When do high performers join startups? (job market paper)
Prior research offers contrasting views on when high performers are likely to join startups. On one hand, high performers face a higher opportunity cost of leaving wage work in early-stage startups encouraging later joining. On the other hand, high performers have higher upside in early-stage startups motivating them to join as early as possible. I resolve this tension by proposing
that personal liquidity constraints amplify the opportunity cost of leaving
wage work leading high performers with higher liquidity constraints to
join later stage startups. I formalize my theory with a simple real options
model and test it with contract-level data on the population of Finnish
startups and their employees. I exploit a home property tax reform as
variation in high performer liquidity constraints in a triple difference estimation and show that higher constraints lead high performers to join
later stage startups. As a supplemental analysis, I show how high performers deferring entry due to the tax reform negatively affected startup
performance. Read more...
Human Resource Redeployability and Entrepreneurial Hiring Strategy: Evidence from Finnish Microdata (3rd round R&R, SMJ)
The timing of talent acquisition is a central decision for new ventures. On one hand, starting small and hiring after demand is proven minimizes losses in case of low demand. On the other hand, hiring before demand is proven allows new ventures to start developing unique capabilities. We resolve this tension by proposing that the extent to which ventures hire before demand depends on human resource redeployability. We further argue that resource redeployability affects the type of employees hired. We test our theory with the population of Finnish standalone and portfolio ventures showing that portfolio entrepreneurs hire more employees early on because they have the option to redeploy them and that they hire employees with more transferable skills in order to benefit from the redeployment. Read more...
A general interindustry relatedness index
This is my R code for the general interindustry relatedness index of Bryce and Winter (2009). The code can be just as well used to generate the time-variant relatedness index of Cetorelli, Jacobides and Stern (2021). In my research, to compute this measure I make use of Finnish Patent and Registration Office's data on Finnish corporate groups. The dataset shows all the corporate group links between limited liability companies in Finland reported in official annual accounts. Based on these links, I calculate the frequency of joint occurrence of all two-digit NACE Rev.2 pairs in a corporate group and apply the frequency scores to portfolio ventures in my venture dataset. To GitHub...