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Jushan Bai

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. Author Profile
    1. Peer Group as of April 2015
      by Matthew Kahn in Environmental and Urban Economics on 2015-05-03 19:55:00

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January.

    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. Jushan Bai & Peng Wang, 2011. "Conditional Markov chain and its application in economic time series analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(5), pages 715-734, August.

    Mentioned in:

    1. Conditional Markov chain and its application in economic time series analysis (Journal of Applied Econometrics 2011) in ReplicationWiki ()
  2. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.

    Mentioned in:

    1. Computation and analysis of multiple structural change models (Journal of Applied Econometrics 2003) in ReplicationWiki ()

Working papers

  1. Jiangtao Duan & Jushan Bai & Xu Han, 2021. "Quasi-maximum likelihood estimation of break point in high-dimensional factor models," Papers 2102.12666, arXiv.org, revised Mar 2021.

    Cited by:

    1. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.

  2. Ercument Cahan & Jushan Bai & Serena Ng, 2021. "Factor-Based Imputation of Missing Values and Covariances in Panel Data of Large Dimensions," Papers 2103.03045, arXiv.org, revised Feb 2022.

    Cited by:

    1. Helena Chuliá & Sabuhi Khalili & Jorge M. Uribe, 2024. "Monitoring time-varying systemic risk in sovereign debt and currency markets with generative AI," IREA Working Papers 202402, University of Barcelona, Research Institute of Applied Economics, revised Feb 2024.
    2. Jungjun Choi & Ming Yuan, 2023. "Matrix Completion When Missing Is Not at Random and Its Applications in Causal Panel Data Models," Papers 2308.02364, arXiv.org.
    3. Jose E. Gomez-Gonzalez & Jorge M. Uribe & Oscar M. Valencia, 2024. "Asymmetric Sovereign Risk: Implications for Climate Change Preparation," IREA Working Papers 202401, University of Barcelona, Research Institute of Applied Economics, revised Jan 2024.
    4. Juan, Aranzazu de & Poncela, Maria Pilar & Ruiz Ortega, Esther, 2023. "Economic activity and C02 emissions in Spain," DES - Working Papers. Statistics and Econometrics. WS 37975, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Christian Fieberg & Daniel Metko & Thorsten Poddig & Thomas Loy, 2023. "Machine learning techniques for cross-sectional equity returns’ prediction," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(1), pages 289-323, March.

  3. Jushan Bai & Serena Ng, 2021. "Approximate Factor Models with Weaker Loadings," Papers 2109.03773, arXiv.org, revised Mar 2023.

    Cited by:

    1. Jungjun Choi & Ming Yuan, 2024. "High Dimensional Factor Analysis with Weak Factors," Papers 2402.05789, arXiv.org.
    2. Wanbo Lu & Guanglin Huang & Kris Boudt, 2024. "Estimation of Non-Gaussian Factors Using Higher-order Multi-cumulants in Weak Factor Models," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 24/1085, Ghent University, Faculty of Economics and Business Administration.
    3. Jie Wei & Yonghui Zhang, 2023. "Does Principal Component Analysis Preserve the Sparsity in Sparse Weak Factor Models?," Papers 2305.05934, arXiv.org.
    4. Lihua Lei & Brad Ross, 2023. "Estimating Counterfactual Matrix Means with Short Panel Data," Papers 2312.07520, arXiv.org.
    5. Jungjun Choi & Hyukjun Kwon & Yuan Liao, 2023. "Inference for Low-rank Models without Estimating the Rank," Papers 2311.16440, arXiv.org.
    6. Jad Beyhum, 2024. "Counterfactuals in factor models," Papers 2401.03293, arXiv.org.

  4. Jushan Bai & Serena Ng, 2020. "Simpler Proofs for Approximate Factor Models of Large Dimensions," Papers 2008.00254, arXiv.org.

    Cited by:

    1. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    2. Philipp Gersing & Christoph Rust & Manfred Deistler, 2023. "Weak Factors are Everywhere," Papers 2307.10067, arXiv.org, revised Jan 2024.
    3. Jonas Krampe & Luca Margaritella, 2021. "Factor Models with Sparse VAR Idiosyncratic Components," Papers 2112.07149, arXiv.org, revised May 2022.
    4. Matteo Barigozzi, 2023. "Quasi Maximum Likelihood Estimation of High-Dimensional Factor Models: A Critical Review," Papers 2303.11777, arXiv.org, revised Dec 2023.
    5. Helena Chuliá & Ignacio Garrón & Jorge M. Uribe, 2021. ""Vulnerable Funding in the Global Economy"," IREA Working Papers 202106, University of Barcelona, Research Institute of Applied Economics, revised Mar 2021.
    6. Matteo Barigozzi, 2022. "On Estimation and Inference of Large Approximate Dynamic Factor Models via the Principal Component Analysis," Papers 2211.01921, arXiv.org, revised Jul 2023.

  5. Jushan Bai & Sung Hoon Choi & Yuan Liao, 2019. "Standard Errors for Panel Data Models with Unknown Clusters," Papers 1910.07406, arXiv.org, revised May 2020.

    Cited by:

    1. Jiti Gao & Bin Peng & Yayi Yan, 2023. "Higher-order Expansions and Inference for Panel Data Models," Monash Econometrics and Business Statistics Working Papers 15/23, Monash University, Department of Econometrics and Business Statistics.
    2. Chen, Hongrui, 2023. "Energy innovations, natural resource abundance, urbanization, and environmental sustainability in the post-covid era. Does environmental regulation matter?," Resources Policy, Elsevier, vol. 85(PB).

  6. Jushan Bai & Sung Hoon Choi & Yuan Liao, 2019. "Feasible Generalized Least Squares for Panel Data with Cross-sectional and Serial Correlations," Papers 1910.09004, arXiv.org, revised Aug 2020.

    Cited by:

    1. Chaitat Jirophat & Pym Manopimoke & Suparit Suwanik, 2022. "The Macroeconomic Effects of Climate Shocks in Thailand," PIER Discussion Papers 188, Puey Ungphakorn Institute for Economic Research.
    2. Maksim Godovykh & Alan Fyall & Abraham Pizam & Jorge Ridderstaat, 2022. "Evaluating the Direct and Indirect Impacts of Tourism on the Health of Local Communities," Academica Turistica - Tourism and Innovation Journal, University of Primorska Press, vol. 15(1), pages 43-52.
    3. Mohammad Anamul Haque & Syed Mehmood Raza Shah & Muhammad Usman Arshad, 2022. "Sustainable Economic Growth and FDI Inflow: A Comparative Panel Econometric Analysis of Low-Income and Middle-Income Nations," Sustainability, MDPI, vol. 14(21), pages 1-14, November.
    4. Zhang, Ailian & Pan, Mengmeng & Liu, Bai & Cao, Xianbin, 2023. "Do high-speed rail (HSR) station and airport affect local government debt risk? Evidence from China," Transport Policy, Elsevier, vol. 134(C), pages 41-51.
    5. Mohd IRSHAD & Syed Hasan QAYED, 2022. "Casual nexus between economic growth, FDI and employment: An inquiry into BRICS and ASEAN," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(2(631), S), pages 107-124, Summer.
    6. Vo, Thang T. & Ha, Truong Thiet, 2021. "Decomposition of gender bias in enterprise employment: Insights from Vietnam," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 182-194.
    7. Chen, Hongrui, 2023. "Energy innovations, natural resource abundance, urbanization, and environmental sustainability in the post-covid era. Does environmental regulation matter?," Resources Policy, Elsevier, vol. 85(PB).
    8. Eleftherios Giovanis & Oznur Ozdamar, 2022. "The impact of climate change on budget balances and debt in the Middle East and North Africa (MENA) region," Climatic Change, Springer, vol. 172(3), pages 1-27, June.
    9. John Bosco Nnyanzi & Susan Kavuma & John Sseruyange & Aisha Nanyiti, 2022. "The manufacturing output effects of infrastructure development, liberalization and governance: evidence from Sub-Saharan Africa," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 49(2), pages 369-400, June.
    10. Alban Pellegris, 2023. "Energy as a limiting factor of economic growth: the profit rate channel," Working Papers hal-04120296, HAL.
    11. Sabyasachi Tripathi & Meenakshi Rajeev, 2023. "Gender-Inclusive Development through Fintech: Studying Gender-Based Digital Financial Inclusion in a Cross-Country Setting," Sustainability, MDPI, vol. 15(13), pages 1-34, June.
    12. Lin, Vera Shanshan & Qin, Yuan & Li, Gang & Jiang, Fan, 2022. "Multiple effects of “distance” on domestic tourism demand: A comparison before and after the emergence of COVID-19," Annals of Tourism Research, Elsevier, vol. 95(C).
    13. Leone Walters & Manoel Bittencourt & Carolyn Chisadza, 2019. "Public Infrastructure Provision and Ethnic Favouritism: Evidence from South Africa," Working Papers 201949, University of Pretoria, Department of Economics.
    14. Liu, Xia, 2023. "Tourism development, environmental regulations, and natural resource management: Evidence from G20 countries," Resources Policy, Elsevier, vol. 86(PA).
    15. Yin, Zi Hui & Zeng, Wei Ping, 2023. "The effects of industrial intelligence on China's energy intensity: The role of technology absorptive capacity," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    16. Alena Vagaská & Miroslav Gombár & Antonín Korauš, 2022. "Mathematical Modeling and Nonlinear Optimization in Determining the Minimum Risk of Legalization of Income from Criminal Activities in the Context of EU Member Countries," Mathematics, MDPI, vol. 10(24), pages 1-25, December.
    17. Qi Li & Vasilis Sarafidis & Joakim Westerlund, 2021. "Essays in honor of Professor Badi H Baltagi," Empirical Economics, Springer, vol. 60(1), pages 1-11, January.
    18. Haykir, Ozkan & Yagli, Ibrahim & Aktekin Gok, Emine Dilara & Budak, Hilal, 2022. "Oil price explosivity and stock return: Do sector and firm size matter?," Resources Policy, Elsevier, vol. 78(C).
    19. Obey Dzomonda & Olawale Fatoki, 2020. "Environmental Sustainability Commitment and Financial Performance of Firms Listed on the Johannesburg Stock Exchange (JSE)," IJERPH, MDPI, vol. 17(20), pages 1-21, October.
    20. Naudé, Wim & Tregenna, Fiona, 2023. "Africa's Industrialization Prospects: A Fresh Look," IZA Discussion Papers 16043, Institute of Labor Economics (IZA).
    21. Pakrooh, Parisa & Kamal, Muhamad Abdul, 2023. "Modeling the potential impacts of climate change on wheat yield in Iran: Evidence from national and provincial data analysis," Ecological Modelling, Elsevier, vol. 486(C).
    22. Gnangnon, Sèna Kimm, 2022. "Effect of the Duty-Free Quota-Free Market access Schemes in favour of Least developed countries' Products on the Volatility of the Utilization Rate of these Schemes," EconStor Preprints 260567, ZBW - Leibniz Information Centre for Economics.
    23. Ozili, Peterson K, 2023. "Financial stability and sustainable development," MPRA Paper 118793, University Library of Munich, Germany.
    24. Li, Qi & Sarafidis, Vasilis & Westerlund, Joakim, 2020. "Essays in Honor of Professor Badi H Baltagi: Editorial," MPRA Paper 104751, University Library of Munich, Germany.
    25. Henryk Dzwigol & Aleksy Kwilinski & Oleksii Lyulyov & Tetyana Pimonenko, 2023. "Renewable Energy, Knowledge Spillover and Innovation: Capacity of Environmental Regulation," Energies, MDPI, vol. 16(3), pages 1-15, January.
    26. Gnangnon, Sèna Kimm, 2023. "The Least developed countries' TRIPS Waiver and the Strength of Intellectual Property Protection," EconStor Preprints 271537, ZBW - Leibniz Information Centre for Economics.
    27. Gnangnon, Sèna Kimm, 2023. "Productive capacities, structural economic vulnerability and fiscal space volatility in developing countries," KDI Journal of Economic Policy, Korea Development Institute (KDI), vol. 45(3), pages 25-48.

  7. Jushan Bai & Serena Ng, 2019. "Matrix Completion, Counterfactuals, and Factor Analysis of Missing Data," Papers 1910.06677, arXiv.org, revised Aug 2021.

    Cited by:

    1. Alexandre Bonnet R. Costa & Pedro Cavalcanti G. Ferreira & Wagner Piazza Gaglianone & Osmani Teixeira C. Guillén & João Victor Issler & Artur Brasil Fialho Rodrigues, 2023. "Predicting Recessions in (almost) Real Time in a Big-data Setting," Working Papers Series 587, Central Bank of Brazil, Research Department.
    2. Yinchu Zhu, 2019. "How well can we learn large factor models without assuming strong factors?," Papers 1910.10382, arXiv.org, revised Nov 2019.
    3. Serena Ng & Susannah Scanlan, 2023. "Constructing High Frequency Economic Indicators by Imputation," Papers 2303.01863, arXiv.org, revised Oct 2023.
    4. Guido Imbens & Nathan Kallus & Xiaojie Mao, 2021. "Controlling for Unmeasured Confounding in Panel Data Using Minimal Bridge Functions: From Two-Way Fixed Effects to Factor Models," Papers 2108.03849, arXiv.org.
    5. Chan, Joshua C.C. & Poon, Aubrey & Zhu, Dan, 2023. "High-dimensional conditionally Gaussian state space models with missing data," Journal of Econometrics, Elsevier, vol. 236(1).
    6. Callaway, Brantly & Karami, Sonia, 2023. "Treatment effects in interactive fixed effects models with a small number of time periods," Journal of Econometrics, Elsevier, vol. 233(1), pages 184-208.
    7. Ercument Cahan & Jushan Bai & Serena Ng, 2021. "Factor-Based Imputation of Missing Values and Covariances in Panel Data of Large Dimensions," Papers 2103.03045, arXiv.org, revised Feb 2022.
    8. Xiong, Ruoxuan & Pelger, Markus, 2023. "Large dimensional latent factor modeling with missing observations and applications to causal inference," Journal of Econometrics, Elsevier, vol. 233(1), pages 271-301.
    9. Brantly Callaway, 2022. "Difference-in-Differences for Policy Evaluation," Papers 2203.15646, arXiv.org.
    10. Michael McCracken & Serena Ng, 2020. "FRED-QD: A Quarterly Database for Macroeconomic Research," NBER Working Papers 26872, National Bureau of Economic Research, Inc.
    11. Xingyu Li & Yan Shen & Qiankun Zhou, 2022. "Confidence Intervals of Treatment Effects in Panel Data Models with Interactive Fixed Effects," Papers 2202.12078, arXiv.org.
    12. FATUM, Rasmus & YAMAMOTO, Yohei & CHEN, Binwei, 2023. "The Trend Effect of Foreign Exchange Intervention," Discussion paper series HIAS-E-132, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    13. Bai, Jushan & Wang, Peng, 2024. "Causal inference using factor models," MPRA Paper 120585, University Library of Munich, Germany.
    14. Joaqui-Barandica, Orlando & Manotas-Duque, Diego F. & Uribe, Jorge M., 2022. "Commonality, macroeconomic factors and banking profitability," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    15. Albert Chiu & Xingchen Lan & Ziyi Liu & Yiqing Xu, 2023. "What To Do (and Not to Do) with Causal Panel Analysis under Parallel Trends: Lessons from A Large Reanalysis Study," Papers 2309.15983, arXiv.org, revised Apr 2024.
    16. Zongwu Cai & Ying Fang & Ming Lin & Zixuan Wu, 2023. "A Quasi Synthetic Control Method for Nonlinear Models With High-Dimensional Covariates," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202305, University of Kansas, Department of Economics, revised Aug 2023.
    17. Alberto Abadie & Anish Agarwal & Raaz Dwivedi & Abhin Shah, 2024. "Doubly Robust Inference in Causal Latent Factor Models," Papers 2402.11652, arXiv.org, revised Apr 2024.
    18. Jungjun Choi & Ming Yuan, 2023. "Matrix Completion When Missing Is Not at Random and Its Applications in Causal Panel Data Models," Papers 2308.02364, arXiv.org.
    19. Alexandre Belloni & Mingli Chen & Oscar Hernan Madrid Padilla & Zixuan & Wang, 2019. "High Dimensional Latent Panel Quantile Regression with an Application to Asset Pricing," Papers 1912.02151, arXiv.org, revised Aug 2022.
    20. Magnac, Thierry, 2023. "Capital humain et recherche d'emploi: un mariage heureux - Human Capital and Search Models: A Happy Match," TSE Working Papers 23-1489, Toulouse School of Economics (TSE).
    21. Ruoxuan Xiong & Markus Pelger, 2019. "Large Dimensional Latent Factor Modeling with Missing Observations and Applications to Causal Inference," Papers 1910.08273, arXiv.org, revised Jan 2022.
    22. 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.
    23. Luis Costa & Vivek F. Farias & Patricio Foncea & Jingyuan (Donna) Gan & Ayush Garg & Ivo Rosa Montenegro & Kumarjit Pathak & Tianyi Peng & Dusan Popovic, 2023. "Generalized Synthetic Control for TestOps at ABI: Models, Algorithms, and Infrastructure," Interfaces, INFORMS, vol. 53(5), pages 336-349, September.
    24. Jungjun Choi & Hyukjun Kwon & Yuan Liao, 2023. "Inference for Low-rank Completion without Sample Splitting with Application to Treatment Effect Estimation," Papers 2307.16370, arXiv.org.
    25. Anish Agarwal & Keegan Harris & Justin Whitehouse & Zhiwei Steven Wu, 2023. "Adaptive Principal Component Regression with Applications to Panel Data," Papers 2307.01357, arXiv.org, revised Oct 2023.

  8. Jushan Bai & Junlong Feng, 2019. "Robust Principal Component Analysis with Non-Sparse Errors," Papers 1902.08735, arXiv.org, revised Nov 2019.

    Cited by:

    1. A. H. Bentbib & A. El Hachimi & K. Jbilou & A. Ratnani, 2022. "A Tensor Regularized Nuclear Norm Method for Image and Video Completion," Journal of Optimization Theory and Applications, Springer, vol. 192(2), pages 401-425, February.
    2. Trucíos Maza, Carlos César & Mazzeu, João H. G. & Hotta, Luiz Koodi & Pereira, Pedro L. Valls & Hallin, Marc, 2020. "Robustness and the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting," Textos para discussão 521, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    3. Sedigheh Mohamadi & Saad Sh. Sammen & Fatemeh Panahi & Mohammad Ehteram & Ozgur Kisi & Amir Mosavi & Ali Najah Ahmed & Ahmed El-Shafie & Nadhir Al-Ansari, 2020. "Zoning map for drought prediction using integrated machine learning models with a nomadic people optimization algorithm," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 104(1), pages 537-579, October.
    4. Alexandre Belloni & Mingli Chen & Oscar Hernan Madrid Padilla & Zixuan & Wang, 2019. "High Dimensional Latent Panel Quantile Regression with an Application to Asset Pricing," Papers 1912.02151, arXiv.org, revised Aug 2022.

  9. Ando, Tomohiro & Bai, Jushan, 2018. "Quantile co-movement in financial markets: A panel quantile model with unobserved heterogeneity," MPRA Paper 88765, University Library of Munich, Germany.

    Cited by:

    1. Dimitris Korobilis & Maximilian Schröder, 2023. "Monitoring multicountry macroeconomic risk," Working Papers No 06/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    2. Yongxia Zhang & Qi Wang & Maozai Tian, 2022. "Smoothed Quantile Regression with Factor-Augmented Regularized Variable Selection for High Correlated Data," Mathematics, MDPI, vol. 10(16), pages 1-30, August.
    3. Anthoulla Phella, 2020. "Forecasting With Factor-Augmented Quantile Autoregressions: A Model Averaging Approach," Papers 2010.12263, arXiv.org.
    4. Daan Opschoor & Dick van Dijk & Philip Hans Franses, 2021. "Heterogeneity in Manufacturing Growth Risk," Tinbergen Institute Discussion Papers 21-036/III, Tinbergen Institute.
    5. Ruofan Xu & Jiti Gao & Tatsushi Oka & Yoon-Jae Whang, 2022. "Estimation of Heterogeneous Treatment Effects Using Quantile Regression with Interactive Fixed Effects," Monash Econometrics and Business Statistics Working Papers 13/22, Monash University, Department of Econometrics and Business Statistics.
    6. Ando, Tomohiro & Bai, Jushan & Li, Kunpeng, 2022. "Bayesian and maximum likelihood analysis of large-scale panel choice models with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 230(1), pages 20-38.
    7. Chen, Liang & Dolado, Juan José & Ramos Ramirez, Andrey David & Gonzalo, Jesús, 2023. "Heterogeneous Predictive Association of CO2 with Global Warming," UC3M Working papers. Economics 36451, Universidad Carlos III de Madrid. Departamento de Economía.
    8. Jiti Gao & Fei Liu & Bin peng, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Monash Econometrics and Business Statistics Working Papers 44/20, Monash University, Department of Econometrics and Business Statistics.
    9. Nicola Borri & Denis Chetverikov & Yukun Liu & Aleh Tsyvinski, 2024. "One Factor to Bind the Cross-Section of Returns," Cowles Foundation Discussion Papers 2386, Cowles Foundation for Research in Economics, Yale University.
    10. Xiao Huang, 2023. "Composite Quantile Factor Models," Papers 2308.02450, arXiv.org.
    11. Tomohiro Ando & Matthew Greenwood-Nimmo & Yongcheol Shin, 2022. "Quantile Connectedness: Modeling Tail Behavior in the Topology of Financial Networks," Management Science, INFORMS, vol. 68(4), pages 2401-2431, April.
    12. Yu Sheng & V. Eldon Ball & Kenneth Erickson & Carlos San Juan Mesonada, 2022. "Cross-country agricultural TFP convergence and capital deepening: evidence for induced innovation from 17 OECD countries," Journal of Productivity Analysis, Springer, vol. 58(2), pages 185-202, December.
    13. Jia Chen Author-Name-First: Jia & Yongcheol Shin & Chaowen Zheng, 2023. "Dynamic Quantile Panel Data Models with Interactive Effects," Economics Discussion Papers em-dp2023-06, Department of Economics, University of Reading.
    14. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Papers 2012.03182, arXiv.org, revised Nov 2021.
    15. Liang Chen & Juan Jose Dolado & Jesus Gonzalo, 2019. "Quantile Factor Models," Papers 1911.02173, arXiv.org, revised Sep 2020.
    16. Zhu, Huiming & Li, Shuang & Huang, Zishan, 2023. "Frequency domain quantile dependence and connectedness between crude oil and exchange rates: Evidence from oil-importing and exporting countries," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 1-30.
    17. Xie, Qichang & Ma, Di & Raza, Muhammad Yousaf & Tang, Songlin & Bai, Dingchuan, 2023. "Toward carbon peaking and neutralization: The heterogeneous stochastic convergence of CO2 emissions and the role of digital inclusive finance," Energy Economics, Elsevier, vol. 125(C).
    18. Ling Peng & Dong Han, 2021. "The Convergence Rate of High-Dimensional Sample Quantiles for φ -Mixing Observation Sequences," Mathematics, MDPI, vol. 9(6), pages 1-8, March.
    19. Dimitris Korobilis & Maximilian Schröder, 2023. "Probabilistic Quantile Factor Analysis," Working Papers No 05/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    20. Anthoulla Phella, 2020. "Consistent Specification Test of the Quantile Autoregression," Papers 2010.03898, arXiv.org, revised Jan 2024.
    21. Jozef Barunik & Matej Nevrla, 2022. "Common Idiosyncratic Quantile Risk," Papers 2208.14267, arXiv.org, revised Jun 2023.
    22. Baruník, Jozef & Čech, František, 2021. "Measurement of common risks in tails: A panel quantile regression model for financial returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    23. Chen, Liang & Dolado, Juan José & Gonzalo, Jesús & Ramos Ramirez, Andrey David, 2013. "Revisiting Granger Causality of CO2 on Global Warming: a Quantile Factor Approach," DES - Working Papers. Statistics and Econometrics. WS 35531, Universidad Carlos III de Madrid. Departamento de Estadística.
    24. Ando, Tomohiro & Li, Kunpeng & Lu, Lina, 2023. "A spatial panel quantile model with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 232(1), pages 191-213.
    25. Zongwu Cai & Xiyuan Liu, 2020. "A Functional-Coefficient VAR Model for Dynamic Quantiles with Constructing Financial Network," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202017, University of Kansas, Department of Economics, revised Oct 2020.

  10. Jushan Bai & Serena Ng, 2017. "Principal Components and Regularized Estimation of Factor Models," Papers 1708.08137, arXiv.org, revised Nov 2017.

    Cited by:

    1. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
    2. Susan Athey & Mohsen Bayati & Nikolay Doudchenko & Guido Imbens & Khashayar Khosravi, 2017. "Matrix Completion Methods for Causal Panel Data Models," Papers 1710.10251, arXiv.org, revised Apr 2022.
    3. Martin Lettau & Markus Pelger, 2018. "Estimating Latent Asset-Pricing Factors," NBER Working Papers 24618, National Bureau of Economic Research, Inc.
    4. Jushan Bai & Sung Hoon Choi & Yuan Liao, 2021. "Feasible generalized least squares for panel data with cross-sectional and serial correlations," Empirical Economics, Springer, vol. 60(1), pages 309-326, January.
    5. Jiangtao Duan & Wei Gao & Hao Qu & Hon Keung Tony, 2019. "Subspace Clustering for Panel Data with Interactive Effects," Papers 1909.09928, arXiv.org, revised Feb 2021.
    6. Alexandre Belloni & Mingli Chen & Oscar Hernan Madrid Padilla & Zixuan & Wang, 2019. "High Dimensional Latent Panel Quantile Regression with an Application to Asset Pricing," Papers 1912.02151, arXiv.org, revised Aug 2022.
    7. Victor Chernozhukov & Christian Hansen & Yuan Liao & Yinchu Zhu, 2019. "Inference for heterogeneous effects using low-rank estimations," CeMMAP working papers CWP31/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Gu, Shihao & Kelly, Bryan & Xiu, Dacheng, 2021. "Autoencoder asset pricing models," Journal of Econometrics, Elsevier, vol. 222(1), pages 429-450.
    9. Philippe Goulet Coulombe, 2020. "Time-Varying Parameters as Ridge Regressions," Papers 2009.00401, arXiv.org, revised Apr 2023.

  11. Ando, Tomohiro & Bai, Jushan, 2014. "A simple new test for slope homogeneity in panel data models with interactive effects," MPRA Paper 60795, University Library of Munich, Germany.

    Cited by:

    1. 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.
    2. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    3. Jean-Baptiste Hasse & Quentin Lajaunie, 2020. "Does the Yield Curve Signal Recessions? New Evidence from an International Panel Data Analysis," AMSE Working Papers 2013, Aix-Marseille School of Economics, France.
    4. Feng Xu & Zekai He, 2020. "Testing slope homogeneity in panel data models with a multifactor error structure," Statistical Papers, Springer, vol. 61(1), pages 201-224, February.
    5. Ando, Tomohiro & Bai, Jushan, 2021. "Large-scale generalized linear longitudinal data models with grouped patterns of unobserved heterogeneity," MPRA Paper 111431, University Library of Munich, Germany.
    6. Olatunji A. Shobande & Simplice A. Asongu, 2021. "Financial Development, Human Capital Development and Climate Change in East and Southern Africa," Research Africa Network Working Papers 21/042, Research Africa Network (RAN).
    7. Mohitosh Kejriwal & Haiqing Zhao, 2019. "Revisiting the Democracy-Growth Nexus:New Evidence from a Dynamic Common Correlated Effects Approach," Purdue University Economics Working Papers 1317, Purdue University, Department of Economics.
    8. Mohitosh Kejriwal & Xiaoxiao Li & Evan Totty, 2020. "Multidimensional skills and the returns to schooling: Evidence from an interactive fixed‐effects approach and a linked survey‐administrative data set," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 548-566, August.
    9. Georg Keilbar & Juan M. Rodriguez-Poo & Alexandra Soberon & Weining Wang, 2022. "A semiparametric approach for interactive fixed effects panel data models," Papers 2201.11482, arXiv.org, revised Mar 2023.
    10. Mohitosh Kejriwal & Xiaoxiao Li & Evan Totty, 2019. "Multidemsional Skills and Returns to Schooling: Evidence from an Interactive Fixed Effects Aproach and a Linked Survey-Administrative Dataset," Purdue University Economics Working Papers 1316, Purdue University, Department of Economics.
    11. Fernandez, Julian, 2020. "Exchange Rate Uncertainty and the Interest Rate Parity," MPRA Paper 116010, University Library of Munich, Germany, revised 2022.
    12. Mehmet Akyol & Emrullah Mete, 2021. "The Relationship Between Labor Productivity, Exports, and Foreign Direct Investment for Transition Economies," Journal of Economic Policy Researches, Istanbul University, Faculty of Economics, vol. 8(2), pages 155-171, July.

  12. Bai, Jushan & Li, Kunpeng & Lu, Lina, 2014. "Estimation and inference of FAVAR models," MPRA Paper 60960, University Library of Munich, Germany.

    Cited by:

    1. Mantas Lukauskas & Vaida Pilinkienė & Jurgita Bruneckienė & Alina Stundžienė & Andrius Grybauskas & Tomas Ruzgas, 2022. "Economic Activity Forecasting Based on the Sentiment Analysis of News," Mathematics, MDPI, vol. 10(19), pages 1-22, September.
    2. Herwartz, Helmut & Rohloff, Hannes, 2018. "Less bang for the buck? Assessing the role of inflation uncertainty for U.S. monetary policy transmission in a data rich environment," University of Göttingen Working Papers in Economics 358, University of Goettingen, Department of Economics.
    3. Ashoka Mody & Milan Nedeljkovic, 2018. "Central Bank Policies and Financial Markets: Lessons from the Euro Crisis," CESifo Working Paper Series 7400, CESifo.
    4. Anindya Banerjee & Victor Bystrov & Paul Mizen, 2017. "Structural Factor Analysis of Interest Rate Pass Through In Four Large Euro Area Economies," Working Papers in Economics 17/07, University of Canterbury, Department of Economics and Finance.
    5. Christian Brownlees & Geert Mesters, 2017. "Detecting Granular Time Series in Large Panels," Working Papers 991, Barcelona School of Economics.
    6. 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.
    7. Jiahe Lin & George Michailidis, 2019. "Approximate Factor Models with Strongly Correlated Idiosyncratic Errors," Papers 1912.04123, arXiv.org.
    8. Simon Beyeler & Sylvia Kaufmann, 2016. "Factor augmented VAR revisited - A sparse dynamic factor model approach," Working Papers 16.08, Swiss National Bank, Study Center Gerzensee.
    9. Chudik, A. & Pesaran, H. & Mohaddes, K., 2018. "Identifying Global and National Output and Fiscal Policy Shocks Using a GVAR," Cambridge Working Papers in Economics 1874, Faculty of Economics, University of Cambridge.
    10. Smeekes, Stephan & Wijler, Etiënne, 2016. "Macroeconomic Forecasting Using Penalized Regression Methods," Research Memorandum 039, Maastricht University, Graduate School of Business and Economics (GSBE).
    11. Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2023. "Inference of Grouped Time-Varying Network Vector Autoregression Models," Monash Econometrics and Business Statistics Working Papers 5/23, Monash University, Department of Econometrics and Business Statistics.
    12. Xiang Gao & Wen Kong & Zhijun Hu, 2022. "The Effects of National Fundamental Factors on Regional House Prices: A Factor-Augmented VAR Analysis," JRFM, MDPI, vol. 15(7), pages 1-19, July.
    13. Tomohiro Ando & Matthew Greenwood-Nimmo & Yongcheol Shin, 2022. "Quantile Connectedness: Modeling Tail Behavior in the Topology of Financial Networks," Management Science, INFORMS, vol. 68(4), pages 2401-2431, April.
    14. Maldonado, Javier & Ruiz Ortega, Esther, 2017. "Accurate Subsampling Intervals of Principal Components Factors," DES - Working Papers. Statistics and Econometrics. WS 23974, Universidad Carlos III de Madrid. Departamento de Estadística.
    15. Ashoka Mody & Milan Nedeljkovic, 2018. "Central Bank Policies and Financial Markets: Lessons from the Euro Crisis," Working Papers 253, Princeton University, Department of Economics, Center for Economic Policy Studies..
    16. Herrala, Risto & Orlandi, Fabrice, 2020. "Win-win? Assessing the global impact of the Chinese economy," BOFIT Discussion Papers 4/2020, Bank of Finland Institute for Emerging Economies (BOFIT).
    17. Yohei Yamamoto & Naoko Hara, 2022. "Identifying factor‐augmented vector autoregression models via changes in shock variances," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 722-745, June.
    18. Franz Ramsauer & Aleksey Min & Michael Lingauer, 2019. "Estimation of FAVAR Models for Incomplete Data with a Kalman Filter for Factors with Observable Components," Econometrics, MDPI, vol. 7(3), pages 1-43, July.
    19. Krampe, J. & Paparoditis, E. & Trenkler, C., 2023. "Structural inference in sparse high-dimensional vector autoregressions," Journal of Econometrics, Elsevier, vol. 234(1), pages 276-300.
    20. 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.
    21. Jiahe Lin & George Michailidis, 2019. "Regularized Estimation of High-dimensional Factor-Augmented Vector Autoregressive (FAVAR) Models," Papers 1912.04146, arXiv.org, revised May 2020.
    22. Zongwu Cai & Xiyuan Liu, 2021. "Solving the Price Puzzle Via A Functional Coefficient Factor-Augmented VAR Model," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202106, University of Kansas, Department of Economics, revised Jan 2021.
    23. Dominik Bertsche, 2019. "The effects of oil supply shocks on the macroeconomy: a Proxy-FAVAR approachThe effects of oil supply shocks on the macroeconomy: a Proxy-FAVAR approach," Working Paper Series of the Department of Economics, University of Konstanz 2019-06, Department of Economics, University of Konstanz.
    24. Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2023. "Estimation of Grouped Time-Varying Network Vector Autoregression Models," Papers 2303.10117, arXiv.org, revised Mar 2024.
    25. Martin Hodula & Martin Macháček & Aleš Melecký, 2020. "Placing the Czech Shadow Banking Sector under the Light," Prague Economic Papers, Prague University of Economics and Business, vol. 2020(1), pages 3-28.
    26. Maurizio Daniele & Julie Schnaitmann, 2019. "A Regularized Factor-augmented Vector Autoregressive Model," Papers 1912.06049, arXiv.org.
    27. Antoine A. Djogbenou, 2024. "Identifying oil price shocks with global, developed, and emerging latent real economy activity factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 128-149, January.

  13. Bai, Jushan & Ando, Tomohiro, 2013. "Panel data models with grouped factor structure under unknown group membership," MPRA Paper 52782, University Library of Munich, Germany.

    Cited by:

    1. Boyuan Zhang, 2020. "Forecasting with Bayesian Grouped Random Effects in Panel Data," Papers 2007.02435, arXiv.org, revised Oct 2020.
    2. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    3. Tomohiro Ando & Jushan Bai, 2015. "Asset Pricing with a General Multifactor Structure," Journal of Financial Econometrics, Oxford University Press, vol. 13(3), pages 556-604.
    4. Stéphane Bonhomme & Thibaut Lamadon & Elena Manresa, 2017. "Discretizing unobserved heterogeneity," IFS Working Papers W17/03, Institute for Fiscal Studies.
    5. Liqian Cai & Arnab Bhattacharjee & Roger Calantone & Taps Maiti, 2019. "Variable Selection with Spatially Autoregressive Errors: A Generalized Moments LASSO Estimator," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 146-200, September.
    6. Jorge A. Rivero, 2023. "Unobserved Grouped Heteroskedasticity and Fixed Effects," Papers 2310.14068, arXiv.org, revised Oct 2023.
    7. Miao, Ke & Li, Kunpeng & Su, Liangjun, 2020. "Panel threshold models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 219(1), pages 137-170.
    8. Carlos Vladimir Rodríguez-Caballero, 2016. "Panel Data with Cross-Sectional Dependence Characterized by a Multi-Level Factor Structure," CREATES Research Papers 2016-31, Department of Economics and Business Economics, Aarhus University.
    9. Simone Bertoli & Jesús Fernández-Huertas Moraga, 2015. "Visa Policies, Networks and the Cliff at the Border," CERDI Working papers halshs-01099863, HAL.
    10. Yang, Shuquan & Ling, Nengxiang, 2023. "Robust projected principal component analysis for large-dimensional semiparametric factor modeling," Journal of Multivariate Analysis, Elsevier, vol. 195(C).
    11. Camacho, Maximo & Lopez-Buenache, German, 2023. "Factor models for large and incomplete data sets with unknown group structure," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1205-1220.
    12. Vasilis Sarafidis & Tom Wansbeek, 2020. "Celebrating 40 Years of Panel Data Analysis: Past, Present and Future," Monash Econometrics and Business Statistics Working Papers 6/20, Monash University, Department of Econometrics and Business Statistics.
    13. Boyuan Zhang, 2022. "Incorporating Prior Knowledge of Latent Group Structure in Panel Data Models," Papers 2211.16714, arXiv.org, revised Oct 2023.
    14. Liu, Ruiqi & Shang, Zuofeng & Zhang, Yonghui & Zhou, Qiankun, 2020. "Identification and estimation in panel models with overspecified number of groups," Journal of Econometrics, Elsevier, vol. 215(2), pages 574-590.
    15. Pigini, Claudia & Pionati, Alessandro & Valentini, Francesco, 2023. "Specification testing with grouped fixed effects," MPRA Paper 117821, University Library of Munich, Germany.
    16. Liu, Yanbo & Phillips, Peter C. B. & Yu, Jun, 2022. "A Panel Clustering Approach to Analyzing Bubble Behavior," Economics and Statistics Working Papers 1-2022, Singapore Management University, School of Economics.
    17. Huang, Wenxin & Jin, Sainan & Phillips, Peter C.B. & Su, Liangjun, 2020. "Nonstationary Panel Models with Latent Group Structures and Cross-Section Dependence," Economics and Statistics Working Papers 7-2020, Singapore Management University, School of Economics.
    18. Leng, Xuan & Chen, Heng & Wang, Wendun, 2023. "Multi-dimensional latent group structures with heterogeneous distributions," Journal of Econometrics, Elsevier, vol. 233(1), pages 1-21.
    19. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    20. Saptorshee Kanto Chakraborty & Massimiliano Mazzanti, 2021. "Revisiting the literature on the dynamic Environmental Kuznets Curves using a latent structure approach," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(3), pages 923-941, October.
    21. Wang, Wuyi & Su, Liangjun, 2017. "Identifying Latent Group Structures in Nonlinear Panels," Economics and Statistics Working Papers 19-2017, Singapore Management University, School of Economics.
    22. Jiaying Gu & Stanislav Volgushev, 2018. "Panel Data Quantile Regression with Grouped Fixed Effects," Papers 1801.05041, arXiv.org, revised Aug 2018.
    23. Denis Chetverikov & Elena Manresa, 2022. "Spectral and post-spectral estimators for grouped panel data models," Papers 2212.13324, arXiv.org, revised Dec 2022.
    24. Xiang, Jingjie & Li, Li, 2022. "Monetary policy uncertainty, debt financing cost and real economic activities: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 1025-1044.
    25. Amparo Soler-Domínguez & Juan Carlos Matallín-Sáez & Diego Víctor de Mingo-López & Emili Tortosa-Ausina, 2020. "Social responsible mutual funds and lowcarbon economy," Working Papers 2020/15, Economics Department, Universitat Jaume I, Castellón (Spain).
    26. Ando, Tomohiro & Bai, Jushan, 2021. "Large-scale generalized linear longitudinal data models with grouped patterns of unobserved heterogeneity," MPRA Paper 111431, University Library of Munich, Germany.
    27. Yang, Xinfeng & Yan, Xiaodong & Huang, Jian, 2019. "High-dimensional integrative analysis with homogeneity and sparsity recovery," Journal of Multivariate Analysis, Elsevier, vol. 174(C).
    28. Yu Hao & Hiroyuki Kasahara, 2022. "Testing the Number of Components in Finite Mixture Normal Regression Model with Panel Data," Papers 2210.02824, arXiv.org, revised Jun 2023.
    29. Nibbering, D. & Paap, R., 2019. "Panel Forecasting with Asymmetric Grouping," Econometric Institute Research Papers EI-2019-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    30. He, Yong & Kong, Xinbing & Trapani, Lorenzo & Yu, Long, 2023. "One-way or two-way factor model for matrix sequences?," Journal of Econometrics, Elsevier, vol. 235(2), pages 1981-2004.
    31. Mehrabani, Ali, 2023. "Estimation and identification of latent group structures in panel data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1464-1482.
    32. Choi, Sung Hoon & Kim, Donggyu, 2023. "Large volatility matrix analysis using global and national factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1917-1933.
    33. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    34. Ando, Tomohiro & Bai, Jushan, 2018. "Quantile co-movement in financial markets: A panel quantile model with unobserved heterogeneity," MPRA Paper 88765, University Library of Munich, Germany.
    35. Francisco Blasques & Meindert Heres Hoogerkamp & Siem Jan Koopman & Ilka van de Werve, 2020. "Dynamic Factor Models with Clustered Loadings: Forecasting Education Flows using Unemployment Data," Tinbergen Institute Discussion Papers 20-078/III, Tinbergen Institute, revised 21 Jan 2021.
    36. Wanbo Lu & Guanglin Huang & Kris Boudt, 2024. "Estimation of Non-Gaussian Factors Using Higher-order Multi-cumulants in Weak Factor Models," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 24/1085, Ghent University, Faculty of Economics and Business Administration.
    37. Max Cytrynbaum, 2020. "Blocked Clusterwise Regression," Papers 2001.11130, arXiv.org.
    38. Millimet, Daniel L. & Bellemare, Marc, 2023. "Fixed Effects and Causal Inference," IZA Discussion Papers 16202, Institute of Labor Economics (IZA).
    39. Amparo Soler‐Domínguez & Juan Carlos Matallín‐Sáez & Diego Víctor de Mingo‐López & Emili Tortosa‐Ausina, 2021. "Looking for sustainable development: Socially responsible mutual funds and the low‐carbon economy," Business Strategy and the Environment, Wiley Blackwell, vol. 30(4), pages 1751-1766, May.
    40. Zhang, Yingying & Wang, Huixia Judy & Zhu, Zhongyi, 2019. "Quantile-regression-based clustering for panel data," Journal of Econometrics, Elsevier, vol. 213(1), pages 54-67.
    41. Bai, Jushan & Ando, Tomohiro, 2013. "Multifactor asset pricing with a large number of observable risk factors and unobservable common and group-specific factors," MPRA Paper 52785, University Library of Munich, Germany, revised Dec 2013.
    42. Dzemski, Andreas & Okui, Ryo, 2018. "Confidence Set for Group Membership," Working Papers in Economics 727, University of Gothenburg, Department of Economics.
    43. Jiangtao Duan & Wei Gao & Hao Qu & Hon Keung Tony, 2019. "Subspace Clustering for Panel Data with Interactive Effects," Papers 1909.09928, arXiv.org, revised Feb 2021.
    44. Lumsdaine, Robin L. & Okui, Ryo & Wang, Wendun, 2023. "Estimation of panel group structure models with structural breaks in group memberships and coefficients," Journal of Econometrics, Elsevier, vol. 233(1), pages 45-65.
    45. Rodríguez-Caballero, Carlos Vladimir, 2022. "Energy consumption and GDP: a panel data analysis with multi-level cross-sectional dependence," Econometrics and Statistics, Elsevier, vol. 23(C), pages 128-146.
    46. Su, Liangjun & Wang, Wuyi & Xu, Xingbai, 2023. "Identifying latent group structures in spatial dynamic panels," Journal of Econometrics, Elsevier, vol. 235(2), pages 1955-1980.
    47. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    48. Fernandez, Julian, 2020. "Exchange Rate Uncertainty and the Interest Rate Parity," MPRA Paper 116010, University Library of Munich, Germany, revised 2022.
    49. Babii, Andrii & Chen, Xi & Ghysels, Eric, 2019. "Commercial and Residential Mortgage Defaults: Spatial Dependence with Frailty," Journal of Econometrics, Elsevier, vol. 212(1), pages 47-77.
    50. Carlomagno Real, Guillermo & Espasa, Antoni, 2017. "Discovering pervasive and non-pervasive common cycles," DES - Working Papers. Statistics and Econometrics. WS 25392, Universidad Carlos III de Madrid. Departamento de Estadística.
    51. Chu, Ba, 2017. "Composite Quasi-Maximum Likelihood Estimation of Dynamic Panels with Group-Specific Heterogeneity and Spatially Dependent Errors," MPRA Paper 79709, University Library of Munich, Germany.
    52. Gu, Jiaying & Volgushev, Stanislav, 2019. "Panel data quantile regression with grouped fixed effects," Journal of Econometrics, Elsevier, vol. 213(1), pages 68-91.
    53. Guðmundsson, Guðmundur Stefán & Brownlees, Christian, 2021. "Detecting groups in large vector autoregressions," Journal of Econometrics, Elsevier, vol. 225(1), pages 2-26.
    54. Andreas Dzemski & Ryo Okui, 2017. "Confidence set for group membership," Papers 1801.00332, arXiv.org, revised Nov 2023.
    55. Matthew Harding & Carlos Lamarche & Chris Muris, 2022. "Estimation of a Factor-Augmented Linear Model with Applications Using Student Achievement Data," Papers 2203.03051, arXiv.org.
    56. Camacho, Maximo & Caro, Angela & Peña, Daniel, 2023. "What drives industrial energy prices?," Economic Modelling, Elsevier, vol. 120(C).

