Mingli Chen
Personal Details
First Name: | Mingli |
Middle Name: | |
Last Name: | Chen |
Suffix: | |
RePEc Short-ID: | pch1688 |
[This author has chosen not to make the email address public] | |
http://blogs.bu.edu/mlchen/research/ | |
Affiliation
Department of Economics
University of Warwick
Coventry, United Kingdomhttp://www.warwick.ac.uk/fac/soc/Economics/
RePEc:edi:dewaruk (more details at EDIRC)
Research output
Jump to: Working papers ArticlesWorking papers
- Mingli Chen & Andreas Joseph & Michael Kumhof & Xinlei Pan & Xuan Zhou, 2021. "Deep Reinforcement Learning in a Monetary Model," Papers 2104.09368, arXiv.org, revised Jan 2023.
- Chen, Mingli & Kato, Kengo & Leng, Chenlei, 2019. "Analysis of Networks via the Sparse β-Model," The Warwick Economics Research Paper Series (TWERPS) 1222, University of Warwick, Department of Economics.
- 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.
- Belloni, Alexandre & Chen, Mingli & Madrid Padilla, Oscar Hernan & Wang, Zixuan (Kevin), 2019. "High Dimensional Latent Panel Quantile Regression with an Application to Asset Pricing," The Warwick Economics Research Paper Series (TWERPS) 1230, University of Warwick, Department of Economics.
- Mingli Chen & Kengo Kato & Chenlei Leng, 2019. "Analysis of Networks via the Sparse $\beta$-Model," Papers 1908.03152, arXiv.org, revised Dec 2020.
- Mingli Chen & Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly, 2017.
"Counterfactual analysis in R: a vignette,"
CeMMAP working papers
CWP64/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Mingli Chen & Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly, 2017. "Counterfactual analysis in R: a vignette," CeMMAP working papers 64/17, Institute for Fiscal Studies.
- Alexandre Belloni & Mingli Chen & Victor Chernozhukov, 2016.
"Quantile Graphical Models: Prediction and Conditional Independence with Applications to Systemic Risk,"
Papers
1607.00286, arXiv.org, revised Oct 2019.
- Alexandre Belloni & Mingli Chen & Victor Chernozhukov, 2017. "Quantile graphical models: prediction and conditional independence with applications to systemic risk," CeMMAP working papers CWP54/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Alexandre Belloni & Mingli Chen & Victor Chernozhukov, 2017. "Quantile graphical models: prediction and conditional independence with applications to systemic risk," CeMMAP working papers 54/17, Institute for Fiscal Studies.
- Belloni, Alexandre. & Chen, Mingli & Chernozhukov, Victor, 2016.
"Quantile Graphical Models: Prediction and Conditional Independence with Applications to Financial Risk Management,"
The Warwick Economics Research Paper Series (TWERPS)
1125, University of Warwick, Department of Economics.
- Belloni, Alexandre & Chen, Mingli & Chernozhukov, Victor, 2016. "Quantile Graphical Models : Prediction and Conditional Independence with Applications to Financial Risk Management," Economic Research Papers 269321, University of Warwick - Department of Economics.
- Chen, Mingli, 2016.
"Estimation of Nonlinear Panel Models with Multiple Unobserved Effects,"
The Warwick Economics Research Paper Series (TWERPS)
1120, University of Warwick, Department of Economics.
- Chen, Mingli, 2016. "Estimation of Nonlinear Panel Models with Multiple Unobserved Effects," Economic Research Papers 269326, University of Warwick - Department of Economics.
- Mingli Chen & Victor Chernozhukov & Iv'an Fern'andez-Val & Blaise Melly, 2016. "Counterfactual: An R Package for Counterfactual Analysis," Papers 1610.07894, arXiv.org.
- 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.
- Chen, Mingli & Fernández-Val, Iván & Weidner, Martin, 2021. "Nonlinear factor models for network and panel data," Journal of Econometrics, Elsevier, vol. 220(2), pages 296-324.
- Mingli Chen & Ivan Fernandez-Val & Martin Weidner, 2018. "Nonlinear factor models for network and panel data," CeMMAP working papers CWP38/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Mingli Chen & Ivan Fernandez-Val & Martin Weidner, 2019. "Nonlinear factor models for network and panel data," CeMMAP working papers CWP18/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
Articles
- Chen, Mingli & Fernández-Val, Iván & Weidner, Martin, 2021.
