ECON 2041

Introductory Econometrics

Intro to unit

Outline

  • Intro to teaching team
  • Salary prediction game
  • Technology and learning materials
  • Assessment
  • Learning outcomes
  • Plan for the semester

Teaching team

Unit convenor: Associate Professor Emilia Tjernstrom

Email: emilia.tjernstrom@mq.edu.au

Consultation hours: Tuesdays 9 - 10 (both in-person and Zoom)

Tutors:

  • Fazeel Jaleel

  • Syed Atif

  • Adithya Krishna


Tutorials start in week 2

Yes, I know…

It’s a beast!

~churn-strom

Teaching team

Unit convenor: Associate Professor Emilia Tjernstrom

Email: emilia.tjernstrom@mq.edu.au

Consultation hours: Tuesdays 9 - 10 (both in-person and Zoom)

A little more about me:

I study how policies work & for whom

I apply and develop econometric tools to understand treatment effect heterogeneity

Teaching team

I design & run large-scale RCTs in developing countries

A little more about me:

What will you earn when you graduate?

The Graduate Outcomes Survey (GOS)

Where I got the data:

  • A national survey of new graduates, run every year since 2016
  • In 2025: over 120,000 graduates from 136 institutions, including all 42 Australian unis
  • Graduates respond 4–6 months after finishing, so these are first-job salaries
  • We will look at the median annual salary of grads working full-time


Remember, the median tells you what the typical new graduate earns, not the average

Source: Social Research Centre (2026), 2025 Graduate Outcomes Survey: national report (QILT)

Salary prediction game

Ten fields of study, for each one: what do you think the typical new graduate earns per year?


  1. Open your portal link (in welcome email)
  2. OR scan the QR code & enter your ID
  3. Move the sliders to your best guess

Quantitative skills pay

Evidence from Texas: used AI to classify coursework for every public-university student, linked to their quarterly earnings after graduation

  • +1 quant course: ca. 1.1% higher early-career earnings, roughly $150 more per quarter
  • Writing-focused coursework: no detectable earnings return
  • Largest gains where the skills are scarcest:
    • 10.6% vs 1.9% for students in less-quantitative majors
    • 9.8% vs 4% for URM students (per SD of quant coursework)

This unit is a great place to start building these skills…

By the end, you will have a portfolio of notebooks showing off the skills you’ve learned!

Source: Xu, Yaling (2026), “Does coursework matter? Uncovering the role of skills in the returns to college,” EdWorkingPaper 26-1484

Logistics & plan

Software

Excel

You can get Excel & other MS Office products through your MQ account


Zoom

  • How to use it (remember to test your mic)
  • We expect people to have their cameras on when in Zoom meetings


Python

  • We’ll cover using Python in next week’s lecture (in Colab)
  • Note: you’ll need a google account

Textbook

Wooldridge et al. (2021)

Introductory Econometrics
(2nd Asia-Pacific ed.)

What is our goal?

a.k.a. demystifying learning outcomes

Learning outcomes

1

Analyse & apply key statistical concepts:

  • probability distributions
  • parameters, estimators & sampling distributions
  • point & interval estimation
  • hypothesis testing


What does this mean in practice?

You should understand the building blocks of statistics as applied to economic questions:

  • how we use samples to learn about a bigger group
  • how confident we can be in our estimates
  • how to tell if a result is real or just random

Learning outcomes

2

Specify, estimate & interpret a regression model


What does this mean in practice?

You should be able to set up and use regression models to
examine data & models

  • explore how one variable (education) affects another (income)
  • interpret regression tables (how economists present results)

Learning outcomes

2

Specify, estimate & interpret a regression model

Answer: Did it work?

Yields, enrolled vs. control Total maize output
(1) (2)
Enrolled 295.43*** 264.90***
(37.23) (85.73)
Control group mean 1128.39 1082.38
Observations 682 682

Learning outcomes

3

Summarise and interpret the estimation results, and draw valid inferences using hypothesis tests


What does this mean in practice?

Make sense of your results! Basically, you should know…

  • what the numbers mean
  • how strong the evidence is
  • whether your conclusions are “real” or could be due to chance

Move from output \rightarrow insight

Learning outcomes

4

Critically evaluate standard regression model assumptions & the consequences of violations


What does this mean in practice?

You should know and understand…

  • what can go wrong when the assumptions underlying a regression model don’t hold up
  • what such violations mean for your results

Become informed consumers

Learning outcomes

5

Use econometric software to solve econometric problems


What does this mean in practice?

Use software to run econometric analyses

Build practical skills!

How to do well in ECON2041

Each week, you should…

1 Read the assigned textbook chapter + any other assigned readings

Each week, you should…

1 Read the assigned textbook chapter + any other assigned readings

2 Watch the Essential Concepts videos (the lecture builds on them)

Each week, you should…

1 Read the assigned textbook chapter + any other assigned readings

2 Watch the Essential Concepts videos (the lecture builds on them)

3 Attend the live lecture

Each week, you should…

1 Read the assigned textbook chapter + any other assigned readings

2 Watch the Essential Concepts videos (the lecture builds on them)

3 Attend the live lecture

4 Attempt the tutorial questions

Each week, you should…

1 Read the assigned textbook chapter + any other assigned readings

2 Watch the Essential Concepts videos (the lecture builds on them)

3 Attend the live lecture

4 Attempt the tutorial questions

5 Attend the tutorial!

Each week, you should…

1 Read the assigned textbook chapter + any other assigned readings

2 Watch the Essential Concepts videos (the lecture builds on them)

3 Attend the live lecture

4 Attempt the tutorial questions

5 Attend the tutorial!

6 Begin working on assessments

Each week, you should…

1 Read the assigned textbook chapter + any other assigned readings

2 Watch the Essential Concepts videos (the lecture builds on them)

3 Attend the live lecture

4 Attempt the tutorial questions

5 Attend the tutorial!

6 Begin working on assessments

7 Ask for help if you need it!

Assessment

Quiz: 20%

Checks your grasp of core concepts and skills in applied econometrics, building on work from tutorials

Format: in-person quiz

Problem set: 30%

You’ll draw on content from lectures & tutorials to apply econometrics to real problems

Format: short answer written submission

We’re building something a little different: think choose-your-own-adventure, with data.
Watch this space!

Final exam: 50%

Format: 2-hour cumulative invigilated on-campus exam, held during Examination Period

The plan

Plan for the semester

1 What is econometrics?

2 Basic mathematical tools

3 Stats fundamentals

4 Stats fundamentals II

5 Simple regression

6 OLS properties & fit

7 Flavors of OLS & OVB Quiz

8 Causality

9 Regression inference

10 Inference, continued PS due 16 Oct

11 Diagnostics

12 Measurement error & IRL

13 Revision

Week 1

Essential concepts

  • What is econometrics?
  • What data do we use in econometrics?

Live lecture

  • Intro to unit
  • Salary prediction game

Tutorial

No tutorial in week 1

Week 2

Essential concepts

  • Summation, proportions, percentages
  • Partial derivatives, non-linear functions

Live lecture

  • Intro to Python
  • Write some code, bring laptops

Tutorial

  • Get started with Python
  • Understanding data types