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Paolo Zaffaroni

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.

Working papers

  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.

    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. Maddalena Cavicchioli & Mario Forni & Marco Lippi & Paolo zaffaroni, 2016. "Eigenvalue Ratio Estimators for the Number of Dynamic Factors," Center for Economic Research (RECent) 123, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".

    Cited by:

    1. Christian Brownlees & Geert Mesters, 2017. "Detecting Granular Time Series in Large Panels," Working Papers 991, Barcelona School of Economics.

  3. Mario Forni & Marc Hallin & Marco Lippi & Paolo Zaffaroni, 2015. "Dynamic Factor Models with Infinite-Dimensional Factor Space: Asymptotic Analysis," Working Papers ECARES ECARES 2015-23, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. 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.
    2. Forni, Mario & Hallin, Marc & Lippi, Marco & Zaffaroni, Paolo, 2015. "Dynamic factor models with infinite-dimensional factor spaces: One-sided representations," Journal of Econometrics, Elsevier, vol. 185(2), pages 359-371.
    3. Marc Hallin & Siegfried Hörmann & Marco Lippi, 2017. "Optimal Dimension Reduction for High-dimensional and Functional Time Series," Working Papers ECARES ECARES 2017-39, ULB -- Universite Libre de Bruxelles.
    4. 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.
    5. Matteo Barigozzi & Marc Hallin, 2024. "The Dynamic, the Static, and the Weak factor models and the analysis of high-dimensional time series," Papers 2407.10653, arXiv.org.
    6. Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
    7. Matteo Barigozzi & Daniele Massacci, 2022. "Modelling Large Dimensional Datasets with Markov Switching Factor Models," Papers 2210.09828, arXiv.org, revised Dec 2024.
    8. Pietro Dallari & Antonio Ribba, 2015. "Dynamic Factor Models with In nite-Dimensional Factor Space: Asymptotic Analysis," Center for Economic Research (RECent) 115, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    9. Miaomiao Niu & Guohao Li, 2022. "The Impact of Climate Change Risks on Residential Consumption in China: Evidence from ARMAX Modeling and Granger Causality Analysis," IJERPH, MDPI, vol. 19(19), pages 1-15, September.
    10. Carlos Trucíos & João H. G. Mazzeu & Marc Hallin & Luiz K. Hotta & Pedro L. Valls Pereira & Mauricio Zevallos, 2022. "Forecasting Conditional Covariance Matrices in High-Dimensional Time Series: A General Dynamic Factor Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(1), pages 40-52, December.
    11. Artūras Juodis & Simas Kučinskas, 2023. "Quantifying noise in survey expectations," Quantitative Economics, Econometric Society, vol. 14(2), pages 609-650, May.
    12. 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.).
    13. Matteo Barigozzi & Matteo Luciani, 2019. "Quasi Maximum Likelihood Estimation of Non-Stationary Large Approximate Dynamic Factor Models," Papers 1910.09841, arXiv.org.
    14. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    15. Mario Forni & Luca Gambetti & marco Lippi & Luca Sala, 2020. "Common Components Structural VARs," Center for Economic Research (RECent) 147, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    16. 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.
    17. Barigozzi, Matteo & Hallin, Marc & Soccorsi, Stefano & von Sachs, Rainer, 2020. "Time-varying general dynamic factor models and the measurement of financial connectedness," LIDAM Reprints ISBA 2020015, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    18. 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.
    19. 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.
    20. 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).
    21. Barigozzi, Matteo & Hallin, Marc, 2017. "Generalized dynamic factor models and volatilities: estimation and forecasting," Journal of Econometrics, Elsevier, vol. 201(2), pages 307-321.
    22. Philipp Gersing & Christoph Rust & Manfred Deistler, 2023. "Weak Factors are Everywhere," Papers 2307.10067, arXiv.org, revised Jan 2024.
    23. F. Della Marra, 2017. "A forecasting performance comparison of dynamic factor models based on static and dynamic methods," Economics Department Working Papers 2017-ME01, Department of Economics, Parma University (Italy).
    24. 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.
    25. 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).
    26. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Working Papers ECARES 2023-15, ULB -- Universite Libre de Bruxelles.
    27. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers 2019-4, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
    28. John Nkwoma Inekwe, 2022. "Economic performance in Africa: The role of fragile financial system," The World Economy, Wiley Blackwell, vol. 45(6), pages 1910-1936, June.
    29. Christian Gross & Pierre L. Siklos, 2019. "Analyzing credit risk transmission to the non-financial sector in Europe: A network approach," CAMA Working Papers 2019-43, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    30. Mario Forni & Alessandro Giovannelli & Marco Lippi & Stefano Soccorsi, 2016. "Dynamic Factor Model with Infinite Dimensional Factor Space: Forecasting," Working Papers ECARES ECARES 2016-16, ULB -- Universite Libre de Bruxelles.
    31. Jiahe Lin & George Michailidis, 2019. "Approximate Factor Models with Strongly Correlated Idiosyncratic Errors," Papers 1912.04123, arXiv.org.
    32. Smeekes, Stephan & Wijler, Etiënne, 2016. "Macroeconomic Forecasting Using Penalized Regression Methods," Research Memorandum 039, Maastricht University, Graduate School of Business and Economics (GSBE).
    33. 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.
    34. Yang, Lu, 2022. "Idiosyncratic information spillover and connectedness network between the electricity and carbon markets in Europe," Journal of Commodity Markets, Elsevier, vol. 25(C).
    35. 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.
    36. Matteo Barigozzi & Marc Hallin, 2018. "Generalized Dynamic Factor Models and Volatilities: Consistency, rates, and prediction intervals," Papers 1811.10045, arXiv.org, revised Jul 2019.
    37. 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.
    38. Jari Miettinen & Katrin Illner & Klaus Nordhausen & Hannu Oja & Sara Taskinen & Fabian J. Theis, 2016. "Separation of Uncorrelated Stationary time series using Autocovariance Matrices," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(3), pages 337-354, May.
    39. 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.
    40. Assaf, A. George & Tsionas, Mike G., 2019. "Forecasting occupancy rate with Bayesian compression methods," Annals of Tourism Research, Elsevier, vol. 75(C), pages 439-449.
    41. 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.
    42. Luca Di Bonaventura & Mario Forni & Francesco Pattarin, 2018. "The Forecasting Performance of Dynamic Factor Models with Vintage Data," Center for Economic Research (RECent) 138, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    43. 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.
    44. Valadkhani, Abbas, 2023. "Asymmetric downside risk across different sectors of the US equity market," Global Finance Journal, Elsevier, vol. 57(C).
    45. Jonas Krampe & Luca Margaritella, 2021. "Factor Models with Sparse VAR Idiosyncratic Components," Papers 2112.07149, arXiv.org, revised May 2022.
    46. Daniel Peña & Victor J. Yohai, 2016. "Generalized Dynamic Principal Components," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(515), pages 1121-1131, July.
    47. 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.
    48. 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.
    49. 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.).
    50. 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.
    51. 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.
    52. Siegfried Hörmann & Gilles Nisol, 2021. "Prediction of Singular VARs and an Application to Generalized Dynamic Factor Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(3), pages 295-313, May.
    53. 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.
    54. Alessandro Giovannelli & Marco Lippi & Tommaso Proietti, 2023. "Band-Pass Filtering with High-Dimensional Time Series," CEIS Research Paper 559, Tor Vergata University, CEIS, revised 15 Jun 2023.
    55. Alonso, Andrés M. & Galeano, Pedro & Peña, Daniel, 2020. "A robust procedure to build dynamic factor models with cluster structure," Journal of Econometrics, Elsevier, vol. 216(1), pages 35-52.
    56. James E. Payne & Xiaojin Sun, 2023. "Time‐varying connectedness of metropolitan housing markets," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 51(2), pages 470-502, March.
    57. 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.
    58. 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.
    59. Yu, Zhen & Liu, Wei & Yang, Fuyu, 2023. "A central bankers’ sentiment index of global financial cycle," Finance Research Letters, Elsevier, vol. 57(C).
    60. Xu Zhang & Xian Yang & Jianping Li & Jun Hao, 2023. "Contemporaneous and noncontemporaneous idiosyncratic risk spillovers in commodity futures markets: A novel network topology approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(6), pages 705-733, June.
    61. 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.
    62. 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.
    63. Simone Tonini & Francesca Chiaromonte & Alessandro Giovannelli, 2022. "On the impact of serial dependence on penalized regression methods," LEM Papers Series 2022/21, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

  4. Mario Forni & Marc Hallin & Marco Lippi & Paolo Zaffaroni, 2012. "Dynamic Factor Models with Infinite-Dimensional Factor Space: One-Sided Representations," Working Papers ECARES ECARES 2012-046, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. 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.
    2. Marc Hallin & Siegfried Hörmann & Marco Lippi, 2017. "Optimal Dimension Reduction for High-dimensional and Functional Time Series," Working Papers ECARES ECARES 2017-39, ULB -- Universite Libre de Bruxelles.
    3. Carlos Cesar Trucios-Maza & João H. G Mazzeu & Luis K. Hotta & Pedro L. Valls Pereira & Marc Hallin, 2019. "On the robustness of the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting," Working Papers ECARES 2019-32, ULB -- Universite Libre de Bruxelles.
    4. Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
    5. Pietro Dallari & Antonio Ribba, 2015. "Dynamic Factor Models with In nite-Dimensional Factor Space: Asymptotic Analysis," Center for Economic Research (RECent) 115, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    6. Carlos Trucíos & João H. G. Mazzeu & Marc Hallin & Luiz K. Hotta & Pedro L. Valls Pereira & Mauricio Zevallos, 2022. "Forecasting Conditional Covariance Matrices in High-Dimensional Time Series: A General Dynamic Factor Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(1), pages 40-52, December.
    7. Artūras Juodis & Simas Kučinskas, 2023. "Quantifying noise in survey expectations," Quantitative Economics, Econometric Society, vol. 14(2), pages 609-650, May.
    8. Norman R. Swanson & Weiqi Xiong, 2018. "Big data analytics in economics: What have we learned so far, and where should we go from here?," Canadian Journal of Economics, Canadian Economics Association, vol. 51(3), pages 695-746, August.
    9. Massacci, Daniele, 2017. "Least squares estimation of large dimensional threshold factor models," Journal of Econometrics, Elsevier, vol. 197(1), pages 101-129.
    10. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    11. Mario Forni & Luca Gambetti & marco Lippi & Luca Sala, 2020. "Common Components Structural VARs," Center for Economic Research (RECent) 147, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    12. Barigozzi, Matteo & Hallin, Marc & Soccorsi, Stefano & von Sachs, Rainer, 2020. "Time-varying general dynamic factor models and the measurement of financial connectedness," LIDAM Reprints ISBA 2020015, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    13. Matteo Barigozzi & Marc Hallin & Matteo Luciani & Paolo Zaffaroni, 2021. "Inferential Theory for Generalized Dynamic Factor Models," Working Papers ECARES 2021-20, ULB -- Universite Libre de Bruxelles.
    14. 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.
    15. Lucchetti, Riccardo & Venetis, Ioannis A., 2020. "A replication of "A quasi-maximum likelihood approach for large, approximate dynamic factor models" (Review of Economics and Statistics, 2012)," Economics Discussion Papers 2020-5, Kiel Institute for the World Economy (IfW Kiel).
    16. Barigozzi, Matteo & Hallin, Marc, 2017. "Generalized dynamic factor models and volatilities: estimation and forecasting," Journal of Econometrics, Elsevier, vol. 201(2), pages 307-321.
    17. Philipp Gersing & Christoph Rust & Manfred Deistler, 2023. "Weak Factors are Everywhere," Papers 2307.10067, arXiv.org, revised Jan 2024.
    18. F. Della Marra, 2017. "A forecasting performance comparison of dynamic factor models based on static and dynamic methods," Economics Department Working Papers 2017-ME01, Department of Economics, Parma University (Italy).
    19. 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.
    20. 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).
    21. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Working Papers ECARES 2023-15, ULB -- Universite Libre de Bruxelles.
    22. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers 2019-4, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
    23. Christian Gross & Pierre L. Siklos, 2019. "Analyzing credit risk transmission to the non-financial sector in Europe: A network approach," CAMA Working Papers 2019-43, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    24. Mario Forni & Alessandro Giovannelli & Marco Lippi & Stefano Soccorsi, 2016. "Dynamic Factor Model with Infinite Dimensional Factor Space: Forecasting," Working Papers ECARES ECARES 2016-16, ULB -- Universite Libre de Bruxelles.
    25. Fiorentini, Gabriele & Galesi, Alessandro & Sentana, Enrique, 2018. "A spectral EM algorithm for dynamic factor models," Journal of Econometrics, Elsevier, vol. 205(1), pages 249-279.
    26. Jiahe Lin & George Michailidis, 2019. "Approximate Factor Models with Strongly Correlated Idiosyncratic Errors," Papers 1912.04123, arXiv.org.
    27. Barigozzi, Matteo & Hallin, Mark, 2015. "Generalized dynamic factor models and volatilities: recovering the market volatility shocks," LSE Research Online Documents on Economics 60980, London School of Economics and Political Science, LSE Library.
    28. Smeekes, Stephan & Wijler, Etiënne, 2016. "Macroeconomic Forecasting Using Penalized Regression Methods," Research Memorandum 039, Maastricht University, Graduate School of Business and Economics (GSBE).
    29. 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.
    30. Yang, Lu, 2022. "Idiosyncratic information spillover and connectedness network between the electricity and carbon markets in Europe," Journal of Commodity Markets, Elsevier, vol. 25(C).
    31. 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.
    32. 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).
    33. Matteo Barigozzi & Marc Hallin, 2018. "Generalized Dynamic Factor Models and Volatilities: Consistency, rates, and prediction intervals," Papers 1811.10045, arXiv.org, revised Jul 2019.
    34. 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.
    35. Jari Miettinen & Katrin Illner & Klaus Nordhausen & Hannu Oja & Sara Taskinen & Fabian J. Theis, 2016. "Separation of Uncorrelated Stationary time series using Autocovariance Matrices," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(3), pages 337-354, May.
    36. 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.
    37. Assaf, A. George & Tsionas, Mike G., 2019. "Forecasting occupancy rate with Bayesian compression methods," Annals of Tourism Research, Elsevier, vol. 75(C), pages 439-449.
    38. 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.
    39. Luca Di Bonaventura & Mario Forni & Francesco Pattarin, 2018. "The Forecasting Performance of Dynamic Factor Models with Vintage Data," Center for Economic Research (RECent) 138, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    40. 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.
    41. Daniel Peña & Victor J. Yohai, 2016. "Generalized Dynamic Principal Components," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(515), pages 1121-1131, July.
    42. Smucler, Ezequiel, 2019. "Consistency of generalized dynamic principal components in dynamic factor models," Statistics & Probability Letters, Elsevier, vol. 154(C), pages 1-1.
    43. 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.).
    44. 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.
    45. Fan, Jianqing & Xue, Lingzhou & Yao, Jiawei, 2017. "Sufficient forecasting using factor models," Journal of Econometrics, Elsevier, vol. 201(2), pages 292-306.
    46. 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.
    47. Siegfried Hörmann & Gilles Nisol, 2021. "Prediction of Singular VARs and an Application to Generalized Dynamic Factor Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(3), pages 295-313, May.
    48. Alonso, Andrés M. & Galeano, Pedro & Peña, Daniel, 2020. "A robust procedure to build dynamic factor models with cluster structure," Journal of Econometrics, Elsevier, vol. 216(1), pages 35-52.
    49. 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.
    50. 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.
    51. Popović Goran & Erić Ognjen & Bjelić Jelena, 2020. "Factor Analysis of Prices and Agricultural Production in the European Union," Economics, Sciendo, vol. 8(1), pages 73-81, June.
    52. 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.
    53. 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.
    54. 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.

