Lecture notes for Econometrics 2002

The main contents of the lecture consist of the following: Univariate time series analysis, the distribution of a sample average, least squares, instrumental variable method, simulating the finite sample properties, GMM, examples and applications of GMM, vector autoregression (VAR), kalman filter, outliers and robust estimators, generalized least squares,. | Lecture Notes for Econometrics 2002 (first year PhD course in Stockholm) Paul Söderlind1 June 2002 (some typos corrected and some material added later) 1 University of St. Gallen. Address: s/bf-HSG, Rosenbergstrasse 52, CH-9000 St. Gallen, Switzerland. E-mail: . Document name: . Contents 1 Introduction Means and Standard Deviation Testing Sample Means . . . . Covariance and Correlation . . Least Squares . . . . . . . . . Maximum Likelihood . . . . . O The Distribution of ˇ . . . . . Diagnostic Tests . . . . . . . . O Testing Hypotheses about ˇ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 5 6 8 10 11 12 14 14 A Practical Matters 16 B A CLT in Action 17 2 . . . . . . . 21 21 22 25 25 28 35 36 The Distribution of a Sample Average Variance of a Sample Average . . . . . . . . . . . . . . . . . . . . . The Newey-West Estimator . . . . . . . . . . . . . . . . . . . . . . . 44 44 48 3 Univariate Time Series Analysis Theoretical Background to Time Series Processes Estimation of Autocovariances . . . . . . . . . . White Noise . . . . . . . . . . . . . . . . . . . . Moving Average . . . . . . . . . . . . . . . . . Autoregression . . . . . . . . . . . . . . . . . . ARMA Models . . . . . . . . . . . . . . . . . . Non-stationary Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 4 Least Squares Definition of the LS Estimator . . .