Ke Miao

Personal Details

First Name:	Ke
Middle Name:
Last Name:	Miao
Suffix:
RePEc Short-ID:	pmi1121
	[This author has chosen not to make the email address public]
	https://sites.google.com/view/kemiao/
Terminal Degree:	2020 School of Economics; Singapore Management University (from RePEc Genealogy)

Affiliation

School of Economics
Fudan University

Shanghai, China
http://www.econ.fudan.edu.cn/
RePEc:edi:sefudcn (more details at EDIRC)

Citations

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

Working papers

1. Ke Miao & Peter C.B. Phillips & Liangjun Su, 2020. "High-Dimensional VARs with Common Factors," Cowles Foundation Discussion Papers 2252, Cowles Foundation for Research in Economics, Yale University.
   • 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.

   Cited by:

   1. Chen, J. & Li, D. & Li, Y. & Linton, O. B., 2022. "Estimating Time-Varying Networks for High-Dimensional Time Series," Cambridge Working Papers in Economics 2273, Faculty of Economics, University of Cambridge.
      • Jia Chen & Degui Li & Yuning Li & Oliver Linton, 2023. "Estimating Time-Varying Networks for High-Dimensional Time Series," Papers 2302.02476, arXiv.org.
      • Chen, Jia & Li, Degui & Li, Yu-Ning & Linton, Oliver, 2025. "Estimating time-varying networks for high-dimensional time series," Journal of Econometrics, Elsevier, vol. 249(PC).
      • Chen, J. & Li, D. & Li, Y. & Linton, O. B., 2022. "Estimating Time-Varying Networks for High-Dimensional Time Series," Janeway Institute Working Papers 2231, Faculty of Economics, University of Cambridge.
   2. Chenyan Lyu & Hung Xuan Do & Rabindra Nepal & Tooraj Jamasb, 2023. "Volatility Spillovers and Carbon Price in the Nordic Wholesale Electricity Markets," CAMA Working Papers 2023-36, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
      • Lyu, Chenyan & Do, Hung Xuan & Nepal, Rabindra & Jamasb, Tooraj, 2024. "Volatility spillovers and carbon price in the Nordic wholesale electricity markets," Energy Economics, Elsevier, vol. 134(C).
      • Lyu, Chenyan & Do, Hung Xuan & Nepal, Rabindra & Jamasb, Tooraj, 2023. "Volatility Spillovers and Carbon Price in the Nordic Wholesale Electricity Markets," Working Papers 5-2023, Copenhagen Business School, Department of Economics.
   3. Zhentao Shi & Jin Xi & Haitian Xie, 2025. "A Synthetic Business Cycle Approach to Counterfactual Analysis with Nonstationary Macroeconomic Data," Papers 2505.22388, arXiv.org.
   4. Christis Katsouris, 2023. "Structural Analysis of Vector Autoregressive Models," Papers 2312.06402, arXiv.org, revised Feb 2024.
   5. 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.
      • Yiren Wang & Peter C B Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Papers 2307.15863, arXiv.org.
      • Wang, Yiren & Phillips, Peter C.B. & Su, Liangjun, 2024. "Panel data models with time-varying latent group structures," Journal of Econometrics, Elsevier, vol. 240(1).
   6. Ando, Tomohiro & Bai, Jushan & Lu, Lina & Vojtech, Cindy M., 2024. "Scenario-based quantile connectedness of the U.S. interbank liquidity risk network," Journal of Econometrics, Elsevier, vol. 244(2).
      • Tomohiro Ando & Jushan Bai & Lina Lu & Cindy M. Vojtech, 2024. "Scenario-based Quantile Connectedness of the U.S. Interbank Liquidity Risk Network," Supervisory Research and Analysis Working Papers SRA 24-02, Federal Reserve Bank of Boston.
   7. Eugene Dettaa & Endong Wang, 2024. "Inference in High-Dimensional Linear Projections: Multi-Horizon Granger Causality and Network Connectedness," Papers 2410.04330, arXiv.org.
   8. Wang, Di & Zheng, Yao & Li, Guodong, 2024. "High-dimensional low-rank tensor autoregressive time series modeling," Journal of Econometrics, Elsevier, vol. 238(1).
   9. Christian Brownlees & Gu{dh}mundur Stef'an Gu{dh}mundsson, 2021. "Performance of Empirical Risk Minimization for Linear Regression with Dependent Data," Papers 2104.12127, arXiv.org, revised May 2023.
   10. Alain Hecq & Luca Margaritella & Stephan Smeekes, 2023. "Inference in Non-stationary High-Dimensional VARs," Papers 2302.01434, arXiv.org, revised Sep 2023.
   11. Lin, Ling & Jiang, Yong & Zhou, Zhongbao, 2024. "Asymmetric spillover and network connectedness of policy uncertainty, fossil fuel energy, and global ESG investment," Applied Energy, Elsevier, vol. 368(C).
   12. Siphat Lim & Edman Flores & Casey Barnett, 2024. "Analyzing the Effectiveness of a System of Equation Model in Comparison to Single Equation Models for Predicting General Price Level in Cambodia," International Journal of Economics and Financial Issues, Econjournals, vol. 14(5), pages 156-166, September.
   13. Paul Haimerl & Stephan Smeekes & Ines Wilms, 2025. "Estimation of Latent Group Structures in Time-Varying Panel Data Models," Papers 2503.23165, arXiv.org.
   14. Timothy B. Armstrong & Martin Weidner & Andrei Zeleneev, 2024. "Robust estimation and inference in panels with interactive fixed effects," CeMMAP working papers 28/24, Institute for Fiscal Studies.
   15. Naeem, Muhammad Abubakr & Senthilkumar, Arunachalam & Arfaoui, Nadia & Mohnot, Rajesh, 2024. "Mapping fear in financial markets: Insights from dynamic networks and centrality measures," Pacific-Basin Finance Journal, Elsevier, vol. 85(C).

