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Alexei Onatski

Citations

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

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Onatski, A. & Wang, C., 2020. "Spurious Factor Analysis," Cambridge Working Papers in Economics 2003, Faculty of Economics, University of Cambridge.

    Mentioned in:

    1. Spurious Factor Analysis
      by Francis Diebold in No Hesitations on 2020-07-14 17:50:00

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Alexei Onatski & Francisco Ruge‐Murcia, 2013. "Factor Analysis Of A Large Dsge Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(6), pages 903-928, September.

    Mentioned in:

    1. > Econometrics > Time Series Models > Dynamic Factor Models > Structural Factor Models
  2. Onatski, Alexei, 2012. "Asymptotics of the principal components estimator of large factor models with weakly influential factors," Journal of Econometrics, Elsevier, vol. 168(2), pages 244-258.

    Mentioned in:

    1. > Econometrics > Time Series Models > Dynamic Factor Models

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Alexei Onatski & Noah Williams, 2010. "Empirical and policy performance of a forward-looking monetary model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 145-176.

    Mentioned in:

    1. Empirical and policy performance of a forward-looking monetary model (Journal of Applied Econometrics 2010) in ReplicationWiki ()

Working papers

  1. Onatski, A. & Wang, C., 2020. "Spurious Factor Analysis," Cambridge Working Papers in Economics 2003, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Ziwei Mei & Zhentao Shi, 2022. "On LASSO for High Dimensional Predictive Regression," Papers 2212.07052, arXiv.org, revised Jan 2024.
    2. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    3. Pablo Guerrón-Quintana & Alexey Khazanov & Molin Zhong, 2023. "Financial and Macroeconomic Data Through the Lens of a Nonlinear Dynamic Factor Model," Finance and Economics Discussion Series 2023-027, Board of Governors of the Federal Reserve System (U.S.).
    4. Bo Zhang & Jiti Gao & Guangming Pan & Yanrong Yang, 2023. "Eigen-Analysis for High-Dimensional Time Series Clustering," Monash Econometrics and Business Statistics Working Papers 22/23, Monash University, Department of Econometrics and Business Statistics.
    5. Lee, Ji Hyung & Shi, Zhentao & Gao, Zhan, 2022. "On LASSO for predictive regression," Journal of Econometrics, Elsevier, vol. 229(2), pages 322-349.
    6. 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.
    7. 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.

  2. Onatski, A. & Wang, C., 2018. "Extreme canonical correlations and high-dimensional cointegration analysis," Cambridge Working Papers in Economics 1805, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Smeekes, Stephan & Wijler, Etienne, 2021. "An automated approach towards sparse single-equation cointegration modelling," Journal of Econometrics, Elsevier, vol. 221(1), pages 247-276.
    2. Anna Bykhovskaya & Vadim Gorin, 2023. "High-Dimensional Canonical Correlation Analysis," Papers 2306.16393, arXiv.org, revised Aug 2023.
    3. Gonzalo, Jesús & Pitarakis, Jean-Yves, 2021. "Spurious relationships in high-dimensional systems with strong or mild persistence," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1480-1497.
    4. Feng, Zongbao & Chen, Weiya & Liu, Yang & Chen, Hongyu & Skibniewski, Mirosław J., 2023. "Long-term equilibrium relationship analysis and energy-saving measures of metro energy consumption and its influencing factors based on cointegration theory and an ARDL model," Energy, Elsevier, vol. 263(PD).
    5. Anna Bykhovskaya & Vadim Gorin, 2022. "Asymptotics of Cointegration Tests for High-Dimensional VAR($k$)," Papers 2202.07150, arXiv.org, revised Nov 2023.
    6. Anna Bykhovskaya & Vadim Gorin, 2020. "Cointegration in large VARs," Papers 2006.14179, arXiv.org, revised Dec 2021.

  3. Johnstone, I. M & Onatski, A., 2018. "Testing in High-Dimensional Spiked Models," Cambridge Working Papers in Economics 1806, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Hafner, Christian & Linton, Oliver & Tang, Haihan, 2020. "Estimation of a multiplicative correlation structure in the large dimensional case," LIDAM Reprints ISBA 2020028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

  4. Onatski, A., 2018. "Asymptotics of the principal components estimator of large factor models with weak factors and i.i.d. Gaussian noise," Cambridge Working Papers in Economics 1808, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Andreou, Elena & Ghysels, Eric, 2021. "Predicting the VIX and the volatility risk premium: The role of short-run funding spreads Volatility Factors," Journal of Econometrics, Elsevier, vol. 220(2), pages 366-398.
    2. Jungjun Choi & Ming Yuan, 2024. "High Dimensional Factor Analysis with Weak Factors," Papers 2402.05789, arXiv.org.
    3. Onatski, A. & Wang, C., 2020. "Spurious Factor Analysis," Cambridge Working Papers in Economics 2003, Faculty of Economics, University of Cambridge.

  5. Alexei Onatski & Chen Wang, 2016. "Alternative Asymptotics for Cointegration Tests in Large VARs," Cambridge Working Papers in Economics 1637, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Matteo Barigozzi & Lorenzo Trapani, 2018. "Determining the dimension of factor structures in non-stationary large datasets," Papers 1806.03647, arXiv.org.
    2. Chiara Casoli & Riccardo (Jack) Lucchetti, 2022. "Permanent-Transitory decomposition of cointegrated time series via dynamic factor models, with an application to commodity prices [Commodity-price comovement and global economic activity]," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 494-514.
    3. Liang, Chong & Schienle, Melanie, 2019. "Determination of vector error correction models in high dimensions," Working Paper Series in Economics 124, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    4. Ziwei Mei & Zhentao Shi, 2022. "On LASSO for High Dimensional Predictive Regression," Papers 2212.07052, arXiv.org, revised Jan 2024.
    5. Morten Ørregaard Nielsen & Wonk-ki Seo & Dakyung Seong, 2022. "Inference on the dimension of the nonstationary subspace in functional time series," CREATES Research Papers 2022-04, Department of Economics and Business Economics, Aarhus University.
    6. Georg Keilbar & Yanfen Zhang, 2021. "On cointegration and cryptocurrency dynamics," Digital Finance, Springer, vol. 3(1), pages 1-23, March.
    7. Alexander Chudik & M. Hashem Pesaran & Kamiar Mohaddes, 2019. "Identifying global and national output and fiscal policy shocks using a GVAR," CAMA Working Papers 2019-06, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    8. Onatski, A. & Wang, C., 2018. "Extreme canonical correlations and high-dimensional cointegration analysis," Cambridge Working Papers in Economics 1805, Faculty of Economics, University of Cambridge.
    9. Escribano, Alvaro & Peña, Daniel & Ruiz, Esther, 2021. "30 years of cointegration and dynamic factor models forecasting and its future with big data: Editorial," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1333-1337.
    10. Gianluca Cubadda & Marco Mazzali, 2023. "The Vector Error Correction Index Model: Representation, Estimation and Identification," CEIS Research Paper 556, Tor Vergata University, CEIS, revised 04 Apr 2023.
    11. Gonzalo, Jesús & Pitarakis, Jean-Yves, 2021. "Spurious relationships in high-dimensional systems with strong or mild persistence," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1480-1497.
    12. Lee, Ji Hyung & Shi, Zhentao & Gao, Zhan, 2022. "On LASSO for predictive regression," Journal of Econometrics, Elsevier, vol. 229(2), pages 322-349.
    13. Morten {O}rregaard Nielsen & Won-Ki Seo & Dakyung Seong, 2023. "Inference on common trends in functional time series," Papers 2312.00590, arXiv.org, revised Dec 2023.
    14. Anna Bykhovskaya & Vadim Gorin, 2022. "Asymptotics of Cointegration Tests for High-Dimensional VAR($k$)," Papers 2202.07150, arXiv.org, revised Nov 2023.
    15. Anna Bykhovskaya & Vadim Gorin, 2020. "Cointegration in large VARs," Papers 2006.14179, arXiv.org, revised Dec 2021.

  6. Alexei Onatski & Marcelo Moreira J. & Marc Hallin, 2012. "Signal Detection in High Dmension: The Multispiked Case," Working Papers ECARES ECARES 2012-036, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. 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.
    2. Badi H. Baltagi & Chihwa Kao & Fa Wang, 2017. "Asymptotic power of the sphericity test under weak and strong factors in a fixed effects panel data model," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 853-882, October.
    3. Anders Bredahl Kock & David Preinerstorfer, 2017. "Power in High-dimensional testing Problems," Working Papers ECARES ECARES 2017-42, ULB -- Universite Libre de Bruxelles.
    4. Christine Cutting & Davy Paindaveine & Thomas Verdebout, 2015. "Testing Uniformity on High-Dimensional Spheres against Contiguous Rotationally Symmetric Alternatives," Working Papers ECARES ECARES 2015-04, ULB -- Universite Libre de Bruxelles.

  7. Alexei Onatski & Marcelo Moreira J. & Marc Hallin, 2011. "Asymptotic Power of Sphericity Tests for High-Dimensional Data," Working Papers ECARES ECARES 2011-018, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Guo, Wenwen & Cui, Hengjian, 2019. "Projection tests for high-dimensional spiked covariance matrices," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 21-32.
    2. Peng, Bin & Shen, Xinyuan & Ye, Jinqi, 2019. "Testing for sphericity in a fixed effects panel data model with time-varying variances," Economics Letters, Elsevier, vol. 181(C), pages 85-89.
    3. Onatski, Alexei, 2012. "Asymptotics of the principal components estimator of large factor models with weakly influential factors," Journal of Econometrics, Elsevier, vol. 168(2), pages 244-258.
    4. Gobillon, Laurent & Magnac, Thierry, 2013. "Regional Policy Evaluation:Interactive Fixed Effects and Synthetic Controls," TSE Working Papers 13-419, Toulouse School of Economics (TSE).
    5. Jianqing Fan & Ricardo Masini & Marcelo C. Medeiros, 2021. "Bridging factor and sparse models," Papers 2102.11341, arXiv.org, revised Sep 2022.
    6. Laurent Gobillon & François-Charles Wolff, 2017. "The local effects of an innovation: Evidence from the French fish market," Working Papers halshs-01431160, HAL.
    7. Moreira, Humberto & Moreira, Marcelo J., 2019. "Optimal two-sided tests for instrumental variables regression with heteroskedastic and autocorrelated errors," Journal of Econometrics, Elsevier, vol. 213(2), pages 398-433.
    8. Wang, Cheng, 2014. "Asymptotic power of likelihood ratio tests for high dimensional data," Statistics & Probability Letters, Elsevier, vol. 88(C), pages 184-189.
    9. Jamshid Namdari & Debashis Paul & Lili Wang, 2021. "High-Dimensional Linear Models: A Random Matrix Perspective," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(2), pages 645-695, August.
    10. Laurent Gobillon & François-Charles Wolff, 2015. "Évaluer l’effet des politiques publiques locales avec les contrôles synthétiques et les modèles à facteurs : Une application au marché du poisson français," Working Papers halshs-01183455, HAL.
    11. Badi H. Baltagi & Chihwa Kao & Fa Wang, 2017. "Asymptotic power of the sphericity test under weak and strong factors in a fixed effects panel data model," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 853-882, October.
    12. Anders Bredahl Kock & David Preinerstorfer, 2017. "Power in High-dimensional testing Problems," Working Papers ECARES ECARES 2017-42, ULB -- Universite Libre de Bruxelles.
    13. Davy Paindaveine & Thomas Verdebout, 2013. "Universal Asymptotics for High-Dimensional Sign Tests," Working Papers ECARES ECARES 2013-40, ULB -- Universite Libre de Bruxelles.
    14. Wei Lan & Ronghua Luo & Chih-Ling Tsai & Hansheng Wang & Yunhong Yang, 2015. "Testing the Diagonality of a Large Covariance Matrix in a Regression Setting," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 76-86, January.
    15. Li, Weiming & Qin, Yingli, 2014. "Hypothesis testing for high-dimensional covariance matrices," Journal of Multivariate Analysis, Elsevier, vol. 128(C), pages 108-119.
    16. Muni S. Srivastava & Hirokazu Yanagihara & Tatsuya Kubokawa, 2014. "Tests for Covariance Matrices in High Dimension with Less Sample Size," CIRJE F-Series CIRJE-F-933, CIRJE, Faculty of Economics, University of Tokyo.
    17. Marc Hallin & Marcelo Moreira J. & Alexei Onatski, 2013. "Group Invariance, Likelihood Ratio Tests, and the Incidental Parameter Problem in a High-Dimensional Linear Model," Working Papers ECARES ECARES 2013-04, ULB -- Universite Libre de Bruxelles.
    18. Christine Cutting & Davy Paindaveine & Thomas Verdebout, 2015. "Testing Uniformity on High-Dimensional Spheres against Contiguous Rotationally Symmetric Alternatives," Working Papers ECARES ECARES 2015-04, ULB -- Universite Libre de Bruxelles.
    19. Alexei Onatski & Marcelo Moreira J. & Marc Hallin, 2012. "Signal Detection in High Dmension: The Multispiked Case," Working Papers ECARES ECARES 2012-036, ULB -- Universite Libre de Bruxelles.

