Students

ECON2032 – Intermediate Econometrics

2024 – Session 2, In person-scheduled-weekday, North Ryde

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff
Hanbat Jeong
hanbat.jeong@mq.edu.au
Credit points Credit points
10
Prerequisites Prerequisites
ECON241 or ECON2041 or STAT272 or STAT2372 or STAT171 or STAT1371 or STAT270 or STAT2170 or STAT273 or STAT2173 or STAT271 or STAT2371
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description

This unit covers econometric techniques that go beyond the classical regression model. It helps students to develop literacy in important methods commonly used to analyse data in economics, finance and business environments. The topics covered may include heteroscedasticity, stochastic regressors, limited dependent variables, time-series regression and panel data analysis.

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates

Learning Outcomes

On successful completion of this unit, you will be able to:

  • ULO1: Identify and describe econometric concepts and theories.
  • ULO2: Estimate econometric models and test parametric hypotheses using techniques that are appropriate for the problem at hand.
  • ULO3: Diagnose and resolve problems relating to the violation of standard assumptions in econometric models, and make conclusions and recommendations.
  • ULO4: Critique the appropriateness of alternative econometric techniques in practical applications to appropriate problems.

General Assessment Information

Late Assessment Submission Penalty (written assessments)

Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark) will be applied each day a written assessment is not submitted, up until the 7th day (including weekends). After the 7th day, a grade of ‘0’ will be awarded even if the assessment is submitted. Submission time for all written assessments is set at 11.55pm. A 1-hour grace period is provided to students who experience a technical concern.  For any late submissions of time-sensitive tasks, such as scheduled tests/exams, performance assessments/presentations, and/or scheduled practical assessments/labs, students need to submit an application for Special Consideration.

Assessment Tasks

Name Weighting Hurdle Due
Assignment 20% No Week 13
Final exam 50% No University Examination Week
Tutorial exercises 15% No Weeks 3, 5, 7, 9, and 11
Mid-session Test 15% No Week 8

Assignment

Assessment Type 1: Modelling task
Indicative Time on Task 2: 19 hours
Due: Week 13
Weighting: 20%

 

Students will be given an applied econometric problem to work on and will be required to submit a written report on their investigation of the problem. Students may also be required to submit relevant computer files.

 
On successful completion you will be able to:
  • Identify and describe econometric concepts and theories.
  • Estimate econometric models and test parametric hypotheses using techniques that are appropriate for the problem at hand.
  • Diagnose and resolve problems relating to the violation of standard assumptions in econometric models, and make conclusions and recommendations.
  • Critique the appropriateness of alternative econometric techniques in practical applications to appropriate problems.

Final exam

Assessment Type 1: Examination
Indicative Time on Task 2: 50 hours
Due: University Examination Week
Weighting: 50%

 

A two-hour examination, consisting of multiple choice, numerical, and short answer questions, will be held during the University Examination Period.

 
On successful completion you will be able to:
  • Identify and describe econometric concepts and theories.
  • Estimate econometric models and test parametric hypotheses using techniques that are appropriate for the problem at hand.
  • Diagnose and resolve problems relating to the violation of standard assumptions in econometric models, and make conclusions and recommendations.
  • Critique the appropriateness of alternative econometric techniques in practical applications to appropriate problems.

Tutorial exercises

Assessment Type 1: Problem set
Indicative Time on Task 2: 5 hours
Due: Weeks 3, 5, 7, 9, and 11
Weighting: 15%

 

Tutorial exercise quiz in W3 is weighted 5% and designed to ensure that you quickly review key concepts in maths and statistics taught in prerequisite units which will be necessary for you to progress through the new material in this unit; the remaining Tutorial exercise quizzes in W5, 7, 9, 11 are worth 2.5% each. Each quiz will be a problem set to be completed at the end of the week in a designated time window. The tutorial classes will help you prepare for the quizzes.

 
On successful completion you will be able to:
  • Identify and describe econometric concepts and theories.
  • Estimate econometric models and test parametric hypotheses using techniques that are appropriate for the problem at hand.
  • Diagnose and resolve problems relating to the violation of standard assumptions in econometric models, and make conclusions and recommendations.
  • Critique the appropriateness of alternative econometric techniques in practical applications to appropriate problems.

Mid-session Test

Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 3 hours
Due: Week 8
Weighting: 15%

 

The test assesses the work covered in lectures up to the submission deadline, and consists of a set of questions to be answered on iLearn. It may consist of true-false, multiple choice, numerical and simple answer questions.

