Spring 2027

Introduction to Applied Econometrics

Introduction to applied econometrics covering statistical methods for evaluating empirical relationships and testing economic theory, with emphasis on applying these methods to real-world data using modern statistical software.

offering recorded4 credits
Recorded instructors · Spring 2027 Christopher Mckelvey4.5/5

Summary

1 / 6

Past student reviews · Christopher McKelvey

Past students reported one problem set per week and two exams. McKelvey indicated exams were hard to test understanding but he curved them, while problem sets were reasonable in length.

What you’ll be able to do

  • Discuss the properties of an ordinary least squares (OLS) estimator for a linear regression model

  • Test theories about the true model using formal hypothesis tests

  • State the assumptions underpinning OLS, recognize violations of these assumptions, discuss the consequences of such violations, and - where possible - suggest alternative statistical approaches that are more appropriate given the circumstances

  • Evaluate the extent to which econometric methods can be used to determine whether a statistical association represents a causal relationship

  • Use statistical software to apply these statistical techniques to analyze the relationship between real-world economic variables

  • Read and interpret results from applied economics journal articles that employ these statistical techniques

Source: UW Guide

Grade history

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

Prerequisites

Course map

ECON 310, (STAT 240 and 340), STAT 302, 303, 311, 324,STAT/​MATH 309, or 431. Not open to students with credit forECON 410.

ECON 400 used by

“Used by” includes alternatives; linked courses may have other requirements. This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree

Professors

Spring 2027

Christopher Mckelvey

Adjusted rating
RMP difficulty
captured reviews
About this rating

Raw average: 4.64/5 from 94 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 · 14 reviews

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

Past student reviews · Christopher McKelvey

Christopher Mckelvey taught ECON 400 with a manageable workload consisting of one problem set per week and two exams. Students found the exams to be difficult and accounted for 64% of the final grade, though Mckelvey noted they were fair and curved.

Students described Mckelvey as an entertaining lecturer who explained difficult material clearly, making the course enjoyable despite the challenging subject matter. Lectures were recorded, and solutions were posted for all assignments.

Recent recorded grades — Spring 2025: 3.11 GPA, 43.9% A/AB (n=205 letter grades); Fall 2025: 3.07 GPA, 42.0% A/AB (n=143 letter grades); Spring 2026: 3.06 GPA, 42.6% A/AB (n=197 letter grades).

Historical instructors & teaching patterns

Past student reviews · Matthew Friedman

Students described Matthew Friedman’s lectures as interesting and the exam material as straightforward, noting it was easier than the homework. Some reported he cared about students and that the class material was top-notch, while others found his sarcasm rude but excusable.

CHRISTOPHER MCKELVEY is recorded teaching in Fall 2018, Spring 2019, Fall 2019, Fall 2020, Fall 2021, Spring 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.

MATTHEW FRIEDMAN is recorded teaching in Spring 2020, Fall 2022. 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 / 2160
DIS 301Classroom Instruction0 / 240
DIS 302Classroom Instruction0 / 240
DIS 303Classroom Instruction0 / 240
DIS 304Classroom Instruction0 / 240
DIS 305Classroom Instruction0 / 240
DIS 306Classroom Instruction0 / 240
DIS 307Classroom Instruction0 / 240
DIS 308Classroom Instruction0 / 240
DIS 309Classroom 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 · Christopher McKelvey

McKelvey made difficult economic concepts accessible and entertaining, often telling the story behind problems. Students described his exams as fair and well-written, noting they learned more from his course than others.

Recent recorded grades — Spring 2025: 3.11 GPA, 43.9% A/AB (n=205 letter grades); Fall 2025: 3.07 GPA, 42.0% A/AB (n=143 letter grades); Spring 2026: 3.06 GPA, 42.6% A/AB (n=197 letter grades).

difficulty & workload

Past student reviews · Christopher McKelvey

Past students reported one problem set per week and two exams. McKelvey indicated exams were hard to test understanding but he curved them, while problem sets were reasonable in length.

Past student reviews · Christopher McKelvey

McKelvey was responsive to emails within the day and available for help. Students found his lectures clear and interesting, which was helpful because the textbook was confusing.

Topics

  • Ordinary Least Squares (OLS) estimation and linear regression models
  • Formal hypothesis testing for econometric models
  • OLS assumptions, violations, and alternative statistical approaches
  • Causal inference and distinguishing association from causation
  • Application of statistical techniques to real-world economic variables
  • Interpretation of applied economics research literature

Skills

  • Discuss OLS estimator properties for linear regression models
  • Apply formal hypothesis tests to evaluate model theories
  • Identify OLS assumption violations and suggest alternative statistical approaches
  • Assess causal interpretation of statistical associations
  • Analyze real-world economic variables using statistical software
  • Interpret results from applied economics journal articles

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.

6 earlier forecasts · 0.13 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.

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Selected offering source records
ECON 400 · Spring 2027

Introduction to Applied Econometrics

Recorded 2026-10-29
Raw records 
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  {
    "run_id": "20261029T213040-0fa85c20",
    "semester": "1274",
    "observed_at": "2026-10-29 21:30:40.248904+00:00",
    "offering_id": "1274:296:025031",
    "course_id": "ECON 400",
    "course_uid": "course_67164e31bc510b3170f584a8",
    "term_id": "1274",
    "source_course_id": "025031",
    "source_subject_id": "296",
    "title": "Introduction to Applied Econometrics",
    "credits_min": 4,
    "credits_max": 4,
    "typically_offered": "Fall, Spring, Summer"
  }
]
Rate My Professors

Student reviews

Original comments behind the course and instructor summaries.

Read original reviews
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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

Explore recorded grades
Dataset & model

Recorded 2026-10-29

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 2Download part 3
Model & dataset provenance 
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  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "a4819b7a77931b86b1cb66e4190d7360be7bb5b0b8dea2b9e915317603f0c884",
  "requirements_status": "needs_review",
  "dataset_revision": "c9cd06eaa45f9ddf7e69faa38b89ff3d3dd995dd",
  "observed_at": "2026-10-29 21:30:40.248904+00:00"
}