Examination arrangement

Course content

Part 1:

• Quantitative research designs. Measurement in the social sciences. Validity and reliability.
• Statistical principles. Estimation and hypothesis testing.
• T-tests, one and two samples. Analysis of variances ANOVA . F-tests. Simultaneous confidence intervals.
• The assumptions for the tests. Applications using modern statistical software.

Part 2:

• The classical multiple regression model.
• Ordinary least squares OLS. The classical assumptions. Gauss-Markov theorem.
• Hypothesis testing for the regression model: T-tests for the regression coefficients. F-test of overall significance. F-tests for multiple hypothesis.
• Correlation analysis. T-tests for the correlation coefficients.

Part 3:

• Violations of the classical OLS assumptions. Theory and applications.
• Specification. Choosing variables. Functional form. Ramsey RESET test for specification error.
• Nonlinear regression models. Logarithmic transformations. Log form. Polynomial form. Invers form. Use of dummy variables. Lagged variables.
• Multicollinearity. Consequences of multicollinearity. VIF indices.
• Serial correlation. Consequences of serial Correlation. Correlogram. Ljung-Box test. Lagrange Multiplier test. Durbin-Watson test. Newey-West standard errors. Generalized Least Squares GLS.
• Heteroskedasticity. Consequences of heteroskedasticity. Breusch-Pagan test. White test. Heteroskedasticity-Corrected standard errors. Weighted Least Squares WLS.

Part 4:

• Time-series models. Distributed lag models. Dynamic models. Autoregressive (AR) models. Spurious regression. Stationarity. Dickey-Fuller test.
• Dummy dependent variable techniques. The linear probability model. Logistic regression model.
• Simultaneous equations. The bias of OLS. Two-stage-Least squares.
• Panel data. Fixed versus random effects.
• Factor analysis. How to perform and interpret factor analysis.

Applications of statistical methods and econometrics within economic analysis, using modern statistical software.

The analytical software that will be used during the course will be announced at the start of the semester.

Reserve the right to make changes in academic content.

Learning outcome

Knowledge

The student:

• Has in-depth knowledge of quantitative research methodology in basic econometrics.
• Has knowledge of estimation and testing in the field of multiple regression analysis, and the classical assumptions. Deviations from the classical assumptions are discussed both theoretically and economically.
• Has knowledge of widely used multivariate techniques such as analysis of variance, correlation analysis, logistic regression analysis and exploratory factor analysis.
• Can interpret results of empirical analyzes and draw conclusions based on these and make qualified choices between different models.

Skills

The student can:

• Perform relevant statistical analyzes of economic data using modern statistical software.
• Interpret results of empirical analyzes and draw conclusions based on these analyzes.
• Be critical of modern statistical software results and present them professionally.

General competence

The student can:

• Apply their knowledge and skills in quantitative methodology and econometrics to economic issues. This is a basis for using statistical methods and understanding quantitative research articles in conjunction with the master thesis.
• Communicate statistical results critically and present the uncertainty of different statistical methods.

Learning methods and activities

Lectures and group work, where students work actively with applications of the various statistical methods in economic analysis, using modern analytical software. Exercises based on data sets from the various main profiles. Student assistants will guide in exercises. Candidates will work independently with both compulsory and voluntary exercises during the course.

Compulsory assignments

• Obligatorisk innlevering

Further on evaluation

Supporting material allowed on exams: Approved calculator in accordance with NTNUs support material code C "specific basic calculator". Other calculators that are allowed in the course are: Casio FC-100V, Casio FC-100V-2 and Texas Instruments - BAII Plus. Formula collection handed out at the exam. Admission to study programme is required, see "special conditions".

Note: students who attend the Master in Accounting and Auditing will have access to a postponed exam in August without any requirement of a valid due date or fail due to a potential need to achieve a C requirement in the course. These students must contact the department before the registration deadline of 9 July.

Specific conditions

Recommended previous knowledge

None

Required previous knowledge

None

Course materials

Curriculum will be announced at the start of the semester.