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Dante Amengual

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. Dante Amengual & Gabriele Fiorentini & Martín Almuzara & Enrique Sentana, 2022. "GDP Solera: The Ideal Vintage Mix," Staff Reports 1027, Federal Reserve Bank of New York.

    Cited by:

    1. Gabriele Fiorentini & Martín Almuzara & Enrique Sentana, 2021. "Aggregate Output Measurements: A Common Trend Approach," Staff Reports 962, Federal Reserve Bank of New York.
    2. Buccheri, Giuseppe & Renò, Roberto & Vocalelli, Giorgio, 2025. "Taking advantage of biased proxies for forecast evaluation," Journal of Econometrics, Elsevier, vol. 251(C).
    3. Eiji Goto & Jan P.A.M. Jacobs & Simon van Norden, 2025. "Data-Driven Learning About Trend Productivity Growth," CIRANO Working Papers 2025s-29, CIRANO.

  2. Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2021. "Moment tests of independent components," Working Papers wp2021_2102, CEMFI.

    Cited by:

    1. Robin Braun, 2023. "The importance of supply and demand for oil prices: Evidence from non‐Gaussianity," Quantitative Economics, Econometric Society, vol. 14(4), pages 1163-1198, November.
    2. Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2022. "Specification tests for non-Gaussian structural vector autoregressions," Working Papers wp2022_2212, CEMFI.
    3. Davis, Richard & Ng, Serena, 2023. "Time series estimation of the dynamic effects of disaster-type shocks," Journal of Econometrics, Elsevier, vol. 235(1), pages 180-201.
    4. Gabriele Fiorentini & Enrique Sentana, 2021. "Specification tests for non‐Gaussian maximum likelihood estimators," Quantitative Economics, Econometric Society, vol. 12(3), pages 683-742, July.
    5. Gabriele Fiorentini & Alessio Moneta & Francesca Papagni, 2024. "Identification of one independent shock in structural VARs," LEM Papers Series 2024/28, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    6. Fiorentini, Gabriele & Sentana, Enrique, 2023. "Discrete mixtures of normals pseudo maximum likelihood estimators of structural vector autoregressions," Journal of Econometrics, Elsevier, vol. 235(2), pages 643-665.
    7. Sascha A. Keweloh, 2023. "Structural Vector Autoregressions and Higher Moments: Challenges and Solutions in Small Samples," Papers 2310.08173, arXiv.org.

  3. Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2021. "Multivariate Hermite polynomials and information matrix tests," Econometrics Working Papers Archive 2021_07, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2021. "Tests for random coefficient variation in vector autoregressive models," Econometrics Working Papers Archive 2021_18, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

  4. Sentana, Enrique & Amengual, Dante & Bei, Xinyue, 2020. "Hypothesis tests with a repeatedly singular information matrix," CEPR Discussion Papers 14415, C.E.P.R. Discussion Papers.

    Cited by:

    1. Dante Amengual & Xinyue Bei & Enrique Sentana, 2022. "Normal but skewed?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(7), pages 1295-1313, November.
    2. Dante Amengual & Xinyue Bei & Marine Carrasco & Enrique Sentana, 2023. "Score-type tests for normal mixtures," CIRANO Working Papers 2023s-02, CIRANO.

  5. Sentana, Enrique & Amengual, Dante & Tian, Zhanyuan, 2020. "Gaussian rank correlation and regression," CEPR Discussion Papers 14914, C.E.P.R. Discussion Papers.

    Cited by:

    1. Tony Chernis & Patrick J. Coe & Shaun P. Vahey, 2023. "Reassessing the dependence between economic growth and financial conditions since 1973," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(2), pages 260-267, March.
    2. Amengual, Dante & Bei, Xinyue & Carrasco, Marine & Sentana, Enrique, 2025. "Score-type tests for normal mixtures," Journal of Econometrics, Elsevier, vol. 248(C).
    3. Dante Amengual & Xinyue Bei & Enrique Sentana, 2021. "Normal but Skewed?," Working Papers wp2021_2104, CEMFI.
    4. Dante Amengual & Xinyue Bei & Enrique Sentana, 2020. "Hypothesis Tests with a Repeatedly Singular Information Matrix," Working Papers wp2020_2002, CEMFI.
    5. Garratt, Anthony & Henckel, Timo & Vahey, Shaun P., 2023. "Empirically-transformed linear opinion pools," International Journal of Forecasting, Elsevier, vol. 39(2), pages 736-753.

  6. Amengual, D.; Bueren, J.; Crego, J.A.;, 2017. "Endogenous Health Groups and Heterogeneous Dynamics of the Elderly," Health, Econometrics and Data Group (HEDG) Working Papers 17/18, HEDG, c/o Department of Economics, University of York.

    Cited by:

    1. Roozbei Hosseini & Karen Kopecky & Kai Zhao, 2022. "The Evolution of Health over the Life Cycle," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 45, pages 237-263, July.
    2. Maira Colacce & Julia Córdoba & Alejandra Marroig & Guillermo Sánchez, 2021. "Clases latentes de dependencia en Uruguay," Documentos de Trabajo (working papers) 21-23, Instituto de Economía - IECON.
    3. Martin Garcia-Vazquez, 2021. "Identification and Estimation of Non-stationary Hidden Markov Models," Working Papers 2021-023, Human Capital and Economic Opportunity Working Group.
    4. Siqi Wei, 2022. "Income, Employment and Health Risks of Older Workers," Working Papers wp2022_2205, CEMFI.

  7. Tincho Almuzara & Dante Amengual & Enrique Sentana, 2017. "Normality Tests for Latent Variables," Working Papers wp2017_1708, CEMFI.

    Cited by:

    1. Demetrescu, Matei & Kruse-Becher, Robinson, 2025. "Is U.S. real output growth non-normal? A tale of time-varying location and scale," Journal of Economic Dynamics and Control, Elsevier, vol. 171(C).
    2. Gabriele Fiorentini & Martín Almuzara & Enrique Sentana, 2021. "Aggregate Output Measurements: A Common Trend Approach," Staff Reports 962, Federal Reserve Bank of New York.
    3. Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2022. "Moment tests of independent components," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(1), pages 429-474, May.
    4. Amengual, Dante & Bei, Xinyue & Carrasco, Marine & Sentana, Enrique, 2025. "Score-type tests for normal mixtures," Journal of Econometrics, Elsevier, vol. 248(C).
    5. Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2021. "Tests for random coefficient variation in vector autoregressive models," Econometrics Working Papers Archive 2021_18, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    6. Amengual, Dante & Fiorentini, Gabriele & Sentana, Enrique, 2025. "Information matrix tests for multinomial logit models," Economics Letters, Elsevier, vol. 247(C).
    7. 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.
    8. Matei Demetrescu & Robinson Kruse-Becher, 2021. "Is U.S. real output growth really non-normal? Testing distributional assumptions in time-varying location-scale models," CREATES Research Papers 2021-07, Department of Economics and Business Economics, Aarhus University.
    9. Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2024. "The information matrix test for Gaussian mixtures," Working Papers wp2024_2401, CEMFI.
    10. Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2025. "The information matrix test for Markov switching autoregressive models with covariate-dependent transition probabilities," Working Papers wp2025_2502, CEMFI.

