This is the first half of the second course in the econometrics sequence for first-year, finance PhD students. We will start by reviewing basic time series concepts and the asymptotic distribution theory associated with estimating well behaved time series models. Then, we will cover the generalized method of moments. Vector autoregressions are next, followed by maximum likelihood estimation and modeling conditional heteroskedasticity. We will then cover non-stationary time series including unit root econometrics and cointegration, and we will finish with an introduction to Bayesian analysis and the Kalman filter.
Nomura Professor of International Finance
Professor Hodrick teaches both fundamental and advanced courses in international finance. His expertise is in the valuation of financial assets. His current research explores the empirical implications of theoretical pricing models that generate time-varying risk premiums in the markets for bonds, equities and foreign currencies. He is also a research associate of the National Bureau of Economic Research.