"Nonlinear factor models for network and panel data,"
Journal of Econometrics, Elsevier, vol. 220(2), pages 296-324.
- Mingli Chen & Ivan Fernandez-Val & Martin Weidner, 2018. "Nonlinear factor models for network and panel data," CeMMAP working papers CWP38/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- 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.
- Mingli Chen & Ivan Fernandez-Val & Martin Weidner, 2019. "Nonlinear factor models for network and panel data," CeMMAP working papers CWP18/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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
- Mingli Chen & Andreas Joseph & Michael Kumhof & Xinlei Pan & Xuan Zhou, 2021.
"Deep Reinforcement Learning in a Monetary Model,"
Papers
2104.09368, arXiv.org, revised Jan 2023.
Cited by:
- Michael Curry & Alexander Trott & Soham Phade & Yu Bai & Stephan Zheng, 2022. "Analyzing Micro-Founded General Equilibrium Models with Many Agents using Deep Reinforcement Learning," Papers 2201.01163, arXiv.org, revised Feb 2022.
- Rui (Aruhan) Shi, 2021. "Learning from Zero: How to Make Consumption-Saving Decisions in a Stochastic Environment with an AI Algorithm," CESifo Working Paper Series 9255, CESifo.
- Qirui Mi & Zhiyu Zhao & Siyu Xia & Yan Song & Jun Wang & Haifeng Zhang, 2024. "Learning Macroeconomic Policies based on Microfoundations: A Stackelberg Mean Field Game Approach," Papers 2403.12093, arXiv.org, revised Oct 2024.
- Rui & Shi, 2021. "Learning from zero: how to make consumption-saving decisions in a stochastic environment with an AI algorithm," Papers 2105.10099, arXiv.org, revised Feb 2022.
- Artem Kuriksha, 2021. "An Economy of Neural Networks: Learning from Heterogeneous Experiences," Papers 2110.11582, arXiv.org.
- Hinterlang, Natascha & Tänzer, Alina, 2021. "Optimal monetary policy using reinforcement learning," Discussion Papers 51/2021, Deutsche Bundesbank.
- Rui & Shi, 2021. "Can an AI agent hit a moving target?," Papers 2110.02474, arXiv.org, revised Oct 2022.
- 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.
- Belloni, Alexandre & Chen, Mingli & Madrid Padilla, Oscar Hernan & Wang, Zixuan (Kevin), 2019. "High Dimensional Latent Panel Quantile Regression with an Application to Asset Pricing," The Warwick Economics Research Paper Series (TWERPS) 1230, University of Warwick, Department of Economics.
Cited by:
- 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.
- 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.
- Andrii Babii & Ryan T. Ball & Eric Ghysels & Jonas Striaukas, 2020.
"Machine Learning Panel Data Regressions with Heavy-tailed Dependent Data: Theory and Application,"
Papers
2008.03600, arXiv.org, revised Nov 2021.
- Babii, Andrii & Ball, Ryan T. & Ghysels, Eric & Striaukas, Jonas, 2023. "Machine learning panel data regressions with heavy-tailed dependent data: Theory and application," Journal of Econometrics, Elsevier, vol. 237(2).
- Shujie Ma & Liangjun Su & Yichong Zhang, 2020.
"Detecting Latent Communities in Network Formation Models,"
Papers
2005.03226, arXiv.org, revised Mar 2021.
- Ma, Shujie & Su, Liangjun & Zhang, Yichong, 2020. "Detecting Latent Communities in Network Formation Models," Economics and Statistics Working Papers 12-2020, Singapore Management University, School of Economics.
- 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.
- Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
- Michael Vogt & Christopher Walsh & Oliver Linton, 2022. "CCE Estimation of High-Dimensional Panel Data Models with Interactive Fixed Effects," Papers 2206.12152, arXiv.org.
- Kean Ming Tan & Lan Wang & Wen‐Xin Zhou, 2022. "High‐dimensional quantile regression: Convolution smoothing and concave regularization," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(1), pages 205-233, February.
- 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.
- Alexandre Belloni & Mingli Chen & Victor Chernozhukov, 2016.
