[Forside] [Hovedområder] [Perioder] [Udannelser] [Alle kurser på en side]
The objectives of the course are that the participants can:
• formulate the multiple linear regression model and its underlying assumptions in matrix form
• estimate and interpret the parameters of multiple linear regressions
• describe the statistical properties of the estimated parameters
• apply hypothesis testing concerning the parameters of multiple regression models
• apply the estimated regression model to compute forecasts and to interpret the precision of these forecasts
• describe the consequences of multicollinearity, omitted variables, functional form misspecification,
heteroskedasticity and autocorrelation in multiple regression models
• evaluate the adequacy of the estimated regression models by performing test for omitted variables, functional
form misspecification as well as neglected heteroskedasticity and autocorrelation
• apply efficient estimation in regression models with heteroskedastic innovations
• interpret and evaluate autocorrelation and heteroskedastic consistent statistics
• apply statistical inference in dynamic multiple regressions.
The course introduces the students to regression analysis and teaches them to apply basic statistical techniques to estimate key parameters in economic models for describing economic and operational relations. The course lso covers use of various databases and statistical software, including PcGive and GiveWin for analysis of
macroeconomic issues.
• Regression analysis with several explanatory variables.
• Model estimation and specification.
• Hypothesis testing in multiple regressions.
• Partial regression.
• Functional form, dummy variables and parameter stability.
• Heteroskedasticity.
• Autocorrelation and dynamic regression models.
REQUIRED COURSES: 2030: MiMaSt (Micro, Mathematics, Statistics)
Christos Ntantamis
The lectures will cover various theoretical topics as well as empirical illustrations. The software package Eviews will be used extensively in the lectures throughout the course.
English
The total number of pages of required reading for the course equals approximately 350.
FORM OF ASSESSMENT:
A 4-hour written exam jointly with Surveys and Qualitative Data. Students who are not taking Surveys and Qualitative Data will only take a 2 hour-written exam in Regression Analysis. An approved obligatory assignment is a requirement to take the exam.
The obligatory assignment will be handed out and solved during the last week of the course. The obligatory assignment can be solved in groups of up to 4 persons.
EXAMINATION AIDS ALLOWED: All - except any means of electronic communication including PCs. A simple calculator will be available for the students in the examination hall.