  8. Dante Amengual & Marine Carrasco & Enrique Sentana, 2017. "Testing Distributional Assumptions Using a Continuum of Moments," Working Papers wp2017_1709, CEMFI.

    Cited by:

    1. Dante Amengual & Xinyue Bei & Marine Carrasco & Enrique Sentana, 2023. "Score-type tests for normal mixtures," CIRANO Working Papers 2023s-02, CIRANO.
    2. Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2022. "Specification tests for non-Gaussian structural vector autoregressions," Working Papers wp2022_2212, CEMFI.
    3. Guay, Alain & Pelgrin, Florian, 2023. "Structural VAR models in the Frequency Domain," Journal of Econometrics, Elsevier, vol. 236(1).
    4. Gabriele Fiorentini & Enrique Sentana, 2021. "Specification tests for non‐Gaussian maximum likelihood estimators," Quantitative Economics, Econometric Society, vol. 12(3), pages 683-742, July.
    5. Ron Mittelhammer & George Judge & Miguel Henry, 2022. "An Entropy-Based Approach for Nonparametrically Testing Simple Probability Distribution Hypotheses," Econometrics, MDPI, vol. 10(1), pages 1-19, January.
    6. Antoine, Bertille & Sun, Wenqian, 2025. "Simulation-based estimation with many auxiliary statistics applied to long-run dynamic analysis," Journal of Econometrics, Elsevier, vol. 248(C).

  9. Dante Amengual & Enrique Sentana, 2015. "Is a Normal Copula the Right Copula?," Working Papers wp2015_1504, CEMFI.

    Cited by:

    1. Fiorentini, Gabriele & Sentana, Enrique, 2021. "New testing approaches for mean–variance predictability," Journal of Econometrics, Elsevier, vol. 222(1), pages 516-538.
    2. Amengual, Dante & Fiorentini, Gabriele & Sentana, Enrique, 2024. "Specification tests for non-Gaussian structural vector autoregressions," Journal of Econometrics, Elsevier, vol. 244(2).
    3. Shiraya, Kenichiro & Yamakami, Tomohisa, 2024. "Constructing copulas using corrected Hermite polynomial expansion for estimating cross foreign exchange volatility," European Journal of Operational Research, Elsevier, vol. 314(3), pages 1195-1214.
    4. Liang Chen & Juan J. Dolado & Jesús Gonzalo, 2021. "Quantile Factor Models," Econometrica, Econometric Society, vol. 89(2), pages 875-910, March.
    5. Oh, Dong Hwan & Patton, Andrew J., 2023. "Dynamic factor copula models with estimated cluster assignments," Journal of Econometrics, Elsevier, vol. 237(2).
    6. Dante Amengual & Xinyue Bei & Enrique Sentana, 2020. "Hypothesis Tests with a Repeatedly Singular Information Matrix," Working Papers wp2020_2002, CEMFI.
    7. Woźny, Jakub & Jaworski, Piotr & Jelito, Damian & Pitera, Marcin & Wyłomańska, Agnieszka, 2025. "Gaussian dependence structure pairwise goodness-of-fit testing based on conditional covariance and the 20/60/20 rule," Journal of Multivariate Analysis, Elsevier, vol. 206(C).

  10. Dante Amengual & Luca Repetto, 2014. "Testing a Large Number of Hypotheses in Approximate Factor Models," Working Papers wp2014_1410, CEMFI.

    Cited by:

    1. Di Iorio, Francesca & Fachin, Stefano, 2021. "Evaluating restricted common factor models for non-stationary data," Econometrics and Statistics, Elsevier, vol. 17(C), pages 64-75.

  11. Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2012. "Sequential Estimation of Shape Parameters in Multivariate Dynamic Models," Working Papers wp2012_1201, CEMFI.

    Cited by:

    1. Francq, Christian & Zakoïan, Jean-Michel, 2025. "Inference on dynamic systemic risk measures," Journal of Econometrics, Elsevier, vol. 247(C).
    2. Sentana, Enrique & Fiorentini, Gabriele, 2018. "Specification tests for non-Gaussian maximum likelihood estimators," CEPR Discussion Papers 12934, C.E.P.R. Discussion Papers.
    3. Amengual, Dante & Fiorentini, Gabriele & Sentana, Enrique, 2024. "Specification tests for non-Gaussian structural vector autoregressions," Journal of Econometrics, Elsevier, vol. 244(2).
    4. Fiorentini, Gabriele & Sentana, Enrique, 2019. "Consistent non-Gaussian pseudo maximum likelihood estimators," Journal of Econometrics, Elsevier, vol. 213(2), pages 321-358.
    5. Bontemps, Christian, 2013. "Moment-Based Tests for Discrete Distributions," IDEI Working Papers 772, Institut d'Économie Industrielle (IDEI), Toulouse, revised Oct 2014.
    6. Javier Mencía & Enrique Sentana, 2015. "Volatility-Related Exchange Traded Assets: An Econometric Investigation," Working Papers wp2015_1501, CEMFI.
    7. Gabriele Fiorentini & Enrique Sentana, 2019. "Dynamic specification tests for dynamic factor models," Econometrics Working Papers Archive 2018_07, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    8. Bontemps, Christian, 2018. "Moment-based tests under parameter uncertainty," IDEI Working Papers 18-883, Institut d'Économie Industrielle (IDEI), Toulouse.
    9. Loïc Cantin & Christian Francq & Jean-Michel Zakoïan, 2022. "Estimating dynamic systemic risk measures," Working Papers 2022-11, Center for Research in Economics and Statistics.
    10. Bontemps, Christian, 2014. "Simple moment-based tests for value-at-risk models and discrete distribution," TSE Working Papers 14-535, Toulouse School of Economics (TSE).
    11. Enrique Sentana, 2018. "Volatility, Diversification and Contagion," Working Papers wp2018_1803, CEMFI.
    12. Gabriele Fiorentini & Enrique Sentana, 2012. "Tests for Serial Dependence in Static, Non-Gaussian Factor Models," Working Papers wp2012_1211, CEMFI.

  12. Dante Amengual & Enrique Sentana, 2008. "A Comparison of Mean-Variance Efficiency Tests," Working Papers wp2008_0806, CEMFI.

