Wei Lan, Hansheng Wang and Chih-Ling Tsai (2012) “A Bayesian information criterion for portfolio selection,” Computational Statistics & Data Analysis, 56, 88--99.
Wei Lan, Hansheng Wang and Chih-Ling Tsai (2014) “Testing covariates in high dimensional regression,” Annals of the Institute of Statistical Mathematics，66, 279--301.
Jing Zhou, On Kit Tam, and Wei Lan (2015) “Are investor protection and ownership concentration substitutes in Chinese family firms?” Emerging Markets Finance and Trade, 51, 432--443.
Wei Lan, Ronghua Luo, Chih-Ling Tsai, Hansheng Wang, and Yunhong Yang (2015) “Testing the diagonality of a large covariance matrix in a regression setting,” Journal of Business & Economic Statistics, 33, 77--86.
Yingying Ma, Wei Lan and Hansheng Wang (2015) “Testing predictor significance with ultra high dimensional multivariate responses,” Computational Statistics & Data Analysis, 83, 275--286.
Yingying Ma, Wei Lan and Hansheng Wang (2015) “A high dimensional two-sample test under a low dimensional factor structure,” Journal of Multivariate Analysis, 140,162--170.
Wei Lan, Yue Ding, Zheng Fang and Kuangnan Fang (2016) “Testing covariates in high dimension linear regression with latent factors,” Journal of Multivariate Analysis, 144, 25--37.
Wei Lan, Ping-Shou Zhong, Runze Li, Hansheng Wang and Chih-Ling Tsai (2016) “Testing a single regression coefficient in high dimensional linear models,” Journal of Econometrics, 195, 154--168.
Jing Zhou, On Kit Tam, and Wei Lan (2016) “Solving agency problems in Chinese family firms-A law and finance perspective,” Asian Business & Management, 15, 57--82.
Jing Zhou, Wei Lan and Tang, Y (2016) “The value of institutional shareholders: Evidence from cross-border acquisitions by Chinese listed firms,” Management Decision, 54, 44--65.
Tao Zou, Wei Lan, Hansheng Wang, Chih-Ling Tsai (2017) “Covariance regression analysis,” Journal of the American Statistical Association, 112, 266--281.
Ronghua Luo and Wei Lan (2017) “Detecting homogeneous predictors in high dimensional panel model with a MCMC algorithm,” Communication in Statistics--Simulation and Computation, 46, 7376--7392.
Pingshou Zhong, Wei Lan, Peter Song and Chih-Ling Tsai (2017) “Tests for covariance structures with high dimensional repeated measurements,” The Annals of Statistics, 45, 1185-1213.
Wei Lan, Rui Pan, Ronghua Luo and Yongwei Chen (2017) “High dimensional cross-sectional dependence test under arbitrary serial correlation,” Science China-Mathematics, 60, 345--360.
Wei Lan, Yingying Ma, Junlong Zhao, Hansheng Wang and Chih-Ling Tsai (2018) “Sequential model averaging for high dimensional linear regression models,” Statistica Sinica, 28,449--469.
Wei Lan, Zheng Fang, Hansheng Wang and Chih-Ling Tsai (2018) “Covariance matrix estimation via network structure,” Journal of Business & Economics Statistics, 36, 359--369.
Wei Lan, Long Feng and Ronghua Luo (2018) “Testing high dimensional linear asset pricing models,” Journal of Financial Econometrics, 16,191--210.
Jing Zhou and Wei Lan (2018) “Investor protection and cross-border acquisitions by Chinese listed firms: The moderating role of institutional shareholders ,” International Review of Economics and Finance, 56, 438--450.
Lilun Du, Wei Lan, Ronghua Luo and Pingshou Zhong (2018) “Factor adjusted multiple testing of correlations,” Computational Statistics & Data Analysis, 128, 34--47.
Danyang Huang, Wei Lan, Zhang, H, Hansheng Wang (2019) “Least squares estimation for social autocorrelation in large-scale networks,” Electronic Journal of Statistics, 13, 1135--1165.
Fang Fang, Wei Lan, Jingjing Tong and Jun Shao (2019) “Model averagying for prediction with fragmentary data,” Journal of Business & Economic Statistics, 37, 517--527.
