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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 & 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.

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

  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 & 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. 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.

  5. 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. 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.
    2. Matteo Barigozzi & Marc Hallin, 2018. "Generalized Dynamic Factor Models and Volatilities: Consistency, Rates, and Prediction Intervals," Working Papers ECARES 2018-33, ULB -- Universite Libre de Bruxelles.
    3. 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 Discussion Papers 2020-5, Kiel Institute for the World Economy (IfW Kiel).
    4. 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.
    5. 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).
    6. Niţoi, Mihai & Pochea, Maria Miruna, 2022. "The nexus between bank connectedness and investors’ sentiment," Finance Research Letters, Elsevier, vol. 44(C).
    7. 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.
    8. Alessandro Giovannelli & Daniele Massacci & Stefano Soccorsi, 2020. "Forecasting Stock Returns with Large Dimensional Factor Models," Working Papers 305661169, Lancaster University Management School, Economics Department.
    9. 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.

  6. 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. 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.
    2. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
    3. Serena Ng & Susannah Scanlan, 2023. "Constructing High Frequency Economic Indicators by Imputation," Papers 2303.01863, arXiv.org, revised Oct 2023.
    4. 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 Discussion Papers 2020-5, Kiel Institute for the World Economy (IfW Kiel).
    5. 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).
    6. Poncela Blanco, Maria Pilar, 2020. "Factor extraction using Kalman filter and smoothing: this is not just another survey," DES - Working Papers. Statistics and Econometrics. WS 30644, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Paolo Andreini & Cosimo Izzo & Giovanni Ricco, 2023. "Deep Dynamic Factor Models," Working Papers 2023-08, Center for Research in Economics and Statistics.
    12. Matteo Barigozzi, 2023. "Quasi Maximum Likelihood Estimation of High-Dimensional Factor Models: A Critical Review," Papers 2303.11777, arXiv.org, revised May 2024.
    13. 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.).
    14. Matteo Barigozzi & Daniele Massacci, 2022. "Modelling Large Dimensional Datasets with Markov Switching Factor Models," Papers 2210.09828, arXiv.org, revised Jun 2024.
    15. 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).

  7. 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. 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.
    2. Jozef Barunik & Mattia Bevilacqua & Robert Faff, 2021. "Dynamic industry uncertainty networks and the business cycle," Papers 2101.06957, arXiv.org, revised Mar 2021.
    3. Jozef Barunik & Michael Ellington, 2020. "Persistence in Financial Connectedness and Systemic Risk," Papers 2007.07842, arXiv.org, revised Nov 2023.
    4. 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).
    5. Kole, Erik & van Dijk, Dick, 2023. "Moments, shocks and spillovers in Markov-switching VAR models," Journal of Econometrics, Elsevier, vol. 236(2).
    6. Luigi Longo & Massimo Riccaboni & Armando Rungi, 2021. "A Neural Network Ensemble Approach for GDP Forecasting," Working Papers 02/2021, IMT School for Advanced Studies Lucca, revised Mar 2021.
    7. Jonas Krampe & Luca Margaritella, 2024. "Global bank network connectedness revisited: What is common, idiosyncratic and when?," Papers 2402.02482, arXiv.org.
    8. 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.
    9. Jianqing Fan & Ricardo Masini & Marcelo C. Medeiros, 2021. "Bridging factor and sparse models," Papers 2102.11341, arXiv.org, revised Sep 2022.
    10. Ellington, Michael, 2022. "Fat tails, serial dependence, and implied volatility index connections," European Journal of Operational Research, Elsevier, vol. 299(2), pages 768-779.
    11. 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).
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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).
    17. 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.
    18. 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.
    19. 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.

  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. 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).
    2. Poncela Blanco, Maria Pilar, 2020. "Factor extraction using Kalman filter and smoothing: this is not just another survey," DES - Working Papers. Statistics and Econometrics. WS 30644, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Filippo Pellegrino, 2021. "Factor-augmented tree ensembles," Papers 2111.14000, arXiv.org, revised Jun 2023.
    4. Danilo Cascaldi-Garcia & Matteo Luciani & Michele Modugno, 2023. "Lessons from Nowcasting GDP across the World," International Finance Discussion Papers 1385, Board of Governors of the Federal Reserve System (U.S.).
    5. 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.
    6. 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.
    7. Diego Fresoli & Pilar Poncela & Esther Ruiz, 2024. "Dealing with idiosyncratic cross-correlation when constructing confidence regions for PC factors," Papers 2407.06883, arXiv.org.
    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. 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. 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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Marc Hallin & Luis K. Hotta & João H. G Mazzeu & Carlos Cesar Trucios-Maza & Pedro L. Valls Pereira & Mauricio Zevallos, 2019. "Forecasting Conditional Covariance Matrices in High-Dimensional Time Series: a General Dynamic Factor Approach," Working Papers ECARES 2019-14, ULB -- Universite Libre de Bruxelles.
    6. Nummi, Patrik & Viitasaari, Lauri, 2024. "Necessary and sufficient conditions for continuity of hypercontractive processes and fields," Statistics & Probability Letters, Elsevier, vol. 208(C).
    7. Jianqing Fan & Ricardo Masini & Marcelo C. Medeiros, 2021. "Bridging factor and sparse models," Papers 2102.11341, arXiv.org, revised Sep 2022.
    8. 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).
    9. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.
    10. 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.
    11. 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.
    12. 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.
    13. Matteo Barigozzi, 2023. "Quasi Maximum Likelihood Estimation of High-Dimensional Factor Models: A Critical Review," Papers 2303.11777, arXiv.org, revised May 2024.
    14. Liao, Gaoke & Li, Yanling & Wang, Mengxin, 2024. "Contagion network of idiosyncratic volatility: Does corporate environmental responsibility matter?," Energy Economics, Elsevier, vol. 129(C).
    15. 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.

  10. 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.

  11. 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," Post-Print hal-03545424, 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. Barnett, William & Chauvet, Marcelle & Leiva-Leon, Danilo & Su, Liting, 2016. "The credit-card-services augmented Divisia monetary aggregates," MPRA Paper 73245, University Library of Munich, Germany.
    5. Conti, Antonio M., 2021. "Resurrecting the Phillips Curve in Low-Inflation Times," Economic Modelling, Elsevier, vol. 96(C), pages 172-195.

  12. 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)," LEM Papers Series 2020/06, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    2. Gnangnon, Sèna Kimm, 2023. "Aid for Trade flows, Patent Rights Protection and Total Factor Productivity," EconStor Preprints 274650, ZBW - Leibniz Information Centre for Economics.
    3. 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).
    4. 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.

  13. 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. 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.
    2. 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).
    3. Wang, Lu & Wu, Jianhong, 2022. "Estimation of high-dimensional factor models with multiple structural changes," Economic Modelling, Elsevier, vol. 108(C).
    4. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
    5. Thomas Despois & Catherine Doz, 2021. "Identifying and interpreting the factors in factor models via sparsity: Different approaches," Working Papers halshs-02235543, HAL.
    6. Cho, Haeran & Kirch, Claudia, 2024. "Data segmentation algorithms: Univariate mean change and beyond," Econometrics and Statistics, Elsevier, vol. 30(C), pages 76-95.
    7. 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.
    8. 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).
    9. Matteo Barigozzi & Lorenzo Trapani, 2018. "Sequential testing for structural stability in approximate factor models," Discussion Papers 18/04, University of Nottingham, Granger Centre for Time Series Econometrics.
    10. Ma, Chenchen & Tu, Yundong, 2023. "Shrinkage estimation of multiple threshold factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1876-1892.
    11. Fernandez, Julian, 2020. "Exchange Rate Uncertainty and the Interest Rate Parity," MPRA Paper 116010, University Library of Munich, Germany, revised 2022.
    12. 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.
    13. 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.
    14. 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).
    15. Jushan Bai & Jiangtao Duan & Xu Han, 2022. "Likelihood ratio test for structural changes in factor models," Papers 2206.08052, arXiv.org, revised Dec 2023.
    16. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.
    17. 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.
    18. Li, Degui, 2024. "Estimation of Large Dynamic Covariance Matrices: A Selective Review," Econometrics and Statistics, Elsevier, vol. 29(C), pages 16-30.
    19. Matteo Barigozzi & Matteo Luciani, 2024. "Quasi Maximum Likelihood Estimation and Inference of Large Approximate Dynamic Factor Models via the EM algorithm," Finance and Economics Discussion Series 2024-086, Board of Governors of the Federal Reserve System (U.S.).
    20. 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.
    21. 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.
    22. 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.
    23. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    24. 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.
    25. Matteo Barigozzi & Daniele Massacci, 2022. "Modelling Large Dimensional Datasets with Markov Switching Factor Models," Papers 2210.09828, arXiv.org, revised Jun 2024.
    26. 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.
    27. Christis Katsouris, 2023. "Break-Point Date Estimation for Nonstationary Autoregressive and Predictive Regression Models," Papers 2308.13915, arXiv.org.
    28. Thomas Despois & Catherine Doz, 2021. "Identifying and interpreting the factors in factor models via sparsity: Different approaches," PSE Working Papers halshs-02235543, HAL.
    29. 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.
    30. 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.

