• Offered by Research School of Economics
• ANU College ANU College of Business and Economics
• Course subject Econometrics
• Areas of interest Econometrics
• Academic career PGRD
• Course convener
• Kailing Shen
• Mode of delivery In Person
• Co-taught Course
• Offered in First Semester 2017
Applied micro-econometrics (EMET8001)

The overall aim of the course is to introduce students to the practical application of micro-econometric methods. Micro-econometrics is concerned mainly with the analysis of crosssectional and short panel data from individuals, households, firms, regions etc. (Macro-econometrics is concerned mainly with analysing economic time series and long panel data from one or more countries.) The course goes beyond the linear regression models used to estimate simple associations between dependent and independent variables. It covers nonlinear models used to analyse for example discrete and censored dependent variables, and it covers estimation of causal effects as opposed to associations. The necessary econometric theory will be covered/reviewed and numerous applications will be discussed. In addition, practical aspects of data analysis will be discussed using the software Stata.

## Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

Upon completion of the course, the students will know:

• Explain the principles and purpose of Monte Carlo simulation methods.
• Explain parametric and nonparametric curve fitting methods.
• Explain econometric concepts such as causality, endogeneity, confounding factors, selection, and simultaneity.
• Explain econometric techniques for estimating causal effects.
• Appreciate econometric research and journal articles using the techniques discussed.
• Investigate the properties of econometric techniques using Monte Carlo simulation.
• Identify issues and problems (such as endogeneity) in empirical applications which may affect the analysis or the interpretation of estimates and tests.
• Use Stata to manage and analyse data.
• Carry out an empirical analysis of data using the econometric techniques discussed.
• Interpret the findings in an empirical analysis, and discuss caveats and potential problems.

## Indicative Assessment

Assignments, midsession exam, final exam. From weighting see course outline RSE web site.

The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.

Four contact hours per week (three-hour lectures and one tutorial) plus private study time

## Requisite and Incompatibility

To enrol in this course you must have completed EMET8005. Incompatible with EMET3006.

## Fees

Tuition fees are for the academic year indicated at the top of the page.

If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Student Contribution Band:
3
Unit value:
6 units

If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees.  Where there is a unit range displayed for this course, not all unit options below may be available.

Units EFTSL
6.00 0.12500

## Course fees

Domestic fee paying students
Year Fee
2017 \$3852
International fee paying students
Year Fee
2017 \$5130
Note: Please note that fee information is for current year only.

## Offerings, Dates and Class Summary Links

The list of offerings for future years is indicative only.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.

### First Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
3691 20 Feb 2017 27 Feb 2017 31 Mar 2017 26 May 2017 In Person N/A

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