Econometrics subject guide PDF

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ECOM 20001 Econometrics 1 SUBJECT GUIDE

Semester 1, 2020

Prepared by A/Prof David Byrne [email protected]

Department of Economics Faculty of Business and Economics

Subject Outline Introduction Welcome to ECOM 20001: Econometrics 1. In this subject, students will explore ways to use data to learn how the world works in order to inform and evaluate decision-making by businesses and governments. In doing so, students will be trained in a state-of-the-art statistical program called R, which is invaluable for data analysis, and in high demand in both industry and government. Subject Overview and Aims This subject aims to introduce econometrics, which involves using data and statistical methods to estimate economic relationships, test economic theory, and predict the impact of policy. Topics include probability and statistics, single linear regression, multiple linear regression, nonlinear regression, model internal and external validity, field and natural experiments, and time series models. Econometric methodology and application will be motivated and illustrated through applications to economics, accounting, finance, marketing, and management.

Learning Outcomes Learning Outcomes and Generic Skills To view the subject objectives and the generic skills you will develop through successful completion of this subject, please see the University Handbook: https://handbook.unimelb.edu.au/2020/subjects/ecom20001/

Eligibility and Requirements To view the eligibility and requirements, including prerequisites, corequisites, recommended background knowledge and core participation requirements for this subject, please see the University Handbook: https://handbook.unimelb.edu.au/2020/subjects/ecom20001/eligibility-and-requirements

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Academic Staff Contact Details Please see the subject LMS site for full contact details of the teaching staff in this subject. Subject Coordinator Contact Details Name: Associate Professor David Byrne Email: [email protected] Phone: +61 03 8344 3880 Consultation Hours: Thursdays, 3:00-5:00pm Email Protocol Please note that we are only able to respond to student emails coming from a University email address. Please do not use personal email addresses such as Yahoo, Hotmail or even business email addresses. Emails from non-University email addresses may be filtered by the University’s spam filter, which means that we may not receive your email. All correspondence relating to this subject will only be sent to your University email address. Note that you must first activate your University email address before you can send or receive emails at that address. You can activate your email account at this link: http://accounts.unimelb.edu.au/. While academic staff endeavor to address queries received via email, it is more appropriate to resolve substantive questions during lectures and tutorials and during normal consultation hours. With this in mind, we encourage students to attend all lectures and tutorials and to familiarise themselves with the consultation hours offered by both the lecturer and tutors.

Lectures / Seminars We will have two one-hour lectures each week: •

Tuesdays, 4.15pm-5.15pm, The Spot-B01 (Copland Theatre)

•

Thursdays, 1.00pm-2.00pm, The Spot-B01 (Copland Theatre)

Note that at each of these lecture times, if needed, there is an overflow lecture theatre: The Spot – Level 1 Theatre, where the live lecture where will be broadcast. Students are expected to attend and participate in lectures. While there is no formal grade for lecture participation, history in this subject shows students who attend lectures tend to do much better on assignments and on the final exam.

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Lecture Schedule Note: lecture slides will be placed on the LMS page at least one week prior to each lecture. Week

Date Topic Commencing

Textbook Reading

1

2 March

Subject introduction, random processes and probabilities, discrete and continuous random variables, probability density functions, cumulative density functions, mean, variance, skewness, kurtosis

Ch. 1 (all)

Descriptive statistics, joint distribution with two random variables, marginal distribution, conditional distribution, covariance, correlation, independence, distributions: Normal, ChiSquared, Student- t, F-distribution, random sampling, Law of Large Numbers, Central Limit Theorem, estimators, hypothesis testing of population means, p-values

Ch. 2, pp. 65-91,

2

9 March

Ch. 2 pp. 55-65

Ch. 3, pp. 103- 112

3

16 March

Standard error of sample mean, t-statistics, sample variance, sample standard deviation and standard error, one-sided alternatives, confidence intervals, comparing means from different populations, t-statistic with small sample sizes, scatterplots, sample covariance and correlation