  8. Marc Henry & Alexei Onatski, 2011. "Set Coverage and Robust Policy," CIRANO Working Papers 2011s-61, CIRANO.

    Cited by:

    1. Lukáš Lafférs, 2019. "Bounding average treatment effects using linear programming," Empirical Economics, Springer, vol. 57(3), pages 727-767, September.
    2. Magnac, Thierry, 2014. "Identification partielle: méthodes et conséquences pour les applications empiriques," TSE Working Papers 14-458, Toulouse School of Economics (TSE).
    3. Galichon, Alfred & Henry, Marc, 2013. "Dilation bootstrap," Journal of Econometrics, Elsevier, vol. 177(1), pages 109-115.
    4. Francesca Molinari, 2020. "Microeconometrics with Partial Identi?cation," CeMMAP working papers CWP15/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Francesca Molinari, 2019. "Econometrics with Partial Identification," CeMMAP working papers CWP25/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Marc Henry & Romuald Méango & Maurice Queyranne, 2012. "Combinatorial Bootstrap Inference IN in Prtially Identified Incomplete Structural Models," CIRJE F-Series CIRJE-F-837, CIRJE, Faculty of Economics, University of Tokyo.

  9. Alexei Onatski & Francisco J. Ruge-Murcia, 2010. "Factor Analysis of a Large DSGE Model," Working Paper series 50_10, Rimini Centre for Economic Analysis.

    Cited by:

    1. Ivashchenko, S., 2020. "Long-term growth sources for sectors of Russian economy," Journal of the New Economic Association, New Economic Association, vol. 48(4), pages 86-112.
    2. Francisco J. Ruge-Murcia & Alexander L. Wolman, 2022. "Relative Price Shocks and Inflation," Working Paper 22-07, Federal Reserve Bank of Richmond.

  10. Onatski, Alexei & Uhlig, Harald, 2009. "Unit Roots in White Noise," MPRA Paper 14057, University Library of Munich, Germany.

    Cited by:

    1. James A. Duffy & Jerome R. Simons, 2020. "Cointegration without Unit Roots," Papers 2002.08092, arXiv.org, revised Apr 2023.
    2. Jurgen A. Doornik & Rocco Mosconi & Paolo Paruolo, 2017. "Formula I(1) and I(2): Race Tracks for Likelihood Maximization Algorithms of I(1) and I(2) Cointegrated VAR Models," Econometrics, MDPI, vol. 5(4), pages 1-30, November.
    3. Stephan B. Bruns & Zsuzsanna Csereklyei & David I. Stern, 2018. "A Multicointegration Model of Global Climate Change," CCEP Working Papers 1801, Centre for Climate & Energy Policy, Crawford School of Public Policy, The Australian National University.

  11. A. Onatski & V. Karguine, 2005. "Curve Forecasting by Functional Autoregression," Computing in Economics and Finance 2005 59, Society for Computational Economics.

    Cited by:

    1. Benatia, David & Carrasco, Marine & Florens, Jean-Pierre, 2017. "Functional linear regression with functional response," Journal of Econometrics, Elsevier, vol. 201(2), pages 269-291.
    2. Sven Otto & Nazarii Salish, 2022. "Approximate Factor Models for Functional Time Series," Papers 2201.02532, arXiv.org, revised Aug 2022.
    3. Blanke, D. & Bosq, D., 2016. "Detecting and estimating intensity of jumps for discretely observed ARMAD(1,1) processes," Journal of Multivariate Analysis, Elsevier, vol. 146(C), pages 119-137.
    4. Atefeh Zamani & Hossein Haghbin & Maryam Hashemi & Rob J. Hyndman, 2022. "Seasonal functional autoregressive models," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(2), pages 197-218, March.
    5. Horváth, Lajos & Husková, Marie & Kokoszka, Piotr, 2010. "Testing the stability of the functional autoregressive process," Journal of Multivariate Analysis, Elsevier, vol. 101(2), pages 352-367, February.
    6. Horváth, Lajos & Liu, Zhenya & Rice, Gregory & Wang, Shixuan, 2020. "A functional time series analysis of forward curves derived from commodity futures," International Journal of Forecasting, Elsevier, vol. 36(2), pages 646-665.
    7. Clive G. Bowsher & Roland Meeks, 2008. "The dynamics of economics functions: modelling and forecasting the yield curve," Working Papers 0804, Federal Reserve Bank of Dallas.
    8. Horváth, Lajos & Hušková, Marie & Rice, Gregory, 2013. "Test of independence for functional data," Journal of Multivariate Analysis, Elsevier, vol. 117(C), pages 100-119.
    9. Ajroldi, Niccolò & Diquigiovanni, Jacopo & Fontana, Matteo & Vantini, Simone, 2023. "Conformal prediction bands for two-dimensional functional time series," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).
    10. Gabrys Robertas & Hörmann Siegfried & Kokoszka Piotr, 2013. "Monitoring the Intraday Volatility Pattern," Journal of Time Series Econometrics, De Gruyter, vol. 5(2), pages 87-116, July.
    11. Haixu Wang & Jiguo Cao, 2023. "Nonlinear prediction of functional time series," Environmetrics, John Wiley & Sons, Ltd., vol. 34(5), August.
    12. Zhang, Xianyang, 2016. "White noise testing and model diagnostic checking for functional time series," Journal of Econometrics, Elsevier, vol. 194(1), pages 76-95.
    13. Devin Didericksen & Piotr Kokoszka & Xi Zhang, 2012. "Empirical properties of forecasts with the functional autoregressive model," Computational Statistics, Springer, vol. 27(2), pages 285-298, June.
    14. Gregory Rice & Han Lin Shang, 2017. "A Plug-in Bandwidth Selection Procedure for Long-Run Covariance Estimation with Stationary Functional Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(4), pages 591-609, July.
    15. Dominique Guegan & Matteo Iacopini, 2018. "Nonparametric forecasting of multivariate probability density functions," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01821815, HAL.
    16. Canale, Antonio & Vantini, Simone, 2016. "Constrained functional time series: Applications to the Italian gas market," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1340-1351.
    17. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    18. Klepsch, J. & Klüppelberg, C., 2017. "An innovations algorithm for the prediction of functional linear processes," Journal of Multivariate Analysis, Elsevier, vol. 155(C), pages 252-271.
    19. Caio Almeida & Romeu Gomes & André Leite & José Vicente, 2007. "Does Curvature Enhance Forecasting?," Working Papers Series 155, Central Bank of Brazil, Research Department.
    20. Mestre, Guillermo & Portela, José & Rice, Gregory & Muñoz San Roque, Antonio & Alonso, Estrella, 2021. "Functional time series model identification and diagnosis by means of auto- and partial autocorrelation analysis," Computational Statistics & Data Analysis, Elsevier, vol. 155(C).
    21. Chen, Yichao & Pun, Chi Seng, 2019. "A bootstrap-based KPSS test for functional time series," Journal of Multivariate Analysis, Elsevier, vol. 174(C).
    22. Alexander Gleim & Nazarii Salish, 2022. "Forecasting Environmental Data: An example to ground-level ozone concentration surfaces," Papers 2202.03332, arXiv.org.
    23. Alexander Aue & Diogo Dubart Norinho & Siegfried Hörmann, 2015. "On the Prediction of Stationary Functional Time Series," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 378-392, March.
    24. Bosq, D., 2014. "Computing the best linear predictor in a Hilbert space. Applications to general ARMAH processes," Journal of Multivariate Analysis, Elsevier, vol. 124(C), pages 436-450.
    25. Rice, Gregory & Wirjanto, Tony & Zhao, Yuqian, 2023. "Exploring volatility of crude oil intraday return curves: A functional GARCH-X model," Journal of Commodity Markets, Elsevier, vol. 32(C).
    26. Dominique Guégan & Matteo Iacopini, 2018. "Nonparameteric forecasting of multivariate probability density functions," Documents de travail du Centre d'Economie de la Sorbonne 18012, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    27. Rice, Gregory & Wirjanto, Tony & Zhao, Yuqian, 2021. "Exploring volatility of crude oil intra-day return curves: a functional GARCH-X Model," MPRA Paper 109231, University Library of Munich, Germany.
    28. Matteo Iacopini & Dominique Guégan, 2018. "Nonparametric Forecasting of Multivariate Probability Density Functions," Working Papers 2018:15, Department of Economics, University of Venice "Ca' Foscari".
    29. Clive Bowsher & Roland Meeks, 2006. "High Dimensional Yield Curves: Models and Forecasting," Economics Series Working Papers 2006-FE-11, University of Oxford, Department of Economics.
    30. Niccol`o Ajroldi & Jacopo Diquigiovanni & Matteo Fontana & Simone Vantini, 2022. "Conformal Prediction Bands for Two-Dimensional Functional Time Series," Papers 2207.13656, arXiv.org, revised Jul 2023.
    31. Goia, Aldo & May, Caterina & Fusai, Gianluca, 2010. "Functional clustering and linear regression for peak load forecasting," International Journal of Forecasting, Elsevier, vol. 26(4), pages 700-711, October.
    32. Rob J. Hyndman & Han Lin Shang, 2008. "Rainbow plots, Bagplots and Boxplots for Functional Data," Monash Econometrics and Business Statistics Working Papers 9/08, Monash University, Department of Econometrics and Business Statistics.
    33. Characiejus, Vaidotas & Rice, Gregory, 2020. "A general white noise test based on kernel lag-window estimates of the spectral density operator," Econometrics and Statistics, Elsevier, vol. 13(C), pages 175-196.
    34. Álvarez-Liébana, J. & Bosq, D. & Ruiz-Medina, M.D., 2017. "Asymptotic properties of a component-wise ARH(1) plug-in predictor," Journal of Multivariate Analysis, Elsevier, vol. 155(C), pages 12-34.
    35. Daniel R. Kowal & David S. Matteson & David Ruppert, 2019. "Functional Autoregression for Sparsely Sampled Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(1), pages 97-109, January.
    36. Battey, Heather & Sancetta, Alessio, 2013. "Conditional estimation for dependent functional data," Journal of Multivariate Analysis, Elsevier, vol. 120(C), pages 1-17.
    37. Almeida, Caio Ibsen Rodrigues de & Vicente, José, 2007. "The role of no-arbitrage on forecasting: lessons from a parametric term structure model," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 657, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    38. Koo, B. & La Vecchia, D. & Linton, O., 2019. "Nonparametric Recovery of the Yield Curve Evolution from Cross-Section and Time Series Information," Cambridge Working Papers in Economics 1916, Faculty of Economics, University of Cambridge.
    39. Brendan K. Beare & Juwon Seo & Won-Ki Seo, 2017. "Cointegrated Linear Processes in Hilbert Space," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(6), pages 1010-1027, November.
    40. Horváth, Lajos & Kokoszka, Piotr & Rice, Gregory, 2014. "Testing stationarity of functional time series," Journal of Econometrics, Elsevier, vol. 179(1), pages 66-82.
    41. Álvarez-Liébana, Javier & Bosq, Denis & Ruiz-Medina, María D., 2016. "Consistency of the plug-in functional predictor of the Ornstein–Uhlenbeck process in Hilbert and Banach spaces," Statistics & Probability Letters, Elsevier, vol. 117(C), pages 12-22.
    42. Massimo Franchi & Paolo Paruolo, 2017. "Cointegration in functional autoregressive processes," Papers 1712.07522, arXiv.org, revised Oct 2018.
    43. Butler, Sunil & Kokoszka, Piotr & Miao, Hong & Shang, Han Lin, 2021. "Neural network prediction of crude oil futures using B-splines," Energy Economics, Elsevier, vol. 94(C).
    44. Klepsch, J. & Klüppelberg, C. & Wei, T., 2017. "Prediction of functional ARMA processes with an application to traffic data," Econometrics and Statistics, Elsevier, vol. 1(C), pages 128-149.
    45. Koo, Bonsoo & La Vecchia, Davide & Linton, Oliver, 2021. "Estimation of a nonparametric model for bond prices from cross-section and time series information," Journal of Econometrics, Elsevier, vol. 220(2), pages 562-588.
    46. Boukhiar, Souad & Mourid, Tahar, 2022. "Resolvent estimators for functional autoregressive processes with random coefficients," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    47. Horváth, Lajos & Reeder, Ron, 2012. "Detecting changes in functional linear models," Journal of Multivariate Analysis, Elsevier, vol. 111(C), pages 310-334.
    48. Cerovecki, Clément & Hörmann, Siegfried, 2017. "On the CLT for discrete Fourier transforms of functional time series," Journal of Multivariate Analysis, Elsevier, vol. 154(C), pages 282-295.
    49. Dominique Guegan & Matteo Iacopini, 2018. "Nonparametric forecasting of multivariate probability density functions," Post-Print halshs-01821815, HAL.
    50. Lajos Horváth & Gregory Rice, 2014. "Extensions of some classical methods in change point analysis," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(2), pages 219-255, June.
    51. Xu, Meng & Li, Jialiang & Chen, Ying, 2017. "Varying coefficient functional autoregressive model with application to the U.S. treasuries," Journal of Multivariate Analysis, Elsevier, vol. 159(C), pages 168-183.
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    6. Rochelle M. Edge & Thomas Laubach & John C. Williams, 2010. "Welfare‐maximizing monetary policy under parameter uncertainty," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 129-143, January.
    7. Huang, Kevin X.D. & Meng, Qinglai & Xue, Jianpo, 2009. "Is forward-looking inflation targeting destabilizing? The role of policy's response to current output under endogenous investment," Journal of Economic Dynamics and Control, Elsevier, vol. 33(2), pages 409-430, February.
    8. Dennis, Richard, 2010. "When is discretion superior to timeless perspective policymaking?," Journal of Monetary Economics, Elsevier, vol. 57(3), pages 266-277, April.
    9. Charlotta Groth & Hashmat Khan, 2010. "Investment Adjustment Costs: An Empirical Assessment," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(8), pages 1469-1494, December.
    10. Matthieu Darracq Paries, 2018. "Financial frictions and monetary policy conduct," Erudite Ph.D Dissertations, Erudite, number ph18-01 edited by Ferhat Mihoubi, December.
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    45. Antonella Trigari, 2006. "The Role of Search Frictions and Bargaining for Inflation Dynamics," Working Papers 304, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    46. Teo, Wing Leong, 2011. "Inventories and optimal monetary policy in a small open economy," Journal of International Money and Finance, Elsevier, vol. 30(8), pages 1719-1748.
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    49. Christoph Gortz & John D Tsoukalas, 2012. "News and Financial Intermediation in Aggregate and Sectoral Fluctuations," Discussion Papers 12-10, Department of Economics, University of Birmingham.
    50. Juan Pablo Medina & Claudio Soto, 2005. "Oil Shocks and Monetary Policy in an Estimated DSGE Model for a Small Open Economy," Working Papers Central Bank of Chile 353, Central Bank of Chile.
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    52. Mayumi Ojima & Junnosuke Shino & Kozo Ueda, 2014. "Buyer-Size Discounts and Inflation Dynamics," Working Papers e071, Tokyo Center for Economic Research.
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    1. B. Li & S. Boubaker & Z. Liu & W. Louhichi & Y. Yao, 2023. "Exploring the Nonlinear Idiosyncratic Volatility Puzzle: Evidence from China," Post-Print hal-04435519, HAL.

