Review of conditional distributions, expectation, regression and principles of inference. Linear regression models, ordinary and generalised least squares, heteroscedasticity. Non-linear least squares. Hypothesis testing and confidence intervals. Maximum likelihood estimation and testing. Introduction to models and methods for discrete and censored data. Simultaneity, exogeneity, instrumental variables methods. Dynamic models: autoregressive and moving average processes, vector autoregressions. Causality, stationarity, unit root tests, and cointegration. Introduction to panel data methods and models. Prerequisite(s): None

Upon completion of this course, the students will be able to: 1. understand the role data analysis in economic analysis; 2. be familiar with modern methods in data analysis; and 3. be prepared for writing empirical papers in economics.