Wei Lan and Lilun Du (2019) “A factor-adjusted multiple testing procedure with application to mutual fund selection”,Journal of Business & Economics Statistics, 37, 147--157.
Ronghua Luo, Yi Liu and Wei Lan (2019) “A penalized expected risk criterion for portfolio selection”, China Finance Review International, 3, 386--400.
Kuangnan Kuang, Xinyan Fan, Wei Lan and Bingquan Wang (2019) “Nonparametric additive beta regression for fractional response with application to body fat data,” Annals of Operations Research, 276,331--347.
Tao Zou, Ronghua Luo, Wei Lan and Chih-Ling Tsai (2020) “Covariance Regression Model for Non-Normal Data,” Handbook of Financial Econometrics, Mathematics, Statistics, and Machine Learning (Chapter 113). Ed. Lee, C. F. and Lee, J. World Scientific: Singapore.
Yingying Ma, Wei Lan, Fanyin Zhou and Hansheng Wang (2020) “Approximate least squares estimation for spatial autoregressive models with covariates”, Computational Statistics & Data Analysis,143,106833.
Shujie Ma, Wei Lan, Liangjun Su and Chih-Ling Tsai (2020) “Testing alpha in conditional time-varying factor models with high dimensional assets,” Journal of Business & Economic Statistics, 38,214--227.
Lin, H, Wei Liu and Wei Lan (2021) “Regression analysis with individual-specific patterns of missing covariates,” Journal of Business & Economic Statistics, 39, 179—188.
Tao Zou, Ronghua Luo, Wei Lan and Chih-Ling Tsai (2021) “Network influence analysis,” Statistica Sinica, 31, 1727--1748.
Long Feng, Wei Lan, Binghui Liu and Yanyuan Ma (2022) “High-dimensional test for alpha in linear factor pricing models with sparse alternatives,” Journal of Econometrics, 229, 152--175.
Wei Lan, Xuerong Chen, Tao Zou and Chih-Ling Tsai (2022) “Imputations for high missing rate data in covariates via semi-supervised learning approach,” Journal of Business & Economic Statistics, 40,1282--1290.
Yujia Wu, Wei Lan, Tao Zou and Chih-Ling Tsai (2022) “Inward and outward network influence analysis,” Journal of Business & Economic Statistics, 40, 1617--1628.
Tao Zou, Wei Lan, Runze Li and Chih-Ling Tsai (2022) “Inferences on covariance-mean regression,” Journal of Econometrics, 230, 318--338.
Bofei Xiao, Bo Lei, Wei Lan and Bin Guo (2022) “A blockwise network autoregressive model with application for fraud detection,” Annals of the Institute of Statistical Mathematics, 74, 1043--1065.
Rong Zhang, Jing Zhou, Wei Lan and Hansheng Wang (2022) “A case study on the shareholder network effect of stock market data: An SARMA approach,” Science China Mathematics, 65, 2219--2242.
Jing Zhou, Wei Lan and Hansheng Wang (2022) “Asymptotic covariance estimation by Gaussian random perturbation,” Computational Statistics & Data Analysis,171, 107459.
Bo Lei, Wei Lan, Nengsheng Fang and Jing Zhou (2023) “Polynomial network autoregressive models with divergent order,” Science China Mathematics, 66, 1073--1086.
Kuangnan Fang, Wei Lan, Dan Pu and Qingzhao Zhang (2024) “Spatial autoregressive models with generalized spatial disturbances,” Statistica Sinica, 34, 725--745.
Xinyan Fan, Wei Lan, Zou Tao and Chih-Ling Tsai (2024) “Covariance model with general linear structure and divergent parameters,” Journal of Business & Economic Statistics, 42, 36--48.
Xinyan Fan, Wei Lan, Zou Tao and Chih-Ling Tsai (2024) “Mutual influence regression model,” Statistica Sinica, 34, 1723--1743.
Wei Lan, Bo Lei, Long Feng and Chih-Ling Tsai (2024) “Maximum-subsampling test of equal predictive ability,” Journal of Business & Economic Statistics, 42, 1344--1355.
Yujia Wu, Wei Lan, Xinyan Fan and Kuangnan Fang (2024) “Bipartite network influence analysis of a two-mode network," Journal of Econometrics, 239, 105562.
