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Advanced time-series and nonstationary panel econometric techniques.
This paper examines aspects of time-series and nonstationary panel data econometrics that have become widely used in the estimation and testing of macroeconomic relationships in recent years. The objective of the paper is to develop an understanding of the econometric analysis of non-stationary data and the cointegration literature. At the end of the paper students should be able to interpret and critically evaluate applied time-series and panel time-series econometric studies in the literature, and to apply macroeconometric methods, using appropriate computer software, to relevant data in practice and interpret the results obtained.
|Teaching period||Semester 1 (On campus)|
|Domestic Tuition Fees (NZD)||$1,132.73|
|International Tuition Fees||Tuition Fees for international students are elsewhere on this website.|
- ECON 375
- ECON 490, ECON 495
- Teaching staff
- Professor Dorian Owen
Reading will consist primarily of journal articles, but recommended texts include:
K. Patterson, An Introduction to Applied Econometrics: A Time Series Approach, Macmillan, 2000
B.H. Baltagi, Econometric Analysis of Panel Data (4th ed.), John Wiley, 2008
D.F. Hendry and J.A. Doornik, Empirical Model Discovery and Theory Evaluation: Automatic Selection Methods in Econometrics, MIT Press, 2014
M. Soderbom, F. Teal, M. Eberhardt, S. Quinn and A. Zeitlin, Empirical Development Economics, Routledge, 2015
J.L. Castle and D.F. Hendry, Modelling Our Changing World, Palgrave Macmillan, 2019
- Graduate Attributes Emphasised
- Scholarship, Communication, Critical thinking, Information literacy, Research.
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- Learning Outcomes
Students who successfully complete this paper should be able to
- Demonstrate an understanding of contemporary econometric methods used in time-series and panel time-series data analysis in macroeconomic contexts and critically assess their use in applications to economic problems
- Apply macroeconometric methods, using appropriate computer software, to relevant data in practice and interpret the results obtained
- Explain the relevant estimation and testing methods and interpretation of results using written English and Mathematics, as appropriate