(Since July 2016)
Uematsu, Y. and Yamagata, T., 2023. "Discovering the Network Granger Causality in Large Vector Autoregressive Models."
Chen, J., Li D., Li, Y. and Linton, O., 2023. "Estimating time-varying networks for high-dimensional time series." arXiv preprint arXiv:2302.02476.
Lin, R. and Shin, Y., 2022. "Generalised Canonical Correlation Estimation of the Multilevel Factor Model." Available at SSRN 4295429.
Magnus, J.R., Ikefuji, M. and Yamagata, T., 2022. "Revealing Priors from Posteriors." Available at SSRN 4130839.
Li, J., Chen, L., Wang, W. and Wu, W.B., 2022. "$\ell^ 2$ Inference for Change Points in High-Dimensional Time Series via a Two-Way MOSUM."arXiv preprint arXiv:2208.13074.
Chernozhukov, V., Huang, C. and Wang, W., 2021. "Learning Network with Focally Sparse Structure." arXiv preprint arXiv:2105.07424.
Cui, G., Sarafidis, V., Yamagata, T., 2020, "IV Estimation of Spatial Dynamic Panels with Interactive Effects: Large Sample Theory and an Application on Bank Attitude".
JS Cho, M Greenwood-Nimmo, Y Shin, 2019, "Two-Step Estimation of the Nonlinear Autoregressive Distributed Lag Model", Yonsei Economics Research Institute Working papers.
Jia Chen., Gu, Y., Jones, A. and Peng, B., 2019, "Modelling health care expenditures -- a semiparametric approach", To be submitted.
G Kapetanios, L Serlenga, Y Shin, 2019, ''Testing for Correlated Factor Loadings in Cross Sectionally Dependent Panels,'' SERIES Working papers N. 02/2019.
Hayakawa, K., Pesaran, MH., Smith, LV., 2018 (revised in Feb 2020) "Short T Dynamic Panel Data Models with Individual, Time and Interactive Effects."
Pesaran, M.H., Yamagata, T., 2017, "Testing for Alpha in Linear Factor Pricing Models with a Large Number of Securities," Discussion Papers 17/04, Department of Economics, University of York.
Li, Y.N., Chen, J. and Linton, O., 2023. Estimation of common factors for microstructure noise and efficient price in a high-frequency dual factor model. Journal of Econometrics, forthcoming.
Choi, I., Lin, R. and Shin, Y., 2023. Canonical correlation-based model selection for the multilevel factors. Journal of Econometrics, 233(1), pp.22-44.
Shin, Y., Kapetanios, G. and Serlenga, L., 2023. Testing for Correlation between the Regressors and Factor Loadings in Heterogeneous Panels with Interactive Effects. Empirical Economics.
Chen, L., Wang, W. and Wu, W.B., 2022. Inference of breakpoints in high-dimensional time series. Journal of the American Statistical Association, 117(540), pp.1951-1963.
Bravo, F., 2022. Second order expansions of estimators in nonparametric moment conditions models with weakly dependent data. Econometric Reviews, 41(6), pp.583-606.
Bravo, F., 2022. Misspecified semiparametric model selection with weakly dependent observations. Journal of Time Series Analysis, 43(4), pp.558-586.
Ando, T., Greenwood-Nimmo, M. and Shin, Y., 2022. Quantile connectedness: modeling tail behavior in the topology of financial networks. Management Science, 68(4), pp.2401-2431.
Keilbar, G. and Wang, W., 2022. Modelling systemic risk using neural network quantile regression. Empirical Economics, 62(1), pp.93-118.
Xu, X., Wang, W., Shin, Y. and Zheng, C., 2022. Dynamic network quantile regression model. Journal of Business & Economic Statistics, pp.1-15.
Uematsu, Y. and Yamagata, T., 2022. Inference in sparsity-induced weak factor models. Journal of Business & Economic Statistics, 41(1), pp.126-139.
Uematsu, Y. and Yamagata, T., 2022. Estimation of sparsity-induced weak factor models. Journal of Business & Economic Statistics, 41(1), pp.213-227.
Cui, G., Hayakawa, K., Nagata, S. and Yamagata, T., 2022. A Robust Approach to Heteroscedasticity, Error Serial Correlation and Slope Heterogeneity in Linear Models with Interactive Effects for Large Panel Data. Journal of Business & Economic Statistics, pp.1-14.
Cui, G., Norkutė, M., Sarafidis, V. and Yamagata, T., 2022. Two-stage instrumental variable estimation of linear panel data models with interactive effects. The Econometrics Journal, 25(2), pp.340-361.
Jia Chen, Shin, Y. and Zheng, C., 2022. Estimation and inference in heterogeneous spatial panels with a multifactor error structure. Journal of Econometrics, 229(1), pp.55-79.
Chen, J., Li D., Wei, L. and Zhang, W., 2021. Nonparametric homogeneity pursuit in functional-coefficient models. Journal of Nonparametric Statistics, 33(3-4), pp.387-416.