2. Liangjun Su & Ke Miao & Sainan Jin, 2019. "On Factor Models with Random Missing: EM Estimation, Inference, and Cross Validation," Economics and Statistics Working Papers 4-2019, Singapore Management University, School of Economics.
   • 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.

   Cited by:

   1. Duan, Junting & Pelger, Markus & Xiong, Ruoxuan, 2024. "Target PCA: Transfer learning large dimensional panel data," Journal of Econometrics, Elsevier, vol. 244(2).
   2. Chaohua Dong & Jiti Gao & Oliver Linton & Bin Peng, 2020. "On the Time Trend of COVID-19: A Panel Data Study," Papers 2006.11060, arXiv.org, revised Jun 2020.
      • Chaohua Dong & Jiti Gao & Oliver Linton & Bin peng, 2020. "On Time Trend of COVID-19: A Panel Data Study," Monash Econometrics and Business Statistics Working Papers 22/20, Monash University, Department of Econometrics and Business Statistics.
      • Dong, C. & Gao, J. & Linton, O. & Peng, B., 2020. "On Time Trend of COVID-19: A Panel Data Study," Cambridge Working Papers in Economics 2065, Faculty of Economics, University of Cambridge.
   3. Wei, Jie & Chen, Hui, 2020. "Determining the number of factors in approximate factor models by twice K-fold cross validation," Economics Letters, Elsevier, vol. 191(C).
   4. Artūras Juodis & Simas Kučinskas, 2023. "Quantifying noise in survey expectations," Quantitative Economics, Econometric Society, vol. 14(2), pages 609-650, May.
   5. Liddle, Brantley & Hasanov, Fakhri J. & Parker, Steven, 2022. "Your mileage may vary: Have road-fuel demand elasticities changed over time in middle-income countries?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 38-53.
   6. Ke, Shuyao & Phillips, Peter C.B. & Su, Liangjun, 2024. "Robust inference of panel data models with interactive fixed effects under long memory: A frequency domain approach," Journal of Econometrics, Elsevier, vol. 241(2).
   7. 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.
      • 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. 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.
      • Jushan Bai & Serena Ng, 2019. "Matrix Completion, Counterfactuals, and Factor Analysis of Missing Data," Papers 1910.06677, arXiv.org, revised Aug 2021.
   9. Choi, Jungjun & Kwon, Hyukjun & Liao, Yuan, 2024. "Inference for low-rank completion without sample splitting with application to treatment effect estimation," Journal of Econometrics, Elsevier, vol. 240(1).
   10. Gao, J. & Linton, O. & Peng, B., 2022. "A Nonparametric Panel Model for Climate Data with Seasonal and Spatial Variation," Janeway Institute Working Papers 2215, Faculty of Economics, University of Cambridge.
       • Jiti Gao & Oliver Linton & Bin Peng, 2022. "A Nonparametric Panel Model for Climate Data with Seasonal and Spatial Variation," Monash Econometrics and Business Statistics Working Papers 9/22, Monash University, Department of Econometrics and Business Statistics.
       • Gao, J. & Linton, O. & Peng, B., 2022. "A Nonparametric Panel Model for Climate Data with Seasonal and Spatial Variation," Cambridge Working Papers in Economics 2239, Faculty of Economics, University of Cambridge.
   11. Zhou, Ruichao & Wu, Jianhong, 2023. "Determining the number of change-points in high-dimensional factor models by cross-validation with matrix completion," Economics Letters, Elsevier, vol. 232(C).
   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. Liu, Wei & Luo, Lan & Zhou, Ling, 2023. "Online missing value imputation for high-dimensional mixed-type data via generalized factor models," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).
   14. Jean-Baptiste Hasse & Capucine Nobletz, 2024. "Critical Raw Materials Index -CRMI," Working Papers hal-04759077, HAL.
       • Jean-Baptiste Hasse & Capucine Nobletz, 2024. "Critical Raw Materials Index - CRMI," AMSE Working Papers 2428, Aix-Marseille School of Economics, France.
   15. 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.
       • 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.
   16. Serena Ng & Susannah Scanlan, 2024. "Constructing high frequency economic indicators by imputation," The Econometrics Journal, Royal Economic Society, vol. 27(1), pages 1-30.
       • Serena Ng & Susannah Scanlan, 2023. "Constructing High Frequency Economic Indicators by Imputation," Papers 2303.01863, arXiv.org, revised Oct 2023.
   17. Yinchu Zhu, 2019. "How well can we learn large factor models without assuming strong factors?," Papers 1910.10382, arXiv.org, revised Nov 2019.
   18. 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.
   19. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
   20. Bian, Yulin & Su, Liangjun, 2025. "A note on factor models with latent group structures," Economics Letters, Elsevier, vol. 252(C).
   21. Victor Chernozhukov & Christian Hansen & Yuan Liao & Yinchu Zhu, 2021. "Inference for Low-Rank Models," Papers 2107.02602, arXiv.org, revised Jan 2023.
   22. Junting Duan & Markus Pelger & Ruoxuan Xiong, 2023. "Target PCA: Transfer Learning Large Dimensional Panel Data," Papers 2308.15627, arXiv.org.
   23. 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. Miao Ke & Liangjun Su & Wendun Wang, 2019. "Panel threshold regressions with latent group structures," Economics and Statistics Working Papers 13-2019, Singapore Management University, School of Economics.
   • Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.