  14. Alexei Onatski & Noah Williams, 2003. "Modeling Model Uncertainty," NBER Working Papers 9566, National Bureau of Economic Research, Inc.

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    1. Svensson, Lars E. O. & Williams, Noah, 2005. "Monetary policy with model uncertainty: distribution forecast targeting," Discussion Paper Series 1: Economic Studies 2005,35, Deutsche Bundesbank.
    2. Marc P. Giannoni, 2007. "Robust optimal monetary policy in a forward-looking model with parameter and shock uncertainty," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 179-213.
    3. Walsh, Carl E., 2004. "Implications of a Changing Economic Structure for the Strategy of Monetary Policy," Santa Cruz Department of Economics, Working Paper Series qt84g1q1g6, Department of Economics, UC Santa Cruz.
    4. Levine, Paul & McAdam, Peter & Pearlman, Joseph, 2012. "Probability models and robust policy rules," European Economic Review, Elsevier, vol. 56(2), pages 246-262.
    5. Del Negro, Marco & Schorfheide, Frank, 2005. "Monetary policy analysis with potentially misspecified models," Working Paper Series 475, European Central Bank.
    6. Ramón Adalid & Günter Coenen & Peter McAdam & Stefano Siviero, 2005. "The Performance and Robustness of Interest-Rate Rules in Models of the Euro Area," International Journal of Central Banking, International Journal of Central Banking, vol. 1(1), May.
    7. William A. Brock & Steven N. Durlauf & James M. Nason & Giacomo Rondina, 2007. "Simple versus optimal rules as guides to policy," FRB Atlanta Working Paper 2007-07, Federal Reserve Bank of Atlanta.
    8. William A. Brock & Steven N. Durlauf & Kenneth D. West, 2003. "Policy Evaluation in Uncertain Economic Environments," NBER Working Papers 10025, National Bureau of Economic Research, Inc.
    9. Luo, Yulei & Nie, Jun & Young, Eric, 2014. "Model Uncertainty and Intertemporal Tax Smoothing," MPRA Paper 54268, University Library of Munich, Germany.
    10. Leitemo, Kai & Söderström, Ulf, 2005. "Robust monetary policy in a small open economy," Bank of Finland Research Discussion Papers 20/2005, Bank of Finland.
    11. Fabio Milani, 2004. "Monetary Policy with a Wider Information Set: a Bayesian Model Averaging Approach," Macroeconomics 0401004, University Library of Munich, Germany.
    12. Tetlow, Robert J. & von zur Muehlen, Peter, 2006. "Robustifying learnability," Working Paper Series 593, European Central Bank.
    13. van der Ploeg, Frederick, 2004. "Prudent Monetary Policy: Applications of Cautious LQG Control and Prediction," CEPR Discussion Papers 4222, C.E.P.R. Discussion Papers.
    14. Ormerod, Paul, 2015. "The economics of radical uncertainty," Economics Discussion Papers 2015-40, Kiel Institute for the World Economy (IfW Kiel).
    15. Juha Kilponen, 2004. "A positive theory of monetary policy and robust control," Macroeconomics 0404036, University Library of Munich, Germany.
    16. Michael Paetz, 2007. "Robust Control and Persistence in the New Keynesian Economy," Quantitative Macroeconomics Working Papers 20711, Hamburg University, Department of Economics.
    17. Di Bartolomeo Giovanni & Giuli Francesco, 2009. "Fiscal and monetary interaction under monetary policy uncertainty," wp.comunite 0061, Department of Communication, University of Teramo.
    18. William A. Brock & Steven N. Durlauf, 2004. "Elements of a Theory of Design Limits to Optimal Policy," Manchester School, University of Manchester, vol. 72(s1), pages 1-18, September.
    19. Svetlana Makarova, 2014. "Risk and Uncertainty: Macroeconomic Perspective," UCL SSEES Economics and Business working paper series 129, UCL School of Slavonic and East European Studies (SSEES).
    20. Alexei Onatski & Noah Williams, 2010. "Empirical and policy performance of a forward-looking monetary model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 145-176.
    21. Vardas, Giannis & XEPAPADEAS, Anastasios, 2008. "Model Uncertainty, Ambiguity and the Precautionary Principle: Implications for Biodiversity Management," MPRA Paper 10236, University Library of Munich, Germany.
    22. Richhild Moessner, 2006. "Optimal discretionary policy in rational expectations models with regime switching," Bank of England working papers 299, Bank of England.
    23. Wieland, Volker & Küster, Keith, 2005. "Insurance Policies for Monetary Policy in the Euro Area," CEPR Discussion Papers 4956, C.E.P.R. Discussion Papers.
    24. Ullrich, Antje & Volk, Martin, 2009. "Application of the Soil and Water Assessment Tool (SWAT) to predict the impact of alternative management practices on water quality and quantity," Agricultural Water Management, Elsevier, vol. 96(8), pages 1207-1217, August.
    25. Robert J. Tetlow & Peter Von zur Muehlen, 2002. "Avoiding Nash inflation: Bayesian and robust responses to model uncertainty," Finance and Economics Discussion Series 2002-9, Board of Governors of the Federal Reserve System (U.S.).
    26. Thomas A. Lubik & Christian Matthes & Fabio Verona, 2019. "Assessing U.S. Aggregate Fluctuations Across Time and Frequencies," Working Paper 19-6, Federal Reserve Bank of Richmond.
    27. Kilponen, Juha & Leitemo, Kai, 2006. "Robustness in monetary policymaking: a case for the Friedman rule," Bank of Finland Research Discussion Papers 4/2006, Bank of Finland.
    28. Kohei Hasui, 2021. "How robustness can change the desirability of speed limit policy," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(5), pages 553-570, November.
    29. Sorge, Marco M., 2013. "Robust delegation with uncertain monetary policy preferences," Economic Modelling, Elsevier, vol. 30(C), pages 73-78.
    30. David K. Backus & Bryan R. Routledge & Stanley E. Zin, 2005. "Exotic Preferences for Macroeconomists," NBER Chapters, in: NBER Macroeconomics Annual 2004, Volume 19, pages 319-414, National Bureau of Economic Research, Inc.
    31. William Ascher, 2021. "Coping with intelligence deficits in poverty-alleviation policies in low-income countries," Policy Sciences, Springer;Society of Policy Sciences, vol. 54(2), pages 345-370, June.
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  16. Alexei Onatski, 2000. "Minimax Analysis of Monetary Policy Under Model Uncertainty," Econometric Society World Congress 2000 Contributed Papers 1818, Econometric Society.

