Adelaide University · S2 2026 · FACULTY OF ECONOMICS

ECON2002 Intermediate Applied Econometrics

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The Complete Study & Assessment Guide · S2 2026

ECON2002 Overview

Intermediate Applied Econometrics
— A source-grounded ECON2002 guide to cross-sectional data, time-series data, data visualisation and the complete published assessment structure.
  • Adelaide University School of Economics
  • Semester 2, 2026
  • an undergraduate level 2 course
  • 6 units
  • a university-wide elective and an included course in the Bachelor of Economics
  • four multiple-choice components worth 20% in total, a 15% report, a 15% oral defence, and a 50% problem-solving task

ECON2002 Intermediate Applied Econometrics develops data description, simple and multiple regression, inference, qualitative regressors, heteroskedasticity and model specification using statistical software. It is taught within Adelaide University School of Economics. It is an undergraduate level 2 course. It carries 6 units.

  • Four evidence modes The 20/15/15/50 split tests recognition, written reporting, oral defence and extended problem solving.
  • Interpretation first Every coefficient needs units, a ceteris-paribus reading and a statement of the assumptions that make inference defensible.
  • Offering boundary The public S2 page names a 50% problem-solving task. An LMS snapshot contains exam conditions for its captured offering, but live S2 instructions control the current format, duration and resources.
  • Code boundary This build follows current ECON2002 and its ECON2515 antirequisite, without folding in the separate ECON2006 course.
ECON2002 · Adelaide University
An independent, AskSia-authored study guide. AskSia is not affiliated with, endorsed by, or sponsored by Adelaide University; the course code and name are used for identification only.
Assessment

How ECON2002 is assessed

ComponentWeightFormat
Multiple-Choice Components20%Four multiple-choice components in total; live timing and conditions are not on the public page
Report15%Written econometric report; current brief and deadline must be checked in the course site
Oral Defence15%Oral communication and defence of method or result; current format must be checked live
Problem-Solving Task50%The public page does not describe this item as an examination

The current public page publishes four MCQ components worth 20% together, a 15% report, a 15% oral defence and a 50% problem-solving task. A captured LMS page describes secure-assessment conditions for its captured offering, but the public S2 2026 page neither labels the current 50% item an examination nor publishes its conditions. This guide does not transfer those older conditions to the current offering; confirm the live task brief.

Current dates · verify in LMS

Current ECON2002 dates

DateItemControl
21 August 2026Semester 2 enrol-by dateAdministrative enrolment date, not an assessment deadline.
4 September 2026Semester 2 census dateConfirm financial and enrolment implications on the official page.
18 September 2026Semester 2 last day to withdraw without failAssessment due dates are not published on the captured course page.

Current-offering dates captured in the current Adelaide University public course page. Confirm changes and exact submission settings in the live LMS.

Contents · every chapter, one map

What ECON2002 covers

Build the course in three arcs: Economic Data and Visual Evidence establishes the frame, Qualitative Regressors and Group Comparisons deepens it, and Econometric Report, Oral Defence and Problem Solving tests the complete method.

01

Economic Data and Visual Evidence

cross-sectional data · time-series data · data visualisation · classify an economic data set and choose a visual that reveals structure relevant to modelling
02

Simple Regression and the OLS Estimator

population regression function · ordinary least squares · fitted value and residual · estimate a simple relationship and decompose each observation into fitted value and residual
03

Sampling Uncertainty and Inference

sampling variance · standard error · confidence interval · move from a fitted coefficient to an interval or test while keeping the sampling assumptions visible
04

Multiple Regression and Ceteris-Paribus Interpretation

multiple regression · ceteris-paribus coefficient · omitted-variable bias · interpret a partial coefficient and explain what is and is not held constant in the comparison
05

Qualitative Regressors and Group Comparisons

dummy variable · reference category · interaction term · encode categories, choose a reference group and test whether slopes or intercepts differ meaningfully
06

Functional Form and Logarithmic Models

functional form · logarithmic transformation · marginal effect · select a level or logarithmic specification and translate its coefficient using the correct units
07

Heteroskedasticity and Robust Inference

heteroskedasticity · robust standard error · residual diagnostic · detect unequal error variance and explain what robust inference corrects and what it leaves unresolved
08

Model Specification and Statistical Validity

model specification · specification error · statistical validity · compare plausible specifications and use theory, diagnostics and sensitivity to justify a preferred model
09

Econometric Report, Oral Defence and Problem Solving

reproducible analysis · result-to-claim chain · oral defence · turn software output into a written and spoken argument that can survive specification questions

It is positioned as a university-wide elective and an included course in the Bachelor of Economics.

The current Adelaide University page couples econometric method with interpretation and communication. Its assessment design separates repeated multiple-choice checks, a report, an oral defence and a large problem-solving task.

Captured notes, Workshops and solutions add course-specific teaching evidence without being allowed to override the current public assessment labels.