    Cited by:

    1. Manuel Arellano & Lars Peter Hansen & Enrique Sentana, 2009. "Underidentification? (Resumen)," Working Papers wp2009_0905, CEMFI.
    2. Sentana, Enrique & Fiorentini, Gabriele, 2018. "Specification tests for non-Gaussian maximum likelihood estimators," CEPR Discussion Papers 12934, C.E.P.R. Discussion Papers.
    3. Beaulieu, Marie-Claude & Dufour, Jean-Marie & Khalaf, Lynda, 2010. "Asset-pricing anomalies and spanning: Multivariate and multifactor tests with heavy-tailed distributions," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 763-782, September.
    4. Roberto Serrano, 2009. "On Watson’s Non-Forcing Contracts and Renegotiation," Working Papers wp2009_0907, CEMFI.
    5. Enrique Sentana, 2008. "The Econometrics of Mean-Variance Efficiency Tests: A Survey," Working Papers wp2008_0807, CEMFI.
    6. Fiorentini, Gabriele & Sentana, Enrique, 2019. "Consistent non-Gaussian pseudo maximum likelihood estimators," Journal of Econometrics, Elsevier, vol. 213(2), pages 321-358.
    7. Roberto Serrano & Rajiv Vohra, 2009. "Multiplicity of Mixed Equilibria in Mechanisms: A Unified Approach to Exact and Approximate Implementation," Working Papers wp2009_0908, CEMFI.
    8. Gabriele Fiorentini & Enrique Sentana, 2018. "New Testing Approaches for Mean-Variance Predictability," Working Papers wp2018_1814, CEMFI.
    9. Peñaranda, Francisco & Sentana, Enrique, 2012. "Spanning tests in return and stochastic discount factor mean–variance frontiers: A unifying approach," Journal of Econometrics, Elsevier, vol. 170(2), pages 303-324.
    10. Gabriele Fiorentini & Enrique Sentana, 2009. "Dynamic Specification Tests for Static Factor Models," Working Papers wp2009_0912, CEMFI.
    11. Zeng-Hua Lu, 2020. "Bahadur intercept with applications to one-sided testing," Statistical Papers, Springer, vol. 61(2), pages 645-658, April.
    12. Gabriele Fiorentini & Enrique Sentana, 2007. "On the Efficiency and Consistency of Likelihood Estimation in Multivariate Conditionally Heteroskedastic Dynamic Regression Models," Working Papers wp2007_0713, CEMFI.
    13. Yusuke Kamishiro & Roberto Serrano, 2009. "Equilibrium Blocking in Large Quasilinear Economies," Working Papers wp2009_0911, CEMFI.
    14. Rafael Repullo & Javier Suarez, 2008. "The Procyclical Effects of Basel II," Working Papers wp2008_0809, CEMFI.
    15. Gulliksson, Mårten & Mazur, Stepan, 2019. "An Iterative Approach to Ill-Conditioned Optimal Portfolio Selection," Working Papers 2019:3, Örebro University, School of Business.
    16. Max Bruche, 2009. "Bankruptcy Codes, Liquidation Timing, and Debt Valuation," Working Papers wp2009_0902, CEMFI.
    17. Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2012. "Sequential Estimation of Shape Parameters in Multivariate Dynamic Models," Working Papers wp2012_1201, CEMFI.
    18. Enrique Sentana, 2018. "Volatility, Diversification and Contagion," Working Papers wp2018_1803, CEMFI.
    19. Taras Bodnar & Nestor Parolya & Wolfgang Schmid, 2012. "A Closed-Form Solution of the Multi-Period Portfolio Choice Problem for a Quadratic Utility Function," Papers 1207.1003, arXiv.org, revised Nov 2014.
    20. Gabriele Fiorentini & Enrique Sentana, 2012. "Tests for Serial Dependence in Static, Non-Gaussian Factor Models," Working Papers wp2012_1211, CEMFI.

Articles

  1. Dante Amengual & Enrique Sentana, 2020. "Is a Normal Copula the Right Copula?," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 350-366, April.
    See citations under working paper version above.
  2. Amengual, Dante & Carrasco, Marine & Sentana, Enrique, 2020. "Testing distributional assumptions using a continuum of moments," Journal of Econometrics, Elsevier, vol. 218(2), pages 655-689.
    See citations under working paper version above.
  3. Martín Almuzara & Dante Amengual & Enrique Sentana, 2019. "Normality tests for latent variables," Quantitative Economics, Econometric Society, vol. 10(3), pages 981-1017, July.
    See citations under working paper version above.
  4. Amengual, Dante & Xiu, Dacheng, 2018. "Resolution of policy uncertainty and sudden declines in volatility," Journal of Econometrics, Elsevier, vol. 203(2), pages 297-315.

    Cited by:

    1. Gu, Chen & Kurov, Alexander & Wolfe, Marketa Halova, 2018. "Relief Rallies after FOMC Announcements as a Resolution of Uncertainty," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 1-18.
    2. Bollerslev, Tim & Todorov, Viktor, 2023. "The jump leverage risk premium," Journal of Financial Economics, Elsevier, vol. 150(3).
    3. Yang-Ho Park, 2019. "Variance Disparity and Market Frictions," Finance and Economics Discussion Series 2019-059, Board of Governors of the Federal Reserve System (U.S.).
    4. Caporin, Massimiliano & Kolokolov, Alexey & Renò, Roberto, 2016. "Systemic co-jumps," SAFE Working Paper Series 149, Leibniz Institute for Financial Research SAFE.
    5. Lorella Fatone & Francesca Mariani & Francesco Zirilli, 2024. "Calibration in the “real world” of a partially specified stochastic volatility model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(1), pages 75-102, January.
    6. Ai, Hengjie & Han, Leyla Jianyu & Pan, Xuhui Nick & Xu, Lai, 2022. "The cross section of the monetary policy announcement premium," Journal of Financial Economics, Elsevier, vol. 143(1), pages 247-276.
    7. Hollstein, Fabian & Prokopczuk, Marcel & Wese Simen, Chardin, 2017. "The Term Structure of Systematic and Idiosyncratic Risk," Hannover Economic Papers (HEP) dp-618, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    8. Aeimit Lakdawala & Michael Bauer & Philippe Mueller, 2019. "Market-Based Monetary Policy Uncertainty," 2019 Meeting Papers 1403, Society for Economic Dynamics.
    9. Megaritis, Anastasios & Vlastakis, Nikolaos & Triantafyllou, Athanasios, 2021. "Stock market volatility and jumps in times of uncertainty," Journal of International Money and Finance, Elsevier, vol. 113(C).
    10. Kiosses, Nikolaos & Leventis, Stergios & Subeniotis, Demetres & Tampakoudis, Ioannis, 2025. "The impact of policy uncertainty on shareholder wealth: Evidence from bank M&A," Journal of Financial Stability, Elsevier, vol. 76(C).
    11. Martin Hodula & Jan Janku & Simona Malovana & Ngoc Anh Ngo, 2024. "Geopolitical Risks and Their Impact on Global Macro-Financial Stability: Literature and Measurements," Working Papers 2024/8, Czech National Bank, Research and Statistics Department.
    12. Nguyen, Thanh Cong, 2022. "Economic policy uncertainty: The probability and duration of economic recessions in major European Union countries," Research in International Business and Finance, Elsevier, vol. 62(C).
    13. Liu, Hong & Tang, Xiaoxiao & Zhou, Guofu, 2022. "Recovering the FOMC risk premium," Journal of Financial Economics, Elsevier, vol. 145(1), pages 45-68.
    14. Deniz Erdemlioglu & Christopher J. Neely & Xiye Yang, 2023. "Testing for Multi-Asset Systemic Tail Risk," Working Papers 2023-016, Federal Reserve Bank of St. Louis, revised 09 Sep 2025.
    15. Wang, Yuchen & Wang, Xiaoming, 2023. "Economic policy uncertainty and information intermediary: The case of short seller," Economic Modelling, Elsevier, vol. 120(C).
    16. Pacati, Claudio & Pompa, Gabriele & Renò, Roberto, 2018. "Smiling twice: The Heston++ model," Journal of Banking & Finance, Elsevier, vol. 96(C), pages 185-206.
    17. Wu, Bin & Chen, Pengzhan & Ye, Wuyi, 2024. "Variance swaps with mean reversion and multi-factor variance," European Journal of Operational Research, Elsevier, vol. 315(1), pages 191-212.
    18. Difang Huang & Yubin Li & Xinjie Wang & Zhaodong (Ken) Zhong, 2022. "Does the Federal Open Market Committee cycle affect credit risk?," Financial Management, Financial Management Association International, vol. 51(1), pages 143-167, March.
    19. Hunter Ng, 2024. "Strategic Control of Facial Expressions by the Fed Chair," Papers 2410.20214, arXiv.org.
    20. Hong, Yun & Qu, Bo & Yang, Zhuohang & Jiang, Yanhui, 2023. "The contagion of fake news concern and extreme stock market risks during the COVID-19 period," Finance Research Letters, Elsevier, vol. 58(PA).
    21. Thomas Eisenbach & Martin Schmalz & Marianne Andries, 2015. "Asset Pricing with Horizon-Dependent Risk Aversion," 2015 Meeting Papers 1069, Society for Economic Dynamics.
    22. Bruno Feunou & Mohammad R. Jahan-Parvar & Cédric Okou, 2015. "Downside Variance Risk Premium," Staff Working Papers 15-36, Bank of Canada.
    23. Ahmed Al Samman & Mostafa Kotb GabAlla, 2020. "Impact of Country Risk and Return on FPI," International Journal of Economics and Financial Issues, Econjournals, vol. 10(6), pages 57-68.
    24. Ruijun Bu & Fredj Jawadi & Yuyi Li, 2018. "A Multi-Factor Transformed Diffusion Model with Applications to VIX and VIX Futures," Working Papers 20183, University of Liverpool, Department of Economics.
    25. Bucci, Andrea & Palomba, Giulio & Rossi, Eduardo, 2023. "The role of uncertainty in forecasting volatility comovements across stock markets," Economic Modelling, Elsevier, vol. 125(C).
    26. Baxa, Jaromir & Buliskeria, Nino & Elminejad, Ali & Havranek, Tomas & Havrankova, Zuzana & Kundu, Suranjana, 2023. "A comment on Bauer, Lakdawala, Mueller: Market-Based Monetary Policy Uncertainty (2022)," I4R Discussion Paper Series 77, The Institute for Replication (I4R).
    27. Wang, Qi & Wang, Zerong, 2020. "VIX valuation and its futures pricing through a generalized affine realized volatility model with hidden components and jump," Journal of Banking & Finance, Elsevier, vol. 116(C).
    28. Byomakesh Debata & Jitendra Mahakud, 2018. "Economic policy uncertainty and stock market liquidity," Journal of Financial Economic Policy, Emerald Group Publishing Limited, vol. 10(1), pages 112-135, April.
    29. Bin Wu & Pengzhan Chen & Wuyi Ye, 2021. "Jump activity analysis of the equity index and the corresponding volatility: Evidence from the Chinese market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(7), pages 1055-1073, July.
    30. Ruijun Bu & Rodrigo Hizmeri & Marwan Izzeldin & Anthony Murphy & Mike G. Tsionas, 2021. "The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility," Working Papers 202109, University of Liverpool, Department of Economics.
    31. Aït-Sahalia, Yacine & Matthys, Felix & Osambela, Emilio & Sircar, Ronnie, 2025. "When uncertainty and volatility are disconnected: Implications for asset pricing and portfolio performance," Journal of Econometrics, Elsevier, vol. 248(C).
    32. Danilo Cascaldi-Garcia & Deepa Dhume Datta & Thiago Revil T. Ferreira & Olesya V. Grishchenko & Mohammad R. Jahan-Parvar & Juan M. Londono & Francesca Loria & Sai Ma & Marius del Giudice Rodriguez & J, 2020. "What is Certain about Uncertainty?," International Finance Discussion Papers 1294, Board of Governors of the Federal Reserve System (U.S.).
      • Danilo Cascaldi-Garcia & Cisil Sarisoy & Juan M. Londono & Bo Sun & Deepa D. Datta & Thiago Ferreira & Olesya Grishchenko & Mohammad R. Jahan-Parvar & Francesca Loria & Sai Ma & Marius Rodriguez & Ilk, 2023. "What Is Certain about Uncertainty?," Journal of Economic Literature, American Economic Association, vol. 61(2), pages 624-654, June.
    33. Yu, Miao, 2023. "Forecasting Sector-Level Stock Market Volatility: The Role of World Uncertainty Index," Finance Research Letters, Elsevier, vol. 58(PC).
    34. Wang, Xinya & Lucey, Brian M. & Huang, Shupei, 2025. "Financial uncertainties drive extreme risks in China," International Review of Financial Analysis, Elsevier, vol. 104(PB).
    35. Vilhelmsson, Anders, 2020. "Macro news and long-run volatility expectations," Knut Wicksell Working Paper Series 2020/1, Lund University, Knut Wicksell Centre for Financial Studies.
    36. Marianne Andries & Thomas M. Eisenbach & Martin C. Schmalz, 2014. "Horizon-Dependent Risk Aversion and the Timing and Pricing of Uncertainty," Staff Reports 703, Federal Reserve Bank of New York.
    37. Andrea Bucci & Giulio Palomba & Eduardo Rossi, 2019. "Does macroeconomics help in predicting stock markets volatility comovements? A nonlinear approach," Working Papers 440, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    38. Bruno Feunou & Cédric Okou, 2018. "Risk‐neutral moment‐based estimation of affine option pricing models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 1007-1025, November.
    39. Luu Duc Huynh, Toan, 2020. "The effect of uncertainty on the precious metals market: New insights from Transfer Entropy and Neural Network VAR," Resources Policy, Elsevier, vol. 66(C).
    40. Oh, Dong Hwan & Park, Yang-Ho, 2023. "GARCH option pricing with volatility derivatives," Journal of Banking & Finance, Elsevier, vol. 146(C).
    41. Peter Van Tassel, 2017. "Global Variance Term Premia and Intermediary Risk Appetite," 2017 Meeting Papers 149, Society for Economic Dynamics.
    42. Yacine Aït-Sahalia & Felix Matthys & Emilio Osambela & Ronnie Sircar, 2021. "When Uncertainty and Volatility Are Disconnected: Implications for Asset Pricing and Portfolio Performance," Finance and Economics Discussion Series 2021-063, Board of Governors of the Federal Reserve System (U.S.).
    43. Kundu, Srikanta & Paul, Amartya, 2022. "Effect of economic policy uncertainty on stock market return and volatility under heterogeneous market characteristics," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 597-612.
    44. Zaremba, Adam & Kizys, Renatas & Aharon, David Y., 2021. "Volatility in International Sovereign Bond Markets: The role of government policy responses to the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 43(C).
    45. Claudiu Tiberiu Albulescu & Eugenia Grecu, 2023. "Government Interventions and Sovereign Bond Market Volatility during COVID-19: A Quantile Analysis," Mathematics, MDPI, vol. 11(5), pages 1-14, February.
    46. Park, Yang-Ho, 2020. "Variance disparity and market frictions," Journal of Econometrics, Elsevier, vol. 214(2), pages 326-348.
    47. Ye, Wuyi & Xia, Wenjing & Wu, Bin & Chen, Pengzhan, 2022. "Using implied volatility jumps for realized volatility forecasting: Evidence from the Chinese market," International Review of Financial Analysis, Elsevier, vol. 83(C).
    48. Daniel Perico Ortiz, 2023. "Economic policy statements, social media, and stock market uncertainty: An analysis of Donald Trump’s tweets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(2), pages 333-367, June.
    49. Kurov, Alexander & Wolfe, Marketa Halova & Gilbert, Thomas, 2021. "The disappearing pre-FOMC announcement drift," Finance Research Letters, Elsevier, vol. 40(C).
    50. Christopher Thiem, 2020. "Cross-Category, Trans-Pacific Spillovers of Policy Uncertainty and Financial Market Volatility," Open Economies Review, Springer, vol. 31(2), pages 317-342, April.
    51. Ekow A. Aikins & Alexander Kurov, 2025. "Which Way Does the Wind Blow Between SPX Futures and VIX Futures?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 45(2), pages 79-90, February.
    52. Perico Ortiz, Daniel, 2021. "The high frequency impact of economic policy narratives on stock market uncertainty," FAU Discussion Papers in Economics 02/2021, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    53. Katherine B. Ensor & Yu Han & Barbara Ostdiek & Stuart M. Turnbull, 2020. "Dynamic jump intensities and news arrival in oil futures markets," Journal of Asset Management, Palgrave Macmillan, vol. 21(4), pages 292-325, July.
    54. Isiaka Akande Raifu, 2023. "Examining structural stability and time-varying causality between economic policy uncertainty and Asia-Pacific Islamic stock price," Economics Bulletin, AccessEcon, vol. 43(1), pages 28-37.
    55. Fulop, Andras & Li, Junye, 2019. "Bayesian estimation of dynamic asset pricing models with informative observations," Journal of Econometrics, Elsevier, vol. 209(1), pages 114-138.
    56. Anastasios Megaritis & Alexandros Kontonikas & Nikolaos Vlastakis & Athanasios Triantafyllou, 2025. "The term structure of interest rates as predictor of stock market volatility," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 30(3), pages 3212-3229, July.