  5. Marco Avarucci & Eric Beutner & Paolo Zaffaroni, 2012. "On moment conditions for quasi-maximum likelihood estimation of multivariate ARCH models," DSS Empirical Economics and Econometrics Working Papers Series 2012/1, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.

    Cited by:

    1. Rasmus Søndergaard Pedersen & Anders Rahbek, 2012. "Multivariate Variance Targeting in the BEKK-GARCH Model," Discussion Papers 12-23, University of Copenhagen. Department of Economics.
    2. Nielsen, Heino Bohn & Rahbek, Anders, 2014. "Unit root vector autoregression with volatility induced stationarity," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 144-167.
    3. Serge Darolles & Christian Francq & Sébastien Laurent, 2018. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," Post-Print hal-04590232, HAL.
    4. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    5. Manabu Asai & Chia-Lin Chang & Michael McAleer & Laurent Pauwels, 2018. "Asymptotic Theory for Rotated Multivariate GARCH Models," Documentos de Trabajo del ICAE 2018-27, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    6. Blasques, F. & Francq, Christian & Laurent, Sébastien, 2024. "Autoregressive conditional betas," Journal of Econometrics, Elsevier, vol. 238(2).
    7. Monica Billio & Massimiliano Caporin & Lorenzo Frattarolo & Loriana Pelizzon, 2016. "Networks in risk spillovers: a multivariate GARCH perspective," Working Papers 2016:03, Department of Economics, University of Venice "Ca' Foscari".
    8. Rasmus Søndergaard Pedersen & Olivier Wintenberger, 2017. "On the tail behavior of a class of multivariate conditionally heteroskedastic processes," Post-Print hal-01436267, HAL.
    9. Christian Francq & Jean-Michel Zakoïan, 2016. "Estimating multivariate volatility models equation by equation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(3), pages 613-635, June.
    10. Hetland, Simon & Pedersen, Rasmus Søndergaard & Rahbek, Anders, 2023. "Dynamic conditional eigenvalue GARCH," Journal of Econometrics, Elsevier, vol. 237(2).

  6. Mario Forni & Marc Hallin & Marco Lippi & Paolo Zaffaroni, 2011. "One-Sided Representations of Generalized Dynamic Factor Models," EIEF Working Papers Series 1106, Einaudi Institute for Economics and Finance (EIEF), revised Mar 2011.

    Cited by:

    1. Forni, Mario & Hallin, Marc & Lippi, Marco & Zaffaroni, Paolo, 2015. "Dynamic factor models with infinite-dimensional factor spaces: One-sided representations," Journal of Econometrics, Elsevier, vol. 185(2), pages 359-371.
    2. Carlos Trucíos & João H. G. Mazzeu & Marc Hallin & Luiz K. Hotta & Pedro L. Valls Pereira & Mauricio Zevallos, 2022. "Forecasting Conditional Covariance Matrices in High-Dimensional Time Series: A General Dynamic Factor Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(1), pages 40-52, December.
    3. Marc Hallin & Marco Lippi, 2013. "Factor Models in High-Dimensional Time Series: A Time-Domain Approach," Working Papers ECARES ECARES 2013-15, ULB -- Universite Libre de Bruxelles.

  7. M. Hashem Pesaran & Paolo Zaffaroni, 2009. "Optimality and Diversifiability of Mean Variance and Arbitrage Pricing Portfolios," CESifo Working Paper Series 2857, CESifo.

    Cited by:

    1. Chen, Jia & Li, Degui & Linton, Oliver, 2019. "A new semiparametric estimation approach for large dynamic covariance matrices with multiple conditioning variables," Journal of Econometrics, Elsevier, vol. 212(1), pages 155-176.

  8. Pesaran, M.H. & Zaffaroni, P., 2008. "Optimal Asset Allocation with Factor Models for Large Portfolios," Cambridge Working Papers in Economics 0813, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Fan, Jianqing & Liao, Yuan & Shi, Xiaofeng, 2013. "Risks of large portfolios," MPRA Paper 44206, University Library of Munich, Germany.
    2. Jianqing Fan & Fang Han & Han Liu & Byron Vickers, 2015. "Robust Inference of Risks of Large Portfolios," Papers 1501.02382, arXiv.org.
    3. Jianqing Fan & Jingjin Zhang & Ke Yu, 2008. "Asset Allocation and Risk Assessment with Gross Exposure Constraints for Vast Portfolios," Papers 0812.2604, arXiv.org.
    4. C. Gourieroux & A. Monfort, 2013. "Granularity Adjustment for Efficient Portfolios," Econometric Reviews, Taylor & Francis Journals, vol. 32(4), pages 449-468, December.
    5. Lam, Clifford & Yao, Qiwei, 2012. "Factor modeling for high-dimensional time series: inference for the number of factors," LSE Research Online Documents on Economics 45684, London School of Economics and Political Science, LSE Library.

  9. Pesaran, M.H. & Schleicher, C. & Zaffaroni, P., 2008. "Model Averaging in Risk Management with an Application to Futures Markets," Cambridge Working Papers in Economics 0808, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Qingfeng Liu & Qingsong Yao & Guoqing Zhao, 2020. "Model averaging estimation for conditional volatility models with an application to stock market volatility forecast," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(5), pages 841-863, August.
    2. Antonio Ciccone & Marek Jarocinski, 2010. "Determinants of Economic Growth: Will Data Tell?," Working Papers 1009, BBVA Bank, Economic Research Department.
    3. Bahram Pesaran & M. Hashem Pesaran, 2010. "Conditional Volatility and Correlations of Weekly Returns and the VaR Analysis of 2008 Stock Market Crash," CESifo Working Paper Series 3023, CESifo.
    4. Valeria Bignozzi & Claudio Macci & Lea Petrella, 2017. "Large deviations for risk measures in finite mixture models," Papers 1710.03252, arXiv.org, revised Feb 2018.
    5. McAleer, M.J., 2008. "The ten commandments for optimizing value-at-risk and daily capital charges," Econometric Institute Research Papers EI 2008-32, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Amengual, Dante & Fiorentini, Gabriele & Sentana, Enrique, 2013. "Sequential estimation of shape parameters in multivariate dynamic models," Journal of Econometrics, Elsevier, vol. 177(2), pages 233-249.
    7. Gloria Gonzalez-Rivera & Emre Yoldas, 2010. "Multivariate Autocontours for Specification Testing in Multivariate GARCH Models," Working Papers 201436, University of California at Riverside, Department of Economics.
    8. Nanying Wang & Jack E. Houston, 2016. "The Co-Movement between Non-GM and GM Soybean Prices in China: Evidence from Dalian Futures Market (2004-2014)," Applied Economics and Finance, Redfame publishing, vol. 3(4), pages 37-47, November.
    9. Wang, Nanying & Houston, Jack, 2015. "The Comovement between Non-GM and GM Soybean Price in China: Evidence from Dalian Futures Market," 2015 Annual Meeting, January 31-February 3, 2015, Atlanta, Georgia 196775, Southern Agricultural Economics Association.
    10. González-Rivera, Gloria & Yoldas, Emre, 2012. "Autocontour-based evaluation of multivariate predictive densities," International Journal of Forecasting, Elsevier, vol. 28(2), pages 328-342.
    11. Hugh Christensen & Simon Godsill & Richard E Turner, 2020. "Hidden Markov Models Applied To Intraday Momentum Trading With Side Information," Papers 2006.08307, arXiv.org.
    12. Zhang, Xinyu & Wan, Alan T.K. & Zou, Guohua, 2013. "Model averaging by jackknife criterion in models with dependent data," Journal of Econometrics, Elsevier, vol. 174(2), pages 82-94.
    13. Adam Clements & Mark Bernard Doolan, 2020. "Combining multivariate volatility forecasts using weighted losses," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(4), pages 628-641, July.
    14. Vanina Forget, 2012. "Doing well and doing good: a multi-dimensional puzzle," Working Papers hal-00672037, HAL.
    15. Assenmacher-Wesche, Katrin & Pesaran, M. Hashem, 2007. "Assessing Forecast Uncertainties in a VECX Model for Switzerland: An Exercise in Forecast Combination across Models and Observation Windows," IZA Discussion Papers 3071, Institute of Labor Economics (IZA).
    16. Wang, Nanying & Houston, Jack E., 2015. "The Co-movement between Non-GM and GM Soybean Price in China: Evidence from China Futures Market," 2015 Conference, August 9-14, 2015, Milan, Italy 211914, International Association of Agricultural Economists.
    17. Laporta, Alessandro G. & Merlo, Luca & Petrella, Lea, 2018. "Selection of Value at Risk Models for Energy Commodities," Energy Economics, Elsevier, vol. 74(C), pages 628-643.
    18. Farhat Iqbal & Mamoona Zahid & Dimitrios Koutmos, 2023. "Cryptocurrency Trading and Downside Risk," Risks, MDPI, vol. 11(7), pages 1-18, July.
    19. Noman, Abu Hanifa Md & Karim, Muhammad Mahmudul & Hassan, Mohammad Kabir & Khan, Muhammad Asif & Pervin, Sajeda, 2023. "COVID-19 pandemic and the dynamics of major investable assets: What gives shelter to investors?," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 14-30.
    20. Gradojevic, Nikola & Gençay, Ramazan, 2013. "Fuzzy logic, trading uncertainty and technical trading," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 578-586.
    21. Moral-Benito, Enrique, 2010. "Model averaging in economics," MPRA Paper 26047, University Library of Munich, Germany.
    22. George Chalamandaris & Leonidas S. Rompolis, 2021. "Recovering the market risk premium from higher‐order moment risks," European Financial Management, European Financial Management Association, vol. 27(1), pages 147-186, January.
    23. Enrique Moral-Benito, 2015. "Model Averaging In Economics: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 46-75, February.
    24. Alena Skolkova, 2023. "Model Averaging with Ridge Regularization," CERGE-EI Working Papers wp758, The Center for Economic Research and Graduate Education - Economics Institute, Prague.

  10. Mojon, Benoît & Altissimo, Filippo & Zaffaroni, Paolo, 2007. "Fast micro and slow macro: can aggregation explain the persistence of inflation?," Working Paper Series 729, European Central Bank.

    Cited by:

    1. Smets, Frank & Maćkowiak, Bartosz, 2008. "On implications of micro price data for macro models," Working Paper Series 960, European Central Bank.
    2. Byrne, Joseph P. & Kontonikas, Alexandros & Montagnoliz, Alberto, 2010. "International Evidence on the New Keynesian Phillips Curve Using Aggregate and Disaggregate Data," SIRE Discussion Papers 2010-57, Scottish Institute for Research in Economics (SIRE).
    3. Eric Jondeau & Jean-Guillaume Sahuc, 2008. "Optimal Monetary Policy in an Estimated DSGE Model of the Euro Area with Cross-Country Heterogeneity," International Journal of Central Banking, International Journal of Central Banking, vol. 4(2), pages 23-72, June.
    4. Ian Babetskii & Fabrizio Coricelli & Roman Horvath, 2009. "Assessing Inflation Persistence: Micro Evidence on an Inflation Targeting Economy," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00643340, HAL.
    5. Chong, Terence Tai Leung & Zhu, Tingting & Rafiq, M.S., 2013. "Are Prices Sticky in Large Developing Economies? An Empirical Comparison of China and India," MPRA Paper 60985, University Library of Munich, Germany.
    6. Carlomagno, Guillermo, 2014. "The pairwise approach to model a large set of disaggregates with common trends," DES - Working Papers. Statistics and Econometrics. WS ws141309, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. Zsuzsanna Zsibók & Balázs Varga, 2012. "Inflation Persistence in Hungary: a Spatial Analysis," Working Papers 1203, Department of Mathematical Economics and Economic Analysis, Corvinus University of Budapest.
    8. Pawe³ Gajewski, 2017. "Patterns of regional inflation persistence in a CEE country. The case of Poland," Lodz Economics Working Papers 5/2017, University of Lodz, Faculty of Economics and Sociology.
    9. Andrea Vaona & Guido Ascari, 2012. "Regional Inflation Persistence: Evidence from Italy," Regional Studies, Taylor & Francis Journals, vol. 46(4), pages 509-523, June.
    10. Joseph P. Byrne & Norbert Fiess, 2007. "Euro Area Inflation: Aggregation Bias and Convergence," Working Papers 2007_41, Business School - Economics, University of Glasgow.
    11. Todd E. Clark, 2003. "Disaggregate evidence on the persistence of consumer price inflation," Research Working Paper RWP 03-11, Federal Reserve Bank of Kansas City.
    12. Jondeau, Eric & Imbs, Jean & Pelgrin, Florian, 2007. "Aggregating Phillips Curves," CEPR Discussion Papers 6184, C.E.P.R. Discussion Papers.
    13. Philip Bunn & Colin Ellis, 2012. "How do Individual UK Producer Prices Behave?," Economic Journal, Royal Economic Society, vol. 122(558), pages 16-34, February.
    14. Lamla, Michael & Dräger, Lena, 2013. "Imperfect Information and Inflation Expectations: Evidence from Microdata," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79908, Verein für Socialpolitik / German Economic Association.
    15. Simone Elmer & Thomas Maag, 2009. "The Persistence of Inflation in Switzerland," KOF Working papers 09-235, KOF Swiss Economic Institute, ETH Zurich.
    16. Bouakez, Hafedh & Cardia, Emanuela & Ruge-Murcia, Francisco, 2014. "Sectoral price rigidity and aggregate dynamics," European Economic Review, Elsevier, vol. 65(C), pages 1-22.
    17. Joseph P. Byrne & Alexandros Kontonikas & Alberto Montagnoli, 2010. "The Time‐Series Properties Of Uk Inflation: Evidence From Aggregate And Disaggregate Data," Scottish Journal of Political Economy, Scottish Economic Society, vol. 57(1), pages 33-47, February.
    18. Maarten Dossche, 2009. "Understanding inflation dynamics : Where do we stand ?," Working Paper Research 165, National Bank of Belgium.
    19. Lena Draeger & Michael J. Lamla, 2013. "Imperfect information and inflation expectations," KOF Working papers 13-329, KOF Swiss Economic Institute, ETH Zurich.
    20. Roman Horvath & Fabrizio Coricelli, 2010. "Price setting and market structure: an empirical analysis of micro data in Slovakia," PSE-Ecole d'économie de Paris (Postprint) hal-00643319, HAL.
    21. Ian Babetskii & Fabrizio Coricelli & Roman Horváth, 2007. "Measuring and Explaining Inflation Persistence: Disaggregate Evidence on the Czech Republic," Working Papers IES 2007/22, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Aug 2007.
    22. Fabricio Coricelli & Roman Horváth, 2008. "Price Setting and Market Structure: An Empirical Analysis of Micro Data," Working Papers IES 2008/23, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2008.
    23. Marcos R. de Castro & Solange N. Gouvea & André Minella & Rafael C. dos Santos & Nelson F. Souza-Sobrinho, 2011. "SAMBA: Stochastic Analytical Model with a Bayesian Approach," Working Papers Series 239, Central Bank of Brazil, Research Department.
    24. Dräger, Lena & Lamla, Michael J., 2012. "Updating inflation expectations: Evidence from micro-data," Economics Letters, Elsevier, vol. 117(3), pages 807-810.
    25. Giannoni, Marc & Mihov, Ilian & Boivin, Jean, 2007. "Sticky Prices and Monetary Policy: Evidence from Disaggregated US Data," CEPR Discussion Papers 6101, C.E.P.R. Discussion Papers.
    26. Carlomagno, Guillermo, 2015. "Forecasting a large set of disaggregates with common trends and outliers," DES - Working Papers. Statistics and Econometrics. WS ws1518, Universidad Carlos III de Madrid. Departamento de Estadística.
    27. Nagayasu, Jun, 2012. "Regional inflation and industrial structure in monetary union," MPRA Paper 37310, University Library of Munich, Germany.
    28. Logan Rangasamy, 2009. "Inflation Persistence And Core Inflation: The Case Of South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 77(3), pages 430-444, September.
    29. Migliardo, Carlo, 2012. "Heterogeneity in price setting behavior, spatial disparities and sectoral diversity: Evidence from a panel of Italian firms," Economic Modelling, Elsevier, vol. 29(4), pages 1106-1118.
    30. Sevim Kosem Alp, 2010. "Optimal Monetary Policy under Sectoral Heterogeneity in Inflation Persistence (Sektorel Enflasyon Ataleti Farkliligi Altinda Optimal Para Politikasi)," Working Papers 1004, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    31. Giovanni Caggiano & Efrem Castelnuovo, 2008. "Long Memory and Non-Linearities in International Inflation," "Marco Fanno" Working Papers 0076, Dipartimento di Scienze Economiche "Marco Fanno".
    32. Hasan Engin Duran & Burak Dindaroğlu, 2021. "Regional inflation persistence in Turkey," Growth and Change, Wiley Blackwell, vol. 52(1), pages 460-491, March.
    33. Mumtaz, Haroon & Zabczyk, Pawel & Ellis, Colin, 2009. "What lies beneath: what can disaggregated data tell us about the behaviour of prices?," Bank of England working papers 364, Bank of England.
    34. Arthur Charpentier & Mathieu Pigeon, 2016. "Macro vs. Micro Methods in Non-Life Claims Reserving (an Econometric Perspective)," Risks, MDPI, vol. 4(2), pages 1-18, May.
    35. Tommaso Monacelli & Luca Sala, 2009. "The International Dimension of Inflation: Evidence from Disaggregated Consumer Price Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(s1), pages 101-120, February.
    36. Lena Dräger & Michael J. Lamla, 2017. "Imperfect Information and Consumer Inflation Expectations: Evidence from Microdata," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(6), pages 933-968, December.
    37. Carlomagno, Guillermo, 2016. "Discovering common trends in a large set of disaggregates: statistical procedures and their properties," DES - Working Papers. Statistics and Econometrics. WS ws1519, Universidad Carlos III de Madrid. Departamento de Estadística.
    38. Senra, Eva, 2017. "22 Years of inflation assessment and forecasting experience at the bulletin of EU & US inflation and macroeconomic analysis," DES - Working Papers. Statistics and Econometrics. WS 24678, Universidad Carlos III de Madrid. Departamento de Estadística.
    39. Ailenei, Dorel & Cristescu, Amalia, 2010. "Regional Distribution of Inflationary Pressures in Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 32-43, December.
    40. Antoni Espasa & Eva Senra, 2017. "Twenty-Two Years of Inflation Assessment and Forecasting Experience at the Bulletin of EU & US Inflation and Macroeconomic Analysis," Econometrics, MDPI, vol. 5(4), pages 1-28, October.
    41. Konstantin Belyaev & Aelita Belyaeva & Tomas Konecny & Jakub Seidler & Martin Vojtek, 2012. "Macroeconomic Factors as Drivers of LGD Prediction: Empirical Evidence from the Czech Republic," Working Papers 2012/12, Czech National Bank.

  11. Robinson, Peter M. & Zaffaroni, Paolo, 2005. "Pseudo-maximum likelihood estimation of ARCH(∞) models," LSE Research Online Documents on Economics 58182, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Han, Heejoon & Park, Joon Y., 2006. "Time series properties of ARCH processes with persistent covariates," MPRA Paper 5199, University Library of Munich, Germany.

  12. Hashem Pesaran & Paolo Zaffaroni & Banca d'Italia), 2004. "Model Averaging and Value-at-Risk based Evaluation of Large Multi Asset Volatility Models for Risk Management," Money Macro and Finance (MMF) Research Group Conference 2004 101, Money Macro and Finance Research Group.

    Cited by:

    1. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    2. Antonio Ciccone & Marek Jarocinski, 2010. "Determinants of Economic Growth: Will Data Tell?," Working Papers 1009, BBVA Bank, Economic Research Department.
    3. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," PIER Working Paper Archive 05-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    4. Chew Lian Chua & Sandy Suardi & Sarantis Tsiaplias, 2011. "Predicting Short-Term Interest Rates: Does Bayesian Model Averaging Provide Forecast Improvement?," Melbourne Institute Working Paper Series wp2011n01, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    5. Chun Liu & John M. Maheu, 2009. "Forecasting realized volatility: a Bayesian model-averaging approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(5), pages 709-733.
    6. Chua, Chew Lian & Suardi, Sandy & Tsiaplias, Sarantis, 2013. "Predicting short-term interest rates using Bayesian model averaging: Evidence from weekly and high frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 442-455.
    7. Anthony Garratt & Kevin Lee & Emi Mise & Kalvinder Shields, 2006. "Real Time Representation of the UK Output Gap in the Presence of Trend Uncertainty," Birkbeck Working Papers in Economics and Finance 0618, Birkbeck, Department of Economics, Mathematics & Statistics.
    8. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
    9. Amendola, Alessandra & Storti, Giuseppe, 2009. "Combination of multivariate volatility forecasts," SFB 649 Discussion Papers 2009-007, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    10. M. Hashem Pesaran & Bahram Pesaran, 2007. "Volatilities and Conditional Correlations in Futures Markets with a Multivariate t Distribution," CESifo Working Paper Series 2056, CESifo.
    11. James Mitchell & Stephen G. Hall, 2005. "Evaluating, Comparing and Combining Density Forecasts Using the KLIC with an Application to the Bank of England and NIESR ‘Fan’ Charts of Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 995-1033, December.
    12. Garratt, Anthony & Lee, Kevin & Mise, Emi & Shields, Kalvinder, 2009. "Real time representation of the UK output gap in the presence of model uncertainty," International Journal of Forecasting, Elsevier, vol. 25(1), pages 81-102.
    13. Pesaran, B. & Pesaran, M.H., 2007. "Modelling Volatilities and Conditional Correlations in Futures Markets with a Multivariate t Distribution," Cambridge Working Papers in Economics 0734, Faculty of Economics, University of Cambridge.
    14. Imed Gammoudi & Lotfi BelKacem & Mohamed El Ghourabi, 2014. "Value at Risk Estimation for Heavy Tailed Distributions," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 8(3), pages 109-125.

  13. Paolo Zaffaroni & Peter M. Robinson, 2004. "PSEUDO-MAXIMUM LIKELIHOOD ESTIMATION OF ARCH($ \infty $) MODELS," Econometric Society 2004 North American Summer Meetings 326, Econometric Society.

    Cited by:

    1. Christan Francq & Jean-Michel Zakoian, 2012. "Optimal Predictions of Powers of Conditionally Heteroskedastic Processes," Working Papers 2012-17, Center for Research in Economics and Statistics.

  14. Paolo Zaffaroni, 2003. "Gaussian inference on certain long-range dependent volatility models," Temi di discussione (Economic working papers) 472, Bank of Italy, Economic Research and International Relations Area.

    Cited by:

    1. Artiach, Miguel & Arteche, Josu, 2012. "Doubly fractional models for dynamic heteroscedastic cycles," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 2139-2158.
    2. David Mcmillan & Alan Speight, 2008. "Long-memory in high-frequency exchange rate volatility under temporal aggregation," Quantitative Finance, Taylor & Francis Journals, vol. 8(3), pages 251-261.
    3. Robinson, Peter M. & Zaffaroni, Paolo, 2005. "Pseudo-maximum likelihood estimation of ARCH(∞) models," LSE Research Online Documents on Economics 58182, London School of Economics and Political Science, LSE Library.
    4. Quan-Hoang Vuong, 2004. "Analyses on Gold and US Dollar in Vietnam's Transitional Economy," Working Papers CEB 04-033.RS, ULB -- Universite Libre de Bruxelles.
    5. Peter M Robinson & Paolo Zaffaroni, 2005. "Pseudo-Maximum Likelihood Estimation of ARCH(8) Models," STICERD - Econometrics Paper Series 495, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    6. Jean‐Marc Bardet & Paul Doukhan & José Rafael León, 2008. "Uniform limit theorems for the integrated periodogram of weakly dependent time series and their applications to Whittle's estimate," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(5), pages 906-945, September.
    7. Robinson, Peter M. & Zafaroni, Paolo, 2005. "Pseudo-maximum likelihood estimation of ARCH models," LSE Research Online Documents on Economics 4544, London School of Economics and Political Science, LSE Library.
    8. Zaffaroni, Paolo, 2009. "Whittle estimation of EGARCH and other exponential volatility models," Journal of Econometrics, Elsevier, vol. 151(2), pages 190-200, August.
    9. Artiach, Miguel, 2012. "Leverage, skewness and amplitude asymmetric cycles," MPRA Paper 41267, University Library of Munich, Germany.
    10. Banerjee, Anindya & Urga, Giovanni, 2005. "Modelling structural breaks, long memory and stock market volatility: an overview," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 1-34.

  15. Paolo Zaffaroni, 2002. "Contemporaneous aggregation of GARCH processes," Temi di discussione (Economic working papers) 449, Bank of Italy, Economic Research and International Relations Area.

    Cited by:

    1. Richard T. Baillie & Claudio Morana, 2014. "Modeling Long Memory and Structural Breaks in Conditional Variances: An Adaptive FIGARCH Approach," Working Papers 593, Queen Mary University of London, School of Economics and Finance.
    2. Pellegrini, Santiago & Ruiz, Esther & Espasa, Antoni, 2010. "Conditionally heteroscedastic unobserved component models and their reduced form," Economics Letters, Elsevier, vol. 107(2), pages 88-90, May.
    3. Sentana, Enrique, 2004. "Factor representing portfolios in large asset markets," Journal of Econometrics, Elsevier, vol. 119(2), pages 257-289, April.
    4. Zaffaroni, Paolo, 2000. "Contemporaneous aggregation of GARCH processes," LSE Research Online Documents on Economics 6869, London School of Economics and Political Science, LSE Library.
    5. João Caldeira & Guilherme Moura & André Santos, 2015. "Measuring Risk in Fixed Income Portfolios using Yield Curve Models," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 65-82, June.
    6. Kang, Sang Hoon & Cheong, Chongcheul & Yoon, Seong-Min, 2010. "Contemporaneous aggregation and long-memory property of returns and volatility in the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4844-4854.
    7. Eduardo Rossi, 2010. "Univariate GARCH models: a survey (in Russian)," Quantile, Quantile, issue 8, pages 1-67, July.
    8. Dmitrij Celov & Remigijus Leipus & Anne Philippe, 2010. "Asymptotic normality of the mixture density estimator in a disaggregation scheme," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(4), pages 425-442.
    9. Giacomo Sbrana, 2012. "Aggregation and marginalization of GARCH processes: some further results," METRON, Springer;Sapienza Università di Roma, vol. 70(2), pages 165-172, August.
    10. Beran, Jan & Schützner, Martin & Ghosh, Sucharita, 2010. "From short to long memory: Aggregation and estimation," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2432-2442, November.
    11. Jan Beran & Haiyan Liu & Sucharita Ghosh, 2020. "On aggregation of strongly dependent time series," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(3), pages 690-710, September.
    12. Feng, Yuanhua & Zhou, Chen, 2015. "Forecasting financial market activity using a semiparametric fractionally integrated Log-ACD," International Journal of Forecasting, Elsevier, vol. 31(2), pages 349-363.
    13. Zaffaroni, Paolo, 2007. "Aggregation and memory of models of changing volatility," Journal of Econometrics, Elsevier, vol. 136(1), pages 237-249, January.
    14. Dima, Bogdan & Dima, Ştefana Maria, 2017. "Mutual information and persistence in the stochastic volatility of market returns: An emergent market example," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 36-59.
    15. Eric Jondeau, 2008. "Contemporaneous Aggregation of GARCH Models and Evaluation of the Aggregation Bias," Swiss Finance Institute Research Paper Series 08-06, Swiss Finance Institute.