"Quantile Graphical Models: Prediction and Conditional Independence with Applications to Systemic Risk,"
Papers
1607.00286, arXiv.org, revised Oct 2019.
- Alexandre Belloni & Mingli Chen & Victor Chernozhukov, 2017. "Quantile graphical models: prediction and conditional independence with applications to systemic risk," CeMMAP working papers CWP54/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Alexandre Belloni & Mingli Chen & Victor Chernozhukov, 2017. "Quantile graphical models: prediction and conditional independence with applications to systemic risk," CeMMAP working papers 54/17, Institute for Fiscal Studies.
Cited by:
- Matthew A. Masten & Alexandre Poirier, 2018. "Interpreting Quantile Independence," Papers 1804.10957, arXiv.org.
- Matthew A Masten & Alexandre Poirier, 2023.
"Choosing exogeneity assumptions in potential outcome models,"
The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 327-349.
- Matthew A. Masten & Alexandre Poirier, 2022. "Choosing Exogeneity Assumptions in Potential Outcome Models," Papers 2205.02288, arXiv.org.
- Hossein Alidaee & Eric Auerbach & Michael P. Leung, 2020. "Recovering Network Structure from Aggregated Relational Data using Penalized Regression," Papers 2001.06052, arXiv.org.
- Belloni, Alexandre. & Chen, Mingli & Chernozhukov, Victor, 2016.
"Quantile Graphical Models: Prediction and Conditional Independence with Applications to Financial Risk Management,"
The Warwick Economics Research Paper Series (TWERPS)
1125, University of Warwick, Department of Economics.
- Belloni, Alexandre & Chen, Mingli & Chernozhukov, Victor, 2016. "Quantile Graphical Models : Prediction and Conditional Independence with Applications to Financial Risk Management," Economic Research Papers 269321, University of Warwick - Department of Economics.
Cited by:
- Victor Chernozhukov & Wolfgang Härdle & Chen Huang & Weining Wang, 2019.
"LASSO-Driven Inference in Time and Space,"
CeMMAP working papers
CWP20/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Chernozhukov, V. & Härdle, W.K. & Huang, C. & Wang, W., 2018. "LASSO-Driven Inference in Time and Space," Working Papers 18/04, Department of Economics, City University London.
- Chernozhukov, Victor & Härdle, Wolfgang Karl & Huang, Chen & Wang, Weining, 2018. "LASSO-Driven Inference in Time and Space," IRTG 1792 Discussion Papers 2018-021, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Victor Chernozhukov & Wolfgang Härdle & Chen Huang & Weining Wang, 2018. "LASSO-driven inference in time and space," CeMMAP working papers CWP36/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Victor Chernozhukov & Wolfgang K. Hardle & Chen Huang & Weining Wang, 2018. "LASSO-Driven Inference in Time and Space," Papers 1806.05081, arXiv.org, revised May 2020.
- Baumöhl, Eduard & Bouri, Elie & Hoang, Thi-Hong-Van & Hussain Shahzad, Syed Jawad & Výrost, Tomáš, 2022.
"Measuring systemic risk in the global banking sector: A cross-quantilogram network approach,"
Economic Modelling, Elsevier, vol. 109(C).
- Baumöhl, Eduard & Bouri, Elie & Hoang, Thi-Hong-Van & Hussain Shahzad, Syed Jawad & Výrost, Tomáš, 2022. "Measuring systemic risk in the global banking sector: A cross-quantilogram network approach," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics.
- Torri, Gabriele & Giacometti, Rosella & Tichý, Tomáš, 2021. "Network tail risk estimation in the European banking system," Journal of Economic Dynamics and Control, Elsevier, vol. 127(C).
- Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2017.
"Non-separable Models with High-dimensional Data,"
Economics and Statistics Working Papers
15-2017, Singapore Management University, School of Economics.
- Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2019. "Non-separable models with high-dimensional data," Journal of Econometrics, Elsevier, vol. 212(2), pages 646-677.
- Hossein Alidaee & Eric Auerbach & Michael P. Leung, 2020. "Recovering Network Structure from Aggregated Relational Data using Penalized Regression," Papers 2001.06052, arXiv.org.
- Chen, Mingli, 2016.
"Estimation of Nonlinear Panel Models with Multiple Unobserved Effects,"
The Warwick Economics Research Paper Series (TWERPS)
1120, University of Warwick, Department of Economics.