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

    Cited by:

    1. Lorenzo Trapani & Emily Whitehouse, 2020. "Sequential monitoring for cointegrating regressions," Papers 2003.12182, arXiv.org.
    2. Poncela Blanco, Maria Pilar, 2020. "Factor extraction using Kalman filter and smoothing: this is not just another survey," DES - Working Papers. Statistics and Econometrics. WS 30644, Universidad Carlos III de Madrid. Departamento de Estadística.

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

  16. 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. Francisco Corona & Pilar Poncela & Esther Ruiz, 2020. "Estimating Non-stationary Common Factors: Implications for Risk Sharing," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 37-60, January.

  17. 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. 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.
    2. Barigozzi, Matteo & Brownlees, Christian T., 2018. "Nets: network estimation for time series," LSE Research Online Documents on Economics 90493, London School of Economics and Political Science, LSE Library.
    3. Sudarshan Kumar & Tiziana Di Matteo & Anindya S. Chakrabarti, 2020. "Disentangling shock diffusion on complex networks: Identification through graph planarity," Papers 2001.01518, arXiv.org.
    4. Luca Barbaglia & Christophe Croux & Ines Wilms, 2017. "Volatility Spillovers and Heavy Tails: A Large t-Vector AutoRegressive Approach," Papers 1708.02073, arXiv.org.
    5. 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.
    6. 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.
    7. 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.
    8. Jonas Krampe & Luca Margaritella, 2024. "Global bank network connectedness revisited: What is common, idiosyncratic and when?," Papers 2402.02482, arXiv.org.
    9. 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.
    10. 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.
    11. 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).
    12. Jianqing Fan & Ricardo Masini & Marcelo C. Medeiros, 2021. "Bridging factor and sparse models," Papers 2102.11341, arXiv.org, revised Sep 2022.
    13. Niţoi, Mihai & Pochea, Maria Miruna, 2022. "The nexus between bank connectedness and investors’ sentiment," Finance Research Letters, Elsevier, vol. 44(C).
    14. 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.
    15. 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.
    16. 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.
    17. Ke Miao & Peter C.B. Phillips & Liangjun Su, 2020. "High-Dimensional VARs with Common Factors," Cowles Foundation Discussion Papers 2252, Cowles Foundation for Research in Economics, Yale University.
    18. 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.
    19. Raffaele Mattera & Philipp Otto, 2023. "Network log-ARCH models for forecasting stock market volatility," Papers 2303.11064, arXiv.org.
    20. Daniel Felix Ahelegbey & Paolo Giudici & Shatha Qamhieh Hashem, 2020. "Network VAR models to Measure Financial Contagion," DEM Working Papers Series 178, University of Pavia, Department of Economics and Management.
    21. 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.
    22. 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.
    23. Hai-Chuan Xu & Fredj Jawadi & Jie Zhou & Wei-Xing Zhou, 2022. "Quantifying interconnectedness and centrality ranking among financial institutions with TVP-VAR framework," Post-Print hal-04478741, HAL.
    24. Marco Valerio Geraci & Jean-Yves Gnabo, 2015. "Measuring interconnectedness between financial institutions with Bayesian time-varying vector autoregressions," Working Papers ECARES 2015-51, ULB -- Universite Libre de Bruxelles.
    25. 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).
    26. Herculano, Miguel C. & Lütkebohmert, Eva, 2023. "Investor sentiment and global economic conditions," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 134-152.
    27. Jonas Krampe & Luca Margaritella, 2021. "Factor Models with Sparse VAR Idiosyncratic Components," Papers 2112.07149, arXiv.org, revised May 2022.
    28. 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.
    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. Liao, Gaoke & Li, Yanling & Wang, Mengxin, 2024. "Contagion network of idiosyncratic volatility: Does corporate environmental responsibility matter?," Energy Economics, Elsevier, vol. 129(C).
    31. 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.
    32. 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).
    33. 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).
    34. 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.
    35. 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).
    36. 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.
    37. 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.

  18. 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. 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.
    2. 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.
    3. 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.

  19. 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. 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.
    2. Liqiong Chen & Antonio F. Galvao & Suyong Song, 2021. "Quantile Regression with Generated Regressors," Econometrics, MDPI, vol. 9(2), pages 1-35, April.
    3. Christophe Faugère, 2021. "Connectalism: A new paradigm for human choice," Systems Research and Behavioral Science, Wiley Blackwell, vol. 38(6), pages 866-889, November.
    4. Matteo Barigozzi, 2023. "Quasi Maximum Likelihood Estimation of High-Dimensional Factor Models: A Critical Review," Papers 2303.11777, arXiv.org, revised May 2024.

  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. 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.
    3. Smeekes, Stephan & Wijler, Etienne, 2018. "Macroeconomic forecasting using penalized regression methods," International Journal of Forecasting, Elsevier, vol. 34(3), pages 408-430.
    4. 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.
    5. Alessi, Lucia & Kerssenfischer, Mark, 2016. "The response of asset prices to monetary policy shocks: stronger than thought," Working Paper Series 1967, European Central Bank.
    6. 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.
    7. Dalibor Stevanovic & Rachidi Kotchoni & Maxime Leroux, 2017. "Forecasting economic activity in data-rich environment," CIRANO Working Papers 2017s-05, CIRANO.
    8. Ha, Jongrim & Kose, M. Ayhan & Ohnsorge, Franziska, 2023. "One-stop source: A global database of inflation," Journal of International Money and Finance, Elsevier, vol. 137(C).
    9. 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.
    10. 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.
    11. 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).
    12. Francisco Corona & Pilar Poncela & Esther Ruiz, 2020. "Estimating Non-stationary Common Factors: Implications for Risk Sharing," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 37-60, January.
    13. 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.
    14. 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.
    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. 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. 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.
    2. 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.
    3. Matteo Barigozzi & Marc Hallin, 2018. "Generalized Dynamic Factor Models and Volatilities: Consistency, Rates, and Prediction Intervals," Working Papers ECARES 2018-33, ULB -- Universite Libre de Bruxelles.
    4. Sudarshan Kumar & Tiziana Di Matteo & Anindya S. Chakrabarti, 2020. "Disentangling shock diffusion on complex networks: Identification through graph planarity," Papers 2001.01518, arXiv.org.
    5. 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.
    6. 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.
    7. 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.
    8. 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 Discussion Papers 2020-5, Kiel Institute for the World Economy (IfW Kiel).
    9. Marc Hallin & Luis K. Hotta & João H. G Mazzeu & Carlos Cesar Trucios-Maza & Pedro L. Valls Pereira & Mauricio Zevallos, 2019. "Forecasting Conditional Covariance Matrices in High-Dimensional Time Series: a General Dynamic Factor Approach," Working Papers ECARES 2019-14, ULB -- Universite Libre de Bruxelles.
    10. 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.
    11. 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.
    12. Jianqing Fan & Ricardo Masini & Marcelo C. Medeiros, 2021. "Bridging factor and sparse models," Papers 2102.11341, arXiv.org, revised Sep 2022.
    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. Fabrizio Cipollini & Giampiero M. Gallo, 2018. "Modeling Euro STOXX 50 Volatility with Common and Market–specific Components," Working Paper series 18-26, Rimini Centre for Economic Analysis.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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).
    22. Matteo Barigozzi & Marc Hallin, 2015. "Networks, Dynamic Factors, and the Volatility Analysis of High-Dimensional Financial Series," Working Papers ECARES ECARES 2015-34, ULB -- Universite Libre de Bruxelles.
    23. 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.
    24. 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.
    25. 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).
    26. 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.
    27. 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.
    28. 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.
    29. Xinyu Song, 2019. "Large Volatility Matrix Prediction with High-Frequency Data," Papers 1907.01196, arXiv.org, revised Sep 2019.
    30. 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.
    31. 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.