  16. Paolo Zaffaroni, 2000. "Stationarity and Memory of ARCH Models," STICERD - Econometrics Paper Series 383, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Paolo Zaffaroni, 2003. "Gaussian inference on certain long-range dependent volatility models," Temi di discussione (Economic working papers) 472, Bank of Italy, Economic Research and International Relations Area.
    2. Gilles Zumbach, 2004. "Volatility processes and volatility forecast with long memory," Quantitative Finance, Taylor & Francis Journals, vol. 4(1), pages 70-86.

  17. Michelacci, C. & Zaffaroni, P., 2000. "(Fractional) Beta Convergence," Papers 383, Banca Italia - Servizio di Studi.

    Cited by:

    1. Olushina O Awe & Robert Mudida & Luis A. Gil‐Alana, 2021. "Comparative analysis of economic growth in Nigeria and Kenya: A fractional integration approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1197-1205, January.
    2. Luis A. Gil-Alana & Rangan Gupta, 2013. "Persistence and Cycles in Historical Oil Prices Data," Working Papers 201375, University of Pretoria, Department of Economics.
    3. Bandyopadhyay, Sanghamitra, 2018. "The absolute Gini is a more reliable measure of inequality for time dependent analyses (compared with the relative Gini)," Economics Letters, Elsevier, vol. 162(C), pages 135-139.
    4. Lima, Luiz Renato & Notini, Hilton Hostalácio & Reis Gomes, Fábio Augusto, 2010. "Empirical Evidence on Convergence Across Brazilian States," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 64(2), June.
    5. Dolado Juan J. & Gonzalo Jesus & Mayoral Laura, 2008. "Wald Tests of I(1) against I(d) Alternatives: Some New Properties and an Extension to Processes with Trending Components," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(4), pages 1-35, December.
    6. John Nkwoma Inekwe, 2019. "The exploration of economic crises: parameter uncertainty and predictive ability," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(2), pages 290-313, May.
    7. Stengos, Thanasis & Yazgan, M. Ege, 2014. "Persistence In Convergence," Macroeconomic Dynamics, Cambridge University Press, vol. 18(4), pages 753-782, June.
    8. Ke, Shuyao & Phillips, Peter C.B. & Su, Liangjun, 2024. "Robust inference of panel data models with interactive fixed effects under long memory: A frequency domain approach," Journal of Econometrics, Elsevier, vol. 241(2).
    9. Laura Mayoral, 2005. "The persistence of inflation in OECD countries: A fractionally integrated approach," Economics Working Papers 958, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2005.
    10. Steven N. Durlauf & Andros Kourtellos & Chih Ming Tan, 2008. "Empirics of Growth and Development," Chapters, in: Amitava Krishna Dutt & Jaime Ros (ed.), International Handbook of Development Economics, Volumes 1 & 2, volume 0, chapter 3, Edward Elgar Publishing.
    11. Silverberg, Gerald & Verspagen, Bart, 2000. "A Note on Michelacci and Zaffaroni, Long Memory, and Time Series of Economic Growth," Research Memorandum 031, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
    12. 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.
    13. Mateo Isoardi & Luis A. Gil-Alana, 2019. "Inflation in Argentina: Analysis of Persistence Using Fractional Integration," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 45(2), pages 204-223, April.
    14. Mello, Marcelo, 2010. "Stochastic Convergence Across Brazilian States," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 30(1), October.
    15. Thanasis Stengos & M. Ege Yazgan & Harun Özkan, 2018. "Persistence In Convergence And Club Formation," Bulletin of Economic Research, Wiley Blackwell, vol. 70(2), pages 119-138, April.
    16. Gil-Alana, Luis A. & Mudida, Robert & Zerbo, Eleazar, 2021. "GDP per capita IN SUB-SAHARAN Africa: A time series approach using long memory," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 175-190.
    17. Gil-Alana, Luis A. & Mudida, Robert & Yaya, OlaOluwa S & Osuolale, Kazeem & Ogbonna, Ephraim A, 2019. "Influence of US Presidential Terms on S&P500 Index Using a Time Series Analysis Approach," MPRA Paper 93941, University Library of Munich, Germany.
    18. Guglielmo Maria Caporale & Marinko Skare, 2014. "Long Memory in UK Real GDP, 1851-2013: An ARFIMA-FIGARCH Analysis," Discussion Papers of DIW Berlin 1395, DIW Berlin, German Institute for Economic Research.
    19. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2018. "Monetary policy shocks, inflation persistence, and long memory," Journal of Macroeconomics, Elsevier, vol. 55(C), pages 117-127.
    20. Juncal Cunado & Luis A. Gil-Alana & Fernando Pérez de Gracia, 2006. "Additional Empirical Evidence on Real Convergence: A Fractionally Integrated Approach," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 142(1), pages 67-91, April.
    21. Harashima, Taiji, 2009. "A Theory of Total Factor Productivity and the Convergence Hypothesis: Workers’ Innovations as an Essential Element," MPRA Paper 15508, University Library of Munich, Germany.
    22. Michelacci, C., 1999. "Cross-Sectional Heterogeneity and the Persistence of Aggregate Fluctuations," Papers 9906, Centro de Estudios Monetarios Y Financieros-.
    23. Gielens, Katrijn & Dekimpe, Marnik G. & Mukherjee, Anirban & Tuli, Kapil, 2023. "The future of private-label markets: A global convergence approach," International Journal of Research in Marketing, Elsevier, vol. 40(1), pages 248-267.
    24. Marrero, Ángel S. & Marrero, Gustavo A. & González, Rosa Marina & Rodríguez-López, Jesús, 2021. "Convergence in road transport CO2 emissions in Europe," Energy Economics, Elsevier, vol. 99(C).
    25. Gilles Dufrénot & Valérie Mignon & Théo Naccache, 2009. "The slow convergence of per capita income between the developing countries: “growth resistance” and sometimes “growth tragedy”," Discussion Papers 09/03, University of Nottingham, CREDIT.
    26. Gallegati, Marco, 2008. "Wavelet analysis of stock returns and aggregate economic activity," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3061-3074, February.
    27. Giancarlo Corsetti & Marcello Pericoli & Massimo Sbracia, 2001. "Correlation Analysis of Financial Contagion: What One Should Know before Running a Test," Temi di discussione (Economic working papers) 408, Bank of Italy, Economic Research and International Relations Area.
    28. Javier Haulde & Morten Ørregaard Nielsen, 2022. "Fractional integration and cointegration," CREATES Research Papers 2022-02, Department of Economics and Business Economics, Aarhus University.
    29. Gielens, Katrijn & Dekimpe, Marnik & Mukherjee, A. & Tuli, Kapil R., 2023. "The future of private-label markets: A global convergence approach," Other publications TiSEM 06f4bad4-fc32-42f4-8b7f-2, Tilburg University, School of Economics and Management.
    30. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2009. "Long Memory in US Real Output per Capita," Discussion Papers of DIW Berlin 891, DIW Berlin, German Institute for Economic Research.
    31. Godday Uwawunkonye Ebuh & Afees Salisu & Victor Oboh & Nuruddeen Usman, 2023. "A test for the contributions of urban and rural inflation to inflation persistence in Nigeria," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 16(2), pages 222-246, May.
    32. Gil-Alana, Luis A. & Yaya, OlaOluwa S & Shittu, Olanrewaju I, 2014. "GDP Per Capita in Africa before the Global Financial Crisis: Persistence, Mean Reversion and Long Memory Features," MPRA Paper 88758, University Library of Munich, Germany.
    33. Kwon, Yujin & Park, Sung Y., 2023. "Modeling an early warning system for household debt risk in Korea: A simple deep learning approach," Journal of Asian Economics, Elsevier, vol. 84(C).
    34. Ergemen, Yunus Emre, 2023. "Parametric estimation of long memory in factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1483-1499.
    35. Gilles Dufrénot & Valérie Mignon & Théo Naccache, 2012. "Testing Catching-Up Between The Developing Countries: “Growth Resistance” And Sometimes “Growth Tragedy”," Bulletin of Economic Research, Wiley Blackwell, vol. 64(4), pages 470-508, October.
    36. Guglielmo Maria Caporale & Luis Alberiko Gil‐Alana, 2022. "Trends and cycles in macro series: The case of US real GDP," Bulletin of Economic Research, Wiley Blackwell, vol. 74(1), pages 123-134, January.
    37. Sanghamitra Bandyopadhyay, 2021. "The persistence of inequality across Indian states: A time series approach," Review of Development Economics, Wiley Blackwell, vol. 25(3), pages 1150-1171, August.
    38. Katsumi Shimotsu, 2006. "Exact Local Whittle Estimation of Fractional Integration with Unknown Mean and Time Trend," Working Paper 1061, Economics Department, Queen's University.
    39. Abadir, Karim M. & Caggiano, Giovanni & Talmain, Gabriel, 2013. "Nelson–Plosser revisited: The ACF approach," Journal of Econometrics, Elsevier, vol. 175(1), pages 22-34.
    40. G Caggiano & L Leonida, "undated". "International Output Convergence: Evidence from an AutoCorrelation Function Approach," Working Papers 2006_20, Business School - Economics, University of Glasgow.
    41. Théophile Azomahou & Tapas Mishra & Mamata Parhi, 2015. "Economic Growth under Stochastic Population and Pollution Shocks," Post-Print hal-01736166, HAL.
    42. Cunado, J. & Gil-Alana, L. A. & Perez de Gracia, F., 2004. "Real convergence in Taiwan: a fractionally integrated approach," Journal of Asian Economics, Elsevier, vol. 15(3), pages 529-547, June.
    43. Shimotsu, Katsumi, 2002. "Exact Local Whittle Estimation of Fractional Integration with Unknown Mean and Time Trend," Economics Discussion Papers 8844, University of Essex, Department of Economics.
    44. Marcelo Mello & Roberto Guimaraes-Filho, 2007. "A note on fractional stochastic convergence," Economics Bulletin, AccessEcon, vol. 3(16), pages 1-14.
    45. David Grreasley, 2010. "Cliometrics and Time Series Econometrics: Some Theory and Applications," Working Papers in Economics 10/56, University of Canterbury, Department of Economics and Finance.
    46. Nicolae Anca-Iuliana, 2018. "Autoregressive Evolutions For Macroeconomic Indicators Do Confirm Chaos Theories In United States," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 4, pages 29-45, August.
    47. Gil-Alana, Luis A. & Yaya, OlaOluwa S, 2018. "How do Stocks in BRICS co-move with REITs?," MPRA Paper 88753, University Library of Munich, Germany.
    48. Francesco Sarracino & Małgorzata Mikucka, 2017. "Social Capital in Europe from 1990 to 2012: Trends and Convergence," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 131(1), pages 407-432, March.
    49. Laura Mayoral, 2006. "Minimum distance estimation of stationary and non-stationary ARFIMA processes," Economics Working Papers 959, Department of Economics and Business, Universitat Pompeu Fabra.
    50. Caporale, Guglielmo Maria & Gil-Alana, Luis A. & Tripathy, Trilochan, 2020. "Volatility persistence in the Russian stock market," Finance Research Letters, Elsevier, vol. 32(C).
    51. Arielle Beyaert, 2004. "Fractional Output Convergence, with an Application to Nine Developed Countries," Econometric Society 2004 Australasian Meetings 280, Econometric Society.
    52. Luis Alberiko Gil-Alana, 2024. "All Road User Casualties (Killed) in Great Britain from 1926. Linear and Nonlinear Trends with Persistent Data," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 22(3), pages 631-640, September.
    53. Guglielmo Maria Caporale & Gloria Claudio-Quiroga & Luis A. Gil-Alana, 2021. "The Relationship between Prices and Output in the UK and the US," CESifo Working Paper Series 8970, CESifo.
    54. Ivan Kitov, 2012. "Why price inflation in developed countries is systematically underestimated," Papers 1206.0450, arXiv.org.
    55. Sanghamitra Bandyopadhyay, 2016. "The persistence of inequality across Indian states," CSAE Working Paper Series 2016-26, Centre for the Study of African Economies, University of Oxford.
    56. Gil-Alana, Luis A. & Yaya, OlaOluwa S. & Akinsomi, Omokolade & Coskun, Yener, 2020. "How do stocks in BRICS co-move with real estate stocks?," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 93-101.
    57. Guglielmo Maria Caporale & Luis A. Gil-Alana & Trilochan Tripathy, 2018. "Persistence in the Russian Stock Market Volatility Indices," CESifo Working Paper Series 7243, CESifo.
    58. Juan J. Dolado & Jesús Gonzalo & Laura Mayoral, 2005. "Testing I(1) against I(d) alternatives in the presence of deteministic components," Economics Working Papers 957, Department of Economics and Business, Universitat Pompeu Fabra.
    59. Luca Dedola & Eugenio Gaiotti & Luca Silipo, 2004. "Money Demand in theEuroArea: Do National Differences Matter?," Macroeconomics 0404019, University Library of Munich, Germany, revised 24 Apr 2004.
    60. J. Cunado & L.A. Gil-Alana & F. Perez De Gracia, 2007. "Real convergence in some emerging countries : a fractionally integrated approach," Discussion Papers (REL - Recherches Economiques de Louvain) 2007034, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    61. Luis A. Gil‐Alana & Robert Mudida & OlaOluwa S. Yaya & Kazeem A. Osuolale & Ahamuefula E. Ogbonna, 2021. "Mapping US presidential terms with S&P500 index: Time series analysis approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 1938-1954, April.
    62. Laura Mayoral, 2005. "Further evidence on the statistical properties of real GNP," Economics Working Papers 955, Department of Economics and Business, Universitat Pompeu Fabra, revised Feb 2006.
    63. Yunus Emre Ergemen, 2016. "System Estimation of Panel Data Models under Long-Range Dependence," CREATES Research Papers 2016-02, Department of Economics and Business Economics, Aarhus University.
    64. Godfrey Madigu & Luis A. Gil‐Alana, 2021. "What do productivity indices tell us? A case study of U.S. industries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 4946-4978, October.
    65. Zaffaroni, Paolo, 2004. "Contemporaneous aggregation of linear dynamic models in large economies," Journal of Econometrics, Elsevier, vol. 120(1), pages 75-102, May.
    66. Giovanni Caggiano & Leone Leonida, "undated". "A note on the empirics of the neoclassical growth model," Working Papers 2006_2, Business School - Economics, University of Glasgow.
    67. Goodness C. Aye & Hector Carcel & Luis A. Gil-Alana & Rangan Gupta, 2017. "Does Gold Act as a Hedge against Inflation in the UK? Evidence from a Fractional Cointegration Approach Over 1257 to 2016," Working Papers 201753, University of Pretoria, Department of Economics.
    68. Luis Alberiko Gil-Alaña & Borja Balprad & Guglielmo Maria Caporale, 2015. "African Growth, Non-Linearities and Strong Dependence: An Empirical Study," NCID Working Papers 12/2015, Navarra Center for International Development, University of Navarra.
    69. Giorgio Canarella & Stephen M. Miller, 2016. "Inflation Targeting: New Evidence from Fractional Integration and Cointegration," Working papers 2016-08, University of Connecticut, Department of Economics.
    70. Cartone, Alfredo & Postiglione, Paolo & Hewings, Geoffrey J.D., 2021. "Does economic convergence hold? A spatial quantile analysis on European regions," Economic Modelling, Elsevier, vol. 95(C), pages 408-417.
    71. 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.
    72. Juan Carlos Cuestas & Luis A. Gil-Alana & Laura Sauci, 2020. "Public finances in the EU-27: Are they sustainable?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 47(1), pages 181-204, February.
    73. Gil-Alana, Luis A. & Huijbens, Edward H., 2018. "Tourism in Iceland: Persistence and seasonality," Annals of Tourism Research, Elsevier, vol. 68(C), pages 20-29.
    74. Canarella, Giorgio & Miller, Stephen M., 2017. "Inflation targeting and inflation persistence: New evidence from fractional integration and cointegration," Journal of Economics and Business, Elsevier, vol. 92(C), pages 45-62.
    75. Mishra Tapas & Prskawetz Alexia & Parhi Mamata & Diebolt Claude, 2009. "A Note on Long-Memory in Population and Economic Growth," Working Papers 09-06, Association Française de Cliométrie (AFC).