Ch. 3, pp. 112-131

4

23 March

Single linear regression, population true values, ordinary least squares estimator, model fit, standard error of the regression, Least Squares Assumptions #1, #2, #3, sampling distribution of the OLS estimator

Ch. 4, pp. 143- 165

5

30 March

Hypothesis testing with OLS estimator, hypothesis testing examples, one-sided alternatives, confidence intervals with OLS estimators, dummy variables, homoskedasticity, heteroskedasticity, Gauss Markov Theorem

Ch. 5, pp. 179- 195

6

6 April

Omitted variable bias, multiple linear regression model, OLS estimator for multiple linear regression, Least Squares Assumptions #1, #2, #3, #4, sampling distribution of OLS estimators in multiple regression, multicollinearity, dummy variable trap, standard errors, hypothesis tests and confidence intervals for a single coefficient in multiple linear regression

Ch. 6, pp. 211- 235

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Ch. 7, pp. 247- 251

7

20 April

Test of joint hypotheses, overall regression Fstatistic, homoskedasticity-only F-statistic, testing single restrictions involving multiple coefficients, confidence sets, model specification, conditional mean independence, variable of interest and control variables, RSquared, applications of multiple linear regression: evaluating policy, testing theory, exploring new empirical relationships

Ch. 7, pp. 251- 268

8

27 April

Non-linear regression functions, strategy for modelling non-linear regressions, non-linear function of a single independent variable, quadratic regression, polynomial regression, logarithms, logarithmic regression, linear-log models, log-linear models, log-log models

Ch. 8, pp. 277- 297

9

4 May

Control variables in non-linear models, combining polynomial and logarithmic regressions, using polynomial functions for policy-relevant calculations, interactions models: binary-binary, binary-continuous, continuouscontinuous

Ch. 8, pp. 297- 316

10

11 May

Combining polynomial and logarithmic regression models with interactions, application of nonlinear model estimation and testing, internal and external validity, threats to interval validity, using regressions for forecasting

Ch. 9, pp. 330- 355

11

18 May

Lags, first differences, logarithms, growth rates, stationarity, autocorrelation, autocovariances, autocovariance functions, first-order autoregressive model, p-th order autoregressive model, p-th order autoregressive model

Ch. 15, pp. 554-572

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25 May

Forecasting, forecast intervals, determining model lag length, modelling seasonality, stationarity, Granger causality Economics faculty empirical research presentations, semester review, next subjects, careers in economics and data analytics, faculty research assistantships

Ch. 14, pp. 572-578

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Using Lecture Capture Audio and video recordings of lectures delivered in this subject will be made available for review following each lecture. These recordings allow you to revise lectures during the semester, or to review them in preparation for the end of semester exam. You can access recorded lectures by clicking on the Lecture Recordings (or similar) menu item on the LMS page for this subject. Please note that recordings are not a substitute for attendance; rather they are designed for revision. On rare occasions the capture system can fail to record the lecture due to technical reasons. In such cases, the recording will not be made available. In lecture theatres with multiple screens only one screen will be captured, any information projected onto the other screen will not be recorded. The University has recently moved to a new Lecture Capture platform with additional features. Please review the Lecture Capture Student Guides page for more information: https://lms.unimelb.edu.au/support/guides/students/lecture-capture-student-guide

Tutorials Tutorial / Workshop Times Weekly tutorials commence in week 1. Tutorials will be posted on the LMS site at least one week in advance of the tutorial being run. Please refer to the University timetable https://sws.unimelb.edu.au/2020/ or LMS for details on tutorials, their times, and locations. Tutorial / Workshop Participation Requirements Tutorials are designed to train you in econometrics through application, and to prepare you for the final exam. Tutorial / Workshop Schedule Week

