Advanced Econometrics

7.5 credits

Course, Master's level, 2ST123

Expand the information below to show details on how to apply and entry requirements.

Location
Uppsala
Pace of study
50%
Teaching form
On-campus
Instructional time
Daytime
Study period
19 January 2026–23 March 2026
Language of instruction
English
Entry requirements

120 credits including 90 credits in statistics, or 120 credits including 60 credits in statistics and 30 credits in mathematics and/or computer science.

Selection

Higher education credits (maximum 285 credits)

Fees
If you are not a citizen of a European Union (EU) or European Economic Area (EEA) country, or Switzerland, you are required to pay application and tuition fees.
  • First tuition fee instalment: SEK 12,500
  • Total tuition fee: SEK 12,500

Read more about fees.

Application deadline
15 October 2025
Application code
UU-76629

Admitted or on the waiting list?

Registration period
18 December 2025–18 January 2026
Information on registration from the department

Expand the information below to show details on how to apply and entry requirements.

Location
Uppsala
Pace of study
50%
Teaching form
On-campus
Instructional time
Daytime
Study period
18 January 2027–24 March 2027
Language of instruction
English
Entry requirements

120 credits including 90 credits in statistics, or 120 credits including 60 credits in statistics and 30 credits in mathematics and/or computer science.

Selection

Higher education credits (maximum 285 credits)

Fees
If you are not a citizen of a European Union (EU) or European Economic Area (EEA) country, or Switzerland, you are required to pay application and tuition fees.
  • First tuition fee instalment: SEK 15,750
  • Total tuition fee: SEK 15,750

Read more about fees.

Application deadline
15 October 2026
Application code
UU-76629

Admitted or on the waiting list?

Registration period
21 December 2026–11 January 2027
Information on registration from the department

About the course

The course is an advanced course in econometrics focusing on regression analysis and its mathematical foundations for the purpose of a complete understanding. The course focus on theory aiming at solid knowledge of how to model empirical data appropriately when it comes to estimation methods and inferential procedures in relation to assumptions.

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