  5. Aït-Sahalia, Yacine & Amengual, Dante & Manresa, Elena, 2015. "Market-based estimation of stochastic volatility models," Journal of Econometrics, Elsevier, vol. 187(2), pages 418-435.

    Cited by:

    1. Muneer Shaik & S. Maheswaran, 2019. "Robust Volatility Estimation with and Without the Drift Parameter," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(1), pages 57-91, March.
    2. Mohammed Bouasabah & Oshamah Ibrahim Khalaf, 2023. "A Technical Indicator for a Short-term Trading Decision in the NASDAQ Market," Advances in Decision Sciences, Asia University, Taiwan, vol. 27(3), pages 1-13, September.
    3. Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Working Papers in Economics 14/29, University of Canterbury, Department of Economics and Finance.
    4. Aït-Sahalia, Yacine & Li, Chenxu & Li, Chen Xu, 2021. "Closed-form implied volatility surfaces for stochastic volatility models with jumps," Journal of Econometrics, Elsevier, vol. 222(1), pages 364-392.
    5. Chang, C-L. & McAleer, M.J., 2014. "Econometric Analysis of Financial Derivatives," Econometric Institute Research Papers EI 2015-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Amengual, Dante & Xiu, Dacheng, 2018. "Resolution of policy uncertainty and sudden declines in volatility," Journal of Econometrics, Elsevier, vol. 203(2), pages 297-315.
    7. Yang-Ho Park, 2015. "The Effects of Asymmetric Volatility and Jumps on the Pricing of VIX Derivatives," Finance and Economics Discussion Series 2015-71, Board of Governors of the Federal Reserve System (U.S.).
    8. Oh, Dong Hwan & Park, Yang-Ho, 2023. "GARCH option pricing with volatility derivatives," Journal of Banking & Finance, Elsevier, vol. 146(C).
    9. Park, Yang-Ho, 2020. "Variance disparity and market frictions," Journal of Econometrics, Elsevier, vol. 214(2), pages 326-348.
    10. Agarwal, Vikas & Arisoy, Y. Eser & Naik, Narayan Y., 2017. "Volatility of aggregate volatility and hedge fund returns," Journal of Financial Economics, Elsevier, vol. 125(3), pages 491-510.
    11. Park, Yang-Ho, 2016. "The effects of asymmetric volatility and jumps on the pricing of VIX derivatives," Journal of Econometrics, Elsevier, vol. 192(1), pages 313-328.

  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.
    See citations under working paper version above.
  7. Amengual, Dante & Sentana, Enrique, 2010. "A comparison of mean-variance efficiency tests," Journal of Econometrics, Elsevier, vol. 154(1), pages 16-34, January.
    See citations under working paper version above.
  8. Amengual, Dante & Watson, Mark W., 2007. "Consistent Estimation of the Number of Dynamic Factors in a Large N and T Panel," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 91-96, January.

    Cited by:

