虞吉海现任北京大学光华管理学院商务统计与经济计量系的教授，他的主要研究方向为空间计量经济学和微观数据分析。具体来讲，就是对各种静态空间面板模型和动态空间面板模型进行设定、估计及相关的统计推断，同时运用计量工具对区域经济增长、地方政府竞争、和大气污染等领域进行实证分析。

研究成果

英文期刊

[1] Yu, J., R. de Jong and L.F. Lee, 2008. Quasi-Maximum Likelihood Estimators for Spatial Dynamic Panel Data With Fixed Effects When Both n and T Are Large. Journal of Econometrics 146, 118-134.

[2] Lee, L.F., and J. Yu, 2009. Spatial Nonstationarity and Spurious Regression: The Case with Row-Normalized Spatial Weights Matrix. Spatial Economic Analysis 4:3, 301-327.

[3] Lee, L.F., and J. Yu, 2010. Estimation of Spatial Autoregressive Panel Data Models with Fixed Effects. Journal of Econometrics 154, 165-185.

[4] Lee, L.F., and J. Yu, 2010. A Spatial Dynamic Panel Data Model With Both Time and Individual Fixed Effects. Econometric Theory 26, 564-597.

[5] Yu, J. and L.F. Lee, 2010. Estimation of Unit Root Spatial Dynamic Panel Data Models. Econometric Theory 26, 1332-1362.

[6] Lee, L.F., and J. Yu, 2010. Some Recent Developments in Spatial Panel Data Models. Regional Science and Urban Economics 40, 255-271.

[7] Lee, L.F., and J. Yu, 2011. Estimation of Spatial Panels. Foundations and Trends in Econometrics, NOW publisher.

[8] Lee, L.F., and J. Yu, 2011. A Unified Transformation Approach for the Estimation of Spatial Dynamic Panel Data Models: Stability, Spatial Cointegration and Explosive Roots. In: Ullah, A., Giles, D.E.A. (Eds.), Handbook on Empirical Economics and Finance, 397-434 , Taylor & Francis Group, New York.

[9] Yu, J., R. de Jong and L.F. Lee, 2012. Estimation for Spatial Dynamic Panel Data with Fixed Effects: the Case of Spatial Cointegration. Journal of Econometrics 167, 16-37.

[10] Lee, L.F., and J. Yu, 2012. QML Estimation of Spatial Dynamic Panel Data Models with Time Varying Spatial Weights Matrices. Spatial Economic Analysis 7, 31-74.

[11] Lee, L.F., and J. Yu, 2012. Spatial Panels: Random Components vs. Fixed Effects. International Economic Review 53, 1369-1412.

[12] Lee, L.F., and J. Yu, 2012. The C(a)-type Gradient Test for Spatial Autoregressive Models. Letters in Spatial and Resource Sciences 5, 119-135.

[13] Yu, J. and L.F. Lee, 2012. Convergence: A Spatial Dynamic Panel Data Approach. Global Journal of Economics 1, 125006 (36 pages).

[14] Tao, J and J. Yu, 2012. The Spatial Time Lag in Panel Data Models. Economics Letters 117, 544-547.

[15] Lee, L.F., and J. Yu, 2013. Near Unit Root in the Spatial Autoregressive Model. Spatial Economic Analysis 8, 314-351.

[16] Yu., J and G. Zhu, 2013. How Uncertain is Household Income in China. Economics Letters 120, 74-78.

[17] C. Ho, W. Wang and J. Yu, 2013. Growth Spillover through Trade: A Spatial Dynamic Panel Data Approach. Economics Letters 120, 450-453.

[18] Lee, L.F., and J. Yu, 2014. Efficient GMM Estimation of Spatial Dynamic Panel Data Models. Journal of Econometrics 180, 174-197.

[19] Lee, L.F., and J. Yu, 2015. Estimation of Fixed Effects Panel Regression Models with Separable and Nonseparable Space-time Filters. Journal of Econometrics 184, 174-192.

