This course develops techniques necessary for the quantitative analysis of economics 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 applications 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.

Student who successfully complete this course will:

• have a greater understanding of the linear regression model beyond that covered in an introductory course;
• be introduced to binary choice models and to the nature of time series data and regression models on time series data;
• use computer software to employ the methods in applications.

• Assignments (40%)
• Final Exam (60%)

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

For further information please refer to course website