- Chen, Mingli, 2016. "Estimation of Nonlinear Panel Models with Multiple Unobserved Effects," Economic Research Papers 269326, University of Warwick - Department of Economics.
Cited by:
- 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.
- Ivan Fernandez-Val & Martin Weidner, 2017. "Fixed effect estimation of large T panel data models," CeMMAP working papers CWP42/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Iván Fernández-Val & Martin Weidner, 2018. "Fixed Effects Estimation of Large-TPanel Data Models," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 109-138, August.
- Iv'an Fern'andez-Val & Martin Weidner, 2017. "Fixed Effect Estimation of Large T Panel Data Models," Papers 1709.08980, arXiv.org, revised Mar 2018.
- Hyungsik Roger Moon & Martin Weidner, 2019.
"Nuclear norm regularized estimation of panel regression models,"
CeMMAP working papers
CWP14/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Hyungsik Roger Moon & Martin Weidner, 2018. "Nuclear Norm Regularized Estimation of Panel Regression Models," Papers 1810.10987, arXiv.org, revised Jun 2023.
- 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.
- Gao, Jiti & Liu, Fei & Peng, Bin & Yan, Yayi, 2023. "Binary response models for heterogeneous panel data with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 235(2), pages 1654-1679.
- Lena Boneva (Körber) & Oliver Linton, 2017.
"A discrete choice model for large heterogeneous panels with interactive fixed effects with an application to the determinants of corporate bond issuance,"
CeMMAP working papers
CWP02/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Boneva, Lena & Linton, Oliver, 2017. "A discrete choice model for large heterogeneous panels with interactive fixed effects with an application to the determinants of corporate bond issuance," Bank of England working papers 640, Bank of England.
- Boneva, L. & Linton, O., 2017. "A Discrete Choice Model For Large Heterogeneous Panels with Interactive Fixed Effects with an Application to the Determinants of Corporate Bond Issuance," Cambridge Working Papers in Economics 1703, Faculty of Economics, University of Cambridge.
- 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.
- 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.
- 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.
- Chen, Mingli & Fernández-Val, Iván & Weidner, Martin, 2021. "Nonlinear factor models for network and panel data," Journal of Econometrics, Elsevier, vol. 220(2), pages 296-324.
- Mingli Chen & Ivan Fernandez-Val & Martin Weidner, 2018. "Nonlinear factor models for network and panel data," CeMMAP working papers CWP38/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Mingli Chen & Ivan Fernandez-Val & Martin Weidner, 2019. "Nonlinear factor models for network and panel data," CeMMAP working papers CWP18/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Belloni, Alexandre & Chen, Mingli & Madrid Padilla, Oscar Hernan & Wang, Zixuan (Kevin), 2019.
"High Dimensional Latent Panel Quantile Regression with an Application to Asset Pricing,"
The Warwick Economics Research Paper Series (TWERPS)
1230, University of Warwick, Department of Economics.
- 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.
- 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.
- Ye, Xiaoqing & Xu, Juan & Wu, Xiangjun, 2018. "Estimation of an unbalanced panel data Tobit model with interactive effects," Journal of choice modelling, Elsevier, vol. 28(C), pages 108-123.
- Mugnier, Martin & Wang, Ao, 2022. "Identification and (Fast) Estimation of Large Nonlinear Panel Models with Two-Way Fixed Effects," The Warwick Economics Research Paper Series (TWERPS) 1422, University of Warwick, Department of Economics.
- 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.
- Wang, Wuyi & Su, Liangjun, 2021. "Identifying latent group structures in nonlinear panels," Journal of Econometrics, Elsevier, vol. 220(2), pages 272-295.
- Liang Chen & Minyuan Zhang, 2023. "Common Correlated Effects Estimation of Nonlinear Panel Data Models," Papers 2304.13199, arXiv.org.
- Jie Wei & Yonghui Zhang, 2022. "Panel Probit Models with Time‐Varying Individual Effects: Reestimating the Effects of Fertility on Female Labour Participation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(4), pages 799-829, August.
- 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.
- Mingli Chen & Victor Chernozhukov & Iv'an Fern'andez-Val & Blaise Melly, 2016.
"Counterfactual: An R Package for Counterfactual Analysis,"
Papers
1610.07894, arXiv.org.
