Econometrics 1

1. Introduction to econometrics
2. Classical linear multiple regression model
3. Hypothesis testing
4. Prediction with multiple regression model
5. Model specification and diagnostic testing
6. Model diagnostics
7. Regression models with dummy explanatory variables
8. Distributed-lag regression models

Pfajfar, L.: Osnovna ekonometrija: tretja izdaja. Ljubljana: Ekonomska fakulteta, 2022.
Verbič, M., L. Pfajfar in R. Rogelj: Ekonometrični obrazci in postopki: dopolnjena druga izdaja. Ljubljana: Ekonomska fakulteta, 2017.

• To improve and expand the knowledge of quantitative skills with basic econometric methods.
• To become acquainted with the theoretical fundations of econometric methods.
• To obtain the skills necessary for the application of theoretical concepts.
• To develop the capabilities of students to choose appropriate methodology for the analysis of relationships in finance.
• To develop capabilities of students for interpretation of the results.

The course expands and enriches the knowledge of contemporary quantitative methods for detection and analysis of financial developments. It is intended for comprehension of procedures for facing economic and financial theories with the data, i.e. for quantitative estimation and measurement of theoretical concepts. The expertise of basic econometric methods and procedures enables testing of numerous hypotheses based on economic and financial data. Quantitatively measured concepts can thus directly be used in analytic departments of institutes, banks, investment companies and other financial institutions, for facilitating economic decision-making in larger companies, and for concucting economic policies at all levels of the decision-making process. The knowledge of econometric methods is of key importance for graduate studies of finance and financial mathematics.

Lectures and exercise sessions are conducted according to the time schedule. The lecturer will provide students with knowledge of the fundamental theories and techniques at the lectures. Guided exercise sessions will be carried out in the computer room. The course will also enable consultations with the lecturer and self study in the computer room, in particular with the use of Internet (using statistical and econometric computer software, work with data bases, study guides on the Internet, looking through sets of slides in Econometrics).

Final written exam
Midterm exam

Miroslav Verbič:
VERBIČ, Miroslav, SATROVIC, Elma, MUSLIJA, Adnan. Environmental Kuznets curve in Southeastern Europe : the role of urbanization and energy consumption. Environmental science and pollution research. [Print ed.]. 2021, vol. 28, str. 57807-57817. ISSN 0944-1344. [COBISS-SI-ID 66289155]
DOMINKO, Miha, VERBIČ, Miroslav. The effect of income and wealth on subjective well-being in the context of different welfare state regimes. Journal of happiness studies. 2021, vol. 22, iss. 1, str. 181-206. ISSN 1389-4978. [COBISS-SI-ID 1954190]
HALUŽAN, Marko, VERBIČ, Miroslav, ZORIĆ, Jelena. Performance of alternative electricity price forecasting methods : findings from the Greek and Hungarian power exchanges. Applied energy. Nov. 2020, vol. 277, art. 115599, str. 1-15. ISSN 0306-2619. [COBISS-SI-ID 25225731]
SEVER, Ivan, VERBIČ, Miroslav, KLARIĆ SEVER, Eva. Cost attribute in health care DCEs : just adding another attribute or a trigger of change in the stated preferences?. Journal of choice modelling. 2019, vol. 32, art. 100135, 12 str., ilustr. ISSN 1755-5345. [COBISS-SI-ID 24438758]
SEVER, Ivan, VERBIČ, Miroslav. Providing information to respondents in complex choice studies : a survey on recreational trail preferences in an urban nature park. Landscape and urban planning. [Print ed.]. 2018, vol. 169, str. 160-177, ilustr. ISSN 0169-2046. [COBISS-SI-ID 1863054]