Course code:  EKM1A 
Course title in language of instruction:  Econometrics 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) 
Language of instruction:  English 
Level of course:  bachelor 
Semester:  SS 2019/2020 
Name of lecturer:  doc. Ing. Václav Adamec, Ph.D. (examiner, instructor, lecturer, supervisor) 
Prerequisites:  Statistics or 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 Econometry (allowance 1/0)   a.  Definition of Econometry, 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  b.  Ordinary Least Squares method (OLS)  c.  Error term, residuals  d.  Analysis of variance (ANOVA)  e.  Correlation analysis 
 3.  Statistical hypothesis testing, confidence intervals. (allowance 2/4)   a.  Tests of significance for regression coefficients (ttests) and test of overall model significance (Ftest)  b.  Tests of model specification, nonlinearity test and RESET test  c.  Confidence interval for regression coefficients  d.  Confidence interval and prediction interval for the model  e.  Testing coefficient of correlation 
 4.  GaussMarkov theorem, classical model assumptions (allowance 2/4)   a.  Classical assumptions  b.  Properties of OLS estimator 
 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 econometry (allowance 0/4)   a.  Student presentations, discussion 



Learning outcomes and competences: 
Generic competences:     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    Constructing a statistical model for real econometric data    Understanding the methods to describe relationship between two economic variables    Understanding the principles of constructing econometric model 


Type of course unit:  required 
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  Direct teaching  lecture  14 h  practice  28 h  Selfstudy  preparation for exam  58 h  preparation for regular testing  15 h  preparation of presentation  5 h  writing of seminar paper  20 h  Total  140 h 


Assessment methods: 
A credit is granted on the basis of group project (>= 50% score), midterm exam (score at least 50%) and active participation in labs (at most 2 missed labs). Active lab participation is further assessed by 1 point per lab. Credit is required for admission to the final exam. Passing final exam requires at least 50% score. Course grade is made on the basis of the final exam, midterm exam, project and active participation: A [91 – 100]; B [82 – 91); C [73 – 82); D [64 – 73); E [55 – 64); F [0 – 55). The examiner may adjust the grade by 1 step in both directions. The course cannot be taken during overseas internship.


Recommended reading: 
Type  Author  Title  Published in  Publisher  Year  ISBN 

RQ  GUJARATI, D N.  PORTER, D C.  Basic econometrics  Boston  McGrawHill Irwin   9780071276252  RQ  ASHENFELTER, O.  LEVINE, P B.  ZIMMERMAN, D J.  Statistics and econometrics : methods and applications  New York  John Wiley & Sons  2003  0471107875  RQ  WOOLDRIDGE, J M.  Introductory econometrics: a modern approach  Mason, Ohio  SouthWestern  2008  9780324660548  RE  KMENTA, J.  Elements of econometrics  Ann Arbor  University of Michigan Press  2011  0472108867  RE   Using econometrics: a practical guide  Boston  Addison Wesley Pearson   0321316495 