  14. Bai, Jushan & Ando, Tomohiro, 2013. "Multifactor asset pricing with a large number of observable risk factors and unobservable common and group-specific factors," MPRA Paper 52785, University Library of Munich, Germany, revised Dec 2013.

    Cited by:

    1. Bai, Jushan & Ando, Tomohiro, 2013. "Panel data models with grouped factor structure under unknown group membership," MPRA Paper 52782, University Library of Munich, Germany.

  15. Bai, Jushan & Li, Kunpeng, 2013. "Spatial panel data models with common shocks," MPRA Paper 52786, University Library of Munich, Germany, revised 09 Mar 2014.

    Cited by:

    1. Mackenbach, Johan P. & McKee, Martin, 2015. "Government, politics and health policy: A quantitative analysis of 30 European countries," Health Policy, Elsevier, vol. 119(10), pages 1298-1308.
    2. 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.
    3. Li, Yue & Wang, Mingshu & Zhao, Qunshan, 2023. "Understanding Urban Traffic Flows in Response to COVID-19 Pandemic with Emerging Urban Big Data in Glasgow," OSF Preprints kwbdz, Center for Open Science.
    4. Cynthia Fan Yang, 2021. "Common factors and spatial dependence: an application to US house prices," Econometric Reviews, Taylor & Francis Journals, vol. 40(1), pages 14-50, January.
    5. Camilla Mastromarco & Laura Serlenga & Yongcheol Shin, 2023. "Regional Productivity Network in the EU," CESifo Working Paper Series 10404, CESifo.
    6. Bai, Jushan & Li, Kunpeng, 2021. "Dynamic spatial panel data models with common shocks," Journal of Econometrics, Elsevier, vol. 224(1), pages 134-160.
    7. Georg Keilbar & Juan M. Rodriguez-Poo & Alexandra Soberon & Weining Wang, 2022. "A semiparametric approach for interactive fixed effects panel data models," Papers 2201.11482, arXiv.org, revised Mar 2023.
    8. Chen, Jia & Shin, Yongcheol & Zheng, Chaowen, 2022. "Estimation and inference in heterogeneous spatial panels with a multifactor error structure," Journal of Econometrics, Elsevier, vol. 229(1), pages 55-79.
    9. Lina Lu, 2017. "Simultaneous Spatial Panel Data Models with Common Shocks," Supervisory Research and Analysis Working Papers RPA 17-3, Federal Reserve Bank of Boston.

  16. Bai, Jushan, 2013. "Likelihood approach to dynamic panel models with interactive effects," MPRA Paper 50267, University Library of Munich, Germany.

    Cited by:

    1. Juodis, Arturas & Sarafidis, Vasilis, 2014. "Fixed T Dynamic Panel Data Estimators with Multi-Factor Errors," MPRA Paper 57659, University Library of Munich, Germany.
    2. Juodis, Arturas & Sarafidis, Vasilis, 2015. "A Simple Estimator for Short Panels with Common Factors," MPRA Paper 68164, University Library of Munich, Germany.
    3. Kazuhiko Hayakawa & M. Hashem Pesaran & L. Vanessa Smith, 2023. "Short T dynamic panel data models with individual, time and interactive effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 940-967, September.
    4. Yan Sun & Wei Huang, 2022. "Quasi-maximum likelihood estimation of short panel data models with time-varying individual effects," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(1), pages 93-114, January.
    5. Hyungsik Roger Moon & Martin Weidner, 2015. "Linear Regression for Panel With Unknown Number of Factors as Interactive Fixed Effects," Econometrica, Econometric Society, vol. 83(4), pages 1543-1579, July.
    6. Juodis, Arturas & Sarafidis, Vasilis, 2020. "An Incidental Parameters Free Inference Approach for Panels with Common Shocks," MPRA Paper 104906, University Library of Munich, Germany.
    7. Donald Robertson & Vasilis Sarafidis, 2013. "IV Estimation of Panels with Factor Residuals," Cambridge Working Papers in Economics 1321, Faculty of Economics, University of Cambridge.
    8. Kazuhiko Hayakawa & M. Hashem Pesaran & L. Vanessa Smith, 2014. "Transformed Maximum Likelihood Estimation of Short Dynamic Panel Data Models with Interactive Effects," CESifo Working Paper Series 4822, CESifo.
    9. Guido M. Kuersteiner & Ingmar R. Prucha, 2020. "Dynamic Spatial Panel Models: Networks, Common Shocks, and Sequential Exogeneity," Econometrica, Econometric Society, vol. 88(5), pages 2109-2146, September.
    10. Westerlund, Joakim & Norkute, Milda, 2014. "A Factor Analytical Method to Interactive Effects Dynamic Panel Models with or without Unit Root," Working Papers 2014:12, Lund University, Department of Economics.
    11. Maria Elena Bontempi & Jan Ditzen, 2023. "GMM-lev estimation and individual heterogeneity: Monte Carlo evidence and empirical applications," Papers 2312.00399, arXiv.org, revised Dec 2023.
    12. Ignace De Vos & Gerdie Everaert, 2016. "Bias-Corrected Common Correlated Effects Pooled Estimation In Homogeneous Dynamic Panels," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 16/920, Ghent University, Faculty of Economics and Business Administration.
    13. Jushan Bai, 2023. "Efficiency of QMLE for dynamic panel data models with interactive effects," Papers 2312.07881, arXiv.org, revised Apr 2024.

  17. Bai, Jushan & Li, Kunpeng, 2012. "Maximum likelihood estimation and inference for approximate factor models of high dimension," MPRA Paper 42099, University Library of Munich, Germany, revised 19 Oct 2012.

    Cited by:

    1. Miranda Gualdrón, Karen Alejandra & Poncela, Pilar & Ruiz Ortega, Esther, 2021. "Dynamic factor models: does the specification matter?," DES - Working Papers. Statistics and Econometrics. WS 32210, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Filipiak, Katarzyna & Klein, Daniel, 2017. "Estimation of parameters under a generalized growth curve model," Journal of Multivariate Analysis, Elsevier, vol. 158(C), pages 73-86.
    3. Franco Peracchi & Claudio Rossetti, 2019. "A Nonlinear Dynamic Factor Model of Health and Medical Treatment," CSEF Working Papers 524, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    4. Matteo Barigozzi & Daniele Massacci, 2022. "Modelling Large Dimensional Datasets with Markov Switching Factor Models," Papers 2210.09828, arXiv.org, revised Dec 2023.
    5. Urga, Giovanni & Wang, Fa, 2022. "Estimation and Inference for High Dimensional Factor Model with Regime Switching," MPRA Paper 117012, University Library of Munich, Germany, revised 10 Apr 2023.
    6. Alonso, Andrés M. & Galeano, Pedro & Peña, Daniel, 2020. "A robust procedure to build dynamic factor models with cluster structure," Journal of Econometrics, Elsevier, vol. 216(1), pages 35-52.
    7. Hörmann, Siegfried & Jammoul, Fatima, 2022. "Consistently recovering the signal from noisy functional data," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    8. Christian Brownlees & Geert Mesters, 2017. "Detecting Granular Time Series in Large Panels," Working Papers 991, Barcelona School of Economics.
    9. Gabriele Fiorentini & Enrique Sentana, 2013. "Dynamic Specification Tests for Dynamic Factor Models," Working Papers wp2013_1306, CEMFI.
    10. Martin Solberger & Erik Spånberg, 2020. "Estimating a Dynamic Factor Model in EViews Using the Kalman Filter and Smoother," Computational Economics, Springer;Society for Computational Economics, vol. 55(3), pages 875-900, March.
    11. Matteo Luciani, 2020. "Common and Idiosyncratic Inflation," FEDS Notes 2020-03-05, Board of Governors of the Federal Reserve System (U.S.).
    12. Monika Bours & Ansgar Steland, 2021. "Large‐sample approximations and change testing for high‐dimensional covariance matrices of multivariate linear time series and factor models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(2), pages 610-654, June.
    13. Matteo Barigozzi, 2022. "On Estimation and Inference of Large Approximate Dynamic Factor Models via the Principal Component Analysis," Papers 2211.01921, arXiv.org, revised Jul 2023.
    14. Helmut Lütkepohl, 2014. "Structural Vector Autoregressive Analysis in a Data Rich Environment: A Survey," SFB 649 Discussion Papers SFB649DP2014-004, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    15. Fresoli, Diego & Poncela, Pilar & Ruiz, Esther, 2023. "Ignoring cross-correlated idiosyncratic components when extracting factors in dynamic factor models," Economics Letters, Elsevier, vol. 230(C).
    16. Urga, Giovanni & Wang, Fa, 2022. "Estimation and inference for high dimensional factor model with regime switching," MPRA Paper 113172, University Library of Munich, Germany.
    17. Fresoli, Diego Eduardo & Poncela Blanco, Maria Pilar & Ruiz Ortega, Esther, 2022. "Ignoring cross-correlated idiosyncratic components when extracting factors in dynamic factor models," DES - Working Papers. Statistics and Econometrics. WS 36251, Universidad Carlos III de Madrid. Departamento de Estadística.
    18. Shaoxin Wang & Hu Yang & Chaoli Yao, 2019. "On the penalized maximum likelihood estimation of high-dimensional approximate factor model," Computational Statistics, Springer, vol. 34(2), pages 819-846, June.
    19. Luke Hartigan & Michelle Wright, 2021. "Financial Conditions and Downside Risk to Economic Activity in Australia," RBA Research Discussion Papers rdp2021-03, Reserve Bank of Australia.
    20. Joakim Westerlund, 2020. "A cross‐section average‐based principal components approach for fixed‐T panels," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 776-785, September.
    21. Karen Miranda & Pilar Poncela & Esther Ruiz, 2022. "Dynamic factor models: Does the specification matter?," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(1), pages 397-428, May.
    22. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," PSE Working Papers halshs-02262202, HAL.
    23. Linton, O. B. & Tang, H. & Wu, J., 2022. "A Structural Dynamic Factor Model for Daily Global Stock Market Returns," Cambridge Working Papers in Economics 2237, Faculty of Economics, University of Cambridge.
    24. Li, Kunpeng & Li, Qi & Lu, Lina, 2016. "Quasi Maximum Likelihood Analysis of High Dimensional Constrained Factor Models," MPRA Paper 75676, University Library of Munich, Germany.
    25. Matteo Barigozzi, 2023. "Asymptotic equivalence of Principal Components and Quasi Maximum Likelihood estimators in Large Approximate Factor Models," Papers 2307.09864, arXiv.org, revised Sep 2023.
    26. 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.
    27. Wang, Fa, 2017. "Maximum likelihood estimation and inference for high dimensional nonlinear factor models with application to factor-augmented regressions," MPRA Paper 93484, University Library of Munich, Germany, revised 19 May 2019.
    28. Bai, Jushan & Li, Kunpeng & Lu, Lina, 2014. "Estimation and inference of FAVAR models," MPRA Paper 60960, University Library of Munich, Germany.
    29. Alain-Philippe Fortin & Patrick Gagliardini & Olivier Scaillet, 2023. "Latent Factor Analysis in Short Panels," Papers 2306.14004, arXiv.org.
    30. Li, Kunpeng & Lu, Lina, 2014. "Efficient estimation of heterogeneous coefficients in panel data models with common shock," MPRA Paper 59312, University Library of Munich, Germany.
    31. 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.
    32. Yi‐Chiuan Wang & Jyh‐Lin Wu, 2015. "Fundamentals and Exchange Rate Prediction Revisited," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(8), pages 1651-1671, December.
    33. 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.
    34. Matteo Barigozzi, 2023. "Quasi Maximum Likelihood Estimation of High-Dimensional Factor Models: A Critical Review," Papers 2303.11777, arXiv.org, revised Dec 2023.
    35. Peña, Daniel & Smucler, Ezequiel & Yohai, Victor J., 2021. "Sparse estimation of dynamic principal components for forecasting high-dimensional time series," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1498-1508.
    36. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers halshs-02262202, HAL.
    37. Wang, Fa, 2022. "Maximum likelihood estimation and inference for high dimensional generalized factor models with application to factor-augmented regressions," Journal of Econometrics, Elsevier, vol. 229(1), pages 180-200.
    38. Linton, O. B. & Tang, H. & Wu, J., 2022. "A Structural Dynamic Factor Model for Daily Global Stock Market Returns," Janeway Institute Working Papers camjip:2214, Faculty of Economics, University of Cambridge.
    39. Lucchetti, Riccardo & Venetis, Ioannis A., 2020. "A replication of "A quasi-maximum likelihood approach for large, approximate dynamic factor models" (Review of Economics and Statistics, 2012)," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 14, pages 1-14.
    40. 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.
    41. Mikkelsen, Jakob Guldbæk & Hillebrand, Eric & Urga, Giovanni, 2019. "Consistent estimation of time-varying loadings in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 208(2), pages 535-562.
    42. Luke Hartigan & Michelle Wright, 2023. "Monitoring Financial Conditions and Downside Risk to Economic Activity in Australia," The Economic Record, The Economic Society of Australia, vol. 99(325), pages 253-287, June.
    43. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.
    44. Riccardo (Jack) Lucchetti & Ioannis A. Venetis, 2019. "Dynamic Factor Models in gretl. The DFM package," gretl working papers 7, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    45. Matteo Barigozzi & Matteo Luciani, 2019. "Quasi Maximum Likelihood Estimation and Inference of Large Approximate Dynamic Factor Models via the EM algorithm," Papers 1910.03821, arXiv.org, revised Feb 2022.
    46. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
    47. Serena Ng & Susannah Scanlan, 2023. "Constructing High Frequency Economic Indicators by Imputation," Papers 2303.01863, arXiv.org, revised Oct 2023.
    48. Giorgio Calzolari & Roxana Halbleib & Christian Mucher, 2023. "Sequential Estimation of Multivariate Factor Stochastic Volatility Models," Papers 2302.07052, arXiv.org.
    49. Ma, Chenchen & Tu, Yundong, 2023. "Group fused Lasso for large factor models with multiple structural breaks," Journal of Econometrics, Elsevier, vol. 233(1), pages 132-154.
    50. Li, Kunpeng, 2017. "Fixed-effects dynamic spatial panel data models and impulse response analysis," Journal of Econometrics, Elsevier, vol. 198(1), pages 102-121.
    51. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers 2019-4, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.

  18. Bai, Jushan & Wang, Peng, 2012. "Identification and estimation of dynamic factor models," MPRA Paper 38434, University Library of Munich, Germany.

    Cited by:

    1. David Backus & Mikhail Chernov & Stanley E. Zin, 2013. "Identifying Taylor Rules in Macro-Finance Models," NBER Working Papers 19360, National Bureau of Economic Research, Inc.
    2. Junwei Ma & Jianhua Wang & Philip Szmedra, 2019. "Economic Efficiency and Its Influencing Factors on Urban Agglomeration—An Analysis Based on China’s Top 10 Urban Agglomerations," Sustainability, MDPI, vol. 11(19), pages 1-19, September.
    3. Bjørnland, Hilde C. & Ravazzolo, Francesco & Thorsrud, Leif Anders, 2017. "Forecasting GDP with global components: This time is different," International Journal of Forecasting, Elsevier, vol. 33(1), pages 153-173.
    4. Aleksandra Halka & Grzegorz Szafranski, 2018. "What Common Factors are Driving Inflation in CEE Countries?," Prague Economic Papers, Prague University of Economics and Business, vol. 2018(2), pages 131-148.
    5. Backus, David & Zin, Stanley E. & Chernov, Mikhail & Zviadadze, Irina, 2013. "Monetary policy risk: Rules vs. discretion," CEPR Discussion Papers 9611, C.E.P.R. Discussion Papers.
    6. Chan, Joshua C.C. & Eisenstat, Eric & Koop, Gary, 2014. "Large Bayesian VARMAs," SIRE Discussion Papers 2015-06, Scottish Institute for Research in Economics (SIRE).
    7. Hilde C. Bj�rnland & Leif Anders Thorsrud, 2015. "Commodity prices and fiscal policy design: Procyclical despite a rule," Working Papers No 5/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    8. Hilde C. Bj�rnland & Leif Anders Thorsrud, 2014. "Boom or gloom? Examining the Dutch disease in two-speed economies," Working Papers No 6/2014, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    9. Jorge M. Uribe & Helena Chuliá & Montserrat Guillen, 2018. "Trends in the Quantiles of the Life Table Survivorship Function," European Journal of Population, Springer;European Association for Population Studies, vol. 34(5), pages 793-817, December.
    10. Aßmann, Christian & Boysen-Hogrefe, Jens & Pape, Markus, 2016. "Bayesian analysis of static and dynamic factor models: An ex-post approach towards the rotation problem," Journal of Econometrics, Elsevier, vol. 192(1), pages 190-206.
    11. Aßmann, Christian & Boysen-Hogrefe, Jens & Pape, Markus, 2014. "Bayesian analysis of dynamic factor models: An ex-post approach towards the rotation problem," Kiel Working Papers 1902, Kiel Institute for the World Economy (IfW Kiel).
    12. Bastian Gribisch, 2018. "A latent dynamic factor approach to forecasting multivariate stock market volatility," Empirical Economics, Springer, vol. 55(2), pages 621-651, September.
    13. Lauren Stagnol, 2019. "Extracting global factors from local yield curves," Journal of Asset Management, Palgrave Macmillan, vol. 20(5), pages 341-350, September.
    14. Leif Anders Thorsrud, 2016. "Words are the new numbers: A newsy coincident index of business cycles," Working Papers No 4/2016, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    15. Christian Menden & Christian R. Proaño, 2017. "Dissecting the financial cycle with dynamic factor models," Quantitative Finance, Taylor & Francis Journals, vol. 17(12), pages 1965-1994, December.
    16. Chuliá, Helena & Guillén, Montserrat & Uribe, Jorge M., 2017. "Measuring uncertainty in the stock market," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 18-33.
    17. Blanco, Emilio & Elosegui, Pedro & Izaguirre, Alejandro & Montes-Rojas, Gabriel, 2019. "Regional and state heterogeneity of monetary shocks in Argentina," The Journal of Economic Asymmetries, Elsevier, vol. 20(C).
    18. Helena Chuliá & Montserrat Guillén & Jorge M. Uribe, 2015. "Mortality and Longevity Risks in the United Kingdom: Dynamic Factor Models and Copula-Functions," Working Papers 2015-03, Universitat de Barcelona, UB Riskcenter.
    19. Petrella, Ivan & Drechsel, Thomas & Antolin-Diaz, Juan, 2014. "Following the Trend: Tracking GDP when Long-Run Growth is Uncertain," CEPR Discussion Papers 10272, C.E.P.R. Discussion Papers.
    20. Sungyup Chung & Geoffrey J.D. Hewings, 2015. "Competitive and Complementary Relationship between Regional Economies: A Study of the Great Lake States," Spatial Economic Analysis, Taylor & Francis Journals, vol. 10(2), pages 205-229, June.

  19. Chen, Haiqiang & Chong, Terence Tai Leung & Bai, Jushan, 2012. "Theory and Applications of TAR Model with Two Threshold Variables," MPRA Paper 54527, University Library of Munich, Germany.

    Cited by:

    1. Donayre, Luiggi & Panovska, Irina, 2018. "U.S. wage growth and nonlinearities: The roles of inflation and unemployment," Economic Modelling, Elsevier, vol. 68(C), pages 273-292.
    2. Chen, Haiqiang & Li, Yingxing & Lin, Ming & Zhu, Yanli, 2018. "A Regime Shift Model with Nonparametric Switching Mechanism," IRTG 1792 Discussion Papers 2018-020, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Terence T.L. Chong & Isabel K. Yan, 2018. "Forecasting currency crises with threshold models," International Economics, CEPII research center, issue 156, pages 156-174.
    4. Stefan Avdjiev & Zheng Zeng, 2014. "Credit Growth, Monetary Policy, and Economic Activity in a Three-Regime TVAR Model," BIS Working Papers 449, Bank for International Settlements.
    5. Myung Hwan Seo & Yongcheol Shin, 2014. "Dynamic Panels with Threshold Effect and Endogeneity," STICERD - Econometrics Paper Series 577, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    6. Alogoskoufis, George & Malliaris, A.G. & Stengos, Thanasis, 2023. "The scope and methodology of economic and financial asymmetries," The Journal of Economic Asymmetries, Elsevier, vol. 27(C).
    7. Chong, Terence Tai Leung & Chen, Haiqiang & Wong, Tsz Nga & Yan, Isabel K., 2015. "Estimation and Inference of Threshold Regression Models with Measurement Errors," MPRA Paper 68457, University Library of Munich, Germany.
    8. Xiaobing Zheng & Kun Liang & Qiang Xia & Dabin Zhang, 2022. "Best Subset Selection for Double-Threshold-Variable Autoregressive Moving-Average Models: The Bayesian Approach," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1175-1201, March.
    9. Chen, Haiqiang & Chong, Terence Tai Leung & She, Yingni, 2013. "A Principal Component Approach to Measuring Investor Sentiment in China," MPRA Paper 54150, University Library of Munich, Germany.
    10. Klingelhöfer, Jan & Sun, Rongrong, 2018. "China's regime-switching monetary policy," Economic Modelling, Elsevier, vol. 68(C), pages 32-40.
    11. Chong, Terence Tai Leung & Yan, Isabel K., 2014. "Estimating and Testing Threshold Regression Models with Multiple Threshold Variables," MPRA Paper 54732, University Library of Munich, Germany.
    12. Chong, Terence Tai-Leung & Lam, Tau-Hing & Yan, Isabel Kit-Ming, 2012. "Is the Chinese stock market really inefficient?," China Economic Review, Elsevier, vol. 23(1), pages 122-137.
    13. Monica Dudian & Mihaela Mosora & Cosmin Mosora & Stefanija Birova, 2017. "Oil Price and Economic Resilience. Romania’s Case," Sustainability, MDPI, vol. 9(2), pages 1-8, February.
    14. Jean-Marc Le Caillec, 2021. "Threshold autoregressive model blind identification based on array clustering," Post-Print hal-03210735, HAL.
    15. Ni Shuxia & Xia Qiang & Liu Jinshan, 2018. "Bayesian Subset Selection for Two-Threshold Variable Autoregressive Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(4), pages 1-16, September.
    16. Eugene Msizi Buthelezi & Phocenah Nyatanga, 2023. "Threshold of the CAPB That Can Be Attributed to Fiscal Consolidation Episodes in South Africa," Economies, MDPI, vol. 11(6), pages 1-26, May.
    17. Apergis, Nicholas & Eleftheriou, Sofia, 2016. "Gold returns: Do business cycle asymmetries matter? Evidence from an international country sample," Economic Modelling, Elsevier, vol. 57(C), pages 164-170.
    18. Ma, Tao & Zhou, Zhou & Abdulhai, Baher, 2015. "Nonlinear multivariate time–space threshold vector error correction model for short term traffic state prediction," Transportation Research Part B: Methodological, Elsevier, vol. 76(C), pages 27-47.
    19. Arturo Lamadrid-Contreras & N.R. Ramírez-Rondán, 2018. "Panel Models with Two Threshold Variables: The Case of Financial Constraints," Working Papers 128, Peruvian Economic Association.
    20. Mo Zhou & Liang Peng & Rongmao Zhang, 2021. "Empirical likelihood test for the application of swqmele in fitting an arma‐garch model," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(2), pages 222-239, March.

  20. Bai, Jushan & Liao, Yuan, 2012. "Efficient Estimation of Approximate Factor Models," MPRA Paper 41558, University Library of Munich, Germany.

    Cited by:

    1. 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.
    2. Matteo Barigozzi & Christian T. Brownlees, 2013. "Nets: Network estimation for time series," Economics Working Papers 1391, Department of Economics and Business, Universitat Pompeu Fabra.
    3. Fan, Jianqing & Han, Fang & Liu, Han & Vickers, Byron, 2016. "Robust inference of risks of large portfolios," Journal of Econometrics, Elsevier, vol. 194(2), pages 298-308.
    4. Gillen, Benjamin J., 2014. "An empirical Bayesian approach to stein-optimal covariance matrix estimation," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 402-420.
    5. Xu Cheng & Zhipeng Liao & Frank Schorfheide, 2016. "Shrinkage Estimation of High-Dimensional Factor Models with Structural Instabilities," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 83(4), pages 1511-1543.

  21. Bai, Jushan & Wang, Peng, 2011. "Conditional Markov chain and its application in economic time series analysis," MPRA Paper 33369, University Library of Munich, Germany.

    Cited by:

    1. Stéphane Goutte & Benteng Zou, 2012. "Continuous time regime switching model applied to foreign exchange rate," Working Papers hal-00643900, HAL.
    2. Catherine Doz & Laurent Ferrara & Pierre-Alain Pionnier, 2020. "Business cycle dynamics after the Great Recession: An extended Markov-Switching Dynamic Factor Model," OECD Statistics Working Papers 2020/01, OECD Publishing.
    3. Malika Hamadi & Andreas Heinen, 2011. "Ownership Structure and Firm Performance : Evidence from a non-parametric panel," DEM Discussion Paper Series 11-16, Department of Economics at the University of Luxembourg.
    4. Chang, Kuang-Liang, 2016. "Does the return-state-varying relationship between risk and return matter in modeling the time series process of stock return?," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 72-87.
    5. Chevallier, Julien, 2011. "A model of carbon price interactions with macroeconomic and energy dynamics," Energy Economics, Elsevier, vol. 33(6), pages 1295-1312.
    6. Danilo Leiva-Leon, 2014. "A New Approach to Infer Changes in the Synchronization of Business Cycle Phases," Staff Working Papers 14-38, Bank of Canada.
    7. Troy Davig, 2008. "Detecting recessions in the Great Moderation: a real-time analysis," Economic Review, Federal Reserve Bank of Kansas City, vol. 93(Q IV), pages 5-33.
    8. Raphael Homayoun Boroumand & Stéphane Goutte & Simon Porcher & Thomas Porcher, 2015. "A Conditional Markov Regime Switching Model To Study Margins: Application To The French Fuel Retail Markets," Post-Print hal-02148309, HAL.
    9. Goutte, Stéphane, 2014. "Conditional Markov regime switching model applied to economic modelling," Economic Modelling, Elsevier, vol. 38(C), pages 258-269.
    10. Shu-Ping Shi, 2013. "Specification sensitivities in the Markov-switching unit root test for bubbles," Empirical Economics, Springer, vol. 45(2), pages 697-713, October.
    11. Danilo Leiva-Leon, 2017. "Measuring business cycles intra-synchronization in us: a regime-switching interdependence framework," Working Papers 1726, Banco de España.
    12. Sylvia Kaufmann, 2016. "Hidden Markov models in time series, with applications in economics," Working Papers 16.06, Swiss National Bank, Study Center Gerzensee.
    13. Gilbert Mbara, 2017. "Business Cycle Dating after the Great Moderation: A Consistent Two – Stage Maximum Likelihood Method," Working Papers 2017-13, Faculty of Economic Sciences, University of Warsaw.
    14. Chevallier, Julien, 2011. "Evaluating the carbon-macroeconomy relationship: Evidence from threshold vector error-correction and Markov-switching VAR models," Economic Modelling, Elsevier, vol. 28(6), pages 2634-2656.

  22. Bai, Jushan & Li, Kunpeng, 2010. "Theory and methods of panel data models with interactive effects," MPRA Paper 43441, University Library of Munich, Germany, revised Dec 2012.

    Cited by:

    1. Jia Chen, 2019. "Estimating latent group structure in time-varying coefficient panel data models," The Econometrics Journal, Royal Economic Society, vol. 22(3), pages 223-240.
    2. Xuan, Liang & Jiti, Gao & xiaodong, Gong, 2021. "Semiparametric Spatial Autoregressive Panel Data Model with Fixed Effects and Time-Varying Coefficients," MPRA Paper 108497, University Library of Munich, Germany, revised 30 May 2021.
    3. Degui Li & Junhui Qian & Liangjun Su, 2016. "Panel Data Models With Interactive Fixed Effects and Multiple Structural Breaks," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1804-1819, October.
    4. Li, Kathleen T. & Bell, David R., 2017. "Estimation of average treatment effects with panel data: Asymptotic theory and implementation," Journal of Econometrics, Elsevier, vol. 197(1), pages 65-75.
    5. Arteaga-Molina, Luis A. & Rodríguez-Poo, Juan M., 2019. "Empirical likelihood based inference for a categorical varying-coefficient panel data model with fixed effects," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 110-124.
    6. Archer Gong Zhang & Jiahua Chen, 2023. "Optimal Estimation under a Semiparametric Density Ratio Model," Papers 2309.09103, arXiv.org.

  23. Bai, Jushan & Carrion-i-Silvestre, Josep Lluis, 2009. "Testing Panel Cointegration with Unobservable Dynamic Common Factors," MPRA Paper 35243, University Library of Munich, Germany.

    Cited by:

    1. Fakhri J. Hasanov & Zeeshan Khan & Muzzammil Hussain & Muhammad Tufail, 2021. "Theoretical Framework for the Carbon Emissions Effects of Technological Progress and Renewable Energy Consumption," Sustainable Development, John Wiley & Sons, Ltd., vol. 29(5), pages 810-822, September.

  24. Jushan Bai & Chihwa Kao & Serena Ng, 2007. "Panel Cointegration with Global Stochastic Trends," Center for Policy Research Working Papers 90, Center for Policy Research, Maxwell School, Syracuse University.

    Cited by:

    1. Eberhardt, Markus & Helmers, Christian & Strauss, Hubert, 2010. "Do spillovers matter when estimating private returns to R&D?," Economic and Financial Reports 2010/1, European Investment Bank, Economics Department.
    2. Igor Masten & Massimiliano Marcellino & Anindya Banerjeey, 2009. "Forecasting with Factor-augmented Error Correction Models," RSCAS Working Papers 2009/32, European University Institute.
    3. Matteo Barigozzi & Lorenzo Trapani, 2018. "Determining the dimension of factor structures in non-stationary large datasets," Papers 1806.03647, arXiv.org.
    4. Banerjee, Anindya & Marcellino, Massimiliano & Masten, Igor, 2014. "Structural FECM: Cointegration in large-scale structural FAVAR models," CEPR Discussion Papers 9858, C.E.P.R. Discussion Papers.
    5. BODART, Vincent & CANDELON, Bertrand & CARPANTIER, Jean - François, 2011. "Real exchanges rates in commodity producing countries : A reappraisal," LIDAM Discussion Papers CORE 2011006, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Byrne, Joseph P. & Fiess, Norbert & MacDonald, Ronald, 2011. "The global dimension to fiscal sustainability," Journal of Macroeconomics, Elsevier, vol. 33(2), pages 137-150, June.
    7. Bashir, Muhammad Adnan & Dengfeng, Zhao & Amin, Fouzia & Mentel, Grzegorz & Raza, Syed Ali & Bashir, Muhammad Farhan, 2023. "Transition to greener electricity and resource use impact on environmental quality: Policy based study from OECD countries," Utilities Policy, Elsevier, vol. 81(C).
    8. Rafaty, R. & Dolphin, G. & Pretis, F., 2020. "Carbon pricing and the elasticity of CO2 emissions," Cambridge Working Papers in Economics 20116, Faculty of Economics, University of Cambridge.
    9. Gerdie Everaert & Tom De Groote, 2016. "Common Correlated Effects Estimation of Dynamic Panels with Cross-Sectional Dependence," Econometric Reviews, Taylor & Francis Journals, vol. 35(3), pages 428-463, March.
    10. Carl S. Bonham & Peter Fuleky & Qianxue Zhao, 2013. "Estimating Demand Elasticities in Non-Stationary Panels: The Case of Hawaii's Tourism Industry," Working Papers 201303, University of Hawaii at Manoa, Department of Economics.
    11. Syed Abul Basher & Stefano Fachin, 2014. "Investigating long-run demand for broad money in the Gulf Arab countries," Middle East Development Journal, Taylor & Francis Journals, vol. 6(2), pages 199-214, July.
    12. Kassouri, Yacouba & Alola, Andrew Adewale & Savaş, Savaş, 2021. "The dynamics of material consumption in phases of the economic cycle for selected emerging countries," Resources Policy, Elsevier, vol. 70(C).
    13. George Kapetanios & M. Hashem Pesaran & Takashi Yamagata, 2006. "Panels with Nonstationary Multifactor Error Structures," Working Papers 569, Queen Mary University of London, School of Economics and Finance.
    14. Selien De Schryder and Gert Peersman, 2015. "The U.S. Dollar Exchange Rate and the Demand for Oil," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    15. Michal Rubaszek & Dobromil Serwa, 2011. "Determinants of credit to households in a life-cycle model," NBP Working Papers 92, Narodowy Bank Polski.
    16. Hashemizadeh, Ali & Bui, Quocviet & Zaidi, Syed Anees Haider, 2022. "A blend of renewable and nonrenewable energy consumption in G-7 countries: The role of disaggregate energy in human development," Energy, Elsevier, vol. 241(C).
    17. Bai, Jushan & Carrion-i-Silvestre, Josep Lluis, 2009. "Testing Panel Cointegration with Unobservable Dynamic Common Factors," MPRA Paper 35243, University Library of Munich, Germany.
    18. Olivier Damette & Mathilde Maurel & Michael A. Stemmer, 2016. "What does it take to grow out of recession? An error-correction approach towards growth convergence of European and transition countries," Documents de travail du Centre d'Economie de la Sorbonne 16041, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    19. Liu, Haiying & Saleem, Muhammad Mansoor & Al-Faryan, Mamdouh Abdulaziz Saleh & Khan, Irfan & Zafar, Muhammad Wasif, 2022. "Impact of governance and globalization on natural resources volatility: The role of financial development in the Middle East North Africa countries," Resources Policy, Elsevier, vol. 78(C).
    20. Dassanayake, Geekiyanage Disela Malinga & Kumar, Amit, 2012. "Techno-economic assessment of triticale straw for power generation," Applied Energy, Elsevier, vol. 98(C), pages 236-245.
    21. Zaidi, Syed Anees Haider & Wei, Zixiang & Gedikli, Ayfer & Zafar, Muhammad Wasif & Hou, Fujun & Iftikhar, Yaser, 2019. "The impact of globalization, natural resources abundance, and human capital on financial development: Evidence from thirty-one OECD countries," Resources Policy, Elsevier, vol. 64(C).
    22. Posso, Alberto & Zhang, Quanda, 2023. "Social R&D: Does academic freedom contribute to improved societal outcomes?," Information Economics and Policy, Elsevier, vol. 63(C).
    23. Don H. Kim & Mico Loretan & Eli M. Remolona, 2009. "Contagion and Risk in the Amplification of Crisis : Evidence from Asian Names in the CDS Market," EABER Working Papers 22861, East Asian Bureau of Economic Research.
    24. Meryem Duygun & Jiaqi Hao & Anders Isaksson & Robin C. Sickles, 2017. "World Productivity Growth: A Model Averaging Approach," Pacific Economic Review, Wiley Blackwell, vol. 22(4), pages 587-619, October.
    25. Ahmad, Mahmood & Ahmed, Zahoor & Khan, Sana Akbar & Alvarado, Rafael, 2023. "Towards environmental sustainability in E−7 countries: Assessing the roles of natural resources, economic growth, country risk, and energy transition," Resources Policy, Elsevier, vol. 82(C).
    26. Rafaty, Ryan & Dolphin, Geoffroy & Pretis, Felix, 2021. "Carbon Pricing and the Elasticity of CO2 Emissions," RFF Working Paper Series 21-33, Resources for the Future.
    27. Chan, Mark K. & Kwok, Simon, 2016. "Policy Evaluation with Interactive Fixed Effects," Working Papers 2016-11, University of Sydney, School of Economics.
    28. Jia Chen & Jiti Gao, 2014. "Semiparametric Model Selection in Panel Data Models with Deterministic Trends and Cross-Sectional Dependence," Monash Econometrics and Business Statistics Working Papers 15/14, Monash University, Department of Econometrics and Business Statistics.
    29. Josep Lluís Carrion-i-Silvestre & Laura Surdeanu, 2016. "Productivity, Infrastructure and Human Capital in the Spanish Regions," Spatial Economic Analysis, Taylor & Francis Journals, vol. 11(4), pages 365-391, October.
    30. Destek, Mehmet Akif & Manga, Muge, 2020. "Technological Innovation, Financialization and Ecological Footprint: Evidence from BEM Economies," MPRA Paper 114151, University Library of Munich, Germany.
    31. Coudert, Virginie & Couharde, Cécile & Mignon, Valérie, 2015. "On the impact of volatility on the real exchange rate – terms of trade nexus: Revisiting commodity currencies," Journal of International Money and Finance, Elsevier, vol. 58(C), pages 110-127.
    32. Mariam Camarero & Estrella Gómez & Cecilio Tamarit, 2012. "The euro impact on trade. Long run evidence with structural breaks," Working Papers 1209, Department of Applied Economics II, Universidad de Valencia.
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    164. Cao, Yanyan & Xiang, Shihui, 2023. "Natural resources volatility and causal associations for BRICS countries: Evidence from Covid-19 data," Resources Policy, Elsevier, vol. 80(C).
    165. Josep Lluís Carrion-I-Silvestre, 2016. "Fiscal Deficit Sustainability of the Spanish Regions," Regional Studies, Taylor & Francis Journals, vol. 50(10), pages 1702-1713, October.
    166. Fang, Zheng & Chen, Yang, 2017. "Human capital and energy in economic growth – Evidence from Chinese provincial data," Energy Economics, Elsevier, vol. 68(C), pages 340-358.
    167. Destek, Mehmet Akif & Manga, Müge & Cengiz, Orhan & Destek, Gamze, 2022. "Investigating the potential of renewable energy in establishing global peace: Fresh evidence from top energy consumer countries," Renewable Energy, Elsevier, vol. 197(C), pages 170-177.
    168. Mirza, Faisal Mehmood & Sinha, Avik & Khan, Javeria Rehman & Kalugina, Olga A. & Zafar, Muhammad Wasif, 2022. "Impact of Energy Efficiency on CO2 Emissions: Empirical Evidence from Developing Countries," MPRA Paper 111923, University Library of Munich, Germany, revised 2022.
    169. Sadiq, Muhammad & Chavali, Kavita & Kumar, V.V. Ajith & Wang, Kuan-Ting & Nguyen, Phong Thanh & Ngo, Thanh Quang, 2023. "Unveiling the relationship between environmental quality, non-renewable energy usage and natural resource rent: Fresh insights from ten asian economies," Resources Policy, Elsevier, vol. 85(PA).
    170. Nguyen Dinh Hoan, 2022. "Nexus among Green Energy Investment, World Oil Price, Monetary Policy and Business Performance: Evidence from Energy Companies on the Vietnamese Stock Exchange," International Journal of Energy Economics and Policy, Econjournals, vol. 12(6), pages 404-411, November.
    171. Destek, Mehmet Akif & Sarkodie, Samuel Asumadu & Asamoah, Ernest Frimpong, 2020. "Does biomass energy drive environmental sustainability? An SDG perspective for top five biomass consuming countries," MPRA Paper 114218, University Library of Munich, Germany, revised 29 Mar 2021.
    172. Wang, Zhaohua & Bui, Quocviet & Zhang, Bin, 2020. "The relationship between biomass energy consumption and human development: Empirical evidence from BRICS countries," Energy, Elsevier, vol. 194(C).
    173. Mariam Camarero & Estrella Gómez & Cecilio Tamarit, 2012. "EMU and intra-European trade. Long-run evidence using gravity equations," ThE Papers 10/25, Department of Economic Theory and Economic History of the University of Granada..
    174. Dai, Jiapeng & Ahmed, Zahoor & Sinha, Avik & Pata, Ugur Korkut & Alvarado, Rafael, 2023. "Sustainable green electricity, technological innovation, and ecological footprint: Does democratic accountability moderate the nexus?," Utilities Policy, Elsevier, vol. 82(C).