    1. Bajraj, Gent & Lorca, Jorge & Wlasiuk, Juan M., 2023. "On foreign drivers of emerging markets fluctuations," Economic Modelling, Elsevier, vol. 129(C).
    2. Alessi, Lucia & Kerssenfischer, Mark, 2016. "The response of asset prices to monetary policy shocks: stronger than thought," Working Paper Series 1967, European Central Bank.
    3. Mario Forni & Luca Sala & Luca Gambetti, 2015. "No News in Business Cycles," Working Papers 535, Barcelona School of Economics.
    4. Gent Bajraj & Jorge Lorca & Juan M. Wlasiuk, 2022. "On Foreign Drivers of EMEs Fluctuations," Working Papers Central Bank of Chile 951, Central Bank of Chile.
    5. Fulvio Pegoraro & Siegel, A. F. & Luca Tiozzo Pezzoli, 2014. "Specification Analysis of International Treasury Yield Curve Factors," Working papers 490, Banque de France.
    6. Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2009. "A Robust Criterion for Determining the Number of Factors in Approximate Factor Models," Working Papers ECARES 2009_023, ULB -- Universite Libre de Bruxelles.
    7. GUO-FITOUSSI, Liang, 2013. "A Comparison of the Finite Sample Properties of Selection Rules of Factor Numbers in Large Datasets," MPRA Paper 50005, University Library of Munich, Germany.
    8. 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.
    9. Eickmeier, Sandra, 2006. "Comovements and heterogeneity in the Comovements and heterogeneity in the dynamic factor model," Discussion Paper Series 1: Economic Studies 2006,31, Deutsche Bundesbank.
    10. António Rua & Carlos Melo Gouveia & Nuno Lourenço, 2020. "Forecasting tourism with targeted predictors in a data-rich environment," Working Papers w202005, Banco de Portugal, Economics and Research Department.
    11. Mr. Maxym Kryshko, 2011. "Data-Rich DSGE and Dynamic Factor Models," IMF Working Papers 2011/216, International Monetary Fund.
    12. Poncela, Pilar & Ruiz Ortega, Esther, 2012. "More is not always better : back to the Kalman filter in dynamic factor models," DES - Working Papers. Statistics and Econometrics. WS ws122317, Universidad Carlos III de Madrid. Departamento de Estadística.
    13. Jorge Lorca, 2021. "Capital Flows and Emerging Markets Fluctuations," Working Papers Central Bank of Chile 898, Central Bank of Chile.
    14. Sarafidis, Vasilis & Wansbeek, Tom, 2010. "Cross-sectional Dependence in Panel Data Analysis," MPRA Paper 20367, University Library of Munich, Germany.
    15. 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.
    16. Alain Kabundi & Francisco Nadal De Simone, 2011. "France in the global economy: a structural approximate dynamic factor model analysis," Empirical Economics, Springer, vol. 41(2), pages 311-342, October.
    17. Brian D. O. Anderson & Manfred Deistler & Marco Lippi, 2022. "Linear System Challenges of Dynamic Factor Models," Econometrics, MDPI, vol. 10(4), pages 1-26, December.
    18. Ando, Tomohiro & Bai, Jushan & Li, Kunpeng, 2022. "Bayesian and maximum likelihood analysis of large-scale panel choice models with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 230(1), pages 20-38.
    19. 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".
    20. Matteo LUCIANI, "undated". "Monetary Policy and the Housing Market: A Structural Factor Analysis," Working Papers wp2010-7, Department of the Treasury, Ministry of the Economy and of Finance.
    21. Shahin Tavakoli & Gilles Nisol & Marc Hallin, 2023. "Factor models for high‐dimensional functional time series II: Estimation and forecasting," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(5-6), pages 601-621, September.
    22. Matteo Luciani & David Veredas, 2012. "A model for vast panels of volatilities," Working Papers 1230, Banco de España.
    23. Barigozzi, Matteo & Conti, Antonio & Luciani, Matteo, 2012. "Do Euro area countries respond asymmetrically to the common monetary policy?," LSE Research Online Documents on Economics 43344, London School of Economics and Political Science, LSE Library.
    24. Olivier Fortin-Gagnon & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2018. "A Large Canadian Database for Macroeconomic Analysis," CIRANO Working Papers 2018s-25, CIRANO.
    25. Ricardo Reis & Mark W. Watson, 2010. "Relative Goods' Prices, Pure Inflation, and the Phillips Correlation," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(3), pages 128-157, July.
    26. Forni, Mario & Gambetti, Luca, 2010. "The dynamic effects of monetary policy: A structural factor model approach," Journal of Monetary Economics, Elsevier, vol. 57(2), pages 203-216, March.
    27. AMMOURI, Bilel & TOUMI, Hassen & Zitouna, Habib, 2015. "Forecasting Inflation in Tunisia Using Dynamic Factors Model," MPRA Paper 65514, University Library of Munich, Germany.
    28. Chou, Ray Yeutien & Yen, Tso-Jung & Yen, Yu-Min, 2020. "Macroeconomic forecasting using approximate factor models with outliers," International Journal of Forecasting, Elsevier, vol. 36(2), pages 267-291.
    29. Yitian Liu & Jiazhu Pan & Qiang Xia, 2025. "Estimation of Constrained Factor Models for High‐Dimensional Time Series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(4), pages 1467-1477, July.
    30. Xiao Huang, 2023. "Composite Quantile Factor Model," Papers 2308.02450, arXiv.org, revised Nov 2024.
    31. Aït-Sahalia, Yacine & Xiu, Dacheng, 2017. "Using principal component analysis to estimate a high dimensional factor model with high-frequency data," Journal of Econometrics, Elsevier, vol. 201(2), pages 384-399.
    32. Bai, Jushan & Ando, Tomohiro, 2013. "Panel data models with grouped factor structure under unknown group membership," MPRA Paper 52782, University Library of Munich, Germany.
    33. In Choi & Dukpa Kim & Yun Jung Kim & Noh-Sun Kwark, 2016. "A Multilevel Factor Model: Identification, Asymptotic Theory and Applications," Working Papers 1609, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    34. Francisco Dias & Cláudia Duarte & António Rua, 2010. "Inflation expectations in the euro area: are consumers rational?," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 146(3), pages 591-607, September.
    35. 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.
    36. Joakim Westerlund & Sagarika Mishra, 2017. "On the determination of the number of factors using information criteria with data-driven penalty," Statistical Papers, Springer, vol. 58(1), pages 161-184, March.
    37. Ali Babikir & Henry Mwambi, 2016. "Evaluating the combined forecasts of the dynamic factor model and the artificial neural network model using linear and nonlinear combining methods," Empirical Economics, Springer, vol. 51(4), pages 1541-1556, December.
    38. Tino Berger & Lorenzo Pozzi, 2016. "Is there really a Global Business Cycle? A Dynamic Factor Model with Stochastic Factor Selection," Tinbergen Institute Discussion Papers 16-088/VI, Tinbergen Institute.
    39. 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.).
    40. Alessi, Lucia & Barigozzi, Matteo & Capasso, Marco, 2008. "A robust criterion for determining the number of static factors in approximate factor models," Working Paper Series 903, European Central Bank.
    41. Lombardi, Marco J. & Maier, Philipp, 2011. "Forecasting economic growth in the euro area during the Great Moderation and the Great Recession," Working Paper Series 1379, European Central Bank.
    42. Helmut Lütkepohl, 2014. "Structural Vector Autoregressive Analysis in a Data Rich Environment: A Survey," Discussion Papers of DIW Berlin 1351, DIW Berlin, German Institute for Economic Research.
    43. Han, Xu, 2015. "Tests for overidentifying restrictions in Factor-Augmented VAR models," Journal of Econometrics, Elsevier, vol. 184(2), pages 394-419.
    44. Guo, Xiao & Chen, Yu & Tang, Cheng Yong, 2023. "Information criteria for latent factor models: A study on factor pervasiveness and adaptivity," Journal of Econometrics, Elsevier, vol. 233(1), pages 237-250.
