Econometrics Lecture Notes

Econometrics 2002 Paul Soderlind, University of St. Galen This course covers the basic empirical tools used to investigate economic behavior. It develops the classical regression model and its extensions, and demonstrates how to use these tools to investigate real world economic problems. It is a graduate course.

ECON 303: Mathematics for Economics Akila Weerapana, Wellesley College This is an upperlevel course designed for students who are interested in learning more about the use of mathematical techniques in economic analysis. Requires knowledge of calculus and linear algebra. It introduces economic applications using difference and differential equations as well as the basics of dynamic optimization.

ECON 251  Mathematical Economics II Daniel Rondeau, University of Victoria The objective of the course is to prepare students for the study of advanced economics topics in which time becomes an important dimension (e.g. macroeconomic theory, natural resource economics, time series analysis). The course is concerned with the fundamental mathematical methods of economic dynamics: Integration, Difference Equations, Differential Equations, Complex Numbers, Systems of differential
equations and Optimal Control.

Economics 2500: Introductory Statistics for Economists Barry Smith, York University This an introductory guide to statistics in economics for graduate students.

Econ 5336: Introduction to Econometric Analysis Craig A. Depken, University of Texas at Arlington This course covers the basic empirical tools used to investigate economic behavior. It develops the classical regression model and its extensions, and demonstrates how to use these tools to investigate real world economic problems. It is a graduate course.

HyperMetrics Christopher Ferrall, Queens University at Kingston These course notes cover the full array of econometrics topics at varying levels. They also include a glossary of terms.

Graduate Econometrics I Bruce E. Hansen, University of Wisconsin These are lecture notes written for a firstyear Ph.D. course in econometrics.

Econometrics Lecture Notes Andrew J. Buck, Temple University These lectures are for use in a 2 semester econometrics sequence at the graduate level.

B30.3351: Econometrics I William Greene, Stern School of Business, NYU This is an intermediate level, Ph.D. course in Applied Econometrics. Topics to be studied include specification, estimation, and inference in the context of models that include then extend beyond the standard linear multiple regression framework.

Econ 671: Econometrics I Arne Hallam, Iowa State University This course is the first part of the standard graduate curriculum in econometrics. The course provides a systematic approach to econometric theory and techniques associated with single and multiple equation models.
