About the programme


Mode of study and length of the programme in years: Full-time, 4 years

Length of the degree programme in ECTS credits: 240 credit

Language(s) of instruction: Lithuanian/ English

Degree and/or Qualification awarded: Bachelor of Mathematical Sciences


Econometrics combines economical theory and mathematical statistical methods, looking for links between economic objects and processes. One of the most demanded ability on todays job market is  to construct mathematical-statistical models to analyze a wide range of data in the Information Technology Age. Econometrics analyzes the relationships between economical objects and processes using empirical data. For this purposes Econometrics develop new special methods. This is why Econometrics take place  between fields of science: Economics nad Mathematics.

It's worth studying because:

  • Specialists in this field are in particular demand both in Lithuania and abroad.
  • Possibility to work with the latest data provided by Statistics department of Lithuania.
  • Learn from academic and business representatives.
  • Possibility of internships in Lithuanian and foreign institutions or companies.

Career opportunities:

Graduates of the program may work in public institutions (Central bank of the Republic of Lithuania, Ministries of the Republic of Lithuania, Department of Statistics of Lithuania, etc.) and private institutions (market research companies, insurance companies, banks, etc.) as Data and Market Analysts.

International studies and internship opportunities:

Vilnius University encourages the use of various opportunities for studying at foreign universities, allowing students to gain intercultural experience, develop and evaluate their competences, establish contacts abroad, and open wider career opportunities.

Study plan

Course title

Credits

Course title

Credits

1 SEMESTER

30.0

6 SEMESTER

30.0

Compulsary Modules

 

Compulsary Modules

 

Basics of Mathematics

5.0

Discrete Choice Models

5.0

Algebra I

5.0

Behavioural Economics

5.0

Informatics

10.0

Time Series Data

5.0

Introduction to Econometrics Studies

5.0

Markov Processes

5.0

Foreign Language

5.0

GUS*

5.0

 

 

Optional Modules

 

2 SEMESTER

30.0

Elective course units from the list:

 

Compulsary Modules

 

Statistical Modeling

5.0

Mathematical Analysis I

10.0

Sampling Methods

5.0

Algebra II

5.0

Risk Management

5.0

Research Data Analysis

5.0

Statistical Data Theory

5.0

Discrete Mathematics

5.0

 

 

Basics of DVBS

5.0

7 SEMESTER

 

 

 

Compulsary Modules

15.0

3 SEMESTER

30.0

Financial Econometrics Modeling

5.0

Compulsary Modules

 

Macroeconometrics

5.0

Mathematical Analysis II

10.0

Operation Research

5.0

Probability Theory 5.0 Optional Modules 15.0
    Elective course units from the list:  

Microeconomics

5.0

Queueing Theory

5.0

Practical Econometrics with R and Phyton I

5.0

Functional Data Statistics

5.0

GUS*

5.0

Censored Sampling Analysis

5.0

 

 

Numerical Methods

5.0

4 SEMESTRAS

30.0

Public Finance

5.0

Compulsary Modules

     

Stochastic Processes

5.0

 

 

Statistics

5.0

 

 

Data Visualization

10.0

8 SEMESTER

30.0

Practical Econometrics with R and Phyton II

5.0

Compulsary modules

 

Macroeconomics

5.0

Professional Internship

15.0

 

 

Bachelor's Thesis

15.0

 

 

 

 

5 SEMESTER

 30.0

 

 

Compulsary Modules

15.0

 

 

Regression Models

5.0

 

 

Financial Economics

5.0

 

 

Econometris  Project – Course Work

5.0

 

 

GUS

5.0

 

 

Optional course units

10.0

 

 

Elective course units from the list:

 

 

 

Data Tidying and Transformation with R

5.0

 

 

Numerical Methods

5.0

 

 

Categorical Data Analysis

5.0

 

 
Dynamic Systems 5.0    

 

GUS* -  General University Studies. Developed competences depend on the subject chosen by a student.

Expected Learning Outcomes:

  • collect, analyse and interpret information independently, develop ideas and argue critically them;
  • apply the knowledge obtained in economics and statistics for the development of the econometric projects;
  • apply specialized computer programs (R, EVIEWS, GRETL) for data analysis;
  • understand and explain to others the importance of statistical information and its relevance in the modern world;
  • choose an appropriate statistical test for hypothesis testing;
  • make linear regression models, structural and reduced vector models, estimate their parameters, test hypothesis for parameters, interpret the results obtained and apply these results in practice;
  • apply time series models (ARIMA, GARCH, VECM) for real data, estimate their parameters, interpret the results obtained and apply those models in practice;
  • demonstrate knowledge of the principles, concepts and models of microeconomics and macroeconomics;
  • understand economic processes and critically evaluate the laws of economic;
  • analyse the main principles of modelling of mathematical economics and interpret them.

Contacts

Do you have any questions? Contact:

  • Email:
  • Phone: +370 5 219 3055
  • Address: Naugarduko str. 24, room 106, Vilnius, Lithuania