barigozzi & Lucia Alessi & Marco Capasso & Giorgio Fagiolo, 2008. "The Distribution of Consumption-Expenditure Budget Shares. Evidence from Italian Households," Papers on Economics and Evolution 2008-09, Philipps University Marburg, Department of Geography.
    10. Alfarano, Simone & Milaković, Mishael & Irle, Albrecht & Kauschke, Jonas, 2012. "A statistical equilibrium model of competitive firms," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 136-149.
    11. David S. Bieri & Casey J. Dawkins, 2019. "Amenities, affordability, and housing vouchers," Journal of Regional Science, Wiley Blackwell, vol. 59(1), pages 56-82, January.

  42. Marco Capasso & Lucia Alessi & Matteo Barigozzi & Giorgio Fagiolo, 2007. "On approximating the distributions of goodness-of-fit test statistics based on the empirical distribution function: The case of unknown parameters," LEM Papers Series 2007/23, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

    Cited by:

    1. Giuricich, Mario Nicoló & Burnecki, Krzysztof, 2019. "Modelling of left-truncated heavy-tailed data with application to catastrophe bond pricing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 498-513.
    2. Lunardi, José T. & Miccichè, Salvatore & Lillo, Fabrizio & Mantegna, Rosario N. & Gallegati, Mauro, 2014. "Do firms share the same functional form of their growth rate distribution? A statistical test," Journal of Economic Dynamics and Control, Elsevier, vol. 39(C), pages 140-164.
    3. Matthias Duschl & Thomas Brenner, 2013. "Characteristics of regional industry-specific employment growth rates' distributions," Papers in Regional Science, Wiley Blackwell, vol. 92(2), pages 249-270, June.
    4. Giorgio Fagiolo & Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2010. "On the distributional properties of household consumption expenditures: the case of Italy," Empirical Economics, Springer, vol. 38(3), pages 717-741, June.
    5. Dennis Frestad & Fred Espen Benth & Steen Koekebakker, 2010. "Modeling Term Structure Dynamics in the Nordic Electricity Swap Market," The Energy Journal, , vol. 31(2), pages 53-86, April.
    6. Iván Blanco, Juan Ignacio Peña, and Rosa Rodriguez, 2018. "Modelling Electricity Swaps with Stochastic Forward Premium Models," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).

Articles

  1. Barigozzi, Matteo & Hallin, Marc & Luciani, Matteo & Zaffaroni, Paolo, 2024. "Inferential theory for generalized dynamic factor models," Journal of Econometrics, Elsevier, vol. 239(2).
    See citations under working paper version above.
  2. Matteo Barigozzi & Matteo Farnè, 2024. "An Algebraic Estimator for Large Spectral Density Matrices," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 119(545), pages 498-510, January.

    Cited by:

    1. Matteo Barigozzi & Marc Hallin, 2024. "The Dynamic, the Static, and the Weak factor models and the analysis of high-dimensional time series," Papers 2407.10653, arXiv.org.

  3. Matteo Barigozzi & Haeran Cho & Dom Owens, 2024. "FNETS: Factor-Adjusted Network Estimation and Forecasting for High-Dimensional Time Series," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 890-902, July.

    Cited by:

    1. Elie Bouri & Matteo Foglia & Sayar Karmakar & Rangan Gupta, 2024. "Return-Volatility Nexus in the Digital Asset Class: A Dynamic Multilayer Connectedness Analysis," Working Papers 202432, University of Pretoria, Department of Economics.
    2. Matteo Barigozzi & Marc Hallin, 2024. "The Dynamic, the Static, and the Weak factor models and the analysis of high-dimensional time series," Papers 2407.10653, arXiv.org.
    3. Luca Margaritella & Ovidijus Stauskas, 2024. "New Tests of Equal Forecast Accuracy for Factor-Augmented Regressions with Weaker Loadings," Papers 2409.20415, arXiv.org, revised Oct 2024.

  4. Matteo Barigozzi & Matteo Luciani, 2023. "Measuring the Output Gap using Large Datasets," The Review of Economics and Statistics, MIT Press, vol. 105(6), pages 1500-1514, November.