  25. Meng, Ginger & Hu, Gang & Bai, Jushan, 2007. "Olive: a simple method for estimating betas when factors are measured with error," MPRA Paper 33183, University Library of Munich, Germany.

    Cited by:

    1. Sebastien Valeyre & Sofiane Aboura & Denis Grebenkov, 2019. "The Reactive Beta Model," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 42(1), pages 71-113, March.
    2. Prono, Todd, 2011. "When A Factor Is Measured with Error: The Role of Conditional Heteroskedasticity in Identifying and Estimating Linear Factor Models," MPRA Paper 33593, University Library of Munich, Germany.
    3. Sebastien Valeyre, 2020. "Refined model of the covariance/correlation matrix between securities," Papers 2001.08911, arXiv.org.
    4. Jushan Bai & Shuzhong Shi, 2011. "Estimating High Dimensional Covariance Matrices and its Applications," Annals of Economics and Finance, Society for AEF, vol. 12(2), pages 199-215, November.
    5. Christian Calm¨¨s & Raymond Th¨¦oret, 2016. "The Asymmetric Impact of Portfolio Mix on Bank Performance over the Business Cycle: U.S. and Canadian Evidence," Review of Economics & Finance, Better Advances Press, Canada, vol. 6, pages 57-74, February.
    6. Sebastien Valeyre & Denis S. Grebenkov & Sofiane Aboura, 2019. "The Reactive Beta Model," Papers 1911.00919, arXiv.org.
    7. Christian Calmès & Denis Cormier & Francois Éric Racicot & Raymond Théoret, 2012. "Firms' Accruals and Tobin’s q," RePAd Working Paper Series UQO-DSA-wp032012, Département des sciences administratives, UQO.

  26. Jushan Bai & Chihwa Kao, 2005. "On the Estimation and Inference of a Panel Cointegration Model with Cross-Sectional Dependence," Center for Policy Research Working Papers 75, Center for Policy Research, Maxwell School, Syracuse University.

    Cited by:

    1. Byrne, Joseph P. & Fiess, Norbert & MacDonald, Ronald, 2011. "The global dimension to fiscal sustainability," Journal of Macroeconomics, Elsevier, vol. 33(2), pages 137-150, June.
    2. Saeid Mahdavi, 2010. "Fiscal Stringency and Fiscal Sustainability in the American States: Panel Evidence," Working Papers 0016, College of Business, University of Texas at San Antonio.
    3. Piotr Roszkowski & Kamila Sławińska & Andrzej Torój, 2014. "BEER tastes better in a panel of neighbours. On equilibrium exchange rates in CEE countries," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 34, pages 209-226.
    4. Coudert, Virginie & Couharde, Cécile & Mignon, Valérie, 2015. "On the impact of volatility on the real exchange rate – terms of trade nexus: Revisiting commodity currencies," Journal of International Money and Finance, Elsevier, vol. 58(C), pages 110-127.
    5. García Solanes, José & Torrejón-Flores, Fernando, 2008. "The Balassa-Samuelson Hypothesis in Developed Countries and Emerging Market Economies: Different Outcomes Explained," Economics Discussion Papers 2008-14, Kiel Institute for the World Economy (IfW Kiel).
    6. Wagner, Martin & Hlouskova, Jaroslava, 2007. "The Performance of Panel Cointegration Methods. Results from a Large Scale Simulation Study," Economics Series 210, Institute for Advanced Studies.
    7. Mahdavi, Saeid & Westerlund, Joakim, 2011. "Fiscal stringency and fiscal sustainability: Panel evidence from the American state and local governments," Journal of Policy Modeling, Elsevier, vol. 33(6), pages 953-969.
    8. Solarin, Sakiru Adebola & Ozturk, Ilhan, 2016. "The relationship between natural gas consumption and economic growth in OPEC members," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1348-1356.
    9. Tino Berger & Gerdie Everaert, 2009. "A replication note on unemployment in the OECD since the 1960s: what do we know?," Empirical Economics, Springer, vol. 36(2), pages 479-485, May.

  27. Jushan Bai & Serena Ng, 2004. "Evaluating Latent and Observed Factors in Macroeconomics and Financ," Econometrics 0408007, University Library of Munich, Germany.

    Cited by:

    1. Mastromarco, Camilla & Simar, Leopold, 2014. "Global Dependence and Productivity: A Robust Nonparametric World Frontier Analysis," LIDAM Discussion Papers ISBA 2014049, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    2. Marine Carrasco & Barbara Rossi, 2016. "In-sample inference and forecasting in misspecified factor models," Economics Working Papers 1530, Department of Economics and Business, Universitat Pompeu Fabra.
    3. David Rapach & Jack Strauss, 2010. "Bagging or Combining (or Both)? An Analysis Based on Forecasting U.S. Employment Growth," Econometric Reviews, Taylor & Francis Journals, vol. 29(5-6), pages 511-533.
    4. Young Se Kim & Hyok Jung Kim, 2015. "Disaggregated Approach to Measuring Core Inflation," Korean Economic Review, Korean Economic Association, vol. 31, pages 145-176.
    5. 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.
    6. Wu, Jianhong, 2019. "Detecting irrelevant variables in possible proxies for the latent factors in macroeconomics and finance," Economics Letters, Elsevier, vol. 176(C), pages 60-63.
    7. Mastromarco, Camilla & Simar, Leopold, 2018. "Globalization and productivity: A robust nonparametric world frontier analysis," LIDAM Reprints ISBA 2018008, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    8. Marek Chudý & Erhard Reschenhofer, 2019. "Macroeconomic Forecasting with Factor-Augmented Adjusted Band Regression," Econometrics, MDPI, vol. 7(4), pages 1-14, December.
    9. Heaton, Chris & Oslington, Paul, 2010. "Micro vs macro explanations of post-war US unemployment movements," Economics Letters, Elsevier, vol. 106(2), pages 87-91, February.
    10. Chihwa Kao & Lorenzo Trapani & Giovanni Urga, 2012. "Asymptotics for Panel Models with Common Shocks," Econometric Reviews, Taylor & Francis Journals, vol. 31(4), pages 390-439.
    11. In Choi & Jorg Breitung, 2011. "Factor models," Working Papers 1121, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy), revised Dec 2011.
    12. Herrerias, M.J. & Ordoñez, J., 2012. "New evidence on the role of regional clusters and convergence in China (1952–2008)," China Economic Review, Elsevier, vol. 23(4), pages 1120-1133.
    13. Bianco, Dominique & Niang, Abdou-Aziz, 2012. "On international spillovers," Economics Letters, Elsevier, vol. 117(1), pages 280-282.
    14. Araújo, Fabio & Issler, João Victor & Fernandes, Marcelo, 2005. "Estimating the stochastic discount factor without a utility function," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 583, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    15. Eickmeier, Sandra, 2006. "Comovements and heterogeneity in the Comovements and heterogeneity in the dynamic factor model," Discussion Paper Series 1: Economic Studies 2006,31, Deutsche Bundesbank.
    16. Anisha Ghosh & Oliver Linton, 2019. "Estimation with Mixed Data Frequencies: A Bias-Correction Approach," CeMMAP working papers CWP65/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    17. Araújo, Fabio & Issler, João Victor & Fernandes, Marcelo, 2006. "A stochastic discount factor approach to asset pricing using panel data," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 628, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    18. Norman R. Swanson & Nii Ayi Armah, 2011. "Seeing Inside the Black Box: Using Diffusion Index Methodology to Construct Factor Proxies in Largescale Macroeconomic Time Series Environments," Departmental Working Papers 201105, Rutgers University, Department of Economics.
    19. Roberta Fiori & Simonetta Iannotti, 2010. "On the interaction between market and credit risk: a factor-augmented vector autoregressive (FAVAR) approach," Temi di discussione (Economic working papers) 779, Bank of Italy, Economic Research and International Relations Area.
    20. Zhang, Yixiao & Yu, Cindy L. & Li, Haitao, 2022. "Nowcasting GDP Using Dynamic Factor Model with Unknown Number of Factors and Stochastic Volatility: A Bayesian Approach," Econometrics and Statistics, Elsevier, vol. 24(C), pages 75-93.
    21. Mariam Camarero & Estrella Gómez & Cecilio Tamarit, 2012. "The euro impact on trade. Long run evidence with structural breaks," Working Papers 1209, Department of Applied Economics II, Universidad de Valencia.
    22. Liangjun Su & Sainan Jin & Yonghui Zhang, 2014. "Specification Test for Panel Data Models with Interactive Fixed Effects," Working Papers 08-2014, Singapore Management University, School of Economics.
    23. Alhassan Abdullah Mohammed, 2011. "A Coincident Indicator of the Gulf Cooperation Council Business Cycle," Review of Middle East Economics and Finance, De Gruyter, vol. 6(3), pages 1-23, February.
    24. Norman R. Swanson & Weiqi Xiong & Xiye Yang, 2020. "Predicting interest rates using shrinkage methods, real‐time diffusion indexes, and model combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 587-613, August.
    25. Castagnetti, Carolina & Rossi, Eduardo & Trapani, Lorenzo, 2019. "A two-stage estimator for heterogeneous panel models with common factors," Econometrics and Statistics, Elsevier, vol. 11(C), pages 63-82.
    26. Chevallier, Julien, 2011. "Macroeconomics, finance, commodities: Interactions with carbon markets in a data-rich model," Economic Modelling, Elsevier, vol. 28(1-2), pages 557-567, January.
    27. Carriero, Andrea & Kapetanios, George & Marcellino, Massimiliano, 2016. "Structural analysis with Multivariate Autoregressive Index models," Journal of Econometrics, Elsevier, vol. 192(2), pages 332-348.
    28. Sandra Eickmeier & Boris Hofmann, 2022. "What drives inflation? Disentangling Demand and Supply Factors," CAMA Working Papers 2022-74, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    29. Christian Brownlees & Geert Mesters, 2017. "Detecting Granular Time Series in Large Panels," Working Papers 991, Barcelona School of Economics.
    30. Cecilio R. Tamarit Escalona & Estrella Gómez, 2011. "The euro effect on trade: evidence in gravity equations using panel cointegration techniques," Working Papers. Serie EC 2011-07, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    31. Pilar Poncela & Esther Ruiz, 2016. "Small- Versus Big-Data Factor Extraction in Dynamic Factor Models: An Empirical Assessment," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 401-434, Emerald Group Publishing Limited.
    32. Eickmeier, Sandra & Gambacorta, Leonardo & Hofmann, Boris, 2013. "Understanding global liquidity," Discussion Papers 03/2013, Deutsche Bundesbank.
    33. Chen, Liang & Dolado, Juan José & Gonzalo, Jesús, 2011. "Detecting big structural breaks in large factor models," UC3M Working papers. Economics we1141, Universidad Carlos III de Madrid. Departamento de Economía.
    34. Mario J. Crucini & M. Ayhan Kose & Christopher Otrok, 2008. "What Are the Driving Forces of International Business Cycles?," NBER Working Papers 14380, National Bureau of Economic Research, Inc.
    35. Morana, Claudio, 2014. "Insights on the global macro-finance interface: Structural sources of risk factor fluctuations and the cross-section of expected stock returns," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 64-79.
    36. Sinha, Avik & Gupta, Monika & Shahbaz, Muhammad & Sengupta, Tuhin, 2019. "Impact of Corruption in Public Sector on Environmental Quality: Implications for Sustainability in BRICS and Next 11 Countries," MPRA Paper 94357, University Library of Munich, Germany, revised 05 Jun 2019.
    37. Eichengreen, Barry & Mody, Ashoka & Nedeljkovic, Milan & Sarno, Lucio, 2012. "How the Subprime Crisis went global: Evidence from bank credit default swap spreads," Journal of International Money and Finance, Elsevier, vol. 31(5), pages 1299-1318.
    38. Eric Bataille & Catherine Bruneau & Frederic Michaud, 2007. "Business cycle and corporate failure in France: Is there a link?," Computational Economics, Springer;Society for Computational Economics, vol. 29(2), pages 173-197, March.
    39. Kim, Hyun Hak & Swanson, Norman R., 2018. "Mining big data using parsimonious factor, machine learning, variable selection and shrinkage methods," International Journal of Forecasting, Elsevier, vol. 34(2), pages 339-354.
    40. Peter C.B. Phillips & Donggyu Sul, 2007. "Transition Modeling and Econometric Convergence Tests," Cowles Foundation Discussion Papers 1595, Cowles Foundation for Research in Economics, Yale University.
    41. Lima, Luiz Renato Regis de Oliveira & Issler, João Victor, 2008. "A panel data approach to economic forecasting: the bias-corrected average forecast," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 668, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    42. Castagnetti, Carolina & Rossi, Eduardo, 2008. "Estimation methods in panel data models with observed and unobserved components: a Monte Carlo study," MPRA Paper 26196, University Library of Munich, Germany.
    43. Marcellino, Massimiliano & Carriero, Andrea & Corsello, Francesco, 2019. "The Global Component of Inflation Volatility," CEPR Discussion Papers 13470, C.E.P.R. Discussion Papers.
    44. Emmanuel Dhyne & Catherine Fuss & M. Hashem Pesaran & Patrick Sevestre, 2011. "Lumpy Price Adjustments: A Microeconometric Analysis," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(4), pages 529-540, October.
    45. Owyang, Michael T. & Rapach, David E. & Wall, Howard J., 2009. "States and the business cycle," Journal of Urban Economics, Elsevier, vol. 65(2), pages 181-194, March.
    46. Norman R. Swanson & Nii Ayi Armah, 2011. "Some Variables are More Worthy Than Others: New Diffusion Index Evidence on the Monitoring of Key Economic Indicators," Departmental Working Papers 201115, Rutgers University, Department of Economics.
    47. Abdou-Aziz Niang & Abdoulaye Diagne & Marie-Claude Pichery, 2011. "Exploring the finance-real economy link in U.S.: empirical evidence from panel unit root and cointegration analysis," Empirical Economics, Springer, vol. 40(1), pages 253-268, February.
    48. Martin Wagner, 2008. "On PPP, unit roots and panels," Empirical Economics, Springer, vol. 35(2), pages 229-249, September.
    49. Goyal, Amit & Pérignon, Christophe & Villa, Christophe, 2008. "How common are common return factors across the NYSE and Nasdaq?," Journal of Financial Economics, Elsevier, vol. 90(3), pages 252-271, December.
    50. Joakim Westerlund, 2020. "A cross‐section average‐based principal components approach for fixed‐T panels," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 776-785, September.
    51. Wei-Choun Yu, 2008. "Macroeconomic and financial market volatilities: an empirical evidence of factor model," Economics Bulletin, AccessEcon, vol. 3(33), pages 1-18.
    52. Sun, Yucheng & Xu, Wen & Zhang, Chuanhai, 2023. "Identifying latent factors based on high-frequency data," Journal of Econometrics, Elsevier, vol. 233(1), pages 251-270.
    53. Kleibergen, Frank & Zhan, Zhaoguo, 2015. "Unexplained factors and their effects on second pass R-squared’s," Journal of Econometrics, Elsevier, vol. 189(1), pages 101-116.
    54. Herrerias, M.J., 2013. "The environmental convergence hypothesis: Carbon dioxide emissions according to the source of energy," Energy Policy, Elsevier, vol. 61(C), pages 1140-1150.
    55. Dong, Yingjie & Huang, Wenxin & Tse, Yiu-Kuen, 2023. "Price comovement and market segmentation of Chinese A- and H-shares: Evidence from a panel latent-factor model," Journal of International Money and Finance, Elsevier, vol. 131(C).
    56. Nicholas Brown & Joakim Westerlund, 2022. "Testing Factors In Cce," Working Paper 1491, Economics Department, Queen's University.
    57. Norman R. Swanson, 2016. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 348-353, July.
    58. Lin, Jianhao & Wang, Meijin & Cai, Lingfeng, 2012. "Are the Fama–French factors good proxies for latent risk factors? Evidence from the data of SHSE in China," Economics Letters, Elsevier, vol. 116(2), pages 265-268.
    59. Eduardo A. Souza-Rodrigues, 2016. "Nonparametric Regression with Common Shocks," Econometrics, MDPI, vol. 4(3), pages 1-17, September.
    60. Kelly, Logan, 2007. "Measuring the Economic Stock of Money," MPRA Paper 4914, University Library of Munich, Germany.
    61. Jushan Bai & Serena Ng, 2008. "Extremum Estimation when the Predictors are Estimated from Large Panels," Annals of Economics and Finance, Society for AEF, vol. 9(2), pages 201-222, November.
    62. Dai, Chaoxing & Lu, Kun & Xiu, Dacheng, 2019. "Knowing factors or factor loadings, or neither? Evaluating estimators of large covariance matrices with noisy and asynchronous data," Journal of Econometrics, Elsevier, vol. 208(1), pages 43-79.
    63. Demir, Ishak, 2019. "International Spillovers of U.S. Monetary Policy," LEAF Working Paper Series 19-02, University of Lincoln, Lincoln International Business School, Lincoln Economics and Finance Research Group (LEAF).
    64. Cathy Chen & Wolfgang Härdle, 2015. "Common factors in credit defaults swap markets," Computational Statistics, Springer, vol. 30(3), pages 845-863, September.
    65. Atak, Alev & Kapetanios, George, 2013. "A factor approach to realized volatility forecasting in the presence of finite jumps and cross-sectional correlation in pricing errors," Economics Letters, Elsevier, vol. 120(2), pages 224-228.
    66. Zafar, Muhammad Wasif & Zaidi, Syed Anees Haider & Sinha, Avik & Gedikli, Ayfer & Hou, Fujun, 2019. "The role of stock market and banking sector development, and renewable energy consumption in carbon emissions: Insights from G-7 and N-11 countries," Resources Policy, Elsevier, vol. 62(C), pages 427-436.
    67. Markus Pelger, 2020. "Understanding Systematic Risk: A High‐Frequency Approach," Journal of Finance, American Finance Association, vol. 75(4), pages 2179-2220, August.
    68. Abdullah Al-Hassan, 2009. "A Coincident Indicator of the Gulf Cooperation Council (GCC) Business Cycle," IMF Working Papers 2009/073, International Monetary Fund.
    69. Pérez-Quirós, Gabriel & Camacho, Máximo & Alvarez, Rocio, 2012. "Finite sample performance of small versus large scale dynamic factor models," CEPR Discussion Papers 8867, C.E.P.R. Discussion Papers.
    70. Guido M. Kuersteiner & Ingmar R. Prucha, 2020. "Dynamic Spatial Panel Models: Networks, Common Shocks, and Sequential Exogeneity," Econometrica, Econometric Society, vol. 88(5), pages 2109-2146, September.
    71. Muhammad Wasif Zafar & Asif Saeed & Syed Anees Haider Zaidi & Abdul Waheed, 2021. "The linkages among natural resources, renewable energy consumption, and environmental quality: A path toward sustainable development," Sustainable Development, John Wiley & Sons, Ltd., vol. 29(2), pages 353-362, March.
    72. Alain-Philippe Fortin & Patrick Gagliardini & Olivier Scaillet, 2023. "Latent Factor Analysis in Short Panels," Papers 2306.14004, arXiv.org.
    73. Wu, Jianhong & Li, Jinchang, 2014. "Testing for individual and time effects in panel data models with interactive effects," Economics Letters, Elsevier, vol. 125(2), pages 306-310.
    74. Colin T. Bowers & Chris Heaton, 2013. "What does high-dimensional factor analysis tell us about risk factors in the Australian stock market?," Applied Economics, Taylor & Francis Journals, vol. 45(11), pages 1395-1404, April.
    75. Kim Dukpa & Kim Yunjung & Bak Yuhyeon, 2017. "Multi-level factor analysis of bond risk premia," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(5), pages 1-19, December.
    76. Bai, Jushan & Ando, Tomohiro, 2013. "Multifactor asset pricing with a large number of observable risk factors and unobservable common and group-specific factors," MPRA Paper 52785, University Library of Munich, Germany, revised Dec 2013.
    77. Camarero, Mariam & Gómez, Estrella & Tamarit, Cecilio, 2014. "Is the ‘euro effect’ on trade so small after all? New evidence using gravity equations with panel cointegration techniques," Economics Letters, Elsevier, vol. 124(1), pages 140-142.
    78. Shahrin Saaid Shaharuddin & Wee-Yeap Lau & Tien-Ming Yip, 2017. "Dynamic Linkages between Newly Developed Islamic Equity Style Indices: Is Growth Style More Influential Than Value Style?," Capital Markets Review, Malaysian Finance Association, vol. 25(2), pages 49-64.
    79. Kelava, Augustin & Kohler, Michael & Krzyżak, Adam & Schaffland, Tim Fabian, 2017. "Nonparametric estimation of a latent variable model," Journal of Multivariate Analysis, Elsevier, vol. 154(C), pages 112-134.
    80. Kim, Young Se, 2015. "Electricity consumption and economic development: Are countries converging to a common trend?," Energy Economics, Elsevier, vol. 49(C), pages 192-202.
    81. 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.
    82. Hyun Hak Kim, 2013. "Forecasting Macroeconomic Variables Using Data Dimension Reduction Methods: The Case of Korea," Working Papers 2013-26, Economic Research Institute, Bank of Korea.
    83. Westerlund, Joakim & Sharma, Susan Sunila, 2019. "Panel evidence on the ability of oil returns to predict stock returns in the G7 area," Energy Economics, Elsevier, vol. 77(C), pages 3-12.
    84. 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.
    85. Tan, Xueping & Sirichand, Kavita & Vivian, Andrew & Wang, Xinyu, 2022. "Forecasting European carbon returns using dimension reduction techniques: Commodity versus financial fundamentals," International Journal of Forecasting, Elsevier, vol. 38(3), pages 944-969.
    86. Fousekis, Panos, 2009. "Are Food Prices in the EU Converging? Empirical Evidence from the Log t Test," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 62(4), pages 407-423.
    87. Kim, Hyun Hak & Swanson, Norman R., 2014. "Forecasting financial and macroeconomic variables using data reduction methods: New empirical evidence," Journal of Econometrics, Elsevier, vol. 178(P2), pages 352-367.
    88. Pedro Henrique Melo Albuquerque & Yaohao Peng & João Pedro Fontoura da Silva, 2022. "Making the whole greater than the sum of its parts: A literature review of ensemble methods for financial time series forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1701-1724, December.
    89. Kihwan Kim & Hyun Hak Kim & Norman R. Swanson, 2023. "Mixing mixed frequency and diffusion indices in good times and in bad: an assessment based on historical data around the great recession of 2008," Empirical Economics, Springer, vol. 64(3), pages 1421-1469, March.
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  28. Jushan Bai & Serena Ng, 2004. "Confidence Intervals for Diffusion Index Forecasts with a Large Number of Predictor," Econometrics 0408006, University Library of Munich, Germany.

    Cited by:

    1. Massimiliano Marcellino, 2005. "Pooling-based Data Interpolation and Backdating," Working Papers 299, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    2. Kilian, Lutz & Inoue, Atsushi, 2005. "How Useful is Bagging in Forecasting Economic Time Series? A Case Study of US CPI Inflation," CEPR Discussion Papers 5304, C.E.P.R. Discussion Papers.
    3. Jushan Bai & Serena Ng, 2004. "Evaluating Latent and Observed Factors in Macroeconomics and Financ," Econometrics 0408007, University Library of Munich, Germany.
    4. Angelini, Elena & Henry, Jérôme & Marcellino, Massimiliano, 2003. "Interpolation and backdating with a large information set," Working Paper Series 252, European Central Bank.
    5. Antoine A. Djogbenou, 2020. "Comovements in the real activity of developed and emerging economies: A test of global versus specific international factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(3), pages 344-370, April.
    6. Daniel Kaufmann & Sarah M. Lein, 2012. "Is There a Swiss Price Puzzle?," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 148(I), pages 57-75, March.

  29. Jushan Bai; Josep Lluís Carrion-i-Silvestre, 2004. "Structural changes, common stochastic trends and unit roots in panel data," Econometric Society 2004 North American Summer Meetings 345, Econometric Society.

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    1. Murshed, Muntasir & Saboori, Behnaz & Madaleno, Mara & Wang, Hong & Doğan, Buhari, 2022. "Exploring the nexuses between nuclear energy, renewable energy, and carbon dioxide emissions: The role of economic complexity in the G7 countries," Renewable Energy, Elsevier, vol. 190(C), pages 664-674.
    2. Li, Su-Fang & Zhu, Hui-Ming & Yu, Keming, 2012. "Oil prices and stock market in China: A sector analysis using panel cointegration with multiple breaks," Energy Economics, Elsevier, vol. 34(6), pages 1951-1958.
    3. Ma, Qiang & Murshed, Muntasir & Khan, Zeeshan, 2021. "The nexuses between energy investments, technological innovations, emission taxes, and carbon emissions in China," Energy Policy, Elsevier, vol. 155(C).
    4. Sophie Piton, 2016. "A European Disease?Non-tradable inflation and real interest rate divergence," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01321836, HAL.
    5. Li, Zeyun & Kuo, Yen-Ku & Mahmud, Abdul Rahman & Nassani, Abdelmohsen A. & Haffar, Mohamed & Muda, Iskandar, 2022. "Integration of renewable energy, environmental policy stringency, and climate technologies in realizing environmental sustainability: Evidence from OECD countries," Renewable Energy, Elsevier, vol. 196(C), pages 1376-1384.
    6. Shang, Yunfeng & Razzaq, Asif & Chupradit, Supat & Binh An, Nguyen & Abdul-Samad, Zulkiflee, 2022. "The role of renewable energy consumption and health expenditures in improving load capacity factor in ASEAN countries: Exploring new paradigm using advance panel models," Renewable Energy, Elsevier, vol. 191(C), pages 715-722.
    7. Cerqueti, Roy & Costantini, Mauro, 2011. "Testing for rational bubbles in the presence of structural breaks: Evidence from nonstationary panels," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2598-2605, October.
    8. Mariam Camarero & Juan Sapena & Cecilio Tamarit, 2020. "Modelling Time-Varying Parameters in Panel Data State-Space Frameworks: An Application to the Feldstein–Horioka Puzzle," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 87-114, June.
    9. Chien, Fengsheng & Hsu, Ching-Chi & Ozturk, Ilhan & Sharif, Arshian & Sadiq, Muhammad, 2022. "The role of renewable energy and urbanization towards greenhouse gas emission in top Asian countries: Evidence from advance panel estimations," Renewable Energy, Elsevier, vol. 186(C), pages 207-216.
    10. Ahmad, Manzoor & Zheng, Jianghuai, 2021. "Do innovation in environmental-related technologies cyclically and asymmetrically affect environmental sustainability in BRICS nations?," Technology in Society, Elsevier, vol. 67(C).
    11. Zhao, Wei & Liu, Yishu & Huang, Lihua, 2022. "Estimating environmental Kuznets Curve in the presence of eco-innovation and solar energy: An analysis of G-7 economies," Renewable Energy, Elsevier, vol. 189(C), pages 304-314.
    12. Rodríguez, Miguel & Pena-Boquete, Yolanda & Pardo-Fernández, Juan Carlos, 2016. "Revisiting Environmental Kuznets Curves through the energy price lens," Energy Policy, Elsevier, vol. 95(C), pages 32-41.
    13. Josep Lluís CARRION-I-SILVESTRE & Mariam CAMARERO & Josep LLUÍS CARRION-I-SILVESTRE & Cecilio TAMARIT, 2010. "External Imbalances in a Monetary Union. Does the Lawson Doctrine Apply to Europe?," EcoMod2010 259600036, EcoMod.
    14. Shruti Shastri & A. K. Giri & Geetilaxmi Mohapatra, 2018. "Testing the Sustainability of Current Accounts for Major South Asian Economies," South Asia Economic Journal, Institute of Policy Studies of Sri Lanka, vol. 19(1), pages 1-21, March.
    15. Claudio Morana, 2014. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks," Working Papers 273, University of Milano-Bicocca, Department of Economics, revised May 2014.
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    17. Bai, Jushan & Carrion-i-Silvestre, Josep Lluis, 2009. "Testing Panel Cointegration with Unobservable Dynamic Common Factors," MPRA Paper 35243, University Library of Munich, Germany.
    18. Karavias, Yiannis & Tzavalis, Elias, 2012. "Generalized �Fixed-T Panel Unit Root Tests Allowing for Structural Breaks," MPRA Paper 43128, University Library of Munich, Germany.
    19. Wang, Weiguo & Xue, Jing & Du, Chonghua, 2016. "The Balassa–Samuelson hypothesis in the developed and developing countries revisited," Economics Letters, Elsevier, vol. 146(C), pages 33-38.
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    41. Domingo Rodríguez Benavides & Abigail Rodríguez Nava, 2019. "Convergencia de los precios locales en México: un enfoque de pruebas entre pares/Convergence of local prices in Mexico: A pairwise approach," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 34(2), pages 309-332.
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    43. Liddle, Brantley & Messinis, George, 2013. "Which comes first—urbanization or economic growth? Evidence from heterogeneous panel causality tests," MPRA Paper 53983, University Library of Munich, Germany.
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    1. Bertrand Candelon & Elena Ivona Dumitrescu & Christophe Hurlin, 2014. "Currency Crises Early Warning Systems: Why They Should Be Dynamic," Post-Print hal-01385975, HAL.
    2. Reichlin, Lucrezia, 2002. "Factor Models in Large Cross-Sections of Time Series," CEPR Discussion Papers 3285, C.E.P.R. Discussion Papers.
    3. Jerry Coakley & Ana-Maria Fuertes & Ron Smith, 2002. "A Principal Components Approach to Cross-Section Dependence in Panels," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 B5-3, International Conferences on Panel Data.
    4. Jushan Bai; Josep Lluís Carrion-i-Silvestre, 2004. "Structural changes, common stochastic trends and unit roots in panel data," Econometric Society 2004 North American Summer Meetings 345, Econometric Society.
    5. Jorge Selaive C. & Valentín Délano T., 2006. "Sovereign Spreads: a Factorial Approach," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 9(1), pages 49-67, April.
    6. Jönsson, Kristian, 2004. "Testing for Stationarity in Panel Data Models when Disturbances are Cross-Sectionally Correlated," Working Papers 2004:17, Lund University, Department of Economics, revised 26 Nov 2004.
    7. Choi, Chi-Young, 2004. "Searching for evidence of long-run PPP from a post-Bretton Woods panel: separating the wheat from the chaff," Journal of International Money and Finance, Elsevier, vol. 23(7-8), pages 1159-1186.
    8. Simón Sosvilla-Rivero & Emma García, "undated". "Purchasing Power Parity Revisited," Working Papers 2003-20, FEDEA.

  32. Jushan Bai & Serena Ng, 2001. "A PANIC Attack on Unit Roots and Cointegration," Boston College Working Papers in Economics 519, Boston College Department of Economics.

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    7. Christian Dreger & Hans-Eggert Reimers, 2006. "Hysteresis and Persistence in the Course of Unemployment: The EU and US Experience," Discussion Papers of DIW Berlin 572, DIW Berlin, German Institute for Economic Research.
    8. Arturas Juodis, 2014. "Cointegration Testing in Panel VAR Models Under Partial Identification and Spatial Dependence," UvA-Econometrics Working Papers 14-08, Universiteit van Amsterdam, Dept. of Econometrics.
    9. Olaf, POSCH & Klaus, WAELDE, 2005. "Natural volatility, welfare and taxation," Discussion Papers (ECON - Département des Sciences Economiques) 2005009, Université catholique de Louvain, Département des Sciences Economiques.
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    12. Kwaku Addai & Berna Serener & Dervis Kirikkaleli, 2022. "Asymmetricity in the Effect of Economic and Environmental Factors on Social Sustainability: Empirical Evidence from Eastern European Economies using Dynamic Analysis with CCEMG & D-H Causality Approac," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 12(3), pages 75-93.
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    35. Nagayasu, Jun, 2010. "Macroeconomic Interdependence in East Asia," MPRA Paper 27129, University Library of Munich, Germany.
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    37. Sipan Aslan & Ceylan Yozgatligil & Cem Iyigun, 2018. "Temporal clustering of time series via threshold autoregressive models: application to commodity prices," Annals of Operations Research, Springer, vol. 260(1), pages 51-77, January.
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    40. Byrne, Joseph P. & Fiess, Norbert & MacDonald, Ronald, 2011. "The global dimension to fiscal sustainability," Journal of Macroeconomics, Elsevier, vol. 33(2), pages 137-150, June.
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    44. Rafaty, R. & Dolphin, G. & Pretis, F., 2020. "Carbon pricing and the elasticity of CO2 emissions," Cambridge Working Papers in Economics 20116, Faculty of Economics, University of Cambridge.
    45. Chihwa Kao & Lorenzo Trapani & Giovanni Urga, 2012. "Asymptotics for Panel Models with Common Shocks," Econometric Reviews, Taylor & Francis Journals, vol. 31(4), pages 390-439.
    46. In Choi & Jorg Breitung, 2011. "Factor models," Working Papers 1121, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy), revised Dec 2011.
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    48. Gioldasis, Georgios & Musolesi, Antonio & Simioni, Michel, 2023. "Interactive R&D spillovers: An estimation strategy based on forecasting-driven model selection," International Journal of Forecasting, Elsevier, vol. 39(1), pages 144-169.
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    1. Brian M. Doyle & Jon Faust, 2003. "Breaks in the variability and co-movement of G-7 economic growth," International Finance Discussion Papers 786, Board of Governors of the Federal Reserve System (U.S.).
    2. Otavio Ribeiro de Medeiros and Vitor Leone, 2012. "Multiple Changes in Persistence vs. Explosive Behaviour: The Dotcom Bubble," NBS Discussion Papers in Economics 2012/02, Economics, Nottingham Business School, Nottingham Trent University.
    3. Ye Li & Pierre Perron, 2013. "Inference Related to Locally Ordered and Common Breaks in a Multivariate System with Joined Segmented Trends," Boston University - Department of Economics - Working Papers Series 2013-010, Boston University - Department of Economics.
    4. Qu, Zhongjun, 2008. "Testing for structural change in regression quantiles," Journal of Econometrics, Elsevier, vol. 146(1), pages 170-184, September.
    5. Alastair R. Hall & Denise R. Osborn & Nikolaos Sakkas, 2013. "Inference on Structural Breaks using Information Criteria," Manchester School, University of Manchester, vol. 81, pages 54-81, October.
    6. Soo-Bin Jeong & Bong-Hwan Kim & Tae-Hwan Kim & Hyung-Ho Moon, 2017. "Unit Root Tests In The Presence Of Multiple Breaks In Variance," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 62(02), pages 345-361, June.
    7. Yan Qian & Zijun Wang, 2021. "A model selection approach to jointly testing for structural breaks and cointegration with application to the Eurocurrency interest rates market," Empirical Economics, Springer, vol. 61(2), pages 799-825, August.
    8. Hidalgo, Javier & Schafgans, Marcia, 2017. "Inference and testing breaks in large dynamic panels with strong cross sectional dependence," Journal of Econometrics, Elsevier, vol. 196(2), pages 259-274.
    9. Bai, Jushan, 2010. "Common breaks in means and variances for panel data," Journal of Econometrics, Elsevier, vol. 157(1), pages 78-92, July.
    10. Yi-Chi Chen & Wei-Choun Yu, 2011. "Structural change in the forward discount: a Bayesian analysis of forward rate unbiasedness hypothesis," Economics Bulletin, AccessEcon, vol. 31(2), pages 1807-1826.
    11. Duan, Jiangtao & Bai, Jushan & Han, Xu, 2023. "Quasi-maximum likelihood estimation of break point in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 233(1), pages 209-236.
    12. Luca Benati, 2003. "Evolving Post-World War II U.K. Economic Performance," Computing in Economics and Finance 2003 171, Society for Computational Economics.
    13. Bruno Damásio & João Nicolau, 2020. "Time Inhomogeneous Multivariate Markov Chains: Detecting and Testing Multiple Structural Breaks Occurring at Unknown," Working Papers REM 2020/0136, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    14. Tatsushi Oka & Pierre Perron, 2016. "Testing for Common Breaks in a Multiple Equations System," Papers 1606.00092, arXiv.org, revised Jan 2018.
    15. Karsten Schweikert, 2022. "Detecting Multiple Structural Breaks in Systems of Linear Regression Equations with Integrated and Stationary Regressors," Papers 2201.05430, arXiv.org, revised Aug 2023.
    16. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Boston University - Department of Economics - Working Papers Series WP2019-02, Boston University - Department of Economics.
    17. Pierre Perron & Yohei Yamamoto & Jing Zhou, 2020. "Testing jointly for structural changes in the error variance and coefficients of a linear regression model," Quantitative Economics, Econometric Society, vol. 11(3), pages 1019-1057, July.
    18. Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2020. "Modeling Turning Points In Global Equity Market," DEM Working Papers Series 195, University of Pavia, Department of Economics and Management.
    19. Sibbertsen, Philipp & Wenger, Kai & Wingert, Simon, 2020. "Testing for Multiple Structural Breaks in Multivariate Long Memory Time Series," Hannover Economic Papers (HEP) dp-676, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    20. Kurozumi, Eiji & Tuvaandorj, Purevdorj, 2011. "Model selection criteria in multivariate models with multiple structural changes," Journal of Econometrics, Elsevier, vol. 164(2), pages 218-238, October.
    21. Laurent Callot & Johannes Tang Kristensen, 2014. "Vector Autoregressions with Parsimoniously Time Varying Parameters and an Application to Monetary Policy," CREATES Research Papers 2014-41, Department of Economics and Business Economics, Aarhus University.
    22. Giovanni Angelini & Emanuele Bacchiocchi & Giovanni Caggiano & Luca Fanelli, 2019. "Uncertainty across volatility regimes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 437-455, April.
    23. Candelon, B. & Cubadda, G., 2005. "Testing for parameter stability in dynamic models across frequencies," Research Memorandum 021, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    24. Dickinson, David & Liu, Jia, 2007. "The real effects of monetary policy in China: An empirical analysis," China Economic Review, Elsevier, vol. 18(1), pages 87-111.
    25. Loredana Ureche-Rangau & Franck Speeg, 2011. "A simple method for variance shift detection at unknown time points," Economics Bulletin, AccessEcon, vol. 31(3), pages 2204-2218.
    26. Paulo M.M. Rodrigues & João Cruz, 2018. "Structural Changes in the Duration of Bull Markets and Business Cycle Dynamics," Working Papers w201814, Banco de Portugal, Economics and Research Department.
    27. Chan, Kam C. & Chan, Leo H. & Nguyen, Chi M., 2020. "Forecasting oil futures market volatility in a financialized world: Why speculative activities matter," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    28. Javier Hidalgo & Marcia M Schafgans, 2015. "Inference and Testing Breaks in Large Dynamic Panels with Strong Cross Sectional Dependence," STICERD - Econometrics Paper Series /2015/583, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    29. Leone, Vitor & de Medeiros, Otavio Ribeiro, 2015. "Signalling the Dotcom bubble: A multiple changes in persistence approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 55(C), pages 77-86.
    30. Shi, Yujie & Wang, Liming & Ke, Jian, 2021. "Does the US-China trade war affect co-movements between US and Chinese stock markets?," Research in International Business and Finance, Elsevier, vol. 58(C).
    31. Chen, Gongmeng & Choi, Yoon K. & Zhou, Yong, 2005. "Nonparametric estimation of structural change points in volatility models for time series," Journal of Econometrics, Elsevier, vol. 126(1), pages 79-114, May.
    32. KUROZUMI, Eiji & 黒住, 英司 & YAMAMOTO, Yohei & 山本, 庸平, 2015. "Confidence Sets for the Break Date Based on Optimal Tests," Discussion Papers 2015-01, Graduate School of Economics, Hitotsubashi University.
    33. Oka, Tatsushi & Qu, Zhongjun, 2011. "Estimating structural changes in regression quantiles," Journal of Econometrics, Elsevier, vol. 162(2), pages 248-267, June.
    34. Venkata Jandhyala & Stergios Fotopoulos & Ian MacNeill & Pengyu Liu, 2013. "Inference for single and multiple change-points in time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(4), pages 423-446, July.
    35. Chihwa Kao & Lorenzo Trapani & Giovanni Urga, 2012. "Testing for Instability in Covariance Structures," Center for Policy Research Working Papers 131, Center for Policy Research, Maxwell School, Syracuse University.
    36. Neil Kellard & Denise Osborn & Jerry Coakley & Alastair R. Hall & Denise R. Osborn & Nikolaos Sakkas, 2015. "Structural Break Inference Using Information Criteria in Models Estimated by Two-Stage Least Squares," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 741-762, September.
    37. Pierre Perron & Yohei Yamamoto, 2008. "Estimating and Testing Multiple Structural Changes in Models with Endogenous Regressors," Boston University - Department of Economics - Working Papers Series wp2008-017, Boston University - Department of Economics.
    38. Changryong Baek & Benjamin Leinwand & Kristen A. Lindquist & Seok-Oh Jeong & Joseph Hopfinger & Katheleen M. Gates & Vladas Pipiras, 2023. "Detecting Changes in Correlation Networks with Application to Functional Connectivity of fMRI Data," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 636-655, June.
    39. Pierre Perron & Yohei Yamamoto, 2015. "Using OLS to Estimate and Test for Structural Changes in Models with Endogenous Regressors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(1), pages 119-144, January.
    40. Badi H. Baltagi & Qu Feng & Chihwa Kao, 2015. "Estimation of Heterogeneous Panels with Structural Breaks," Center for Policy Research Working Papers 179, Center for Policy Research, Maxwell School, Syracuse University.
    41. Bruinshoofd, W.A. & Candelon, B. & Raabe, K., 2005. "Banking sector strength and the transmission of currency crises," Research Memorandum 022, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    42. Ye Li & Pierre Perron, 2012. "Inference on Locally Ordered Breaks in Multiple Regressions," Boston University - Department of Economics - Working Papers Series wp2015-013, Boston University - Department of Economics, revised 02 Feb 2015.
    43. Zijun Wang, 2006. "The joint determination of the number and the type of structural changes," Economics Letters, Elsevier, vol. 93(2), pages 222-227, November.
    44. Pitarakis, Jean-Yves, 2014. "A joint test for structural stability and a unit root in autoregressions," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 577-587.
    45. Atanu Ghoshray, 2013. "Dynamic Persistence of Primary Commodity Prices," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(1), pages 153-164.
    46. Sugita, Katsuhiro & 杉田, 勝弘, 2006. "Bayesian Analysis of Dynamic Multivariate Models with Multiple Structural Breaks," Discussion Papers 2006-14, Graduate School of Economics, Hitotsubashi University.
    47. Paye, Bradley S. & Timmermann, Allan, 2006. "Instability of return prediction models," Journal of Empirical Finance, Elsevier, vol. 13(3), pages 274-315, June.
    48. Hidalgo, Javier & Schafgans, Marcia, 2017. "Inference and testing breaks in large dynamic panels with strong cross sectional dependence," LSE Research Online Documents on Economics 68839, London School of Economics and Political Science, LSE Library.
    49. Chulwoo Han & Abderrahim Taamouti, 2017. "Partial Structural Break Identification," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(2), pages 145-164, April.
    50. Mahua Barari & Srikanta Kundu, 2019. "The Role of the Federal Reserve in the U.S. Housing Crisis: A VAR Analysis with Endogenous Structural Breaks," JRFM, MDPI, vol. 12(3), pages 1-20, July.
    51. Marie Hušková & Zuzana Prášková & Josef G. Steinebach, 2022. "Estimating a gradual parameter change in an AR(1)-process," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(7), pages 771-808, October.

