The Quantitative Economics Specialisation produces graduates who can think critically, and who can understand, explain and apply the core principles and quantitative methods of economics to resource allocation problems, the functioning of economic institutions, and the decisions of policy makers and other economic agents within a society.
Economics is the social science that studies the behaviour and interactions of economic agents. In particular, economics examines the production, distribution, and consumption of goods and services.
Economics graduates who have a strong analytical and mathematical background are in demand both internationally and nationally.
The Quantitative Economics specialisation will equip graduates with both research informed economic knowledge and the analytical skills required to implement this knowledge in practical real-world situations.
Where can Quantitative Economics take you?
A list of employers of previous Economics graduates includes:
- Policy institutions, such as the New Zealand Treasury, the Ministry of
Business, Innovation & Employment, the Reserve Bank of New Zealand, and
Motu Economic and Public Policy Research;
- Private sector companies, such as Goldman Sachs, ANZ, Fletcher Construction,
GE Capital, NERA Consulting, and HoustonKemp.
Students have also recently gone on to do PhDs in Economics at Harvard University, MIT, University of Chicago, Yale University, Northwestern University, University of Michigan, and the LSE.
The Treasury values a range of skill sets, including economists with strong quantitative skills who are able to support the use of quantitative evidence and analysis in our advice. Graduates that have both technical modelling capabilities and training in the theory and practice of economics are very sought-after, and can be hard to find. There is significant benefit to the Treasury in undergraduate programmes that emphasize and teach technical modelling and quantitative skills.
Meet a graduate
Quantitative Economics was especially important in teaching me the basics of coding for data analysis. This has made me more comfortable analysing some of the large datasets in my work.
Read Chenchen's full story here.