Cited by:
- Qiu, Wanling & Rudkin, Simon & Sharma, Abhijit, 2017. "An Analysis of the Impact of Low Cost Airlines on Tourist Stay Duration and Expenditures," MPRA Paper 81428, University Library of Munich, Germany.
- Delprato, Marcos & Chudgar, Amita, 2018. "Factors associated with private-public school performance: Analysis of TALIS-PISA link data," International Journal of Educational Development, Elsevier, vol. 61(C), pages 155-172.
- 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.
- Chen, Mingli & Fernández-Val, Iván & Weidner, Martin, 2021. "Nonlinear factor models for network and panel data," Journal of Econometrics, Elsevier, vol. 220(2), pages 296-324.
- Mingli Chen & Ivan Fernandez-Val & Martin Weidner, 2018. "Nonlinear factor models for network and panel data," CeMMAP working papers CWP38/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Mingli Chen & Ivan Fernandez-Val & Martin Weidner, 2019. "Nonlinear factor models for network and panel data," CeMMAP working papers CWP18/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
Cited by:
- 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.
- Ivan Fernandez-Val & Martin Weidner, 2013. "Individual and time effects in nonlinear panel models with large N, T," CeMMAP working papers CWP60/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Fernández-Val, Iván & Weidner, Martin, 2016. "Individual and time effects in nonlinear panel models with large N, T," Journal of Econometrics, Elsevier, vol. 192(1), pages 291-312.
- Ivan Fernandez-Val & Martin Weidner, 2014. "Individual and time effects in nonlinear panel models with large N, T," CeMMAP working papers CWP32/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Ivan Fernandez-Val & Martin Weidner, 2015. "Individual and time effects in nonlinear panel models with large N, T," CeMMAP working papers CWP17/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Ivan Fernandez-Val & Hugo Freeman & Martin Weidner, 2020.
"Low-rank approximations of nonseparable panel models,"
CeMMAP working papers
CWP52/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Hugo Freeman & Martin Weidner, 2021. "Low-rank approximations of nonseparable panel models," The Econometrics Journal, Royal Economic Society, vol. 24(2), pages 40-77.
- Ivan Fernandez-Val & Hugo Freeman & Martin Weidner, 2021. "Low-rank approximations of nonseparable panel models," CeMMAP working papers CWP10/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- David W. Hughes, 2021.
"Estimating Nonlinear Network Data Models with Fixed Effects,"
Boston College Working Papers in Economics
1058, Boston College Department of Economics.
- David W. Hughes, 2022. "Estimating Nonlinear Network Data Models with Fixed Effects," Papers 2203.15603, arXiv.org, revised Mar 2023.
- Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Klochkov, Yegor, 2022. "SONIC: SOcial Network analysis with Influencers and Communities," Journal of Econometrics, Elsevier, vol. 228(2), pages 177-220.
- 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.
- Martin Weidner & Thomas Zylkin, 2021.
"Bias and consistency in three-way gravity models,"
CeMMAP working papers
CWP11/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Martin Weidner & Thomas Zylkin, 2019. "Bias and Consistency in Three-way Gravity Models," Papers 1909.01327, arXiv.org, revised Jun 2021.
- Weidner, Martin & Zylkin, Thomas, 2021. "Bias and consistency in three-way gravity models," Journal of International Economics, Elsevier, vol. 132(C).
- Martin Weidner & Thomas Zylkin, 2020. "Bias and Consistency in Three-way Gravity Models," CeMMAP working papers CWP1/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Daniel Czarnowske & Amrei Stammann, 2020. "Inference in Unbalanced Panel Data Models with Interactive Fixed Effects," Papers 2004.03414, arXiv.org.
- Bin Peng & Liangjun Su & Joakim Westerlund & Yanrong Yang, 2021.
"Interactive Effects Panel Data Models with General Factors and Regressors,"
Papers
2111.11506, arXiv.org.
- Bin Ping & Liangju Su & Yanrong Yang & Joakim Westerlund, 2023. "Interactive-effects panel-data models with general factors and regressors," French Stata Users' Group Meetings 2023 14, Stata Users Group.
- 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.
- Francesco Bartolucci & Claudia Pigini & Francesco Valentini, 2024.