  35. Jushan Bai & Serena Ng, 1998. "A Test for Conditional Symmetry in Time Series Models," Boston College Working Papers in Economics 410, Boston College Department of Economics.

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    1. Mr. Francisco Javier Ruge-Murcia, 2001. "Inflation Targeting Under Asymmetric Preferences," IMF Working Papers 2001/161, International Monetary Fund.

  36. BAI, Jushan & PERRON, Pierre, 1998. "Computation and Analysis of Multiple Structural-Change Models," Cahiers de recherche 9807, Universite de Montreal, Departement de sciences economiques.

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    1. Esin Cakan & Rıza Demirer & Rangan Gupta & Hardik A. Marfatia, 2017. "Oil Speculation and Herding Behavior in Emerging Stock Markets," Working Papers 201749, University of Pretoria, Department of Economics.
    2. Jamal Bouoiyour, Refk Selmi, 2019. "Brexit and CDS spillovers across UK and Europe," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 16(1), pages 105-124, June.
    3. Joscha Beckmann & Ansgar Belke & Christian Dreger, 2015. "The relevance of international spillovers and asymmetric effects in the Taylor rule," FIW Working Paper series 140, FIW.
    4. Jesús Otero & Ana María Iregui, 2011. "The Long-Run Behaviour of the Terms of Trade between Primary Commodities and Manufactures: A Panel Data Approach," WIDER Working Paper Series wp-2011-071, World Institute for Development Economic Research (UNU-WIDER).
    5. Bekiros, Stelios & Marcellino, Massimiliano, 2013. "The multiscale causal dynamics of foreign exchange markets," Journal of International Money and Finance, Elsevier, vol. 33(C), pages 282-305.
    6. Óscar Bajo-Rubio & Carmen Díaz-Roldán & Vicente Esteve, "undated". "Us Deficit Sustainability Revisited: A Multiple Structural Change Approach," Working Papers 19-05 Classification-JEL , Instituto de Estudios Fiscales.
    7. Nyman, Rickard & Kapadia, Sujit & Tuckett, David & Gregory, David & Ormerod, Paul & Smith, Robert, 2018. "News and narratives in financial systems: exploiting big data for systemic risk assessment," Bank of England working papers 704, Bank of England.
    8. Bilal Mehmood & Syed Hassan Raza & Mahwish Rana & Huma Sohaib & Muhammad Azhar Khan, 2014. "Triangular Relationship between Energy Consumption, Price Index and National Income in Asian Countries: A Pooled Mean Group Approach in Presence of Structural Breaks," International Journal of Energy Economics and Policy, Econjournals, vol. 4(4), pages 610-620.
    9. Wang, Yudong & Hao, Xianfeng, 2023. "Forecasting the real prices of crude oil: What is the role of parameter instability?," Energy Economics, Elsevier, vol. 117(C).
    10. Antonio Afonso & Florence Huart & João Tovar Jalles & Piotr Stanek, 2018. "Assessing the sustainability of external imbalances in the European Union," Post-Print hal-01914597, HAL.
    11. Federico Bassi & Tom Bauermann & Dany Lang & Mark Setterfield, 2022. "Is capacity utilization variable in the long run? An agent-based sectoral approach to modeling hysteresis in the normal rate of capacity utilization," Post-Print hal-04442394, HAL.
    12. Gil-Alana, Luis Alberiko & Dettoni, Robinson & Costamagna, Rodrigo & Valenzuela, Mario, 2019. "Rational bubbles in the real housing stock market: Empirical evidence from Santiago de Chile," Research in International Business and Finance, Elsevier, vol. 49(C), pages 269-281.
    13. Anna-Leigh Stone, 2019. "Unlimited FDIC Insurance and the Implications for Corporate Cash," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 10(01), pages 1-51, November.
    14. Essahbi Essaadi & Jamel Jouini & Wajih Khallouli, 2004. "The Asian Crisis Contagion: A Dynamic Correlation Approach Analysis," Post-Print halshs-00201220, HAL.
    15. David Hendry & Lea Schneider & Jason E. Smerdon, 2016. "Detecting Volcanic Eruptions in Temperature Reconstructions by Designed Break-Indicator Saturation," Economics Series Working Papers 780, University of Oxford, Department of Economics.
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    20. Tule, Moses K. & Salisu, Afees A. & Chiemeke, Charles C., 2019. "Can agricultural commodity prices predict Nigeria's inflation?," Journal of Commodity Markets, Elsevier, vol. 16(C).
    21. Tiwari, Aviral Kumar & Dar, Arif Billah & Bhanja, Niyati & Gupta, Rangan, 2016. "A historical analysis of the US stock price index using empirical mode decomposition over 1791-2015," Economics Discussion Papers 2016-9, Kiel Institute for the World Economy (IfW Kiel).
    22. Narayan, Paresh Kumar & Liu, Ruipeng, 2015. "A GARCH model for testing market efficiency," Working Papers fe_2015_01, Deakin University, Department of Economics.
    23. Laura Mayoral, 2005. "Further evidence on the statistical properties of real GNP," Economics Working Papers 955, Department of Economics and Business, Universitat Pompeu Fabra, revised Feb 2006.
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    33. A. Talha Yalta, 2010. "The Numerical Reliability of GAUSS 8.0," Working Papers 1004, TOBB University of Economics and Technology, Department of Economics.
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    35. Fernando Fernández-Rodríguez & Marta Gómez-Puig & Simón Sosvilla-Rivero, 2015. "“Financial stress transmission in EMU sovereign bond market volatility: a connectedness analysis”," IREA Working Papers 201510, University of Barcelona, Research Institute of Applied Economics, revised Feb 2015.
    36. Jean-François Goux, 2010. "Une approche déterministe du taux de change euro-dollar," Économie et Prévision, Programme National Persée, vol. 195(4), pages 35-51.
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    39. Ana Aguilar & Carlo Alcaraz & Claudia Ramírez & Cid Alonso Rodríguez-Pérez, 2022. "The NAIRU and informality in the Mexican labor market," BIS Working Papers 1005, Bank for International Settlements.
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    13. Ma, Chenchen & Tu, Yundong, 2023. "Group fused Lasso for large factor models with multiple structural breaks," Journal of Econometrics, Elsevier, vol. 233(1), pages 132-154.

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    4. Fu, Zhonghao & Hong, Yongmiao & Su, Liangjun & Wang, Xia, 2023. "Specification tests for time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 235(2), pages 720-744.
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    7. Jesús Otero & Ana María Iregui, 2011. "The Long-Run Behaviour of the Terms of Trade between Primary Commodities and Manufactures: A Panel Data Approach," WIDER Working Paper Series wp-2011-071, World Institute for Development Economic Research (UNU-WIDER).
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    1380. Gianpaolo Zammarchi & Francesco Mola & Claudio Conversano, 2023. "Using sentiment analysis to evaluate the impact of the COVID-19 outbreak on Italy’s country reputation and stock market performance," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(3), pages 1001-1022, September.
    1381. Ramadas Sendhil & Kashish Arora & Sunny Kumar & Priyanka Lal & Arnab Roy & Ramalingam Jayakumara Varadan & Sivasankar Vedi & Anandan Pouchepparadjou, 2023. "Price Dynamics and Integration in India’s Staple Food Commodities—Evidence from Wholesale and Retail Rice and Wheat Markets," Commodities, MDPI, vol. 2(1), pages 1-21, February.
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    1384. Merih Uctum & Thom Thurston & Remzi Uctum, 2006. "Public Debt, the Unit Root Hypothesis and Structural Breaks: A Multi‐Country Analysis," Economica, London School of Economics and Political Science, vol. 73(289), pages 129-156, February.
    1385. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
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    1389. Boivin, Jean, 2006. "Has U.S. Monetary Policy Changed? Evidence from Drifting Coefficients and Real-Time Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1149-1173, August.
    1390. Yuthana Sethapramote & Suthawan Prukumpai, 2012. "Souvenir production in community-based tourism and poverty reduction in Thailand," The Empirical Econometrics and Quantitative Economics Letters, Faculty of Economics, Chiang Mai University, vol. 1(3), pages 113-130, September.
    1391. D’Haultfœuille, Xavier & Durrmeyer, Isis & Février, Philippe, 2016. "Disentangling sources of vehicle emissions reduction in France: 2003–2008," International Journal of Industrial Organization, Elsevier, vol. 47(C), pages 186-229.
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    1398. Tianfeng Li & June Wei, 2015. "Multiple Structural Breaks and Inflation Persistence: Evidence from China," Asian Economic Journal, East Asian Economic Association, vol. 29(1), pages 1-20, March.
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    1400. Omay, Tolga & Shahbaz, Muhammad & Stewart, Chris, 2021. "Is There Really Hysteresis in OECD Countries’ Unemployment Rates? New Evidence Using a Fourier Panel Unit Root Test," MPRA Paper 107691, University Library of Munich, Germany, revised 10 May 2021.
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    1403. Panday, Anjan, 2015. "Impact of monetary policy on exchange market pressure: The case of Nepal," Journal of Asian Economics, Elsevier, vol. 37(C), pages 59-71.
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    1405. Emilio Congregado & Carmen Díaz-Roldán & Vicente Esteve, 2023. "Deficit sustainability and fiscal theory of price level: the case of Italy, 1861–2020," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 50(3), pages 755-782, August.
    1406. Carlos Santos & David Hendry, 2006. "Saturation in Autoregressive Models," Notas Económicas, Faculty of Economics, University of Coimbra, issue 24, pages 8-19, December.
    1407. Sam Hak Kan Tang & Charles Ka Yui Leung, 2014. "The Deep Historical Roots of Macroeconomic Volatility," Economics Discussion / Working Papers 14-31, The University of Western Australia, Department of Economics.
    1408. Mimouni, Karim & Charfeddine, Lanouar & Al-Azzam, Moh'd, 2016. "Do oil producing countries offer international diversification benefits? Evidence from GCC countries," Economic Modelling, Elsevier, vol. 57(C), pages 263-280.
    1409. Rothfelder, Mario P. & Boldea, Otilia, 2022. "Testing for a Threshold in Models with Endogenous Regressors," Other publications TiSEM 674deead-8826-450a-8f56-f, Tilburg University, School of Economics and Management.
    1410. Hiroshi Yamada & Lan Jin, 2013. "Japan’s output gap estimation and ℓ 1 trend filtering," Empirical Economics, Springer, vol. 45(1), pages 81-88, August.
    1411. Manuel Gómez-Zaldívar & Daniel Ventosa-Santaulária, 2012. "Regional Output Convergence in Mexico," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 49(2), pages 217-236, November.
    1412. Avouyi-Dovi, Sanvi & Sahuc, Jean-Guillaume, 2016. "On the sources of macroeconomic stability in the euro area," European Economic Review, Elsevier, vol. 83(C), pages 40-63.
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    1414. Ahmad Hakimi Tajuddin & Kanesh Gopal & Rasidah Mohd-Rashid & Waqas Mehmood & Elkhan Richard Sadik-Zada, 2023. "Do Share Allocations to the Indigenous Investor Drive the Demand for IPOs?," Economies, MDPI, vol. 11(4), pages 1-18, April.
    1415. Guo, Zhichao & Feng, Yuanhua & Tan, Xiangyong, 2011. "Short- and long-term impact of remarkable economic events on the growth causes of China–Germany trade in agri-food products," Economic Modelling, Elsevier, vol. 28(6), pages 2359-2368.
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    1420. Haselmann, Rainer & Holle, Stephanie & Kool, Clemens & Ziesemer, Thomas, 2002. "Sovereign Risk and Simple Debt Dynamics: The Case of Brazil and Argentina," Research Memorandum 034, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
    1421. Takashi Miyazaki, 2019. "Clarifying the Response of Gold Return to Financial Indicators: An Empirical Comparative Analysis Using Ordinary Least Squares, Robust and Quantile Regressions," JRFM, MDPI, vol. 12(1), pages 1-18, February.
    1422. Diaz-Rainey, Ivan & Roberts, Helen & Lont, David H., 2017. "Crude inventory accounting and speculation in the physical oil market," Energy Economics, Elsevier, vol. 66(C), pages 508-522.
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    1425. Chihiro Shimizu & Kiyohiko Nishimura, 2007. "Pricing Structure in Tokyo Metropolitan Land Markets and its Structural Changes: Pre-bubble, Bubble, and Post-bubble Periods," The Journal of Real Estate Finance and Economics, Springer, vol. 35(4), pages 475-496, November.
    1426. Chengsi Zhang & Denise R. Osborn & Dong Heon Kim, 2006. "The New Keynesian Phillips Curve: from Sticky Inflation to Sticky Prices," Centre for Growth and Business Cycle Research Discussion Paper Series 78, Economics, The University of Manchester.
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    1433. Hayley Jang & Young Hoon Lee & Rodney Fort, 2019. "Winning In Professional Team Sports: Historical Moments," Economic Inquiry, Western Economic Association International, vol. 57(1), pages 103-120, January.
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    1435. Bunzel, Helle & Iglesias, Emma M., 2006. "Testing for Breaks Using Alternating Observations," Staff General Research Papers Archive 12694, Iowa State University, Department of Economics.
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    1438. Simon C. Smith, 2020. "Equity premium prediction and structural breaks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(3), pages 412-429, July.
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    1446. Nappi-Choulet, Ingrid & Maury, Tristan-Pierre, 2008. "A Spatiotemporal Autoregressive Price Index for the Paris Office Property Market," ESSEC Working Papers DR 08008, ESSEC Research Center, ESSEC Business School.
    1447. Ekrem ERDEM & Ahmet KOSEOGLU & Ali Gokhan YUCEL, 2016. "Testing the validity of the Feldstein-Horioka Puzzle: New evidence from structural breaks for Turkey," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(2(607), S), pages 17-26, Summer.
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    1450. Ludwig, Jens & Miller, Douglas L., 2006. "Does Head Start Improve Children's Life Chances? Evidence from a Regression Discontinuity Design," IZA Discussion Papers 2111, Institute of Labor Economics (IZA).
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    1452. Das, Mahamitra & Sarkar, Nityananda, 2019. "Revisiting the Anomalous Relationship between Inflation and REIT Returns in Presence of Structural Breaks: Empirical Evidence from the USA and the UK," MPRA Paper 95130, University Library of Munich, Germany, revised 05 Nov 2019.
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    1458. Nikeel Nishkar Kumar & Arvind Patel & Sean Kimpton & Antony Andrews, 2022. "Asymmetric reactions in the tourism‐led growth hypothesis," Australian Economic Papers, Wiley Blackwell, vol. 61(4), pages 661-677, December.
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    1. Bouhaddioui, Chafik & Ghoudi, Kilani, 2012. "Empirical processes for infinite variance autoregressive models," Journal of Multivariate Analysis, Elsevier, vol. 107(C), pages 319-335.
    2. Linton, Oliver & Seo, Myung Hwan & Whang, Yoon-Jae, 2023. "Testing stochastic dominance with many conditioning variables," Journal of Econometrics, Elsevier, vol. 235(2), pages 507-527.
    3. Mo Li & QiQi Lu, 2022. "Changepoint detection in autocorrelated ordinal categorical time series," Environmetrics, John Wiley & Sons, Ltd., vol. 33(7), November.
    4. Lee, Sangyeol & Meintanis, Simos G. & Pretorius, Charl, 2022. "Monitoring procedures for strict stationarity based on the multivariate characteristic function," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    5. Lu, Xiaohui & Zheng, Xu, 2020. "A goodness-of-fit test for copulas based on martingale transformation," Journal of Econometrics, Elsevier, vol. 215(1), pages 84-117.
    6. Zacharias Psaradakis & Marián Vávra, 2015. "A Quantile-based Test for Symmetry of Weakly Dependent Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(4), pages 587-598, July.
    7. Martínez Ibáñez, Oscar & Olmo, José, 2008. "A nonlinear threshold model for the dependence of extremes of stationary sequences," Working Papers 2072/5361, Universitat Rovira i Virgili, Department of Economics.
    8. Alejandra Cabaña & Enrique M. Cabaña & Marco Scavino, 2012. "Weak Convergence of Marked Empirical Processes for Focused Inference on AR(p) vs AR(p + 1) Stationary Time Series," Methodology and Computing in Applied Probability, Springer, vol. 14(3), pages 793-810, September.
    9. Baisuo Jin & Mong-Na Lo Huang & Baiqi Miao, 2011. "Testing for variance changes in autoregressive models with unknown order," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(5), pages 927-936, January.
    10. Leonie Selk & Natalie Neumeyer, 2013. "Testing for a Change of the Innovation Distribution in Nonparametric Autoregression: The Sequential Empirical Process Approach," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(4), pages 770-788, December.
    11. Rohmer, Tom, 2016. "Some results on change-point detection in cross-sectional dependence of multivariate data with changes in marginal distributions," Statistics & Probability Letters, Elsevier, vol. 119(C), pages 45-54.

  44. Bai, J., 1994. "Estimation of Structural Change Based on Wald-Type Statistics," Working papers 94-06, Massachusetts Institute of Technology (MIT), Department of Economics.

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    1. Perron, Pierre, 2020. "L'estimation de modèles avec changements structurels multiples," L'Actualité Economique, Société Canadienne de Science Economique, vol. 96(4), pages 789-837, Décembre.
    2. Badi H. Baltagi & Qu Feng & Chihwa Kao, 2015. "Estimation of Heterogeneous Panels with Structural Breaks," Center for Policy Research Working Papers 179, Center for Policy Research, Maxwell School, Syracuse University.

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    1. Eric Hillebrand & Gunther Schnabl & Yasemin Ulu, 2006. "Japanese Foreign Exchange Intervention and the Yen/Dollar Exchange Rate: A Simultaneous Equations Approach Using Realized Volatility," CESifo Working Paper Series 1766, CESifo.
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    3. Boldea, Otilia & Hall, Alastair R., 2013. "Estimation and inference in unstable nonlinear least squares models," Journal of Econometrics, Elsevier, vol. 172(1), pages 158-167.
    4. Mohitosh Kejriwal, 2020. "A Robust Sequential Procedure for Estimating the Number of Structural Changes in Persistence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(3), pages 669-685, June.
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    9. Alessandro De Gregorio & Stefano Iacus, 2007. "Change point estimation for the telegraph process observed at discrete times," UNIMI - Research Papers in Economics, Business, and Statistics unimi-1053, Universitá degli Studi di Milano.
    10. Kaddour Hadri & Yao Rao, 2008. "Panel Stationarity Test with Structural Breaks," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(2), pages 245-269, April.
    11. Bill Russell & Dooruj Rambaccussing, 2016. "Breaks and the Statistical Process of Inflation: The Case of the ‘Modern’ Phillips Curve," Dundee Discussion Papers in Economics 294, Economic Studies, University of Dundee.
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    13. Jiang, Feiyu & Zhao, Zifeng & Shao, Xiaofeng, 2023. "Time series analysis of COVID-19 infection curve: A change-point perspective," Journal of Econometrics, Elsevier, vol. 232(1), pages 1-17.
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    133. Alper Kara & Dilem Yildirim & G. Ipek Tunc, 2023. "Market efficiency in non-renewable resource markets: evidence from stationarity tests with structural changes," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 36(2), pages 279-290, June.
    134. Alper Kara & Dilem Yıldırım & Gül İpek Tunç, 2021. "Market Efficiency In Non-Renewable Resource Markets: Evidence From Stationarity Tests With Structural Changes," ERC Working Papers 2103, ERC - Economic Research Center, Middle East Technical University, revised Apr 2021.
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  46. Bai, J., 1993. "Testing for Parameter Constancy in Linear Regressions: Empirical Distribution Function Approach," Working papers 93-9, Massachusetts Institute of Technology (MIT), Department of Economics.

    Cited by:

    1. Mehmet Caner & Bruce E. Hansen, 1998. "Threshold Autoregressions with a Near Unit Root," Working Papers 9821, Department of Economics, Bilkent University.
    2. Christis Katsouris, 2023. "Structural Break Detection in Quantile Predictive Regression Models with Persistent Covariates," Papers 2302.05193, arXiv.org.
    3. Qu, Zhongjun, 2008. "Testing for structural change in regression quantiles," Journal of Econometrics, Elsevier, vol. 146(1), pages 170-184, September.
    4. Zhongjun Qu & Jungmo Yoon, 2011. "Nonparametric Estimation and Inference on Conditional Quantile Processes," Boston University - Department of Economics - Working Papers Series WP2011-059, Boston University - Department of Economics.
    5. Gebrenegus Ghilagaber, 2004. "Another Look at Chow's Test for the Equality of Two Heteroscedastic Regression Models," Quality & Quantity: International Journal of Methodology, Springer, vol. 38(1), pages 81-93, February.
    6. Zhang, Feipeng & Li, Qunhua, 2017. "A continuous threshold expectile model," Computational Statistics & Data Analysis, Elsevier, vol. 116(C), pages 49-66.
    7. Chandra, S. Ajay, 2009. "Testing the equality of error distributions from k independent GARCH models," Journal of Multivariate Analysis, Elsevier, vol. 100(6), pages 1245-1260, July.
    8. Chung-Ming Kuan & Christos Michalopoulos & Zhijie Xiao, 2017. "Quantile Regression on Quantile Ranges – A Threshold Approach," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(1), pages 99-119, January.
    9. Heejoon Han & Oliver Linton & Tatsushi Oka & Yoon-Jae Whang, 2014. "The cross-quantilogram: measuring quantile dependence and testing directional predictability between time series," CeMMAP working papers CWP06/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Dong Jin Lee, 2021. "Bootstrap tests for structural breaks when the regressors and the serially correlated error term are unstable," Bulletin of Economic Research, Wiley Blackwell, vol. 73(2), pages 212-229, April.
    11. Bai, Jushan & Ng, Serena, 2001. "A consistent test for conditional symmetry in time series models," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 225-258, July.
    12. Feipeng Zhang & Qunhua Li, 2023. "Segmented correspondence curve regression for quantifying covariate effects on the reproducibility of high‐throughput experiments," Biometrics, The International Biometric Society, vol. 79(3), pages 2272-2285, September.
    13. Delgado, Miguel A. & Stute, Winfried, 2008. "Distribution-free specification tests of conditional models," Journal of Econometrics, Elsevier, vol. 143(1), pages 37-55, March.
    14. Lu, Xiaohui & Zheng, Xu, 2020. "A goodness-of-fit test for copulas based on martingale transformation," Journal of Econometrics, Elsevier, vol. 215(1), pages 84-117.
    15. Hiroyuki Kawakatsu & Matthew R. Morey, 1999. "An Empirical Examination Of Financial Liberalization And The Efficiency Of Emerging Market Stock Prices," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 22(4), pages 385-411, December.
    16. Oka, Tatsushi & Qu, Zhongjun, 2011. "Estimating structural changes in regression quantiles," Journal of Econometrics, Elsevier, vol. 162(2), pages 248-267, June.
    17. Venkata Jandhyala & Stergios Fotopoulos & Ian MacNeill & Pengyu Liu, 2013. "Inference for single and multiple change-points in time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(4), pages 423-446, July.
    18. Juhl, Ted & Xiao, Zhijie, 2005. "A nonparametric test for changing trends," Journal of Econometrics, Elsevier, vol. 127(2), pages 179-199, August.
    19. Ping Yu & Qin Liao & Peter C.B. Phillips, 2019. "Inference and Specification Testing in Threshold Regression with Endogeneity," Cowles Foundation Discussion Papers 2209, Cowles Foundation for Research in Economics, Yale University.
    20. Torben G. Andersen & Viktor Todorov & Bo Zhou, 2023. "Real-Time Detection of Local No-Arbitrage Violations," Papers 2307.10872, arXiv.org.
    21. Shinn-Juh Lin & Jian Yang, 2000. "Testing Shifts in Financial Models with Conditional Heteroskedasticity: An Empirical Distribution Function Approach," Econometric Society World Congress 2000 Contributed Papers 0063, Econometric Society.
    22. Su, Liangjun & Xiao, Zhijie, 2008. "Testing for parameter stability in quantile regression models," Statistics & Probability Letters, Elsevier, vol. 78(16), pages 2768-2775, November.
    23. Jamie Emerson & Chihwa Kao, 2000. "Testing for Structural Change of a Time Trend Regression in Panel Data," Center for Policy Research Working Papers 15, Center for Policy Research, Maxwell School, Syracuse University.
    24. Delgado, Miguel A. & Farinas, Jose C. & Ruano, Sonia, 2002. "Firm productivity and export markets: a non-parametric approach," Journal of International Economics, Elsevier, vol. 57(2), pages 397-422, August.
    25. Jushan Bai & Serena Ng, 1998. "A Test for Conditional Symmetry in Time Series Models," Boston College Working Papers in Economics 410, Boston College Department of Economics.
    26. Hinich, Melvin J. & Foster, John & Wild, Phillip, 2006. "Structural change in macroeconomic time series: A complex systems perspective," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 136-150, March.
    27. Zhou, Mi & Wang, Huixia Judy & Tang, Yanlin, 2015. "Sequential change point detection in linear quantile regression models," Statistics & Probability Letters, Elsevier, vol. 100(C), pages 98-103.
    28. Kuan, Chung-Ming, 1998. "Tests for changes in models with a polynomial trend," Journal of Econometrics, Elsevier, vol. 84(1), pages 75-91, May.
    29. Cho, Jin Seo & White, Halbert, 2011. "Generalized runs tests for the IID hypothesis," Journal of Econometrics, Elsevier, vol. 162(2), pages 326-344, June.
    30. Mehmet Caner & Bruce E. Hansen, 2001. "Threshold Autoregression with a Unit Root," Econometrica, Econometric Society, vol. 69(6), pages 1555-1596, November.
    31. Yang, Jian, 2001. "Structural change tests under regression misspecifications," Economics Letters, Elsevier, vol. 70(3), pages 311-317, March.
    32. Andres Sagner, 2020. "High Dimensional Quantile Factor Analysis," Working Papers Central Bank of Chile 886, Central Bank of Chile.
    33. Lee, Sangyeol & Oh, Haejune, 2015. "Entropy test and residual empirical process for autoregressive conditional duration models," Computational Statistics & Data Analysis, Elsevier, vol. 86(C), pages 1-12.
    34. Li, Dong & Li, Qi, 2010. "Nonparametric/semiparametric estimation and testing of econometric models with data dependent smoothing parameters," Journal of Econometrics, Elsevier, vol. 157(1), pages 179-190, July.

  47. Hu, Teh-wei & Bai, Jushan & Barnett, Paul G., 1992. "the Impact of 1989 California Major Anti-Smoking Legislation Cigarette Consumption: Three Years Later," Department of Economics, Working Paper Series qt280289bg, Department of Economics, Institute for Business and Economic Research, UC Berkeley.

    Cited by:

    1. Hsieh, Chee-Ruey & Yen, Lee-Lan & Liu, Jin-Tan & Chyongchiou Jeng Lin, 1996. "Smoking, health knowledge, and anti-smoking campaigns: An empirical study in Taiwan," Journal of Health Economics, Elsevier, vol. 15(1), pages 87-104, February.

  48. Hu, Tah-wei & Bai, Jushan & Keeler, Theodore E. & Barnett, Paul G., 1991. "the Impact of a Large Tax Increase on Cigarette Consumption: The Case of California," Department of Economics, Working Paper Series qt3v9919fh, Department of Economics, Institute for Business and Economic Research, UC Berkeley.

    Cited by:

    1. Robert Kaplan, 1994. "Using quality of life information to set priorities in health policy," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 33(1), pages 121-163, August.
    2. Johnson, Ida M. & Sigler, Robert T., 2000. "Public perceptions The stability of the public's endorsements of the definition and criminalization of the abuse of women," Journal of Criminal Justice, Elsevier, vol. 28(3), pages 165-179.

  49. Bai, Jushan, 1991. "Weak convergence of the sequential empirical processes of residuals in ARMA models," MPRA Paper 32915, University Library of Munich, Germany, revised 06 Jul 1993.

    Cited by:

    1. Marc Hallin & Ramon van den Akker & Bas Werker, 2009. "A class of Simple Semiparametrically Efficient Rank-Based Unit Root Tests," Working Papers ECARES 2009_001, ULB -- Universite Libre de Bruxelles.
    2. Òscar Jordà & Alan M. Taylor, 2011. "Performance Evaluation of Zero Net-Investment Strategies," NBER Working Papers 17150, National Bureau of Economic Research, Inc.

Articles

  1. Bai, Jushan, 2024. "Likelihood approach to dynamic panel models with interactive effects," Journal of Econometrics, Elsevier, vol. 240(1).
    See citations under working paper version above.
  2. Bai, Jushan & Choi, Sung Hoon & Liao, Yuan, 2024. "Standard errors for panel data models with unknown clusters," Journal of Econometrics, Elsevier, vol. 240(2).
    See citations under working paper version above.
  3. Duan, Jiangtao & Bai, Jushan & Han, Xu, 2023. "Quasi-maximum likelihood estimation of break point in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 233(1), pages 209-236.
    See citations under working paper version above.
  4. Bai, Jushan & Ng, Serena, 2023. "Approximate factor models with weaker loadings," Journal of Econometrics, Elsevier, vol. 235(2), pages 1893-1916.
    See citations under working paper version above.
  5. Cahan, Ercument & Bai, Jushan & Ng, Serena, 2023. "Factor-based imputation of missing values and covariances in panel data of large dimensions," Journal of Econometrics, Elsevier, vol. 233(1), pages 113-131.
    See citations under working paper version above.
  6. Ando, Tomohiro & Bai, Jushan & Li, Kunpeng, 2022. "Bayesian and maximum likelihood analysis of large-scale panel choice models with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 230(1), pages 20-38.

    Cited by:

    1. Liang Chen & Minyuan Zhang, 2023. "Common Correlated Effects Estimation of Nonlinear Panel Data Models," Papers 2304.13199, arXiv.org.

  7. Jushan Bai & Serena Ng, 2021. "Matrix Completion, Counterfactuals, and Factor Analysis of Missing Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1746-1763, October.
    See citations under working paper version above.
  8. Bai, Jushan & Li, Kunpeng, 2021. "Dynamic spatial panel data models with common shocks," Journal of Econometrics, Elsevier, vol. 224(1), pages 134-160.

    Cited by:

    1. Anna Gloria Bill`e & Marco Rogna, 2020. "The Effect of Weather Conditions on Fertilizer Applications: A Spatial Dynamic Panel Data Analysis," Papers 2002.03922, arXiv.org, revised Dec 2020.
    2. Ting Fung Ma & Fangfang Wang & Jun Zhu & Anthony R. Ives & Katarzyna E. Lewińska, 2023. "Scalable Semiparametric Spatio-temporal Regression for Large Data Analysis," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 28(2), pages 279-298, June.
    3. Manuela Fritz, 2022. "Wave after wave: determining the temporal lag in Covid-19 infections and deaths using spatial panel data from Germany," Journal of Spatial Econometrics, Springer, vol. 3(1), pages 1-30, December.
    4. Camilla Mastromarco & Laura Serlenga & Yongcheol Shin, 2023. "Regional Productivity Network in the EU," CESifo Working Paper Series 10404, CESifo.
    5. Cui, Guowei & Sarafidis, Vasilis & Yamagata, Takashi, 2020. "IV Estimation of Spatial Dynamic Panels with Interactive Effects: Large Sample Theory and an Application on Bank Attitude Toward Risk," MPRA Paper 102488, University Library of Munich, Germany.
    6. Chen, Jia & Shin, Yongcheol & Zheng, Chaowen, 2022. "Estimation and inference in heterogeneous spatial panels with a multifactor error structure," Journal of Econometrics, Elsevier, vol. 229(1), pages 55-79.
    7. Füss, Roland & Ruf, Daniel, 2022. "Information precision and return co-movements in private commercial real estate markets," Journal of Banking & Finance, Elsevier, vol. 138(C).
    8. Ye Yang & Osman Doğan & Süleyman Taşpınar, 2023. "Observed-data DIC for spatial panel data models," Empirical Economics, Springer, vol. 64(3), pages 1281-1314, March.
    9. Higgins, Ayden & Martellosio, Federico, 2023. "Shrinkage estimation of network spillovers with factor structured errors," Journal of Econometrics, Elsevier, vol. 233(1), pages 66-87.
    10. Xiaowen Dai & Libin Jin, 2021. "Minimum distance quantile regression for spatial autoregressive panel data models with fixed effects," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-13, December.
    11. Ando, Tomohiro & Li, Kunpeng & Lu, Lina, 2023. "A spatial panel quantile model with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 232(1), pages 191-213.
    12. Hanzhi Zhang & Qiang Liang & Yu Li & Pengpeng Gao, 2023. "Promoting eco-tourism for the green economic recovery in ASEAN," Economic Change and Restructuring, Springer, vol. 56(3), pages 2021-2036, June.

  9. Jushan Bai & Sung Hoon Choi & Yuan Liao, 2021. "Feasible generalized least squares for panel data with cross-sectional and serial correlations," Empirical Economics, Springer, vol. 60(1), pages 309-326, January.
    See citations under working paper version above.
  10. Tomohiro Ando & Jushan Bai, 2020. "Quantile Co-Movement in Financial Markets: A Panel Quantile Model With Unobserved Heterogeneity," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(529), pages 266-279, January.
    See citations under working paper version above.
  11. Bai, Jushan & Han, Xu & Shi, Yutang, 2020. "Estimation and inference of change points in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 219(1), pages 66-100.

    Cited by:

    1. Urga, Giovanni & Wang, Fa, 2022. "Estimation and Inference for High Dimensional Factor Model with Regime Switching," MPRA Paper 117012, University Library of Munich, Germany, revised 10 Apr 2023.
    2. Duan, Jiangtao & Bai, Jushan & Han, Xu, 2023. "Quasi-maximum likelihood estimation of break point in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 233(1), pages 209-236.
    3. Wang, Lu & Zhou, Ruichao & Wu, Jianhong, 2021. "Determining the number of breaks in large dimensional factor models with structural changes," Economics Letters, Elsevier, vol. 199(C).
    4. Wang, Lu & Wu, Jianhong, 2022. "Estimation of high-dimensional factor models with multiple structural changes," Economic Modelling, Elsevier, vol. 108(C).
    5. Urga, Giovanni & Wang, Fa, 2022. "Estimation and inference for high dimensional factor model with regime switching," MPRA Paper 113172, University Library of Munich, Germany.
    6. Wu, Jianhong, 2021. "Estimation of high dimensional factor model with multiple threshold-type regime shifts," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).
    7. Bai, Jushan & Duan, Jiangtao & Han, Xu, 2024. "The likelihood ratio test for structural changes in factor models," Journal of Econometrics, Elsevier, vol. 238(2).
    8. Cui, Junfeng & Wang, Guanghui & Zou, Changliang & Wang, Zhaojun, 2023. "Change-point testing for parallel data sets with FDR control," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    9. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.
    10. Ma, Chenchen & Tu, Yundong, 2023. "Group fused Lasso for large factor models with multiple structural breaks," Journal of Econometrics, Elsevier, vol. 233(1), pages 132-154.