  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. Matteo Barigozzi & Marc Hallin, 2018. "Generalized Dynamic Factor Models and Volatilities: Consistency, Rates, and Prediction Intervals," Working Papers ECARES 2018-33, ULB -- Universite Libre de Bruxelles.
    2. 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.

  23. 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. Barigozzi, Matteo & Brownlees, Christian T., 2018. "Nets: network estimation for time series," LSE Research Online Documents on Economics 90493, London School of Economics and Political Science, LSE Library.
    2. Demetrescu, Matei & Hacioglu Hoke, Sinem, 2018. "Predictive regressions under asymmetric loss: factor augmentation and model selection," Bank of England working papers 723, Bank of England.
    3. Matteo Barigozzi & Marc Hallin, 2018. "Generalized Dynamic Factor Models and Volatilities: Consistency, Rates, and Prediction Intervals," Working Papers ECARES 2018-33, ULB -- Universite Libre de Bruxelles.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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 Discussion Papers 2020-5, Kiel Institute for the World Economy (IfW Kiel).
    9. Barigozzi, Matteo & Hallin, Marc, 2017. "Generalized dynamic factor models and volatilities: estimation and forecasting," Journal of Econometrics, Elsevier, vol. 201(2), pages 307-321.
    10. Marc Hallin & Luis K. Hotta & João H. G Mazzeu & Carlos Cesar Trucios-Maza & Pedro L. Valls Pereira & Mauricio Zevallos, 2019. "Forecasting Conditional Covariance Matrices in High-Dimensional Time Series: a General Dynamic Factor Approach," Working Papers ECARES 2019-14, ULB -- Universite Libre de Bruxelles.
    11. 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.
    12. Dolado, Juan J & Chen, Liang & Gonzalo, Jesus, 2018. "Quantile Factor Models," CEPR Discussion Papers 12716, C.E.P.R. Discussion Papers.
    13. Elie Bouri & David Gabauer & Rangan Gupta & Aviral Kumar Tiwari, 2020. "Volatility Connectedness of Major Cryptocurrencies: The Role of Investor Happiness," Working Papers 202059, University of Pretoria, Department of Economics.
    14. 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.
    15. 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).
    16. Jianqing Fan & Ricardo Masini & Marcelo C. Medeiros, 2021. "Bridging factor and sparse models," Papers 2102.11341, arXiv.org, revised Sep 2022.
    17. 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).
    18. Fabrizio Cipollini & Giampiero M. Gallo, 2018. "Modeling Euro STOXX 50 Volatility with Common and Market–specific Components," Working Paper series 18-26, Rimini Centre for Economic Analysis.
    19. 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.
    20. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.
    21. 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.
    22. Ma, Yan-Ran & Ji, Qiang & Wu, Fei & Pan, Jiaofeng, 2021. "Financialization, idiosyncratic information and commodity co-movements," Energy Economics, Elsevier, vol. 94(C).
    23. 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).
    24. Matteo Barigozzi & Marc Hallin, 2015. "Networks, Dynamic Factors, and the Volatility Analysis of High-Dimensional Financial Series," Working Papers ECARES ECARES 2015-34, ULB -- Universite Libre de Bruxelles.
    25. 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.
    26. 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.
    27. 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).
    28. 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.
    29. 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.
    30. 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.
    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. 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).
    33. 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.
    34. Xinyu Song, 2019. "Large Volatility Matrix Prediction with High-Frequency Data," Papers 1907.01196, arXiv.org, revised Sep 2019.
    35. 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.
    36. Ruofan Yu & Rong Chen & Han Xiao & Yuefeng Han, 2024. "Dynamic Matrix Factor Models for High Dimensional Time Series," Papers 2407.05624, arXiv.org.
    37. Ergemen, Yunus Emre, 2023. "Parametric estimation of long memory in factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1483-1499.

  24. 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. Barigozzi, Matteo & Brownlees, Christian T., 2018. "Nets: network estimation for time series," LSE Research Online Documents on Economics 90493, London School of Economics and Political Science, LSE Library.
    2. 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.
    3. Harry Vander Elst, 2015. "FloGARCH : Realizing long memory and asymmetries in returns volatility," Working Paper Research 280, National Bank of Belgium.
    4. 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.
    5. 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.
    6. 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.
    7. Giampiero M. Gallo & Edoardo Otranto, 2017. "Combining Sharp and Smooth Transitions in Volatility Dynamics: a Fuzzy Regime Approach," Econometrics Working Papers Archive 2017_05, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    8. Barigozzi, Matteo & Hallin, Marc, 2017. "Generalized dynamic factor models and volatilities: estimation and forecasting," Journal of Econometrics, Elsevier, vol. 201(2), pages 307-321.
    9. 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.
    10. Fabrizio Cipollini & Giampiero M. Gallo, 2021. "Multiplicative Error Models: 20 years on," Papers 2107.05923, arXiv.org.
    11. 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.
    12. Van Nieuwerburgh, Stijn & Lustig, Hanno & Kelly, Bryan & Herskovic, Bernard, 2017. "Firm Volatility in Granual Networks," CEPR Discussion Papers 12284, C.E.P.R. Discussion Papers.
    13. KALNINA, Ilze & TEWOU, Kokouvi, 2015. "Cross-sectional dependence in idiosyncratic volatility," Cahiers de recherche 2015-04, Universite de Montreal, Departement de sciences economiques.
    14. 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.
    15. Fabrizio Cipollini & Giampiero M. Gallo, 2018. "Modeling Euro STOXX 50 Volatility with Common and Market–specific Components," Working Paper series 18-26, Rimini Centre for Economic Analysis.
    16. 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.
    17. 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.
    18. 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.
    19. 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).
    20. Marko Mlikota, 2022. "Cross-Sectional Dynamics Under Network Structure: Theory and Macroeconomic Applications," Papers 2211.13610, arXiv.org, revised Sep 2024.
    21. Zhang, Xingmin & Zhang, Shuai & Lu, Liping, 2022. "The banking instability and climate change: Evidence from China," Energy Economics, Elsevier, vol. 106(C).
    22. Matteo Barigozzi & Marc Hallin, 2015. "Networks, Dynamic Factors, and the Volatility Analysis of High-Dimensional Financial Series," Working Papers ECARES ECARES 2015-34, ULB -- Universite Libre de Bruxelles.
    23. 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.

  25. 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. 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.
    2. Smeekes, Stephan & Wijler, Etienne, 2018. "Macroeconomic forecasting using penalized regression methods," International Journal of Forecasting, Elsevier, vol. 34(3), pages 408-430.
    3. Stefano Soccorsi, 2016. "Measuring Nonfundamentalness for Structural VARs," Working Papers ECARES ECARES 2016-01, ULB -- Universite Libre de Bruxelles.
    4. 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.).
    5. Francisco Corona & Pilar Poncela & Esther Ruiz, 2020. "Estimating Non-stationary Common Factors: Implications for Risk Sharing," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 37-60, January.
    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.).

