Research Affiliate at National University of Singapore. PhD candidate (economics) at Nanyang Technological University. I draw from simple applications of ML, NLP, and GIS in working with unstructured real-world data. My PhD thesis relates to political economy and the mass media.
This paper explores a novel and objective measure of political media slant using the aid of natural language processing and machine learning. Implementing this approach in the institutional context of Singapore, the paper finds that The Straits Times, the flagship daily, is less accurate when quoting the parliamentary speeches of opposition politicians.
In this paper, I exploit the institutional context of Singapore to estimate the effect of board gender diversity on firm performance using a sample from 2000 to 2017. To address endogeneity concerns, I instrument the number of women on board using the increase in women political participation and private firms' differential links to the government. The evidence suggest that having more women in the boardroom does not affect profitability, firm value, or systematic risk.
In this paper I download all tweets containing the MeToo hashtag in the year 2018 leading up to the midterm elections in November, and parse the geolocation tags of the tweeters. With the county level density measure of the tweets in 2018, I test whether the movement can explain the historic performance of women candidates in the 2018 U.S. House elections.
International Trafficking in Persons and Global Health Security: Evidence from Two Modern Pandemics
[Draft]
Does Working from Home Work? A Natural Experiment From Open-Source Software Development and Lockdowns
[Draft, Online appendix]
Detecting High-frequency Social Segregation in Singapore from GPS Records
(with LIM Jing Zhi)
The Political Economy of Clinical Trials and the Media Using Cellphone Data
Unexpected Shocks to Movement and Job Search: Evidence from COVID-19 Policies in Singapore Using Google Data
[Draft]
I use Python for my research work, and have benefited extensively from open-source libraries in the Python ecosystem. As a tiny contribution I wrote Leixcal richness, which I use to generate proxies for language sophistication in my research.
| Email: | lucas@lucasshen.com |
| lsys@nus.edu.sg |