Smith, L.V., Tarui, N. and Yamagata, T., 2021. Assessing the impact of COVID-19 on global fossil fuel consumption and CO2 emissions. Energy economics, 97, p.105170.
Chernozhukov, V., Karl Härdle, W., Huang, C. and Wang, W., 2021. Lasso-driven inference in time and space. The Annals of Statistics, 49(3), pp.1702-1735.
G Kapetanios, L Serlenga, Y Shin, 2021, '' Estimation and Inference for Multi-dimensional Heterogeneous Panel Datasets with Hierarchical Multi-factor Error Structure, '' Journal of Econometrics 220(2), 504-531.
Bravo, F., Li D. and Tjøstheim, D., 2021. Robust nonlinear regression estimation in null recurrent time series. Journal of Econometrics, 224(2), pp.416-438.
Norkute, M., Sarafidis, V., Yamagata, T., Cui, G., 2021 , "Instrumental Variable Estimation of Dynamic Linear Panel Data Models with Defactored Regressors and a Multifactor Error Structure," Journal of Econometrics 220, 416-446.
Coroneo, L. and Iacone, F., 2020. Comparing predictive accuracy in small samples using fixed‐smoothing asymptotics. Journal of Applied Econometrics, 35(4), pp.391-409.
Chen, L., Wang, W., Wu, WB., 2020 "Dynamic Semiparametric Factor Model With Structural Breaks ," Journal of Business & Economic Statistics, 00, 1-15.
Hou, AJ., Wang, W., Chen, CYH, Härdle, WK., "Pricing Cryptocurrency Options," Journal of Financial Econometrics 18(2), 250-279.
M Greenwood-Nimmo, V Nguyen, Y Shin, 2019, ''4 Quantifying informational linkages in a global model of currency spot markets ,'' International Financial Markets, Volume 1.
Chen, J., 2019, Estimating Latent Group Structure in Time-Varying Coefficient Panel Data Models, Econometrics Journal, 22(3) 223-240.
Cai, C.X., Kim, M., Shin, Y.. and Zhang, Q., 2019. FARVaR: functional autoregressive value-at-risk. Journal of Financial Econometrics, 17(2), pp.284-337.
Chen, J., Li, D., Linton, O., 2018, A New Semiparametric Estimation Approach for Large Dynamic Covariance Matrices with Multiple Conditioning Variables, Journal of Econometrics, 212(1), 155-176.
Bailey, N., Pesaran, M.H., Smith, L.V., 2018, A multiple testing approach to the regularisation of large sample correlation matrices, Journal of Econometrics, 208(2), 507-534.
T Omay, M Hasanov, Y Shin, 2018, Testing for Unit Roots in Dynamic Panels with Smooth Breaks and Cross-Sectionally Dependent Errors, Computational Economics, 52 (1), 167-193.
Shin, Y., Greenwood-Nimmo, M. & Nguyen, V. , 2018, Quantifying Informational Linkages in a Global Model of Currency Spot Markets, Advances in Applied Financial Econometrics. Routledge.
Chen, J., Li, D., Linton, O., Lu, Z., 2018, Semiparametric Ultra-High Dimensional Model Averaging of Nonlinear Dynamic Time Series, Journal of the American Statistical Association, 1-30.
Park, H., Shin, Y., 2018, The Effects of Oil Price on the Korean Economy: A Global VAR Approach, Emerging Markets Finance and Trade, 54, 981-991.
Kapetanios, G., Mastromarco, C., Serlenga, L., Shin Y., 2017, Multi-dimensional Panel Data Modelling in the Presence of Cross Sectional Error Dependence , The Econometrics of Multi-dimensional Panels, 291-322.
Park, H., Shin, Y., 2017, Exploring international linkages using generalised connectedness measures: The case of Korea, International Review of Economics and Finance, 50, 49-64.
Shin, Y., Kapetanios, G., Mastromarco, C., Serlenga, L., 2017, Modelling in the Presence of Cross Sectional Error Dependence, The Econometrics of Multi-dimensional Panels: Theory and Applications. Matyas, L. (ed.). Springer, 31 p.
Chen, J., Li, D., Linton, O., Lu, Z., 2018, Semiparametric Ultra-High Dimensional Model Averaging of Nonlinear Dynamic Time Series, Journal of the American Statistical Association, 1-30.
Halunga, A., Orme, C.D., Yamagata, T., 2017, A Heteroskedasticity Robust Breusch-Pagan Test for Contemporaneous Correlation in Dynamic Panel Data Models, Journal of Econometrics, 198, 209-230.
Shin, Y. & Seo, M. H., 2016, Inference for Dynamic Panels with Threshold Effect and Endogeneity, Journal of Econometrics, 195, 169-186
Chen, J., Li D., Linton, O., Lu, Z., 2016, Semiparametric dynamic portfolio choice with multiple conditioning variables, Journal of Econometrics, 194, 309-318.