This course uses econometric tools to analyze choices made by people among a finite set of alternatives. Discrete choice models have been used to understand consumer behavior in many domains - shopping between brands (Toyota vs. BMW), where to go to college (Caltech or MIT), choosing between modes of transportation (car, metro, Uber, or bicycle), etc. Models studied include logit, nested logit, probit, and mixed logit, etc. Simulation techniques that allow estimation of otherwise intractable models will also be discussed. Not offered 2024-25.