  26. 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. 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.
    3. 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).
    4. 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.
    5. 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.
    6. Gabriele Fiorentini & Enrique Sentana, 2020. "Discrete Mixtures of Normals Pseudo Maximum Likelihood Estimators of Structural Vector Autoregressions," Working Papers wp2020_2023, CEMFI.
    7. 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.
    8. 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.
    9. Ahelegbey, Daniel Felix & Giudici, Paolo, 2022. "NetVIX — A network volatility index of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
    10. 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 Aug 2024.
    11. Chuliá, Helena & Estévez, Marc & Uribe, Jorge M., 2023. "Systemic political risk," Economic Modelling, Elsevier, vol. 125(C).
    12. 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.
    13. 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.
    14. Matteo Iacopini & Luca Rossini, 2019. "Bayesian nonparametric graphical models for time-varying parameters VAR," Papers 1906.02140, arXiv.org.
    15. 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.
    16. Abbassi, Puriya & Brownlees, Christian & Hans, Christina & Podlich, Natalia, 2016. "Credit risk interconnectedness: What does the market really know?," Discussion Papers 09/2016, Deutsche Bundesbank.
    17. Ben Craig & Martín Saldías, 2016. "Spatial Dependence and Data-Driven Networks of International Banks," IMF Working Papers 2016/184, International Monetary Fund.
    18. 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).
    19. 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.
    20. 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.
    21. Sessi Tokpavi, 2013. "Testing for the Systemically Important Financial Institutions: a Conditional Approach," EconomiX Working Papers 2013-27, University of Paris Nanterre, EconomiX.
    22. Boyao Wu & Difang Huang & Muzi Chen, 2024. "Estimating Contagion Mechanism in Global Equity Market with Time-Zone Effect," Papers 2404.04335, arXiv.org.
    23. 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.
    24. 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).
    25. 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.
    26. Helena Chuliá & Jorge A. Muñoz-Mendoza & Jorge M. Uribe, 2022. ""Energy Firms in Emerging Markets: Systemic Risk and Diversification Opportunities"," IREA Working Papers 202216, University of Barcelona, Research Institute of Applied Economics, revised Oct 2022.
    27. Jonas Krampe & Luca Margaritella, 2024. "Global bank network connectedness revisited: What is common, idiosyncratic and when?," Papers 2402.02482, arXiv.org.
    28. 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.
    29. 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.
    30. 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.
    31. Guðmundsson, Guðmundur Stefán & Brownlees, Christian, 2021. "Detecting groups in large vector autoregressions," Journal of Econometrics, Elsevier, vol. 225(1), pages 2-26.
    32. René Böheim & Philipp Stöllinger, 2021. "Decomposition of the gender wage gap using the LASSO estimator," Applied Economics Letters, Taylor & Francis Journals, vol. 28(10), pages 817-828, June.
    33. Paolo Giudici & Alessandro Spelta, 2013. "Graphical network models for international financial flows," DEM Working Papers Series 052, University of Pavia, Department of Economics and Management.
    34. Jianqing Fan & Ricardo Masini & Marcelo C. Medeiros, 2021. "Bridging factor and sparse models," Papers 2102.11341, arXiv.org, revised Sep 2022.
    35. 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.
    36. 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).
    37. 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).
    38. 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).
    39. 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).
    40. 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.
    41. Niels Gillmann & Ostap Okhrin, 2023. "Adaptive local VAR for dynamic economic policy uncertainty spillover," Papers 2302.02808, arXiv.org.
    42. 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.
    43. 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.
    44. Aldasoro, Iñaki & Angeloni, Ignazio, 2013. "Input-Output-based Measures of Systemic Importance," MPRA Paper 49557, University Library of Munich, Germany.
    45. Ke Miao & Peter C.B. Phillips & Liangjun Su, 2020. "High-Dimensional VARs with Common Factors," Cowles Foundation Discussion Papers 2252, Cowles Foundation for Research in Economics, Yale University.
    46. 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.
    47. Christian Brownlees & Eulàlia Nualart & Yucheng Sun, 2018. "Realized networks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 986-1006, November.
    48. Alain Hecq & Marie Ternes & Ines Wilms, 2021. "Hierarchical Regularizers for Mixed-Frequency Vector Autoregressions," Papers 2102.11780, arXiv.org, revised Mar 2022.
    49. 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.
    50. 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.
    51. 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.
    52. 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).
    53. Dallakyan, Aramayis & Kim, Rakheon & Pourahmadi, Mohsen, 2022. "Time series graphical lasso and sparse VAR estimation," Computational Statistics & Data Analysis, Elsevier, vol. 176(C).
    54. 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.
    55. 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.
    56. Monica Billio & Roberto Casarin & Luca Rossini, 2016. "Bayesian nonparametric sparse VAR models," Papers 1608.02740, arXiv.org, revised Oct 2018.
    57. Bettendorf, Timo & Heinlein, Reinhold, 2019. "Connectedness between G10 currencies: Searching for the causal structure," Discussion Papers 06/2019, Deutsche Bundesbank.
    58. 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.
    59. Andrea Bastianin & Chiara Casoli & Marzio Galeotti, 2023. "The connectedness of Energy Transition Metals," Working Papers 2023.11, Fondazione Eni Enrico Mattei.
    60. 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.
    61. 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.
    62. Zhang, Xingmin & Zhang, Shuai & Lu, Liping, 2022. "The banking instability and climate change: Evidence from China," Energy Economics, Elsevier, vol. 106(C).
    63. 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.
    64. 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.
    65. Hai-Chuan Xu & Fredj Jawadi & Jie Zhou & Wei-Xing Zhou, 2022. "Quantifying interconnectedness and centrality ranking among financial institutions with TVP-VAR framework," Post-Print hal-04478741, HAL.
    66. 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.
    67. 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).
    68. Nicola, Giancarlo & Cerchiello, Paola & Aste, Tomaso, 2020. "Information network modeling for U.S. banking systemic risk," LSE Research Online Documents on Economics 107563, London School of Economics and Political Science, LSE Library.
    69. 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.
    70. 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.
    71. Jonas Krampe & Luca Margaritella, 2021. "Factor Models with Sparse VAR Idiosyncratic Components," Papers 2112.07149, arXiv.org, revised May 2022.
    72. Agosto, Arianna & Ahelegbey, Daniel Felix & Giudici, Paolo, 2020. "Tree Networks to assess Financial Contagion," MPRA Paper 107066, University Library of Munich, Germany.
    73. Timo Bettendorf & Reinhold Heinlein, 2023. "Connectedness between G10 currencies: Searching for the causal structure," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3938-3959, October.
    74. 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.
    75. 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.
    76. 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).
    77. 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.
    78. 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.
    79. 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.
    80. 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.
    81. 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.