"MCMC conditional maximum likelihood for the two-way fixed-effects logit,"
Econometric Reviews, Taylor & Francis Journals, vol. 43(6), pages 379-404, July.
- Bartolucci, Francesco & Pigini, Claudia & Valentini, Francesco, 2021. "MCMC Conditional Maximum Likelihood for the two-way fixed-effects logit," MPRA Paper 110034, University Library of Munich, Germany.
- Artūras Juodis & Simas Kučinskas, 2023. "Quantifying noise in survey expectations," Quantitative Economics, Econometric Society, vol. 14(2), pages 609-650, May.
- Williams, Benjamin, 2020. "Nonparametric identification of discrete choice models with lagged dependent variables," Journal of Econometrics, Elsevier, vol. 215(1), pages 286-304.
- Hugo Freeman & Martin Weidner, 2021. "Linear Panel Regressions with Two-Way Unobserved Heterogeneity," Papers 2109.11911, arXiv.org, revised Aug 2022.
- 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.
- Gao, Jiti & Liu, Fei & Peng, Bin & Yan, Yayi, 2023. "Binary response models for heterogeneous panel data with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 235(2), pages 1654-1679.
- Lena Boneva (Körber) & Oliver Linton, 2017.
"A discrete choice model for large heterogeneous panels with interactive fixed effects with an application to the determinants of corporate bond issuance,"
CeMMAP working papers
CWP02/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Boneva, Lena & Linton, Oliver, 2017. "A discrete choice model for large heterogeneous panels with interactive fixed effects with an application to the determinants of corporate bond issuance," Bank of England working papers 640, Bank of England.
- Boneva, L. & Linton, O., 2017. "A Discrete Choice Model For Large Heterogeneous Panels with Interactive Fixed Effects with an Application to the Determinants of Corporate Bond Issuance," Cambridge Working Papers in Economics 1703, Faculty of Economics, University of Cambridge.
- 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.
- Artūras Juodis, 2022. "A regularization approach to common correlated effects estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 788-810, June.
- Dolado, Juan J & Chen, Liang & Gonzalo, Jesus, 2018.
"Quantile Factor Models,"
CEPR Discussion Papers
12716, C.E.P.R. Discussion Papers.
- Liang Chen & Juan Jose Dolado & Jesus Gonzalo, 2019. "Quantile Factor Models," Papers 1911.02173, arXiv.org, revised Sep 2020.
- Liang Chen & Juan J. Dolado & Jesús Gonzalo, 2021. "Quantile Factor Models," Econometrica, Econometric Society, vol. 89(2), pages 875-910, March.
- Chen, Liang & Dolado, Juan J. & Gonzalo, Jesús, 2020. "Quantile Factor Models," IZA Discussion Papers 13870, Institute of Labor Economics (IZA).
- Chen, Liang, 2017. "Quantile Factor Models," UC3M Working papers. Economics 25299, Universidad Carlos III de Madrid. Departamento de EconomÃa.
- Chen, Liang & 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 EstadÃstica.
- Iv'an Fern'andez-Val & Hugo Freeman & Martin Weidner, 2020. "Low-Rank Approximations of Nonseparable Panel Models," Papers 2010.12439, arXiv.org, revised Mar 2021.
- Escribano, Alvaro & Peña, Daniel & Ruiz, Esther, 2021. "30 years of cointegration and dynamic factor models forecasting and its future with big data: Editorial," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1333-1337.
- Stéphane Bonhomme & Thibaut Lamadon & Elena Manresa, 2017.
"Discretizing unobserved heterogeneity,"
IFS Working Papers
W17/03, Institute for Fiscal Studies.
- Thibaut Lamadon & Elena Manresa & Stephane Bonhomme, 2016. "Discretizing Unobserved Heterogeneity," 2016 Meeting Papers 1536, Society for Economic Dynamics.
- St'ephane Bonhomme Thibaut Lamadon Elena Manresa, 2021. "Discretizing Unobserved Heterogeneity," Papers 2102.02124, arXiv.org.
- Bonhomme, Stéphane & Lamadon, Thibaut & Manresa, Elena, 2017. "Discretizing Unobserved Heterogeneity," Working Paper Series 2017:21, IFAU - Institute for Evaluation of Labour Market and Education Policy.
- Pigini, Claudia & Pionati, Alessandro & Valentini, Francesco, 2023.
