Spring 2027

Causal Estimation in Economics

Causal Estimation in Economics covers the basic causality issue and contemporary econometric methods for identifying and estimating causal effects of policies, programs, or decisions.

offering recorded3 credits
Recorded instructors · Spring 2027 Fernanda Rojas AmpueroJeffrey Smith

Summary

1 / 3

Recent recorded grades — Spring 2009: 3.61 GPA, 66.7% A/AB (n=9 letter grades); Spring 2010: 4.00 GPA, 100.0% A/AB (n=9 letter grades); Spring 2026: 3.58 GPA, 76.9% A/AB (n=13 letter grades).

What you’ll be able to do

  • Explain the concept of causality

  • Identify and evaluate empirical methods used in papers in microeconomics that estimate causal effects

  • Evaluate and critique empirical papers estimating causal effects - understand the crucial assumptions behind the results, and judge the consequences of these assumptions on the estimates

Source: UW Guide

Grade history

↗
average GPA
letter grades
A
AB
B
BC
C
D
F

All recorded terms · compare terms & instructors

Prerequisites

Course map

ECON 704

ECON 707

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

Prerequisite text tree

Professors

Spring 2027

Recent recorded grades — Spring 2026: 3.58 GPA, 76.9% A/AB (n=13 letter grades). Includes jointly taught sections.

Recent recorded grades — Spring 2026: 3.58 GPA, 76.9% A/AB (n=13 letter grades). Includes jointly taught sections.

Historical instructors & teaching patterns

FERNANDA ROJAS AMPUERO is recorded teaching in Spring 2026. Recorded history may be incomplete and does not establish a future schedule.

JEFFREY SMITH is recorded teaching in 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

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SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction0 / 100

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

Recent recorded grades — Spring 2009: 3.61 GPA, 66.7% A/AB (n=9 letter grades); Spring 2010: 4.00 GPA, 100.0% A/AB (n=9 letter grades); Spring 2026: 3.58 GPA, 76.9% A/AB (n=13 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Concept of causality
  • Causal effects of economic policies, programs, and individual decisions
  • Empirical methods in microeconomics for estimating causal effects

Skills

  • Critique empirical papers by evaluating assumptions and their impact on estimates
  • Apply econometric methods to identify and estimate causal effects

Grades

Latest available · Spring 2026— not enough history to project Spring 2027.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F

Grades over time

Through Spring 2026

More grade details Grade mix, volume & source data

Not enough comparable courses for Spring 2027 in UW–Madison.

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 707 · Spring 2027

Causal Estimation in 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": "1274:296:027024",
    "course_id": "ECON 707",
    "course_uid": "course_ff29e0a44da6f7aeeb4a72d1",
    "term_id": "1274",
    "source_course_id": "027024",
    "source_subject_id": "296",
    "title": "Causal Estimation in Economics",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Not Applicable"
  }
]
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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

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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 1
Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "04ccad4dbdfe76a878a3ce0094d372166149dc746346c4be7275e356bcf9b41c",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}