    45. 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.
    46. Yoshimasa Uematsu & Takashi Yamagata, 2019. "Estimation of Weak Factor Models," ISER Discussion Paper 1053, Institute of Social and Economic Research, The University of Osaka.
    47. 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".
    48. Pellényi, Gábor, 2012. "A monetáris politika hatása a magyar gazdaságra. Elemzés strukturális, dinamikus faktormodellel [The sectoral effects of monetary policy in Hungary: a structural factor]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(3), pages 263-284.
    49. Bai, Jushan & Ando, Tomohiro, 2013. "Multifactor asset pricing with a large number of observable risk factors and unobservable common and group-specific factors," MPRA Paper 52785, University Library of Munich, Germany, revised Dec 2013.
    50. Andreou, Elena & Gagliardini, Patrick & Ghysels, Eric & Rubin, Mirco, 2017. "Is Industrial Production Still the Dominant Factor for the US Economy?," CEPR Discussion Papers 12219, C.E.P.R. Discussion Papers.
    51. Breitung, Jörg & Eickmeier, Sandra, 2009. "Testing for structural breaks in dynamic factor models," Discussion Paper Series 1: Economic Studies 2009,05, Deutsche Bundesbank.
    52. Tsay, Ruey S. & Ando, Tomohiro, 2012. "Bayesian panel data analysis for exploring the impact of subprime financial crisis on the US stock market," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3345-3365.
    53. Patrick Gagliardini & Elisa Ossola & Olivier Scaillet, 2016. "A diagnostic criterion for approximate factor structure," Papers 1612.04990, arXiv.org, revised Aug 2017.
    54. Christian Brownlees & Gu{dh}mundur Stef'an Gu{dh}mundsson & Yaping Wang, 2024. "Performance of Empirical Risk Minimization For Principal Component Regression," Papers 2409.03606, arXiv.org, revised Sep 2024.
    55. Forni, Mario & Gambetti, Luca, 2010. "Fiscal Foresight and the Effects of Goverment Spending," CEPR Discussion Papers 7840, C.E.P.R. Discussion Papers.
    56. Bates, Brandon J. & Plagborg-Møller, Mikkel & Stock, James H. & Watson, Mark W., 2013. "Consistent Factor Estimation in Dynamic Factor Models with Structural Instability," Scholarly Articles 28469786, Harvard University Department of Economics.
    57. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers halshs-02262202, HAL.
    58. António Rua & Francisco Craveiro Dias, 2008. "Determining the number of factors in approximate factor models with global and group-specific factors," Working Papers w200809, Banco de Portugal, Economics and Research Department.
    59. Jean-Stéphane Mésonnier & Dalibor Stevanovic, 2012. "Bank Leverage Shocks and the Macroeconomy: a New Look in a Data-Rich Environment," CIRANO Working Papers 2012s-23, CIRANO.
    60. Dias Francisco & Pinheiro Maximiano & Rua António, 2013. "Determining the number of global and country-specific factors in the euro area," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(5), pages 573-617, December.
    61. Agnieszka Pierzak, 2013. "Forecasting inflation in Poland using dynamic factor model," MF Working Papers 17, Ministry of Finance in Poland.
    62. 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.
    63. 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.
    64. Dalibor Stevanovic, 2015. "Factor augmented autoregressive distributed lag models with macroeconomic applications," CIRANO Working Papers 2015s-33, CIRANO.
    65. In Choi, 2012. "Model Selection for Factor Analysis: Some New Criteria and Performance Comparisons," Working Papers 1209, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    66. 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.
    67. Dong He & Wei Liao, 2011. "Asian Business Cycle Synchronisation," Working Papers 062011, Hong Kong Institute for Monetary Research.
    68. Berger Tino & Hienzsch Sebastian, 2025. "Which Global Cycle? A Stochastic Factor Selection Approach for Global Macro-Financial Cycles," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 29(5), pages 541-559.
    69. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.
    70. Sandra Eickmeier, 2009. "Comovements and heterogeneity in the euro area analyzed in a non-stationary dynamic factor model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(6), pages 933-959.
    71. Marouane Daoui & Bouchra Benyacoub, 2021. "Monetary Policy Shocks and Economic Growth in Morocco: A Factor-Augmented Vector Autoregression (FAVAR) Approach [Chocs de politique monétaire et croissance économique au Maroc : Une approche de ty," Post-Print hal-03277727, HAL.
    72. Vrinda Gupta & Amlendu Dubey, 2024. "US monetary policy, the global financial cycle and cross-country financial cycles," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 48(4), pages 999-1019, December.
    73. António Rua, 2016. "A wavelet-based multivariate multiscale approach for forecasting," Working Papers w201612, Banco de Portugal, Economics and Research Department.
    74. Lourenço, Nuno & Rua, António, 2021. "The Daily Economic Indicator: tracking economic activity daily during the lockdown," Economic Modelling, Elsevier, vol. 100(C).
    75. Pelger, Markus, 2019. "Large-dimensional factor modeling based on high-frequency observations," Journal of Econometrics, Elsevier, vol. 208(1), pages 23-42.
    76. Mehmet Caner & Xu Han, 2014. "Selecting the Correct Number of Factors in Approximate Factor Models: The Large Panel Case With Group Bridge Estimators," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(3), pages 359-374, July.
    77. Proietti, Tommaso, 2008. "Estimation of Common Factors under Cross-Sectional and Temporal Aggregation Constraints: Nowcasting Monthly GDP and its Main Components," MPRA Paper 6860, University Library of Munich, Germany.
    78. Lorenzo Boldrini & Eric Hillebrand, 2015. "Supervision in Factor Models Using a Large Number of Predictors," CREATES Research Papers 2015-38, Department of Economics and Business Economics, Aarhus University.
    79. Francesco Moscone & Elisa Tosetti, 2009. "A Review And Comparison Of Tests Of Cross‐Section Independence In Panels," Journal of Economic Surveys, Wiley Blackwell, vol. 23(3), pages 528-561, July.
    80. Yu, Long & He, Yong & Zhang, Xinsheng, 2019. "Robust factor number specification for large-dimensional elliptical factor model," Journal of Multivariate Analysis, Elsevier, vol. 174(C).
    81. YAMAMOTO, Yohei & 山本, 庸平, 2015. "Asymptotic Inference for Common Factor Models in the Presence of Jumps," Discussion Papers 2015-05, Graduate School of Economics, Hitotsubashi University.
    82. Greenaway-McGrevy, Ryan & Han, Chirok & Sul, Donggyu, 2012. "Estimating the number of common factors in serially dependent approximate factor models," Economics Letters, Elsevier, vol. 116(3), pages 531-534.
    83. Nathan Bedock & Dalibor Stevanović, 2017. "An empirical study of credit shock transmission in a small open economy," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 50(2), pages 541-570, May.
    84. Francisco Dias & Maximiano Pinheiro & António Rua, 2010. "Forecasting using targeted diffusion indexes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(3), pages 341-352.
    85. Jack Fosten, 2016. "Model selection with factors and variables," University of East Anglia School of Economics Working Paper Series 2016-07, School of Economics, University of East Anglia, Norwich, UK..
    86. In Choi & Jorg Breitung, 2011. "Factor models," Working Papers 1121, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy), revised Dec 2011.
    87. Forni, Mario & Cavicchioli, Maddalena & Lippi, Marco & Zaffaroni, Paolo, 2016. "Eigenvalue Ratio Estimators for the Number of Common Factors," CEPR Discussion Papers 11440, C.E.P.R. Discussion Papers.