  27. 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. Laura E. Jackson & Michael T. Owyang & Sarah Zubairy, 2017. "Debt and Stabilization Policy: Evidence from a Euro Area FAVAR," Working Papers 2017-22, Federal Reserve Bank of St. Louis.
    3. 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.
    4. 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.
    5. Georgios Georgiadis & Martina Jancokova, 2017. "Financial Globalisation, Monetary Policy Spillovers and Macro-modelling: Tales from 1001 Shocks," GRU Working Paper Series GRU_2017_008, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    6. 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.).
    7. 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.
    8. 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.
    9. 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.
    10. Mattia Guerini & Duc Thi Luu & Mauro Napoletano, 2019. "Synchronization Patterns in the European Union," LEM Papers Series 2019/33, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    11. 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).
    12. Flaccadoro, Marco, 2024. "Exchange rate pass-through in small, open, commodity-exporting economies: Lessons from Canada," Journal of International Economics, Elsevier, vol. 148(C).
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. Harald Badinger & Stefan Schiman, 2020. "Measuring Monetary Policy with Residual Sign Restrictions at Known Shock Dates," Department of Economics Working Papers wuwp300, Vienna University of Economics and Business, Department of Economics.
    19. 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.
    20. Giancarlo Corsetti & Joao B. Duarte & Samuel Mann, 2020. "One Money, Many Markets: Monetary Transmission and Housing Financing in the Euro Area," IMF Working Papers 2020/108, International Monetary Fund.
    21. 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.
    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. Mattia Guerini & Duc Thi Luu & Mauro Napoletano, 2022. "Synchronization patterns in the European Union," SciencePo Working papers Main hal-04531116, HAL.
    24. 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.
    25. 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.
    26. Potjagailo, Galina & Wolters, Maik H, 2020. "Global financial cycles since 1880," Bank of England working papers 867, Bank of England.
    27. Nikolay Hristov & Oliver Hülsewig & Thomas Siemsen & Timo Wollmershäuser, 2019. "Restoring euro area monetary transmission: Which role for government bond rates?," Empirical Economics, Springer, vol. 57(3), pages 991-1021, September.
    28. Neri, Stefano & Nobili, Andrea & Conti, Antonio M., 2017. "Low inflation and monetary policy in the euro area," Working Paper Series 2005, European Central Bank.
    29. 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.
    30. Norhana Endut & James Morley & Pao-Lin Tien, 2018. "The changing transmission mechanism of US monetary policy," Empirical Economics, Springer, vol. 54(3), pages 959-987, May.
    31. 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.
    32. 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.
    33. Michael Pfarrhofer & Anna Stelzer, 2019. "The international effects of central bank information shocks," Papers 1912.03158, arXiv.org.
    34. 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.
    35. 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.
    36. 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.
    37. von Borstel, Julia & Eickmeier, Sandra & Krippner, Leo, 2015. "The interest rate pass-through in the euro area during the sovereign debt crisis," Discussion Papers 10/2015, Deutsche Bundesbank.
    38. Ute Volz & Martin Mandler & Michael Scharnagl, 2016. "Heterogeneity in Euro Area Monetary Policy Transmission: Results from a large Multi-Country BVAR," EcoMod2016 9609, EcoMod.
    39. 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.
    40. Gabe de Bondt, 2017. "Confidence and monetary policy transmission," EcoMod2017 10197, EcoMod.
    41. 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.
    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. 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.
    44. 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.
    45. Giancarlo Corsetti & Joao B Duarte & Samuel Mann, 2022. "One Money, Many Markets [Fixed Rate Versus Adjustable Rate Mortgages: Evidence from Euro Area Banks]," Journal of the European Economic Association, European Economic Association, vol. 20(1), pages 513-548.
    46. 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).
    47. Conti, Antonio M., 2021. "Resurrecting the Phillips Curve in Low-Inflation Times," Economic Modelling, Elsevier, vol. 96(C), pages 172-195.
    48. Max Hanisch, 2017. "US Monetary Policy and the Euro Area," Discussion Papers of DIW Berlin 1701, DIW Berlin, German Institute for Economic Research.
    49. Forni, Mario & Gambetti, Luca & Lippi, Marco & Sala, Luca, 2020. "Common Component Structural VARs," CEPR Discussion Papers 15529, C.E.P.R. Discussion Papers.
    50. Hanisch, Max, 2019. "US monetary policy and the euro area," Journal of Banking & Finance, Elsevier, vol. 100(C), pages 77-96.
    51. 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.
    52. 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.
    53. 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.
    54. 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.
    55. Simona Hašková & Marek Vochozka, 2018. "Duality in Cyclical Trends in European Union Confirmed," SAGE Open, , vol. 8(1), pages 21582440177, January.
    56. Lukas Berend & Jan Pruser, 2024. "The Transmission of Monetary Policy via Common Cycles in the Euro Area," Papers 2410.05741, arXiv.org, revised Oct 2024.
    57. 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).
    58. 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.
    59. 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.
    60. 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).
    61. 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.

  28. 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. 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.
    3. 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.
    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. 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.

  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 & 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. 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).
    2. Yuichi Ikeda & Hiroshi Iyetomi, 2018. "Trade Network Reconstruction and Simulation with Changes in Trade Policy," Papers 1806.00605, arXiv.org.
    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.
    4. 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.
    5. 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.
    6. Giorgio Fagiolo & Tiziano Squartini & Diego Garlaschelli, 2013. "Null models of economic networks: the case of the world trade web," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 75-107, April.
    7. 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.
    8. 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).
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. Marco Duenas & Giorgio Fagiolo, 2011. "Modeling the International-Trade Network: A Gravity Approach," LEM Papers Series 2011/25, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    20. 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.
    21. Nicole Palan & Nadia Simoes & Nuno Crespo, 2019. "Measuring Fifty Years of Trade Globalization," Graz Economics Papers 2019-14, University of Graz, Department of Economics.
    22. 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.
    23. 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.
    24. 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.
    25. Yuichi Ikeda, 2020. "An Interacting Agent Model of Economic Crisis," Papers 2001.11843, arXiv.org.
    26. 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.
    27. Juan Lucio & Raúl Mínguez & Asier Minondo & Francisco Requena, 2016. "Networks and the Dynamics of Firms' Export Portfolio: Evidence for Mexico," The World Economy, Wiley Blackwell, vol. 39(5), pages 708-736, May.
    28. 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).
    29. 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).
    30. 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.
    31. Matteo Barigozzi & Marc Hallin, 2015. "Networks, Dynamic Factors, and the Volatility Analysis of High-Dimensional Financial Series," Working Papers ECARES ECARES 2015-34, ULB -- Universite Libre de Bruxelles.
    32. 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.
    33. 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.
    34. 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.
    35. 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.
    36. 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.
    37. 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.
    38. 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).
    39. 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.
    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. 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).
    42. 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.
    43. 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.
    44. 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).
    45. 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.
    46. 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.
    47. 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.
    48. 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).
    49. 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).
    50. Stefania Vitali & Stefano Battiston, 2014. "The Community Structure of the Global Corporate Network," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-13, August.
    51. 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.
    52. 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.
    53. 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.
    54. 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).
    55. 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.
    56. 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.
    57. 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.
    58. 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.

  31. 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. 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.
    2. Bernard Herskovic & Bryan T. Kelly & Hanno Lustig & Stijn Van Nieuwerburgh, 2014. "The Common Factor in Idiosyncratic Volatility: Quantitative Asset Pricing Implications," NBER Working Papers 20076, National Bureau of Economic Research, Inc.
    3. Van Nieuwerburgh, Stijn & Lustig, Hanno & Kelly, Bryan & Herskovic, Bernard, 2017. "Firm Volatility in Granual Networks," CEPR Discussion Papers 12284, C.E.P.R. Discussion Papers.
    4. Matteo Luciani & David Veredas, 2012. "A model for vast panels of volatilities," Working Papers 1230, Banco de España.
    5. 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.

  32. 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. 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.
    3. 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.

  33. 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. 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.
    3. 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.
    4. Xisong Jin & Francisco Nadal De Simone, 2013. "Banking Systemic Vulnerabilities: A Tail-risk Dynamic CIMDO Approach," BCL working papers 82, Central Bank of Luxembourg.
    5. 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.
    6. 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.
    7. Xisong Jin & Francisco Nadal De Simone, 2017. "Systemic Financial Sector and Sovereign Risks," BCL working papers 109, Central Bank of Luxembourg.
    8. Travaglini, Guido, 2011. "Principal Components and Factor Analysis. A Comparative Study," MPRA Paper 35486, University Library of Munich, Germany.
    9. 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.
    10. Xisong Jin & Francisco Nadal De Simone, 2015. "Investment funds? vulnerabilities: A tail-risk dynamic CIMDO approach," BCL working papers 95, 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.

  34. 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).

  35. 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. 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.
    2. 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.
    3. 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.
    4. Barigozzi, Matteo & Hallin, Marc, 2017. "Generalized dynamic factor models and volatilities: estimation and forecasting," Journal of Econometrics, Elsevier, vol. 201(2), pages 307-321.
    5. Marc Hallin & Luis K. Hotta & João H. G Mazzeu & Carlos Cesar Trucios-Maza & Pedro L. Valls Pereira & Mauricio Zevallos, 2019. "Forecasting Conditional Covariance Matrices in High-Dimensional Time Series: a General Dynamic Factor Approach," Working Papers ECARES 2019-14, ULB -- Universite Libre de Bruxelles.
    6. 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.
    7. 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.
    8. Chevallier, Julien, 2011. "Macroeconomics, finance, commodities: Interactions with carbon markets in a data-rich model," Economic Modelling, Elsevier, vol. 28(1-2), pages 557-567, January.
    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).
    10. 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.
    11. Matteo Luciani & David Veredas, 2012. "A model for vast panels of volatilities," Working Papers 1230, Banco de España.
    12. 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.
    13. 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.

