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Only for plus members Get exciting benefits. Introduction to Econometrics is the ideal text for anyone new to econometrics. This text has been revised and updated throughout to be even more accessible and comprehensive than ever before. More practical exercises give you hands-on experience meaning you can practise what you've learnt, and step-by-step explanations of mathematical proofs help you develop a full appreciation of the material.

Harold Hitchings Burbank Professor of Political Economy

Instead, it builds on the excellent and popular textbook " Introductory Econometrics " by Jeffrey M. Some other editions and versions work as well, see below. It is compatible in terms of topics, organization, terminology and notation, and is designed for a seamless transition from theory to practice.

Topics include:. A gentle introduction to R Simple and multiple regression in matrix form and using black box routines Inference in small samples and asymptotics Monte Carlo simulations Heteroscedasticity Time series regression Pooled cross-sections and panel data Instrumental variables and two-stage least squares Simultaneous equation models Limited dependent variables: binary, count data, censoring, truncation, and sample selection Formatted reports and research papers combining R with R Markdown or LaTeX.

Assuming the reader is familiar with the concepts discussed there, this book explains and demonstrates how to implement everything in R and replicates many textbook examples.


We also open some black boxes of the built-in functions for estimation and inference by directly applying the formulas known from the textbook to reproduce the results. Course Objective By the end of this course students will have had an introduction to modern econometric techniques, that will enable them to conduct methodological or empirical analyses of their own. In particular, students will be familiar with both econometric theory and with real-world applications in macroeconomics, finance and business. Course Content A review will be given of estimation and testing in the linear cross-sectional regression model. We will discuss the classical assumptions, and the consequences arising when these assumptions are not fulfilled.

Throughout the course, the focus will lie on developing an intuition for state-of-the-art econometric concepts.

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