1. Download the Python package PyTimeVar using the command pip install PyTimeVar, see https://pypi.org/project/PyTimeVar/ for more info.
2. Python code for the paper “Domain ddaptation with Cauchy-Schwarz divergence.”
3. MATLAB code and EUETS dataset for the sieve bootstrap inference proposed in the paper “Sieve bootstrap inference for linear time-varying coefficient models.”
4. Python code and macroeconomic data for the estimation method and the autoregressive wild bootstrap used in the paper “Modelling time-varying relations in housing prices: A semiparametric panel approach.”
5. Python code and the data for the bootstrap methods proposed in the paper “Bootstrap inference for linear time-varying coefficient models in locally stationary time series.”
6. MATLAB code and the data for the estimation method and the panel autoregressive wild bootstrap inference established in the paper “Bootstrapping trending time-varying coefficient panel models with missing observations.”

Notes

• All code is provided under a GPL 2 or later license.
• The code may also be available on my GitHub page.
• Feel free to reach out via email with any inquiries about how to utilize these codes or to provide feedback. If you use the code for your research, kindly acknowledge the source by referring to this website and citing the relevant papers.