    Cited by:

    1. Rudebusch, Glenn D., 2000. "Assessing nominal income rules for monetary policy with model and data uncertainty," Working Paper Series 14, European Central Bank.
    2. Castelnuovo, Efrem & Paolo Surico, 2003. "Why are Federal Funds Rates so Smooth?," Royal Economic Society Annual Conference 2003 39, Royal Economic Society.
    3. Stefano Eusepi, 2004. "Does Central Bank Transparency Matter for Economic Stability," Computing in Economics and Finance 2004 176, Society for Computational Economics.
    4. Adam, Klaus, 2004. "On the relation between robust and Bayesian decision making," Journal of Economic Dynamics and Control, Elsevier, vol. 28(10), pages 2105-2117, September.

  17. Alexei Onatski & James H. Stock, 2000. "Robust Monetary Policy Under Model Uncertainty in a Small Model of the U.S. Economy," NBER Working Papers 7490, National Bureau of Economic Research, Inc.

    Cited by:

    1. Marc P. Giannoni, 2007. "Robust optimal monetary policy in a forward-looking model with parameter and shock uncertainty," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 179-213.
    2. Walsh, Carl E., 2004. "Implications of a Changing Economic Structure for the Strategy of Monetary Policy," Santa Cruz Department of Economics, Working Paper Series qt84g1q1g6, Department of Economics, UC Santa Cruz.
    3. Eilev S. Jansen, 2004. "Modelling inflation in the Euro Area," Working Paper 2004/10, Norges Bank.
    4. Klaus Schmidt-Hebbel & Carl E. Walsh, 2009. "Monetary Policy under Uncertainty and Learning: An Overview," Central Banking, Analysis, and Economic Policies Book Series, in: Klaus Schmidt-Hebbel & Carl E. Walsh & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Series (ed.),Monetary Policy under Uncertainty and Learning, edition 1, volume 13, chapter 1, pages 001-025, Central Bank of Chile.
    5. Lars E.O. Svensson, 2002. "What Is Wrong with Taylor Rules? Using Judgment in Monetary Policy through Targeting Rules," Working Papers 118, Princeton University, Department of Economics, Center for Economic Policy Studies..
    6. Favero, Carlo A. & Milani, Fabio, 2005. "Parameter Instability, Model Uncertainty and the Choice of Monetary Policy," CEPR Discussion Papers 4909, C.E.P.R. Discussion Papers.
    7. Del Negro, Marco & Schorfheide, Frank, 2005. "Monetary policy analysis with potentially misspecified models," Working Paper Series 475, European Central Bank.
    8. Francesca Rondina, 2010. "Policy Evaluation and Uncertainty About the Effects of Oil Prices on Economic Activity," Working Papers 522, Barcelona School of Economics.
    9. Bohdan Kłos, 2003. "Rules of Percentage Rate in Conditions of Uncertainty," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 9.
    10. Ramón Adalid & Günter Coenen & Peter McAdam & Stefano Siviero, 2005. "The Performance and Robustness of Interest-Rate Rules in Models of the Euro Area," International Journal of Central Banking, International Journal of Central Banking, vol. 1(1), May.
    11. William A. Brock & Steven N. Durlauf & James M. Nason & Giacomo Rondina, 2007. "Simple versus optimal rules as guides to policy," FRB Atlanta Working Paper 2007-07, Federal Reserve Bank of Atlanta.
    12. Miguel Casares, 2006. "A close look at model-dependent monetary policy design," Review, Federal Reserve Bank of St. Louis, vol. 88(Sep), pages 451-470.
    13. Marine Charlotte André & Meixing Dai, 2016. "Learning, robust monetray policy and the merit of precaution," Working Papers of BETA 2016-54, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    14. William A. Brock & Steven N. Durlauf & Kenneth D. West, 2003. "Policy Evaluation in Uncertain Economic Environments," NBER Working Papers 10025, National Bureau of Economic Research, Inc.
    15. Glenn D. Rudebusch, 1999. "Is the Fed too timid? Monetary policy in an uncertain world," Working Papers in Applied Economic Theory 99-05, Federal Reserve Bank of San Francisco.
    16. Leitemo, Kai & Söderström, Ulf, 2005. "Robust monetary policy in a small open economy," Bank of Finland Research Discussion Papers 20/2005, Bank of Finland.
    17. Fabio Milani, 2004. "Monetary Policy with a Wider Information Set: a Bayesian Model Averaging Approach," Macroeconomics 0401004, University Library of Munich, Germany.
    18. Tetlow, Robert J. & von zur Muehlen, Peter, 2006. "Robustifying learnability," Working Paper Series 593, European Central Bank.
    19. Shin-ichi Fukuda, 2012. "Infrequent Changes of the Policy Target: Robust Optimal Monetary Policy under Ambiguity," CIRJE F-Series CIRJE-F-863, CIRJE, Faculty of Economics, University of Tokyo.
    20. Alexei Onatski & Noah Williams, 2003. "Modeling Model Uncertainty," Journal of the European Economic Association, MIT Press, vol. 1(5), pages 1087-1122, September.
    21. Lars E.O. Svensson, 1999. "Price Stability as a Target for Monetary Policy: Defining and Maintaining Price Stability," NBER Working Papers 7276, National Bureau of Economic Research, Inc.
    22. Ekaterina Pirozhkova, 2017. "Financial frictions and robust monetary policy in the models of New Keynesian framework," BCAM Working Papers 1701, Birkbeck Centre for Applied Macroeconomics.
    23. Mésonnier, J-S. & Renne, J-P., 2004. "A Time-Varying Natural Rate for the Euro Area," Working papers 115, Banque de France.
    24. van der Ploeg, Frederick, 2004. "Prudent Monetary Policy: Applications of Cautious LQG Control and Prediction," CEPR Discussion Papers 4222, C.E.P.R. Discussion Papers.
    25. Söderström, Ulf, 1999. "Monetary policy with uncertain parameters," Working Paper Series 83, Sveriges Riksbank (Central Bank of Sweden).
    26. Li Qin & Moïse SIDIROPOULOS & Eleftherios Spyromitros, 2009. "Robust Monetary Policy under Model Uncertainty and Inflation Persistence," Working Papers of BETA 2009-09, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    27. Gadi Barlevy, 2011. "Robustness and Macroeconomic Policy," Annual Review of Economics, Annual Reviews, vol. 3(1), pages 1-24, September.
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    35. William A. Brock & Steven N. Durlauf, 2004. "Elements of a Theory of Design Limits to Optimal Policy," Manchester School, University of Manchester, vol. 72(s1), pages 1-18, September.
    36. Coenen, Günter, 2003. "Inflation persistence and robust monetary policy design," Working Paper Series 290, European Central Bank.
    37. Alexander Kriwoluzky & Christian Stoltenberg, 2007. "Optimal Policy Under Model Uncertainty: A Structural-Bayesian Estimation Approach," SFB 649 Discussion Papers SFB649DP2007-040, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    38. Guy Debelle & Adam Cagliarini, 2000. "The Effect of Uncertainty on Monetary Policy: How Good are the Brakes?," RBA Research Discussion Papers rdp2000-07, Reserve Bank of Australia.
    39. Kunting Chen & Changbiao Zhong, 2011. "The effect mechanism of credit constraint on cycle's formation," China Finance Review International, Emerald Group Publishing Limited, vol. 1(4), pages 408-424, September.
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    41. Orphanides, Athanasios & Wieland, Volker, 2000. "Inflation zone targeting," European Economic Review, Elsevier, vol. 44(7), pages 1351-1387, June.
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    44. Efrem CASTELNUOVO, 2010. "Regime Shifts and the Stability of Backward Looking Phillips Curves in Open Economies," EcoMod2004 330600035, EcoMod.
    45. Felipe Morandé & Mauricio Tejada, 2009. "Sources of Uncertainty in Conducting Monetary Policy in Chile," Central Banking, Analysis, and Economic Policies Book Series, in: Klaus Schmidt-Hebbel & Carl E. Walsh & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Series (ed.),Monetary Policy under Uncertainty and Learning, edition 1, volume 13, chapter 12, pages 451-509, Central Bank of Chile.
    46. Hans M. Amman & David A. Kendrick, 2003. "A Classification System for Economic Stochastic Control Models," Computing in Economics and Finance 2003 114, Society for Computational Economics.
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    48. Roberto M. Billi, 2005. "The Optimal Inflation Buffer with a Zero Bound on Nominal Interest Rates," Computing in Economics and Finance 2005 25, Society for Computational Economics.
    49. Swanson, Eric T., 2004. "Signal Extraction And Non-Certainty-Equivalence In Optimal Monetary Policy Rules," Macroeconomic Dynamics, Cambridge University Press, vol. 8(1), pages 27-50, February.
    50. Anton Muscatelli & Carmine Trecroci, 2000. "Monetary Policy Rules, Policy Preferences, and Uncertainty: Recent Empirical Evidence," Journal of Economic Surveys, Wiley Blackwell, vol. 14(5), pages 597-627, December.
    51. Robert J. Tetlow & Peter Von zur Muehlen, 2002. "Avoiding Nash inflation: Bayesian and robust responses to model uncertainty," Finance and Economics Discussion Series 2002-9, Board of Governors of the Federal Reserve System (U.S.).
    52. Seonghoon Cho & Koen Inghelbrecht & Geert Bekaert & Antonio Moreno & Lieven Baele, 2011. "Macroeconomic Regimes," 2011 Meeting Papers 817, Society for Economic Dynamics.
    53. Dai, Meixing & Spyromitros, Eleftherios, 2012. "A Note On Monetary Policy, Asset Prices, And Model Uncertainty," Macroeconomic Dynamics, Cambridge University Press, vol. 16(5), pages 777-790, November.
    54. Humala, Alberto & Rodríguez, Gabriel, 2009. "Estimation of a Time Varying Natural Interest Rate for Peru," Working Papers 2009-009, Banco Central de Reserva del Perú.
    55. Ippei Fujiwara & Naoko Hara & Naohisa Hirakata & Takeshi Kimura & Shinichiro Watanabe, 2007. "Japanese Monetary Policy during the Collapse of the Bubble Economy: A View of Policymaking under Uncertainty," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 25(2), pages 89-128, November.
    56. Carlo Altavilla & Matteo Ciccarelli, 2009. "The Effects of Monetary Policy on Unemployment Dynamics under Model Uncertainty: Evidence from the United States and the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(7), pages 1265-1300, October.
    57. A. Hakan Kara, 2003. "Optimal Monetary Policy, Commitment, and Imperfect Credibility," Working Papers 0301, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    58. Arnulfo Rodriguez & Pedro N. Rodriguez, 2006. "Recursive Thick Modeling and the Choice of Monetary Policy in Mexico," Computing in Economics and Finance 2006 30, Society for Computational Economics.
    59. David Hudgins & Patrick M. Crowley, 2023. "Resilient Control for Macroeconomic Models," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1403-1431, April.
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    61. Kirdan Lees, 2004. "Uncertainty and the open economy: a view through two different lenses," Econometric Society 2004 Australasian Meetings 235, Econometric Society.
    62. Michael Funke & Michael Paetz, 2007. "Environmental Policy Under Model Uncertainty: A Robust Optimal Control Approach," Quantitative Macroeconomics Working Papers 20703, Hamburg University, Department of Economics.
    63. John C. Williams & Andrew T. Levin, 2003. "Robust Monetary Policy with Competing Reference Models," Computing in Economics and Finance 2003 291, Society for Computational Economics.
    64. Stephen G. Cecchetti & Stefan Krause, 2006. "Inflation Targeting versus Price-Path Targeting: Looking For Improvements," Working Papers Central Bank of Chile 399, Central Bank of Chile.
    65. Walsh, Carl E., 2005. "Parameter misspecification and robust monetary policy rules," Working Paper Series 477, European Central Bank.
    66. Orphanides, Athanasios, 2003. "The quest for prosperity without inflation," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 633-663, April.
    67. João Henrique Gonçalves Mazzeu & Esther Ruiz & Helena Veiga, 2018. "Uncertainty And Density Forecasts Of Arma Models: Comparison Of Asymptotic, Bayesian, And Bootstrap Procedures," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 388-419, April.
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    69. Levin, Andrew T. & Wieland, Volker & Williams, John C., 2001. "The performance of forecast-based monetary policy rules under model uncertainty," Working Paper Series 68, European Central Bank.
    70. Efrem Castelnuovo, 2003. "Taylor Rules and Interest Rate Smoothing in the US and EMU," Macroeconomics 0303002, University Library of Munich, Germany.
    71. Meixing Dai, 2020. "La réponse de la BCE face à la pandémie de Covid-19," Post-Print hal-04080460, HAL.
    72. Carlo Altavilla & Matteo Ciccarelli, 2009. "The Effects of Monetary Policy on Unemployment Dynamics Under Model Uncertainty. Evidence from the US and the Euro Area," CSEF Working Papers 231, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    73. Daniel Kienzler & Kai D. Schmid, 2014. "Hysteresis in Potential Output and Monetary Policy," Scottish Journal of Political Economy, Scottish Economic Society, vol. 61(4), pages 371-396, September.
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    84. Traficante, Guido, 2013. "Monetary policy, parameter uncertainty and welfare," Journal of Macroeconomics, Elsevier, vol. 35(C), pages 73-80.
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    87. Cornel OROS & Blandine ZIMMER, 2019. "Myopic governments and conservative central banks: are they compatible?," Working Papers of LaRGE Research Center 2019-06, Laboratoire de Recherche en Gestion et Economie (LaRGE), Université de Strasbourg.
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    89. Efrem Castelnuovo, 2003. "Squeezing the Interest Rate Smoothing Weight with a Hybrid Expectations Model," Working Papers 2003.6, Fondazione Eni Enrico Mattei.
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    93. Giannis Vardas & Anastasios Xepapadeas, 2004. "Uncertainty Aversion, Robust Control and Asset Holdings," Working Papers 0402, University of Crete, Department of Economics.
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    107. Cohen-Cole, Ethan B. & Durlauf, Steven N. & Rondina, Giacomo, 2012. "Nonlinearities in growth: From evidence to policy," Journal of Macroeconomics, Elsevier, vol. 34(1), pages 42-58.
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    143. Gonzalez F. & Rodriguez A. & Gonzalez-Garcia J.R., 2005. "Uncertainty about the Persistence of Periods with Large Price Shocks and the Optimal Reaction of the Monetary Authority," Computing in Economics and Finance 2005 402, Society for Computational Economics.
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    146. William A. Brock & Steven N. Durlauf & Giacomo Rondina, 2008. "Design Limits and Dynamic Policy Analysis," NBER Working Papers 14357, National Bureau of Economic Research, Inc.
    147. Aaron Tornell, 2000. "Robust-H-infinity Forecasting and Asset Pricing Anomalies," NBER Working Papers 7753, National Bureau of Economic Research, Inc.
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    151. Han, Junhee & Lee, Keun, 2022. "Heterogeneous technology and specialization for economic growth beyond the middle-income stage," Economic Modelling, Elsevier, vol. 112(C).
    152. Joe Haslag & R.W. Hafer & Garett Jones, 2003. "The Effect of Monetary Policy on Economic Output," Working Papers 0311, Department of Economics, University of Missouri.
    153. A. Hakan Kara, 2002. "Robust Targeting Rules for Monetary Policy," Discussion Papers 0208, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    154. Marc Giannoni, 2006. "Robust Optimal Policy in a Forward-Looking Model with Parameter and Shock Uncertainty," NBER Working Papers 11942, National Bureau of Economic Research, Inc.
    155. Mr. Robert Tchaidze & Ms. Alina Carare, 2005. "The Use and Abuse of Taylor Rules: How Precisely Can We Estimate Them?," IMF Working Papers 2005/148, International Monetary Fund.
    156. Benjamin Hunt & Peter Isard, 2003. "Some implications for monetary policy of uncertain exchange rate pass‐through," Scottish Journal of Political Economy, Scottish Economic Society, vol. 50(5), pages 567-584, November.
    157. Gonçalves Mazzeu, Joao Henrique & Ruiz Ortega, Esther & Veiga, Helena, 2015. "Model uncertainty and the forecast accuracy of ARMA models: A survey," DES - Working Papers. Statistics and Econometrics. WS ws1508, Universidad Carlos III de Madrid. Departamento de Estadística.
    158. Mariusz Górajski & Zbigniew Kuchta, 2022. "Which hallmarks of optimal monetary policy rules matter in Poland? A stochastic dominance approach," Bank i Kredyt, Narodowy Bank Polski, vol. 53(2), pages 149-182.
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Articles

