Part-time Research Associate/ Assitant I/ II/ Technical Assistant (Project at Hong Kong Metropolitan University

, Hong Kong, China -

Full Time

Start Date

Immediate

Expiry Date

16 Dec, 25

Salary

0.0

Posted On

17 Sep, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Econometrics, Stata, R, Python, Data Cleaning, Research Writing, Macroprudential Policy, Banking, Housing Markets, Time-Series Econometrics, VAR, SVAR, ARDL, Unit Root Tests, Cointegration Tests, Chinese-Language Policy Documents

Industry

Description

Founded in 1989, Hong Kong Metropolitan University (HKMU) is a modern, vibrant and dynamic university. We tailor our professional programmes to adapt to market trends and meet industry needs, thus providing our students with quality professional education and clear career paths. Being the first University of Applied Sciences (UAS) in Hong Kong, we pledge to play a pioneering role in enhancing recognition of vocational and professional education and training, and nurturing talents with both applied skills and knowledge. As a faculty-driven, student-centred university in support of innovative teaching and learning, strategic research, and stakeholder outreach to provide maximum benefit to our communities, we conduct research that advances knowledge and enhances teaching, focusing on strategic areas, including digital humanities and literature, international business, gerontechnology, personalised care, smart city, open and innovative education, and bilingual learning and teaching. HKMU is becoming an ever more vital link in addressing and helping Hong Kong to solve many difficult challenges – as part of our involvement in, and commitment to, the ‘metropolis’ of Hong Kong. Our plans to expand into the Greater Bay Area (GBA) will also cultivate talent to serve Hong Kong and the wider metropolitan GBA. For more information about the University, please visit https://www.hkmu.edu.hk. Project (R2088) : Navigating Regulatory Landscapes: The Impact of Macroprudential Policies on Financial Development and Economic Growth in Hong Kong This project examines how macroprudential toolkit—such as LTV/DTI caps, countercyclical buffers, and sectoral capital requirements—shapes financial development and real-economy outcomes. We will build a structured policy database, merge it with market- and macro-level datasets, and estimate causal effects using modern econometric techniques. We are now looking for a suitable person to fill the following position in the Lee Shau Kee School of Business and Administration: Major Duties and Responsibilities The appointee will be responsible mainly for the following: Conducting systematic literature reviews on macroprudential policy, financial development, and growth (academic and policy sources); Collecting, cleaning, and merging time-series/panel data (bank-level, credit, housing, firm outcomes, and macro indicators); Implementing empirical analyses (e.g., event studies, DiD, panel regressions, SVAR/time-series models); Building reproducible code and documentation (version control, data dictionaries, replication files); and Draftinfing concise memos, figures, and tables for working papers and presentations. Candidates Candidates should possess the following qualifications, experience and competence: A Current Master’s/PhD student (or strong final-year undergraduate) in economics, finance, public policy, data science, or related field; Solid econometrics skills and experience with Stata, R, or Python (pandas/statsmodels); Proven data cleaning/merging skills and attention to detail; Strong research writing ability in English; Coursework or prior work on macroprudential policy, banking, or housing markets; Familiarity with Hong Kong’s financial system and HKMA publications; Experience with time-series econometrics (VAR/SVAR, ARDL, unit root/cointegration tests); and Ability to read Chinese-language policy documents. Terms and Conditions for Appointment Successful candidate will be appointed on a temporary part-time contract. Benefits will be provided in accordance with the statutory provisions. To Apply Candidates who are interested in joining us may submit their applications via the University’s eRecruitment System. The personal data collected will be used for the purpose of considering your application for employment. For details, please refer to the “Personal Data (Privacy) Notice for Job Applicant” on the University’s website. If you are not contacted by the University within eight weeks from the closing date of application, you may assume that your application was unsuccessful.

Responsibilities

The appointee will conduct systematic literature reviews, collect and clean data, implement empirical analyses, and draft memos and figures for presentations. They will also build reproducible code and documentation.