This course develops techniques necessary for the quantitative analysis of economic and business problems that are beyond the scope of the linear regression model. The course will deepen students understanding of the statistical foundations of econometrics. The course provides an introduction to estimation and hypothesis testing in non-linear models. It also examines model selection and specification analysis. Specific applicaitons may include discrete choice and limited dependent variable models, non-linear regression models, flexible functional forms, expectations formation and dynamic adjustment. Use of computer software provides the opportunity to employ the methods in application from actual economic and business case studies.

Upon successful completion of the requirements for this course, students will be able to:

• Understand, at an introductory level, the three main estimation methods used in econometrics:  least squares, maximum likelihood and generalized method of moments
• Understand, at an introductory level, the three main hypothesis testing approaches used in econometrics:  Wald, likelihood ratio and lagrange multiplier tests
• Apply these estimation and hypothesis testing strategies to a variety of linear and non-linear models
• Think clearly about the relationship between data, model and estimation in econometrics
• Use computer software to estimate and test econometric models

Assignments - 40%

Final Examination - 60%

10 Hours per week (including 3 hours of class time and 1 hour of computer lab/tutorial)

EMET2007 Econometrics I: Econometric Methods or STAT2008 Regression Modelling, and ECON1101 Microeconomics 1.

For further information please refer to course website