Jun Zhang, Lan Wei, Xinyan Fan* and Wen Chen (2023),“Maximum Conditional Alpha Test for Conditional Multi-Factor Models”，Statistical Sinica, In Press.
Dan Pu, Kuangnan Fang, Wei Lan, Jihai Yu and Qingzhao Zhang (2024) “Multivariate spatiotemporal models with low rank coefficient matrix,” Journal of Econometrics, 246, 105897.
Dan Pu, Kuangnan Fang, Wei Lan, Jihai Yu and Qingzhao Zhang (2025) “Reduced rank spatio-temporal models,” Journal of Business & Economic Statistics, 43, 98--109.
Yuanxing Chen, Kuangnan Fang, Wei Lan, Chih-Ling Tsai and Qingzhao Zhang (2025) “Community influence analysis in social networks,” Computational Statistics & Data Analysis, 202, 108037.
Yingying Ma, Wei Lan, Chenlei Leng, Ting Li and Hansheng Wang (2025) “Supervised centrality via sparse network influence regression: An application to the 2021 Henan floods,” Annals of Applied Statistics, In Press.
Tao Zou, Wei Lan, Runze Li and Chih-Ling Tsai (2025) “Fixed and random covariance regression analyses,” Annals of Statistics, In Press.
Xinyan Fan, Kuangnan Fang, Wei Lan and Chih-Ling Tsai (2025) “Network varying coefficient model,” Journal of the American Statistical Association, In Press.
Dongxue Zhang, Long Feng, Yujia Wu, Wei Lan, and Jing Zhou (2025) “Temporal network influence model with application to the COVID-19 population flow network,” Annals of Applied Statistics, In Press.
罗荣华，兰伟，杨云红（2011），“基金的主动性管理提升了业绩吗，” 《金融研究》2011年第10期。
罗荣华，兰伟，杨云红(2015)，“基金排名与主动性水平：理论与实证，”《中国管理科学》，2015年第8期，158—167.
严成樑，李涛，兰伟(2016)，“金融发展、创新与二氧化碳排放”，《金融研究》2016年第1期。
贺平，兰伟，丁月（2021），“中国股票市场可以预测吗？基于组合LASSO-logistic方法的视角”，《统计研究》，2021年第5期。
和泽慧，路晓蒙，罗荣华，兰伟（2023），“打破刚性兑付,资金何去何从?——基于家庭资产配置的微观视角”，《经济学季刊》，2023年第4期。
丁月，方匡南，兰伟，徐顺（2024），“基于网络关系的分类变量预测研究”，《统计研究》，2024年第1期。
常琦，雷博，罗荣华，兰伟（2024），“强制性社会责任报告披露政策的规制效用评估——基于同伴效应的视角”，《统计研究》，2024年第10期。
研究项目
1. 国家自然科学基金优秀青年基金项目，“金融风险管理中的计量经济学方法研究”，项目批准号：72422020，项目主持人。
2. 国家自然科学基金面上项目，“大型协方差矩阵的结构化估计和检验”，项目批准号：12171395,2022/1-2025/12，项目主持人。
3. 国家青年自然科学基金，“高维近似因子模型框架下的多重检验及其应用”，项目批准号：11401482,2015/1-2017/12，项目主持人。
4. 国家自然科学基金重点项目，“空间/网络计量建模理论及其经济应用”，项目批准号：72333001,2024/1-2028/12，子项目负责人。
5. 国家自然科学基金重点项目，“半参数集成回归推断”，项目批准号：11931014, 2020/1-2024/12，子项目负责人。
6. 国家自然科学基金重点项目，“大数据驱动的管理决策模型和算法”，项目批准号：71532001，2016/1-2020/12，子项目负责人。
7. 国家自然科学基金重大项目子课题，“时空数据建模与预测研究”，项目批准号：71991472，2020/1-2024/12，参与人。
8. 科技部重点研发计划，“分布式统计学习理论与方法”，项目批准号：2022YFA1003702，2022/12-2027/11，参与人。
社会兼职：
中国青年统计学家协会副会长，四川省现场统计学会副理事长，全国工业统计学教学研究会常务理事，《STAT》副主编，Journal of the American Statistical Association、The Annals of Statistics、Journal of Business and Economic Statistics、Journal of Econometrics等国内外著名期刊匿名审稿人。