  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. Aldasoro, Iñaki & Alves, Iván, 2018. "Multiplex interbank networks and systemic importance: An application to European data," Journal of Financial Stability, Elsevier, vol. 35(C), pages 17-37.
    2. 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.
    3. Yuichi Ikeda & Hiroshi Iyetomi, 2018. "Trade Network Reconstruction and Simulation with Changes in Trade Policy," Papers 1806.00605, arXiv.org.
    4. Peiteng Shi & Jiang Zhang & Bo Yang & Jingfei Luo, 2014. "Hierarchicality of Trade Flow Networks Reveals Complexity of Products," Papers 1401.3103, arXiv.org.
    5. 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.
    6. 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).
    7. 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.
    8. Bartesaghi, Paolo & Clemente, Gian Paolo & Grassi, Rosanna & Luu, Duc Thi, 2022. "The multilayer architecture of the global input-output network and its properties," Journal of Economic Behavior & Organization, Elsevier, vol. 204(C), pages 304-341.
    9. Giorgio Fagiolo & Tiziano Squartini & Diego Garlaschelli, 2013. "Null models of economic networks: the case of the world trade web," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 75-107, April.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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).
    16. Vivek Kandiah & Hubert Escaith & Dima L. Shepelyansky, 2015. "Google matrix of the world network of economic activities," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 88(7), pages 1-20, July.
    17. Giudici, Paolo & Huang, Bihong & Spelta, Alessandro, 2018. "Trade Networks and Economic Fluctuations in Asia," ADBI Working Papers 832, Asian Development Bank Institute.
    18. 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.
    19. 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.
    20. 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.
    21. Marco Duenas & Giorgio Fagiolo, 2011. "Modeling the International-Trade Network: A Gravity Approach," LEM Papers Series 2011/25, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    22. 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.
    23. 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.
    24. 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.
    25. 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).
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    31. 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.
    32. Yuichi Ikeda, 2020. "An Interacting Agent Model of Economic Crisis," Papers 2001.11843, arXiv.org.
    33. 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.
    34. 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.
    35. 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.
    36. Shi, Qing & Sun, Xiaoqi & Xu, Man & Wang, Mengjiao, 2022. "The multiplex network structure of global cobalt industry chain," Resources Policy, Elsevier, vol. 76(C).
    37. 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.
    38. Shen, Xinran & Lovrić, Marko, 2022. "Structural determinants of global trade in graphic paper and pulp products," Forest Policy and Economics, Elsevier, vol. 134(C).
    39. 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).
    40. 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.
    41. 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.
    42. 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.
    43. 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.
    44. Matteo Barigozzi & Marc Hallin, 2015. "Networks, Dynamic Factors, and the Volatility Analysis of High-Dimensional Financial Series," Working Papers ECARES ECARES 2015-34, ULB -- Universite Libre de Bruxelles.
    45. Ceriotti, C. & Della Torre, M. & Grassetti, F. & Marazzina, D., 2023. "Should I have closed? A multiplex network approach for the short-term economic effect of Covid-19 containment measures in the EU," Socio-Economic Planning Sciences, Elsevier, vol. 90(C).
    46. Luca De Benedictis & Silvia Nenci & Gianluca Santoni & Lucia Tajoli & Claudio Vicarelli, 2013. "Network Analysis of World Trade using the BACI-CEPII dataset," Working Papers 2013-24, CEPII research center.
    47. Grazzini, Jakob & Spelta, Alessandro, 2022. "An empirical analysis of the global input–output network and its evolution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
    48. 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.
    49. 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).
    50. Leonardo Ermann & Dima L. Shepelyansky, 2015. "Google matrix analysis of the multiproduct world trade network," Papers 1501.03371, arXiv.org.
    51. Kim, Min Jae & Kim, Sehyun & Jo, Yong Hwan & Kim, Soo Yong, 2011. "Dependence structure of the commodity and stock markets, and relevant multi-spread strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(21), pages 3842-3854.
    52. 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.
    53. 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.
    54. 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).
    55. 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.
    56. 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.
    57. C'elestin Coquid'e & Jos'e Lages & Dima L. Shepelyansky, 2020. "Crisis contagion in the world trade network," Papers 2002.07100, arXiv.org.
    58. Célestin Coquidé & José Lages & Dima Shepelyansky, 2020. "Interdependence of sectors of economic activities for world countries from the reduced Google matrix analysis of WTO data," Post-Print hal-02132487, HAL.
    59. 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.
    60. 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.
    61. Deepika Srivastava & M. Rahul, 2024. "Network analysis of trade and FDI," SN Business & Economics, Springer, vol. 4(1), pages 1-27, January.
    62. 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).
    63. V. Kandiah & H. Escaith & D. L. Shepelyansky, 2015. "Contagion effects in the world network of economic activities," Papers 1507.03278, arXiv.org.
    64. 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.
    65. Marco Bardoscia & Paolo Barucca & Stefano Battiston & Fabio Caccioli & Giulio Cimini & Diego Garlaschelli & Fabio Saracco & Tiziano Squartini & Guido Caldarelli, 2021. "The Physics of Financial Networks," Papers 2103.05623, arXiv.org.
    66. 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.
    67. Di Vece, Marzio & Garlaschelli, Diego & Squartini, Tiziano, 2023. "Reconciling econometrics with continuous maximum-entropy network models," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    68. 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.
    69. 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.
    70. 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.
    71. C'elestin Coquid'e & Jos'e Lages & Dima L. Shepelyansky, 2023. "Prospects of BRICS currency dominance in international trade," Papers 2305.00585, arXiv.org.
    72. Yanni Huang & Taha Hossein Rashidi & Lauren Gardner, 2018. "Modelling the global maritime container network," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 20(3), pages 400-420, September.
    73. 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.
    74. 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).
    75. 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.
    76. 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.
    77. 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.
    78. 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).

  37. 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. Joachim Kaldasch, 2012. "Evolutionary Model of the Personal Income Distribution," Papers 1203.6507, arXiv.org.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    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.

  38. 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. Gianluca Cubadda & Francesco Giancaterini & Alain Hecq & Joann Jasiak, 2023. "Optimization of the Generalized Covariance Estimator in Noncausal Processes," Papers 2306.14653, arXiv.org, revised Jan 2024.
    2. G. Fagiolo & A. Roventini, 2009. "On the Scientific Status of Economic Policy: A Tale of Alternative Paradigms," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 6.
    3. Paul Beaudry & Franck Portier, 2014. "News Driven Business Cycles: Insights and Challenges," 2014 Meeting Papers 289, Society for Economic Dynamics.
    4. Lanne, Markku & Saikkonen, Pentti, 2009. "Noncausal vector autoregression," Bank of Finland Research Discussion Papers 18/2009, Bank of Finland.
    5. Giorgio Fagiolo & Andrea Roventini, 2012. "Macroeconomic Policy in DSGE and Agent-Based Models," Working Papers 07/2012, University of Verona, Department of Economics.
    6. 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.
    7. Fève, Patrick & Jidoud, Ahmat, 2012. "Identifying News Shocks from SVARs," TSE Working Papers 12-287, Toulouse School of Economics (TSE).
    8. Helmut Lütkepohl, 2012. "Fundamental Problems with Nonfundamental Shocks," Discussion Papers of DIW Berlin 1230, DIW Berlin, German Institute for Economic Research.
    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).

  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 & 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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).
    7. Matteo Luciani, 2012. "Monetary Policy and the Housing Market: A Structural Factor Analysis," Working Papers ECARES ECARES 2012-035, ULB -- Universite Libre de Bruxelles.
    8. 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.
    9. 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.
    10. 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.
    11. Christian Menden & Christian R. Proaño, 2017. "Dissecting the financial cycle with dynamic factor models," Quantitative Finance, Taylor & Francis Journals, vol. 17(12), pages 1965-1994, December.
    12. Gao, Quansheng & Hu, Chengjun, 2009. "Dynamic mortality factor model with conditional heteroskedasticity," Insurance: Mathematics and Economics, Elsevier, vol. 45(3), pages 410-423, December.
    13. 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.
    14. 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.
    15. 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.
    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. Le, Vu & Wang, Qing, 2014. "Robust thresholding for Diffusion Index forecast," Economics Letters, Elsevier, vol. 125(1), pages 52-56.
    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. 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. 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.
    2. 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.
    3. Scharfenaker, Ellis, 2020. "Implications of quantal response statistical equilibrium," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    4. Barigozzi, Matteo & Alessi, Lucia & Capasso, Marco & Fagiolo, Giorgio, 2009. "The distribution of households consumption-expenditure budget shares," Working Paper Series 1061, European Central Bank.
    5. Jan Schulz & Daniel M. Mayerhoffer, 2022. "A Network Approach to Consumption," Papers 2203.14259, arXiv.org, revised Apr 2022.
    6. Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2020. "Exploiting ergodicity in forecasts of corporate profitability," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    7. 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.
    8. 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.
    9. 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.
    10. Irle, Albrecht & Milaković, Mishael & Alfarano, Simone & Kauschke, Jonas, 2008. "A Statistical Equilibrium Model of Competitive Firms," Economics Working Papers 2008-10, Christian-Albrechts-University of Kiel, Department of Economics.
    11. Mundt, Philipp & Oh, Ilfan, 2019. "Asymmetric competition, risk, and return distribution," Economics Letters, Elsevier, vol. 179(C), pages 29-32.