    Cited by:

    1. Diego Fresoli & Pilar Poncela & Esther Ruiz, 2024. "Dealing with idiosyncratic cross-correlation when constructing confidence regions for PC factors," Papers 2407.06883, arXiv.org.

  5. Matteo Barigozzi & Lorenzo Trapani, 2022. "Testing for Common Trends in Nonstationary Large Datasets," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1107-1122, June.

    Cited by:

    1. Morten {O}rregaard Nielsen & Won-Ki Seo & Dakyung Seong, 2023. "Inference on common trends in functional time series," Papers 2312.00590, arXiv.org, revised May 2024.
    2. Gianluca Cubadda & Marco Mazzali, 2024. "The vector error correction index model: representation, estimation and identification," The Econometrics Journal, Royal Economic Society, vol. 27(1), pages 126-150.

  6. Barigozzi, Matteo & Hallin, Marc & Soccorsi, Stefano & von Sachs, Rainer, 2021. "Time-varying general dynamic factor models and the measurement of financial connectedness," Journal of Econometrics, Elsevier, vol. 222(1), pages 324-343.
    See citations under working paper version above.
  7. Barigozzi, Matteo & Lippi, Marco & Luciani, Matteo, 2021. "Large-dimensional Dynamic Factor Models: Estimation of Impulse–Response Functions with I(1) cointegrated factors," Journal of Econometrics, Elsevier, vol. 221(2), pages 455-482.

    Cited by:

    1. Shahriyar Aliyev & Evzen Kocenda, 2020. "ECB Monetary Policy and Commodity Prices," Working Papers IES 2020/8, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Apr 2020.
    2. Chiara Casoli & Riccardo (Jack) Lucchetti, 2022. "Permanent-Transitory decomposition of cointegrated time series via dynamic factor models, with an application to commodity prices [Commodity-price comovement and global economic activity]," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 494-514.
    3. Lippi, Marco & Deistler, Manfred & Anderson, Brian, 2023. "High-Dimensional Dynamic Factor Models: A Selective Survey and Lines of Future Research," Econometrics and Statistics, Elsevier, vol. 26(C), pages 3-16.
    4. Donato Ceci & Andrea Silvestrini, 2023. "Nowcasting the state of the Italian economy: The role of financial markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1569-1593, November.
    5. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    6. Gianluca Cubadda & Marco Mazzali, 2024. "The vector error correction index model: representation, estimation and identification," The Econometrics Journal, Royal Economic Society, vol. 27(1), pages 126-150.
    7. Davide Brignone & Alessandro Franconi & Marco Mazzali, 2023. "Robust Impulse Responses using External Instruments: the Role of Information," Papers 2307.06145, arXiv.org.
    8. Haroon Mumtaz & Roman Sustek, 2023. "Global house prices since 1950," Discussion Papers 2307, Centre for Macroeconomics (CFM).
    9. Hie Joo Ahn & Matteo Luciani, 2021. "Relative prices and pure inflation since the mid-1990s," Finance and Economics Discussion Series 2021-069, Board of Governors of the Federal Reserve System (U.S.).
    10. Juho Koistinen & Bernd Funovits, 2022. "Estimation of Impulse-Response Functions with Dynamic Factor Models: A New Parametrization," Papers 2202.00310, arXiv.org, revised Feb 2022.
    11. Cantore, Cristiano & Ferroni, Filippo & Mumtaz, Hroon & Theophilopoulou, Angeliki, 2022. "A tail of labour supply and a tale of monetary policy," Bank of England working papers 989, Bank of England.
    12. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.
    13. Theo Drossidis & Haroon Mumtaz & Angeliki Theophilopoulou, 2024. "The Distributional Effects of Oil Supply New Shocks," Working Papers 975, Queen Mary University of London, School of Economics and Finance.
    14. Mirela Sorina Miescu & Giorgio Motta & Dario Pontiggia & Raffaele Rossi, 2023. "The Expansionary Effects Of Housing Credit Supply Shocks," Working Papers 399832231, Lancaster University Management School, Economics Department.
    15. Takumah, Wisdom, 2023. "Fiscal Policy and Asset Prices in a Dynamic Factor Model with Cointegrated Factors," MPRA Paper 117897, University Library of Munich, Germany, revised 10 Jul 2023.
    16. Ergemen, Yunus Emre, 2023. "Parametric estimation of long memory in factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1483-1499.