[20] Lee, L.F., and J. Yu, 2015. Spatial Panel Data Models. In: Baltagi, B (Eds.), Oxford Handbook of Panel Data. Oxford University Press. 363-401.

[21] Wang, W. and J. Yu, 2015. Estimation of Spatial Panel Data Models with Time Varying Spatial Weights Matrices. Economics Letters 128, 95-99.

[22] Yu, J., L.A. Zhou and G. Zhu, 2016. Strategic Interaction in Political Competition: Evidence from Spatial Effects across Chinese Cities. Regional Science and Urban Economics 57, 23-37.

[23] Lee, L.F. and J. Yu, 2016. Identification of Spatial Panel Durbin models. Journal of Applied Econometrics 31, 133-162.

[24] Yang, Z, J. Yu and S.F. Liu, 2016. Bias Correction and Refined Inference for Fixed Effects Spatial Panel Data Models. Regional Science and Urban Economics 61, 52-72.

[25] Qu, X., L.F. Lee and J. Yu, 2017. QML Estimation of Spatial Dynamic Panel Data Models with Endogenous Time Varying Spatial Weights Matrices. Journal of Econometrics 197, 173-201.

[26] Ho, C., W. Wang and J. Yu, 2018. International Knowledge Spillover through Trade: A Time-Varying Spatial Panel Data Approach. Economics Letters 162, 30-33.

[27] Zhang, X. and J. Yu, 2018. Spatial Weights Matrix Selection and Model Averaging for Spatial Autoregressive Models. Journal of Econometrics 203, 1-18.

[28] Lee, L.F and J. Yu, 2020. Initial conditions of dynamic panel data models: on within and between equations. Econometrics Journal 23, 115-136.

[29] Jin, F., Lee, L.F and J. Yu, 2020. First difference estimation of spatial dynamic panel data models with fixed effects. Economics Letters 189, 109010.

[30] Jin, F., Lee, L.F and J. Yu, 2021. Sequential and efficient GMM estimation of dynamic short panel data models. Econometric Reviews 40:10, 1007-1037.

[31] Chang, H., W. Wang and J. Yu, 2021. Revisiting environmental Kuznets curve in China: A spatial dynamic panel data approach. Energy Economics 104, 105600.

[32] Lee, L.F., C. Yang, and J. Yu, 2022. QML and efficient GMM estimation of spatial autoregressive models with dominant (popular) units. Journal of Business and Economics Statistics, forthcoming.

[33] Jin, F., L.F. Lee and J. Yu, 2022. Estimating flow data models of international trade: Dual gravity and spatial interactions. Econometric Reviews, forthcoming.

[34] Chang, H. and J. Yu, 2024. Impact analysis for spatial autoregressive models: with application to air pollution in China. Statistica Sinica 34(2), forthcoming.

书评

[35] Introduction to Spatial Econometrics by James LeSage and R. Kelley Pace. Geographical Analysis 42 (2010) 356-359.

中文期刊

[36] 王劲松, 虞吉海, 2000. 关于货币政策中间目标变量的比较研究及其启示. 经济学动态, 2000 (04), 62-66.

[37] 虞吉海, 王劲松, 2000. 流动性陷阱与日本的经济萧条. 世界经济, 2000 (07), 73-77.

[38] 虞吉海, 2000. 中央银行和非国有商业银行提高资本金比例的博弈分析. 国际金融研究, 2000 (07), 26-30.

[39] 朱国钟, 乔坤元, 虞吉海, 2014. 中国各省经济增长是否收敛？ 经济学季刊, 2014 (04), 1171-1194.

[40] 张轩瑜,宋晓军,虞吉海 , 2020. 中国环境库兹涅茨曲线--基于省级 PM2.5的实证分析. 环境科学学报,40 (1), 315-324.

[41] 宋晓军,李曦纳,虞吉海, 2020. 空间动态短面板的估计及中国城市经济增长收敛性的分析. 经济学报, 7 (1), 38-59.