EPN-V2

ØASØK4400 Behavioral Economics Course description

Course name in Norwegian
Behavioral Economics
Study programme
Master Programme in Business Administration
Weight
10.0 ECTS
Year of study
2022/2023
Curriculum
SPRING 2023
Schedule
Course history

Introduction

Behavioral economics uses empirical insights from psychology and other fields (such as sociology or neuroscience) in economic analysis. Conventionally, economics assumes that people are "economically rational": they make logically consistent choices in their best self-interest. Of course, sometimes people don't behave that way. Behavioral economics broadens the reach of economic analysis to situations in which people unselfishly contribute to the common good (like giving to the Red Cross), regret a choice (such as eating a candy bar instead of an apple), or make errors in judgement (for example, assign too much weight to highly unlikely events such as a lightning strike). Economic policies can look very different when people exhibit these kinds of behavior.

Required preliminary courses

None.

Learning outcomes

After completing the course, students will acquired the learning outcomes defined in knowledge, skills and general competence:

Knowledge

Students have specialized insight into:

  • How people's decision making processes can fail to match economically rational predictions: context dependence and heuristics leading to systematic biases (for example framing effects, reference dependence and loss aversion)
  • How behavioral models of people's uncertainty preferences can match some observed behavior (for example certainty effects, Allais paradox, Rabin's paradox) better than expected utility theory (for example prospect theory, disappointment and regret aversion)
  • How behavioral models of people's time preferences can match some observed behavior (for example demand for commitment devices, self-control issues) better than discounted utility theory (for example quasi-hyperbolic discounting, habit formation)
  • How behavioral models of people's social preferences can match some observed behavior (for example charitable giving, voluntary adherence to social distancing at high personal cost) better than the standard assumption of pure self-interest (for example inequality aversion, reciprocity, social norms).

Skills

The students can:

  • Create and analyze empirical evidence, often from experiments and games, for behavior that does not adhere to "economic rationality".
  • Model behavioral preferences and decision processes to analyze economic decision making.
  • Critically assess the limitations of behavioral economics, for example excessive paternalism or the lack of a clear welfare criterion.

Teaching and learning methods

Lectures with active student participation.

Course requirements

In order to be able to register for the exam, the student must have the following approved work requirements:

Three;written assignments, individually or in groups. The scope of the assignment (number of pages) varies depending on the nature of the assignment.;

If the assignments are not approved, the student will be given one opportunity to submit a new or improved version. The lecturer will provide more detailed information about deadlines for submission.

Assessment

Written school exam (4 hours).

Permitted exam materials and equipment

Emnet handler om numerisk simulering av fysiske problemer og vitenskapelig visualisering av simuleringsresultater. Studenten vil lære om forskjellen på simuleringsteknikker (inkludert endelig elementmetoder, endelig differanse, endelig volum) og deres anvendelsesområder knyttet opp til konserveringslover. Videre vil emnet gå inn på vitenskapelig visualisering av simuleringsresultater Studenten lærer om utvikling av simuleringskode, visualisering av resultater, samt interaktiv simulering.

Grading scale

Ingen ut over opptakskrav.

Examiners

Etter å ha gjennomført dette emnet har studenten følgende læringsutbytte, definert i kunnskap, ferdigheter og generell kompetanse.

Kunnskap

Studenten kan:

  • Forklare oppbygning og hensikt med numerisk simulering
  • Gjøre rede for verifikasjon av simuleringsresultater.
  • Gjøre rede for forskjellige typer grid, forskjellige typer beregningsskjemaer, samt hva slags type data en simulering produserer.
  • Gjøre rede for sentrale teknikker, konsepter og utfordringer innenfor vitenskapelig visualisering, inkludert skalarfeltvisualisering, vektorvisualisering, tidsavhengig visualisering, to- og tre-dimensjonal visualisering.
  • Forklare og sammenlikne kjøretid og ressursbruk for forskjellige simuleringsteknikker.

Ferdigheter

Studenten kan:

  • Skrive kildekode / program som kan simulere enkle differensiallikninger.
  • Vitenskapelig visualisering av forskjellige typer data (skalar, vektor, tensor, og tidsavhengige)
  • Bruke både egenutviklede og standardiserte verktøy til å løse sammensatte og kompliserte problemer

Generell kompetanse

Studenten kan:

  • delta i diskusjoner og gi råd om hvilke typer grid, beregningsskjemaer, og visualiseringsteknikker det er mest hensiktsmessig å bruke i ulike situasjoner.
  • identifisere når og hvordan det er mest hensiktsmessig å bruke numerisk simulering og vitenskapelig visualisering for fysiske og ingeniørrettede problemstillinger.
  • analysere når en simuleringskode fungerer og gir forventede resultater, og når resultatene er feil.