- Code EMET3006
- Unit Value 6 units
- Offered by Research School of Economics
- ANU College ANU College of Business and Economics
- Course subject Econometrics
- Areas of interest Econometrics
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.
Upon successful completion, students will have the knowledge and skills to:
- 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.
- Assignments. midsession exam, final exam. From weighting see course outline RSE web site. (null) [LO null]
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WorkloadTwo hours lecture and one tutorial per week plus private study time
Requisite and Incompatibility
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- Unit value:
- 6 units
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