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Title: Quantile LASSO with change-points in panel data models Authors:  Matus Maciak - Charles University (Czech Republic) [presenting]
Abstract: Panel data are commonly used in all kinds of econometric problems under various regularity assumptions. We investigate the panel data models with changepoints and the atomic pursuit technique and quantile estimation are applied to obtain the final estimate. Robust estimates and a complex insight into the data generating mechanism are both achieved by adopting the quantile LASSO approach. The final model is produced in a fully data-driven manner in just one single step. The final estimate is, under some reasonable assumptions, shown to be consistent with respect to the model estimation and the changepoint detection performance. The finite sample properties are investigated in a simulation study and the proposed methodology is applied for the Apple call option pricing problem.