  18. Lippi, Marco & Zaffaroni, Paolo, 1998. "Aggregation of simple linear dynamics: exact asymptotic results," LSE Research Online Documents on Economics 6872, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Manmohan S. Kumar & Tatsuyoshi Okimoto, 2007. "Dynamics of Persistence in International Inflation Rates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(6), pages 1457-1479, September.
    2. Tommaso Proietti & Federico Maddanu, 2021. "Modelling Cycles in Climate Series: the Fractional Sinusoidal Waveform Process," CEIS Research Paper 518, Tor Vergata University, CEIS, revised 19 Oct 2021.
    3. Beran, Jan & Schützner, Martin & Ghosh, Sucharita, 2010. "From short to long memory: Aggregation and estimation," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2432-2442, November.
    4. Thornton, Michael A., 2014. "The aggregation of dynamic relationships caused by incomplete information," Journal of Econometrics, Elsevier, vol. 178(P2), pages 342-351.
    5. Jan Beran & Haiyan Liu & Sucharita Ghosh, 2020. "On aggregation of strongly dependent time series," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(3), pages 690-710, September.
    6. Zaffaroni, Paolo, 2004. "Contemporaneous aggregation of linear dynamic models in large economies," Journal of Econometrics, Elsevier, vol. 120(1), pages 75-102, May.

  19. Paolo Zaffaroni, 1997. "Gaussian Estimation of Long-Range Dependent Volatility in Asset Prices," STICERD - Econometrics Paper Series 329, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Pérez, Ana, 2001. "Modelos de memoria larga para series económicas y financieras," DES - Documentos de Trabajo. Estadística y Econometría. DS ds010101, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Bollerslev, Tim & Wright, Jonathan H., 2000. "Semiparametric estimation of long-memory volatility dependencies: The role of high-frequency data," Journal of Econometrics, Elsevier, vol. 98(1), pages 81-106, September.

  20. Paolo Zaffaroni & Peter M. Robinson, 1997. "Nonlinear Time Series With Long Memory: A Model for Stochastic Volatility," FMG Discussion Papers dp253, Financial Markets Group.

    Cited by:

    1. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "The Distribution of Exchange Rate Volatility," Center for Financial Institutions Working Papers 99-08, Wharton School Center for Financial Institutions, University of Pennsylvania.
    2. Arteche González, Jesús María, 2002. "Gaussian Semiparametric Estimation in Long Memory in Stochastic Volatility and Signal Plus Noise Models," BILTOKI 1134-8984, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
    3. Pérez, Ana, 2001. "Modelos de memoria larga para series económicas y financieras," DES - Documentos de Trabajo. Estadística y Econometría. DS ds010101, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Meddahi, N., 2001. "An Eigenfunction Approach for Volatility Modeling," Cahiers de recherche 2001-29, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    5. F. DePenya & L. Gil-Alana, 2006. "Testing of nonstationary cycles in financial time series data," Review of Quantitative Finance and Accounting, Springer, vol. 27(1), pages 47-65, August.

  21. C Michelacci & Paolo Zaffaroni, 1997. "Beta Convergence," STICERD - Econometrics Paper Series 332, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Silverberg, G. & Verspagen, Bart, 1999. "Long Memory in Time Series of Economic Growth and Convergence," Working Papers 99.8, Eindhoven Center for Innovation Studies.
    2. Denis Bouget, 2009. "Trends of Social Welfare Systems : From Convergence to Attractiveness, an Exploratory Approach," Working Papers hal-00441889, HAL.
    3. Vaona, Andrea, 2013. "The sclerosis of regional electricity intensities in Italy: An aggregate and sectoral analysis," Applied Energy, Elsevier, vol. 104(C), pages 880-889.
    4. Liddle, Brantley, 2012. "OECD Energy Intensity: Measures, Trends, and Convergence," MPRA Paper 52085, University Library of Munich, Germany.
    5. Francisco J. Delgado Rivero (*), "undated". "Are The Tax Mix And The Fiscal Pressure Converging In The European Union?," Working Papers 11-06 Classification-JEL , Instituto de Estudios Fiscales.
    6. Zijun Wang, 2009. "The convergence of health care expenditure in the US states," Health Economics, John Wiley & Sons, Ltd., vol. 18(1), pages 55-70, January.
    7. Liddle, Brantley, 2010. "Revisiting world energy intensity convergence for regional differences," Applied Energy, Elsevier, vol. 87(10), pages 3218-3225, October.
    8. Silvia Domeneghetti & Andrea Vaona, 2015. "Regional aspects of aggregate profitability dynamics in Italy," Working Papers 04/2015, University of Verona, Department of Economics.
    9. Liddle, Brantley, 2009. "Electricity intensity convergence in IEA/OECD countries: Aggregate and sectoral analysis," Energy Policy, Elsevier, vol. 37(4), pages 1470-1478, April.
    10. Moutinho, Victor & Robaina-Alves, Margarita & Mota, Jorge, 2014. "Carbon dioxide emissions intensity of Portuguese industry and energy sectors: A convergence analysis and econometric approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 438-449.

  22. Peter M Robinson & Paolo Zaffaroni, 1997. "Modelling Nonlinearity and Long Memory in Time Series - (Now published in 'Nonlinear Dynamics and Time Series', C D Cutler and D T Kaplan (eds), Fields Institute Communications, 11 (1997), pp.61-170.)," STICERD - Econometrics Paper Series 319, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "The Distribution of Exchange Rate Volatility," Center for Financial Institutions Working Papers 99-08, Wharton School Center for Financial Institutions, University of Pennsylvania.
    2. Pérez, Ana, 2001. "Modelos de memoria larga para series económicas y financieras," DES - Documentos de Trabajo. Estadística y Econometría. DS ds010101, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. L. A. Gil-Alana, 2005. "Measuring The Memory Parameter On Several Transformations Of Asset Returns," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 8(06), pages 675-691.

Articles

  1. Wu, Wei Biao & Zaffaroni, Paolo, 2018. "Asymptotic Theory For Spectral Density Estimates Of General Multivariate Time Series," Econometric Theory, Cambridge University Press, vol. 34(1), pages 1-22, February.

    Cited by:

    1. Loubaton, Philippe & Rosuel, Alexis & Vallet, Pascal, 2023. "On the asymptotic distribution of the maximum sample spectral coherence of Gaussian time series in the high dimensional regime," Journal of Multivariate Analysis, Elsevier, vol. 194(C).
    2. Steland, Ansgar, 2024. "Flexible nonlinear inference and change-point testing of high-dimensional spectral density matrices," Journal of Multivariate Analysis, Elsevier, vol. 199(C).
    3. Barigozzi, Matteo & Hallin, Marc & Soccorsi, Stefano & von Sachs, Rainer, 2020. "Time-varying general dynamic factor models and the measurement of financial connectedness," LIDAM Reprints ISBA 2020015, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    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.
    5. Barassi, Marco & Horvath, Lajos & Zhao, Yuqian, 2018. "Change Point Detection in the Conditional Correlation Structure of Multivariate Volatility Models," MPRA Paper 87837, University Library of Munich, Germany.
    6. Matteo Barigozzi & Marc Hallin, 2018. "Generalized Dynamic Factor Models and Volatilities: Consistency, rates, and prediction intervals," Papers 1811.10045, arXiv.org, revised Jul 2019.
    7. Jonas Krampe & Luca Margaritella, 2021. "Factor Models with Sparse VAR Idiosyncratic Components," Papers 2112.07149, arXiv.org, revised May 2022.

  2. Forni, Mario & Hallin, Marc & Lippi, Marco & Zaffaroni, Paolo, 2017. "Dynamic factor models with infinite-dimensional factor space: Asymptotic analysis," Journal of Econometrics, Elsevier, vol. 199(1), pages 74-92.
    See citations under working paper version above.
  3. Goliński, Adam & Zaffaroni, Paolo, 2016. "Long memory affine term structure models," Journal of Econometrics, Elsevier, vol. 191(1), pages 33-56.

    Cited by:

    1. Goliński, Adam, 2021. "Monetary policy at the zero lower bound: Information in the Federal Reserve’s balance sheet," European Economic Review, Elsevier, vol. 131(C).
    2. Li, Johnny Siu-Hang & Liu, Yanxin & Chan, Wai-Sum, 2023. "Hedging longevity risk under non-Gaussian state-space stochastic mortality models: A mean-variance-skewness-kurtosis approach," Insurance: Mathematics and Economics, Elsevier, vol. 113(C), pages 96-121.
    3. Salman Huseynov, 2021. "Long and short memory in dynamic term structure models," CREATES Research Papers 2021-15, Department of Economics and Business Economics, Aarhus University.
    4. Abbritti, Mirko & Carcel, Hector & Gil-Alana, Luis & Moreno, Antonio, 2023. "Term premium in a fractionally cointegrated yield curve," Journal of Banking & Finance, Elsevier, vol. 149(C).
    5. Goliński, Adam & Spencer, Peter, 2017. "The advantages of using excess returns to model the term structure," Journal of Financial Economics, Elsevier, vol. 125(1), pages 163-181.
    6. Bruno Feunou & Jean-Sébastien Fontaine & Anh Le & Christian Lundblad, 2022. "Tractable Term Structure Models," Management Science, INFORMS, vol. 68(11), pages 8411-8429, November.
    7. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2018. "Monetary policy shocks, inflation persistence, and long memory," Journal of Macroeconomics, Elsevier, vol. 55(C), pages 117-127.
    8. Lovcha, Yuliya & Pérez Laborda, Àlex, 2016. "Structural shocks and dinamic elasticities in a long memory model of the US gasoline retail market," Working Papers 2072/261538, Universitat Rovira i Virgili, Department of Economics.
    9. Zongwu Cai & Jiazi Chen & Linlin Niu, 2021. "A Semiparametric Model for Bond Pricing with Life Cycle Fundamental," Working Papers 2021-01-06, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    10. Zongwu Cai & Jiazi Chen & Linlin Liu, 2021. "Estimating Impact of Age Distribution on Bond Pricing: A Semiparametric Functional Data Analysis Approach," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202102, University of Kansas, Department of Economics, revised Jan 2021.
    11. Anne Lundgaard Hansen, 2018. "Volatility-Induced Stationarity and Error-Correction in Macro-Finance Term Structure Modeling," Discussion Papers 18-12, University of Copenhagen. Department of Economics.
    12. Hansen, Anne Lundgaard, 2021. "Modeling persistent interest rates with double-autoregressive processes," Journal of Banking & Finance, Elsevier, vol. 133(C).
    13. Lovcha, Yuliya & Pérez Laborda, Àlex, 2018. "Volatility Spillovers in a Long-Memory VAR: an Application to Energy Futures Returns," Working Papers 2072/307362, Universitat Rovira i Virgili, Department of Economics.

  4. Forni, Mario & Hallin, Marc & Lippi, Marco & Zaffaroni, Paolo, 2015. "Dynamic factor models with infinite-dimensional factor spaces: One-sided representations," Journal of Econometrics, Elsevier, vol. 185(2), pages 359-371.
    See citations under working paper version above.
  5. Avarucci, Marco & Beutner, Eric & Zaffaroni, Paolo, 2013. "On Moment Conditions For Quasi-Maximum Likelihood Estimation Of Multivariate Arch Models," Econometric Theory, Cambridge University Press, vol. 29(3), pages 545-566, June.
    See citations under working paper version above.
  6. Zaffaroni, Paolo, 2009. "Whittle estimation of EGARCH and other exponential volatility models," Journal of Econometrics, Elsevier, vol. 151(2), pages 190-200, August.

