1. 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.
2. 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.
3. 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.
4. Zhang, X. and J. Yu, 2018. Spatial Weights Matrix Selection and Model Averaging for Spatial Autoregressive Models. Journal of Econometrics 203, 1-18.
5. Lee, L.F and J. Yu, 2020. Initial conditions of dynamic panel data models: on within and between equations. Econometrics Journal 23, 115-136.
6. 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.
7. 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.
8. Chang, H., W. Wang and J. Yu, 2021. Revisiting environmental Kuznets curve in China: A spatial dynamic panel data approach. Energy Economics 104, 105600.
9. 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.
10. Jin, F., L.F. Lee and J. Yu, 2022. Estimating flow data models of international trade: Dual gravity and spatial interactions. Econometric Reviews , forthcoming.
11. Chang, H. and J. Yu, 2024. Impact analysis for spatial autoregressive models: with application to air pollution in China. Statistica Sinica 34(2), forthcoming.