 
On successful completion you will be able to:
  • Identify and describe econometric concepts and theories.
  • Estimate econometric models and test parametric hypotheses using techniques that are appropriate for the problem at hand.
  • Diagnose and resolve problems relating to the violation of standard assumptions in econometric models, and make conclusions and recommendations.
  • Critique the appropriateness of alternative econometric techniques in practical applications to appropriate problems.

1 If you need help with your assignment, please contact:

  • the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
  • the Writing Centre for academic skills support.

2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation

Delivery and Resources

Delivery format

Two hours of face-to-face lecture

One hour of face-to-face or online tutorial

Each week, there will be two hours of face-to-face lectures. Also, weekly one-hour tutorials will be held to review assigned problems. The problems covered in the tutorial sessions will reinforce the topics discussed in the main lectures.

REQUIRED AND RECOMMENDED TEXTS AND/OR MATERIALS

Wooldridge, Jeffrey M., Introductory Econometrics: A Modern Approach, 7th edition,

  The textbook is available online via the Macquarie University Library. As the unit progresses, material such as lecture slides, examples, etc., will be made available on the unit website.

TECHNOLOGIES USED AND REQUIRED

The main software package used is Gretl. It is free and open-source, and available on Windows, Mac, or Linux. Students will need to install Gretl on their personal computers. Visit the Gretl website:

https://gretl.sourceforge.net/

choose an operating system from the left-hand side of the page, and follow the download and installation instructions.

EMAIL USE

It is University policy that the University issued email account will be used for official University communication. All students are required to access their University account frequently. Only contact Macquarie University staff (including tutors), using your official MQ student’s account because this is one method used to verify your identity.  

Unit Schedule

Week 1: Probability theory

  • Summary
  • Probability Spaces
  • Random Variables
  • Distribution Functions (discrete and continuous)
  • Expected value, Variance, and Moments
  • Readings

Wooldridge, Introductory Econometrics: A Modern Approach (7th ed): Appendices A and B (pp. 666-697) 

Week 2: Probability theory

  • Summary
  • Important Distribution Functions
  • Joint Probability Distribution Functions
  • Covariance and Correlation
  • Conditional Probability Distribution Functions
  • Conditional Moments
  • Law of Iterated Expectations
  • The Sample Mean/The Laws of Large Numbers
  • The Central Limit Theorem
  • Reading

Wooldridge, Introductory Econometrics: A Modern Approach (7th ed): Appendix B (pp. 697-713)

Week 3: Estimation and hypothesis testing

  • Summary
  • Identify a point estimator and the small and large sample properties that may be of interest.
  • Construct a confidence interval
  • Standardize a random variable
  • Understand when a standardized sample mean follows a Standard Normal versus a t-distribution
  • Perform a hypothesis test
  • Understand critical value method and p-value method
  • Understand one-sided versus two-sided tests.
  • Reading

Wooldridge, Introductory Econometrics: A Modern Approach (7th ed): Appendix C (pp. 714-743)

Week 4: Linear regression

  • Summary
  • Understand the main features of a Linear Model
  • Understand how to estimate the parameters of a Linear Model
  • Know the Classical Assumptions motivating the Ordinary Least Square (OLS) Estimator
  • Perform Hypothesis Testing on Linear Models
  • Reading

Wooldridge, Introductory Econometrics: A Modern Approach (7th ed): Chapter 2 (pp. 20-36) [Univariate Regression]

Wooldridge, Introductory Econometrics: A Modern Approach (7th ed): Chapter 3 (pp. 67-96) [Multivariate Regression]

Wooldridge, Introductory Econometrics: A Modern Approach (7th ed): Chapter 4 (pp. 120-145) [Hypothesis Testing]

Week 5: Heteroskedasticity

  • Summary
  • Understand the definition of Heteroskedasticity in Linear Regression
  • Know the impacts of Heteroskedasticity for the OLS estimator
  • Recognize Heteroskedasticity in a plot
  • Know how to test for the presence of Heteroskedasticity
  • Know how to correct for Heteroskedasticity
  • Reading

Wooldridge, Introductory Econometrics: A Modern Approach (7th ed): Chapter 8 (pp. 262-284)

