Economics C: Analysis of Economic Data
Course, Bachelor's level, 2NE775
Expand the information below to show details on how to apply and entry requirements.
Autumn 2026 Autumn 2026, Uppsala, 50%, On-campus, Swedish Only available as part of a course package
- Location
- Uppsala
- Pace of study
- 50%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 31 August 2026–3 November 2026
- Language of instruction
- Swedish
- Entry requirements
-
At least 52.5 credits from Economics A and B and 15 credits in statistics or mathematics.
- Application deadline
- 15 April 2026
Admitted or on the waiting list?
- Registration period
- 28 July 2026–24 August 2026
- Information on registration from the department
Expand the information below to show details on how to apply and entry requirements.
Spring 2027 Spring 2027, Uppsala, 50%, On-campus, Swedish Only available as part of a course package
- Location
- Uppsala
- Pace of study
- 50%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 18 January 2027–24 March 2027
- Language of instruction
- Swedish
- Entry requirements
-
At least 52.5 credits from Economics A and B and 15 credits in statistics or mathematics.
- Application deadline
- 15 October 2026
Admitted or on the waiting list?
About the course
The course will cover tools and concepts that are widely used in economic and many other social science studies as well as within a large number of professional areas such as public administration, financial analysis, and marketing. The course focuses on the analysis of cross-sectional data and the concepts, intuition and software skills needed to independently perform and interpret results from a multiple regression analysis.
The statistical methods and concepts covered include multiple regression analysis with continuous, dummy, and interaction variables, t- and F-tests, and omitted variable bias. The course also introduces you to the intuition behind more advanced statistical methods commonly used in economics to isolate causal effects, such as instrumental variable methods. The discussed methods are applied to real-world data with the use of the statistical software Stata.
Reading list
- Reading list valid from Autumn 2026
- Reading list valid from Spring 2025
- Reading list valid from Autumn 2024
- Reading list valid from Spring 2024
- Reading list valid from Spring 2021
- Reading list valid from Spring 2017
- Reading list valid from Autumn 2016
- Reading list valid from Autumn 2015
- Reading list valid from Spring 2015
- Reading list valid from Autumn 2014
- Reading list valid from Spring 2014
- Reading list valid from Spring 2012