Jiatong Zhong, PhD
Assistant Professor, Faculty of Arts - Economics Dept
Faculty of Arts - Economics Dept
Tory (H.M.) Building
11211 Saskatchewan Drive NWEdmonton ABT6G 2H4
I am an Assistant Professor in the Department of Economics at the University of Alberta. I received my Ph.D. in 2019 from Purdue University. Before that, I received my Master degree in Economics from the London School of Economics and Political Science and my Bachelor degree in Economics and Finance from the Hong Kong University of Science and Technology.
My research interests are in international trade and applied microeconomics.
Econ 323 International Economics
Econ 421 International Trade
Econ 384 Intermediate Microeconomic Theory II
Econ 403/603 Topics in Economics III (Introductory data analysis with Python)
ECON 323 - International Economics
A survey of the principles of international economics and the applications to economic policy. Topics include international trade in goods and financial assets, trade policy and exchange rate determination. Prerequisites: ECON 109 and ECON 281. Note: Not open to students with credit in or enrolled in ECON 421 or 422.
ECON 421 - International Trade
Nature and relevance of international trade; early trade doctrines; the theory of comparative advantage, classical and modern approaches and empirical evidence for them; new approaches to the pure theory of international trade; economic growth and international trade; market imperfections and trade; commercial policy; economic integration and the gains from trade. Prerequisites: ECON 109, ECON 281 and MATH 156 or equivalent.
ECON 494 - Economic Data Analysis I
Computer programming for the statistical analysis and econometric modelling of data in economics. The statistical programs introduced and used in the course include SAS, R, Python or similar computer programming languages. Prerequisites: ECON 109 and ECON 299 or equivalent.
ECON 594 - Economic Data Analysis II
Computer programming for the statistical analysis and econometric modelling of data in economics. The statistical programs introduced and used in the course include SAS, R, Python or similar computer programming languages.