Tutorial Topic

1

Introduction to R: A Statistical Program for Doing Econometrics

2

Visualising and Describing Data in R, Summation Practice Problems

3

Distributions, Law of Large Numbers, Central Limit Theory, Conditional Probability

4

Hypothesis Testing, p-values, Confidence Intervals, Testing Differences of Means

5

Single Linear Regression Estimation

6

Single Linear Regression Testing

6

7

Dummy Variables, Heteroskedasticity, Omitted Variables

8

Dummy Variable Trap, Multicollinearity

9

Joint Hypothesis Testing with Multiple Linear Regression

10

Polynomial Regression

11

Logarithmic Regression and Interactions

12

Time Series Regression

Assessment Assessment Overview Your assessment for this subject comprises the following: Individual or Group

Due

Weight

Assignment 1 (8 pages A4)

Individual or Groups of 2 or 3

6 April 2019, 8am

5%

Assignment 2 (8 pages A4)

Individual or Groups of 2 or 3

4 May 2018. 8am

5%

Assignment 3 (8 pages A4)

Individual or Groups of 2 or 3

25 May 2019, 8am

5%

Participation in Tutorials

Individual

Weekly, weeks 1-12

5%

Weekly Quizzes

Individual

Weekly, weeks 1-12

10%

2-hour end of semester examination

Individual

During the University exam period

70%

Assessment Task

Faculty Hurdle requirement: To pass this subject, students must pass the end of semester examination

Assessment Details Assignments: involve exam-type questions and involve data analysis using R. These can be submitted individually or in groups of up to 3 (max). Group members do not necessarily have to be from the same tutorial. All group members must have their name and student number of the cover page of the assignment to receive credit for the assignment.

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Tutorials: you must attend and participate in tutorials to earn your tutorial mark each week. Students only get a tutorial mark for attending the tutorial in which they are officially enrolled in (their ‘official’ tutorial). Students with a legitimate reason (such as illness) for attending a tutorial other than their official one (or being unable to attend any tutorial) can apply to have the tutorial marke for that week transferred to the final exam by emailing the tutorial coordinator (Mr Richard Hayes) their documentary evidence such as a medical certificate within a week of missing the official tutorial. Late requests or requests sent to tutors will not be considered. No more than two tutorial markets will be transferred for any student during the semester. You can miss 2 tutorials without penalty through the course of the semester. This covers all excuses for missed tutorials except for severe medical circumstances with a doctor’s note, as mentioned above. Note: for students unable to be on campus because of the coronavirus travel ban, tutorial participation will not be recorded until the ban is lifted and the University confirms when you are able to arrive back on campus. Quizzes: each week you will have a short 3-question quiz. We will use your best 10 of 12 quiz scores to compute an average quiz score for the semester and use this average we will compute your quiz grade for the semester. Because you can miss 2 quizzes without penalty, this covers all excuses for missed quizzes except for severe medical circumstances with a doctor’s note. Final Exam: will be 2 hours in duration and will involve multiple choice questions (similar to quiz questions), problem solving and econometric analyses (similar to tutorials and assignments). Assignment and Quiz Submissions Assignment submission is via the LMS Assignment Submission link for all written assignments. Assignments must be submitted by 8am on their respective due dates. Please note that you are required to keep a copy of your assignment after it has been submitted as you must be able to produce a copy of your assignment at the request of teaching staff at any time after the submission due date. Quiz submission is via the LMS Quiz Submission link for all quizzes. Quizzes must be submitted by 8am on Monday each week of the semester, except in week 1 when there is no quiz due for submission. Penalties for Late Submissions Solutions for the assignments and quizzes are posted just after the 8am submission deadlines week-to-week. As such, late submissions for assignments and quizzes will not be accepted. For information about setting penalties, please see the Assessment and Results Policy (MPF1326) Assessment penalties section. Students with a genuine and acceptable reason for not completing an assignment (or other assessment task), such as illness, can apply for special consideration (see policy below).