  41. 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. 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.
    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. 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.
    4. 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.
    5. 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.
    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. 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.

  2. 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. 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.
    2. 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.
    3. 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. 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.
  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, 2023. "The Vector Error Correction Index Model: Representation, Estimation and Identification," CEIS Research Paper 556, Tor Vergata University, CEIS, revised 04 Apr 2023.

  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. 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.
    4. Poncela Blanco, Maria Pilar, 2020. "Factor extraction using Kalman filter and smoothing: this is not just another survey," DES - Working Papers. Statistics and Econometrics. WS 30644, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. 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.
    6. Davide Brignone & Alessandro Franconi & Marco Mazzali, 2023. "Robust Impulse Responses using External Instruments: the Role of Information," Papers 2307.06145, arXiv.org.
    7. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.
    8. Donato Ceci & Andrea Silvestrini, 2022. "Nowcasting the state of the Italian economy: the role of financial markets," Temi di discussione (Economic working papers) 1362, Bank of Italy, Economic Research and International Relations Area.
    9. 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.
    10. Haroon Mumtaz & Roman Sustek, 2023. "Global house prices since 1950," Discussion Papers 2307, Centre for Macroeconomics (CFM).
    11. 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.
    12. 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.).
    13. 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.
    14. Gianluca Cubadda & Marco Mazzali, 2023. "The Vector Error Correction Index Model: Representation, Estimation and Identification," CEIS Research Paper 556, Tor Vergata University, CEIS, revised 04 Apr 2023.
    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 & 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.
  9. 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.
  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. Poncela Blanco, Maria Pilar, 2020. "Factor extraction using Kalman filter and smoothing: this is not just another survey," DES - Working Papers. Statistics and Econometrics. WS 30644, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Sergej Gričar & Štefan Bojnec, 2021. "Technical Analysis of Tourism Price Process in the Eurozone," JRFM, MDPI, vol. 14(11), pages 1-25, October.
    5. Donato Ceci & Andrea Silvestrini, 2022. "Nowcasting the state of the Italian economy: the role of financial markets," Temi di discussione (Economic working papers) 1362, Bank of Italy, Economic Research and International Relations Area.
    6. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.
    7. 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.
    8. 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.
    9. 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.
    10. 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.

  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. 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.
  17. 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.
  18. 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.
  19. 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.
  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. Fornaro, Paolo, 2016. "Predicting Finnish economic activity using firm-level data," International Journal of Forecasting, Elsevier, vol. 32(1), pages 10-19.
    2. Stella, Andrea, 2015. "Firm dynamics and the origins of aggregate fluctuations," Journal of Economic Dynamics and Control, Elsevier, vol. 55(C), pages 71-88.
    3. 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.

