Course code:  EKM1 
Course title in language of instruction:  Ekonometrie I 
Course title in Czech:  Econometrics I 
Course title in English:  Econometrics I 
Mode of completion and number of credits:  Exam (5 credits) (1 ECTS credit = 28 hours of workload) 
Mode of delivery/Timetabled classes:  fulltime, 1/2 (hours of lectures per week / hours of seminars per week) parttime, 16/0 (lectures per period / seminars per period) 
Language of instruction:  Czech 
Level of course:  bachelor 
Semester:  WS 2017/2018 
Name of lecturer:  doc. Ing. Luboš Střelec, Ph.D. (examiner, supervisor) 
Prerequisites:  Statistics 

Aims of the course: 
Obtaining theoretical knowledge and practical experience with construction of basic econometric models based on linear regression and models of univariate time series. Students are able to evaluate the econometric models, interpret in economic context and apply for predictions. Students can apply statistical software. Knowledge and skills learned in this course are expected to be used during work on student bachelor's thesis. 

Course contents: 
1.  Introduction to Econometrics (allowance 1/0)   a.  Definition of Econometrics, evolution and history  b.  Basic steps of econometric analysis  c.  Econometric data types 
 2.  Regression and correlation analysis, error term (allowance 4/6)   a.  Regression analysis, regression model, variables in regression model  b.  Ordinary Least Squares (OLS)  c.  Fits, residuals  d.  Decomposition of variability, coefficient of determination, information criteria  e.  Analysis of variance (ANOVA)  f.  Correlation analysis, pairwise, multiple and partial coefficient of correlation 
 3.  Testing statistical hypotheses, confidence intervals (allowance 2/4)   a.  Tests of significance for regression coefficients (ttests) and test of overall model significance (Ftest)  b.  Confidence interval for regression coefficients  c.  Confidence interval and prediction interval for the model  d.  Significance test of correlation coefficient  e.  Tests of model specification, LM test of specification and RESET test 
 4.  GaussMarkov theorem, classical model assumptions (allowance 2/4)   a.  Classical assumptions and methods of verification  b.  Properties of OLS estimator under GaussMarkov theorem  c.  Violations of classical requirements, consequences for the model 
 5.  Introduction to time series analysis (allowance 1/2)   a.  Time series data, definition, properties, types  b.  Time series dynamics 
 6.  Models of time series (allowance 4/8)   a.  Qualitative (expert) methods  b.  Moving averages, exponential filters  c.  Time series decomposition  d.  Modeling seasonality  e.  Models based on filters  f.  Causal regression models  g.  Criteria of model fit 
 7.  Applied econometrics (allowance 0/4)   a.  Student presentations, discussion 



Learning outcomes and competences: 
Generic competences:     ability to analyse and synthesize    ability to apply knowledge    basic computing skills    science and research skills    skilled at utilizing and processing information    work in team 
 Specific competences:     Ability to apply the principles of constructing model of univariate time series    Ability to build econometric model on crosssectional economic data.    Understanding the principles of constructing econometric models    Understanding the statistical methods to describe relationship between two economic variables. 


Type of course unit:  optional 
Year of study:  Not applicable  the subject could be chosen at anytime during the course of the programme. 
Work placement:  There is no compulsory work placement in the course unit. 
Recommended study modules:   

Learning activities and study load (hours of study load): 
Type of teaching method  Daily attendance  Combined form  Direct teaching  lecture  14 h  16 h  practice  28 h  0 h  Selfstudy  preparation for exam  53 h  78 h  preparation for regular testing  15 h  0 h  preparation of presentation  5 h  0 h  writing of seminar paper  25 h  46 h  Total  140 h  140 h 


Assessment methods: 
Midterm exam (50 minutes) is held after regression and correlation material is completed (minimum 60% score is required to pass). Written report of the semester project (1622 pages) is due at the end of the semester. PowerPoint presentations of the project are planned before the class. The project is graded on pass  fail basis. Course grade is primarily based on written final exam (60 minutes) covering realworld problems and answering theoretical questions. Minimum 55% score is required to receive a passing grade. 

Recommended reading: 
Type  Author  Title  Published in  Publisher  Year  ISBN 

RQ  ADAMEC, V.  STŘELEC, L.  HAMPEL, D.  Ekonometrie I: učební text     9788073757038  RQ  ADAMEC, V.  STŘELEC, L.  Ekonometrie I: cvičebnice  Brno  Mendelova univerzita v Brně  2013  9788073757069  RE  GUJARATI, D N.  PORTER, D C.  Basic econometrics  Boston  McGrawHill Irwin   9780071276252  RE  HAMPEL, D.  BLAŠKOVÁ, V.  STŘELEC, L.  Ekonometrie 2  Brno  Mendelova univerzita v Brně  2012  9788073756642  RE  HINDLS, R. et al.  Statistika pro ekonomy  Praha  Professional publishing  2006  8086946169  RE  HUŠEK, R.  PELIKÁN, J.  Aplikovaná ekonometrie: teorie a praxe  Praha  Professional Publishing  2003  8086419290  RE  MAREK, L. et al.  Statistika pro ekonomy: aplikace  Praha  Professional Publishing  2007  9788086946405 