    Cited by:

    1. Artiach, Miguel & Arteche, Josu, 2012. "Doubly fractional models for dynamic heteroscedastic cycles," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 2139-2158.
    2. Shelton Peiris & Manabu Asai & Michael McAleer, 2017. "Estimating and Forecasting Generalized Fractional Long Memory Stochastic Volatility Models," JRFM, MDPI, vol. 10(4), pages 1-16, December.
    3. Wintenberger, Olivier, 2013. "Continuous invertibility and stable QML estimation of the EGARCH(1,1) model," MPRA Paper 46027, University Library of Munich, Germany.
    4. Asai, M. & Chang, C-L. & McAleer, M.J., 2017. "Realized Stochastic Volatility with General Asymmetry and Long Memory," Econometric Institute Research Papers TI 2017-038/III, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Hafner, Christian & Linton, Oliver, 2017. "An Almost Closed Form Estimator For The EGARCH Model," LIDAM Reprints ISBA 2017040, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Wintenberger, Olivier & Cai, Sixiang, 2011. "Parametric inference and forecasting in continuously invertible volatility models," MPRA Paper 31767, University Library of Munich, Germany.
    7. Fu, Yang & Zheng, Zeyu, 2020. "Volatility modeling and the asymmetric effect for China’s carbon trading pilot market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    8. Ruiz Esther & Pérez Ana, 2012. "Maximally Autocorrelated Power Transformations: A Closer Look at the Properties of Stochastic Volatility Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(3), pages 1-33, September.
    9. Asai, M. & McAleer, M.J. & Peiris, S., 2017. "Realized Stochastic Volatility Models with Generalized Gegenbauer Long Memory," Econometric Institute Research Papers EI2017-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    10. Zikes, Filip & Barunik, Jozef & Shenai, Nikhil, 2015. "Modeling and forecasting persistent financial durations," FinMaP-Working Papers 36, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    11. Royer, Julien, 2023. "Conditional asymmetry in Power ARCH(∞) models," Journal of Econometrics, Elsevier, vol. 234(1), pages 178-204.
    12. Jozef Baruník & Lucie Kraicová, 2014. "Estimation of Long Memory in Volatility Using Wavelets," Working Papers IES 2014/33, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2014.
    13. Antonis Demos & Dimitra Kyriakopoulou, 2011. "Bias Correction of ML and QML Estimators in the EGARCH(1,1) Model," DEOS Working Papers 1108, Athens University of Economics and Business.
    14. Royer, Julien, 2021. "Conditional asymmetry in Power ARCH($\infty$) models," MPRA Paper 109118, University Library of Munich, Germany.
    15. Hafner C. & Linton, O., 2013. "An Almost Closed Form Estimator for the EGARCH," LIDAM Discussion Papers ISBA 2013010, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    16. Yuanhua Feng & Thomas Gries & Sebastian Letmathe, 2023. "FIEGARCH, modulus asymmetric FILog-GARCH and trend-stationary dual long memory time series," Working Papers CIE 156, Paderborn University, CIE Center for International Economics.
    17. Balli, Faruk & de Bruin, Anne & Chowdhury, Md Iftekhar Hasan, 2019. "Spillovers and the determinants in Islamic equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    18. Chih-Wen Hsiao & Ya-Chuan Chan & Mei-Yu Lee & Hsi-Peng Lu, 2021. "Heteroscedasticity and Precise Estimation Model Approach for Complex Financial Time-Series Data: An Example of Taiwan Stock Index Futures before and during COVID-19," Mathematics, MDPI, vol. 9(21), pages 1-18, October.
    19. Sucarrat, Genaro, 2010. "The power log-GARCH model," UC3M Working papers. Economics we1013, Universidad Carlos III de Madrid. Departamento de Economía.

  7. Pesaran, M. Hashem & Schleicher, Christoph & Zaffaroni, Paolo, 2009. "Model averaging in risk management with an application to futures markets," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 280-305, March.
    See citations under working paper version above.
  8. Altissimo, Filippo & Mojon, Benoit & Zaffaroni, Paolo, 2009. "Can aggregation explain the persistence of inflation?," Journal of Monetary Economics, Elsevier, vol. 56(2), pages 231-241, March.

    Cited by:

    1. Carlos Carvalho & Jae Won Lee, 2011. "Sectoral Price Facts in a Sticky-Price Model," Departmental Working Papers 201133, Rutgers University, Department of Economics.
    2. Gaglianone, Wagner Piazza & Guillén, Osmani Teixeira de Carvalho & Figueiredo, Francisco Marcos Rodrigues, 2018. "Estimating inflation persistence by quantile autoregression with quantile-specific unit roots," Economic Modelling, Elsevier, vol. 73(C), pages 407-430.
    3. Smets, Frank & Maćkowiak, Bartosz, 2008. "On implications of micro price data for macro models," Working Paper Series 960, European Central Bank.
    4. Ibrahim Abdulhamid Danlami, 2019. "Inflation Persistence in the West African Commonwealth Countries," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 5(3), pages 80-89, September.
    5. Francisco Corona & Pilar Poncela & Esther Ruiz, 2017. "Determining the number of factors after stationary univariate transformations," Empirical Economics, Springer, vol. 53(1), pages 351-372, August.
    6. Föllmi, Reto & Minsch, Rudolf & Schnell, Fabian, 2016. "What Determines Price Changes and the Distribution of Prices? Evidence from the Swiss CPI," Economics Working Paper Series 1610, University of St. Gallen, School of Economics and Political Science.
    7. Eric Jondeau & Jean-Guillaume Sahuc, 2008. "Optimal Monetary Policy in an Estimated DSGE Model of the Euro Area with Cross-Country Heterogeneity," International Journal of Central Banking, International Journal of Central Banking, vol. 4(2), pages 23-72, June.
    8. Ian Babetskii & Fabrizio Coricelli & Roman Horvath, 2009. "Assessing Inflation Persistence: Micro Evidence on an Inflation Targeting Economy," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00643340, HAL.
    9. Cristina Conflitti & Matteo Luciani, 2019. "Oil Price Pass-Through into Core Inflation," FEDS Notes 2019-04-30, Board of Governors of the Federal Reserve System (U.S.).
    10. Alexander Chudik & M. Hashem Pesaran, 2011. "Aggregation in large dynamic panels," Globalization Institute Working Papers 101, Federal Reserve Bank of Dallas.
    11. Andrea Vaona & Guido Ascari, 2012. "Regional Inflation Persistence: Evidence from Italy," Regional Studies, Taylor & Francis Journals, vol. 46(4), pages 509-523, June.
    12. Richiardi, Matteo & Valenzuela, Luis, 2019. "Firm Heterogeneity and the Aggregate Labour Share," INET Oxford Working Papers 2019-08, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    13. Joseph P. Byrne & Norbert Fiess, 2007. "Euro Area Inflation: Aggregation Bias and Convergence," Working Papers 2007_41, Business School - Economics, University of Glasgow.
    14. Foellmi, Reto & Jäggi, Adrian & Schnell, Fabian, 2020. "Currency appreciation, distance to border and price changes: Evidence from Swiss retail prices," CEPR Discussion Papers 15019, C.E.P.R. Discussion Papers.
    15. Fröhling, Annette & Lommatzsch, Kirsten, 2011. "Output sensitivity of inflation in the euro area: Indirect evidence from disaggregated consumer prices," Discussion Paper Series 1: Economic Studies 2011,25, Deutsche Bundesbank.
    16. Philip Bunn & Colin Ellis, 2012. "How do Individual UK Producer Prices Behave?," Economic Journal, Royal Economic Society, vol. 122(558), pages 16-34, February.
    17. Pami Dua & Deepika Goel, 2021. "Inflation Persistence in India," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(3), pages 525-553, September.
    18. Jeffrey C. Fuhrer, 2009. "Inflation persistence," Working Papers 09-14, Federal Reserve Bank of Boston.
    19. J. Eduardo Vera-Valdés, 2021. "Temperature Anomalies, Long Memory, and Aggregation," Econometrics, MDPI, vol. 9(1), pages 1-22, March.
    20. Simone Elmer & Thomas Maag, 2009. "The Persistence of Inflation in Switzerland," KOF Working papers 09-235, KOF Swiss Economic Institute, ETH Zurich.
    21. Laura Mayoral, 2009. "Heterogeneous dynamics, aggregation and the persistence of economic shocks," UFAE and IAE Working Papers 786.09, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    22. Peter Tillmann, 2013. "Inflation Targeting and Regional Inflation Persistence: Evidence from Korea," Pacific Economic Review, Wiley Blackwell, vol. 18(2), pages 147-161, May.
    23. Bouakez, Hafedh & Cardia, Emanuela & Ruge-Murcia, Francisco, 2014. "Sectoral price rigidity and aggregate dynamics," European Economic Review, Elsevier, vol. 65(C), pages 1-22.
    24. Kaufmann, Daniel & Lein, Sarah M., 2013. "Sticky prices or rational inattention – What can we learn from sectoral price data?," European Economic Review, Elsevier, vol. 64(C), pages 384-394.
    25. Luis Gil-Alana & Antonio Moreno & Fernando Pérez de Gracia, 2011. "Exploring Survey-Based Inflation Forecasts," Faculty Working Papers 05/11, School of Economics and Business Administration, University of Navarra.
    26. Abbritti, Mirko & Carcel, Hector & Gil-Alana, Luis & Moreno, Antonio, 2023. "Term premium in a fractionally cointegrated yield curve," Journal of Banking & Finance, Elsevier, vol. 149(C).
    27. Baumeister, Christiane & Liu, Philip & Mumtaz, Haroon, 2010. "Changes in the transmission of monetary policy: evidence from a time-varying factor-augmented VAR," Bank of England working papers 401, Bank of England.
    28. 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.
    29. Arturo Leccadito & Omar Rachedi & Giovanni Urga, 2015. "True Versus Spurious Long Memory: Some Theoretical Results and a Monte Carlo Comparison," Econometric Reviews, Taylor & Francis Journals, vol. 34(4), pages 452-479, April.
    30. Nuwat Nookhwun & Pym Manopimoke, 2023. "Disaggregated Inflation Dynamics in Thailand: Which Shocks Matter?," PIER Discussion Papers 211, Puey Ungphakorn Institute for Economic Research.
    31. Julien Chevallier, 2011. "Macroeconomics, finance, commodities: Interactions with carbon markets in a data-rich model," Post-Print hal-00991961, HAL.
    32. Marlene Amstad & Simon M. Potter & Robert W. Rich, 2017. "The New York Fed Staff Underlying Inflation Gauge (UIG)," Economic Policy Review, Federal Reserve Bank of New York, issue 23-2, pages 1-32.
    33. J. Eduardo Vera-Vald'es, 2017. "On Long Memory Origins and Forecast Horizons," Papers 1712.08057, arXiv.org.
    34. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2018. "Monetary policy shocks, inflation persistence, and long memory," Journal of Macroeconomics, Elsevier, vol. 55(C), pages 117-127.
    35. Gregory E. Givens & Robert R. Reed, 2018. "Monetary Policy and Investment Dynamics: Evidence from Disaggregate Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(8), pages 1851-1878, December.
    36. Eric JONDEAU & Florian PELGRIN, 2014. "Estimating Aggregate Autoregressive Processes When Only Macro Data are Available," Swiss Finance Institute Research Paper Series 14-43, Swiss Finance Institute.
    37. Gianluca Moretti & Giulio Nicoletti, 2010. "Estimating DSGE models with unknown data persistence," Temi di discussione (Economic working papers) 750, Bank of Italy, Economic Research and International Relations Area.
    38. Chevillon, G. & Hecq, A.W. & Laurent, S.F.J.A., 2015. "Long memory through marginalization of large systems and hidden cross-section dependence," Research Memorandum 014, Maastricht University, Graduate School of Business and Economics (GSBE).
    39. Giannoni, Marc & Mihov, Ilian & Boivin, Jean, 2007. "Sticky Prices and Monetary Policy: Evidence from Disaggregated US Data," CEPR Discussion Papers 6101, C.E.P.R. Discussion Papers.
    40. Andrade, Philippe & Zachariadis, Marios, 2016. "Global versus local shocks in micro price dynamics," Journal of International Economics, Elsevier, vol. 98(C), pages 78-92.
    41. Wagner Piazza Gaglianone & Osmani Teixeira de Carvalho Guillén & Francisco Marcos Rodrigues Figueiredo, 2015. "Local Unit Root and Inflationary Inertia in Brazil," Working Papers Series 406, Central Bank of Brazil, Research Department.
    42. Godday Uwawunkonye Ebuh & Afees Salisu & Victor Oboh & Nuruddeen Usman, 2023. "A test for the contributions of urban and rural inflation to inflation persistence in Nigeria," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 16(2), pages 222-246, May.
    43. Mario Forni & Marc Hallin & Marco Lippi & Paolo Zaffaroni, 2011. "One-Sided Representations of Generalized Dynamic Factor Models," EIEF Working Papers Series 1106, Einaudi Institute for Economics and Finance (EIEF), revised Mar 2011.
    44. Alberto Humala & Gabriel Rodríguez, 2011. "A Factorial Decomposition Of Inflation In Peru, An Alternative Measure Of Core Inflation," Documentos de Trabajo / Working Papers 2011-315, Departamento de Economía - Pontificia Universidad Católica del Perú.
    45. Bennouna, Hicham, 2019. "Interest rate pass-through in Morocco: Evidence from bank-level survey data," Economic Modelling, Elsevier, vol. 80(C), pages 142-157.
    46. Coleman, Simeon, 2012. "Where Does the Axe Fall? Inflation Dynamics and Poverty Rates: Regional and Sectoral Evidence for Ghana," World Development, Elsevier, vol. 40(12), pages 2454-2467.
    47. Nagayasu, Jun, 2012. "Regional inflation and industrial structure in monetary union," MPRA Paper 37310, University Library of Munich, Germany.
    48. Kumar, Ankit & Dash, Pradyumna, 2020. "Changing transmission of monetary policy on disaggregate inflation in India," Economic Modelling, Elsevier, vol. 92(C), pages 109-125.
    49. Jean Imbs & Eric Jondeau & Florian Pelgrin, 2011. "Sectoral Phillips curves and the aggregate Phillips curve," PSE-Ecole d'économie de Paris (Postprint) hal-00612310, HAL.
    50. Ivan Petrella & Emiliano Santoro, 2012. "Inflation Dynamics and Real Marginal Costs: New Evidence from U.S. Manufacturing Industries," Birkbeck Working Papers in Economics and Finance 1202, Birkbeck, Department of Economics, Mathematics & Statistics.
    51. Chi-Young Choi & Joo Yong Lee & Róisín O'Sullivan, 2015. "Monetary Policy Regime Change and Regional Inflation Dynamics: Looking through the Lens of Sector-Level Data for Korea," Working Papers 2015-20, Economic Research Institute, Bank of Korea.
    52. Tule, Moses K. & Salisu, Afees A. & Ebuh, Godday U., 2020. "A test for inflation persistence in Nigeria using fractional integration & fractional cointegration techniques," Economic Modelling, Elsevier, vol. 87(C), pages 225-237.
    53. Ryo Kato & Tatsushi Okuda & Takayuki Tsuruga, 2020. "Sectoral inflation persistence, market concentration and imperfect common knowledge," ISER Discussion Paper 1082, Institute of Social and Economic Research, Osaka University.
    54. Christiane Baumeister & Philip Liu & Haroon Mumtaz, 2012. "Changes in the Effects of Monetary Policy on Disaggregate Price Dynamics," Staff Working Papers 12-13, Bank of Canada.
    55. Bernard Candelpergher & Michel Miniconi & Florian Pelgrin, 2015. "Long-memory process and aggregation of AR(1) stochastic processes: A new characterization," Working Papers hal-01166527, HAL.
    56. Caggiano, Giovanni & Castelnuovo, Efrem, 2011. "On the dynamics of international inflation," Economics Letters, Elsevier, vol. 112(2), pages 189-191, August.
    57. Mirko Abbritti & Luis A. Gil-Alana & Yuliya Lovcha & Antonio Moreno, 2016. "Term Structure Persistence," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 331-352.
    58. Goliński, Adam & Zaffaroni, Paolo, 2016. "Long memory affine term structure models," Journal of Econometrics, Elsevier, vol. 191(1), pages 33-56.
    59. Panpan Zhu & Qingjie Zhou & Yinpeng Zhang, 2024. "Investor attention and consumer price index inflation rate: Evidence from the United States," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.
    60. Sondermann, David, 2012. "Productivity in the euro area: any evidence of convergence?," Working Paper Series 1431, European Central Bank.
    61. Pongpitch Amatyakul & Deniz Igan & Marco Jacopo Lombardi, 2024. "Sectoral price dynamics in the last mile of post-Covid-19 disinflation," BIS Quarterly Review, Bank for International Settlements, March.
    62. Marcus Cobb, 2009. "Forecasting Chilean Inflation From Disaggregate Components," Working Papers Central Bank of Chile 545, Central Bank of Chile.
    63. Jamie Armour, 2006. "An Evaluation of Core Inflation Measures," Staff Working Papers 06-10, Bank of Canada.
    64. César Castro & Rebeca Jiménez-Rodríguez & Pilar Poncela & Eva Senra, 2017. "A new look at oil price pass-through into inflation: evidence from disaggregated European data," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 34(1), pages 55-82, April.
    65. Carvalho Carlos, 2006. "Heterogeneity in Price Stickiness and the Real Effects of Monetary Shocks," The B.E. Journal of Macroeconomics, De Gruyter, vol. 6(1), pages 1-58, December.
    66. Claudio Borio & Piti Disyatat & Dora Xia & Egon Zakrajšek, 2021. "Monetary policy, relative prices and inflation control: flexibility born out of success," BIS Quarterly Review, Bank for International Settlements, September.
    67. Viacheslav Kramkov, 2023. "Does CPI disaggregation improve inflation forecast accuracy?," Bank of Russia Working Paper Series wps112, Bank of Russia.
    68. Gregory de Walque & Frank Smets & Raf Wouters, 2006. "Price Shocks in General Equilibrium: Alternative Specifications," CESifo Economic Studies, CESifo Group, vol. 52(1), pages 153-176, March.
    69. Gianluca, MORETTI & Giulio, NICOLETTI, 2008. "Estimating DGSE models with long memory dynamics," Discussion Papers (ECON - Département des Sciences Economiques) 2008037, Université catholique de Louvain, Département des Sciences Economiques.
    70. Marlene Amstad & Simon Potter & Robert Rich, 2014. "The FRBNY Staff Underlying Inflation Gauge: UIG," BIS Working Papers 453, Bank for International Settlements.
    71. Claudio Borio & Marco Jacopo Lombardi & James Yetman & Egon Zakrajsek, 2023. "The two-regime view of inflation," BIS Papers, Bank for International Settlements, number 133.
    72. Agnieszka Leszczynska & Katarzyna Hertel, 2013. "Inflation persistence – a disaggregated approach," EcoMod2013 5692, EcoMod.
    73. Horváth, Roman & Podpiera, Anca, 2012. "Heterogeneity in bank pricing policies: The Czech evidence," Economic Systems, Elsevier, vol. 36(1), pages 87-108.
    74. Shu-hen Chiang, 2016. "Rising residential rents in Chinese mega cities: The role of monetary policy," Urban Studies, Urban Studies Journal Limited, vol. 53(16), pages 3493-3509, December.
    75. Choi, Chi-Young & O'Sullivan, Róisín, 2013. "Heterogeneous response of disaggregate inflation to monetary policy regime change: The role of price stickiness," Journal of Economic Dynamics and Control, Elsevier, vol. 37(9), pages 1814-1832.
    76. David Fielding, 2010. "Non-monetary Determinants of Inflation Volatility: Evidence from Nigeria," Journal of African Economies, Centre for the Study of African Economies, vol. 19(1), pages 111-139, January.
    77. Cristina Conflitti, 2020. "Alternative measures of underlying inflation in the euro area," Questioni di Economia e Finanza (Occasional Papers) 593, Bank of Italy, Economic Research and International Relations Area.
    78. Gent Bajraj & Guillermo Carlomagno & Juan M. Wlasiuk, 2023. "Where is the Inflation? The Diverging Patterns of Prices of Goods and Services," Working Papers Central Bank of Chile 969, Central Bank of Chile.
    79. Philippe Andrade & Marios Zachariadis, 2010. "Trends in International Prices," University of Cyprus Working Papers in Economics 02-2010, University of Cyprus Department of Economics.
    80. Millard, Stephen & O'Grady, Tom, 2012. "What do sticky and flexible prices tell us?," Bank of England working papers 457, Bank of England.