    88. Bai, Jushan & Wang, Peng, 2012. "Identification and estimation of dynamic factor models," MPRA Paper 38434, University Library of Munich, Germany.
    89. Berger, Tino & Everaert, Gerdie & Pozzi, Lorenzo, 2021. "Testing for international business cycles: A multilevel factor model with stochastic factor selection," Journal of Economic Dynamics and Control, Elsevier, vol. 128(C).
    90. Mario Forni & Luca Gambetti & Antonio Granese & Luca Sala & Stefano Soccorsi, 2025. "An American Macroeconomic Picture: Supply and Demand Shocks in the Frequency Domain," American Economic Journal: Macroeconomics, American Economic Association, vol. 17(3), pages 311-341, July.
    91. Laumer, Sebastian, 2020. "Government spending and heterogeneous consumption dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 114(C).
    92. Stock, James H. & Watson, Mark, 2011. "Dynamic Factor Models," Scholarly Articles 28469541, Harvard University Department of Economics.
    93. 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.
    94. Dalibor Stevanovic & Charles Olivier Mao Takongmo, 2014. "Selection of the number of factors in presence of structural instability: a Monte Carlo study," CIRANO Working Papers 2014s-44, CIRANO.
    95. Mario Forni & Marc Hallin & Marco Lippi & Paolo Zaffaroni, 2011. "One-Sided Representations of Generalized Dynamic Factor Models," Working Papers ECARES ECARES 2011-019, ULB -- Universite Libre de Bruxelles.
    96. Otter, Pieter W. & Jacobs, Jan P.A.M. & Reijer, Ard H.J. de, 2014. "A criterion for the number of factors in a data-rich environment," Research Report 14008-EEF, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    97. Alexander Chudik & M. Hashem Pesaran, 2013. "Large panel data models with cross-sectional dependence: a survey," Globalization Institute Working Papers 153, Federal Reserve Bank of Dallas.
    98. Yamamoto, Yohei & Tanaka, Shinya, 2015. "Testing for factor loading structural change under common breaks," Journal of Econometrics, Elsevier, vol. 189(1), pages 187-206.
    99. Yuefeng Han & Rong Chen & Cun-Hui Zhang, 2020. "Rank Determination in Tensor Factor Model," Papers 2011.07131, arXiv.org, revised May 2022.
    100. Gabriele Fiorentini & Enrique Sentana, 2019. "Dynamic specification tests for dynamic factor models," Econometrics Working Papers Archive 2018_07, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    101. Jean Boivin & Marc P. Giannoni & Dalibor Stevanovic, 2016. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," CIRANO Working Papers 2016s-55, CIRANO.
    102. Forni, Mario & Gambetti, Luca, 2010. "Macroeconomic Shocks and the Business Cycle: Evidence from a Structural Factor Model," CEPR Discussion Papers 7692, C.E.P.R. Discussion Papers.
    103. Mario Forni & Luca Gambetti, 2021. "Policy and Business Cycle Shocks: A Structural Factor Model Representation of the US Economy," JRFM, MDPI, vol. 14(8), pages 1-21, August.
    104. Han, Xu, 2018. "Estimation and inference of dynamic structural factor models with over-identifying restrictions," Journal of Econometrics, Elsevier, vol. 202(2), pages 125-147.
    105. Xia, Qiang & Liang, Rubing & Wu, Jianhong, 2017. "Transformed contribution ratio test for the number of factors in static approximate factor models," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 235-241.
    106. Xu Cheng & Zhipeng Liao & Frank Schorfheide, 2013. "Shrinkage estimation of high-dimensional factor models with structural instabilities," Working Papers 14-4, Federal Reserve Bank of Philadelphia.
    107. Demir, Ishak, 2019. "International Spillovers of U.S. Monetary Policy," LEAF Working Paper Series 19-02, University of Lincoln, Lincoln International Business School, Lincoln Economics and Finance Research Group (LEAF).
    108. Lourenço, Nuno & Gouveia, Carlos Melo & Rua, António, 2021. "Forecasting tourism with targeted predictors in a data-rich environment," Economic Modelling, Elsevier, vol. 96(C), pages 445-454.
    109. Ruiz Ortega, Esther & Poncela, Pilar, 2015. "Small versus big-data factor extraction in Dynamic Factor Models: An empirical assessment," DES - Working Papers. Statistics and Econometrics. WS ws1502, Universidad Carlos III de Madrid. Departamento de Estadística.
    110. Guido Bulligan & Roberto Golinelli & Giuseppe Parigi, 2010. "Forecasting monthly industrial production in real-time: from single equations to factor-based models," Empirical Economics, Springer, vol. 39(2), pages 303-336, October.
    111. Huang, Feiqing & Lu, Kexin & Zheng, Yao & Li, Guodong, 2025. "Supervised factor modeling for high-dimensional linear time series," Journal of Econometrics, Elsevier, vol. 249(PB).
    112. Gent Bajraj & Andrés Fernández & Miguel Fuentes & Benjamín García & Jorge Lorca & Manuel Paillacar & Juan Marcos Wlasiuk, 2022. "Global Drivers and Macroeconomic Volatility in EMEs: a Dynamic Factor, General Equilibrium Perspective," Working Papers Central Bank of Chile 963, Central Bank of Chile.
    113. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2016. "Dynamic Factor Models, Cointegration, and Error Correction Mechanisms," Finance and Economics Discussion Series 2016-018, Board of Governors of the Federal Reserve System (U.S.).
    114. Ruofan Yu & Rong Chen & Han Xiao & Yuefeng Han, 2024. "Dynamic Matrix Factor Models for High Dimensional Time Series," Papers 2407.05624, arXiv.org.
    115. Boysen-Hogrefe, Jens & Pape, Markus, 2011. "More than just one labor market cycle in Germany? : an analysis of regional unemployment data," Zeitschrift für ArbeitsmarktForschung - Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 44(3), pages 279-292.
    116. Pierre Guérin & Danilo Leiva-Leon & Massimiliano Marcellino, 2017. "Markov-Switching Three-Pass Regression Filter," Staff Working Papers 17-13, Bank of Canada.
    117. Luca Gambetti, 2015. "Fiscal Policy, Foresight and the Trade Balance in the U.S," Working Papers 505, Barcelona School of Economics.
    118. 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.
    119. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
    120. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2013. "Dynamic Factor Models: A review of the Literature ," Working papers 430, Banque de France.
    121. Ruey S. Tsay, 2016. "Some Methods for Analyzing Big Dependent Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 673-688, October.
    122. António Rua, 2010. "A Wavelet Approach for Factor-Augmented Forecasting," Working Papers w201007, Banco de Portugal, Economics and Research Department.
    123. Gu, Shihao & Kelly, Bryan & Xiu, Dacheng, 2021. "Autoencoder asset pricing models," Journal of Econometrics, Elsevier, vol. 222(1), pages 429-450.
    124. Zhao Zhao & Guowei Cui & Shaoping Wang, 2017. "A Monte Carlo comparison of estimating the number of dynamic factors," Empirical Economics, Springer, vol. 53(3), pages 1217-1241, November.
    125. Heaton, Chris & Solo, Victor, 2012. "Estimation of high-dimensional linear factor models with grouped variables," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 348-367.
    126. Marc Hallin & Gilles Nisol & Shahin Tavakoli, 2023. "Factor models for high‐dimensional functional time series I: Representation results," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(5-6), pages 578-600, September.
    127. Takumah, Wisdom, 2023. "Fiscal Policy and Asset Prices in a Dynamic Factor Model with Cointegrated Factors," MPRA Paper 117897, University Library of Munich, Germany, revised 10 Jul 2023.
    128. Mouloud El Hafidi & Marouane Daoui, 2019. "Chocs de la politique monétaire et croissance économique au Maroc : une approche en terme de modèles FAVAR," Post-Print hal-03311354, HAL.

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