   Cited by:

   1. 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.
   2. Saptorshee Kanto Chakraborty & Antoine Mandel, 2024. "Understanding EU regional macroeconomic tipping points using panel threshold technique," Economic Change and Restructuring, Springer, vol. 57(3), pages 1-30, June.
   3. Huang, Wenxin & Jin, Sainan & Phillips, Peter C.B. & Su, Liangjun, 2021. "Nonstationary panel models with latent group structures and cross-section dependence," Journal of Econometrics, Elsevier, vol. 221(1), pages 198-222.
      • Wenxin Huang & Sainan Jin & Peter C.B. Phillips & Liangjun Su, 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.
   4. Yu, Lu & Gu, Jiaying & Volgushev, Stanislav, 2024. "Spectral clustering with variance information for group structure estimation in panel data," Journal of Econometrics, Elsevier, vol. 241(1).
   5. Huang, Danyang & Hu, Wei & Jing, Bingyi & Zhang, Bo, 2023. "Grouped spatial autoregressive model," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
   6. 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.
   7. Woosik Gong & Myung Hwan Seo, 2022. "Bootstraps for Dynamic Panel Threshold Models," Papers 2211.04027, arXiv.org, revised Jul 2025.
   8. Gupta, Mahima & Dubey, Amlendu, 2025. "Structural characteristics and non-linear fiscal multipliers," Economic Systems, Elsevier, vol. 49(1).
   9. Choudhury, Atrayee & Sahu, Sohini, 2025. "The asymmetric impact of fiscal decentralization on ecological footprint-accounting for methodological refinements and globalization facets," The Journal of Economic Asymmetries, Elsevier, vol. 31(C).
   10. Lawal, Adedoyin Isola & Ozturk, Ilhan & Olanipekun, Ifedolapo O. & Asaleye, Abiola John, 2020. "Examining the linkages between electricity consumption and economic growth in African economies," Energy, Elsevier, vol. 208(C).
   11. 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.
   12. Pionati, Alessandro, 2025. "Latent grouped structures in panel data: a review," MPRA Paper 123954, University Library of Munich, Germany.