  8. Barigozzi, Matteo & Trapani, Lorenzo, 2020. "Sequential testing for structural stability in approximate factor models," Stochastic Processes and their Applications, Elsevier, vol. 130(8), pages 5149-5187.
    See citations under working paper version above.
  9. Barigozzi, Matteo & Hallin, Marc, 2020. "Generalized dynamic factor models and volatilities: Consistency, rates, and prediction intervals," Journal of Econometrics, Elsevier, vol. 216(1), pages 4-34.
    See citations under working paper version above.
  10. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2020. "Cointegration and Error Correction Mechanisms for Singular Stochastic Vectors," Econometrics, MDPI, vol. 8(1), pages 1-23, February.

    Cited by:

    1. Feng, Zongbao & Chen, Weiya & Liu, Yang & Chen, Hongyu & Skibniewski, Mirosław J., 2023. "Long-term equilibrium relationship analysis and energy-saving measures of metro energy consumption and its influencing factors based on cointegration theory and an ARDL model," Energy, Elsevier, vol. 263(PD).
    2. Chiara Casoli & Riccardo (Jack) Lucchetti, 2022. "Permanent-Transitory decomposition of cointegrated time series via dynamic factor models, with an application to commodity prices [Commodity-price comovement and global economic activity]," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 494-514.
    3. Sergej Gričar & Štefan Bojnec, 2021. "Technical Analysis of Tourism Price Process in the Eurozone," JRFM, MDPI, vol. 14(11), pages 1-25, October.
    4. Lippi, Marco & Deistler, Manfred & Anderson, Brian, 2023. "High-Dimensional Dynamic Factor Models: A Selective Survey and Lines of Future Research," Econometrics and Statistics, Elsevier, vol. 26(C), pages 3-16.
    5. Donato Ceci & Andrea Silvestrini, 2023. "Nowcasting the state of the Italian economy: The role of financial markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1569-1593, November.
    6. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    7. Tibor Szendrei & Katalin Varga, 2020. "FISS - A Factor-based Index of Systemic Stress in the Financial System," Russian Journal of Money and Finance, Bank of Russia, vol. 79(1), pages 3-34, March.
    8. Juho Koistinen & Bernd Funovits, 2022. "Estimation of Impulse-Response Functions with Dynamic Factor Models: A New Parametrization," Papers 2202.00310, arXiv.org, revised Feb 2022.
    9. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.
    10. Barigozzi, Matteo & Lippi, Marco & Luciani, Matteo, 2021. "Large-dimensional Dynamic Factor Models: Estimation of Impulse–Response Functions with I(1) cointegrated factors," Journal of Econometrics, Elsevier, vol. 221(2), pages 455-482.