  1. Alexei Onatski & Chen Wang, 2021. "Spurious Factor Analysis," Econometrica, Econometric Society, vol. 89(2), pages 591-614, March.
    See citations under working paper version above.
  2. Onatski, Alexei & Wang, Chen, 2019. "Extreme canonical correlations and high-dimensional cointegration analysis," Journal of Econometrics, Elsevier, vol. 212(1), pages 307-322.
    See citations under working paper version above.
  3. Alexei Onatski & Chen Wang, 2018. "Alternative Asymptotics for Cointegration Tests in Large VARs," Econometrica, Econometric Society, vol. 86(4), pages 1465-1478, July.
    See citations under working paper version above.
  4. Onatski, Alexei, 2015. "Asymptotic analysis of the squared estimation error in misspecified factor models," Journal of Econometrics, Elsevier, vol. 186(2), pages 388-406.

    Cited by:

    1. 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.
    2. Alain-Philippe Fortin & Patrick Gagliardini & Olivier Scaillet, 2022. "Eigenvalue tests for the number of latent factors in short panels," Papers 2210.16042, arXiv.org.
    3. Jie Wei & Yonghui Zhang, 2023. "Does Principal Component Analysis Preserve the Sparsity in Sparse Weak Factor Models?," Papers 2305.05934, arXiv.org.
    4. 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.
    5. 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.
    6. Marine Carrasco & Barbara Rossi, 2016. "In-Sample Inference and Forecasting in Misspecified Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 313-338, July.
    7. Gregory Connor & Robert A. Korajczyk, 2019. "Semi-strong factors in asset returns," Economics Department Working Paper Series n294-19.pdf, Department of Economics, National University of Ireland - Maynooth.
    8. Patrick Gagliardini & Elisa Ossola & Olivier Scaillet, 2016. "A diagnostic criterion for approximate factor structure," Papers 1612.04990, arXiv.org, revised Aug 2017.
    9. Barigozzi, Matteo & Cho, Haeran & Fryzlewicz, Piotr, 2018. "Simultaneous multiple change-point and factor analysis for high-dimensional time series," LSE Research Online Documents on Economics 88110, London School of Economics and Political Science, LSE Library.
    10. Andrés Sagner, 2020. "Measuring Systemic Risk: A Quantile Factor Analysis," Working Papers Central Bank of Chile 874, Central Bank of Chile.
    11. Allen, David, 2022. "Asset Pricing Tests, Endogeneity issues and Fama-French factors," MPRA Paper 113610, University Library of Munich, Germany.
    12. Sampi Bravo,James Robert Ezequiel & Jooste,Charl, 2020. "Nowcasting Economic Activity in Times of COVID-19 : An Approximation from the Google Community Mobility Report," Policy Research Working Paper Series 9247, The World Bank.
    13. Simon Freyaldenhoven, 2021. "Factor Models with Local Factors—Determining the Number of Relevant Factors," Working Papers 21-15, Federal Reserve Bank of Philadelphia.
    14. Onatski, A. & Wang, C., 2020. "Spurious Factor Analysis," Cambridge Working Papers in Economics 2003, Faculty of Economics, University of Cambridge.
    15. Norman R. Swanson, 2016. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 348-353, July.
    16. James Sampi, 2016. "High Dimensional Factor Models: An Empirical Bayes Approach," Working Papers 75, Peruvian Economic Association.
    17. Marco Avarucci & Paolo Zaffaroni, 2019. "Robust Nearly-Efficient Estimation of Large Panels with Factor Structures," Papers 1902.11181, arXiv.org.
    18. 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.

  5. Alexei Onatski & Francisco Ruge‐Murcia, 2013. "Factor Analysis Of A Large Dsge Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(6), pages 903-928, September.
    See citations under working paper version above.
  6. Henry, Marc & Onatski, Alexei, 2012. "Set coverage and robust policy," Economics Letters, Elsevier, vol. 115(2), pages 256-257.
    See citations under working paper version above.
  7. Onatski, Alexei & Uhlig, Harald, 2012. "Unit Roots In White Noise," Econometric Theory, Cambridge University Press, vol. 28(3), pages 485-508, June.
    See citations under working paper version above.
  8. Onatski, Alexei, 2012. "Asymptotics of the principal components estimator of large factor models with weakly influential factors," Journal of Econometrics, Elsevier, vol. 168(2), pages 244-258.