  9. Paolo Zaffaroni, 2008. "Large‐scale volatility models: theoretical properties of professionals’ practice," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(3), pages 581-599, May.

    Cited by:

    1. João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.
    2. Sbrana, Giacomo & Silvestrini, Andrea, 2013. "Aggregation of exponential smoothing processes with an application to portfolio risk evaluation," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1437-1450.
    3. Erik Kole & Thijs Markwat & Anne Opschoor & Dick van Dijk, 2017. "Forecasting Value-at-Risk under Temporal and Portfolio Aggregation," Journal of Financial Econometrics, Oxford University Press, vol. 15(4), pages 649-677.
    4. Pesaran, M. Hashem & Schleicher, Christoph & Zaffaroni, Paolo, 2009. "Model averaging in risk management with an application to futures markets," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 280-305, March.
    5. Morana, Claudio & Sbrana, Giacomo, 2019. "Climate change implications for the catastrophe bonds market: An empirical analysis," Economic Modelling, Elsevier, vol. 81(C), pages 274-294.
    6. Hugh Christensen & Simon Godsill & Richard E Turner, 2020. "Hidden Markov Models Applied To Intraday Momentum Trading With Side Information," Papers 2006.08307, arXiv.org.
    7. Santos, André Alves Portela & Ferreira, Alexandre R., 2017. "On the choice of covariance specifications for portfolio selection problems," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 37(1), May.

  10. Paolo Zaffaroni, 2007. "Contemporaneous aggregation of GARCH processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(4), pages 521-544, July.
    See citations under working paper version above.
  11. Hidalgo, Javier & Zaffaroni, Paolo, 2007. "A goodness-of-fit test for ARCH([infinity]) models," Journal of Econometrics, Elsevier, vol. 141(2), pages 835-875, December.

    Cited by:

    1. Sergei Guriev & Mikhail Klimenko, 2015. "Duration and Term Structure of Trade Agreements," Economic Journal, Royal Economic Society, vol. 125(589), pages 1818-1849, December.
    2. Corradi, Valentina & Iglesias, Emma M., 2008. "Bootstrap refinements for QML estimators of the GARCH(1,1) parameters," Journal of Econometrics, Elsevier, vol. 144(2), pages 500-510, June.
    3. Christophe Hurlin & Sébastien Laurent & Rogier Quaedvlieg & Stephan Smeekes, 2017. "Risk Measure Inference," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 499-512, October.
    4. González-Rivera, Gloria & Veiga, Helena, 2016. "A Bootstrap Approach for Generalized Autocontour Testing," DES - Working Papers. Statistics and Econometrics. WS 23457, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Moon, Seongman & Velasco, Carlos, 2013. "Tests for m-dependence based on sample splitting methods," Journal of Econometrics, Elsevier, vol. 173(2), pages 143-159.
    6. Christian Conrad, 2007. "Non-negativity Conditions for the Hyperbolic GARCH Model," KOF Working papers 07-162, KOF Swiss Economic Institute, ETH Zurich.

  12. Zaffaroni, Paolo, 2007. "Aggregation and memory of models of changing volatility," Journal of Econometrics, Elsevier, vol. 136(1), pages 237-249, January.

    Cited by:

    1. Pilipauskaitė, Vytautė & Surgailis, Donatas, 2015. "Joint aggregation of random-coefficient AR(1) processes with common innovations," Statistics & Probability Letters, Elsevier, vol. 101(C), pages 73-82.
    2. Pilipauskaitė, Vytautė & Surgailis, Donatas, 2014. "Joint temporal and contemporaneous aggregation of random-coefficient AR(1) processes," Stochastic Processes and their Applications, Elsevier, vol. 124(2), pages 1011-1035.
    3. Rosella Castellano & Roy Cerqueti & Giulia Rotundo, 2020. "Exploring the financial risk of a temperature index: a fractional integrated approach," Annals of Operations Research, Springer, vol. 284(1), pages 225-242, January.
    4. Andrea Silvestrini & David Veredas, 2008. "Temporal aggregation of univariate and multivariate time series models: A survey," Temi di discussione (Economic working papers) 685, Bank of Italy, Economic Research and International Relations Area.
    5. Beran, Jan & Schützner, Martin & Ghosh, Sucharita, 2010. "From short to long memory: Aggregation and estimation," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2432-2442, November.
    6. Samet Günay, 2016. "Performance of the Multifractal Model of Asset Returns (MMAR): Evidence from Emerging Stock Markets," IJFS, MDPI, vol. 4(2), pages 1-17, May.
    7. Jan Beran & Haiyan Liu & Sucharita Ghosh, 2020. "On aggregation of strongly dependent time series," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(3), pages 690-710, September.

  13. Zaffaroni, Paolo, 2004. "Stationarity And Memory Of Arch(∞) Models," Econometric Theory, Cambridge University Press, vol. 20(1), pages 147-160, February.

    Cited by:

    1. Josu Arteche, 2012. "Standard and seasonal long memory in volatility: an application to Spanish inflation," Empirical Economics, Springer, vol. 42(3), pages 693-712, June.
    2. Li, Muyi & Li, Wai Keung & Li, Guodong, 2015. "A new hyperbolic GARCH model," Journal of Econometrics, Elsevier, vol. 189(2), pages 428-436.
    3. Dominique Guegan, 2005. "How can we Define the Concept of Long Memory? An Econometric Survey," Econometric Reviews, Taylor & Francis Journals, vol. 24(2), pages 113-149.
    4. Harry Vander Elst, 2015. "FloGARCH : Realizing long memory and asymmetries in returns volatility," Working Paper Research 280, National Bank of Belgium.
    5. Kwan, Wilson & Li, Wai Keung & Li, Guodong, 2012. "On the estimation and diagnostic checking of the ARFIMA–HYGARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3632-3644.
    6. Carl Lönnbark, 2016. "Asymmetry with respect to the memory in stock market volatilities," Empirical Economics, Springer, vol. 50(4), pages 1409-1419, June.
    7. Serge Darolles & Gaëlle Le Fol & Yang Lu & Ran Sun, 2019. "Bivariate integer-autoregressive process with an application to mutual fund flows," Post-Print hal-04582262, HAL.
    8. Royer, Julien, 2023. "Conditional asymmetry in Power ARCH(∞) models," Journal of Econometrics, Elsevier, vol. 234(1), pages 178-204.
    9. Conrad, Christian & Karanasos, Menelaos, 2006. "The impulse response function of the long memory GARCH process," Economics Letters, Elsevier, vol. 90(1), pages 34-41, January.
    10. Robinson, Peter M. & Zaffaroni, Paolo, 2005. "Pseudo-maximum likelihood estimation of ARCH(∞) models," LSE Research Online Documents on Economics 58182, London School of Economics and Political Science, LSE Library.
    11. Royer, Julien, 2021. "Conditional asymmetry in Power ARCH($\infty$) models," MPRA Paper 109118, University Library of Munich, Germany.
    12. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "Predicting bid-ask spreads using long memory autoregressive conditional poisson models," SFB 649 Discussion Papers 2011-044, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    13. Bordignon, Silvano & Caporin, Massimiliano & Lisi, Francesco, 2007. "Generalised long-memory GARCH models for intra-daily volatility," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5900-5912, August.
    14. Dominique Guegan, 2007. "La persistance dans les marchés financiers," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00179269, HAL.
    15. Christian Conrad, 2007. "Non-negativity Conditions for the Hyperbolic GARCH Model," KOF Working papers 07-162, KOF Swiss Economic Institute, ETH Zurich.
    16. Veiga, Helena, 2006. "Modelling long-memory volatilities with leverage effect: ALMSV versus FIEGARCH," DES - Working Papers. Statistics and Econometrics. WS ws066016, Universidad Carlos III de Madrid. Departamento de Estadística.
    17. Peter M Robinson & Paolo Zaffaroni, 2005. "Pseudo-Maximum Likelihood Estimation of ARCH(8) Models," STICERD - Econometrics Paper Series 495, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    18. Muyi Li & Wai Keung Li & Guodong Li, 2013. "On Mixture Memory Garch Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(6), pages 606-624, November.
    19. Bildirici, Melike & Ersin, Özgür, 2012. "Nonlinear volatility models in economics: smooth transition and neural network augmented GARCH, APGARCH, FIGARCH and FIAPGARCH models," MPRA Paper 40330, University Library of Munich, Germany, revised May 2012.
    20. Antypas, Antonios & Koundouri, Phoebe & Kourogenis, Nikolaos, 2013. "Aggregational Gaussianity and barely infinite variance in financial returns," Journal of Empirical Finance, Elsevier, vol. 20(C), pages 102-108.
    21. Robinson, Peter M. & Zafaroni, Paolo, 2005. "Pseudo-maximum likelihood estimation of ARCH models," LSE Research Online Documents on Economics 4544, London School of Economics and Political Science, LSE Library.
    22. Jondeau, Eric, 2015. "The dynamics of squared returns under contemporaneous aggregation of GARCH models," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 80-93.
    23. Souhir Ben Amor & Heni Boubaker & Lotfi Belkacem, 2022. "A Dual Generalized Long Memory Modelling for Forecasting Electricity Spot Price: Neural Network and Wavelet Estimate," Papers 2204.08289, arXiv.org.
    24. Darolles, Serge & Fol, Gaëlle Le & Lu, Yang & Sun, Ran, 2019. "Bivariate integer-autoregressive process with an application to mutual fund flows," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 181-203.