Week 6: Model specification

  • Summary
  • Concept of model specification
  • Identify different violations of correct model specification and their impact
  • Understand how non-linear relationships can be captured by linear models (in higher dimensional spaces)
  • Know what a dummy variable is and how they affect a linear model
  • Know how to test null hypotheses about model specification
  • Reading

Wooldridge, Introductory Econometrics: A Modern Approach (7th ed): Chapter 6 (pp. 186-194)

Wooldridge, Introductory Econometrics: A Modern Approach (7th ed): Chapter 9 (pp. 295-303, 310-313)

Week 7: Endogeneity

  • Summary
  • Define Endogeneity and describe its impact on the OLS estimator
  • Define an Instrumental Variable and know the definition of a valid instrument
  • Understand Two Stage Least Squares
  • Understand the problem of weak instruments
  • Implement tests for exogeneity and instrument strength
  • Reading

Wooldridge, Introductory Econometrics: A Modern Approach (7th ed): Chapter 15 (pp. 495-519)

Week 8: Binary Dependent variables

  • Summary
  • Define a binary variable, and state its Probability Distribution Function and Moments
  • Understand the problems with standard OLS (aka the Linear Probability Model) given a binary dependent variable
  • Understand the Maximum Likelihood Estimation (MLE) Method
  • Gain some intuition on how the estimation procedure of Maximum Likelihood works
  • Understand the Logit and Probit models, how we estimate them, and how we generate predictions using them
  • Conduct hypothesis testing with Logit and Probit (possibly in early next weeks lectures)
  • Reading

Wooldridge, Introductory Econometrics: A Modern Approach (7th ed): Chapter 17 (pp. 559-571)

Week 9: Stationary Time Series

  • Summary
  • Understand how time-series analysis differs from the cross-section
  • Define autocorrelation and understand it in the context of several popular time series models
  • Understand Weak Dependence, especially in the context of Autocorrelation
  • Laws of Large numbers and Central Limit Theorems for Time-series
  • Reading

Wooldridge, Introductory Econometrics: A Modern Approach (7th ed): Chapter 10 (pp. 334-344)

Week 10: Stationary Time Series

  • Summary
  • Understand the Strong Time Series Assumptions for OLS, including strict exogeneity
  • Define Stationarity
  • Understand the regular Time Series Assumptions for OLS
  • Heteroskedasticity and Autocorrelation Consistent Standard Errors
  • Distributed Lag Models, Autoregressive Models, and Autoregressive Distributed Lag Models
  • Reading

Wooldridge, Introductory Econometrics: A Modern Approach (7th ed): Chapter 11 (pp. 367-376)

Wooldridge, Introductory Econometrics: A Modern Approach (7th ed): Chapter 12 (pp. 394-401)

Week 11: Nonstationary Time Series

  • Summary
  • Detecting Autocorrelation in OLS residuals
  • Definition of Nonstationarity
  • Nonstationarity in Autoregressive models and Random Walks
  • Nonstationarity and deterministic trends
  • Further topics for advanced courses (financial econometrics)
  • Reading

Wooldridge, Introductory Econometrics: A Modern Approach (7th ed): Chapter 12 (pp. 401-407)

Wooldridge, Introductory Econometrics: A Modern Approach (7th ed): Chapter 10 (pp. 351-357)

Week 12: Panel Data

  • Summary
  • Definition of Panel Data
  • Common Panel Data restrictions and assumptions
  • Pooled Regression Models
  • Policy analysis with pooled cross sections
  • Reading

Wooldridge, Introductory Econometrics: A Modern Approach (7th ed): Chapter 13 (pp. 426-461)

Week 13: Panel Data

  • Summary
  • Two-Period Panel Data analysis
  • Policy analysis with Two-Period Panel Data
  • Differencing with More Than Two Time Periods
  • Fixed-Effect Models and Random-Effect Models

 Wooldridge, Introductory Econometrics: A Modern Approach (7th ed): Chapter 13 (pp. 426-461)

Wooldridge, Introductory Econometrics: A Modern Approach (7th ed): Chapter 14 (pp. 462-494)

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Results

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Academic Integrity

At Macquarie, we believe academic integrity – honesty, respect, trust, responsibility, fairness and courage – is at the core of learning, teaching and research. We recognise that meeting the expectations required to complete your assessments can be challenging. So, we offer you a range of resources and services to help you reach your potential, including free online writing and maths support, academic skills development and wellbeing consultations.

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Unit information based on version 2024.03 of the Handbook