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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: Paul.Soderlind@unisg.ch. Document name: EcmAll.TeX. Contents 1 Introduction 1.1 Means and Standard Deviation 1.2 Testing Sample Means . . . . 1.3 Covariance and Correlation . . 1.4 Least Squares . . . . . . . . . 1.5 Maximum Likelihood . . . . . O 1.6 The Distribution of ˇ . . . . . 1.7 Diagnostic Tests . . . . . . . . O 1.8 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 3.1 Variance of a Sample Average . . . . . . . . . . . . . . . . . . . . . 3.2 The Newey-West Estimator . . . . . . . . . . . . . . . . . . . . . . . 44 44 48 3 Univariate Time Series Analysis 2.1 Theoretical Background to Time Series Processes 2.2 Estimation of Autocovariances . . . . . . . . . . 2.3 White Noise . . . . . . . . . . . . . . . . . . . . 2.4 Moving Average . . . . . . . . . . . . . . . . . 2.5 Autoregression . . . . . . . . . . . . . . . . . . 2.6 ARMA Models . . . . . . . . . . . . . . . . . . 2.7 Non-stationary Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 3.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 4 Least Squares 4.1 Definition of the LS Estimator . . .