Fall 2026

Wages and the Labor Market

ECON 450 examines wages and the labor market, covering labor supply and demand, wage theories, unemployment, and labor mobility.

no offering record for this termCredits unavailable
Recorded instructors · Fall 2026 No instructors listed

Summary

1 / 5

Historical reviews of Chao FU: Exams are tough and require deep understanding rather than memorizing homework problems. The content is challenging, and exams test this understanding through difficult questions.

Grade history

average GPA
letter grades
A
AB
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BC
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F

All recorded terms · compare terms & instructors

Prerequisites

Course map

ECON 301 or 311

ECON 450

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

Prerequisite text tree

Professors

Fall 2026

No instructors recorded for this selection.

Historical instructors & teaching patterns

Historical reviews of Chao FU: Chao Fu is a highly recommended lecturer who explains nuances and broader economic contexts effectively, though some find her delivery dry. Recent reviewers emphasize that attending lectures is crucial for success, as the material is challenging but manageable with effort. While the textbook is unnecessary, exams are tough and require deep understanding beyond simple homework repetition.

CHAO FU is recorded teaching in Fall 2010, Fall 2011, Spring 2012, Spring 2013, Spring 2014, Fall 2014, Spring 2015, Fall 2015, Spring 2016, Fall 2016, Fall 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2022, Spring 2023, Fall 2023, Spring 2025, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.

JOHN KENNAN is recorded teaching in Fall 2007, Fall 2008. Recorded history may be incomplete and does not establish a future schedule.

RASMUS LENTZ is recorded teaching in Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2017. 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

Fall 2026

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SectionModeEnrolled / capacityWaitlist

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

Meeting source records

No records available.

Student experience

the class

Historical reviews of Chao FU: Recent reviews for Chao Fu describe the course as highly recommended with engaging lectures that provide necessary context beyond the textbook. While the content and exams are challenging, attending lectures and completing homework allows students to achieve high grades.

Recent recorded grades — Fall 2023: 3.04 GPA, 43.2% A/AB (n=37 letter grades); Spring 2025: 2.95 GPA, 48.7% A/AB (n=39 letter grades); Spring 2026: 2.97 GPA, 44.4% A/AB (n=45 letter grades).

difficulty & workload

Historical reviews of Chao FU: Exams are tough and require deep understanding rather than memorizing homework problems. The content is challenging, and exams test this understanding through difficult questions.

Historical reviews of Chao FU: The textbook is unnecessary as all materials are posted online. Lectures are essential for understanding nuances, and Professor Fu is praised for making complex economic concepts clear and relevant.

Topics

  • Labor supply and demand
  • Wage theories
  • Unemployment
  • Labor mobility
  • Functioning of labor markets

Skills

  • Analyze economic and institutional forces determining labor supply and demand
  • Apply wage theories to understand wages in the economy
  • Explain the functioning of labor markets

Grades

Historical instructor

Fall 2026 · 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 recent 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.

6 earlier forecasts · 0.06 GPA average error.

Grades over time

Through Fall 2026

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

1283 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.

Selected offering source records

No offering records for the selected term.

Raw records
[]
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Student reviews

Original comments behind the course and instructor summaries.

Read original reviews
Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

Explore recorded grades
Model outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
LLM outputs across runs
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Model & dataset provenance
{
  "model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "5b8aae0530c6789d44f32e7a4d8b3f33dda9fe94832233dc9ad5fd83698209d5",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}