  12. Bai, Jushan & Ng, Serena, 2019. "Rank regularized estimation of approximate factor models," Journal of Econometrics, Elsevier, vol. 212(1), pages 78-96.

    Cited by:

    1. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    2. Jonas Krampe & Luca Margaritella, 2021. "Factor Models with Sparse VAR Idiosyncratic Components," Papers 2112.07149, arXiv.org, revised May 2022.
    3. Jushan Bai & Serena Ng, 2021. "Approximate Factor Models with Weaker Loadings," Papers 2109.03773, arXiv.org, revised Mar 2023.
    4. Jungjun Choi & Ming Yuan, 2024. "High Dimensional Factor Analysis with Weak Factors," Papers 2402.05789, arXiv.org.
    5. Hörmann, Siegfried & Jammoul, Fatima, 2022. "Consistently recovering the signal from noisy functional data," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    6. Miao, Ke & Phillips, Peter C.B. & Su, Liangjun, 2023. "High-dimensional VARs with common factors," Journal of Econometrics, Elsevier, vol. 233(1), pages 155-183.
    7. 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.
    8. Freyaldenhoven, Simon, 2022. "Factor models with local factors — Determining the number of relevant factors," Journal of Econometrics, Elsevier, vol. 229(1), pages 80-102.
    9. Jie Wei & Yonghui Zhang, 2023. "Does Principal Component Analysis Preserve the Sparsity in Sparse Weak Factor Models?," Papers 2305.05934, arXiv.org.
    10. Guido W. Imbens & Davide Viviano, 2023. "Identification and Inference for Synthetic Controls with Confounding," Papers 2312.00955, arXiv.org.
    11. Orlando Joaqui-Barandica & Diego F. Manotas-Duque & Jorge M. Uribe-Gil, 2021. ""Commonality, macroeconomic factors and banking profitability"," IREA Working Papers 202113, University of Barcelona, Research Institute of Applied Economics, revised Jun 2021.
    12. Liang Chen & Juan Jose Dolado & Jesus Gonzalo, 2019. "Quantile Factor Models," Papers 1911.02173, arXiv.org, revised Sep 2020.
    13. 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.
    14. Hong, Shengjie & Su, Liangjun & Jiang, Tao, 2023. "Profile GMM estimation of panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 235(2), pages 927-948.
    15. Jushan Bai & Serena Ng, 2021. "Matrix Completion, Counterfactuals, and Factor Analysis of Missing Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1746-1763, October.
    16. 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.
    17. Jushan Bai & Serena Ng, 2020. "Simpler Proofs for Approximate Factor Models of Large Dimensions," Papers 2008.00254, arXiv.org.
    18. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    19. Serena Ng & Susannah Scanlan, 2023. "Constructing High Frequency Economic Indicators by Imputation," Papers 2303.01863, arXiv.org, revised Oct 2023.
    20. Rishab Guha & Serena Ng, 2019. "A Machine Learning Analysis of Seasonal and Cyclical Sales in Weekly Scanner Data," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 403-436, National Bureau of Economic Research, Inc.

  13. Tomohiro Ando & Jushan Bai, 2018. "Selecting the regularization parameters in high-dimensional panel data models: Consistency and efficiency," Econometric Reviews, Taylor & Francis Journals, vol. 37(3), pages 183-211, March.

    Cited by:

    1. Ando, Tomohiro & Bai, Jushan, 2018. "Quantile co-movement in financial markets: A panel quantile model with unobserved heterogeneity," MPRA Paper 88765, University Library of Munich, Germany.

  14. Tomohiro Ando & Jushan Bai, 2017. "Clustering Huge Number of Financial Time Series: A Panel Data Approach With High-Dimensional Predictors and Factor Structures," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 1182-1198, July.

    Cited by:

    1. Nusrat Jafrin & Muhammad Mehedi Masud & Abu Naser Mohammad Saif & Masnun Mahi & Moriam Khanam, 2021. "A panel data estimation of the determinants of life expectancy in selected SAARC countries," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(4), pages 69-87.
    2. Riccardo Borghi & Eric Hillebrand & Jakob Mikkelsen & Giovanni Urga, 2018. "The dynamics of factor loadings in the cross-section of returns," CREATES Research Papers 2018-38, Department of Economics and Business Economics, Aarhus University.
    3. Xiaorong Yang & Jia Chen & Degui Li & Runze Li, 2023. "Functional-Coefficient Quantile Regression for Panel Data with Latent Group Structure," Papers 2303.13218, arXiv.org.
    4. Guohua Feng & Jiti Gao & Fei Liu & Bin Peng, 2024. "Estimation and Inference for Three-Dimensional Panel Data Models," Papers 2404.08365, arXiv.org.
    5. Camacho, Maximo & Caro Navarro, Ángela & Peña, Daniel, 2020. "What do international energy prices have in common after taking into account the key drivers?," DES - Working Papers. Statistics and Econometrics. WS 31647, Universidad Carlos III de Madrid. Departamento de Estadística.
    6. Matteo Barigozzi & Christian T. Brownlees, 2013. "Nets: Network estimation for time series," Economics Working Papers 1391, Department of Economics and Business, Universitat Pompeu Fabra.
    7. Simon Freyaldenhoven, 2020. "Identification Through Sparsity in Factor Models," Working Papers 20-25, Federal Reserve Bank of Philadelphia.
    8. Alessio Farcomeni & Monia Ranalli & Sara Viviani, 2021. "Dimension reduction for longitudinal multivariate data by optimizing class separation of projected latent Markov models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(2), pages 462-480, June.
    9. Tingting Cheng & Chaohua Dong & Jiti Gao & Oliver Linton, 2022. "GMM Estimation for High-Dimensional Panel Data Models," Monash Econometrics and Business Statistics Working Papers 11/22, Monash University, Department of Econometrics and Business Statistics.
    10. Zhaoxing Gao & Ruey S. Tsay, 2021. "Divide-and-Conquer: A Distributed Hierarchical Factor Approach to Modeling Large-Scale Time Series Data," Papers 2103.14626, arXiv.org.
    11. Esther Acquah & Lorenzo Carbonari & Alessio Farcomeni & Giovanni Trovato, 2023. "Institutions and economic development: new measurements and evidence," Empirical Economics, Springer, vol. 65(4), pages 1693-1728, October.
    12. Camacho, Maximo & Lopez-Buenache, German, 2023. "Factor models for large and incomplete data sets with unknown group structure," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1205-1220.
    13. Ando, Tomohiro & Bai, Jushan & Li, Kunpeng, 2022. "Bayesian and maximum likelihood analysis of large-scale panel choice models with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 230(1), pages 20-38.
    14. Alonso, Andrés M. & Galeano, Pedro & Peña, Daniel, 2020. "A robust procedure to build dynamic factor models with cluster structure," Journal of Econometrics, Elsevier, vol. 216(1), pages 35-52.
    15. Yoshimasa Uematsu & Takashi Yamagata, 2020. "Inference in Weak Factor Models," ISER Discussion Paper 1080, Institute of Social and Economic Research, Osaka University.
    16. Bagnara, Matteo & Goodarzi, Milad, 2023. "Clustering-based sector investing," SAFE Working Paper Series 397, Leibniz Institute for Financial Research SAFE.
    17. Coroneo, Laura & Jackson, Laura E. & Owyang, Michael T., 2020. "International Stock Comovements with Endogenous Clusters," Journal of Economic Dynamics and Control, Elsevier, vol. 116(C).
    18. 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.
    19. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    20. In Choi & Rui Lin & Yongcheol Shin, 2020. "Canonical Correlation-based Model Selection for the Multilevel Factors," Working Papers 2008, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    21. Bin Peng & Liangjun Su & Joakim Westerlund & Yanrong Yang, 2021. "Interactive Effects Panel Data Models with General Factors and Regressors," Monash Econometrics and Business Statistics Working Papers 23/21, Monash University, Department of Econometrics and Business Statistics.
    22. Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2023. "Inference of Grouped Time-Varying Network Vector Autoregression Models," Monash Econometrics and Business Statistics Working Papers 5/23, Monash University, Department of Econometrics and Business Statistics.
    23. Denis Chetverikov & Elena Manresa, 2022. "Spectral and post-spectral estimators for grouped panel data models," Papers 2212.13324, arXiv.org, revised Dec 2022.
    24. Jiti Gao & Fei Liu & Bin peng, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Monash Econometrics and Business Statistics Working Papers 44/20, Monash University, Department of Econometrics and Business Statistics.
    25. Arturas Juodis & Yiannis Karavias & Vasilis Sarafidis, 2020. "A Homogeneous Approach to Testing for Granger Non-Causality in Heterogeneous Panels," Monash Econometrics and Business Statistics Working Papers 32/20, Monash University, Department of Econometrics and Business Statistics.
    26. Marcin Jaskowski & Michael McAleer, 2018. "Spurious Cross-Sectional Dependence in Credit Spread Changes," Documentos de Trabajo del ICAE 2018-21, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    27. Chan, Joshua C.C. & Eisenstat, Eric & Strachan, Rodney W., 2020. "Reducing the state space dimension in a large TVP-VAR," Journal of Econometrics, Elsevier, vol. 218(1), pages 105-118.
    28. Pierpaolo D’Urso & Livia Giovanni & Riccardo Massari, 2021. "Trimmed fuzzy clustering of financial time series based on dynamic time warping," Annals of Operations Research, Springer, vol. 299(1), pages 1379-1395, April.
    29. Fei Liu & Jiti Gao & Yanrong Yang, 2019. "Nonparametric Estimation in Panel Data Models with Heterogeneity and Time Varyingness," Monash Econometrics and Business Statistics Working Papers 24/19, Monash University, Department of Econometrics and Business Statistics.
    30. Ando, Tomohiro & Bai, Jushan, 2021. "Large-scale generalized linear longitudinal data models with grouped patterns of unobserved heterogeneity," MPRA Paper 111431, University Library of Munich, Germany.
    31. Freyaldenhoven, Simon, 2022. "Factor models with local factors — Determining the number of relevant factors," Journal of Econometrics, Elsevier, vol. 229(1), pages 80-102.
    32. Jie Wei & Yonghui Zhang, 2023. "Does Principal Component Analysis Preserve the Sparsity in Sparse Weak Factor Models?," Papers 2305.05934, arXiv.org.
    33. Guohua Feng & Jiti Gao & Bin Peng, 2021. "Productivity Convergence in Manufacturing: A Hierarchical Panel Data Approach," Monash Econometrics and Business Statistics Working Papers 16/21, Monash University, Department of Econometrics and Business Statistics.
    34. Feng, Guohua & Gao, Jiti & Peng, Bin, 2022. "An integrated panel data approach to modelling economic growth," Journal of Econometrics, Elsevier, vol. 228(2), pages 379-397.
    35. Choi, Sung Hoon & Kim, Donggyu, 2023. "Large volatility matrix analysis using global and national factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1917-1933.
    36. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Papers 2012.03182, arXiv.org, revised Nov 2021.
    37. Yufeng Mao & Bin Peng & Mervyn J Silvapulle & Param Silvapulle & Yanrong Yang, 2021. "Decomposition of Bilateral Trade Flows Using a Three-Dimensional Panel Data Model," Monash Econometrics and Business Statistics Working Papers 7/21, Monash University, Department of Econometrics and Business Statistics.
    38. Kaizheng Wang & Xiao Xu & Xun Yu Zhou, 2022. "Variable Clustering via Distributionally Robust Nodewise Regression," Papers 2212.07944, arXiv.org, revised Dec 2022.
    39. Zhang, Yingying & Wang, Huixia Judy & Zhu, Zhongyi, 2019. "Quantile-regression-based clustering for panel data," Journal of Econometrics, Elsevier, vol. 213(1), pages 54-67.
    40. Yufeng Mao & Bin Peng & Mervyn Silvapulle & Param Silvapulle & Yanrong Yang, 2021. "Decomposition of Bilateral Trade Flows Using a Three-Dimensional Panel Data Model," Papers 2101.06805, arXiv.org.
    41. Georg Keilbar & Juan M. Rodriguez-Poo & Alexandra Soberon & Weining Wang, 2022. "A semiparametric approach for interactive fixed effects panel data models," Papers 2201.11482, arXiv.org, revised Mar 2023.
    42. Rodríguez-Caballero, Carlos Vladimir, 2022. "Energy consumption and GDP: a panel data analysis with multi-level cross-sectional dependence," Econometrics and Statistics, Elsevier, vol. 23(C), pages 128-146.
    43. Pedro Galeano & Daniel Peña, 2019. "Data science, big data and statistics," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 289-329, June.
    44. Fernandez, Julian, 2020. "Exchange Rate Uncertainty and the Interest Rate Parity," MPRA Paper 116010, University Library of Munich, Germany, revised 2022.
    45. Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2023. "Estimation of Grouped Time-Varying Network Vector Autoregression Models," Papers 2303.10117, arXiv.org, revised Mar 2024.
    46. Mahsa Ghorbani & Edwin K. P. Chong, 2022. "A dimension reduction method for stock-price prediction using multiple predictors," Operational Research, Springer, vol. 22(3), pages 2859-2878, July.
    47. Ando, Tomohiro & Li, Kunpeng & Lu, Lina, 2023. "A spatial panel quantile model with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 232(1), pages 191-213.
    48. Antoine A. Djogbenou, 2024. "Identifying oil price shocks with global, developed, and emerging latent real economy activity factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 128-149, January.
    49. Camacho, Maximo & Caro, Angela & Peña, Daniel, 2023. "What drives industrial energy prices?," Economic Modelling, Elsevier, vol. 120(C).

  15. Bai, Jushan & Liao, Yuan, 2017. "Inferences in panel data with interactive effects using large covariance matrices," Journal of Econometrics, Elsevier, vol. 200(1), pages 59-78.

    Cited by:

    1. Tingting Cheng & Chaohua Dong & Jiti Gao & Oliver Linton, 2022. "GMM Estimation for High-Dimensional Panel Data Models," Monash Econometrics and Business Statistics Working Papers 11/22, Monash University, Department of Econometrics and Business Statistics.
    2. Daniel Czarnowske & Amrei Stammann, 2020. "Inference in Unbalanced Panel Data Models with Interactive Fixed Effects," Papers 2004.03414, arXiv.org.
    3. Marco Avarucci & Paolo Zaffaroni, 2019. "Robust Nearly-Efficient Estimation of Large Panels with Factor Structures," Papers 1902.11181, arXiv.org.
    4. Jianqing Fan & Ricardo Masini & Marcelo C. Medeiros, 2021. "Bridging factor and sparse models," Papers 2102.11341, arXiv.org, revised Sep 2022.
    5. Ayden Higgins & Federico Martellosio, 2019. "Shrinkage Estimation of Network Spillovers with Factor Structured Errors," Papers 1909.02823, arXiv.org, revised Nov 2021.
    6. Saman Banafti & Tae-Hwy Lee, 2023. "Inferential Theory for Granular Instrumental Variables in High Dimensions," Working Papers 202308, University of California at Riverside, Department of Economics.
    7. Liu, Hao, 2019. "The communication and European Regional economic growth: The interactive fixed effects approach," Economic Modelling, Elsevier, vol. 83(C), pages 299-311.
    8. Feng, Guohua & Peng, Bin & Su, Liangjun & Yang, Thomas Tao, 2019. "Semi-parametric single-index panel data models with interactive fixed effects: Theory and practice," Journal of Econometrics, Elsevier, vol. 212(2), pages 607-622.
    9. Jushan Bai & Sung Hoon Choi & Yuan Liao, 2019. "Feasible Generalized Least Squares for Panel Data with Cross-sectional and Serial Correlations," Papers 1910.09004, arXiv.org, revised Aug 2020.
    10. Chaohua Dong & Jiti Gao & Bin Peng, 2018. "Varying-coefficient panel data models with partially observed factor structure," Monash Econometrics and Business Statistics Working Papers 1/18, Monash University, Department of Econometrics and Business Statistics.
    11. Higgins, Ayden & Martellosio, Federico, 2023. "Shrinkage estimation of network spillovers with factor structured errors," Journal of Econometrics, Elsevier, vol. 233(1), pages 66-87.
    12. Guowei Cui & Kazuhiko Hayakawa & Shuichi Nagata & Takashi Yamagata, 2018. "A robust approach to heteroskedasticity, error serial correlation and slope heterogeneity for large linear panel data models with interactive effects," ISER Discussion Paper 1037r, Institute of Social and Economic Research, Osaka University, revised Jun 2019.

  16. Jushan Bai & Xu Han, 2016. "Structural Changes in High Dimensional Factor Models," Frontiers of Economics in China-Selected Publications from Chinese Universities, Higher Education Press, vol. 11(1), pages 9-39, March.

    Cited by:

    1. Matteo Barigozzi & Daniele Massacci, 2022. "Modelling Large Dimensional Datasets with Markov Switching Factor Models," Papers 2210.09828, arXiv.org, revised Dec 2023.
    2. Duan, Jiangtao & Bai, Jushan & Han, Xu, 2023. "Quasi-maximum likelihood estimation of break point in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 233(1), pages 209-236.
    3. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Boston University - Department of Economics - Working Papers Series WP2019-02, Boston University - Department of Economics.
    4. Duván Humberto Cataño & Carlos Vladimir Rodríguez-Caballero & Daniel Peña, 2019. "Wavelet Estimation for Dynamic Factor Models with Time-Varying Loadings," CREATES Research Papers 2019-23, Department of Economics and Business Economics, Aarhus University.
    5. Bai, Jushan & Han, Xu & Shi, Yutang, 2020. "Estimation and inference of change points in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 219(1), pages 66-100.
    6. Baltagi, Badi H. & Kao, Chihwa & Wang, Fa, 2021. "Estimating and testing high dimensional factor models with multiple structural changes," Journal of Econometrics, Elsevier, vol. 220(2), pages 349-365.
    7. Daniel Wochner, 2020. "Dynamic Factor Trees and Forests – A Theory-led Machine Learning Framework for Non-Linear and State-Dependent Short-Term U.S. GDP Growth Predictions," KOF Working papers 20-472, KOF Swiss Economic Institute, ETH Zurich.

  17. Jushan Bai & Peng Wang, 2016. "Econometric Analysis of Large Factor Models," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 53-80, October.

    Cited by:

    1. Trucíos Maza, Carlos César & Mazzeu, João H. G. & Hallin, Marc & Hotta, Luiz Koodi & Pereira, Pedro L. Valls & Zevallos, Mauricio, 2019. "Forecasting conditional covariance matrices in high-dimensional time series: a general dynamic factor approach," Textos para discussão 505, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    2. Mingli Chen & Iv'an Fern'andez-Val & Martin Weidner, 2014. "Nonlinear Factor Models for Network and Panel Data," Papers 1412.5647, arXiv.org, revised Oct 2019.
    3. Carlos Cesar Trucios-Maza & João H. G Mazzeu & Luis K. Hotta & Pedro L. Valls Pereira & Marc Hallin, 2019. "On the robustness of the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting," Working Papers ECARES 2019-32, ULB -- Universite Libre de Bruxelles.
    4. Ivan Fernandez-Val & Martin Weidner, 2017. "Fixed effect estimation of large T panel data models," CeMMAP working papers 42/17, Institute for Fiscal Studies.
    5. Ivan Fernandez-Val & Martin Weidner, 2018. "Fixed effect estimation of large T panel data models," CeMMAP working papers CWP22/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Vasilis Sarafidis & Tom Wansbeek, 2020. "Celebrating 40 Years of Panel Data Analysis: Past, Present and Future," Monash Econometrics and Business Statistics Working Papers 6/20, Monash University, Department of Econometrics and Business Statistics.
    7. Norkutė, Milda & Sarafidis, Vasilis & Yamagata, Takashi & Cui, Guowei, 2021. "Instrumental variable estimation of dynamic linear panel data models with defactored regressors and a multifactor error structure," Journal of Econometrics, Elsevier, vol. 220(2), pages 416-446.
    8. Sokbae Lee & Yuan Liao & Myung Hwan Seo & Youngki Shin, 2019. "Factor-Driven Two-Regime Regression," Working Paper Series no128, Institute of Economic Research, Seoul National University.
    9. Steven Campbell & Ting-Kam Leonard Wong, 2022. "Efficient Convex PCA with applications to Wasserstein geodesic PCA and ranked data," Papers 2211.02990, arXiv.org, revised Aug 2023.
    10. Wang,Dieter, 2021. "Natural Capital and Sovereign Bonds," Policy Research Working Paper Series 9606, The World Bank.
    11. Xiao Huang, 2023. "Composite Quantile Factor Models," Papers 2308.02450, arXiv.org.
    12. Davide Ferrari & Francesco Ravazzolo & Joaquin Vespignani, 2021. "Forecasting Energy Commodity Prices: A Large Global Dataset Sparse Approach," BEMPS - Bozen Economics & Management Paper Series BEMPS83, Faculty of Economics and Management at the Free University of Bozen.
    13. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," PSE Working Papers halshs-02262202, HAL.
    14. He, Yong & Kong, Xinbing & Trapani, Lorenzo & Yu, Long, 2023. "One-way or two-way factor model for matrix sequences?," Journal of Econometrics, Elsevier, vol. 235(2), pages 1981-2004.
    15. Jia Chen Author-Name-First: Jia & Yongcheol Shin & Chaowen Zheng, 2023. "Dynamic Quantile Panel Data Models with Interactive Effects," Economics Discussion Papers em-dp2023-06, Department of Economics, University of Reading.
    16. Trucíos, Carlos & Mazzeu, João H.G. & Hotta, Luiz K. & Valls Pereira, Pedro L. & Hallin, Marc, 2021. "Robustness and the general dynamic factor model with infinite-dimensional space: Identification, estimation, and forecasting," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1520-1534.
    17. Li, Yan & Gao, Zhigen & Huang, Wei & Guo, Jianhua, 2023. "Matrix-variate data analysis by two-way factor model with replicated observations," Statistics & Probability Letters, Elsevier, vol. 202(C).
    18. Hugo Freeman & Martin Weidner, 2021. "Linear Panel Regressions with Two-Way Unobserved Heterogeneity," Papers 2109.11911, arXiv.org, revised Aug 2022.
    19. Dimitar EFTIMOSKI, 2019. "Improving Short-Term Forecasting of Macedonian GDP: Comparing the Factor Model with the Macroeconomic Structural Equation Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 32-53, June.
    20. Maldonado, Javier & Ruiz Ortega, Esther, 2017. "Accurate Subsampling Intervals of Principal Components Factors," DES - Working Papers. Statistics and Econometrics. WS 23974, Universidad Carlos III de Madrid. Departamento de Estadística.
    21. 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.
    22. Beyhum, Jad & Gautier, Eric, 2021. "Factor and factor loading augmented estimators for panel regression," TSE Working Papers 21-1219, Toulouse School of Economics (TSE).
    23. 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.
    24. Christian Glocker & Serguei Kaniovski, 2020. "Macroeconometric Forecasting Using a Cluster of Dynamic Factor Models," WIFO Working Papers 614, WIFO.
    25. Thomaidis, Nikolaos S. & Christodoulou, Theodoros & Santos-Alamillos, Francisco J., 2023. "Handling the risk dimensions of wind energy generation," Applied Energy, Elsevier, vol. 339(C).
    26. Vidal-Llana, Xenxo & Uribe, Jorge M. & Guillén, Montserrat, 2023. "European stock market volatility connectedness: The role of country and sector membership," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    27. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers halshs-02262202, HAL.
    28. Yuki Takara & Shingo Takagi, 2023. "An empirical approach to measure unobserved cultural relations using music trade data," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 47(2), pages 205-245, June.
    29. 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.
    30. Ekvall, Karl Oskar, 2022. "Targeted principal components regression," Journal of Multivariate Analysis, Elsevier, vol. 190(C).
    31. Philipp Gersing & Christoph Rust & Manfred Deistler, 2023. "Weak Factors are Everywhere," Papers 2307.10067, arXiv.org, revised Jan 2024.
    32. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
    33. Daniel Wochner, 2020. "Dynamic Factor Trees and Forests – A Theory-led Machine Learning Framework for Non-Linear and State-Dependent Short-Term U.S. GDP Growth Predictions," KOF Working papers 20-472, KOF Swiss Economic Institute, ETH Zurich.
    34. Francisco Corona & Graciela Gonz'alez-Far'ias & Jes'us L'opez-P'erez, 2021. "A nowcasting approach to generate timely estimates of Mexican economic activity: An application to the period of COVID-19," Papers 2101.10383, arXiv.org.
    35. Matthew Harding & Carlos Lamarche & Chris Muris, 2022. "Estimation of a Factor-Augmented Linear Model with Applications Using Student Achievement Data," Papers 2203.03051, arXiv.org.
    36. Lukoianove, Tatiana & Agarwal, James & Osiyevskyy, Oleksiy, 2022. "Modeling a country's political environment using dynamic factor analysis (DFA): A new methodology for IB research," Journal of World Business, Elsevier, vol. 57(5).
    37. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers 2019-4, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.

  18. Jushan Bai & Badi Baltagi & Hashem Pesaran, 2016. "Cross‐Sectional Dependence in Panel Data Models: A Special Issue," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 1-3, January.

    Cited by:

    1. Paulo M.M. Rodrigues & Matei Demetrescu, 2022. "Cross-Sectional Error Dependence in Panel Quantile Regressions," Working Papers w202213, Banco de Portugal, Economics and Research Department.
    2. Demetrescu, Matei & Hosseinkouchack, Mehdi & Rodrigues, Paulo M. M., 2023. "Tests of no cross-sectional error dependence in panel quantile regressions," Ruhr Economic Papers 1041, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    3. Aslanidis, Nektarios & Bariviera, Aurelio F. & Perez-Laborda, Alejandro, 2021. "Are cryptocurrencies becoming more interconnected?," Economics Letters, Elsevier, vol. 199(C).
    4. Qi Li & Vasilis Sarafidis & Joakim Westerlund, 2021. "Essays in honor of Professor Badi H Baltagi," Empirical Economics, Springer, vol. 60(1), pages 1-11, January.
    5. Badi H. Baltagi & Sophia Ding & Peter H. Egger, 2022. "A Panel Data Model with Generalized Higher-Order Network Effects," Advances in Econometrics, in: Essays in Honor of M. Hashem Pesaran: Panel Modeling, Micro Applications, and Econometric Methodology, volume 43, pages 9-35, Emerald Group Publishing Limited.
    6. Li, Qi & Sarafidis, Vasilis & Westerlund, Joakim, 2020. "Essays in Honor of Professor Badi H Baltagi: Editorial," MPRA Paper 104751, University Library of Munich, Germany.

  19. Jushan Bai & Kunpeng Li, 2016. "Maximum Likelihood Estimation and Inference for Approximate Factor Models of High Dimension," The Review of Economics and Statistics, MIT Press, vol. 98(2), pages 298-309, May.
    See citations under working paper version above.
  20. Tomohiro Ando & Jushan Bai, 2016. "Panel Data Models with Grouped Factor Structure Under Unknown Group Membership," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 163-191, January.
    See citations under working paper version above.
  21. Jushan Bai & Jianqing Fan & Ruey Tsay, 2016. "Special Issue on Big Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 487-488, October.

    Cited by:

    1. Huck, Nicolas, 2019. "Large data sets and machine learning: Applications to statistical arbitrage," European Journal of Operational Research, Elsevier, vol. 278(1), pages 330-342.

  22. Jushan Bai & Kunpeng Li & Lina Lu, 2016. "Estimation and Inference of FAVAR Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 620-641, October.
    See citations under working paper version above.
  23. Bai, Jushan & Liao, Yuan, 2016. "Efficient estimation of approximate factor models via penalized maximum likelihood," Journal of Econometrics, Elsevier, vol. 191(1), pages 1-18.

    Cited by:

    1. Hörmann, Siegfried & Jammoul, Fatima, 2023. "Prediction in functional regression with discretely observed and noisy covariates," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
    2. Elena Geminiani & Giampiero Marra & Irini Moustaki, 2021. "Single- and Multiple-Group Penalized Factor Analysis: A Trust-Region Algorithm Approach with Integrated Automatic Multiple Tuning Parameter Selection," Psychometrika, Springer;The Psychometric Society, vol. 86(1), pages 65-95, March.
    3. Alexander Robitzsch, 2022. "Comparing the Robustness of the Structural after Measurement (SAM) Approach to Structural Equation Modeling (SEM) against Local Model Misspecifications with Alternative Estimation Approaches," Stats, MDPI, vol. 5(3), pages 1-42, July.
    4. Miao, Ke & Li, Kunpeng & Su, Liangjun, 2020. "Panel threshold models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 219(1), pages 137-170.
    5. Maurizio Daniele & Winfried Pohlmeier & Aygul Zagidullina, 2018. "Sparse Approximate Factor Estimation for High-Dimensional Covariance Matrices," Working Paper Series of the Department of Economics, University of Konstanz 2018-07, Department of Economics, University of Konstanz.
    6. Hörmann, Siegfried & Jammoul, Fatima, 2022. "Consistently recovering the signal from noisy functional data," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    7. Kung, Ko-Lun & MacMinn, Richard D. & Kuo, Weiyu & Tsai, Chenghsien Jason, 2022. "Multi-population mortality modeling: When the data is too much and not enough," Insurance: Mathematics and Economics, Elsevier, vol. 103(C), pages 41-55.
    8. Kristoffer H. Hellton & Magne Thoresen, 2017. "When and Why are Principal Component Scores a Good Tool for Visualizing High-dimensional Data?," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(3), pages 581-597, September.
    9. Sung Hoon Choi, 2021. "Feasible Weighted Projected Principal Component Analysis for Factor Models with an Application to Bond Risk Premia," Papers 2108.10250, arXiv.org, revised May 2022.
    10. Fan, Jianqing & Ke, Yuan & Liao, Yuan, 2021. "Augmented factor models with applications to validating market risk factors and forecasting bond risk premia," Journal of Econometrics, Elsevier, vol. 222(1), pages 269-294.
    11. Shaoxin Wang & Hu Yang & Chaoli Yao, 2019. "On the penalized maximum likelihood estimation of high-dimensional approximate factor model," Computational Statistics, Springer, vol. 34(2), pages 819-846, June.
    12. Simon Hediger & Jeffrey Näf & Marc S. Paolella & Paweł Polak, 2023. "Heterogeneous tail generalized common factor modeling," Digital Finance, Springer, vol. 5(2), pages 389-420, June.
    13. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," PSE Working Papers halshs-02262202, HAL.
    14. Vogt, M. & Walsh, C. & Linton, O., 2022. "CCE Estimation of High-Dimensional Panel Data Models with Interactive Fixed Effects," Janeway Institute Working Papers 2218, Faculty of Economics, University of Cambridge.
    15. Matteo Barigozzi, 2023. "Asymptotic equivalence of Principal Components and Quasi Maximum Likelihood estimators in Large Approximate Factor Models," Papers 2307.09864, arXiv.org, revised Sep 2023.
    16. Matteo Barigozzi & Matteo Luciani, 2017. "Common Factors, Trends, and Cycles in Large Datasets," Finance and Economics Discussion Series 2017-111, Board of Governors of the Federal Reserve System (U.S.).
    17. Massacci, Daniele, 2017. "Least squares estimation of large dimensional threshold factor models," Journal of Econometrics, Elsevier, vol. 197(1), pages 101-129.
    18. Matteo Barigozzi, 2023. "Quasi Maximum Likelihood Estimation of High-Dimensional Factor Models: A Critical Review," Papers 2303.11777, arXiv.org, revised Dec 2023.
    19. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers halshs-02262202, HAL.
    20. Vogt, M. & Walsh, C. & Linton, O., 2022. "CCE Estimation of High-Dimensional Panel Data Models with Interactive Fixed Effects," Cambridge Working Papers in Economics 2242, Faculty of Economics, University of Cambridge.
    21. Geminiani, Elena & Marra, Giampiero & Moustaki, Irini, 2021. "Single and multiple-group penalized factor analysis: a trust-region algorithm approach with integrated automatic multiple tuning parameter selection," LSE Research Online Documents on Economics 108873, London School of Economics and Political Science, LSE Library.
    22. Matteo Barigozzi & Matteo Luciani, 2019. "Quasi Maximum Likelihood Estimation and Inference of Large Approximate Dynamic Factor Models via the EM algorithm," Papers 1910.03821, arXiv.org, revised Feb 2022.
    23. Rachida Ouysse, 2017. "Constrained principal components estimation of large approximate factor models," Discussion Papers 2017-12, School of Economics, The University of New South Wales.
    24. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
    25. Michael Vogt & Christopher Walsh & Oliver Linton, 2022. "CCE Estimation of High-Dimensional Panel Data Models with Interactive Fixed Effects," Papers 2206.12152, arXiv.org.
    26. Ando, Tomohiro & Li, Kunpeng & Lu, Lina, 2023. "A spatial panel quantile model with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 232(1), pages 191-213.
    27. Weichuan Deng & Pawel Polak & Abolfazl Safikhani & Ronakdilip Shah, 2023. "A Unified Framework for Fast Large-Scale Portfolio Optimization," Papers 2303.12751, arXiv.org, revised Nov 2023.
    28. Giorgio Calzolari & Roxana Halbleib & Christian Mucher, 2023. "Sequential Estimation of Multivariate Factor Stochastic Volatility Models," Papers 2302.07052, arXiv.org.
    29. Maurizio Daniele & Julie Schnaitmann, 2019. "A Regularized Factor-augmented Vector Autoregressive Model," Papers 1912.06049, arXiv.org.
    30. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers 2019-4, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.

  24. Jushan Bai & Peng Wang, 2015. "Identification and Bayesian Estimation of Dynamic Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 221-240, April.

    Cited by:

