BASIC DESCRIPTION
Course coordinator
Course title
Study programme
Course status
Year
ECTS credits and teaching
Tea Baldigara, Ph.D., Associate Professor
Econometrics
Undergraduate university study: Business Administration in Tourism and
Hospitality
Elective
5th year, 8th semester, summer term
ECTS student ‘s workload coefficient
5,5 ECTSa
Number of hours (L+E+S)
(60)
COURSE DESCRIPTION
Course objectives
The course intends to develop student’s research competencies and enable students to understand the necessary tools
required for proper applied research. The emphasis is on practical problems of estimating and testing economic models in
tourism and hospitality areas. The course intent to develop general and specific competencies needed to relate economic
theory, statistical and mathematical methods with the purpose to extrapolate; econometrically model them, analyze, and
interpret information from empirical data linked to the tourism and hospitality industry.
Expected course learning outcomes
To make students capable for mathematical thinking and making quantity relations between economic variables on the basis of
economic theory and observed information with help of statistical methods. To teach students the basis of econometrics and to
apply the previous knowledge of mathematics, statistics and economic theory for modelling of economic processes and using
those models to make researches and analyze real economic systems and predict the effects of different measures of
economic policy. After passing the exam of the course of Econometrics (6 ECTS) students shall be able to:
 Correctly interpret and explain theoretical concepts of Econometrics and understand its nature;
 Estimate and interpret econometric models;
 Make economic forecasts;
 Critically understand journal articles, economic research papers;
 Use new econometrics’ theoretical and software achievements in applied model estimating and evaluating;
 Develop a critical perspective on the use of econometric analysis, be proficient in using an advanced econometric
package; and
 Be able to independently replicate econometric analyses of economic data.
Course content
Introduction to Econometrics: The nature and scope of Econometrics. The methodology of Econometrics.
The linear regression model: Basic ideas of linear regression. The population regression function and the sample regression
function. The two-variable model. The ordinary least square method. The properties of OLS estimators. The classical linear
regression model.
Multiple regression: The three variable linear regression model. Assumption of the multiple linear regression model. Estimation
and Hypothesis Testing.
Regression analysis in practice: the violation of the classical linear regression model: Multicolinearity. Heteroscedasticity.
Autocorrelation.
Intoroduction to time-series analysis: descriptive methods in time series analysis. Time series models. Smoothing methods.
Seasonality. Time series forecasting. Stochastic processes. Autocorrelation function and partial autocorrelation function.
Stationarity.
Assigned reading (at the time of proposing study programme)
1. Davidson, R., MacKinnon, J.G., (2004),Econometric theory and methods, Oxford University Press, New York, available at:
http://econ.queensu.ca/ETM/.
2. Zellener, A, Palm, C.F., (2004), The Structural Econometric Time Series Analysis Approach, The Press Syndicate of the University
Of Cambridge, available at: http://www.cambridge.org/aus/catalogue/catalogue.
Vujković, T., Ekonometrijske metode i tehnike(Econometric methods and techniques), Informator, Zagreb, 1976.
Optional / additional reading
3.
4.
5.
6.
Gujarati, D., Essentials of Econometrics, McGraw-Hill, Boston, 1992.
Maddala, G. S., Introduction to Econometrics, Macmillian Publishing Company, New York, 1992.
Cappuccio, N., Orsi, R., Econometria, Il Mulino, Bologna, 1991.
Woolddridge, J.M., Introductory Econometrics: A Modern Approach, South-Western College Publishing, Boston, 2000.