4. Xun Lu & Ke Miao & Liangjun Su, 2018. "Determination of Different Types of Fixed Effects in Three-Dimensional Panels," Economics and Statistics Working Papers 10-2018, Singapore Management University, School of Economics.
   • Xun Lu & Ke Miao & Liangjun Su, 2021. "Determination of different types of fixed effects in three-dimensional panels," Econometric Reviews, Taylor & Francis Journals, vol. 40(9), pages 867-898, October.

   Cited by:

   1. Chiang, Harold D. & Rodrigue, Joel & Sasaki, Yuya, 2023. "Post-Selection Inference In Three-Dimensional Panel Data," Econometric Theory, Cambridge University Press, vol. 39(3), pages 623-658, June.
      • Harold D. Chiang & Joel Rodrigue & Yuya Sasaki, 2019. "Post-Selection Inference in Three-Dimensional Panel Data," Papers 1904.00211, arXiv.org, revised Apr 2019.

Articles

1. 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.
   • Ke Miao & Peter C.B. Phillips & Liangjun Su, 2020. "High-Dimensional VARs with Common Factors," Cowles Foundation Discussion Papers 2252, Cowles Foundation for Research in Economics, Yale University.
   See citations under working paper version above.
2. 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.
   • Liangjun Su & Ke Miao & Sainan Jin, 2019. "On Factor Models with Random Missing: EM Estimation, Inference, and Cross Validation," Economics and Statistics Working Papers 4-2019, Singapore Management University, School of Economics.
   See citations under working paper version above.
3. Xun Lu & Ke Miao & Liangjun Su, 2021. "Determination of different types of fixed effects in three-dimensional panels," Econometric Reviews, Taylor & Francis Journals, vol. 40(9), pages 867-898, October.
   • Xun Lu & Ke Miao & Liangjun Su, 2018. "Determination of Different Types of Fixed Effects in Three-Dimensional Panels," Economics and Statistics Working Papers 10-2018, Singapore Management University, School of Economics.
   See citations under working paper version above.
4. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
   • Miao Ke & Liangjun Su & Wendun Wang, 2019. "Panel threshold regressions with latent group structures," Economics and Statistics Working Papers 13-2019, Singapore Management University, School of Economics.
   See citations under working paper version above.
5. Miao, Ke & Li, Kunpeng & Su, Liangjun, 2020. "Panel threshold models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 219(1), pages 137-170.

   Cited by:

   1. Yi Li & Xingxing Luo & Mengqi Liao, 2025. "Incorporating Prior Information in Latent Structures Identification for Panel Data Models," Mathematics, MDPI, vol. 13(9), pages 1-26, May.
   2. Piaopeng Song & Yuxiao Gu & Bin Su & Arifa Tanveer & Qiao Peng & Weijun Gao & Shaomin Wu & Shihong Zeng, 2023. "The Impact of Green Technology Research and Development (R&D) Investment on Performance: A Case Study of Listed Energy Companies in Beijing, China," Sustainability, MDPI, vol. 15(16), pages 1-24, August.
   3. Timothy B. Armstrong & Martin Weidner & Andrei Zeleneev, 2024. "Robust estimation and inference in panels with interactive fixed effects," CeMMAP working papers 28/24, Institute for Fiscal Studies.
   4. Paravee Maneejuk & Woraphon Yamaka, 2021. "The Impact of Higher Education on Economic Growth in ASEAN-5 Countries," Sustainability, MDPI, vol. 13(2), pages 1-28, January.
   5. Feng Dong & Yujie Zhang & Jianheng Huang & Yajie Liu & Ying Chen, 2025. "Nonlinear impact of the coordination of IFDI and OFDI on green total factor productivity in the context of “Dual Circulation”," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-32, December.

More information

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Statistics

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 5 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.

1. NEP-ECM: Econometrics (5) 2018-07-30 2019-02-11 2019-07-29 2020-08-31 2023-05-15. Author is listed
2. NEP-SEA: South East Asia (3) 2018-07-30 2019-02-11 2019-07-29. Author is listed
3. NEP-ETS: Econometric Time Series (2) 2019-02-11 2020-08-31. Author is listed
4. NEP-ORE: Operations Research (2) 2019-07-29 2020-08-31. Author is listed

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