    Cited by:

    1. Matteo Barigozzi & Lorenzo Trapani, 2018. "Determining the dimension of factor structures in non-stationary large datasets," Papers 1806.03647, arXiv.org.
    2. 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.
    3. Jushan Bai & Serena Ng, 2021. "Approximate Factor Models with Weaker Loadings," Papers 2109.03773, arXiv.org, revised Mar 2023.
    4. Natalia Bailey & George Kapetanios & M. Hashem Pesaran, 2021. "Measurement of factor strength: Theory and practice," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 587-613, August.
    5. Matteo Barigozzi & Christian Brownlees, 2013. "Nets: Network Estimation for Time Series," Working Papers 723, Barcelona School of Economics.
    6. Gobillon, Laurent & Magnac, Thierry, 2013. "Regional Policy Evaluation:Interactive Fixed Effects and Synthetic Controls," TSE Working Papers 13-419, Toulouse School of Economics (TSE).
    7. Hyungsik Roger Roger Moon & Martin Weidner, 2014. "Linear regression for panel with unknown number of factors as interactive fixed effects," CeMMAP working papers 35/14, Institute for Fiscal Studies.
    8. Anatolyev, Stanislav & Mikusheva, Anna, 2021. "Limit Theorems For Factor Models," Econometric Theory, Cambridge University Press, vol. 37(5), pages 1034-1074, October.
    9. Horváth, Lajos & Trapani, Lorenzo, 2016. "Statistical inference in a random coefficient panel model," Journal of Econometrics, Elsevier, vol. 193(1), pages 54-75.
    10. Alain-Philippe Fortin & Patrick Gagliardini & Olivier Scaillet, 2022. "Eigenvalue tests for the number of latent factors in short panels," Papers 2210.16042, arXiv.org.
    11. Lettau, Martin & Pelger, Markus, 2018. "Factors that Fit the Time Series and Cross-Section of Stock Returns," CEPR Discussion Papers 13049, C.E.P.R. Discussion Papers.
    12. Stefano Giglio & Dacheng Xiu, 2017. "Inference on Risk Premia in the Presence of Omitted Factors," NBER Working Papers 23527, National Bureau of Economic Research, Inc.
    13. Jie Wei & Yonghui Zhang, 2023. "Does Principal Component Analysis Preserve the Sparsity in Sparse Weak Factor Models?," Papers 2305.05934, arXiv.org.
    14. Nathan Bedock & Dalibor Stevanovic, 2012. "An Empirical Study of Credit Shock Transmission in a Small Open Economy," CIRANO Working Papers 2012s-16, CIRANO.
    15. Poncela, Pilar & Ruiz, Esther, 2020. "A comment on the dynamic factor model with dynamic factors," Economics Discussion Papers 2020-7, Kiel Institute for the World Economy (IfW Kiel).
    16. Stanislav Anatolyev & Anna Mikusheva, 2018. "Factor models with many assets: strong factors, weak factors, and the two-pass procedure," Papers 1807.04094, arXiv.org, revised Apr 2019.
    17. Hugo Freeman & Martin Weidner, 2021. "Linear Panel Regressions with Two-Way Unobserved Heterogeneity," Papers 2109.11911, arXiv.org, revised Aug 2022.
    18. Jin, Sainan & Miao, Ke & Su, Liangjun, 2021. "On factor models with random missing: EM estimation, inference, and cross validation," Journal of Econometrics, Elsevier, vol. 222(1), pages 745-777.
    19. Andrii Babii & Eric Ghysels & Junsu Pan, 2022. "Tensor Principal Component Analysis," Papers 2212.12981, arXiv.org, revised Aug 2023.
    20. 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.
    21. Marko Mlikota, 2022. "Cross-Sectional Dynamics Under Network Structure: Theory and Macroeconomic Applications," Papers 2211.13610, arXiv.org, revised Dec 2023.
    22. Jushan Bai & Serena Ng, 2020. "Simpler Proofs for Approximate Factor Models of Large Dimensions," Papers 2008.00254, arXiv.org.
    23. Patrick Gagliardini & Elisa Ossola & Olivier Scaillet, 2016. "A diagnostic criterion for approximate factor structure," Papers 1612.04990, arXiv.org, revised Aug 2017.
    24. Simon Freyaldenhoven, 2017. "A Generalized Factor Model with Local Factors," 2017 Papers pfr361, Job Market Papers.
    25. 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.
    26. Hyungsik Roger Moon & Martin Weidner, 2013. "Linear regression for panel with unknown number of factors as interactive fixed effects," CeMMAP working papers CWP49/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    27. Philipp Gersing & Christoph Rust & Manfred Deistler, 2023. "Weak Factors are Everywhere," Papers 2307.10067, arXiv.org, revised Jan 2024.
    28. Jushan Bai, 2023. "Efficiency of QMLE for dynamic panel data models with interactive effects," Papers 2312.07881, arXiv.org.
    29. Doemeland,Doerte & Estevão,Marcello & Jooste,Charl & Sampi Bravo,James Robert Ezequiel & Tsiropoulos,Vasileios, 2022. "Debt Vulnerability Analysis : A Multi-Angle Approach," Policy Research Working Paper Series 9929, The World Bank.
    30. Jianqing Fan & Yuan Liao & Han Liu, 2016. "An overview of the estimation of large covariance and precision matrices," Econometrics Journal, Royal Economic Society, vol. 19(1), pages 1-32, February.
    31. Horváth, Lajos & Rice, Gregory, 2019. "Asymptotics for empirical eigenvalue processes in high-dimensional linear factor models," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 138-165.
    32. Fan, Jianqing & Wang, Weichen & Zhong, Yiqiao, 2019. "Robust covariance estimation for approximate factor models," Journal of Econometrics, Elsevier, vol. 208(1), pages 5-22.
    33. Hsiao, Cheng, 2018. "Panel models with interactive effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 645-673.
    34. Jungjun Choi & Ming Yuan, 2024. "High Dimensional Factor Analysis with Weak Factors," Papers 2402.05789, arXiv.org.
    35. Smith, Simon C. & Timmermann, Allan & Zhu, Yinchu, 2019. "Variable selection in panel models with breaks," Journal of Econometrics, Elsevier, vol. 212(1), pages 323-344.
    36. 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).
    37. 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.
    38. Lingwei Kong, 2023. "Weak (Proxy) Factors Robust Hansen-Jagannathan Distance For Linear Asset Pricing Models," Papers 2307.14499, arXiv.org.
    39. Silvia Gonçalves & Benoit Perron, 2012. "Bootstrapping factor-augmented regression models," CIRANO Working Papers 2012s-12, CIRANO.
    40. Robert Adamek & Stephan Smeekes & Ines Wilms, 2020. "Lasso Inference for High-Dimensional Time Series," Papers 2007.10952, arXiv.org, revised Sep 2022.
    41. Corona, Francisco & Orraca, Pedro, 2016. "Remittances in Mexico and their unobserved components," DES - Working Papers. Statistics and Econometrics. WS 22674, Universidad Carlos III de Madrid. Departamento de Estadística.
    42. Sampi Bravo,James Robert Ezequiel & Jooste,Charl, 2020. "Nowcasting Economic Activity in Times of COVID-19 : An Approximation from the Google Community Mobility Report," Policy Research Working Paper Series 9247, The World Bank.
    43. Kelly, Bryan & Pruitt, Seth, 2015. "The three-pass regression filter: A new approach to forecasting using many predictors," Journal of Econometrics, Elsevier, vol. 186(2), pages 294-316.
    44. 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.
    45. Corona, Francisco & Poncela, Pilar & Ruiz Ortega, Esther, 2017. "Estimating non-stationary common factors : Implications for risk sharing," DES - Working Papers. Statistics and Econometrics. WS 24585, Universidad Carlos III de Madrid. Departamento de Estadística.
    46. Simon Freyaldenhoven, 2021. "Factor Models with Local Factors—Determining the Number of Relevant Factors," Working Papers 21-15, Federal Reserve Bank of Philadelphia.
    47. Badi H. Baltagi & Chihwa Kao & Fa Wang, 2017. "Asymptotic power of the sphericity test under weak and strong factors in a fixed effects panel data model," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 853-882, October.
    48. Hou, Lei & Li, Kunpeng & Li, Qi & Ouyang, Min, 2021. "Revisiting the location of FDI in China: A panel data approach with heterogeneous shocks," Journal of Econometrics, Elsevier, vol. 221(2), pages 483-509.
    49. Frank Kleibergen & Zhaoguo Zhan, 2014. "Unexplained factors and their effects on second pass R-squared’s," UvA-Econometrics Working Papers 14-05, Universiteit van Amsterdam, Dept. of Econometrics.
    50. Luciani, Matteo, 2014. "Forecasting with approximate dynamic factor models: The role of non-pervasive shocks," International Journal of Forecasting, Elsevier, vol. 30(1), pages 20-29.
    51. Xu Cheng & Bruce E. Hansen, 2012. "Forecasting with Factor-Augmented Regression: A Frequentist Model Averaging Approach," PIER Working Paper Archive 12-046, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    52. Maurizio Daniele & Julie Schnaitmann, 2019. "A Regularized Factor-augmented Vector Autoregressive Model," Papers 1912.06049, arXiv.org.
    53. Kapetanios, G. & Pesaran, M.H. & Reese, S., 2021. "Detection of units with pervasive effects in large panel data models," Journal of Econometrics, Elsevier, vol. 221(2), pages 510-541.
    54. Li, Kunpeng & Cui, Guowei & Lu, Lina, 2020. "Efficient estimation of heterogeneous coefficients in panel data models with common shocks," Journal of Econometrics, Elsevier, vol. 216(2), pages 327-353.
    55. Xun Lu & Su Liangjun, 2015. "Shrinkage Estimation of Dynamic Panel Data Models with Interactive Fixed Effects," Working Papers 02-2015, Singapore Management University, School of Economics.
    56. Ma, Shujie & Su, Liangjun, 2018. "Estimation of large dimensional factor models with an unknown number of breaks," Journal of Econometrics, Elsevier, vol. 207(1), pages 1-29.
    57. Onatski, Alexei, 2015. "Asymptotic analysis of the squared estimation error in misspecified factor models," Journal of Econometrics, Elsevier, vol. 186(2), pages 388-406.
    58. Jonas Krampe & Luca Margaritella, 2021. "Factor Models with Sparse VAR Idiosyncratic Components," Papers 2112.07149, arXiv.org, revised May 2022.
    59. Christian Brownlees & Gu{dh}mundur Stef'an Gu{dh}mundsson, 2021. "Performance of Empirical Risk Minimization for Linear Regression with Dependent Data," Papers 2104.12127, arXiv.org, revised May 2023.
    60. Anna Bykhovskaya & Vadim Gorin, 2023. "High-Dimensional Canonical Correlation Analysis," Papers 2306.16393, arXiv.org, revised Aug 2023.
    61. Yoshimasa Uematsu & Takashi Yamagata, 2019. "Estimation of Weak Factor Models," ISER Discussion Paper 1053r, Institute of Social and Economic Research, Osaka University, revised Mar 2020.
    62. Hyungsik Roger Roger Moon & Martin Weidner, 2013. "Linear regression for panel with unknown number of factors as interactive fixed effects," CeMMAP working papers 49/13, Institute for Fiscal Studies.
    63. Denis Chetverikov & Elena Manresa, 2022. "Spectral and post-spectral estimators for grouped panel data models," Papers 2212.13324, arXiv.org, revised Dec 2022.
    64. Jiti Gao & Guangming Pan & Yanrong Yang & Bo Zhang, 2019. "Estimation of Cross-Sectional Dependence in Large Panels," Papers 1904.06843, arXiv.org.
    65. Martin Lettau & Markus Pelger, 2018. "Estimating Latent Asset-Pricing Factors," NBER Working Papers 24618, National Bureau of Economic Research, Inc.
    66. 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.
    67. Matteo Barigozzi, 2023. "Quasi Maximum Likelihood Estimation of High-Dimensional Factor Models: A Critical Review," Papers 2303.11777, arXiv.org, revised Dec 2023.
    68. Jianqing Fan & Yuan Ke & Yuan Liao, 2016. "Augmented Factor Models with Applications to Validating Market Risk Factors and Forecasting Bond Risk Premia," Papers 1603.07041, arXiv.org, revised Sep 2018.
    69. Servén, Luis & Abate, Girum Dagnachew, 2020. "Adding space to the international business cycle," Journal of Macroeconomics, Elsevier, vol. 65(C).
    70. James Sampi, 2016. "High Dimensional Factor Models: An Empirical Bayes Approach," Working Papers 75, Peruvian Economic Association.
    71. Mohitosh Kejriwal & Xiaoxiao Li & Linh Nguyen & Evan Totty, 2024. "The efficacy of ability proxies for estimating the returns to schooling: A factor model‐based evaluation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 3-21, January.
    72. Yinchu Zhu, 2019. "How well can we learn large factor models without assuming strong factors?," Papers 1910.10382, arXiv.org, revised Nov 2019.
    73. Hugo Freeman & Martin Weidner, 2021. "Linear panel regressions with two-way unobserved heterogeneity," CeMMAP working papers CWP39/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    74. Gregory Cox, 2022. "Weak Identification in Low-Dimensional Factor Models with One or Two Factors," Papers 2211.00329, arXiv.org, revised Mar 2024.
    75. Mariano González-Sánchez & M. Encina Morales de Vega, 2021. "Influence of Bloomberg’s Investor Sentiment Index: Evidence from European Union Financial Sector," Mathematics, MDPI, vol. 9(4), pages 1-21, February.
    76. Dashan Huang & Fuwei Jiang & Kunpeng Li & Guoshi Tong & Guofu Zhou, 2022. "Scaled PCA: A New Approach to Dimension Reduction," Management Science, INFORMS, vol. 68(3), pages 1678-1695, March.
    77. António Rua, 2016. "A wavelet-based multivariate multiscale approach for forecasting," Working Papers w201612, Banco de Portugal, Economics and Research Department.
    78. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
    79. Xu Cheng & Bruce E. Hansen, 2012. "Forecasting with Factor-Augmented Regression: A Frequentist Model Averaging Approach, Second Version," PIER Working Paper Archive 13-061, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 03 Sep 2013.
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    Cited by:

    1. Alessi, Lucia & Kerssenfischer, Mark, 2016. "The response of asset prices to monetary policy shocks: stronger than thought," Working Paper Series 1967, European Central Bank.
    2. Mario Forni & Luca Gambetti & Luca Sala, 2011. "No News in Business Cycles," Working Papers 535, Barcelona School of Economics.
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    4. Guo, Wenwen & Cui, Hengjian, 2019. "Projection tests for high-dimensional spiked covariance matrices," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 21-32.
    5. Qin, Duo & He, Xinhua, 2012. "Modelling the impact of aggregate financial shocks external to the Chinese economy," BOFIT Discussion Papers 25/2012, Bank of Finland Institute for Emerging Economies (BOFIT).
    6. Liu, Yan & Bai, Zhidong & Li, Hua & Hu, Jiang & Lv, Zhihui & Zheng, Shurong, 2022. "RDS free CLT for spiked eigenvalues of high-dimensional covariance matrices," Statistics & Probability Letters, Elsevier, vol. 187(C).
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    148. Ke, Xiao & Chen, Haiqiang & Hong, Yongmiao & Hsiao, Cheng, 2017. "Do China's high-speed-rail projects promote local economy?—New evidence from a panel data approach," China Economic Review, Elsevier, vol. 44(C), pages 203-226.
    149. Bystrov, Victor & di Salvatore, Antonietta, 2013. "Martingale approximation of eigenvalues for common factor representation," Statistics & Probability Letters, Elsevier, vol. 83(1), pages 233-237.
    150. Giorgio Calzolari & Roxana Halbleib & Christian Mucher, 2023. "Sequential Estimation of Multivariate Factor Stochastic Volatility Models," Papers 2302.07052, arXiv.org.
    151. Rey, Hélène & Miranda-Agrippino, Silvia, 2015. "World Asset Markets and the Global Financial Cycle," CEPR Discussion Papers 10936, C.E.P.R. Discussion Papers.
    152. Victor Stango & Joanne Yoong & Jonathan Zinman, 2017. "The Quest for Parsimony in Behavioral Economics: New Methods and Evidence on Three Fronts," NBER Working Papers 23057, National Bureau of Economic Research, Inc.
    153. Corsetti, Giancarlo & Duarte, Joao B. & Mann, Samuel, 2018. "One money, many markets: a factor model approach to monetary policy in the Euro Area with high-frequency identification," LSE Research Online Documents on Economics 87182, London School of Economics and Political Science, LSE Library.
    154. 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).
    155. 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.
    156. Angelopoulos, Jason & Sahoo, Satya & Visvikis, Ilias D., 2020. "Commodity and transportation economic market interactions revisited: New evidence from a dynamic factor model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    157. 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.
    158. Christian Brownlees & Geert Mesters, 2017. "Detecting Granular Time Series in Large Panels," Working Papers 991, Barcelona School of Economics.
    159. Marco Avarucci & Paolo Zaffaroni, 2019. "Robust Nearly-Efficient Estimation of Large Panels with Factor Structures," Papers 1902.11181, arXiv.org.
    160. Hautsch, Nikolaus & Kyj, Lada M. & Hautsch, Nikolaus, 2009. "A blocking and regularization approach to high dimensional realized covariance estimation," CFS Working Paper Series 2009/20, Center for Financial Studies (CFS).
    161. 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.
    162. Jiti Gao & Guangming Pan & Yanrong Yang, 2016. "CEstimation of Structural Breaks in Large Panels with Cross-Sectional Dependence," Monash Econometrics and Business Statistics Working Papers 12/16, Monash University, Department of Econometrics and Business Statistics.
    163. Kihwan Kim & Norman Swanson, 2013. "Diffusion Index Model Specification and Estimation Using Mixed Frequency Datasets," Departmental Working Papers 201315, Rutgers University, Department of Economics.
    164. Chou, Ray Yeutien & Yen, Tso-Jung & Yen, Yu-Min, 2017. "Risk evaluations with robust approximate factor models," Journal of Banking & Finance, Elsevier, vol. 82(C), pages 244-264.
    165. Johannes Forkman & Julie Josse & Hans-Peter Piepho, 2019. "Hypothesis Tests for Principal Component Analysis When Variables are Standardized," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(2), pages 289-308, June.
    166. Ding, Xiucai & Yang, Fan, 2022. "Edge statistics of large dimensional deformed rectangular matrices," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    167. Wang, Qinwen & Silverstein, Jack W. & Yao, Jian-feng, 2014. "A note on the CLT of the LSS for sample covariance matrix from a spiked population model," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 194-207.
    168. 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.
    169. Li, Xiao & Qiao, Yuanbo & Shi, Lei, 2019. "Has China's war on pollution slowed the growth of its manufacturing and by how much? Evidence from the Clean Air Action," China Economic Review, Elsevier, vol. 53(C), pages 271-289.
    170. Alexei Onatski & Marcelo Moreira J. & Marc Hallin, 2012. "Signal Detection in High Dmension: The Multispiked Case," Working Papers ECARES ECARES 2012-036, ULB -- Universite Libre de Bruxelles.
    171. Bada, Oualid & Kneip, Alois, 2014. "Parameter cascading for panel models with unknown number of unobserved factors: An application to the credit spread puzzle," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 95-115.
    172. 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.
    173. Yuyang Xu & Zhonghua Liu & Jianfeng Yao, 2023. "An eigenvalue ratio approach to inferring population structure from whole genome sequencing data," Biometrics, The International Biometric Society, vol. 79(2), pages 891-902, June.

  11. Kargin, V. & Onatski, A., 2008. "Curve forecasting by functional autoregression," Journal of Multivariate Analysis, Elsevier, vol. 99(10), pages 2508-2526, November.
    See citations under working paper version above.
  12. Onatski, Alexei, 2006. "Winding number criterion for existence and uniqueness of equilibrium in linear rational expectations models," Journal of Economic Dynamics and Control, Elsevier, vol. 30(2), pages 323-345, February.

    Cited by:

    1. Tan, Fei, 2018. "A Frequency-Domain Approach to Dynamic Macroeconomic Models," MPRA Paper 90487, University Library of Munich, Germany.
    2. Ariane Szafarz, 2015. "Market Efficiency and Crises: Don’t Throw the Baby out with the Bathwater," ULB Institutional Repository 2013/239874, ULB -- Universite Libre de Bruxelles.
    3. Majid Al-Sadoon & Piotr Zwiernik, 2019. "The identification problem for linear rational expectations models," Economics Working Papers 1669, Department of Economics and Business, Universitat Pompeu Fabra.
    4. Al-Sadoon, Majid M., 2014. "Geometric and long run aspects of Granger causality," Journal of Econometrics, Elsevier, vol. 178(P3), pages 558-568.
    5. Marco M. Sorge, 2020. "Arbitrary initial conditions and the dimension of indeterminacy in linear rational expectations models," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 43(1), pages 363-372, June.
    6. Frank Hespeler, 2008. "Solution Algorithm to a Class of Monetary Rational Equilibrium Macromodels with Optimal Monetary Policy Design," Computational Economics, Springer;Society for Computational Economics, vol. 31(3), pages 207-223, April.
    7. Bernd Funovits, 2020. "Identifiability and Estimation of Possibly Non-Invertible SVARMA Models: A New Parametrisation," Papers 2002.04346, arXiv.org, revised Feb 2021.
    8. Adrien Auclert & Bence Bardóczy & Matthew Rognlie & Ludwig Straub, 2019. "Using the Sequence-Space Jacobian to Solve and Estimate Heterogeneous-Agent Models," NBER Working Papers 26123, National Bureau of Economic Research, Inc.
    9. Majid M. Al-Sadoon, 2016. "The linear systems approach to linear rational expectations models," Economics Working Papers 1511, Department of Economics and Business, Universitat Pompeu Fabra.
    10. Zadrozny, Peter A., 2022. "Linear identification of linear rational-expectations models by exogenous variables reconciles Lucas and Sims," CFS Working Paper Series 682, Center for Financial Studies (CFS).
    11. Ariane Szafarz, 2009. "How Did Financial-Crisis-Based Criticisms of Market Efficiency Get It So Wrong?," Working Papers CEB 09-048.RS, ULB -- Universite Libre de Bruxelles.
    12. Peter A. Zadrozny, 2022. "Linear Identification of Linear Rational-Expectations Models by Exogenous Variables Reconciles Lucas and Sims," CESifo Working Paper Series 10078, CESifo.
    13. Frank Hespeler, 2012. "On Boundary Conditions Within the Solution of Macroeconomic Dynamic Models with Rational Expectations," Computational Economics, Springer;Society for Computational Economics, vol. 40(3), pages 265-291, October.
    14. Tan, Fei & Walker, Todd B., 2015. "Solving generalized multivariate linear rational expectations models," Journal of Economic Dynamics and Control, Elsevier, vol. 60(C), pages 95-111.
    15. Mostafavi, Moeen & Fatehi, Ali-Reza & Shakouri G., Hamed & Von zur Muehlen, Peter, 2011. "A predictive multi-agent approach to model systems with linear rational expectations," MPRA Paper 35351, University Library of Munich, Germany, revised 11 Dec 2011.
    16. Majid M. Al-Sadoon, 2020. "Regularized Solutions to Linear Rational Expectations Models," Papers 2009.05875, arXiv.org, revised Oct 2020.
    17. William A. Brock & Steven N. Durlauf & Giacomo Rondina, 2008. "Design Limits and Dynamic Policy Analysis," NBER Working Papers 14357, National Bureau of Economic Research, Inc.
    18. Meyer-Gohde, Alexander & Tzaawa-Krenzler, Mary, 2023. "Sticky information and the Taylor principle," IMFS Working Paper Series 189, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    19. Majid M. Al-Sadoon, 2020. "The Spectral Approach to Linear Rational Expectations Models," Papers 2007.13804, arXiv.org, revised Jun 2023.

