EIE311 Real Estate Development, Economic Analysis and Valuation
Credits (ECTS):10
Course responsible:Sølve Bærug
Campus / Online:Taught campus Ås
Teaching language:Norsk
Limits of class size:None
Course frequency:Annually
Nominal workload:Ca. 40 hours of lectures and common supervision. Ca. 210 hours of self study or study in groups.
Teaching and exam period:This course starts in Autumn parallel. This course has teaching/evaluation in Autumn parallel
About this course
Introduction to DCF og NPV. Discount rates, Advanced micro-level valuation. Leverage and financing in practice. Real estate portefolios. Real options and land value. Leases and leasing strategy.
Learning outcome
Knowledge:
After completed course, the student should have knowledge on:
- tax and duties on commercial real estate
- characteristics of real estate leasing market
- development cost estimates
- commercial real estate profits
- investment value of commercial real estate and development projects
- the concepts of commercial real estate and real estate valuation
- the norwegian and english terminology of commercial real estate and real estate valuation of commercial real estate
- international valuation standards
- basic urban economics
- deep understanding of the risk and profits relation
Skills:
After completed course, the student should be able to:
- perform advanced economic analysis of real estate development projects
- perform advanced economic analysis in spreadsheets
- calculate shifts by the 4Q model
- efficiently search large information sets
General qualifications:
After completed course, the student
- knows the current practice in the Norwegian real estate business
- can extract relevant information from real estate business news
- can reflect on the ethical aspects of real estate development
- can reflect on the connection between economic estimates, real estate development and UN sustainable development goal 12
- can reflect on the connection between economic estimates, real estate development and innovation
- Learning activities
- Teaching support
- Syllabus
- Prerequisites
- Recommended prerequisites
- Assessment method
- About use of AI
- Examiner scheme
- Mandatory activity
- Teaching hours
- Preferential right
- Admission requirements