ETC3410 course guide PDF

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Monash University DEPARTMENT OF ECONOMETRICS AND BUSINESS STATISTICS ETC3410/ETC5341/BEX3410 APPLIED ECONOMETRICS SEMESTER 1 2019

Chief Examiner and Unit Coordinator Name: Dr. Jun Sung Kim Room: CL_20Chn/E856 Phone: 9905-0789 Email: [email protected]

Lecturer Name: Dr. Jun Sung Kim Room: CL_20Chn/E856 Phone: 9905-0789 Email: [email protected] Consultation Hours: Wed 11:00-11:45, Thu 15:00-15:45 Tutors Name: Lachlan Macquarie Room: CL_20Chn/W1107 Phone: 9905-5841 Email: [email protected] Consultation Hours: Wed: 12:30-14:30 Name: Kanchana Nadarajah Room: CL_20Chn/W1105 Email: [email protected] Consultation Hours: Wed 16:30-18:00

Lecture Times and Location Wed: 10:00-11:00 CL_21Col/E3 Thu: 14:00-15:00 CL_21Col/E3

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Tutorial Times and Location (There will be tutorials in Week 1.) Tue: 13:00-14:30 CL_20Chn/E157 Wed: 11:00-12:30 CL_20Chn/E160 Wed: 15:00-16:30 CL_20Chn/S317 Thu: 9:30-11:00 CL_20Chn/E151 Fri: 11:00-12:30 CL_20Chn/E151

Prerequisite ETC2410/ETC3440

Unit Objectives  

Introduce students to important econometric models and techniques that are widely used in empirical analysis in the disciplines of economics and finance. Teach students how to use the software package Stata to conduct empirical work using these models and techniques.

Prescribed Text Wooldridge, J. (2013) "Introductory Econometrics: A Modern Approach", 5th edition, South-Western, Cengage Learning *** Note: 4th, 6th, 7th editions of this book may also be used. Recommended texts   

Stock, J, and M. Watson (2012) “Introduction to Econometrics”, 3rd edition , Pearson (SW) Davidson, R. and J.G. MacKinnon (2004) "Econometric Theory and Methods”, Oxford University Press. Wooldridge, J. (2012) “Econometric Analysis of Cross Section and Panel Data”, MIT Press

The above texts are on reserve in the Monash Library. Many of the topics covered in this unit are discussed at an elementary level in the following texts:

 

Johnston, J. and DiNardo J. (1997) “Econometric Methods”, McGraw-Hill. Hill, R., Griffiths, W. and Judge G. (2000) “Undergraduate Econometrics”, John Wiley and Sons.

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Moodle There is a unit site on Moodle. Assignment data and other information relevant to the unit will be posted on this site. It is recommended that you check this web site on a regular basis.

STATA We will be using the statistical package, STATA. STATA is widely used by empirical researchers in (micro) economics and the social sciences. In the first tutorial you will get a chance to familiarise yourself with STATA and use it to examine some empirical data and do some preliminary analysis. The availability of STATA at Monash computer labs can be found here: http://monash.edu/locate-a-lab

Assessment Summary Group Assignment 1: 20% Group Assignment 2: 20% Examination (closed book, 2 hours): 60% Hurdle Requirements To pass this unit your combined mark on all pieces of assessment must exceed 49% and your mark on the final examination must exceed 39%. Where a student fails to achieve this hurdle requirement the returned mark will be the minimum of their combined mark on all pieces of assessment and 48%.

Return of Final Marks The final mark that a student receives for a unit will be determined by the Board of Examiners on the recommendation of the Chief Examiner taking into account all aspects of assessment. The final mark for this unit will be released by the Board of Examiners on the date nominated in the Faculty Calendar.

Applications for Extension of Time For information regarding extensions of time, please refer to http://www.buseco.monash.edu.au/asg/agu/policies/written-assign.html#extoftime

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Unit Outline: Topic 1. Background Material

Recommended Reading Lecture notes, topic 1

    

Review of some basic statistical concepts Some elementary asymptotic theory A review of multivariate linear regression Testing linear restrictions Heteroskedasticity

Wooldridge, appendices B and C

Lecture notes, topic 2

2. Binary Outcome Models  



Wooldridge, chapter 17.1

The linear probability model Logit and probit models o Maximum Likelihood Estimation o Marginal effects Applications

Lecture notes, topic 3

3. Instrumental Variables (IV) Estimation

Wooldridge, chapter 15 and 16        

Endogeneity bias: consequences and causes Simple IV estimation in the linear regression model Generalized IV estimation in the linear regression model Testing for endogeneity Testing overidentifying restrictions Proxy variables as an alternative to IV estimation Simultaneous equations models o Identification in SEMs o 2SLS estimation Applications

Lecture notes, topic 4

4. Static Panel Data Models

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       

Wooldridge, chapter 13 and 14

Pooled OLS The unobserved effects model The fixed effects (FE) estimator The first-difference estimator The random effects (RE) estimator Choosing between FE and RE estimation The least squares dummy variable model Applications

Lecture notes, topic 5

5. Program Evaluation      



Stock and Watson, Ch 13.

Randomized controlled trial (RCT) Quasi-experiment Average treatment effect (ATE) Propensity score matching Differences-in-differences Some recent topics (if time permits): e.g. regression discontinuity design, synthetic control, partial identification, social interaction models Applications

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