  13. Alexei Onatski & Noah Williams, 2004. "Empirical and policy performance of a forward-looking monetary model," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.

    Cited by:

    1. Haider, Adnan & Khan, Safdar Ullah, 2008. "A Small Open Economy DSGE Model for Pakistan," MPRA Paper 12977, University Library of Munich, Germany, revised 17 Jan 2009.
    2. Adolfson, Malin & Laséen, Stefan & Lindé, Jesper & Villani, Mattias, 2005. "Bayesian Estimation of an Open Economy DSGE Model with Incomplete Pass-Through," Working Paper Series 179, Sveriges Riksbank (Central Bank of Sweden).
    3. Eilev S. Jansen, 2004. "Modelling inflation in the Euro Area," Working Paper 2004/10, Norges Bank.
    4. Pelin Ilbas, 2007. "Optimal Monetary Policy Rules for the Euro Area in a DSGE Framework," Money Macro and Finance (MMF) Research Group Conference 2006 59, Money Macro and Finance Research Group.
    5. 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.
    6. Del Negro, Marco & Schorfheide, Frank, 2005. "Monetary policy analysis with potentially misspecified models," Working Paper Series 475, European Central Bank.
    7. Martin Melecky & Diego Rodríguez Palenzuela & Ulf Söderström, 2008. "Inflation Target Transparency and the Macroeconomy," Working Papers Central Bank of Chile 490, Central Bank of Chile.
    8. Wieland, Volker & Taylor, John B., 2010. "Surprising comparative properties of monetary models: Results from a new model database," Working Paper Series 1261, European Central Bank.
    9. John H. Cochrane, 2007. "Determinacy and Identification with Taylor Rules," NBER Working Papers 13410, National Bureau of Economic Research, Inc.
    10. Minford, Patrick & Ou, Zhirong, 2009. "Taylor Rule or Optimal Timeless Policy? Reconsidering the Fed's behaviour since 1982," Cardiff Economics Working Papers E2009/19, Cardiff University, Cardiff Business School, Economics Section, revised May 2010.
    11. Lars E. O. Svensson, 2005. "Targeting versus instrument rules for monetary policy: what is wrong with McCallum and Nelson?," Review, Federal Reserve Bank of St. Louis, vol. 87(Sep), pages 613-626.
    12. Linzert, Tobias & Christoffel, Kai & Kuester, Keith, 2009. "The role of labor markets for euro area monetary policy," Working Paper Series 1035, European Central Bank.
    13. Levin, Andrew T. & Coenen, Günter, 2004. "Identifying the influences of nominal and real rigidities in aggregate price-setting behavior," Working Paper Series 418, European Central Bank.
    14. Costantini, Mauro & Gunter, Ulrich & Kunst, Robert M., 2014. "Forecast combinations in a DSGE-VAR lab," Economics Series 309, Institute for Advanced Studies.
    15. Smets, Frank & Wouters, Raf & Del Negro, Marco & Schorfheide, Frank, 2005. "On the fit and forecasting performance of New-Keynesian models," Working Paper Series 491, European Central Bank.
    16. Jensen, Henrik & Ravn, Søren Hove & Santoro, Emiliano, 2019. "Kinks and Gains from Credit Cycles," CEPR Discussion Papers 13795, C.E.P.R. Discussion Papers.
    17. Iiboshi, Hirokuni & Matsumae, Tatsuyoshi & Namba, Ryoichi & Nishiyama, Shin-Ichi, 2015. "Estimating a DSGE model for Japan in a data-rich environment," Journal of the Japanese and International Economies, Elsevier, vol. 36(C), pages 25-55.
    18. Walsh, Carl E., 2005. "Parameter misspecification and robust monetary policy rules," Working Paper Series 477, European Central Bank.
    19. Peersman, Gert & Straub, Roland, 2004. "Technology shocks and robust sign restrictions in a euro area SVAR," Working Paper Series 373, European Central Bank.
    20. Magda Kandil, 2010. "Demand shocks and the cyclical behavior of the real wage: Some international evidence," Journal of Applied Economics, Universidad del CEMA, vol. 13, pages 135-158, May.
    21. Carla Soares, 2008. "Impact on Welfare of Country Heterogeneity in a Currency Union," Working Papers w200814, Banco de Portugal, Economics and Research Department.
    22. Levine, Paul & McAdam, Peter & Pearlman, Joseph, 2008. "Quantifying and sustaining welfare gains from monetary commitment," Journal of Monetary Economics, Elsevier, vol. 55(7), pages 1253-1276, October.
    23. Den Haan, Wouter & Drechsel, Thomas, 2018. "Agnostic Structural Disturbances (ASDs): Detecting and Reducing Misspecification in Empirical Macroeconomic Models," CEPR Discussion Papers 13145, C.E.P.R. Discussion Papers.
    24. Pytlarczyk, Ernest, 2005. "An estimated DSGE model for the German economy within the euro area," Discussion Paper Series 1: Economic Studies 2005,33, Deutsche Bundesbank.
    25. John C. Williams, 2005. "Robust estimation and monetary policy with unobserved structural change," Proceedings, Board of Governors of the Federal Reserve System (U.S.), pages 53-81.
    26. Schorfheide, Frank & An, Sungbae, 2005. "Bayesian Analysis of DSGE Models," CEPR Discussion Papers 5207, C.E.P.R. Discussion Papers.
    27. Kolasa, Marcin, 2008. "Structural heterogeneity or asymmetric shocks? Poland and the euro area through the lens of a two-country DSGE model," MPRA Paper 8750, University Library of Munich, Germany.
    28. F. Owen Irvine & Scott Schuh, 2007. "The roles of comovement and inventory investment in the reduction of output volatility," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
    29. Andrew T. Levin & Alexei Onatski & John C. Williams & Noah Williams, 2005. "Monetary Policy Under Uncertainty in Micro-Founded Macroeconometric Models," NBER Working Papers 11523, National Bureau of Economic Research, Inc.
    30. Givens, Gregory E., 2016. "On the gains from monetary policy commitment under deep habits," Journal of Macroeconomics, Elsevier, vol. 50(C), pages 19-36.
    31. Roland Straub & Günter Coenen, 2005. "Non-Ricardian Households and Fiscal Policy in an Estimated DSGE Model of the Euro Area," Computing in Economics and Finance 2005 102, Society for Computational Economics.
    32. Boivin, J. & Giannoni, M., 2007. "DSGE Models in a Data-Rich Environment," Working papers 162, Banque de France.
    33. Mr. Roland Straub & Gert Peersman, 2006. "Putting the New Keynesian Model to a Test," IMF Working Papers 2006/135, International Monetary Fund.
    34. Daniel O. Beltran & David Draper, 2016. "Estimating Dynamic Macroeconomic Models : How Informative Are the Data?," International Finance Discussion Papers 1175, Board of Governors of the Federal Reserve System (U.S.).
    35. Juillard, Michel & Le Bihan, Herve & Millard, Stephen, 2013. "Non-uniform wage-staggering: European evidence and monetary policy implications," Bank of England working papers 477, Bank of England.
    36. Iiboshi, Hirokuni & Nishiyama, Shin-Ichi & Watanabe, Toshiaki, 2006. "An Estimated Dynamic Stochastic General Equilibrium Model of the Japanese Economy: A Bayesian Analysis," MPRA Paper 85702, University Library of Munich, Germany.
    37. Patrick Minford & Zhirong Ou & Michael Wickens, 2015. "Revisiting the Great Moderation: Policy or Luck?," Open Economies Review, Springer, vol. 26(2), pages 197-223, April.
    38. Costantini, Mauro & Gunter, Ulrich & Kunst, Robert M., 2012. "Forecast Combination Based on Multiple Encompassing Tests in a Macroeconomic DSGE-VAR System," Economics Series 292, Institute for Advanced Studies.
    39. Levin, Andrew T. & Moessner, Richhild, 2005. "Inflation persistence and monetary policy design: an overview," Working Paper Series 539, European Central Bank.
    40. Fabio Milani, 2005. "Expectations, Learning and Macroeconomic Persistence," Macroeconomics 0510022, University Library of Munich, Germany.
    41. IIBOSHI Hirokuni, 2012. "Measuring the Effects of Monetary Policy: A DSGE-DFM Approach," ESRI Discussion paper series 292, Economic and Social Research Institute (ESRI).
    42. Gregory E. Givens, 2012. "Estimating Central Bank Preferences under Commitment and Discretion," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(6), pages 1033-1061, September.
    43. Ben Ali, Samir, 2010. "A New Keynesian Phillips curve for Tunisia : Estimation and analysis of sensitivity," MPRA Paper 29624, University Library of Munich, Germany.
    44. Marco Del Negro & Frank Schorfheide, 2004. "Policy predictions if the model doesn’t fit," FRB Atlanta Working Paper 2004-38, Federal Reserve Bank of Atlanta.
    45. Daichi Shirai, 2014. "A note on hump-shaped output in the RBC model," CIGS Working Paper Series 14-009E, The Canon Institute for Global Studies.
    46. Tillmann, Peter, 2005. "The New Keynesian Phillips Curve in Europe: does it fit or does it fail?," Discussion Paper Series 1: Economic Studies 2005,04, Deutsche Bundesbank.
    47. Lars E.O. Svensson, 2004. "Targeting Rules vs. Instrument Rules for Monetary Policy: What is Wrong with McCallum and Nelson?," NBER Working Papers 10747, National Bureau of Economic Research, Inc.
    48. Kawther Alimi & Mohamed Chakroun, 2022. "Wage Rigidity Impacts on Unemployment and Inflation Persistence in Tunisia: Evidence from an Estimated DSGE Model," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(1), pages 474-500, March.
    49. Pelin Ilbas, 2008. "Estimation of monetary policy preferences in a forward-looking model : a Bayesian approach," Working Paper Research 129, National Bank of Belgium.

  14. Alexei Onatski & Noah Williams, 2003. "Modeling Model Uncertainty," Journal of the European Economic Association, MIT Press, vol. 1(5), pages 1087-1122, September.
    See citations under working paper version above.
  15. Kremer, Michael & Onatski, Alexei & Stock, James, 2001. "Searching for prosperity," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 55(1), pages 275-303, December.
    See citations under working paper version above.
  16. Alexei Onatski & James H. Stock, 1999. "Robust monetary policy under model uncertainty in a small model of the U.S. economy," Proceedings, Federal Reserve Bank of San Francisco.
    See citations under working paper version above.

Chapters

  1. Andrew T. Levin & Alexei Onatski & John Williams & Noah M. Williams, 2006. "Monetary Policy under Uncertainty in Micro-Founded Macroeconometric Models," NBER Chapters, in: NBER Macroeconomics Annual 2005, Volume 20, pages 229-312, National Bureau of Economic Research, Inc.
    See citations under working paper version above.Sorry, no citations of chapters recorded.
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