Time series and dynamic panel data 1600-SZD-WM-SCiPD
Classes are devoted to the methods of data analysis with a time dimension i.e. time-series data. Regardless of whether we want to analyze trends in financial markets or changes in fertility or poverty, time is an important factor to consider in our research. A time series is simply a series of data points ordered in time. However, time-series modeling raises several questions about the nature of our data. Are the variables stationary? Is there seasonality in the data? Are variables characterized by autocorrelation? In the class, I will present various features of time series and dynamic panels, followed by the way they are modeled to obtain accurate (as much as possible) analyzes. The aim of the course is, thus, to gain knowledge about the use of statistics in the analysis of data with a time dimension. Therefore, each participant will have the opportunity to use these skills in practice. Teams of at most 2 participants will be asked to write a final essay of up to 14 pages on a selected topic. Authors should use the tools shown during classes analyzing the answers to one of the common issues in the scientific literature. All teams are required to present their work (max 15 minutes) at the end of the course in the form of a presentation.
1) Mode of Teaching: lab
Type of course
Course coordinators
Learning outcomes
WK3, UW1
Assessment criteria
Assessment Tasks:
The objective of the course is to gain knowledge of the applicationof statistics to time-series data. Therefore,everyone will have the chance to exercise these skills inpractice. Teams of at most 2 students will write a coursepaper up to 10 pages on a chosen macroeconomic topic. Theauthors should use the econometric tools shown during thecourse to answer one of the conventionalscientificissues prevalent in the literature.First, you are required to prepare a one-page description ofyour proposed topic. This abstract should include a shorttheoretical introduction (why&what), data sources (briefly –though one should be certain about availability of the neededdata), variables, choice of the estimation method (withjustification), research hypothesis/hypotheses. I will discussthe research plan with each team individually and provide youwith feedback.Afterward, you will have up to 3 weeks to carry out theproposed application and submit the final paper (up to 10pages) together with a short PowerPoint presentation. Allteams are required to present their paper (15-20 minutes) atthe end of the course.
1) Learning Outcomes Assessment:
The papers will be evaluated in terms of statistical validity of the hypothesis’sverification, the capacity to draw conclusions, and the ability to present them clearly and concisely.
2) Assessment criteria:
Approved abstract of the paper - 25% of the final grade,
The final version of the work with the prepared statistical model - 50%,
Presentation - 25%.
Bibliography
Major Readings: all data and handouts will be available via course webpage.
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: