Econ 475: Economic Forecasting

I have been following Tesla stock since its June 29, 2010 IPO at $17 per share. This summer, TSLA celebrated its 10th birthday and sold for 10,000% of its IPO price! 

For the past several years, my students have been tracking TSLA and other economic phenomena, including GDP, inflation, oil prices, and the latest jobs numbers.

These students have gone on to successful careers in economics, finance, business, or graduate studies. I have former students pursuing graduate degrees in places like UIUC, Northwestern, and MIT.

Course Description:

This course provides an overview of modern, quantitative, statistical and econometric methods for forecasting and evaluating forecasts. Topics include linear regressions; modeling and forecasting trend and seasonality; characterizing and forecasting cycles; MA, AR, and ARMA models; forecasting with regressions; evaluating and combining forecasts; unit roots; stochastic trends; ARIMA models; and smoothing. Advanced topics such as volatility measurement, modeling, and forecasting will be covered if time permits. Students will be required to write code in one of several software environments commonly used for forecasting.

Credits: 3 hours (Undergraduate)/4 hours (Master)

Prerequisites: Students are assumed to have taken ECON202, ECON203 (Economic Statistics 1 and 2) or equivalent statistics and econometrics courses. Knowledge about basic calculus is also required.