    1. Oxana Babecka Kucharcukova & Jan Bruha, 2016. "Nowcasting the Czech Trade Balance," Working Papers 2016/11, Czech National Bank.
    2. Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2018. "Common factors of commodity prices," Research Bulletin, European Central Bank, vol. 51.
    3. Yuefeng Han & Dan Yang & Cun-Hui Zhang & Rong Chen, 2021. "CP Factor Model for Dynamic Tensors," Papers 2110.15517, arXiv.org, revised Apr 2024.
    4. Song, Zefang & Song, Xinyuan & Li, Yuan, 2023. "Bayesian Analysis of ARCH-M model with a dynamic latent variable," Econometrics and Statistics, Elsevier, vol. 28(C), pages 47-62.
    5. Byrne, Joseph P. & Cao, Shuo & Korobilis, Dimitris, 2019. "Decomposing global yield curve co-movement," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 500-513.
    6. Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2022. "A Model of the Fed's View on Inflation," The Review of Economics and Statistics, MIT Press, vol. 104(4), pages 686-704, October.
    7. Michael Funke & Andrew Tsang, 2021. "The Direction and Intensity of China’s Monetary Policy: A Dynamic Factor Modelling Approach," The Economic Record, The Economic Society of Australia, vol. 97(316), pages 100-122, March.
    8. Florian Eckert & Nina Mühlebach, 2021. "Global and Local Components of Output Gaps," KOF Working papers 21-497, KOF Swiss Economic Institute, ETH Zurich.
    9. Bjørnland, Hilde C. & Ravazzolo, Francesco & Thorsrud, Leif Anders, 2017. "Forecasting GDP with global components: This time is different," International Journal of Forecasting, Elsevier, vol. 33(1), pages 153-173.
    10. Berger, Tino & Everaert, Gerdie & Pozzi, Lorenzo, 2021. "Testing for international business cycles: A multilevel factor model with stochastic factor selection," Journal of Economic Dynamics and Control, Elsevier, vol. 128(C).
    11. Manu García & Juan F. Rubio-Ramírez, 2019. "Now-casting Spain," Working Papers 2019-03, FEDEA.
    12. Helmut Herwartz & Christian Ochsner & Hannes Rohloff, 2021. "The Credit Composition of Global Liquidity," MAGKS Papers on Economics 202115, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    13. Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2024. "Tracking Weekly State-Level Economic Conditions," The Review of Economics and Statistics, MIT Press, vol. 106(2), pages 483-504, March.
    14. Mattia Guerini & Duc Thi Luu & Mauro Napoletano, 2019. "Synchronization Patterns in the European Union," GREDEG Working Papers 2019-30, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    15. Mayer, Alexander & Wied, Dominik, 2023. "Estimation and inference in factor copula models with exogenous covariates," Journal of Econometrics, Elsevier, vol. 235(2), pages 1500-1521.
    16. Alessio Farcomeni & Monia Ranalli & Sara Viviani, 2021. "Dimension reduction for longitudinal multivariate data by optimizing class separation of projected latent Markov models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(2), pages 462-480, June.
    17. Eraslan, Sercan & Reif, Magnus, 2023. "A latent weekly GDP indicator for Germany," Technical Papers 08/2023, Deutsche Bundesbank.
    18. Zeyyad Mandalinci & Haroon Mumtaz, 2019. "Global Economic Divergence and Portfolio Capital Flows to Emerging Markets," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(6), pages 1713-1730, September.
    19. Camacho, Maximo & Perez-Quiros, Gabriel & Pacce, Matías, 2020. "Spillover effects in international business cycles," Working Paper Series 2484, European Central Bank.
    20. Esther Acquah & Lorenzo Carbonari & Alessio Farcomeni & Giovanni Trovato, 2023. "Institutions and economic development: new measurements and evidence," Empirical Economics, Springer, vol. 65(4), pages 1693-1728, October.
    21. Paul Beaudry & Fabrice Collard & Patrick Feve & Alain Guay & Franck Portier, 2022. "Dynamic Identification in VARs," Working Papers 22-08, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    22. Jisheng Yang & Nan Yang, 2023. "Macroeconomic shocks, investment volatility and centrality in global manufacturing network," Empirical Economics, Springer, vol. 65(3), pages 1433-1451, September.
    23. Alvarez, Rocio & Camacho, Maximo & Perez-Quiros, Gabriel, 2016. "Aggregate versus disaggregate information in dynamic factor models," International Journal of Forecasting, Elsevier, vol. 32(3), pages 680-694.
    24. Cai, Zhengzheng & Zhu, Yanli & Han, Xiaoyi, 2022. "Bayesian analysis of spatial dynamic panel data model with convex combinations of different spatial weight matrices: A reparameterized approach," Economics Letters, Elsevier, vol. 217(C).
    25. Yifan Shen & Tilak Abeysinghe, 2021. "International Transmission Mechanism And World Business Cycle," Economic Inquiry, Western Economic Association International, vol. 59(1), pages 510-531, January.
    26. Iader Giraldo & Carlos Giraldo & José E. Gomez-Gonzalez & Jorge Mario Uribe, 2023. "US uncertainty shocks, credit, production, and prices: The case of fourteen Latin American countries," Documentos de trabajo 20667, FLAR.
    27. Matteo Luciani, 2020. "Common and Idiosyncratic Inflation," FEDS Notes 2020-03-05, Board of Governors of the Federal Reserve System (U.S.).
    28. Juan Antolin-Diaz & Thomas Drechsel & Ivan Petrella, 2014. "Tracking the Slowdown in Long-Run GDP Growth," Discussion Papers 1604, Centre for Macroeconomics (CFM), revised Jan 2016.
    29. Florian Eckert & Samad Sarferaz, 2019. "Agnostic Output Gap Estimation and Decomposition in Large Cross-Sections," KOF Working papers 19-467, KOF Swiss Economic Institute, ETH Zurich.
    30. Hanna Armelius & Martin Solberger & Erik Spånberg & Pär Österholm, 2024. "The evolution of the natural rate of interest: evidence from the Scandinavian countries," Empirical Economics, Springer, vol. 66(4), pages 1633-1659, April.
    31. Amélie Charles & Chew Lian Chua & Olivier Darné & Sandy Suardi, 2021. "Oil Price Shocks, Real Economic Activity and Uncertainty," Post-Print hal-03284089, HAL.
    32. Nalan Basturk & Agnieszka Borowska & Stefano Grassi & Lennart Hoogerheide & Herman K. van Dijk, 2018. "Forecast Density Combinations of Dynamic Models and Data Driven Portfolio Strategies," Working Paper 2018/10, Norges Bank.
    33. Tiia‐Maria Pasanen & Miikka Voutilainen & Jouni Helske & Harri Högmander, 2022. "A Bayesian spatio‐temporal analysis of markets during the Finnish 1860s famine," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1282-1302, November.
    34. Han, Xu, 2018. "Estimation and inference of dynamic structural factor models with over-identifying restrictions," Journal of Econometrics, Elsevier, vol. 202(2), pages 125-147.
    35. Krzysztof Beck & Piotr Stanek, 2019. "Globalization or Regionalization of Stock Markets? the Case of Central and Eastern European Countries," Eastern European Economics, Taylor & Francis Journals, vol. 57(4), pages 317-330, July.
    36. Luke Hartigan & Michelle Wright, 2021. "Financial Conditions and Downside Risk to Economic Activity in Australia," RBA Research Discussion Papers rdp2021-03, Reserve Bank of Australia.
    37. Petrella, Ivan & Antolin-Diaz, Juan & Drechsel, Thomas, 2021. "Advances in Nowcasting Economic Activity: Secular Trends, Large Shocks and New Data," CEPR Discussion Papers 15926, C.E.P.R. Discussion Papers.
    38. Linton, O. B. & Tang, H. & Wu, J., 2022. "A Structural Dynamic Factor Model for Daily Global Stock Market Returns," Cambridge Working Papers in Economics 2237, Faculty of Economics, University of Cambridge.
    39. Li, Yong & Yu, Jun & Zeng, Tao, 2020. "Deviance information criterion for latent variable models and misspecified models," Journal of Econometrics, Elsevier, vol. 216(2), pages 450-493.
    40. Helena Chuliá & Sabuhi Khalili & Jorge M. Uribe, 2024. "Monitoring time-varying systemic risk in sovereign debt and currency markets with generative AI," IREA Working Papers 202402, University of Barcelona, Research Institute of Applied Economics, revised Feb 2024.
    41. 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.
    42. Choi, Sung Hoon & Kim, Donggyu, 2023. "Large volatility matrix analysis using global and national factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1917-1933.
    43. Sung Hoon Choi & Donggyu Kim, 2023. "Large Global Volatility Matrix Analysis Based on Observation Structural Information," Papers 2305.01464, arXiv.org, revised Feb 2024.
    44. Peter Zorn, 2020. "Investment under Rational Inattention: Evidence from US Sectoral Data," CESifo Working Paper Series 8436, CESifo.
    45. Bai, Jushan & Liao, Yuan, 2016. "Efficient estimation of approximate factor models via penalized maximum likelihood," Journal of Econometrics, Elsevier, vol. 191(1), pages 1-18.
    46. Umut Akovali, 2020. "Beyond Connectedness: A Covariance Decomposition based Network Risk Model," Koç University-TUSIAD Economic Research Forum Working Papers 2003, Koc University-TUSIAD Economic Research Forum.
    47. Jose E. Gomez-Gonzalez & Jorge M. Uribe & Oscar M. Valencia, 2024. "Asymmetric Sovereign Risk: Implications for Climate Change Preparation," IREA Working Papers 202401, University of Barcelona, Research Institute of Applied Economics, revised Jan 2024.
    48. Linton, O. B. & Tang, H. & Wu, J., 2022. "A Structural Dynamic Factor Model for Daily Global Stock Market Returns," Janeway Institute Working Papers camjip:2214, Faculty of Economics, University of Cambridge.
    49. Ductor, Lorenzo & Leiva-León, Danilo, 2022. "Fluctuations in global output volatility," Journal of International Money and Finance, Elsevier, vol. 120(C).
    50. Funke, Michael & Tsang, Andrew, 2019. "The direction and intensity of China's monetary policy conduct: A dynamic factor modelling approach," BOFIT Discussion Papers 8/2019, Bank of Finland Institute for Emerging Economies (BOFIT).
    51. Lucchetti, Riccardo & Venetis, Ioannis A., 2020. "A replication of "A quasi-maximum likelihood approach for large, approximate dynamic factor models" (Review of Economics and Statistics, 2012)," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 14, pages 1-14.
    52. Juho Koistinen & Bernd Funovits, 2022. "Estimation of Impulse-Response Functions with Dynamic Factor Models: A New Parametrization," Papers 2202.00310, arXiv.org, revised Feb 2022.
    53. Younghoon Kim & Zachary F. Fisher & Vladas Pipiras, 2023. "Latent Gaussian dynamic factor modeling and forecasting for multivariate count time series," Papers 2307.10454, arXiv.org.
    54. Andres Algaba & Samuel Borms & Kris Boudt & Brecht Verbeken, 2021. "Daily news sentiment and monthly surveys: A mixed–frequency dynamic factor model for nowcasting consumer confidence," Working Paper Research 396, National Bank of Belgium.
    55. Truong, Chi & Sheen, Jeffrey & Trück, Stefan & Villafuerte, James, 2022. "Early warning systems using dynamic factor models: An application to Asian economies," Journal of Financial Stability, Elsevier, vol. 58(C).
    56. Luke Hartigan & Michelle Wright, 2023. "Monitoring Financial Conditions and Downside Risk to Economic Activity in Australia," The Economic Record, The Economic Society of Australia, vol. 99(325), pages 253-287, June.
    57. Cem Çakmakli & Hamza Dem I˙rcani & Sumru Altug, 2021. "Modelling of Economic and Financial Conditions for Real‐Time Prediction of Recessions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 663-685, June.
    58. Riccardo (Jack) Lucchetti & Ioannis A. Venetis, 2019. "Dynamic Factor Models in gretl. The DFM package," gretl working papers 7, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    59. Matteo Barigozzi & Matteo Luciani, 2019. "Quasi Maximum Likelihood Estimation and Inference of Large Approximate Dynamic Factor Models via the EM algorithm," Papers 1910.03821, arXiv.org, revised Feb 2022.
    60. Haroon Mumtaz & Fulvia Marotta, 2023. "Vulnerability to Climate Change: Evidence from a Dynamic Factor Model," Working Papers 961, Queen Mary University of London, School of Economics and Finance.
    61. Florian Eckert & Nina Mühlebach, 2023. "Global and local components of output gaps," Empirical Economics, Springer, vol. 65(5), pages 2301-2331, November.
    62. Nalan Basturk & Stefano Grassi & Lennart Hoogerheide & Herman K. van Dijk, 2016. "Time-varying Combinations of Bayesian Dynamic Models and Equity Momentum Strategies," Tinbergen Institute Discussion Papers 16-099/III, Tinbergen Institute.
    63. Berger, Tino & Grabert, Sibylle & Kempa, Bernd, 2017. "Global macroeconomic uncertainty," Journal of Macroeconomics, Elsevier, vol. 53(C), pages 42-56.
    64. Venetis, Ioannis & Ladas, Avgoustinos, 2022. "Co-movement and global factors in sovereign bond yields," MPRA Paper 115801, University Library of Munich, Germany.
    65. Gerdie Everaert & Lorenzo Pozzi, 2022. "Encompassing measures of international consumption risk sharing and their link with trade and financial globalization," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 433-449, March.
    66. Marc Anderes, 2021. "Housing Demand Shocks and Households Balance Sheets," KOF Working papers 21-492, KOF Swiss Economic Institute, ETH Zurich.
    67. Sung Hoon Choi & Donggyu Kim, 2022. "Large Volatility Matrix Analysis Using Global and National Factor Models," Papers 2208.12323, arXiv.org, revised Dec 2022.
    68. Takumah, Wisdom, 2023. "Fiscal Policy and Asset Prices in a Dynamic Factor Model with Cointegrated Factors," MPRA Paper 117897, University Library of Munich, Germany, revised 10 Jul 2023.

  25. Tomohiro Ando & Jushan Bai, 2015. "Asset Pricing with a General Multifactor Structure," Journal of Financial Econometrics, Oxford University Press, vol. 13(3), pages 556-604.

    Cited by:

    1. YAMAMOTO, Yohei & 山本, 庸平, 2015. "Asymptotic Inference for Common Factor Models in the Presence of Jumps," Discussion Papers 2015-05, Graduate School of Economics, Hitotsubashi University.
    2. Isabel Casas & Eva Ferreira & Susan Orbe, 2017. "Time-varying coefficient estimation in SURE models. Application to portfolio management," CREATES Research Papers 2017-33, Department of Economics and Business Economics, Aarhus University.
    3. Levent Kutlu & Robin C. Sickles & Mike G. Tsionas & Emmanuel Mamatzakis, 2022. "Heterogeneous decision-making and market power: an application to Eurozone banks," Empirical Economics, Springer, vol. 63(6), pages 3061-3092, December.
    4. Jean-Baptiste Hasse & Quentin Lajaunie, 2020. "Does the Yield Curve Signal Recessions? New Evidence from an International Panel Data Analysis," AMSE Working Papers 2013, Aix-Marseille School of Economics, France.
    5. Candelon, Bertrand & Hasse, Jean-Baptiste & Lajaunie, Quentin, 2021. "ESG-Washing in the Mutual Funds Industry? From Information Asymmetry to Regulation," LIDAM Reprints LFIN 2021023, Université catholique de Louvain, Louvain Finance (LFIN).
    6. Kutlu, Levent & Sickles, Robin & Tsionas, Mike G., 2019. "Heterogeneous Decision-Making and Market Power," Working Papers 19-008, Rice University, Department of Economics.
    7. Alexandre Belloni & Victor Chernozhukov & Christian Hansen & Damian Kozbur, 2016. "Inference in High-Dimensional Panel Models With an Application to Gun Control," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 590-605, October.
    8. Camacho, Maximo & Lopez-Buenache, German, 2023. "Factor models for large and incomplete data sets with unknown group structure," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1205-1220.
    9. Castagnetti, Carolina & Rossi, Eduardo & Trapani, Lorenzo, 2019. "A two-stage estimator for heterogeneous panel models with common factors," Econometrics and Statistics, Elsevier, vol. 11(C), pages 63-82.
    10. Giovanni Bonaccolto & Massimiliano Caporin & Sandra Paterlini, 2015. "Asset Allocation Strategies Based On Penalized Quantile Regression," "Marco Fanno" Working Papers 0199, Dipartimento di Scienze Economiche "Marco Fanno".
    11. Marco Avarucci & Paolo Zaffaroni, 2019. "Robust Nearly-Efficient Estimation of Large Panels with Factor Structures," Papers 1902.11181, arXiv.org.
    12. Rombouts, Jeroen V.K. & Stentoft, Lars & Violante, Francesco, 2020. "Variance swap payoffs, risk premia and extreme market conditions," Econometrics and Statistics, Elsevier, vol. 13(C), pages 106-124.
    13. Anatolyev, Stanislav & Mikusheva, Anna, 2021. "Limit Theorems For Factor Models," Econometric Theory, Cambridge University Press, vol. 37(5), pages 1034-1074, October.
    14. Alain-Philippe Fortin & Patrick Gagliardini & Olivier Scaillet, 2022. "Eigenvalue tests for the number of latent factors in short panels," Papers 2210.16042, arXiv.org.
    15. Yu Sheng & V. Eldon Ball & Kenneth Erickson & Carlos San Juan Mesonada, 2022. "Cross-country agricultural TFP convergence and capital deepening: evidence for induced innovation from 17 OECD countries," Journal of Productivity Analysis, Springer, vol. 58(2), pages 185-202, December.
    16. Gagliardini, Patrick & Ossola, Elisa & Scaillet, Olivier, 2019. "A diagnostic criterion for approximate factor structure," Journal of Econometrics, Elsevier, vol. 212(2), pages 503-521.
    17. Choi, Sung Hoon & Kim, Donggyu, 2023. "Large volatility matrix analysis using global and national factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1917-1933.
    18. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    19. Eugen Ivanov & Aleksey Min & Franz Ramsauer, 2017. "Copula-Based Factor Models for Multivariate Asset Returns," Econometrics, MDPI, vol. 5(2), pages 1-24, May.
    20. Ando, Tomohiro & Bai, Jushan, 2018. "Quantile co-movement in financial markets: A panel quantile model with unobserved heterogeneity," MPRA Paper 88765, University Library of Munich, Germany.
    21. Sung Hoon Choi & Donggyu Kim, 2023. "Large Global Volatility Matrix Analysis Based on Observation Structural Information," Papers 2305.01464, arXiv.org, revised Feb 2024.
    22. Ando, Tomohiro & Bai, Jushan, 2014. "A simple new test for slope homogeneity in panel data models with interactive effects," MPRA Paper 60795, University Library of Munich, Germany.
    23. Alain-Philippe Fortin & Patrick Gagliardini & Olivier Scaillet, 2023. "Latent Factor Analysis in Short Panels," Papers 2306.14004, arXiv.org.
    24. Kim Dukpa & Kim Yunjung & Bak Yuhyeon, 2017. "Multi-level factor analysis of bond risk premia," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(5), pages 1-19, December.
    25. Lina Lu, 2017. "Simultaneous Spatial Panel Data Models with Common Shocks," Supervisory Research and Analysis Working Papers RPA 17-3, Federal Reserve Bank of Boston.
    26. Sung Hoon Choi & Donggyu Kim, 2022. "Large Volatility Matrix Analysis Using Global and National Factor Models," Papers 2208.12323, arXiv.org, revised Dec 2022.

  26. Bai, Jushan & Zhou, Guofu, 2015. "Fama–MacBeth two-pass regressions: Improving risk premia estimates," Finance Research Letters, Elsevier, vol. 15(C), pages 31-40.

    Cited by:

    1. Han, Yufeng & Zhou, Guofu & Zhu, Yingzi, 2016. "A trend factor: Any economic gains from using information over investment horizons?," Journal of Financial Economics, Elsevier, vol. 122(2), pages 352-375.
    2. Pesaran, M. Hashem & Smith, Ron P., 2023. "Arbitrage pricing theory, the stochastic discount factor and estimation of risk premia from portfolios," Econometrics and Statistics, Elsevier, vol. 26(C), pages 17-30.
    3. M. Hashem Pesaran & Run Smith, 2021. "Arbitrage pricing theory, the stochastic discount factor and estimation of risk premia in portfolios," BCAM Working Papers 2108, Birkbeck Centre for Applied Macroeconomics.
    4. Elias Cavalcante-Filho, Fernando Chague, Rodrigo De Losso, Bruno Giovannetti, 2019. "US Risk Premia under Emerging Markets Constraints," Working Papers, Department of Economics 2019_28, University of São Paulo (FEA-USP).
    5. 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.
    6. M. Hashem Pesaran & Ron P. Smith, 2021. "Factor Strengths, Pricing Errors, and Estimation of Risk Premia," CESifo Working Paper Series 8947, CESifo.
    7. José Luis Montiel Olea & Pietro Ortoleva & Mallesh Pai & Andrea Prat, 2021. "Competing Models," Working Papers 2021-89, Princeton University. Economics Department..
    8. M. Hashem Pesaran & Ron P. Smith, 2019. "The Role of Factor Strength and Pricing Errors for Estimation and Inference in Asset Pricing Models," CESifo Working Paper Series 7919, CESifo.

  27. Ando, Tomohiro & Bai, Jushan, 2015. "A simple new test for slope homogeneity in panel data models with interactive effects," Economics Letters, Elsevier, vol. 136(C), pages 112-117.
    See citations under working paper version above.
  28. Bai, Jushan & Wang, Peng, 2014. "Identification theory for high dimensional static and dynamic factor models," Journal of Econometrics, Elsevier, vol. 178(2), pages 794-804.

    Cited by:

    1. Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2018. "Common factors of commodity prices," Research Bulletin, European Central Bank, vol. 51.
    2. Yuefeng Han & Dan Yang & Cun-Hui Zhang & Rong Chen, 2021. "CP Factor Model for Dynamic Tensors," Papers 2110.15517, arXiv.org, revised Apr 2024.
    3. Franco Peracchi & Claudio Rossetti, 2019. "A Nonlinear Dynamic Factor Model of Health and Medical Treatment," CSEF Working Papers 524, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    4. 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.
    5. Kaufmann, Sylvia & Schumacher, Christian, 2019. "Bayesian estimation of sparse dynamic factor models with order-independent and ex-post mode identification," Journal of Econometrics, Elsevier, vol. 210(1), pages 116-134.
    6. Pilar Poncela & Esther Ruiz, 2016. "Small- Versus Big-Data Factor Extraction in Dynamic Factor Models: An Empirical Assessment," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 401-434, Emerald Group Publishing Limited.
    7. Vegard H. Larsen & Leif Anders Thorsrud, 2019. "Business Cycle Narratives," CESifo Working Paper Series 7468, CESifo.
    8. Martin Solberger & Erik Spånberg, 2020. "Estimating a Dynamic Factor Model in EViews Using the Kalman Filter and Smoother," Computational Economics, Springer;Society for Computational Economics, vol. 55(3), pages 875-900, March.
    9. Simon Beyeler & Sylvia Kaufmann, 2016. "Factor augmented VAR revisited - A sparse dynamic factor model approach," Working Papers 16.08, Swiss National Bank, Study Center Gerzensee.
    10. Hauber, Philipp & Schumacher, Christian, 2021. "Precision-based sampling with missing observations: A factor model application," Discussion Papers 11/2021, Deutsche Bundesbank.
    11. Han, Xu, 2018. "Estimation and inference of dynamic structural factor models with over-identifying restrictions," Journal of Econometrics, Elsevier, vol. 202(2), pages 125-147.
    12. Dimitar EFTIMOSKI, 2019. "Improving Short-Term Forecasting of Macedonian GDP: Comparing the Factor Model with the Macroeconomic Structural Equation Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 32-53, June.
    13. 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.
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    10. Emna Trabelsi, 2022. "Macroprudential Transparency and Price Stability in Emerging and Developing Countries," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 11(1), pages 105-129.
    11. Simon Freyaldenhoven, 2020. "Identification Through Sparsity in Factor Models," Working Papers 20-25, Federal Reserve Bank of Philadelphia.
    12. Claudio Morana, 2013. "New Insights on the US OIS Spreads Term Structure During the Recent Financial Turmoil," CeRP Working Papers 137, Center for Research on Pensions and Welfare Policies, Turin (Italy).
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    125. Weichuan Deng & Pawel Polak & Abolfazl Safikhani & Ronakdilip Shah, 2023. "A Unified Framework for Fast Large-Scale Portfolio Optimization," Papers 2303.12751, arXiv.org, revised Nov 2023.
    126. Francisco Corona & Graciela Gonz'alez-Far'ias & Jes'us L'opez-P'erez, 2021. "A nowcasting approach to generate timely estimates of Mexican economic activity: An application to the period of COVID-19," Papers 2101.10383, arXiv.org.
    127. Lina Lu, 2017. "Simultaneous Spatial Panel Data Models with Common Shocks," Supervisory Research and Analysis Working Papers RPA 17-3, Federal Reserve Bank of Boston.
    128. Rueben Ellul & Germano Ruisi, 2022. "Nowcasting the Maltese economy with a dynamic factor model," CBM Working Papers WP/02/2022, Central Bank of Malta.
    129. Javier Maldonado & Esther Ruiz, 2021. "Accurate Confidence Regions for Principal Components Factors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(6), pages 1432-1453, December.
    130. Thomas Despois & Catherine Doz, 2022. "Identifying and interpreting the factors in factor models via sparsity : Different approaches," PSE Working Papers halshs-03626503, HAL.
    131. Ting Fung Ma & Fangfang Wang & Jun Zhu, 2023. "On generalized latent factor modeling and inference for high‐dimensional binomial data," Biometrics, The International Biometric Society, vol. 79(3), pages 2311-2320, September.
    132. Antoine A. Djogbenou, 2024. "Identifying oil price shocks with global, developed, and emerging latent real economy activity factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 128-149, January.
    133. Thomas Despois & Catherine Doz, 2023. "Identifying and interpreting the factors in factor models via sparsity: Different approaches," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 533-555, June.
    134. Camacho, Maximo & Caro, Angela & Peña, Daniel, 2023. "What drives industrial energy prices?," Economic Modelling, Elsevier, vol. 120(C).

  30. Jushan Bai, 2013. "Fixed‐Effects Dynamic Panel Models, a Factor Analytical Method," Econometrica, Econometric Society, vol. 81(1), pages 285-314, January.

    Cited by:

    1. Bao, Yong & Yu, Xuewen, 2023. "Indirect inference estimation of dynamic panel data models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1027-1053.
    2. Juodis, Arturas & Sarafidis, Vasilis, 2014. "Fixed T Dynamic Panel Data Estimators with Multi-Factor Errors," MPRA Paper 57659, University Library of Munich, Germany.
    3. Geert Dhaene & Koen Jochmans, 2014. "Split-Panel Jackknife Estimation of Fixed-Effect Models," SciencePo Working papers Main hal-01070553, HAL.
    4. Zheng, Jiajia & Wang, Xingwu, 2022. "Impacts on human development index due to combinations of renewables and ICTs --new evidence from 26 countries," Renewable Energy, Elsevier, vol. 191(C), pages 330-344.
    5. Bai, Jushan, 2013. "Likelihood approach to dynamic panel models with interactive effects," MPRA Paper 50267, University Library of Munich, Germany.
    6. Norkute, Milda, 2014. "A Monte Carlo Study of a Factor Analytical Method for Fixed-Effects Dynamic Panel Models," Working Papers 2014:7, Lund University, Department of Economics.
    7. Liu, Shasha & Sickles, Robin, 2020. "The Agency Problem Revisited: A Structural Analysis of Managerial Productivity and CEO Compensation in Large U.S. Commercial Banks," Working Papers 20-001, Rice University, Department of Economics.
    8. Samuel Brien, 2021. "Wealth Inequality, Uninsurable Entrepreneurial Risk and Firms Markup," Working Paper 1476, Economics Department, Queen's University.
    9. Maurice J.G. Bun & Martin A. Carree & Artūras Juodis, 2017. "On Maximum Likelihood Estimation of Dynamic Panel Data Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(4), pages 463-494, August.
    10. In Choi & Sanghyun Jung, 2020. "Cross-sectional quasi maximum likelihood and bias-corrected pooled least squares estimators for short dynamic panels," Working Papers 2007, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    11. Nocera, A. & Pesaran, M. H., 2022. "Causal effects of the Fed's large-scale asset purchases on firms' capital structure," Cambridge Working Papers in Economics 2224, Faculty of Economics, University of Cambridge.
    12. Xuan Leng & Jiaming Mao & Yutao Sun, 2023. "Debiased inference for dynamic nonlinear models with two-way fixed effects," Papers 2305.03134, arXiv.org, revised Oct 2023.
    13. Alexander Chudik & M. Hashem Pesaran, 2017. "A Bias-Corrected Method of Moments Approach to Estimation of Dynamic Short-T Panels," CESifo Working Paper Series 6688, CESifo.
    14. Scheubel, Beatrice & Tafuro, Andrea & Vonessen, Benjamin, 2018. "Stigma? What stigma? A contribution to the debate on financial market effects of IMF lending," Working Paper Series 2198, European Central Bank.
    15. Jose Diogo Barbosa & Marcelo Moreira, 2017. "Likelihood inference and the role of initial conditions for the dynamic panel data model," CeMMAP working papers CWP04/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Subhash C. Sharma & Anil K. Bera, 2021. "Estimation of Random Components and Prediction in One and Two-Way Error Component Regression Models," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 419-441, December.
    17. Norkute, Milda, 2014. "A Monte Carlo study of a factor analytical method for fixed-effects dynamic panel models," Economics Letters, Elsevier, vol. 123(3), pages 348-351.
    18. Suhal Kusairi & Suriyani Muhamad & M Musdholifah & Shu-Chen Chang, 2019. "Labor Market and Household Debt in Asia Pacific Countries: Dynamic Heterogeneous Panel Data Analysis," Journal of International Commerce, Economics and Policy (JICEP), World Scientific Publishing Co. Pte. Ltd., vol. 10(02), pages 1-15, June.
    19. Hsiao, Cheng & Zhou, Qiankun, 2018. "Incidental parameters, initial conditions and sample size in statistical inference for dynamic panel data models," Journal of Econometrics, Elsevier, vol. 207(1), pages 114-128.
    20. Beatrice D. Scheubel & Andrea Tafuro & Benjamin Vonessen, 2018. "STIGMA? WHAT STIGMA? A Contribution to the Debate on the Effectiveness of IMF Lending," CESifo Working Paper Series 7036, CESifo.
    21. Alexander Chudik & M. Hashem Pesaran, 2017. "An Augmented Anderson-Hsiao Estimator for Dynamic Short-T Panels," Globalization Institute Working Papers 327, Federal Reserve Bank of Dallas, revised 27 Mar 2021.
    22. Marcelo OLARREAGA & Stephan SPERLICH & Virginie TRACHSEL, 2017. "Export Promotion: what works?," Working Papers P184, FERDI.
    23. Abdelfeteh Bitat, 2018. "Environmental regulation and eco-innovation: the Porter hypothesis refined," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 8(3), pages 299-321, September.
    24. Alvarez, Javier & Arellano, Manuel, 2022. "Robust likelihood estimation of dynamic panel data models," Journal of Econometrics, Elsevier, vol. 226(1), pages 21-61.
    25. Khalaf, Lynda & Saunders, Charles J., 2020. "Monte Carlo two-stage indirect inference (2SIF) for autoregressive panels," Journal of Econometrics, Elsevier, vol. 218(2), pages 419-434.
    26. Jerry A. Hausman & Maxim L. Pinkovskiy, 2017. "Estimating dynamic panel models: backing out the Nickell Bias," Staff Reports 824, Federal Reserve Bank of New York.
    27. Bodnar, Taras & Reiß, Markus, 2016. "Exact and asymptotic tests on a factor model in low and large dimensions with applications," Journal of Multivariate Analysis, Elsevier, vol. 150(C), pages 125-151.
    28. Mitchell J. Lovett & Renana Peres & Linli Xu, 2019. "Can your advertising really buy earned impressions? The effect of brand advertising on word of mouth," Quantitative Marketing and Economics (QME), Springer, vol. 17(3), pages 215-255, September.
    29. Jan Bruha & Jaromir Tonner, 2017. "An Exchange Rate Floor as an Instrument of Monetary Policy: An Ex-post Assessment of the Czech Experience," Working Papers 2017/04, Czech National Bank.
    30. Jerry Hausman & Maxim L. Pinkovskiy, 2017. "Estimating dynamic panel models: backing out the Nickell Bias," CeMMAP working papers 53/17, Institute for Fiscal Studies.
    31. Norkutė, Milda & Westerlund, Joakim, 2019. "The factor analytical method for interactive effects dynamic panel models with moving average errors," Econometrics and Statistics, Elsevier, vol. 11(C), pages 83-104.
    32. Junrong Liu & Robin C. Sickles & E. G. Tsionas, 2017. "Bayesian Treatments for Panel Data Stochastic Frontier Models with Time Varying Heterogeneity," Econometrics, MDPI, vol. 5(3), pages 1-21, July.
    33. Westerlund, Joakim & Norkute, Milda, 2014. "A Factor Analytical Method to Interactive Effects Dynamic Panel Models with or without Unit Root," Working Papers 2014:12, Lund University, Department of Economics.
    34. Norkutė, Milda & Westerlund, Joakim, 2021. "The factor analytical approach in near unit root interactive effects panels," Journal of Econometrics, Elsevier, vol. 221(2), pages 569-590.
    35. Constantinescu, Mihnea & Lastauskas, Povilas, 2018. "The knotty interplay between credit and housing," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 241-266.
    36. Juan Carlos Bou & Albert Satorra, 2014. "Univariate versus multivariate modeling of panel data," Economics Working Papers 1417, Department of Economics and Business, Universitat Pompeu Fabra.
    37. Jerry Hausman & Maxim L. Pinkovskiy, 2017. "Estimating dynamic panel models: backing out the Nickell Bias," CeMMAP working papers CWP53/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    38. Li, Kunpeng, 2017. "Fixed-effects dynamic spatial panel data models and impulse response analysis," Journal of Econometrics, Elsevier, vol. 198(1), pages 102-121.
    39. Breitung, Jörg & Kripfganz, Sebastian & Hayakawa, Kazuhiko, 2022. "Bias-corrected method of moments estimators for dynamic panel data models," Econometrics and Statistics, Elsevier, vol. 24(C), pages 116-132.
    40. Robertson, Donald & Sarafidis, Vasilis & Westerlund, Joakim, 2014. "GMM Unit Root Inference in Generally Trending and Cross-Correlated Dynamic Panels," MPRA Paper 53419, University Library of Munich, Germany.

  31. Jushan Bai & Josep Lluís Carrion‐i‐Silvestre, 2013. "Testing panel cointegration with unobservable dynamic common factors that are correlated with the regressors," Econometrics Journal, Royal Economic Society, vol. 16(2), pages 222-249, June.

    Cited by:

    1. Kaddour Hadri & Eiji Kurozumi & Yao Rao, 2014. "Novel Panel Cointegration Tests Emending for Cross-Section Dependence with N Fixed," Economics Working Papers 14-02, Queen's Management School, Queen's University Belfast.
    2. Liu, Shasha & Sickles, Robin, 2020. "The Agency Problem Revisited: A Structural Analysis of Managerial Productivity and CEO Compensation in Large U.S. Commercial Banks," Working Papers 20-001, Rice University, Department of Economics.
    3. Wang, Weiguo & Xue, Jing & Du, Chonghua, 2016. "The Balassa–Samuelson hypothesis in the developed and developing countries revisited," Economics Letters, Elsevier, vol. 146(C), pages 33-38.
    4. Gerdie Everaert & Freddy Heylen & Ruben Schoonackers, 2014. "Fiscal policy and TFP in the OECD : Measuring direct and indirect effects," Working Paper Research 274, National Bank of Belgium.
    5. Predrag Petrović & Mikhail M. Lobanov, 2022. "Impact of financial development on CO2 emissions: improved empirical results," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(5), pages 6655-6675, May.
    6. Özçelik, Emre & Tuğan, Mustafa, 2019. "Terms of Trade Effects of Productivity Shocks and Economic Development," MPRA Paper 91473, University Library of Munich, Germany.
    7. Tim Buyse & Freddy Heylen & Ruben Schoonackers, 2016. "On the role of public policies and wage formation for private investment in R&D:A long-run panel analysis," Working Paper Research 292, National Bank of Belgium.
    8. Petrović, Predrag & Lobanov, Mikhail M., 2022. "Energy intensity and foreign direct investment nexus: Advanced panel data analysis," Applied Energy, Elsevier, vol. 311(C).
    9. Nana Kwabena Kufuor & Kevin Williams, 2024. "A source of funding for illicit activities or a solution to crime? Evidence from remittance inflows to Jamaica," Journal of International Development, John Wiley & Sons, Ltd., vol. 36(1), pages 3-25, January.
    10. Karaman Örsal, Deniz Dilan & Arsova, Antonia, 2017. "Meta-analytic cointegrating rank tests for dependent panels," Econometrics and Statistics, Elsevier, vol. 2(C), pages 61-72.
    11. Antonia Arsova & Deniz Dilan Karaman Örsal, 2018. "Likelihood-based panel cointegration test in the presence of a linear time trend and cross-sectional dependence," Econometric Reviews, Taylor & Francis Journals, vol. 37(10), pages 1033-1050, November.
    12. Reese, Simon & Westerlund, Joakim, 2014. "PANICCA - PANIC on Cross-Section Averages," Working Papers 2015:3, Lund University, Department of Economics, revised 24 Mar 2015.
    13. In Choi, 2012. "Panel Cointegration," Working Papers 1208, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    14. Antonia Arsova & Deniz Dilan Karaman Örsal, 2016. "An intersection test for the cointegrating rank in dependent panel data," Working Paper Series in Economics 357, University of Lüneburg, Institute of Economics.
    15. Westerlund, Joakim, 2015. "The power of PANIC," Journal of Econometrics, Elsevier, vol. 185(2), pages 495-509.
    16. Josep Lluís Carrion-I-Silvestre, 2016. "Fiscal Deficit Sustainability of the Spanish Regions," Regional Studies, Taylor & Francis Journals, vol. 50(10), pages 1702-1713, October.

  32. Haiqiang Chen & Terence Chong & Jushan Bai, 2012. "Theory and Applications of TAR Model with Two Threshold Variables," Econometric Reviews, Taylor & Francis Journals, vol. 31(2), pages 142-170.
    See citations under working paper version above.
  33. Jushan Bai & Shuzhong Shi, 2011. "Estimating High Dimensional Covariance Matrices and its Applications," Annals of Economics and Finance, Society for AEF, vol. 12(2), pages 199-215, November.

    Cited by:

    1. Efthymios G. Tsionas, 2014. "On modeling banking risk," Working Papers 183, Bank of Greece.
    2. Hannart, Alexis & Naveau, Philippe, 2014. "Estimating high dimensional covariance matrices: A new look at the Gaussian conjugate framework," Journal of Multivariate Analysis, Elsevier, vol. 131(C), pages 149-162.
    3. Taras Bodnar & Solomiia Dmytriv & Nestor Parolya & Wolfgang Schmid, 2017. "Tests for the weights of the global minimum variance portfolio in a high-dimensional setting," Papers 1710.09587, arXiv.org, revised Jul 2019.
    4. Soloveychik, I. & Trushin, D., 2016. "Gaussian and robust Kronecker product covariance estimation: Existence and uniqueness," Journal of Multivariate Analysis, Elsevier, vol. 149(C), pages 92-113.
    5. Hayakawa, Kazuhiko, 2019. "Alternative over-identifying restriction test in the GMM estimation of panel data models," Econometrics and Statistics, Elsevier, vol. 10(C), pages 71-95.
    6. Laurent A. F. Callot & Anders B. Kock & Marcelo C. Medeiros, 2014. "Estimation and Forecasting of Large Realized Covariance Matrices and Portfolio Choice," CREATES Research Papers 2014-42, Department of Economics and Business Economics, Aarhus University.
    7. Ruili Sun & Tiefeng Ma & Shuangzhe Liu & Milind Sathye, 2019. "Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review," JRFM, MDPI, vol. 12(1), pages 1-34, March.
    8. Bodnar, Taras & Parolya, Nestor & Schmid, Wolfgang, 2018. "Estimation of the global minimum variance portfolio in high dimensions," European Journal of Operational Research, Elsevier, vol. 266(1), pages 371-390.
    9. Taras Bodnar & Stepan Mazur & Nestor Parolya, 2019. "Central limit theorems for functionals of large sample covariance matrix and mean vector in matrix‐variate location mixture of normal distributions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 46(2), pages 636-660, June.
    10. Nhat Minh Nguyen & Trung Duc Nguyen & Eleftherios I. Thalassinos & Hoang Anh Le, 2022. "The Performance of Shrinkage Estimator for Stock Portfolio Selection in Case of High Dimensionality," JRFM, MDPI, vol. 15(6), pages 1-12, June.
    11. Tatsuya Kubokawa & Akira Inoue, 2012. "Estimation of Covariance and Precision Matrices in High Dimension," CIRJE F-Series CIRJE-F-855, CIRJE, Faculty of Economics, University of Tokyo.
    12. Bodnar, Taras & Gupta, Arjun K. & Parolya, Nestor, 2016. "Direct shrinkage estimation of large dimensional precision matrix," Journal of Multivariate Analysis, Elsevier, vol. 146(C), pages 223-236.
    13. Taras Bodnar & Yarema Okhrin & Nestor Parolya, 2016. "Optimal shrinkage-based portfolio selection in high dimensions," Papers 1611.01958, arXiv.org, revised Nov 2021.
    14. Monika Bours & Ansgar Steland, 2021. "Large‐sample approximations and change testing for high‐dimensional covariance matrices of multivariate linear time series and factor models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(2), pages 610-654, June.
    15. Ikeda, Yuki & Kubokawa, Tatsuya & Srivastava, Muni S., 2016. "Comparison of linear shrinkage estimators of a large covariance matrix in normal and non-normal distributions," Computational Statistics & Data Analysis, Elsevier, vol. 95(C), pages 95-108.
    16. Zhang, Yongli & Rolling, Craig & Yang, Yuhong, 2021. "Estimating and forecasting dynamic correlation matrices: A nonlinear common factor approach," Journal of Multivariate Analysis, Elsevier, vol. 183(C).
    17. Shaoxin Wang & Hu Yang & Chaoli Yao, 2019. "On the penalized maximum likelihood estimation of high-dimensional approximate factor model," Computational Statistics, Springer, vol. 34(2), pages 819-846, June.
    18. Yuki Ikeda & Tatsuya Kubokawa & Muni S. Srivastava, 2015. "Comparison of Linear Shrinkage Estimators of a Large Covariance Matrix in Normal and Non-normal Distributions," CIRJE F-Series CIRJE-F-970, CIRJE, Faculty of Economics, University of Tokyo.
    19. Tsionas, Mike G., 2016. "Parameters measuring bank risk and their estimation," European Journal of Operational Research, Elsevier, vol. 250(1), pages 291-304.
    20. Zhongzhi Lawrence He, 2018. "Generalized Information Ratio," Papers 1803.01381, arXiv.org, revised Apr 2018.
    21. Taras Bodnar & Arjun K. Gupta & Nestor Parolya, 2013. "On the Strong Convergence of the Optimal Linear Shrinkage Estimator for Large Dimensional Covariance Matrix," Papers 1308.2608, arXiv.org, revised Jun 2014.
    22. Dou, Baojun & Parrella, Maria Lucia & Yao, Qiwei, 2016. "Generalized Yule–Walker estimation for spatio-temporal models with unknown diagonal coefficients," LSE Research Online Documents on Economics 67151, London School of Economics and Political Science, LSE Library.
    23. Ruili Sun & Tiefeng Ma & Shuangzhe Liu, 2020. "Portfolio selection: shrinking the time-varying inverse conditional covariance matrix," Statistical Papers, Springer, vol. 61(6), pages 2583-2604, December.
    24. Jianqing Fan & Yuan Liao & Martina Mincheva, 2013. "Large covariance estimation by thresholding principal orthogonal complements," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(4), pages 603-680, September.
    25. Taras Bodnar & Arjun K. Gupta & Nestor Parolya, 2013. "Optimal Linear Shrinkage Estimator for Large Dimensional Precision Matrix," Papers 1308.0931, arXiv.org, revised Mar 2014.
    26. Gasser, Stephan M. & Rammerstorfer, Margarethe & Weinmayer, Karl, 2017. "Markowitz revisited: Social portfolio engineering," European Journal of Operational Research, Elsevier, vol. 258(3), pages 1181-1190.
    27. Bauder, David & Bodnar, Taras & Parolya, Nestor & Schmid, Wolfgang, 2020. "Bayesian inference of the multi-period optimal portfolio for an exponential utility," Journal of Multivariate Analysis, Elsevier, vol. 175(C).
    28. De Nard, Gianluca & Zhao, Zhao, 2023. "Using, taming or avoiding the factor zoo? A double-shrinkage estimator for covariance matrices," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 23-35.
    29. Bai, Jushan & Zhou, Guofu, 2015. "Fama–MacBeth two-pass regressions: Improving risk premia estimates," Finance Research Letters, Elsevier, vol. 15(C), pages 31-40.
    30. Taras Bodnar & Solomiia Dmytriv & Yarema Okhrin & Nestor Parolya & Wolfgang Schmid, 2020. "Statistical inference for the EU portfolio in high dimensions," Papers 2005.04761, arXiv.org.
    31. Gautam Sabnis & Debdeep Pati & Anirban Bhattacharya, 2019. "Compressed Covariance Estimation with Automated Dimension Learning," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(2), pages 466-481, December.
    32. Tsubasa Ito & Tatsuya Kubokawa, 2015. "Linear Ridge Estimator of High-Dimensional Precision Matrix Using Random Matrix Theory ," CIRJE F-Series CIRJE-F-995, CIRJE, Faculty of Economics, University of Tokyo.
    33. Jonathan Gillard & Emily O’Riordan & Anatoly Zhigljavsky, 2023. "Polynomial whitening for high-dimensional data," Computational Statistics, Springer, vol. 38(3), pages 1427-1461, September.
    34. Dou, Baojun & Parrella, Maria Lucia & Yao, Qiwei, 2016. "Generalized Yule–Walker estimation for spatio-temporal models with unknown diagonal coefficients," Journal of Econometrics, Elsevier, vol. 194(2), pages 369-382.
    35. Schlütter, Sebastian & Fianu, Emmanuel Senyo & Gründl, Helmut, 2022. "Responsible investments in life insurers' optimal portfolios under solvency constraints," ICIR Working Paper Series 45/22, Goethe University Frankfurt, International Center for Insurance Regulation (ICIR).
    36. Dante Amengual & Luca Repetto, 2014. "Testing a Large Number of Hypotheses in Approximate Factor Models," Working Papers wp2014_1410, CEMFI.
    37. Tatsuya Kubokawa & Muni S. Srivastava, 2013. "Optimal Ridge-type Estimators of Covariance Matrix in High Dimension," CIRJE F-Series CIRJE-F-906, CIRJE, Faculty of Economics, University of Tokyo.
    38. Ruili Sun & Tiefeng Ma & Shuangzhe Liu, 2018. "A Stein-type shrinkage estimator of the covariance matrix for portfolio selections," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(8), pages 931-952, November.