  14. Zaffaroni, Paolo, 2004. "Contemporaneous aggregation of linear dynamic models in large economies," Journal of Econometrics, Elsevier, vol. 120(1), pages 75-102, May.

    Cited by:

    1. Frédérick Demers & Annie De Champlain, 2005. "Forecasting Core Inflation in Canada: Should We Forecast the Aggregate or the Components?," Staff Working Papers 05-44, Bank of Canada.
    2. Yulei Luo & Jun Nie & Eric R. Young, 2015. "Slow Information Diffusion And The Inertial Behavior Of Durable Consumption," Journal of the European Economic Association, European Economic Association, vol. 13(5), pages 805-840, October.
    3. Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018. "Generating Univariate Fractional Integration within a Large VAR(1)," AMSE Working Papers 1844, Aix-Marseille School of Economics, France.
    4. Ian Babetskii & Fabrizio Coricelli & Roman Horvath, 2009. "Assessing Inflation Persistence: Micro Evidence on an Inflation Targeting Economy," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00643340, HAL.
    5. Remigijus Leipus & Anne Philippe & Vytautė Pilipauskaitė & Donatas Surgailis, 2020. "Estimating Long Memory in Panel Random‐Coefficient AR(1) Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(4), pages 520-535, July.
    6. Pilipauskaitė, Vytautė & Surgailis, Donatas, 2015. "Joint aggregation of random-coefficient AR(1) processes with common innovations," Statistics & Probability Letters, Elsevier, vol. 101(C), pages 73-82.
    7. Cristina Conflitti & Matteo Luciani, 2019. "Oil Price Pass-Through into Core Inflation," FEDS Notes 2019-04-30, Board of Governors of the Federal Reserve System (U.S.).
    8. Alexander Chudik & M. Hashem Pesaran, 2011. "Aggregation in large dynamic panels," Globalization Institute Working Papers 101, Federal Reserve Bank of Dallas.
    9. Winkelried, Diego & Castillo, Paul, 2010. "Dollarization persistence and individual heterogeneity," Journal of International Money and Finance, Elsevier, vol. 29(8), pages 1596-1618, December.
    10. Jondeau, Eric & Imbs, Jean & Pelgrin, Florian, 2007. "Aggregating Phillips Curves," CEPR Discussion Papers 6184, C.E.P.R. Discussion Papers.
    11. Kunal Saha & Vinodh Madhavan & Chandrashekhar G. R. & David McMillan, 2020. "Pitfalls in long memory research," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1733280-173, January.
    12. Pilipauskaitė, Vytautė & Surgailis, Donatas, 2014. "Joint temporal and contemporaneous aggregation of random-coefficient AR(1) processes," Stochastic Processes and their Applications, Elsevier, vol. 124(2), pages 1011-1035.
    13. Chevillon, Guillaume & Mavroeidis, Sophocles, 2011. "Learning generates Long Memory," ESSEC Working Papers WP1113, ESSEC Research Center, ESSEC Business School.
    14. Jeffrey C. Fuhrer, 2009. "Inflation persistence," Working Papers 09-14, Federal Reserve Bank of Boston.
    15. Laura Mayoral, 2005. "The persistence of inflation in OECD countries: A fractionally integrated approach," Economics Working Papers 958, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2005.
    16. J. Eduardo Vera-Valdés, 2021. "Temperature Anomalies, Long Memory, and Aggregation," Econometrics, MDPI, vol. 9(1), pages 1-22, March.
    17. Simone Elmer & Thomas Maag, 2009. "The Persistence of Inflation in Switzerland," KOF Working papers 09-235, KOF Swiss Economic Institute, ETH Zurich.
    18. Laura Mayoral, 2009. "Heterogeneous dynamics, aggregation and the persistence of economic shocks," UFAE and IAE Working Papers 786.09, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    19. Joseph P. Byrne & Alexandros Kontonikas & Alberto Montagnoli, 2010. "The Time‐Series Properties Of Uk Inflation: Evidence From Aggregate And Disaggregate Data," Scottish Journal of Political Economy, Scottish Economic Society, vol. 57(1), pages 33-47, February.
    20. Angelos Liontakis & Dimitris Kremmydas, 2013. "Food Inflation in EU: Distribution Analysis and Spatial Effects," Working Papers 2013-3, Agricultural University of Athens, Department Of Agricultural Economics.
    21. Taner Yigit, 2007. "Inflation Targeting : An Indirect Approach to Assess the Direct Impact," Working Papers 0706, Department of Economics, Bilkent University.
    22. M. Dolores Gadea & Laura Mayoral, 2009. "Aggregation is not the solution: the PPP puzzle strikes back," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(6), pages 875-894.
    23. Gil-Alana, Luis A. & Mudida, Robert & Zerbo, Eleazar, 2021. "GDP per capita IN SUB-SAHARAN Africa: A time series approach using long memory," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 175-190.
    24. Arturo Leccadito & Omar Rachedi & Giovanni Urga, 2015. "True Versus Spurious Long Memory: Some Theoretical Results and a Monte Carlo Comparison," Econometric Reviews, Taylor & Francis Journals, vol. 34(4), pages 452-479, April.
    25. J. Eduardo Vera-Vald'es, 2017. "On Long Memory Origins and Forecast Horizons," Papers 1712.08057, arXiv.org.
    26. Carlos Carvalho & Fernanda Nechio, 2008. "Aggregation and the PPP puzzle in a sticky-price model," Staff Reports 351, Federal Reserve Bank of New York.
    27. Roman Horvath & Fabrizio Coricelli, 2010. "Price setting and market structure: an empirical analysis of micro data in Slovakia," PSE-Ecole d'économie de Paris (Postprint) hal-00643319, HAL.
    28. Ian Babetskii & Fabrizio Coricelli & Roman Horváth, 2007. "Measuring and Explaining Inflation Persistence: Disaggregate Evidence on the Czech Republic," Working Papers IES 2007/22, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Aug 2007.
    29. Patrick Lünnemann & Thomas Y. Mathä, 2004. "Inflation persistence in Luxembourg: a comparison with EU15 countries at the disaggregate level," BCL working papers 12, Central Bank of Luxembourg.
    30. Eric JONDEAU & Florian PELGRIN, 2014. "Estimating Aggregate Autoregressive Processes When Only Macro Data are Available," Swiss Finance Institute Research Paper Series 14-43, Swiss Finance Institute.
    31. Chevillon, G. & Hecq, A.W. & Laurent, S.F.J.A., 2015. "Long memory through marginalization of large systems and hidden cross-section dependence," Research Memorandum 014, Maastricht University, Graduate School of Business and Economics (GSBE).
    32. Javier Haulde & Morten Ørregaard Nielsen, 2022. "Fractional integration and cointegration," CREATES Research Papers 2022-02, Department of Economics and Business Economics, Aarhus University.
    33. Maria Kalli & Jim Griffin, 2015. "Flexible Modeling of Dependence in Volatility Processes," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 102-113, January.
    34. Kang, Sang Hoon & Cheong, Chongcheul & Yoon, Seong-Min, 2010. "Contemporaneous aggregation and long-memory property of returns and volatility in the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4844-4854.
    35. Haldrup, Niels & Vera Valdés, J. Eduardo, 2017. "Long memory, fractional integration, and cross-sectional aggregation," Journal of Econometrics, Elsevier, vol. 199(1), pages 1-11.
    36. Dmitrij Celov & Remigijus Leipus & Anne Philippe, 2010. "Asymptotic normality of the mixture density estimator in a disaggregation scheme," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(4), pages 425-442.
    37. Jean Imbs & Eric Jondeau & Florian Pelgrin, 2011. "Sectoral Phillips curves and the aggregate Phillips curve," PSE-Ecole d'économie de Paris (Postprint) hal-00612310, HAL.
    38. Giovanni Caggiano & Efrem Castelnuovo, 2008. "Long Memory and Non-Linearities in International Inflation," "Marco Fanno" Working Papers 0076, Dipartimento di Scienze Economiche "Marco Fanno".
    39. Beran, Jan & Schützner, Martin & Ghosh, Sucharita, 2010. "From short to long memory: Aggregation and estimation," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2432-2442, November.
    40. Federico Carlini & Paolo Santucci de Magistris, 2019. "Resuscitating the co-fractional model of Granger (1986)," CREATES Research Papers 2019-02, Department of Economics and Business Economics, Aarhus University.
    41. Neusser, Klaus, 2008. "Interdependencies of US manufacturing sectoral TFPs: A spatial VAR approach," Journal of Macroeconomics, Elsevier, vol. 30(3), pages 991-1004, September.
    42. Thornton, Michael A., 2014. "The aggregation of dynamic relationships caused by incomplete information," Journal of Econometrics, Elsevier, vol. 178(P2), pages 342-351.
    43. Anne Philippe & Donata Puplinskaite & Donatas Surgailis, 2014. "Contemporaneous Aggregation Of Triangular Array Of Random-Coefficient Ar(1) Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(1), pages 16-39, January.
    44. Jan Beran & Haiyan Liu & Sucharita Ghosh, 2020. "On aggregation of strongly dependent time series," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(3), pages 690-710, September.
    45. Bernard Candelpergher & Michel Miniconi & Florian Pelgrin, 2015. "Long-memory process and aggregation of AR(1) stochastic processes: A new characterization," Working Papers hal-01166527, HAL.
    46. Laura Mayoral, 2013. "Heterogeneous Dynamics, Aggregation, And The Persistence Of Economic Shocks," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 54(4), pages 1295-1307, November.
    47. Goliński, Adam & Zaffaroni, Paolo, 2016. "Long memory affine term structure models," Journal of Econometrics, Elsevier, vol. 191(1), pages 33-56.
    48. Roy Cerqueti & Giulia Rotundo, 2015. "A review of aggregation techniques for agent-based models: understanding the presence of long-term memory," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(4), pages 1693-1717, July.
    49. Zaffaroni, Paolo, 2007. "Aggregation and memory of models of changing volatility," Journal of Econometrics, Elsevier, vol. 136(1), pages 237-249, January.
    50. Chevillon, Guillaume & Mavroeidis, Sophocles, 2017. "Learning can generate long memory," Journal of Econometrics, Elsevier, vol. 198(1), pages 1-9.
    51. Altissimo, Filippo & Mojon, Benoit & Zaffaroni, Paolo, 2009. "Can aggregation explain the persistence of inflation?," Journal of Monetary Economics, Elsevier, vol. 56(2), pages 231-241, March.
    52. Grassi, Stefano & Santucci de Magistris, Paolo, 2014. "When long memory meets the Kalman filter: A comparative study," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 301-319.
    53. Laura Mayoral, 2005. "Further evidence on the statistical properties of real GNP," Economics Working Papers 955, Department of Economics and Business, Universitat Pompeu Fabra, revised Feb 2006.
    54. M. Ege Yazgan & Hakan Yilmazkuday, 2015. "High versus Low Inflation: Implications for Price-Level Convergence," Working Papers 1503, Florida International University, Department of Economics.
    55. J. Eduardo Vera-Vald'es, 2018. "Nonfractional Memory: Filtering, Antipersistence, and Forecasting," Papers 1801.06677, arXiv.org.
    56. Caporale, Guglielmo Maria & Gil-Alana, Luis A. & Poza, Carlos, 2020. "High and low prices and the range in the European stock markets: A long-memory approach," Research in International Business and Finance, Elsevier, vol. 52(C).
    57. Jondeau, Eric, 2015. "The dynamics of squared returns under contemporaneous aggregation of GARCH models," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 80-93.
    58. Federico Carlini & Paolo Santucci de Magistris, 2019. "Resuscitating the co-fractional model of Granger (1986)," Discussion Papers 19/01, University of Nottingham, Granger Centre for Time Series Econometrics.
    59. Horváth, Roman & Podpiera, Anca, 2012. "Heterogeneity in bank pricing policies: The Czech evidence," Economic Systems, Elsevier, vol. 36(1), pages 87-108.
    60. Katsurako Sonoda, 2006. "An Empirical Analysis of Price Stickiness and Price Revision Behavior in Japan Using Micro CPI Data," Bank of Japan Working Paper Series 06-E-8, Bank of Japan.
    61. Jim Griffin & Maria Kalli & Mark Steel, 2018. "Discussion of “Nonparametric Bayesian Inference in Applications”: Bayesian nonparametric methods in econometrics," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(2), pages 207-218, June.
    62. Czado, Claudia & Ivanov, Eugen & Okhrin, Yarema, 2019. "Modelling temporal dependence of realized variances with vines," Econometrics and Statistics, Elsevier, vol. 12(C), pages 198-216.

  15. Zaffaroni, Paolo & d'Italia, Banca, 2003. "Gaussian inference on certain long-range dependent volatility models," Journal of Econometrics, Elsevier, vol. 115(2), pages 199-258, August.
    See citations under working paper version above.
  16. Michelacci, Claudio & Zaffaroni, Paolo, 2000. "(Fractional) beta convergence," Journal of Monetary Economics, Elsevier, vol. 45(1), pages 129-153, February.
    See citations under working paper version above.
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