Skip to content
printicon

Econometrics I D12

  • Number of credits 7.5 Credits
  • Level Master’s level
  • Starting Autumn Term 2018

About the course

The course covers the fundamental tools in the econometrics of the linear and nonlinear regression models. Least squares estimation and hypothesis testing are studied in depth. The implications for estimation and inference of non-linearity, measurement error, multicollinearity, endogeneity, heteroskedasticity and autocorrelation are studied.

Application and eligibility

Econometrics I D12, 7.5 hp

Visa tillfällen för föregående termin Autumn Term 2018 Det finns inga senare terminer för kursen

Starts

Lectures begin on week starting 1 October 2018

Ends

Lectures end during the week of 5 November 2018

Study location

Umeå

Language

English

Type of studies

Daytime, 100%

Required Knowledge

90 ECTS of undergraduate courses in economics, whereof 30 ECTS on C-level (G2F). Proficiency in English equivalent to the Swedish upper secondary course English B/6. Mathematical Economics I D7 or the equivalent.

Selection

Academic Credits Applicants in some programs at Umeå University have guaranteed admission to this course. The number of places for a single course may therefore be limited.

Application code

UMU-23025

Application

The online application opens 15 March 2018 at 13:00 CET. Application deadline is 16 April 2018.

Application and Tuition fees

As a citizen of a country outside the European Union (EU), the European Economic Area (EEA) or Switzerland, you are required to pay application and tuition fees for studies at Umeå University.

Application fee

SEK900

Tuition fee, first instalment

SEK11,250

Total fee

SEK11,250

Contact us

Please be aware that the university is a state body and that what you write here can be included in a public document. Therefore, be careful if you are writing about sensitive or personal matters in this contact form. If you have a such an enquiry, please call us instead. All data will be treated in accordance with The Personal Data Act.