  34. Jushan Bai & Peng Wang, 2011. "Conditional Markov chain and its application in economic time series analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(5), pages 715-734, August.
    See citations under working paper version above.
  35. J. Ginger Meng & Gang Hu & Jushan Bai, 2011. "Olive: A Simple Method For Estimating Betas When Factors Are Measured With Error," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 34(1), pages 27-60, March.
    See citations under working paper version above.
  36. Bai, Jushan, 2010. "Common breaks in means and variances for panel data," Journal of Econometrics, Elsevier, vol. 157(1), pages 78-92, July.

    Cited by:

    1. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    2. Tae-Hwy Lee & Ekaterina Seregina, 2022. "Combining Forecasts under Structural Breaks Using Graphical LASSO," Working Papers 202213, University of California at Riverside, Department of Economics.
    3. Sheng, Yu & Chancellor, Will & Jackson, Thomas, 2020. "Deregulation reforms, resource reallocation and aggregate productivity growth in the Australian dairy industry," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 64(2), April.
    4. Badi Baltagi & Qu Feng & Chihwa Kao, 2019. "Structural Changes in Heterogeneous Panels with Endogenous Regressors," Center for Policy Research Working Papers 214, Center for Policy Research, Maxwell School, Syracuse University.
    5. Otilia Boldea & Bettina Drepper & Zhuojiong Gan, 2018. "Change Point Estimation in Panel Data with Time-Varying Individual Effects," Papers 1808.03109, arXiv.org.
    6. V. Brault & C. Lévy-Leduc & A. Mathieu & A. Jullien, 2018. "Change-Point Estimation in the Multivariate Model Taking into Account the Dependence: Application to the Vegetative Development of Oilseed Rape," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 23(3), pages 374-389, September.
    7. Paolo Verme & Kirsten Schuettler, 2019. "The Impact of Forced Displacement on Host Communities: A Review of the Empirical Literature in Economics," HiCN Working Papers 302, Households in Conflict Network.
    8. Haoran Lu & Dianpeng Wang, 2024. "Grouped Change-Points Detection and Estimation in Panel Data," Mathematics, MDPI, vol. 12(5), pages 1-20, March.
    9. Lorenzo Trapani, 2014. "Comments on: 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 283-286, June.
    10. Barbora Peštová & Michal Pešta, 2015. "Testing structural changes in panel data with small fixed panel size and bootstrap," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(6), pages 665-689, August.
    11. Eunju Hwang & Dong Wan Shin, 2017. "Stationary bootstrapping for common mean change detection in cross-sectionally dependent panels," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(6), pages 767-787, November.
    12. Karavias, Yiannis & Tzavalis, Elias, 2012. "Generalized �Fixed-T Panel Unit Root Tests Allowing for Structural Breaks," MPRA Paper 43128, University Library of Munich, Germany.
    13. Jan Ditzen & Yiannis Karavias & Joakim Westerlund, 2023. "Multiple structural breaks in interactive effects panel data and the impace of quantitative easing on bank lending," Discussion Papers 23-02, Department of Economics, University of Birmingham.
    14. Luintel, Kul B. & Khan, Mosahid & Leon-Gonzalez, Roberto & Li, Guangjie, 2016. "Financial development, structure and growth: New data, method and results," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 43(C), pages 95-112.
    15. Yiannis Karavias & Paresh Narayan & Joakim Westerlund, 2021. "Structural Breaks in Interactive Effects Panels and the Stock Market Reaction to COVID-19," Papers 2111.03035, arXiv.org.
    16. Duan, Jiangtao & Bai, Jushan & Han, Xu, 2023. "Quasi-maximum likelihood estimation of break point in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 233(1), pages 209-236.
    17. Gary Gorton, 2015. "Stress for Success: A Review of Timothy Geithner's Financial Crisis Memoir," Journal of Economic Literature, American Economic Association, vol. 53(4), pages 975-995, December.
    18. Dionne, Georges & Maalaoui Chun, Olfa, 2013. "Default and liquidity regimes in the bond market during the 2002-2012 period," Working Papers 13-4, HEC Montreal, Canada Research Chair in Risk Management.
    19. 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.
    20. Mullally, Conner & Lusk, Jayson, 2017. "The Impact of Farm Animal Housing Restrictions on Egg Prices, Consumer Welfare, and Production in California," SocArXiv cn36m, Center for Open Science.
    21. Gary Gorton & Tyler Muir, 2016. "Mobile Collateral versus Immobile Collateral," NBER Working Papers 22619, National Bureau of Economic Research, Inc.
    22. Xu, Yuhong & Yang, Zhenlin, 2020. "Specification Tests for Temporal Heterogeneity in Spatial Panel Data Models with Fixed Effects," Regional Science and Urban Economics, Elsevier, vol. 81(C).
    23. Yamamoto, Yohei & Tanaka, Shinya, 2015. "Testing for factor loading structural change under common breaks," Journal of Econometrics, Elsevier, vol. 189(1), pages 187-206.
    24. Tatsushi Oka & Pierre Perron, 2016. "Testing for Common Breaks in a Multiple Equations System," Papers 1606.00092, arXiv.org, revised Jan 2018.
    25. Shu, Lei & Chen, Yu & Zhang, Weiping & Wang, Xueqin, 2022. "Spatial rank-based high-dimensional change point detection via random integration," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
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    Cited by:

    1. Emirmahmutoglu, Furkan & Omay, Tolga, 2014. "Reexamining the PPP hypothesis: A nonlinear asymmetric heterogeneous panel unit root test," Economic Modelling, Elsevier, vol. 40(C), pages 184-190.
    2. Kurt A. Hafner & David Mayer-Foulkes, 2012. "Fertility, Human Development, and Economic Growth: Long- term Short-term Causal Links," DEGIT Conference Papers c017_024, DEGIT, Dynamics, Economic Growth, and International Trade.
    3. Gioldasis, Georgios & Musolesi, Antonio & Simioni, Michel, 2023. "Interactive R&D spillovers: An estimation strategy based on forecasting-driven model selection," International Journal of Forecasting, Elsevier, vol. 39(1), pages 144-169.
    4. Ghoshray, Atanu & Monfort, Mercedes & Ordóñez, Javier, 2020. "Re-examining inequality persistence," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 14, pages 1-9.
    5. Xingwu Zhou & Martin Solberger, 2017. "A Lagrange Multiplier-Type Test for Idiosyncratic Unit Roots in the Exact Factor Model," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(1), pages 22-50, January.
    6. Joakim Westerlund & Mehdi Hosseinkouchack, 2016. "Modified CADF and CIPS Panel Unit Root Statistics with Standard Chi-squared and Normal Limiting Distributions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(3), pages 347-364, June.
    7. Westerlund, Joakim & Larsson, Rolf, 2015. "New tools for understanding the local asymptotic power of panel unit root tests," Journal of Econometrics, Elsevier, vol. 188(1), pages 59-93.
    8. Afees A. Salisu, 2018. "United we stand, divided we fall: A PANICCA test evidence for stock exchanges in OECD," Working Papers 049, Centre for Econometric and Allied Research, University of Ibadan.
    9. Ostadzad, Ali Hossein, 2022. "Innovation and carbon emissions: Fixed-effects panel threshold model estimation for renewable energy," Renewable Energy, Elsevier, vol. 198(C), pages 602-617.
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    11. Rafaty, Ryan & Dolphin, Geoffroy & Pretis, Felix, 2021. "Carbon Pricing and the Elasticity of CO2 Emissions," RFF Working Paper Series 21-33, Resources for the Future.
    12. Feng, Gen-Fu & Wang, Quan-Jing & Chu, Yin & Wen, Jun & Chang, Chun-Ping, 2021. "Does the shale gas boom change the natural gas price-production relationship? Evidence from the U.S. market," Energy Economics, Elsevier, vol. 93(C).
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    40. Joakim Westerlund, 2016. "An IV Test for a Unit Root in Generally Trending and Correlated Panels," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(5), pages 752-764, October.
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    44. Ana Angulo & Peter Burridge & Jes�s Mur, 2017. "Testing for breaks in the weighting matrix," Documentos de Trabajo dt2017-01, Facultad de Ciencias Económicas y Empresariales, Universidad de Zaragoza.
    45. Georgios Gioldasis & Antonio Musolesi & Michel Simioni, 2021. "Interactive R&D Spillovers: An estimation strategy based on forecasting-driven model selection," SEEDS Working Papers 0621, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Jun 2021.
    46. Antonia Arsova, 2019. "Exchange rate pass-through to import prices in Europe: A panel cointegration approach," Working Paper Series in Economics 384, University of Lüneburg, Institute of Economics.
    47. Karaman Örsal, Deniz Dilan, 2014. "Do the global stochastic trends drive the real house prices in OECD countries?," Economics Letters, Elsevier, vol. 123(1), pages 9-13.
    48. Yiannis Karavias & Elias Tzavalis, 2014. "Testing for unit roots in panels with structural changes, spatial and temporal dependence when the time dimension is finite," Discussion Papers 14/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    49. ZEREN, Feyyaz & YILMAZ, Tayfun & BELKE, Murat, 2019. "Testing The Validity Of Fama French Five Factor Asset Pricing Model: Evidence From Turkey," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 23(2), pages 97-113, June.
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    53. Palm, F.C. & Smeekes, S. & Urbain, J.R.Y.J., 2008. "Cross-sectional dependence robust block bootstrap panel unit root tests," Research Memorandum 048, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    54. Ergemen, Yunus Emre & Velasco, Carlos, 2017. "Estimation of fractionally integrated panels with fixed effects and cross-section dependence," Journal of Econometrics, Elsevier, vol. 196(2), pages 248-258.
    55. 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.
    56. Hu, Haiqing & Wei, Wei & Chang, Chun-Ping, 2019. "Do shale gas and oil productions move in convergence? An investigation using unit root tests with structural breaks," Economic Modelling, Elsevier, vol. 77(C), pages 21-33.
    57. Wilman Gómez & Carlos Esteban Posada & Remberto Rhenals, 2018. "Determinants of Total Factor Productivity: The cases of the main Latin American and emerging economies of Asia (1960 - 2015)," Documentos de Trabajo de Valor Público 17203, Universidad EAFIT.
    58. Atwi, Majed & Barberán, Ramón & Mur, Jesús & Angulo, Ana, 2018. "CO2 Kuznets Curve Revisited: From Cross-Sections to Panel Data Models," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 40, pages 169-196.
    59. Deniz Dilan Karaman Örsal, 2021. "Long-run economic determinants of asylum applications," Economics Bulletin, AccessEcon, vol. 41(1), pages 48-59.
    60. Antonia Arsova, 2021. "Exchange rate pass-through to import prices in Europe: a panel cointegration approach," Empirical Economics, Springer, vol. 61(1), pages 61-100, July.
    61. Alejandro C. García-Cintado & Diego Romero-Ávila & Carlos Usabiaga, 2016. "The economic integration of Spain: a change in the inflation pattern," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 25(1), pages 1-41, December.
    62. Claudio Detotto & Sauveur Giannoni & Claire Goavec, 2017. "Does good governance attract tourists?," Working Papers 002, Laboratoire Lieux, Identités, eSpaces et Activités (LISA).
    63. Georgios Gioldasis & Antonio Musolesi & Michel Simioni, 2021. "Interactive R&D Spillovers: an estimation strategy based on forecasting-driven model selection," Working Papers hal-03224910, HAL.
    64. Carmelo Algeri & Luc Anselin & Antonio Fabio Forgione & Carlo Migliardo, 2022. "Spatial dependence in the technical efficiency of local banks," Papers in Regional Science, Wiley Blackwell, vol. 101(3), pages 685-716, June.
    65. Mitch Kunce, 2022. "A 'Natural' Suicide Rate, Hysteresis or Suicide Persistence? Evidence from U.S. State-Level Panel Data, 1980-2020," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 11(2), pages 1-2.
    66. Gregori, Tullio, 2021. "Protectionism and international trade: A long-run view," International Economics, Elsevier, vol. 165(C), pages 1-13.
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    Cited by:

    1. Jean-Armand Gnagne & Kevin Moran, 2020. "Forecasting Bank Failures in a Data-Rich Environment," Working Papers 20-13, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    2. Francisco Dias & Maximiano Pinheiro & António Rua, 2010. "Forecasting using targeted diffusion indexes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(3), pages 341-352.
    3. Jack Fosten, 2016. "Model selection with factors and variables," University of East Anglia School of Economics Working Paper Series 2016-07, School of Economics, University of East Anglia, Norwich, UK..
    4. Teresa Buchen & Klaus Wohlrabe, 2013. "Assessing the Macroeconomic Forecasting Performance of Boosting - Evidence for the United States, the Euro Area, and Germany," CESifo Working Paper Series 4148, CESifo.
    5. Pierdzioch Christian & Gupta Rangan, 2020. "Uncertainty and Forecasts of U.S. Recessions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(4), pages 1-20, September.
    6. Shahram Fattahi & Kiomars Sohaili & Hamed Monkaresi & Fatemeh Mehrabi, 2017. "Modelling and Forecasting Recessions in Oil-exporting Countries: The Case of Iran," International Journal of Economics and Financial Issues, Econjournals, vol. 7(3), pages 569-574.
    7. Lahiri, Kajal & Yang, Cheng, 2022. "Boosting tax revenues with mixed-frequency data in the aftermath of COVID-19: The case of New York," International Journal of Forecasting, Elsevier, vol. 38(2), pages 545-566.
    8. Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020. "Macroeconomic Data Transformations Matter," Papers 2008.01714, arXiv.org, revised Mar 2021.
    9. Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05, Department of Economics, University of Birmingham.
    10. Frenger, Monika & Emrich, Eike & Geber, Sebastian & Follert, Florian & Pierdzioch, Christian, 2019. "The influence of performance parameters on market value," Working Papers of the European Institute for Socioeconomics 30, European Institute for Socioeconomics (EIS), Saarbrücken.
    11. Alessandro Giovannelli & Tommaso Proietti, 2015. "On the Selection of Common Factors for Macroeconomic Forecasting," CEIS Research Paper 332, Tor Vergata University, CEIS, revised 12 Mar 2015.
    12. Rossi, Lorenza & Zanetti Chini, Emilio, 2021. "Temporal disaggregation of business dynamics: New evidence for U.S. economy," Journal of Macroeconomics, Elsevier, vol. 69(C).
    13. Kai Carstensen & Steffen Henzel & Johannes Mayr & Klaus Wohlrabe, 2009. "IFOCAST: Methods of the Ifo short-term forecast," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(23), pages 15-28, December.
    14. Maehashi, Kohei & Shintani, Mototsugu, 2020. "Macroeconomic forecasting using factor models and machine learning: an application to Japan," Journal of the Japanese and International Economies, Elsevier, vol. 58(C).
    15. Souhaib Ben Taieb & Rob J Hyndman, 2014. "Boosting multi-step autoregressive forecasts," Monash Econometrics and Business Statistics Working Papers 13/14, Monash University, Department of Econometrics and Business Statistics.
    16. Robert Lehmann & Klaus Wohlrabe, 2016. "Boosting and Regional Economic Forecasting: The Case of Germany," CESifo Working Paper Series 6157, CESifo.
    17. Emrich Eike & Pierdzioch Christian, 2016. "Public Goods, Private Consumption, and Human Capital: Using Boosted Regression Trees to Model Volunteer Labour Supply," Review of Economics, De Gruyter, vol. 67(3), pages 263-283, December.
    18. Norman R. Swanson & Weiqi Xiong & Xiye Yang, 2020. "Predicting interest rates using shrinkage methods, real‐time diffusion indexes, and model combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 587-613, August.
    19. Lorenzo Boldrini & Eric Hillebrand, 2015. "The Forecasting Power of the Yield Curve, a Supervised Factor Model Approach," CREATES Research Papers 2015-39, Department of Economics and Business Economics, Aarhus University.
    20. Saiz, Lorena & Ashwin, Julian & Kalamara, Eleni, 2021. "Nowcasting euro area GDP with news sentiment: a tale of two crises," Working Paper Series 2616, European Central Bank.
    21. Jörg Döpke & Ulrich Fritsche & Christian Pierdzioch, 2015. "Predicting Recessions With Boosted Regression Trees," Working Papers 2015-004, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    22. Marcellino, Massimiliano & Kapetanios, George & Carriero, Andrea, 2009. "Forecasting Large Datasets with Bayesian Reduced Rank Multivariate Models," CEPR Discussion Papers 7446, C.E.P.R. Discussion Papers.
    23. Wei Lin & Zhentao Shi & Yishu Wang & Ting Hin Yan, 2023. "Unfolding Beijing in a Hedonic Way," Computational Economics, Springer;Society for Computational Economics, vol. 61(1), pages 317-340, January.
    24. Pesaran, M.H. & Pick, A. & Timmermann, A., 2009. "Variable Selection and Inference for Multi-period Forecasting Problems," Cambridge Working Papers in Economics 0901, Faculty of Economics, University of Cambridge.
    25. Christian Pierdzioch & Marian Risse & Sebastian Rohloff, 2016. "A boosting approach to forecasting gold and silver returns: economic and statistical forecast evaluation," Applied Economics Letters, Taylor & Francis Journals, vol. 23(5), pages 347-352, March.
    26. Fosten, Jack, 2019. "CO2 emissions and economic activity: A short-to-medium run perspective," Energy Economics, Elsevier, vol. 83(C), pages 415-429.
    27. Kim, Hyun Hak & Swanson, Norman R., 2018. "Mining big data using parsimonious factor, machine learning, variable selection and shrinkage methods," International Journal of Forecasting, Elsevier, vol. 34(2), pages 339-354.
    28. Peter C. B. Phillips & Zhentao Shi, 2021. "Boosting: Why You Can Use The Hp Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 521-570, May.
    29. Ziwei Mei & Zhentao Shi & Peter C. B. Phillips, 2022. "The boosted HP filter is more general than you might think," Cowles Foundation Discussion Papers 2348, Cowles Foundation for Research in Economics, Yale University.
    30. Damian Kozbur, 2017. "Sharp convergence rates for forward regression in high-dimensional sparse linear models," ECON - Working Papers 253, Department of Economics - University of Zurich, revised Apr 2018.
    31. Buchen, Teresa & Wohlrabe, Klaus, 2011. "Forecasting with many predictors: Is boosting a viable alternative?," Economics Letters, Elsevier, vol. 113(1), pages 16-18, October.
    32. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
    33. Cheng, Xu & Hansen, Bruce E., 2015. "Forecasting with factor-augmented regression: A frequentist model averaging approach," Journal of Econometrics, Elsevier, vol. 186(2), pages 280-293.
    34. Pesaran, M. Hashem & Pick, Andreas & Timmermann, Allan, 2011. "Variable selection, estimation and inference for multi-period forecasting problems," Journal of Econometrics, Elsevier, vol. 164(1), pages 173-187, September.
    35. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," PSE Working Papers halshs-02262202, HAL.
    36. Zhentao Shi & Jingyi Huang, 2019. "Forward-Selected Panel Data Approach for Program Evaluation," Papers 1908.05894, arXiv.org, revised Apr 2021.
    37. Kevin Moran & Simplice Aimé Nono & Imad Rherrad, 2018. "Forecasting with Many Predictors: How Useful are National and International Confidence Data?," Cahiers de recherche 1814, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
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    40. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2021. "Economic Predictions With Big Data: The Illusion of Sparsity," Econometrica, Econometric Society, vol. 89(5), pages 2409-2437, September.
    41. Kim, Jaeho, 2015. "Bayesian Inference in a Non-linear/Non-Gaussian Switching State Space Model: Regime-dependent Leverage Effect in the U.S. Stock Market," MPRA Paper 67153, University Library of Munich, Germany.
    42. Matteo Luciani, 2011. "Forecasting with Approximate Dynamic Factor Models: the Role of Non-Pervasive Shocks," Working Papers ECARES ECARES 2011‐022, ULB -- Universite Libre de Bruxelles.
    43. Luca Margaritella & Joakim Westerlund, 2023. "Using information criteria to select averages in CCE," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 405-421.
    44. Lenza, Michele & Moutachaker, Inès & Paredes, Joan, 2023. "Density forecasts of inflation: a quantile regression forest approach," Working Paper Series 2830, European Central Bank.
    45. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2016. "A boosting approach to forecasting the volatility of gold-price fluctuations under flexible loss," Resources Policy, Elsevier, vol. 47(C), pages 95-107.
    46. Akgun, Oguzhan & Pirotte, Alain & Urga, Giovanni, 2020. "Forecasting using heterogeneous panels with cross-sectional dependence," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1211-1227.
    47. 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.
    48. Damian Kozbur, 2015. "Testing-Based Forward Model Selection," ECON - Working Papers 283, Department of Economics - University of Zurich, revised Apr 2018.
    49. Hande Karabiyik & Joakim Westerlund, 2021. "Forecasting using cross-section average–augmented time series regressions," The Econometrics Journal, Royal Economic Society, vol. 24(2), pages 315-333.
    50. Travis J. Berge, 2017. "Understanding Survey Based Inflation Expectations," Finance and Economics Discussion Series 2017-046, Board of Governors of the Federal Reserve System (U.S.).
    51. Jean Armand Gnagne & Kevin Moran, 2018. "Monitoring Bank Failures in a Data-Rich Environment," Cahiers de recherche 1815, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    52. Mittnik, Stefan & Robinzonov, Nikolay & Spindler, Martin, 2015. "Stock market volatility: Identifying major drivers and the nature of their impact," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 1-14.
    53. Guilherme Lindenmeyer & Pedro Pablo Skorin & Hudson da Silva Torrent, 2021. "Using boosting for forecasting electric energy consumption during a recession: a case study for the Brazilian State Rio Grande do Sul," Letters in Spatial and Resource Sciences, Springer, vol. 14(2), pages 111-128, August.
    54. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers halshs-02262202, HAL.
    55. Hyun Hak Kim, 2013. "Forecasting Macroeconomic Variables Using Data Dimension Reduction Methods: The Case of Korea," Working Papers 2013-26, Economic Research Institute, Bank of Korea.
    56. Zeng, Jing, 2014. "Forecasting Aggregates with Disaggregate Variables: Does boosting help to select the most informative predictors?," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100310, Verein für Socialpolitik / German Economic Association.
    57. Fan, Jianqing & Xue, Lingzhou & Yao, Jiawei, 2017. "Sufficient forecasting using factor models," Journal of Econometrics, Elsevier, vol. 201(2), pages 292-306.
    58. Shi, Zhentao, 2016. "Econometric estimation with high-dimensional moment equalities," Journal of Econometrics, Elsevier, vol. 195(1), pages 104-119.
    59. Antoine A. Djogbenou, 2017. "Model Selection In Factor-augmented Regressions With Estimated Factors," Working Paper 1391, Economics Department, Queen's University.
    60. Jing Zeng, 2014. "Forecasting Aggregates with Disaggregate Variables: Does Boosting Help to Select the Most Relevant Predictors?," Working Paper Series of the Department of Economics, University of Konstanz 2014-20, Department of Economics, University of Konstanz.
    61. Tan, Xueping & Sirichand, Kavita & Vivian, Andrew & Wang, Xinyu, 2022. "Forecasting European carbon returns using dimension reduction techniques: Commodity versus financial fundamentals," International Journal of Forecasting, Elsevier, vol. 38(3), pages 944-969.
    62. Kim, Hyun Hak & Swanson, Norman R., 2014. "Forecasting financial and macroeconomic variables using data reduction methods: New empirical evidence," Journal of Econometrics, Elsevier, vol. 178(P2), pages 352-367.
    63. Kihwan Kim & Hyun Hak Kim & Norman R. Swanson, 2023. "Mixing mixed frequency and diffusion indices in good times and in bad: an assessment based on historical data around the great recession of 2008," Empirical Economics, Springer, vol. 64(3), pages 1421-1469, March.
    64. Embaye, Weldensie T. & Zereyesus, Yacob A., 2017. "Measuring the value of housing services in household surveys: an application of machine learning approach," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252851, Southern Agricultural Economics Association.
    65. Damian Kozbur, 2013. "Inference in additively separable models with a high-dimensional set of conditioning variables," ECON - Working Papers 284, Department of Economics - University of Zurich, revised Apr 2018.
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    69. Wolfgang Nierhaus & Timo Wollmershäuser, 2016. "ifo Konjunkturumfragen und Konjunkturanalyse: Band II," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 72.
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    71. Lehmann, Robert & Wohlrabe, Klaus, 2015. "The role of component-wise boosting for regional economic forecasting," MPRA Paper 68186, University Library of Munich, Germany, revised 03 Dec 2015.
    72. Paolo Fornaro & Henri Luomaranta, 2020. "Nowcasting Finnish real economic activity: a machine learning approach," Empirical Economics, Springer, vol. 58(1), pages 55-71, January.
    73. Lorenzo Boldrini & Eric Hillebrand, 2015. "Supervision in Factor Models Using a Large Number of Predictors," CREATES Research Papers 2015-38, Department of Economics and Business Economics, Aarhus University.
    74. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers 2019-4, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.

  40. Ng Serena & Bai Jushan, 2009. "Selecting Instrumental Variables in a Data Rich Environment," Journal of Time Series Econometrics, De Gruyter, vol. 1(1), pages 1-34, April.

    Cited by:

    1. Tae-Hwy Lee & Tao Wang, 2023. "Estimation and Testing of Forecast Rationality with Many Moments," Working Papers 202307, University of California at Riverside, Department of Economics.
    2. Tomohiro Ando & Naoya Sueishi, 2019. "On the Convergence Rate of the SCAD-Penalized Empirical Likelihood Estimator," Econometrics, MDPI, vol. 7(1), pages 1-14, March.
    3. Ludovica Gambaro & Guido Neidhöfer & C. Katharina Spieß, 2019. "The Effect of Early Childhood Education and Care Services on the Social Integration of Refugee Families," Discussion Papers of DIW Berlin 1828, DIW Berlin, German Institute for Economic Research.
    4. Christoph Breunig & Enno Mammen & Anna Simoni, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Post-Print hal-03089879, HAL.
    5. Stephane Dees & M. Hashem Pesaran & L. Vanessa Smith & Ron P. Smith, 2009. "Identification of New Keynesian Phillips Curves from a Global Perspective," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(7), pages 1481-1502, October.
    6. Bayar, Omer, 2018. "Weak instruments and estimated monetary policy rules," Journal of Macroeconomics, Elsevier, vol. 58(C), pages 308-317.
    7. Geoffrey R. Dunbar & Casey Jones, 2018. "The (Un)Demand for Money in Canada," Staff Working Papers 18-20, Bank of Canada.
    8. Berriel, Tiago & Medeiros, Marcelo C. & Sena, Marcelo J., 2016. "Instrument selection for estimation of a forward-looking Phillips Curve," Economics Letters, Elsevier, vol. 145(C), pages 123-125.
    9. Scheufele, Rolf, 2008. "Evaluating the German (New Keynesian) Phillips Curve," IWH Discussion Papers 10/2008, Halle Institute for Economic Research (IWH).
    10. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2013. "High dimensional methods and inference on structural and treatment effects," CeMMAP working papers CWP59/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Cheng, Xu & Liao, Zhipeng, 2015. "Select the valid and relevant moments: An information-based LASSO for GMM with many moments," Journal of Econometrics, Elsevier, vol. 186(2), pages 443-464.
    12. Max-Sebastian Dov`i, 2021. "Inference on the New Keynesian Phillips Curve with Very Many Instrumental Variables," Papers 2101.09543, arXiv.org, revised Mar 2021.
    13. Hao Hao & Bai Huang & Tae-Hwy Lee, 2022. "Model Averaging Estimation of Panel Data Models with Many Instruments and Boosting," Working Papers 202212, University of California at Riverside, Department of Economics.
    14. Belloni, Alexandre & Hansen, Christian & Newey, Whitney, 2022. "High-dimensional linear models with many endogenous variables," Journal of Econometrics, Elsevier, vol. 228(1), pages 4-26.
    15. Hansen, Christian & Kozbur, Damian, 2014. "Instrumental variables estimation with many weak instruments using regularized JIVE," Journal of Econometrics, Elsevier, vol. 182(2), pages 290-308.
    16. Bhatt, Vipul & Kishor, Kundan & Marfatia, Hardik, 2017. "Estimating excess sensitivity and habit persistence in consumption using Greenbook forecast as an instrument," MPRA Paper 79748, University Library of Munich, Germany.
    17. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2010. "LASSO Methods for Gaussian Instrumental Variables Models," Papers 1012.1297, arXiv.org, revised Feb 2011.
    18. Victor Chernozhukov & Iv'an Fern'andez-Val & Chen Huang & Weining Wang, 2024. "Arellano-Bond LASSO Estimator for Dynamic Linear Panel Models," Papers 2402.00584, arXiv.org, revised Apr 2024.
    19. Gambaro, Ludovica & Neidhöfer, Guido & Spiess, C. Katharina, 2021. "The effect of early childhood education and care services on the integration of refugee families," Labour Economics, Elsevier, vol. 72(C).
    20. Xu Cheng & Zhipeng Liao, 2012. "Select the Valid and Relevant Moments: A One-Step Procedure for GMM with Many Moments," PIER Working Paper Archive 12-045, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    21. Sirisankanan, Aeggarchat, 2023. "The Response of Household Savings to Anticipated Income Changes: Natural Experiments Using Natural and Non-Natural Factors," Journal of Economic Development, The Economic Research Institute, Chung-Ang University, vol. 48(2), pages 1-31, June.
    22. Omer Bayar, 2022. "Reducing large datasets to improve the identification of estimated policy rules," Empirical Economics, Springer, vol. 63(1), pages 113-140, July.
    23. Vipul Bhatt & N. Kundan Kishor & Hardik Marfatia, 2020. "Estimating Excess Sensitivity and Habit Persistence in Consumption Using Greenbook Forecasts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(2), pages 257-284, April.

  41. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.

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    1. Dominik Schraff & Frank Schimmelfennig, 2019. "Eurozone bailouts and national democracy: Detachment or resilience?," European Union Politics, , vol. 20(3), pages 361-383, September.
    2. Mastromarco, Camilla & Simar, Leopold, 2014. "Global Dependence and Productivity: A Robust Nonparametric World Frontier Analysis," LIDAM Discussion Papers ISBA 2014049, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    3. Eberhardt, Markus & Helmers, Christian & Strauss, Hubert, 2010. "Do spillovers matter when estimating private returns to R&D?," Economic and Financial Reports 2010/1, European Investment Bank, Economics Department.
    4. Simone Bertoli & Herbert Brücker & Jesús Fernández-Huertas Moraga, 2013. "The European Crisis and Migration to Germany: Expectations and the Diversion of Migration Flows," CERDI Working papers halshs-00913869, HAL.
    5. Rustam Ibragimov & Johan Walden, 2011. "Value at risk and efficiency under dependence and heavy-tailedness: models with common shocks," Annals of Finance, Springer, vol. 7(3), pages 285-318, August.
    6. Simone Bertoli & Herbert Brücker & Jesús Fernández-Huertas Moraga, 2016. "The European crisis and migration to Germany," Post-Print hal-01687482, HAL.
    7. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Productivity Measurement, Model Averaging, and World Trends in Growth and Inequality," Working Papers 15-019, Rice University, Department of Economics.
    8. Simplice A. Asongu & Voxi H. S. Amavilah & Antonio R. Andres, 2019. "Business Dynamics, Knowledge Economy, and the Economic Performance of African Countries," Working Papers of the African Governance and Development Institute. 19/004, African Governance and Development Institute..
    9. Ivan Fernandez-Val & Martin Weidner, 2013. "Individual and Time Effects in Nonlinear Panel Models with Large N, T," Papers 1311.7065, arXiv.org, revised Dec 2018.
    10. Paulo M.M. Rodrigues & Matei Demetrescu, 2022. "Cross-Sectional Error Dependence in Panel Quantile Regressions," Working Papers w202213, Banco de Portugal, Economics and Research Department.
    11. Demetrescu, Matei & Hosseinkouchack, Mehdi & Rodrigues, Paulo M. M., 2023. "Tests of no cross-sectional error dependence in panel quantile regressions," Ruhr Economic Papers 1041, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    12. 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.
    13. Diego Restrepo-Tobón & Subal Kumbhakar & Kai Sun, 2015. "Obelix vs. Asterix: Size of US commercial banks and its regulatory challenge," Journal of Regulatory Economics, Springer, vol. 48(2), pages 125-168, October.
    14. Asongu, Simplice A. & Nwachukwu, Jacinta C., 2016. "The Mobile Phone in the Diffusion of Knowledge for Institutional Quality in Sub-Saharan Africa," World Development, Elsevier, vol. 86(C), pages 133-147.
    15. Combes, Pierre-Philippe & Gobillon, Laurent, 2015. "The Empirics of Agglomeration Economies," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 247-348, Elsevier.
    16. Qu, Xi & Lee, Lung-fei & Yang, Chao, 2021. "Estimation of a SAR model with endogenous spatial weights constructed by bilateral variables," Journal of Econometrics, Elsevier, vol. 221(1), pages 180-197.
    17. Greenaway-McGrevy, Ryan & Han, Chirok & Sul, Donggyu, 2012. "Asymptotic distribution of factor augmented estimators for panel regression," Journal of Econometrics, Elsevier, vol. 169(1), pages 48-53.
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    19. Moscone, F. & Tosetti, E., 2010. "Testing for error cross section independence with an application to US health expenditure," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 283-291, September.
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    21. Luisa Gagliardi & Simona Iammarino & Andrés Rodríguez-Pose, 2021. "Exposure to OFDI and regional labour markets: evidence for routine and non-routine jobs in Great Britain [Who’s got the aces up his sleeve? Functional specialization of cities and entrepreneurship]," Journal of Economic Geography, Oxford University Press, vol. 21(5), pages 783-806.
    22. Mastromarco, Camilla & Simar, Leopold, 2018. "Globalization and productivity: A robust nonparametric world frontier analysis," LIDAM Reprints ISBA 2018008, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    23. Asongu, Simplice & Odhiambo, Nicholas, 2019. "Governance, Capital flight and Industrialisation in Africa," MPRA Paper 101923, University Library of Munich, Germany.
    24. Simplice A. Asongu, 2019. "FDI in Selected Developing Countries: Evidence from Bundling and Unbundling Governance," Research Africa Network Working Papers 19/057, Research Africa Network (RAN).
    25. Eberhardt, Markus, 2021. "Democracy, Growth, Heterogeneity, and Robustness," CEPR Discussion Papers 16719, C.E.P.R. Discussion Papers.
    26. Dong-Hyeon Kim & Shu-Chin Lin, 2017. "Natural Resources and Economic Development: New Panel Evidence," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 66(2), pages 363-391, February.
    27. Stéphane Bonhomme & Thibaut Lamadon & Elena Manresa, 2022. "Discretizing Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 90(2), pages 625-643, March.
    28. Jie Jiang & Qihang Zhang & Yifan Hui, 2023. "The Impact of Market and Non-Market-Based Environmental Policy Instruments on Firms’ Sustainable Technological Innovation: Evidence from Chinese Firms," Sustainability, MDPI, vol. 15(5), pages 1-21, March.
    29. Daragh Clancy & Lorenzo Ricci, 2019. "Loss aversion, economic sentiments and international consumption smoothing," Working Papers 35, European Stability Mechanism.
    30. Yiren Wang & Peter C. B. Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Cowles Foundation Discussion Papers 2364, Cowles Foundation for Research in Economics, Yale University.
    31. Peng, Bin, 2016. "Inference on modelling cross-sectional dependence for a varying-coefficient model," Economics Letters, Elsevier, vol. 145(C), pages 1-5.
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    33. Rafaty, R. & Dolphin, G. & Pretis, F., 2020. "Carbon pricing and the elasticity of CO2 emissions," Cambridge Working Papers in Economics 20116, Faculty of Economics, University of Cambridge.
    34. Wei Chen & Zaiyan Wei & Karen Xie, 2022. "The Battle for Homes: How Does Home Sharing Disrupt Local Residential Markets?," Management Science, INFORMS, vol. 68(12), pages 8589-8612, December.
    35. Marc K. Chan & Simon S. Kwok, 2022. "The PCDID Approach: Difference-in-Differences When Trends Are Potentially Unparallel and Stochastic," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1216-1233, June.
    36. Bertoli, Simone & Fernández-Huertas Moraga, Jesús & Keita, Sekou, 2016. "The Elasticity of the Migrant Labor Supply: Evidence from Temporary Filipino Migrants," IZA Discussion Papers 10031, Institute of Labor Economics (IZA).
    37. Arnab Bhattacharjee & Jan Ditzen & Sean Holly, 2021. "Spatial and Spatio-temporal Error Correction, Networks and Common Correlated Effects," BEMPS - Bozen Economics & Management Paper Series BEMPS76, Faculty of Economics and Management at the Free University of Bozen.
    38. Kurt Mitman & Iourii Manovskii & Marcus Hagedorn, 2015. "The Impact of Unemployment Benefit Extensions on Employment: The 2014 Employment Miracle?," 2015 Meeting Papers 1318, Society for Economic Dynamics.
    39. In Choi & Jorg Breitung, 2011. "Factor models," Working Papers 1121, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy), revised Dec 2011.
    40. Gioldasis, Georgios & Musolesi, Antonio & Simioni, Michel, 2023. "Interactive R&D spillovers: An estimation strategy based on forecasting-driven model selection," International Journal of Forecasting, Elsevier, vol. 39(1), pages 144-169.
    41. Gagliardi, Luisa, 2019. "The impact of foreign technological innovation on domestic employment via the industry mix," Research Policy, Elsevier, vol. 48(6), pages 1523-1533.
    42. Dmitry Arkhangelsky & Susan Athey & David A. Hirshberg & Guido W. Imbens & Stefan Wager, 2019. "Synthetic Difference in Differences," Working Papers wp2019_1907, CEMFI.
    43. Fei Liu & Jiti Gao & Yanrong Yang, 2020. "Time-Varying Panel Data Models with an Additive Factor Structure," Monash Econometrics and Business Statistics Working Papers 42/20, Monash University, Department of Econometrics and Business Statistics.
    44. Geert Dhaene & Koen Jochmans, 2014. "Split-Panel Jackknife Estimation of Fixed-Effect Models," SciencePo Working papers Main hal-01070553, HAL.
    45. Mingli Chen & Iv'an Fern'andez-Val & Martin Weidner, 2014. "Nonlinear Factor Models for Network and Panel Data," Papers 1412.5647, arXiv.org, revised Oct 2019.
    46. Asongu, Simplice, 2015. "Determinants of Growth in Fast Developing Countries: Evidence from Bundling and Unbundling Institutions," MPRA Paper 67310, University Library of Munich, Germany.
    47. Badi Baltagi & Qu Feng & Chihwa Kao, 2019. "Structural Changes in Heterogeneous Panels with Endogenous Regressors," Center for Policy Research Working Papers 214, Center for Policy Research, Maxwell School, Syracuse University.
    48. Mastromarco Camilla & Laura Serlenga & Yongcheol Shin, 2013. "Globalisation and technological convergence in the EU," Journal of Productivity Analysis, Springer, vol. 40(1), pages 15-29, August.
    49. Gobillon, Laurent & Magnac, Thierry & Selod, Haris, 2012. "L’effet des Zones Franches Urbaines sur le Retour à l’Emploi," CEPREMAP Working Papers (Docweb) 1209, CEPREMAP.
    50. Isabel Casas & Jiti Gao & Shangyu Xie, 2018. "Modelling Time-Varying Income Elasticities of Health Care Expenditure for the OECD," CREATES Research Papers 2018-29, Department of Economics and Business Economics, Aarhus University.
    51. Bresson, G. & Etienne, J-M. & Mohnen, P., 2014. "How important is innovation? : A Bayesian factor-augmented productivity model on panel data," MERIT Working Papers 2014-052, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
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    57. Josip Tica & Viktor Viljevac & Matija Matiæ, 2023. "Employment rate and economic growth:The case of transition countries," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 41(1), pages 9-39.
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    60. Kassouri, Yacouba & Altıntaş, Halil & Alancioğlu, Erdal & Kacou, Kacou Yves Thierry, 2021. "New insights on the debt-growth nexus: A combination of the interactive fixed effects and panel threshold approach," International Economics, Elsevier, vol. 168(C), pages 40-55.
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  42. Bai, Jushan & Kao, Chihwa & Ng, Serena, 2009. "Panel cointegration with global stochastic trends," Journal of Econometrics, Elsevier, vol. 149(1), pages 82-99, April.
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  44. Bai, Jushan & Chen, Zhihong, 2008. "Testing multivariate distributions in GARCH models," Journal of Econometrics, Elsevier, vol. 143(1), pages 19-36, March.