  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. 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.
  25. 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. Weifeng Jin, 2023. "Quantile Autoregression-based Non-causality Testing," Papers 2301.02937, arXiv.org.
    2. Stefano Soccorsi, 2016. "Measuring Nonfundamentalness for Structural VARs," Working Papers ECARES ECARES 2016-01, ULB -- Universite Libre de Bruxelles.
    3. 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.
    4. Alessi, Lucia & Kerssenfischer, Mark, 2016. "The response of asset prices to monetary policy shocks: stronger than thought," Working Paper Series 1967, European Central Bank.
    5. Iskrev, Nikolay, 2019. "On the sources of information about latent variables in DSGE models," European Economic Review, Elsevier, vol. 119(C), pages 318-332.
    6. Francesco Giancaterini & Alain Hecq, 2020. "Inference in mixed causal and noncausal models with generalized Student's t-distributions," Papers 2012.01888, arXiv.org, revised Nov 2022.
    7. Nektarios A. Michail & Christos S. Savva & Demetris Koursaros, 2017. "Size Effects of Fiscal Policy and Business Confidence in the Euro Area," IJFS, MDPI, vol. 5(4), pages 1-15, November.
    8. Ellahie, Atif & Ricco, Giovanni, 2017. "Government purchases reloaded: Informational insufficiency and heterogeneity in fiscal VARs," Journal of Monetary Economics, Elsevier, vol. 90(C), pages 13-27.
    9. Raffaella Giacomini, 2013. "The relationship between DSGE and VAR models," CeMMAP working papers 21/13, Institute for Fiscal Studies.
    10. Nikolay Iskrev, 2021. "Spectral decomposition of the information about latent variables in dynamic macroeconomic models," Working Papers w202105, Banco de Portugal, Economics and Research Department.
    11. Lanne, Markku & Saikkonen, Pentti, 2009. "Noncausal vector autoregression," Bank of Finland Research Discussion Papers 18/2009, Bank of Finland.
    12. Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.
    13. Hamidi Sahneh, Mehdi, 2015. "Are the shocks obtained from SVAR fundamental?," MPRA Paper 65126, University Library of Munich, Germany.
    14. Giovanni Angelini & Marco M. Sorge, 2021. "Under the same (Chole)sky: DNK models, timing restrictions and recursive identification of monetary policy shocks," Working Papers wp1160, Dipartimento Scienze Economiche, Universita' di Bologna.
    15. Lof Matthijs, 2013. "Noncausality and asset pricing," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(2), pages 211-220, April.
    16. Hecq, Alain & Issler, João Victor & Telg, Sean, 2017. "Mixed Causal-Noncausal Autoregressions with Strictly Exogenous Regressors," MPRA Paper 80767, University Library of Munich, Germany.
    17. Hecq, Alain & Telg, Sean & Lieb, Lenard, 2016. "Do Seasonal Adjustments Induce Noncausal Dynamics in Inflation Rates?," MPRA Paper 74922, University Library of Munich, Germany, revised 04 Nov 2016.
    18. Marco M. Sorge, 2013. "On the Fundamentalness of Nonfundamentalness in DSGE Models," CSEF Working Papers 340, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    19. Antonio Aguirre & Ignacio N. Lobato, 2024. "Evidence of non-fundamentalness in OECD capital stocks," Empirical Economics, Springer, vol. 67(2), pages 761-772, August.
    20. Fève, Patrick & Jidoud, Ahmat, 2012. "Identifying News Shocks from SVARs," TSE Working Papers 12-287, Toulouse School of Economics (TSE).
    21. Nyholm, Juho, 2017. "Residual-based diagnostic tests for noninvertible ARMA models," MPRA Paper 81033, University Library of Munich, Germany.
    22. Lof, Matthijs, 2013. "Essays on Expectations and the Econometrics of Asset Pricing," MPRA Paper 59064, University Library of Munich, Germany.
    23. Kang, Jihye & Kim, Soyoung, 2022. "Government spending news and surprise shocks: It’s the timing and persistence," Journal of Macroeconomics, Elsevier, vol. 73(C).
    24. Alain Hecq & Li Sun, 2019. "Identification of Noncausal Models by Quantile Autoregressions," Papers 1904.05952, arXiv.org.
    25. Lobato, Ignacio N. & Velasco, Carlos, 2018. "Efficiency improvements for minimum distance estimation of causal and invertible ARMA models," Economics Letters, Elsevier, vol. 162(C), pages 150-152.
    26. Fanelli, Luca & Sorge, Marco M., 2017. "Indeterminate forecast accuracy under indeterminacy," Journal of Macroeconomics, Elsevier, vol. 53(C), pages 57-70.
    27. J. Baron & J. Schmidt, 2014. "Technological Standardization, Endogenous Productivity and Transitory Dynamics," Working papers 503, Banque de France.
    28. Martin Hodula & Lukas Pfeifer, 2018. "The Impact of Credit Booms and Economic Policy on Labour Productivity: A Sectoral Analysis," ACTA VSFS, University of Finance and Administration, vol. 12(1), pages 10-42.
    29. Paul Levine & Joseph Pearlman & Stephen Wright & Bo Yang, 2023. "Imperfect Information and Hidden Dynamics," School of Economics Discussion Papers 1223, School of Economics, University of Surrey.
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    32. Luca Fanelli & Marco M. Sorge, 2015. "Indeterminacy, Misspecification and Forecastability: Good Luck in Bad Policy?," CSEF Working Papers 402, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    33. Pellényi, Gábor, 2012. "A monetáris politika hatása a magyar gazdaságra. Elemzés strukturális, dinamikus faktormodellel [The sectoral effects of monetary policy in Hungary: a structural factor]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(3), pages 263-284.
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    2. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2013. "Dynamic factor models: A review of the literature," Post-Print hal-01385974, HAL.
    3. Gonzalez Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir, 2021. "Expecting the unexpected: economic growth under stress," DES - Working Papers. Statistics and Econometrics. WS 32148, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Smeekes, Stephan & Wijler, Etienne, 2018. "Macroeconomic forecasting using penalized regression methods," International Journal of Forecasting, Elsevier, vol. 34(3), pages 408-430.
    5. Forni, Mario & Giovannelli, Alessandro & Lippi, Marco & Soccorsi, Stefano, 2016. "Dynamic Factor model with infinite dimensional factor space: forecasting," CEPR Discussion Papers 11161, C.E.P.R. Discussion Papers.
    6. Leu, Shawn C.-Y. & Robertson, Mari L., 2021. "Mortgage credit volumes and monetary policy after the Great Recession," Economic Modelling, Elsevier, vol. 94(C), pages 483-500.
    7. Alain Kabundi & Elmarie Nel & Franz Ruch, 2016. "Nowcasting Real GDP growth in South Africa," Working Papers 581, Economic Research Southern Africa.
    8. Ms. Deniz O Igan & Alain N. Kabundi & Mr. Francisco d Nadal De Simone & Ms. Natalia T. Tamirisa, 2013. "Monetary Policy and Balance Sheets," IMF Working Papers 2013/158, International Monetary Fund.
    9. 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.
    10. Marc Hallin & Marcelo Moreira J. & Alexei Onatski, 2013. "Group Invariance, Likelihood Ratio Tests, and the Incidental Parameter Problem in a High-Dimensional Linear Model," Working Papers ECARES ECARES 2013-04, ULB -- Universite Libre de Bruxelles.
    11. Oguzhan Cepni & I. Ethem Guney & Norman R. Swanson, 2020. "Forecasting and nowcasting emerging market GDP growth rates: The role of latent global economic policy uncertainty and macroeconomic data surprise factors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 18-36, January.
    12. Demetrescu, Matei & Hacioglu Hoke, Sinem, 2018. "Predictive regressions under asymmetric loss: factor augmentation and model selection," Bank of England working papers 723, Bank of England.
    13. Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," CIRANO Working Papers 2021s-09, CIRANO.
    14. Freyaldenhoven, Simon, 2022. "Factor models with local factors — Determining the number of relevant factors," Journal of Econometrics, Elsevier, vol. 229(1), pages 80-102.
    15. Alessi, Lucia & Kerssenfischer, Mark, 2016. "The response of asset prices to monetary policy shocks: stronger than thought," Working Paper Series 1967, European Central Bank.
    16. Tommaso Proietti & Alessandro Giovannelli, 2020. "Nowcasting Monthly GDP with Big Data: a Model Averaging Approach," CEIS Research Paper 482, Tor Vergata University, CEIS, revised 12 May 2020.
    17. Mustafa Çakir & Alain Kabundi, 2017. "Transmission of China's Shocks to the BRIS Countries," South African Journal of Economics, Economic Society of South Africa, vol. 85(3), pages 430-454, September.
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    19. 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.
    20. Javier Emmanuel Anguiano Pita & Antonio Ruiz Porras, 2020. "Market dynamics and integration of the financial markets of the NAFTA countries," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 92, pages 67-100, Enero-Jun.
    21. Afanasyeva, Elena & Güntner, Jochen, 2014. "Lending standards, credit booms and monetary policy," IMFS Working Paper Series 85, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    22. 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.).
    23. Jianqing Fan & Yuan Liao & Martina Mincheva, 2013. "Large covariance estimation by thresholding principal orthogonal complements," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(4), pages 603-680, September.
    24. Hallin, Marc & Lippi, Marco, 2013. "Factor models in high-dimensional time series—A time-domain approach," Stochastic Processes and their Applications, Elsevier, vol. 123(7), pages 2678-2695.
    25. Nathan Bedock & Dalibor Stevanović, 2017. "An empirical study of credit shock transmission in a small open economy," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 50(2), pages 541-570, May.
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    28. Julien Chevallier & Florian Ielpo & Ling-Ni Boon, 2013. "Common risk factors in commodities," Economics Bulletin, AccessEcon, vol. 33(4), pages 2801-2816.
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    30. 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.
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    34. Kappler, Marcus & Schleer, Frauke, 2017. "A financially stressed euro area," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 11, pages 1-37.
    35. Fernando Nascimento de Oliveira & Wagner Piazza Gaglianone, 2019. "Expectations Anchoring Indexes for Brazil using Kalman Filter: exploring signals of inflation anchoring in the long term," Working Papers Series 497, Central Bank of Brazil, Research Department.
    36. Lombardi, Marco J. & Maier, Philipp, 2011. "Forecasting economic growth in the euro area during the Great Moderation and the Great Recession," Working Paper Series 1379, European Central Bank.
    37. Andrew S. Duncan & Alain Kabundi, 2014. "Global Financial Crises and Time-Varying Volatility Comovement in World Equity Markets," South African Journal of Economics, Economic Society of South Africa, vol. 82(4), pages 531-550, December.
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    39. 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.
    40. Jianqing Fan & Yuan Liao & Han Liu, 2016. "An overview of the estimation of large covariance and precision matrices," Econometrics Journal, Royal Economic Society, vol. 19(1), pages 1-32, February.
    41. Barigozzi, Matteo & Hallin, Marc, 2017. "Generalized dynamic factor models and volatilities: estimation and forecasting," Journal of Econometrics, Elsevier, vol. 201(2), pages 307-321.
    42. Marc Hallin & Luis K. Hotta & João H. G Mazzeu & Carlos Cesar Trucios-Maza & Pedro L. Valls Pereira & Mauricio Zevallos, 2019. "Forecasting Conditional Covariance Matrices in High-Dimensional Time Series: a General Dynamic Factor Approach," Working Papers ECARES 2019-14, ULB -- Universite Libre de Bruxelles.
    43. Rangan Gupta & Faaiqa Hartley, 2013. "The Role of Asset Prices in Forecasting Inflation and Output in South Africa," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 12(3), pages 239-291, December.
    44. Rangan Gupta & Mampho P. Modise & Josine Uwilingiye, 2016. "Out-of-Sample Equity Premium Predictability in South Africa: Evidence from a Large Number of Predictors," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 52(8), pages 1935-1955, August.
    45. 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.
    46. Olivier Fortin-Gagnon & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "A Large Canadian Database for Macroeconomic Analysis," Working Papers 20-07, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
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    48. Chou, Ray Yeutien & Yen, Tso-Jung & Yen, Yu-Min, 2020. "Macroeconomic forecasting using approximate factor models with outliers," International Journal of Forecasting, Elsevier, vol. 36(2), pages 267-291.
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    51. Matteo Luciani, 2012. "Monetary Policy and the Housing Market: A Structural Factor Analysis," Working Papers ECARES ECARES 2012-035, ULB -- Universite Libre de Bruxelles.
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    64. Matteo Barigozzi & Lorenzo Trapani, 2018. "Sequential testing for structural stability in approximate factor models," Discussion Papers 18/04, University of Nottingham, Granger Centre for Time Series Econometrics.
    65. Matteo Barigozzi & Antonio M. Conti & Matteo Luciani, 2013. "Do euro area countries respond asymmetrically to the common monetary policy?," Temi di discussione (Economic working papers) 923, Bank of Italy, Economic Research and International Relations Area.
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  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.
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