"Specification testing with grouped fixed effects,"
MPRA Paper
117821, University Library of Munich, Germany.
- Claudia Pigini & Alessandro Pionati & Francesco Valentini, 2023. "Specification testing with grouped fixed effects," Papers 2310.01950, arXiv.org.
- 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.
- 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.
- 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.
- Hacioglu Hoke, Sinem & Kapetanios, George, 2017. "Common correlated effect cross-sectional dependence corrections for non-linear conditional mean panel models," Bank of England working papers 683, Bank of England.
- Nicholas Brown & Jeffrey Wooldridge, 2023. "More Efficient Estimation of Multiplicative Panel Data Models in the Presence of Serial Correlation," Working Paper 1497, Economics Department, Queen's University.
- Junhui Cai & Dan Yang & Wu Zhu & Haipeng Shen & Linda Zhao, 2021. "Network regression and supervised centrality estimation," Papers 2111.12921, arXiv.org.
- Bartolucci, Francesco & Pigini, Claudia, 2019.
"Partial effects estimation for fixed-effects logit panel data models,"
MPRA Paper
92243, University Library of Munich, Germany.
- Francesco Bartolucci & Claudia Pigini, 2018. "Partial effects estimation for fixed-effects logit panel data models," Working Papers 431, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
- 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.
- Liang Chen & Minyuan Zhang, 2023. "Common Correlated Effects Estimation of Nonlinear Panel Data Models," Papers 2304.13199, arXiv.org.
- Jin Zhou & Bei Liu & LU Mai, 2020.
"The Impact of a Prototypical Home Visiting Program on Child Skills,"
Working Papers
2020-047, Human Capital and Economic Opportunity Working Group.
- Zhou, Jin & Heckman, James J. & Liu, Bei & Lu, Mai, 2022. "The Impacts of a Prototypical Home Visiting Program on Child Skills," IZA Discussion Papers 15132, Institute of Labor Economics (IZA).
- James J. Heckman & Bei Liu & Mai Lu & Jin Zhou, 2020. "The Impacts of a Prototypical Home Visiting Program on Child Skills," NBER Working Papers 27356, National Bureau of Economic Research, Inc.
- 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.
- Jie Wei & Yonghui Zhang, 2022. "Panel Probit Models with Time‐Varying Individual Effects: Reestimating the Effects of Fertility on Female Labour Participation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(4), pages 799-829, August.
- 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.
- 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.
- Hugo Freeman, 2022. "Linear multidimensional regression with interactive fixed-effects," Papers 2209.11691, arXiv.org, revised Aug 2024.
Articles
- Chen, Mingli & Fernández-Val, Iván & Weidner, Martin, 2021.
"Nonlinear factor models for network and panel data,"
Journal of Econometrics, Elsevier, vol. 220(2), pages 296-324.
See citations under working paper version above.Sorry, no citations of articles recorded.
- Mingli Chen & Ivan Fernandez-Val & Martin Weidner, 2018. "Nonlinear factor models for network and panel data," CeMMAP working papers CWP38/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- 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.
- Mingli Chen & Ivan Fernandez-Val & Martin Weidner, 2019. "Nonlinear factor models for network and panel data," CeMMAP working papers CWP18/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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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 10 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.- NEP-ECM: Econometrics (7) 2016-03-29 2016-07-30 2018-01-15 2019-02-18 2019-08-26 2020-01-06 2020-01-06. Author is listed
- NEP-RMG: Risk Management (3) 2016-07-30 2017-10-08 2018-01-15
- NEP-ORE: Operations Research (2) 2016-03-29 2020-01-06
- NEP-BAN: Banking (1) 2018-01-15
- NEP-BIG: Big Data (1) 2021-04-26
- NEP-CBA: Central Banking (1) 2021-04-26
- NEP-CMP: Computational Economics (1) 2021-04-26
- NEP-DCM: Discrete Choice Models (1) 2019-02-18
- NEP-DGE: Dynamic General Equilibrium (1) 2021-04-26
- NEP-ETS: Econometric Time Series (1) 2016-03-29
- NEP-MFD: Microfinance (1) 2019-08-26
- NEP-MON: Monetary Economics (1) 2021-04-26
- NEP-NET: Network Economics (1) 2020-01-13
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