This project will primarily examine the economic behavior of different types of firms, e.g., indigenous firms and foreign invested enterprises (FIEs), in China. The project also requires some analysis by comparing Chinese firms with those from other countries and do quantitative analysis at global level. The primary task is data mining/analysis. The secondary task is complementary data collection and literature review, etc. The main data would be provided to students by professor, though sometimes students need to collect supplementary data to complete the analysis. [Check some examples of my past students' project reports before you decide to apply: available at http://urop.ust.hk/docs/UROP_Proceedings_2011-12.pdf (page 87-90) and also http://urop.ust.hk/docs/urop_proceedings_2012-13.pdf (page 110-113)]
UROP1000 UROP1100 UROP2100 UROP3100 UROP4100
Duties: data mining and data analysis, data collection, literature review, etc. Students are expected to continue the UROP series conditional on satisfactory performance. All students are required to sign the confidentiality agreement before they can use the confidential data provided by supervisor.
Time commitment: average 10-20 hours per week in summer term and average no more than 10 hours per week in Fall/Spring semester.
Requirement: background knowledge of microeconomics/macroeconomics and statistics/econometrics, as well as the software Stata.
(If a student does not have any prior knowledge of Stata, she/he will need to learn how to use Stata first. The first 6 class notes with movies at the following link http://www.ats.ucla.edu/stat/stata/notes/ will provide a good starting point.)
Applicant's Learning Objectives:
Primary: based on Chinese data, understand the characteristics of different types of firms (e.g., pure exporters/pure importers/both exporters and importers; FIEs/indigenous firms) and/or the relations between them as well as their interactions with the rest of the world.
Secondary: obtain more advanced knowledge of the software Stata and quantitative analysis skills.