Assessment in ECON2002 is distributed as follows: four multiple-choice components worth 20% in total, a 15% report, a 15% oral defence, and a 50% problem-solving task

The operational assessment conditions matter here.

The current S2 2026 public page labels the 50% component a problem-solving task and does not publish duration, permitted resources or task dates. A captured LMS exam-information page describes a two-hour, face-to-face, closed-book exam with one A4 aid for its captured offering; those conditions are retained as historical study evidence and are not transferred to the current offering.

Check the live task brief.

What makes ECON2002 demanding is concrete: Separating what OLS calculates from what an economic interpretation can claim: students must identify the data structure, justify specification and inference assumptions, diagnose violations and communicate how the result changes the substantive question.

No component-level hurdle is published on the captured official course page.

This is source silence, and a live course-site instruction may still add an operational requirement.

For enrolment planning, Students must have completed ECON1000 Principles of Economics and ECON1012 Data Analytics; ECON2515 is an antirequisite.

Build the course in three arcs: Economic Data and Visual Evidence establishes the frame, Qualitative Regressors and Group Comparisons deepens it, and Econometric Report, Oral Defence and Problem Solving tests the complete method.

Coverage note: ECON2002 is the current Adelaide University code and ECON2515 is its antirequisite; this guide does not substitute the separate ECON2006 course found in some new program structures.

Worked example · free

Interpret a log-wage coefficient and test the specification boundary

Q [4 marks]. In an AskSia-authored regression, log hourly wage is modelled against years of education and experience. The education coefficient is 0.072. Give the approximate interpretation and name one reason it may not be causal.
  • 1Identify log wage as the dependent variable and education as the focal explanatory variable.
  • 1Translate 0.072 into an approximate 7.2% conditional wage difference for one additional year of education.
  • 1Hold included experience constant and avoid describing the coefficient as an unconditional difference.
  • 1Name a plausible omitted factor, such as ability or local labour-market access, that can undermine a causal reading.
The fitted model associates one additional year of education with about 7.2% higher hourly wage, conditional on included experience. A causal claim would need a design or assumptions addressing omitted factors, selection and reverse pathways.
Sia tip — A regression coefficient is not automatically a causal effect, even when its p-value is small.
Glossary

Key terms

Ordinary least squares
An estimation method choosing coefficients that minimise the sum of squared sample residuals.
Heteroskedasticity
A condition in which the regression error variance differs across observations or explanatory-variable values.
Model specification
The selection of variables, transformations and structural relationships included in an empirical model.
Dependent variable
The outcome variable whose conditional behaviour a regression model is designed to explain or predict.
Explanatory variable
A measured variable included in a model to account for variation in the dependent variable.
Regression coefficient
A model parameter describing the conditional change in an outcome associated with an explanatory variable.
Statistical inference
The use of sample evidence and a probability model to make qualified claims about population parameters.
Dummy variable
A numerical indicator, commonly coded zero and one, representing membership in a qualitative category.
Functional form
The mathematical shape chosen to relate the dependent variable to explanatory variables in a model.
FAQ

ECON2002 FAQ

How is ECON2002 assessed?

four multiple-choice components worth 20% in total, a 15% report, a 15% oral defence, and a 50% problem-solving task

Where do students usually lose marks in ECON2002?

Separating what OLS calculates from what an economic interpretation can claim: students must identify the data structure, justify specification and inference assumptions, diagnose violations and communicate how the result changes the substantive question.

Which current ECON2002 dates are captured?

Semester 2 enrol-by date: 21 August 2026; Semester 2 census date: 4 September 2026; Semester 2 last day to withdraw without fail: 18 September 2026. Confirm any change and the exact submission setting in the live LMS.

What is the ECON2002 final assessed-task format?

The current S2 2026 public page labels the 50% component a problem-solving task and does not publish duration, permitted resources or task dates. A captured LMS exam-information page describes a two-hour, face-to-face, closed-book exam with one A4 aid for its captured offering; those conditions are retained as historical study evidence and are not transferred to the current offering. Check the live task brief.

What prerequisites or restrictions apply to ECON2002?

Students must have completed ECON1000 Principles of Economics and ECON1012 Data Analytics; ECON2515 is an antirequisite.

Does ECON2002 have a hurdle or component-level pass rule?

No component-level hurdle is published on the captured official course page. This is source silence, and a live course-site instruction may still add an operational requirement.

Is this ECON2002 resource an official university guide?

No. It is an independent ECON2002 study resource; current institutional instructions remain authoritative for assessment operation.

Study strategy

How to prepare for the assessments

Retrieve the course map, practise the recurring method—define the economic question and data structure, specify and estimate a regression, diagnose the assumptions and translate the statistical output into a defensible substantive claim—on changed scenarios, and verify every operational assessment detail in the live institutional system.

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