Spring 2027

Behavioral Economics

Behavioral Economics examines empirical departures from rational decision-making norms and alternative theories using psychological enrichments, covering topics like loss aversion and time-inconsistent preferences.

offering recorded3–4 credits
Recorded instructors · Spring 2027 Matt Friedman4.2/5

Summary

1 / 6

Past student reviews · Matt Friedman

One student estimated that the reading alone took at least five hours per week, noting that the assignments were extensive even if they rarely appeared on exams.

What you’ll be able to do

  • Describe several decision/search heuristics used by economic agents and explain their association with commonly observed cognitive biases

  • Use economic models to characterize and predict choices made by agents whose preferences diverge from the standard assumptions of rationality.

  • Apply behavioral economic theories to evaluate real-world decision-making scenarios using case studies and empirical data.

  • Critically assess the effectiveness of behavioral interventions in influencing decision-making.

  • Design, describe and/or implement a behavioral intervention aimed at addressing a real-world economic inefficiency, integrating insights from the academic literature.

Source: UW Guide

Grade history

↗
average GPA
letter grades
A
AB
B
BC
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All recorded terms · compare terms & instructors

Prerequisites

Course map

(ECON 301 or 311) and ECON 310; or graduate/professional standing

ECON 455

This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree

Professors

Spring 2027

Matt Friedman

Adjusted rating
RMP difficulty
captured reviews
About this rating

Raw average: 4.74/5 from 23 quality ratings. The adjusted rating blends this with the UW review average (3.66/5), weighted as 20 additional ratings. Smaller samples stay closer to that average. Each captured review is counted once in the prior; this does not correct who chooses to leave a review.

For this course: 4.8/5 raw quality · 3.4/5 difficulty · 13 reviews

RMP profile ↗ · All captured review dates; profile matched by name.

Past student reviews · Matt Friedman

Matt Friedman taught a heavy reading load that took five hours weekly, with weekly quizzes that were difficult but curved. Students noted that attendance and participation points were critical for passing, as the final exam relied heavily on definitions. While some found his lectures scattered or rambling, others described them as entertaining and engaging.

Recent recorded grades — Spring 2025: 3.04 GPA, 39.5% A/AB (n=81 letter grades); Fall 2025: 2.97 GPA, 34.0% A/AB (n=94 letter grades); Spring 2026: 3.19 GPA, 44.8% A/AB (n=87 letter grades).

Historical instructors & teaching patterns

Past student reviews · Matthew Friedman

Matt Friedman taught the course with engaging lectures and answered student questions in class. Students found the final exam easy and noted that quizzes and tests replicated practice problems, making preparation straightforward. Recent reviewers described the class as fun and recommended it highly.

ANDREA WILSON is recorded teaching in Spring 2015, Fall 2015, Spring 2016. Recorded history may be incomplete and does not establish a future schedule.

GWYN PAULEY is recorded teaching in Fall 2017, Spring 2018, Fall 2019, Spring 2020, Fall 2021. Recorded history may be incomplete and does not establish a future schedule.

MATTHEW FRIEDMAN is recorded teaching in Fall 2018, Spring 2019, Fall 2020, Spring 2022, Fall 2022, Spring 2023, Fall 2023, Spring 2024, Fall 2024, Spring 2025, Fall 2025, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.

Recorded history may be incomplete and does not establish a future schedule.

Calendar & sections

Spring 2027

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction0 / 960
DIS 301Classroom Instruction0 / 240
DIS 302Classroom Instruction0 / 240
DIS 303Classroom Instruction0 / 240
DIS 304Classroom Instruction0 / 240

Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.

Meeting source records
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Student experience

the class

Past student reviews · Matt Friedman

Students found the material relatable because it connects to daily life and current news, making the content easier to grasp than abstract concepts.

Recent recorded grades — Spring 2025: 3.04 GPA, 39.5% A/AB (n=81 letter grades); Fall 2025: 2.97 GPA, 34.0% A/AB (n=94 letter grades); Spring 2026: 3.19 GPA, 44.8% A/AB (n=87 letter grades).

difficulty & workload

Past student reviews · Matt Friedman

One student estimated that the reading alone took at least five hours per week, noting that the assignments were extensive even if they rarely appeared on exams.

Past student reviews · Matt Friedman

Weekly quizzes were described as difficult but heavily curved, while one student noted the final exam was primarily composed of definitions with minimal calculations.

Topics

  • Paradox of choice, loss aversion, time-inconsistent preferences, and social preferences
  • Decision and search heuristics associated with cognitive biases
  • Effectiveness of behavioral interventions

Skills

  • Describe decision heuristics and explain associations with cognitive biases
  • Use economic models to characterize and predict non-rational agent choices
  • Critically assess the effectiveness of behavioral interventions
  • Design or implement behavioral interventions for economic inefficiencies

Grades

Historical instructor

Spring 2027 · Projected

Before grades are released

– average GPA

Approximate 80% prediction interval

About this estimate

The course’s semester-average GPA, not an individual student’s grade. The center uses 5 same-season terms, weighted toward recent results.

The range uses the finite-sample 80th-percentile rank of absolute errors from earlier same-season forecasts. Each forecast uses only records from earlier terms. At least four forecasts are required; bounds are rounded outward and limited to 0–4. This is an empirical estimate: changing instructors or grading policies can reduce its coverage.

8 earlier forecasts · 0.19 GPA average error.

Grades over time

Through Spring 2027

More grade details Grade mix, volume & source data

Where this course fits relative to

Latest available grades · Spring 2026 · all course levels

GPA

Higher than % of other courses in this group.

Course GPAs · red marks this course’s range

letter grades

More recorded grades than % of other courses in this group.

Typical course in this group: letter grades.

About this comparison

1280 courses over the same term, each with at least 30 recorded letter grades. Cross-listed courses count once. GPA is not a measure of difficulty or teaching quality. The typical course is the median by recorded grade count; tied values are not counted as lower. Grade counts describe course scale, not unique students or typical section size.

Descriptions compare GPA with this group’s average: at least 0.20 higher or lower; otherwise close to average. Section size uses median recorded enrollment: small up to 30, mid-sized 31–99, large 100+. Lectures and discussion/lab sections are described separately.

Sources & history

UW–Madison

Catalog & offerings

Descriptions, prerequisites, and recorded course offerings.

Catalog observation history

Observations at scan time; dates do not imply when a catalog change took effect.

Download part 1
Selected offering source records
ECON 455 · Spring 2027

Behavioral Economics

Recorded 2026-10-14
Raw records 
[
  {
    "run_id": "20261014T203208-0851c9a1",
    "semester": "1274",
    "observed_at": "2026-10-14 17:50:09.728220+00:00",
    "offering_id": "1274:296:024198",
    "course_id": "ECON 455",
    "course_uid": "course_7bd7653c564300d23aa3d0da",
    "term_id": "1274",
    "source_course_id": "024198",
    "source_subject_id": "296",
    "title": "Behavioral Economics",
    "credits_min": 3,
    "credits_max": 4,
    "typically_offered": "Fall, Spring"
  }
]
Rate My Professors

Student reviews

Original comments behind the course and instructor summaries.

Read original reviews
Download part 1
Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

Explore recorded grades
Dataset & model

Recorded 2026-10-14

View the dataset on Hugging Face
Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Download part 1Download part 2
Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "0cbabbf9d2d18bc6335c4acead6ed808d48e1f1c29e16ede0081877d0d892457",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}