Library Header Image
LSE Theses Online London School of Economics web site

Essays on household finance, venture capital, and labor

Hu, Zhongchen (2021) Essays on household finance, venture capital, and labor. PhD thesis, London School of Economics and Political Science.

[img] Text - Submitted Version
Download (7MB)
[img] Text - Supplemental Material
Download (2MB)
Identification Number: 10.21953/lse.00004271


In the first chapter, I study households’ insurance decisions against flood risk. Flooding is the most costly natural disaster in the US, yet policymakers are puzzled by the low take-up for flood insurance. I argue that households are affected by the low salience of flood risk. Leveraging novel transaction-level data, I use two empirical strategies to support my hypothesis. First, I exploit a staggered campaign that publicizes already freely-available flood risk information. Insurance purchases increase by 30.6% in response. Second, I exploit salient flood events shared through social media. Households purchase significantly more insurance after their geographically distant peers experience floods. My results suggest that behavioral frictions have a major impact on households’ insurance decisions. Chapter two studies the role of venture capitalists (VCs) in the labor market for entrepreneurs. There is an ongoing debate on whether VCs bet on ideas or founders. Prior studies find that successful startups often have kept businesses stable but replaced founders; however, practitioners see founders as more critical. This paper aims to rationalize the two views. I analyze new hand-collected data and find that VCs redeploy entrepreneurs across portfolio companies, highlighting VCs’ emphasis on human capital. I propose that VCs utilize private information about founders, and I show: (1) former VC partners continue influencing founders’ mobility; (2) the redeployment positively predicts VC performance; (3) the redeployment is stronger where information is more asymmetric. In the third chapter (co-authored with Ashwini Agrawal and Isaac Hacamo), we find that rank-and-file labor flows can be used to predict abnormal stock returns. Rank-and-file employees are becoming increasingly critical for many firms, yet we know little about how their employment dynamics matter for stock prices. We analyze new data from the individual CV’s of public company employees and find that rank-and-file labor flows can be used to predict abnormal stock returns. Accounting data and survey evidence indicate that workers’ labor market decisions reflect information about future corporate earnings. Investors, however, do not appear to fully incorporate this information into their earnings expectations. The findings support the hypothesis that rank-and-file employees’ entry and exit decisions convey valuable insight into their employers’ future stock performance.

Item Type: Thesis (PhD)
Additional Information: © 2021 Zhongchen Hu
Library of Congress subject classification: H Social Sciences > HC Economic History and Conditions
H Social Sciences > HD Industries. Land use. Labor
H Social Sciences > HG Finance
Sets: Departments > Finance
Supervisor: Jenter, Dirk and Agrawal, Ashwini

Actions (login required)

Record administration - authorised staff only Record administration - authorised staff only


Downloads per month over past year

View more statistics