Econometrics
BASIC DATA
course listing
A - main register
course code
MEC9080
course title in Estonian
Ökonomeetria
course title in English
Econometrics
course volume CP
-
ECTS credits
6.00
to be declared
yes
assessment form
Examination
teaching semester
autumn
language of instruction
Estonian
English
Study programmes that contain the course
code of the study programme version
course compulsory
MAXD22/22
yes
Structural units teaching the course
ME - Department of Economics and Finance
Course description link
Timetable link
View the timetable
Version:
VERSION SPECIFIC DATA
course aims in Estonian
Õppeaine põhieesmärgiks on arendada ökonomeetria meetodite kasutamise oskusi majandusprobleemide lahendamiseks, majandusteoreetiliste kontseptsioonide ja hüpoteeside kontrollimiseks. Lisaks arendada üliõpilaste empiirilise uurimustöö kogemusi, kasutades selleks sobivat tarkvara.
course aims in English
The first objective is to increase the breadth of students understanding of econometrics methods and to develop students’ skills of model building and testing. The second objective is to get students familiar with the art of conducting empirical work in econometrics through the use of suitable computational software.
learning outcomes in the course in Est.
Üliõpilane oskab erinevate andmetüüpide korral valida sobivat ökonomeetrilist mudelit; viia läbi mudeli parameetrite hindamist, kasutades selleks sobivat tarkvara; hinnata mudelite kirjeldusvõimet ja võrrelda erinevaid mudeleid, kasutades selleks sobivalt valitud suurusi ning interpreteerida ökonomeetrilise analüüsi tulemusi.
learning outcomes in the course in Eng.
After completing the course it is expected that the student is able to: 1) Reflect about the appropriate choice of estimator given certain types of data such as time series data, panel data, and data with a binary dependent variable. 2) Formulate and estimate econometric models based on different data sets such as cross-sections, time series and panel data. 3) Interpret outcomes of econometric analyses and draw appropriate conclusions.
brief description of the course in Estonian
Hinnangute põhiomadused. Suurima tõepära meetod. Binaarse ja binomiaalse funktsioonitunnusega mudelid. Logistiline regressioonanalüüs. Logit, probit ja tobitmudel. Mudeli kirjeldusvõime hindamine, testimine. Paneelandmed, nende eelised ja probleemid. Lineaarsed paneelandmete mudelid. Fikseeritud efektiga mudel. Juhusliku efektiga mudel. Testimine. Simultaansete võrranditega mudelid. Struktuursete võrrandite identifitseerimine. Simultaansete mudelite lahendamine. Modelleerimise metodoloogia. Mudeli spetsifikatsioonivead ja nende testimine. Mudeli valiku kriteeriumid.
brief description of the course in English
Properties of Estimators. Maximum Likelihood Estimation. Qualitative Response Models. The Linear Probability Model. Binary Choice Models: Logit and Probit. Multinomial Logit and Probit Models. Ordinal Logit and Probit Models. Models with Censored Variable. The Tobit Model. Panel Data Regression Models. Why panel Data? The Fixed Effects Approach. The Random Effects Approach. Simultaneous-Equation Models. The Identification Problem. Simultaneous-Equation Methods. Specification of econometric models and specification errors.
type of assessment in Estonian
Kirjalik eksam
type of assessment in English
Written exam
independent study in Estonian
Iseseisev töö kirjandusega, ülesannete lahendamine, õppejõu poolt soovitatud publikatsioonidega tutvumine, iseiseisev töö arvandmetega, (kasutades sobivat tarkvarapaketti).
independent study in English
Students will learn the topics, read research papers recommended by the teacher and do empirical research using the STATA program which is available in the computer lab.
study literature
Verbeek, Marno. A Guide to Modern Econometrics. Wiley, 2012.
Cameron, Colin A., Trivedi; Pravin K. Microeconometrics: Methods and Applications. Cambridge University Press, 2005.
Greene, William H. Econometric Analysis. Prentice Hall, 2003.
study forms and load
daytime study: weekly hours
4.0
session-based study work load (in a semester):
lectures
2.0
lectures
-
practices
0.0
practices
-
exercises
2.0
exercises
-
lecturer in charge
-
LECTURER SYLLABUS INFO
semester of studies
teaching lecturer / unit
language of instruction
Extended syllabus
2025/2026 autumn
Kadri Männasoo, ME - Department of Economics and Finance
English
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    2023/2024 spring
    Kadri Männasoo, ME - Department of Economics and Finance
    English
      2023/2024 autumn
      Kadri Männasoo, ME - Department of Economics and Finance
      English
        2019/2020 spring
        Kadri Männasoo, ME - Department of Economics and Finance
        English
          MEC9080_Econometrics.pdf 
          Course description in Estonian
          Course description in English