  11. Matteo Barigozzi & Marc Hallin & Stefano Soccorsi, 2019. "Identification of Global and Local Shocks in International Financial Markets via General Dynamic Factor Models," Journal of Financial Econometrics, Oxford University Press, vol. 17(3), pages 462-494.
    See citations under working paper version above.
  12. Matteo Barigozzi & Christian Brownlees, 2019. "NETS: Network estimation for time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 347-364, April.
    See citations under working paper version above.
  13. Mercedes Campi & Marco Dueñas & Matteo Barigozzi & Giorgio Fagiolo, 2019. "Intellectual property rights, imitation, and development. The effect on cross-border mergers and acquisitions," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 28(2), pages 230-256, February.
    See citations under working paper version above.
  14. Matteo Barigozzi & Antonio M. Conti, 2018. "On the Stability of Euro Area Money Demand and Its Implications for Monetary Policy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(4), pages 755-787, August.
    See citations under working paper version above.
  15. Barigozzi, Matteo & Cho, Haeran & Fryzlewicz, Piotr, 2018. "Simultaneous multiple change-point and factor analysis for high-dimensional time series," Journal of Econometrics, Elsevier, vol. 206(1), pages 187-225.
    See citations under working paper version above.
  16. Barigozzi, Matteo & Hallin, Marc, 2017. "Generalized dynamic factor models and volatilities: estimation and forecasting," Journal of Econometrics, Elsevier, vol. 201(2), pages 307-321.
    See citations under working paper version above.
  17. Matteo Barigozzi & Marc Hallin, 2017. "A network analysis of the volatility of high dimensional financial series," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(3), pages 581-605, April.
    See citations under working paper version above.
  18. Matteo Barigozzi & Marc Hallin, 2016. "Generalized dynamic factor models and volatilities: recovering the market volatility shocks," Econometrics Journal, Royal Economic Society, vol. 19(1), pages 33-60, February.
    See citations under working paper version above.
  19. Matteo Barigozzi & Alessio Moneta, 2016. "Identifying the Independent Sources of Consumption Variation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(2), pages 420-449, March.
    See citations under working paper version above.
  20. Matteo Barigozzi & Antonio M. Conti & Matteo Luciani, 2014. "Do Euro Area Countries Respond Asymmetrically to the Common Monetary Policy?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(5), pages 693-714, October.
    See citations under working paper version above.
  21. Barigozzi, Matteo & Brownlees, Christian & Gallo, Giampiero M. & Veredas, David, 2014. "Disentangling systematic and idiosyncratic dynamics in panels of volatility measures," Journal of Econometrics, Elsevier, vol. 182(2), pages 364-384.
    See citations under working paper version above.
  22. Alessi, Lucia & Barigozzi, Matteo & Capasso, Marco, 2013. "The common component of firm growth," Structural Change and Economic Dynamics, Elsevier, vol. 26(C), pages 73-82.

    Cited by:

    1. Stella, Andrea, 2015. "Firm dynamics and the origins of aggregate fluctuations," Journal of Economic Dynamics and Control, Elsevier, vol. 55(C), pages 71-88.
    2. Juan Federico & Joan-Lluis Capelleras, 2015. "The heterogeneous dynamics between growth and profits: the case of young firms," Small Business Economics, Springer, vol. 44(2), pages 231-253, February.
    3. Fornaro, Paolo, 2016. "Predicting Finnish economic activity using firm-level data," International Journal of Forecasting, Elsevier, vol. 32(1), pages 10-19.

  23. Barigozzi, Matteo & Alessi, Lucia & Capasso, Marco & Fagiolo, Giorgio, 2012. "The distribution of household consumption-expenditure budget shares," Structural Change and Economic Dynamics, Elsevier, vol. 23(1), pages 69-91.
    See citations under working paper version above.
  24. Matteo Barigozzi & Biagio Speciale, 2011. "Immigrants' legal status, permanence in the destination country and the distribution of consumption expenditure," Applied Economics Letters, Taylor & Francis Journals, vol. 18(14), pages 1341-1347.
    See citations under working paper version above.
  25. Barigozzi, Matteo & Fagiolo, Giorgio & Mangioni, Giuseppe, 2011. "Identifying the community structure of the international-trade multi-network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(11), pages 2051-2066.
    See citations under working paper version above.
  26. Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2011. "Non‐Fundamentalness in Structural Econometric Models: A Review," International Statistical Review, International Statistical Institute, vol. 79(1), pages 16-47, April.

    Cited by:

    1. Berner, Anne & Bruns, Stephan B. & Moneta, Alessio & Stern, David I., 2021. "Do energy efficiency improvements reduce energy use? Empirical evidence on the economy-wide rebound effect in Europe and the United States," University of Göttingen Working Papers in Economics 422, University of Goettingen, Department of Economics.
    2. Alessi, Lucia & Kerssenfischer, Mark, 2016. "The response of asset prices to monetary policy shocks: stronger than thought," Working Paper Series 1967, European Central Bank.
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  28. Giorgio Fagiolo & Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2010. "On the distributional properties of household consumption expenditures: the case of Italy," Empirical Economics, Springer, vol. 38(3), pages 717-741, June.
    See citations under working paper version above.
  29. Marco Capasso & Lucia Alessi & Matteo Barigozzi & Giorgio Fagiolo, 2009. "On Approximating The Distributions Of Goodness-Of-Fit Test Statistics Based On The Empirical Distribution Function: The Case Of Unknown Parameters," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 12(02), pages 157-167.
    See citations under working paper version above.
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