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Subject Resources Prescribed Reference The main reference for the subject is the lecture notes. They draw heavily from and are developed in direct correspondence to the subject textbook: •

Introduction to Econometrics, Global Edition, 4th Edition, by James H. Stock and Mark W. Watson, 2015 (ISBN-13: 978-1-292-26445-5)

•

For details on the book or eBook: https://www.pearson.com.au/9781292264455

This textbook is also used in ECOM30002: Econometrics 2, the econometrics subject that follows this subject. As the textbook represents the world standard for econometrics texts and is fundamental to both subjects, students are strongly encouraged to purchase the textbook for the subject and future subjects in econometrics. All page numbers referenced in the course syllabus, lecture notes, tutorials, and assignments correspond to this version of the textbook and not earlier versions.

Academic Integrity Academic Honesty The University maintains high academic standards in its courses and subjects and expects students to conduct themselves in a manner which is fair, honest and consistent with the principles of academic integrity, particularly when undertaking assessment and research. http://academicintegrity.unimelb.edu.au/ Referencing All sources used for a written piece of assessment must be referenced. This is to acknowledge that your material is not based entirely on your own ideas, but is based, in part, on the ideas, information, and evidence of others. This is desirable as you are attending University in order to learn from others. You will be required to use the Harvard System of referencing. The library has prepared a website to help students correctly reference: http://www.lib.unimelb.edu.au/recite/citations/harvard/generalNotes.html It is important that all material you present for assessment is referenced correctly. Material that has not been referenced correctly may be considered to be plagiarised, and as such may be penalised. We will also look for evidence that material included in the bibliography has been used in the assignment. Including references that have not been used may also result in your assignment being penalised The Academic Skills Unit has produced resources to assist students with referencing https://services.unimelb.edu.au/academicskills/undergrads/top_resources

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The Library also provides advice on referencing: http://library.unimelb.edu.au/cite

University Services Stop 1: Connecting Students and Services Stop 1 is here to provide you with a range of support services throughout your university degree, from help with enrolment, administration and wellbeing to advice on building your skills and experiences. https://students.unimelb.edu.au/stop1 Academic Skills Academic Skills offers a range of workshops and resources to help you with study skills including researching, writing and referencing, presentation skills and preparing for exams. Visit their website via http://services.unimelb.edu.au/academicskills. Service Finder The University of Melbourne offers one of the most comprehensive student support networks in Australia. Use this site to locate a wide range of services http://services.unimelb.edu.au/finder Student Counselling Students attend counselling to talk about personal, emotional, or mental health issues which might be affecting their study and life. The University’s Counselling and Psychological Services (CAPS) provides free, confidential, short-term professional counselling to currently enrolled students and staff. https://services.unimelb.edu.au/counsel/individual Student Equity and Disability Support Student Equity and Disability Support provides services for students who need ongoing support with their studies. They understand that adjustments to learning and assessment are sometimes required to allow all students to reach their full potential. Learn more about the services provided, how to find support and how to register for assistance. http://services.unimelb.edu.au/student-equity University of Melbourne Library Services As well as holding an extensive collection of books, ebooks, digital media and periodicals, library staff provide research guidance and support for students. http://library.unimelb.edu.au/ These Business and Economics Library Guides have been designed specifically for Faculty of Business and Economics staff and students. http://unimelb.libguides.com/sb.php?subject_id=80310

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Policy Alternative Exam Arrangements (AEA) The definition of and eligibility requirements for alternative exam arrangements (AEA) can be found via http://students.unimelb.edu.au/admin/alternate . Assessment and Results Policy The University’s assessment policy provides a framework for the design, delivery and implementation of assessment of students in award and non-award courses and subjects. Assessment is designed to contribute to high quality learning by students, and to allow for quality assurance and the maintenance of high academic standards. https://policy.unimelb.edu.au/MPF1326 Assignment Extension Requests for an assignment e...