Spring 2027

Frontiers in Development Economics 1

Theory and empirical evidence on growth and development in low-income countries, covering poverty, risk, social networks, technology, education, corruption, institutions, and behavioral economics.

no offering record for this termCredits unavailable
Recorded instructors · Spring 2027 No instructors listed

Summary

1 / 6

Past student reviews · Laura Schechter

The course received a difficulty rating of 4 out of 5, indicating a challenging level of effort.

What you’ll be able to do

  • Construct models of credit and insurance markets in developing countries and measure their impacts empirically.

  • Measure corruption and governance and their impact on economic development.

  • Use and evaluate econometric concepts including fixed effects, attenuation bias, and instrumental variables.

  • Think critically about empirical research and write a referee report.

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 709 and 711

AAE 730

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

Prerequisite text tree

Professors

Spring 2027

No instructors recorded for this selection.

Historical instructors & teaching patterns

LAURA ANNE SCHECHTER is recorded teaching in Spring 2008, Spring 2010, Spring 2012, Spring 2014, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2022, Spring 2024. 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

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

Past student reviews · Laura Schechter

Laura Schechter was described as an extremely kind and genuinely humble professor who kept it real.

Recent recorded grades — Spring 2020: 3.50 GPA, 66.7% A/AB (n=6 letter grades); Spring 2022: 3.50 GPA, 50.0% A/AB (n=6 letter grades); Spring 2024: 3.75 GPA, 83.3% A/AB (n=6 letter grades).

difficulty & workload

Past student reviews · Laura Schechter

The course received a difficulty rating of 4 out of 5, indicating a challenging level of effort.

Past student reviews · Laura Schechter

One student called her one of their favorite all-time professors, highlighting her approachable demeanor.

Topics

  • Measurement of poverty and inequality, risk and insurance, social networks, technology adoption, education, corruption, institutions, and behavioral economics.

Skills

  • Constructing models of credit and insurance markets in developing countries and measuring their impacts empirically.
  • Measuring corruption and governance and their impact on economic development.
  • Using and evaluating econometric concepts including fixed effects, attenuation bias, and instrumental variables.
  • Thinking critically about empirical research and writing a referee report.

Grades

Latest available · Spring 2024— 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 2024

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

No offering records for the selected term.

Raw records 
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Student reviews

Original comments behind the course and instructor summaries.

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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
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Full model traces

Recorded model configuration, reasoning, and tool conversations.

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Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "a5a90b3c0fd6382d22f09cd7e612dc6654d6716162ab1f82731ba968c71c440e",
  "requirements_status": "needs_review",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}