    Cited by:

    1. Jonas Dovern & Hans Manner, 2018. "Order Invariant Tests for Proper Calibration of Multivariate Density Forecasts," CESifo Working Paper Series 7023, CESifo.
    2. Gabriele Fiorentini & Enrique Sentana, 2021. "Specification tests for non‐Gaussian maximum likelihood estimators," Quantitative Economics, Econometric Society, vol. 12(3), pages 683-742, July.
    3. Dovern, Jonas & Manner, Hans, 2016. "Robust Evaluation of Multivariate Density Forecasts," VfS Annual Conference 2016 (Augsburg): Demographic Change 145547, Verein für Socialpolitik / German Economic Association.
    4. Francq, Christian & Jiménez Gamero, Maria Dolores & Meintanis, Simos, 2015. "Tests for sphericity in multivariate garch models," MPRA Paper 67411, University Library of Munich, Germany.
    5. João Henrique G. Mazzeu & Gloria González-Rivera & Esther Ruiz & Helena Veiga, 2020. "A bootstrap approach for generalized Autocontour testing Implications for VIX forecast densities," Econometric Reviews, Taylor & Francis Journals, vol. 39(10), pages 971-990, November.
    6. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    7. Polanski, Arnold & Stoja, Evarist, 2012. "Efficient evaluation of multidimensional time-varying density forecasts, with applications to risk management," International Journal of Forecasting, Elsevier, vol. 28(2), pages 343-352.
    8. M. Jiménez Gamero, 2014. "On the empirical characteristic function process of the residuals in GARCH models and applications," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(2), pages 409-432, June.
    9. Francq, C. & Jiménez-Gamero, M.D. & Meintanis, S.G., 2017. "Tests for conditional ellipticity in multivariate GARCH models," Journal of Econometrics, Elsevier, vol. 196(2), pages 305-319.
    10. Kheifets, Igor L., 2018. "Multivariate specification tests based on a dynamic Rosenblatt transform," Computational Statistics & Data Analysis, Elsevier, vol. 124(C), pages 1-14.
    11. Ko, Stanley I.M. & Park, Sung Y., 2013. "Multivariate density forecast evaluation: A modified approach," International Journal of Forecasting, Elsevier, vol. 29(3), pages 431-441.
    12. Dovern, Jonas & Manner, Hans, 2016. "Order Invariant Evaluation of Multivariate Density Forecasts," Working Papers 0608, University of Heidelberg, Department of Economics.
    13. González-Rivera, Gloria & Yoldas, Emre, 2012. "Autocontour-based evaluation of multivariate predictive densities," International Journal of Forecasting, Elsevier, vol. 28(2), pages 328-342.
    14. Donghang Luo & Ke Zhu & Huan Gong & Dong Li, 2020. "Testing error distribution by kernelized Stein discrepancy in multivariate time series models," Papers 2008.00747, arXiv.org.
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    18. Igor Kheifets, 2014. "Specification Tests for Nonlinear Dynamic Models," Cowles Foundation Discussion Papers 1937, Cowles Foundation for Research in Economics, Yale University, revised Oct 2014.
    19. Igor Kheifets, 2011. "Goodness-of-fit testing (in Russian)," Quantile, Quantile, issue 9, pages 25-34, July.
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    21. Polanski, Arnold & Stoja, Evarist & Zhang, Ren, 2013. "Multidimensional risk and risk dependence," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3286-3294.
    22. Karanasos, M. & Kartsaklas, A., 2009. "Dual long-memory, structural breaks and the link between turnover and the range-based volatility," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 838-851, December.
    23. Herman J. Bierens & Li Wang, 2017. "Weighted simulated integrated conditional moment tests for parametric conditional distributions of stationary time series processes," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 103-135, March.
    24. Lee, Sangyeol & Ng, Chi Tim, 2011. "Normality test for multivariate conditional heteroskedastic dynamic regression models," Economics Letters, Elsevier, vol. 111(1), pages 75-77, April.

  45. Jushan Bai & Serena Ng, 2008. "Extremum Estimation when the Predictors are Estimated from Large Panels," Annals of Economics and Finance, Society for AEF, vol. 9(2), pages 201-222, November.

    Cited by:

    1. T. Ando & R. S. Tsay, 2009. "‘Model selection for generalized linear models with factor‐augmented predictors’," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 25(3), pages 243-246, May.
    2. Andrea Cipollini & George Kapetanios, 2008. "Forecasting Financial Crises and Contagion in Asia using Dynamic Factor Analysis," Center for Economic Research (RECent) 014, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    3. Eichengreen, Barry & Mody, Ashoka & Nedeljkovic, Milan & Sarno, Lucio, 2012. "How the Subprime Crisis went global: Evidence from bank credit default swap spreads," Journal of International Money and Finance, Elsevier, vol. 31(5), pages 1299-1318.
    4. Olfa Kaabia & Ilyes Abid, 2012. "Theoretical Channels of International,Transmission During the Subprime Crisis to OCDE Countries: A FAVAR Model Under Bayesian Framework," Working Papers hal-04141045, HAL.
    5. González-Rivera, Gloria & Maldonado, Javier & Ruiz, Esther, 2019. "Growth in stress," International Journal of Forecasting, Elsevier, vol. 35(3), pages 948-966.
    6. Demetrescu, Matei & Hacioglu Hoke, Sinem, 2018. "Predictive regressions under asymmetric loss: factor augmentation and model selection," Bank of England working papers 723, Bank of England.
    7. Liang Chen & Juan Jose Dolado & Jesus Gonzalo, 2019. "Quantile Factor Models," Papers 1911.02173, arXiv.org, revised Sep 2020.
    8. Bellégo, C. & Ferrara, L., 2012. "Macro-financial linkages and business cycles: A factor-augmented probit approach," Economic Modelling, Elsevier, vol. 29(5), pages 1793-1797.
    9. Zhihong Chen & Azhar Iqbal & Huiwen Lai, 2011. "Forecasting the probability of US recessions: a Probit and dynamic factor modelling approach," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 44(2), pages 651-672, May.
    10. Gloria González-Rivera & Carlos Vladimir Rodríguez-Caballero & Esther Ruiz Ortega, 2021. "Expecting the unexpected: economic growth under stress," CREATES Research Papers 2021-06, Department of Economics and Business Economics, Aarhus University.
    11. Mikkelsen, Jakob Guldbæk & Hillebrand, Eric & Urga, Giovanni, 2019. "Consistent estimation of time-varying loadings in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 208(2), pages 535-562.
    12. Kerem Tuzcuoglu, 2019. "Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects," Staff Working Papers 19-16, Bank of Canada.
    13. Giglio, Stefano & Kelly, Bryan & Pruitt, Seth, 2016. "Systemic risk and the macroeconomy: An empirical evaluation," Journal of Financial Economics, Elsevier, vol. 119(3), pages 457-471.
    14. Huiwen Lai & Eric C. Y. Ng, 2020. "On business cycle forecasting," Frontiers of Business Research in China, Springer, vol. 14(1), pages 1-26, December.
    15. Olfa Kaabia & Ilyes Abid, 2012. "Theoretical Channels of International,Transmission During the Subprime Crisis to OCDE Countries : A FAVAR Model Under Bayesian Framework," EconomiX Working Papers 2012-40, University of Paris Nanterre, EconomiX.

  46. Bai, Jushan & Ng, Serena, 2008. "Large Dimensional Factor Analysis," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(2), pages 89-163, June.

    Cited by:

    1. Brandon J. Bates & Mikkel Plagborg-Møller & James H. Stock & Mark W. Watson, "undated". "Consistent factor estimation in dynamic factor models with structural instability," Working Paper 84631, Harvard University OpenScholar.
    2. Gabriele Fiorentini & Enrique Sentana, 2009. "Dynamic Specification Tests for Static Factor Models," Working Papers wp2009_0912, CEMFI.
    3. Konomi Tonogi & Jun-ichi Nakamura & Kazumi Asako, 2014. "Heterogeneity of Capital Stocks in Japan: Classification by Factor Analysis," Journal of Knowledge Management, Economics and Information Technology, ScientificPapers.org, vol. 4(2), pages 1-10, April.
    4. Nathan Bedock & Dalibor Stevanović, 2017. "An empirical study of credit shock transmission in a small open economy," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 50(2), pages 541-570, May.
    5. 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.
    6. Miranda Gualdrón, Karen Alejandra & Poncela, Pilar & Ruiz Ortega, Esther, 2021. "Dynamic factor models: does the specification matter?," DES - Working Papers. Statistics and Econometrics. WS 32210, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. Byron Botha & Rulof Burger & Kevin Kotze & Neil Rankin & Daan Steenkamp, 2022. "Big data forecasting of South African inflation," School of Economics Macroeconomic Discussion Paper Series 2022-03, School of Economics, University of Cape Town.
    8. Derek Bunn & Julien Chevallier & Yannick Le Pen & Benoît Sévi, 2017. "Fundamental and Financial Influences on the Co-movement of Oil and Gas prices," Post-Print hal-01619890, HAL.
    9. Reichlin, Lucrezia & Doz, Catherine & Giannone, Domenico, 2006. "A Quasi Maximum Likelihood Approach for Large Approximate Dynamic Factor Models," CEPR Discussion Papers 5724, C.E.P.R. Discussion Papers.
    10. Gagliardini, Patrick & Gouriéroux, Christian, 2017. "Double instrumental variable estimation of interaction models with big data," Journal of Econometrics, Elsevier, vol. 201(2), pages 176-197.
    11. Sentana, Enrique & Galesi, Alessandro, 2015. "Fast ML estimation of dynamic bifactor models: an application to European inflation," CEPR Discussion Papers 10461, C.E.P.R. Discussion Papers.
    12. Yannick Le Pen & Benoît Sévi, 2013. "Futures trading and the excess comovement of commodity prices," Working Papers 2013-19, Department of Research, Ipag Business School.
    13. Irma Hindrayanto & Siem Jan Koopman & Jasper de Winter, 2014. "Nowcasting and Forecasting Economic Growth in the Euro Area using Principal Components," Tinbergen Institute Discussion Papers 14-113/III, Tinbergen Institute.
    14. Bresson, G. & Etienne, J-M. & Mohnen, P., 2014. "How important is innovation? : A Bayesian factor-augmented productivity model on panel data," MERIT Working Papers 2014-052, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    15. Laurent Callot & Johannes Tang Kristensen, 2016. "Regularized Estimation of Structural Instability in Factor Models: The US Macroeconomy and the Great Moderation," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 437-479, Emerald Group Publishing Limited.
    16. Reese, Simon, 2015. "Asymptotic Inference in the Lee-Carter Model for Modelling Mortality Rates," Working Papers 2015:16, Lund University, Department of Economics.
    17. Onatski, Alexei, 2015. "Asymptotic analysis of the squared estimation error in misspecified factor models," Journal of Econometrics, Elsevier, vol. 186(2), pages 388-406.
    18. Siem Jan Koopman & Geert Mesters, 2014. "Empirical Bayes Methods for Dynamic Factor Models," Tinbergen Institute Discussion Papers 14-061/III, Tinbergen Institute.
    19. Sven Otto & Nazarii Salish, 2022. "Approximate Factor Models for Functional Time Series," Papers 2201.02532, arXiv.org, revised Aug 2022.
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    1. Yu, Ping, 2015. "Consistency of the least squares estimator in threshold regression with endogeneity," Economics Letters, Elsevier, vol. 131(C), pages 41-46.
    2. Pang, Tianxiao & Tai-Leung Chong, Terence & Zhang, Danna & Liang, Yanling, 2018. "Structural Change In Nonstationary Ar(1) Models," Econometric Theory, Cambridge University Press, vol. 34(5), pages 985-1017, October.
    3. MeiChi Huang, 2017. "Vulnerabilities to housing bubbles: Evidence from linkages between housing prices and income fundamentals," International Finance, Wiley Blackwell, vol. 20(1), pages 64-91, March.
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    5. Koo, Bonsoo & Seo, Myung Hwan, 2015. "Structural-break models under mis-specification: Implications for forecasting," Journal of Econometrics, Elsevier, vol. 188(1), pages 166-181.
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    7. TAYANAGI, Toshikazu & 田柳, 俊和 & KUROZUMI, Eiji & 黒住, 英司, 2023. "Change-point estimators with the weighted objective function when estimating breaks one at a time," Discussion Papers 2023-04, Graduate School of Economics, Hitotsubashi University.
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    12. Chong Terence T. L. & He Qing & Hinich Melvin J, 2008. "The Nonlinear Dynamics of Foreign Reserves and Currency Crises," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(4), pages 1-18, December.
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  48. Bai, Jushan & Ng, Serena, 2008. "Forecasting economic time series using targeted predictors," Journal of Econometrics, Elsevier, vol. 146(2), pages 304-317, October.

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    36. T. Ando & R. S. Tsay, 2009. "‘Model selection for generalized linear models with factor‐augmented predictors’," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 25(3), pages 243-246, May.
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    38. Stock, James H. & Watson, Mark, 2011. "Dynamic Factor Models," Scholarly Articles 28469541, Harvard University Department of Economics.
    39. Ricardo Reis & Mark W. Watson, 2007. "Relative Goods' Prices, Pure Inflation, and the Phillips Correlation," NBER Working Papers 13615, National Bureau of Economic Research, Inc.
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    3. Florian Gunsilius & Susanne M. Schennach, 2017. "A nonlinear principal component decomposition," CeMMAP working papers CWP16/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Necati Tekatli, 2010. "A Bayesian Generalized Factor Model with Comparative Analysis (Genellestirilmis Faktor Modellerinin Bayesyen Yaklasimi ve Karsilastirmali Analizi)," Working Papers 1018, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    5. Simplice A. Asongu & Voxi H. S. Amavilah & Antonio R. Andres, 2019. "Business Dynamics, Knowledge Economy, and the Economic Performance of African Countries," Working Papers of the African Governance and Development Institute. 19/004, African Governance and Development Institute..
    6. Marine Carrasco & Barbara Rossi, 2016. "In-sample inference and forecasting in misspecified factor models," Economics Working Papers 1530, Department of Economics and Business, Universitat Pompeu Fabra.
    7. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
    8. Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2018. "Common factors of commodity prices," Research Bulletin, European Central Bank, vol. 51.
    9. YAMAMOTO, Yohei & 山本, 庸平, 2015. "Asymptotic Inference for Common Factor Models in the Presence of Jumps," Discussion Papers 2015-05, Graduate School of Economics, Hitotsubashi University.
    10. Alessi, Lucia & Kerssenfischer, Mark, 2016. "The response of asset prices to monetary policy shocks: stronger than thought," Working Paper Series 1967, European Central Bank.
    11. Young Se Kim & Hyok Jung Kim, 2015. "Disaggregated Approach to Measuring Core Inflation," Korean Economic Review, Korean Economic Association, vol. 31, pages 145-176.
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    14. Yuefeng Han & Dan Yang & Cun-Hui Zhang & Rong Chen, 2021. "CP Factor Model for Dynamic Tensors," Papers 2110.15517, arXiv.org, revised Apr 2024.
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    16. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2004. "The generalised dynamic factor model: consistency and rates," ULB Institutional Repository 2013/10133, ULB -- Universite Libre de Bruxelles.
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    724. Proietti, Tommaso, 2008. "Estimation of Common Factors under Cross-Sectional and Temporal Aggregation Constraints: Nowcasting Monthly GDP and its Main Components," MPRA Paper 6860, University Library of Munich, Germany.
    725. Lena Boneva (Körber) & Oliver Linton & Michael Vogt, 2013. "A semiparametric model for heterogeneous panel data with fixed effects," CeMMAP working papers 02/13, Institute for Fiscal Studies.
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    727. Guowei Cui & Vasilis Sarafidis & Takashi Yamagata, 2020. "IV Estimation of Spatial Dynamic Panels with Interactive Effects: Large Sample Theory and an Application on Bank Attitude," Monash Econometrics and Business Statistics Working Papers 11/20, Monash University, Department of Econometrics and Business Statistics.
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    Cited by:

    1. Lee, Sangyeol, 2013. "A maximum entropy type test of fit: Composite hypothesis case," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 59-67.
    2. Norman R. Swanson & Nii Ayi Armah, 2011. "Predictive Inference Under Model Misspecification with an Application to Assessing the Marginal Predictive Content of Money for Output," Departmental Working Papers 201103, Rutgers University, Department of Economics.
    3. Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019. "From fixed-event to fixed-horizon density forecasts: Obtaining measures of multi-horizon uncertainty from survey density forecasts," Economics Working Papers 1689, Department of Economics and Business, Universitat Pompeu Fabra.
    4. Isao Ishida, 2005. "Scanning Multivariate Conditional Densities with Probability Integral Transforms," CARF F-Series CARF-F-045, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    5. Jonas Dovern & Hans Manner, 2018. "Order Invariant Tests for Proper Calibration of Multivariate Density Forecasts," CESifo Working Paper Series 7023, CESifo.
    6. Elena Andreou, 2004. "The Impact of Sampling Frequency and Volatility Estimators on Change-Point Tests," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 290-318.
    7. Sokbae (Simon) Lee & Kyungchui (Kevin) Song & Yoon-Jae Whang, 2011. "Testing functional inequalities," CeMMAP working papers CWP12/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Gabriele Fiorentini & Enrique Sentana, 2021. "Specification tests for non‐Gaussian maximum likelihood estimators," Quantitative Economics, Econometric Society, vol. 12(3), pages 683-742, July.
    9. Barbara Rossi & Tatevik Sekhposyan, 2015. "Alternative Tests for Correct Specification of Conditional Predictive Densities," Working Papers 758, Barcelona School of Economics.
    10. Carlos Velasco, 2013. "Comments on: Model-free model-fitting and predictive distributions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(2), pages 237-239, June.
    11. Dovern, Jonas & Manner, Hans, 2016. "Robust Evaluation of Multivariate Density Forecasts," VfS Annual Conference 2016 (Augsburg): Demographic Change 145547, Verein für Socialpolitik / German Economic Association.
    12. Qu, Zhongjun, 2008. "Testing for structural change in regression quantiles," Journal of Econometrics, Elsevier, vol. 146(1), pages 170-184, September.
    13. Juan Mora & Alicia Pérez-Alonso, 2009. "Specification tests for the distribution of errors in nonparametric regression: a martingale approach," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 21(4), pages 441-452.
    14. João Henrique G. Mazzeu & Gloria González-Rivera & Esther Ruiz & Helena Veiga, 2020. "A bootstrap approach for generalized Autocontour testing Implications for VIX forecast densities," Econometric Reviews, Taylor & Francis Journals, vol. 39(10), pages 971-990, November.
    15. Yanqin Fan & Xiaohong Chen & Andrew Patton, 2004. "(IAM Series No 003) Simple Tests for Models of Dependence Between Multiple Financial Time Series, with Applications to U.S. Equity Returns and Exchange Rates," FMG Discussion Papers dp483, Financial Markets Group.
    16. Febrer, Antonia & Mora, Juan, 2009. "Flexible estimation of wage distributions in the presence of covariates," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2189-2200, April.
    17. Rossi, Barbara & Sekhposyan, Tatevik, 2013. "Conditional predictive density evaluation in the presence of instabilities," Journal of Econometrics, Elsevier, vol. 177(2), pages 199-212.
    18. Corradi, Valentina & Swanson, Norman R., 2011. "Predictive density construction and accuracy testing with multiple possibly misspecified diffusion models," Journal of Econometrics, Elsevier, vol. 161(2), pages 304-324, April.
    19. Li, Dong & Tao, Yuxin & Yang, Yaxing & Zhang, Rongmao, 2023. "Maximum likelihood estimation for α-stable double autoregressive models," Journal of Econometrics, Elsevier, vol. 236(1).
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    22. Polanski, Arnold & Stoja, Evarist, 2012. "Efficient evaluation of multidimensional time-varying density forecasts, with applications to risk management," International Journal of Forecasting, Elsevier, vol. 28(2), pages 343-352.
    23. Juan Carlos Escanciano & Zaichao Du, 2015. "Backtesting Expected Shortfall: Accounting for Tail Risk," CAEPR Working Papers 2015-001, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    24. Carlos Escanciano, J., 2008. "Joint and marginal specification tests for conditional mean and variance models," Journal of Econometrics, Elsevier, vol. 143(1), pages 74-87, March.
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    26. Valentina Corradi & Norman R. Swanson, 2003. "Bootstrap Specification Tests for Diffusion Processes," Departmental Working Papers 200321, Rutgers University, Department of Economics.
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    29. Juan Mora & Antonia Febrer, 2005. "Wage Distribution In Spain, 1994-1999: An Application Of A Flexible Estimator Of Conditional Distributions," Working Papers. Serie EC 2005-04, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    30. Charles Shaw, 2018. "Conditional heteroskedasticity in crypto-asset returns," Papers 1804.07978, arXiv.org, revised Dec 2018.
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    35. Dovern, Jonas & Manner, Hans, 2016. "Order Invariant Evaluation of Multivariate Density Forecasts," Working Papers 0608, University of Heidelberg, Department of Economics.
    36. Andreou, E. & Werker, B.J.M., 2004. "An Alternative Asymptotic Analysis of Residual-Based Statistics," Other publications TiSEM 93fe16c1-9f21-4dab-9b73-4, Tilburg University, School of Economics and Management.
    37. Thomas Parker, 2010. "A comparison of alternative approaches to sup-norm goodness of fit tests with estimated parameters," CeMMAP working papers CWP34/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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    39. Amendola, Alessandra & Christian, Francq, 2009. "Concepts and tools for nonlinear time series modelling," MPRA Paper 15140, University Library of Munich, Germany.
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    41. Papanicolaou, Alex & Giesecke, Kay, 2016. "Variation-based tests for volatility misspecification," Journal of Econometrics, Elsevier, vol. 191(1), pages 217-230.
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    44. González-Rivera, Gloria & Yoldas, Emre, 2012. "Autocontour-based evaluation of multivariate predictive densities," International Journal of Forecasting, Elsevier, vol. 28(2), pages 328-342.
    45. Xiaohong Chen & Yanqin Fan, 2002. "Evaluating Density Forecasts via the Copula Approach," Vanderbilt University Department of Economics Working Papers 0225, Vanderbilt University Department of Economics, revised Sep 2003.
    46. Hill, Jonathan B. & Aguilar, Mike, 2013. "Moment condition tests for heavy tailed time series," Journal of Econometrics, Elsevier, vol. 172(2), pages 255-274.
    47. Chung-Ming Kuan & Yu-Wei Hsieh, 2006. "Improved HAC Covariance Matrix Estimation Based on Forecast Errors," IEAS Working Paper : academic research 06-A008, Institute of Economics, Academia Sinica, Taipei, Taiwan.
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    49. Gonçalves Mazzeu, Joao Henrique & González-Rivera, Gloria & Ruiz Ortega, Esther & Veiga, Helena, 2016. "A Bootstrap Approach for Generalized Autocontour Testing," DES - Working Papers. Statistics and Econometrics. WS 23457, Universidad Carlos III de Madrid. Departamento de Estadística.
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    71. Andreou, E. & Werker, B.J.M., 2004. "An Alternative Asymptotic Analysis of Residual-Based Statistics," Discussion Paper 2004-56, Tilburg University, Center for Economic Research.
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    73. Shamiri, Ahmed & Shaari, Abu Hassan & Isa, Zaidi, 2007. "Practical Volatility Modeling for Financial Market Risk Management," MPRA Paper 9790, University Library of Munich, Germany, revised 15 May 2008.
    74. Vance Martin & Yoshihiko Nishiyama & John Stachurski, 2011. "A Goodness Of Fit Test For Ergodic Markov Processes," KIER Working Papers 787, Kyoto University, Institute of Economic Research.
    75. Christian Kascha & Francesco Ravazzolo, 2008. "Combining inflation density forecasts," Working Paper 2008/22, Norges Bank.
    76. Chen, Xiaohong & Fan, Yanqin & Patton, Andrew J., 2004. "Simple tests for models of dependence between multiple financial time series, with applications to U.S. equity returns and exchange rates," LSE Research Online Documents on Economics 24681, London School of Economics and Political Science, LSE Library.
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    79. Xiangjin Shen & Hiroki Tsurumi, 2011. "Comparison of Bayesian Model Selection Criteria and Conditional Kolmogorov Test as Applied to Spot Asset Pricing Models," Departmental Working Papers 201126, Rutgers University, Department of Economics.
    80. Shaw, Charles, 2018. "Conditional heteroskedasticity in crypto-asset returns," MPRA Paper 90437, University Library of Munich, Germany.
    81. Cai, Lili & Swanson, Norman R., 2011. "In- and out-of-sample specification analysis of spot rate models: Further evidence for the period 1982-2008," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 743-764, September.
    82. Polanski, Arnold & Stoja, Evarist & Zhang, Ren, 2013. "Multidimensional risk and risk dependence," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3286-3294.
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    84. Juan Carlos Escanciano & Chuan Goh, 2010. "Specification Analysis of Structural Quantile Regression Models," Working Papers tecipa-415, University of Toronto, Department of Economics.
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    1. Óscar Bajo-Rubio & Carmen Díaz-Roldán & Vicente Esteve, "undated". "Us Deficit Sustainability Revisited: A Multiple Structural Change Approach," Working Papers 19-05 Classification-JEL , Instituto de Estudios Fiscales.
    2. Antonio Afonso & Florence Huart & João Tovar Jalles & Piotr Stanek, 2018. "Assessing the sustainability of external imbalances in the European Union," Post-Print hal-01914597, HAL.
    3. Essahbi Essaadi & Jamel Jouini & Wajih Khallouli, 2004. "The Asian Crisis Contagion: A Dynamic Correlation Approach Analysis," Post-Print halshs-00201220, HAL.
    4. Laura Mayoral, 2005. "Further evidence on the statistical properties of real GNP," Economics Working Papers 955, Department of Economics and Business, Universitat Pompeu Fabra, revised Feb 2006.
    5. Zied Ftiti & Walid Hichri, 2014. "The price stability under inflation targeting regime: An analysis with a new intermediate approach," Post-Print halshs-00958660, HAL.
    6. Gogas, Periklis & Papadimitriou, Theophilos & Plakandaras, Vasilios & Gupta, Rangan, 2019. "The Informational Content of the Term-Spread in Forecasting the U.S. Inflation Rate: A Nonlinear Approach," DUTH Research Papers in Economics 3-2016, Democritus University of Thrace, Department of Economics.
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    See citations under working paper version above.
  60. Bai, Jushan & Ng, Serena, 2001. "A consistent test for conditional symmetry in time series models," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 225-258, July.

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    1. Esfandiar Maasoumi & Jeffrey Racine, 2009. "A Robust Entropy-Based Test of Asymmetry for Discrete and Continuous Processes," Econometric Reviews, Taylor & Francis Journals, vol. 28(1-3), pages 246-261.
    2. Joseph Ngatchou-Wandji & Michel Harel, 2013. "A Cramér-von Mises test for symmetry of the error distribution in asymptotically stationary stochastic models," Statistical Inference for Stochastic Processes, Springer, vol. 16(3), pages 207-236, October.
    3. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions," Working Papers 20-02R, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
    4. Francq, Christian & Jiménez Gamero, Maria Dolores & Meintanis, Simos, 2015. "Tests for sphericity in multivariate garch models," MPRA Paper 67411, University Library of Munich, Germany.
    5. Kuosmanen, Timo & Fosgerau, Mogens, 2009. "Neoclassical versus frontier production models? Testing for the skewness of regression residuals," MPRA Paper 24208, University Library of Munich, Germany.
    6. Philippe Lambert & Sébastien Laurent & David Veredas, 2012. "Testing conditional asymmetry. A residual based approach," ULB Institutional Repository 2013/136195, ULB -- Universite Libre de Bruxelles.
    7. Escanciano, J. Carlos, 2010. "Asymptotic Distribution-Free Diagnostic Tests For Heteroskedastic Time Series Models," Econometric Theory, Cambridge University Press, vol. 26(3), pages 744-773, June.
    8. Fujiwara, Ippei & Körber, Lena Mareen & Nagakura, Daisuke, 2013. "Asymmetry in government bond returns," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3218-3226.
    9. Tao Chen & Gautam Tripathi, 2014. "A simple consistent test of conditional symmetry in symmetrically trimmed tobit models," DEM Discussion Paper Series 14-04, Department of Economics at the University of Luxembourg.
    10. Carlos Escanciano, J., 2008. "Joint and marginal specification tests for conditional mean and variance models," Journal of Econometrics, Elsevier, vol. 143(1), pages 74-87, March.
    11. Francq, C. & Jiménez-Gamero, M.D. & Meintanis, S.G., 2017. "Tests for conditional ellipticity in multivariate GARCH models," Journal of Econometrics, Elsevier, vol. 196(2), pages 305-319.
    12. Claude Diebolt & Jamel Trabelsi, 2008. "Human Capital and French Macroeconomic Growth in the Long Run," Working Papers 08-11, Association Française de Cliométrie (AFC).
    13. Narayan, Paresh Kumar & Popp, Stephan, 2009. "Can the electricity market be characterised by asymmetric behaviour?," Energy Policy, Elsevier, vol. 37(11), pages 4364-4372, November.
    14. Mora, Juan & Neumeyer, Natalie, 2005. "The Two-Sample Problem with Regression Errors : An Empirical Process Approach," Technical Reports 2005,05, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    15. Alicia Pérez Alonso, 2006. "A Bootstrap Approach To Test The Conditional Symmetry In Time Series Models," Working Papers. Serie AD 2006-18, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    16. Igor Kheifets & Carlos Velasco, 2012. "Model Adequacy Checks for Discrete Choice Dynamic Models," Working Papers w0170, Center for Economic and Financial Research (CEFIR).
    17. Marcelo FERNANDES & Eduardo F. MENDES & Olivier SCAILLET, 2011. "Testing for Symmetry and Conditional Symmetry Using Asymmetric Kernels," Swiss Finance Institute Research Paper Series 11-32, Swiss Finance Institute.
    18. Song, Kyungchul, 2010. "Testing semiparametric conditional moment restrictions using conditional martingale transforms," Journal of Econometrics, Elsevier, vol. 154(1), pages 74-84, January.
    19. Andrea Bastianin, 2019. "Robust measures of skewness and kurtosis for macroeconomic and financial time series," Working Papers 408, University of Milano-Bicocca, Department of Economics, revised 06 May 2019.
    20. Dante Amengual & Xinyue Bei & Marine Carrasco & Enrique Sentana, 2023. "Score-type tests for normal mixtures," CIRANO Working Papers 2023s-02, CIRANO.
    21. Laïb Naâmane & Lemdani Mohamed & Ould Saïd Elias, 2013. "A functional conditional symmetry test for a GARCH-SM model: Power asymptotic properties," Statistics & Risk Modeling, De Gruyter, vol. 30(1), pages 75-104, March.
    22. Paolo Zagaglia, 2006. "How reliable are Taylor rules? A view from asymmetry in the U.S. Fed funds rate," Economics Bulletin, AccessEcon, vol. 5(14), pages 1-11.
    23. Andreou, Elena & Werker, Bas J.M., 2015. "Residual-based rank specification tests for AR–GARCH type models," Journal of Econometrics, Elsevier, vol. 185(2), pages 305-331.
    24. Niu, Cuizhen & Guo, Xu & Li, Yong & Zhu, Lixing, 2018. "Pairwise distance-based tests for conditional symmetry," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 145-162.
    25. Su, Liangjun, 2006. "A simple test for multivariate conditional symmetry," Economics Letters, Elsevier, vol. 93(3), pages 374-378, December.
    26. Chung, EunYi & Olivares, Mauricio, 2021. "Permutation test for heterogeneous treatment effects with a nuisance parameter," Journal of Econometrics, Elsevier, vol. 225(2), pages 148-174.
    27. Luke Hartigan, 2016. "Testing for Symmetry in Weakly Dependent Time Series," Discussion Papers 2016-18, School of Economics, The University of New South Wales.
    28. Ivanović, Blagoje & Milošević, Bojana & Obradović, Marko, 2020. "Comparison of symmetry tests against some skew-symmetric alternatives in i.i.d. and non-i.i.d. setting," Computational Statistics & Data Analysis, Elsevier, vol. 151(C).
    29. Li, Fuchun & Tkacz, Greg, 2006. "A consistent bootstrap test for conditional density functions with time-series data," Journal of Econometrics, Elsevier, vol. 133(2), pages 863-886, August.
    30. Simos Meintanis, 2013. "Comments on: An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 432-436, September.
    31. Chen, Qiang & Zheng, Xu & Pan, Zhiyuan, 2015. "Asymptotically distribution-free tests for the volatility function of a diffusion," Journal of Econometrics, Elsevier, vol. 184(1), pages 124-144.
    32. Zacharias Psaradakis & Marián Vávra, 2015. "A Quantile-based Test for Symmetry of Weakly Dependent Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(4), pages 587-598, July.
    33. Halunga, Andreea G. & Orme, Chris D., 2009. "First-Order Asymptotic Theory For Parametric Misspecification Tests Of Garch Models," Econometric Theory, Cambridge University Press, vol. 25(2), pages 364-410, April.
    34. Corradi, Valentina & Swanson, Norman R., 2006. "Bootstrap conditional distribution tests in the presence of dynamic misspecification," Journal of Econometrics, Elsevier, vol. 133(2), pages 779-806, August.
    35. Delgado, Miguel A. & Song, Xiaojun, 2018. "Nonparametric tests for conditional symmetry," Journal of Econometrics, Elsevier, vol. 206(2), pages 447-471.
    36. Tao Chen & Gautam Tripathi, 2011. "Testing Conditional Symmetry Without Smoothing," Working papers 2011-01, University of Connecticut, Department of Economics.
    37. Masayuki Hirukawa & Mari Sakudo, 2016. "Testing Symmetry of Unknown Densities via Smoothing with the Generalized Gamma Kernels," Econometrics, MDPI, vol. 4(2), pages 1-27, June.
    38. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    39. Elena Andreou & Bas J.M. Werker, 2014. "Residual-based Rank Specification Tests for AR-GARCH type models," University of Cyprus Working Papers in Economics 02-2014, University of Cyprus Department of Economics.
    40. Chen Yi-Ting & Lin Chang-Ching, 2008. "On the Robustness of Symmetry Tests for Stock Returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(2), pages 1-40, May.
    41. Yi-Ting Chen & Chung-Ming Kuan, 2003. "A Generalized Jarque-Bera Test of Conditional Normality," IEAS Working Paper : academic research 03-A003, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    42. Bai, Jushan & Chen, Zhihong, 2008. "Testing multivariate distributions in GARCH models," Journal of Econometrics, Elsevier, vol. 143(1), pages 19-36, March.
    43. Mora, Juan, 2005. "Comparing distribution functions of errors in linear models: A nonparametric approach," Statistics & Probability Letters, Elsevier, vol. 73(4), pages 425-432, July.
    44. Chen Yi-Ting, 2003. "Testing Serial Independence against Time Irreversibility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(3), pages 1-30, October.
    45. Delgado, Miguel A. & Velasco, Carlos, 2005. "Sign tests for long-memory time series," Journal of Econometrics, Elsevier, vol. 128(2), pages 215-251, October.
    46. Delgado, Miguel A. & Carlos Escanciano, J., 2007. "Nonparametric tests for conditional symmetry in dynamic models," Journal of Econometrics, Elsevier, vol. 141(2), pages 652-682, December.
    47. Philippe Lambert & Sébastien Laurent, 2008. "Testing Conditional Dynamics in Asymmetry. A Residual-Based Approach," Working Papers ECARES 2008_009, ULB -- Universite Libre de Bruxelles.
    48. Werker, Bas J M & Andreou, Elena, 2013. "Residual-based Rank Specification Tests for AR-GARCH type models," CEPR Discussion Papers 9583, C.E.P.R. Discussion Papers.
    49. Maasoumi, Esfandiar & Racine Jeff, 2003. "A Robust Entropy-Based Test for Asymmetry," Departmental Working Papers 0508, Southern Methodist University, Department of Economics.
    50. Liangjun Su & Sainan Jin, 2005. "A Bootstrap Test for Conditional Symmetry," Annals of Economics and Finance, Society for AEF, vol. 6(2), pages 251-261, November.
    51. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    52. Chen, Yi-Ting, 2012. "A simple approach to standardized-residuals-based higher-moment tests," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 427-453.

  61. Jushan Bai, 2000. "Vector Autoregressive Models with Structural Changes in Regression Coefficients and in Variance-Covariance Matrices," Annals of Economics and Finance, Society for AEF, vol. 1(2), pages 303-339, November.
    See citations under working paper version above.
  62. Bai, Jushan, 1999. "Likelihood ratio tests for multiple structural changes," Journal of Econometrics, Elsevier, vol. 91(2), pages 299-323, August.

    Cited by:

    1. Laura Mayoral, 2005. "Further evidence on the statistical properties of real GNP," Economics Working Papers 955, Department of Economics and Business, Universitat Pompeu Fabra, revised Feb 2006.
    2. Boldea, Otilia & Hall, Alastair R., 2013. "Estimation and inference in unstable nonlinear least squares models," Journal of Econometrics, Elsevier, vol. 172(1), pages 158-167.
    3. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    4. Mohitosh Kejriwal, 2020. "A Robust Sequential Procedure for Estimating the Number of Structural Changes in Persistence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(3), pages 669-685, June.
    5. Erfani , Alireza & Abbasi , Saeed, 2018. "The Effect of Monetary Policy on Regime Changes of Financial Assets," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 13(3), pages 319-341, July.
    6. Elliott, Graham & Muller, Ulrich K., 2007. "Confidence sets for the date of a single break in linear time series regressions," Journal of Econometrics, Elsevier, vol. 141(2), pages 1196-1218, December.
    7. Hock Peng Chan & Tze Leung Lai, 2002. "Boundary Crossing Probabilities for Scan Statistics and Their Applications to Change-Point Detection," Methodology and Computing in Applied Probability, Springer, vol. 4(4), pages 317-336, December.
    8. Hervé Le Bihan, 2004. "Tests de ruptures : une application au PIB tendanciel français," Économie et Prévision, Programme National Persée, vol. 163(2), pages 133-154.
    9. Mei-Hui Wang & Tai-Hsin Huang, 2009. "Threshold effects of financial status on the cost frontiers of financial institutions in nondynamic panels," Applied Economics, Taylor & Francis Journals, vol. 41(26), pages 3389-3401.
    10. Alastair R. Hall & Denise R. Osborn & Nikolaos Sakkas, 2013. "Inference on Structural Breaks using Information Criteria," Manchester School, University of Manchester, vol. 81, pages 54-81, October.
    11. Jan Ditzen & Yiannis Karavias & Joakim Westerlund, 2023. "Multiple structural breaks in interactive effects panel data and the impace of quantitative easing on bank lending," Discussion Papers 23-02, Department of Economics, University of Birmingham.
    12. Xintong Yang & Yu Zhang & Qi Li, 2021. "The role of price spillovers: what is different in China," Empirical Economics, Springer, vol. 60(1), pages 459-485, January.
    13. Papell, David H., 2002. "The great appreciation, the great depreciation, and the purchasing power parity hypothesis," Journal of International Economics, Elsevier, vol. 57(1), pages 51-82, June.
    14. Duarte, Agustin & Venetis, Ioannis A. & Paya, Ivan, 2005. "Predicting real growth and the probability of recession in the Euro area using the yield spread," International Journal of Forecasting, Elsevier, vol. 21(2), pages 261-277.
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    1. Jamel JOUINI & Mohamed BOUTAHAR, 2007. "wrong estimation of the true number of shifts in structural break models: Theoretical and numerical evidence," Economics Bulletin, AccessEcon, vol. 3(3), pages 1-10.
    2. Granger, Clive W. J. & Hyung, Namwon, 2004. "Occasional structural breaks and long memory with an application to the S&P 500 absolute stock returns," Journal of Empirical Finance, Elsevier, vol. 11(3), pages 399-421, June.
    3. Phillips, Peter C.B., 2005. "Challenges of trending time series econometrics," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 68(5), pages 401-416.
    4. Charfeddine, Lanouar & Guégan, Dominique, 2012. "Breaks or long memory behavior: An empirical investigation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5712-5726.
    5. McAleer, Michael & Medeiros, Marcelo C., 2008. "A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries," Journal of Econometrics, Elsevier, vol. 147(1), pages 104-119, November.
    6. Marriott, John & Newbold, Paul, 2000. "The strength of evidence for unit autoregressive roots and structural breaks: A Bayesian perspective," Journal of Econometrics, Elsevier, vol. 98(1), pages 1-25, September.
    7. Seong Yeon Chang & Pierre Perron, 2016. "Inference on a Structural Break in Trend with Fractionally Integrated Errors," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(4), pages 555-574, July.
    8. Wang, Dabin & Tomek, William G., 2004. "Commodity Prices And Unit Root Tests," 2004 Annual meeting, August 1-4, Denver, CO 20141, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    9. Lanouar Charfeddine & Dominique Guegan, 2009. "Breaks or Long Memory Behaviour: An empirical Investigation," Post-Print halshs-00377485, HAL.
    10. Georgios KOURETAS & Mark E. WOHAR, 2010. "The Dynamics of Inflation: A Study of a Large Number of Countries," EcoMod2010 259600096, EcoMod.
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    13. Jamel JOUINI & Mohamed BOUTAHAR, 2007. "Spuriousness of information criteria when selecting the number of breaks in stationary AR(p) process," Economics Bulletin, AccessEcon, vol. 3(38), pages 1-11.
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