07:20 PM to 10:00 PM W
Innovation Hall 328
Section Information for Spring 2019
This course aims at helping you develop skills to analyze data that evolves over time, such as GDP, interest rates, stock prices, etc. The focus is primarily applied, as opposed to theoretical. As such, we will rely on statistical software (primarily STATA) to understand and develop stationary models (including ARMA and ARIMA, which are used in forecasting). We will also learn how to deal with non-stationary series (stochastic detrending, linear filtering, etc.). In addition, we will cover VAR models (vector autoregressions), Structural VARs, Cointegration and Error Correction. Finally, you will be introduced to analysis in the frequency domain as well as elementary spectral analysis. Applications will include, but are not limited to, Austrian Business Cycle Theory, pricing of cryptocurrencies, international political relations, simulations, etc. To get the most out of this course, previous exposure to econometrics, basic differential equations, and basic linear algebra would be very helpful. The course is open to all Ph.D. as well as M.A. students.
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Enrollment is limited to Graduate level students.