Narrow Results

Small business owners use a variety of bootstrap financing methods to acquire the needed resources necessary to survive and eventually grow their businesses. One such method is to lease equipment and/or machinery. Leasing is a viable alternative to bank financing and for small businesses, leasing is a flexible strategy to preserve cash. In this study, we analyze the impact of asset specificity and growth opportunities on leasing decisions of a large cohort of startup businesses. To test our hypotheses, we use a unique dataset provided by the Kauffman Foundation.¹ Our longitudinal analyses show that startups with unique/specific assets have a lower propensity to lease whereas startups with high growth opportunities are more likely to lease their assets. We also argue that the owners’ demographic and socioeconomic characteristics are likely to impact their individual risk-taking behavior. Thus, factors such as owners’ experience, education, age, gender, and race are likely to impact the decision to lease assets. Our results show that owners’ characteristics do have a significant impact on these decisions. The findings reveal that female and older entrepreneurs as well as highly educated owners are less likely to lease. Our work advances prior research on the determinants of leasing in large, publicly traded firms and provides additional insights on entrepreneurial bootstrapping.

The solution to climate change is simple: 100% CHEAP renewable energy. The important word here is CHEAP. If it was for climate morality only, California is the leader. In fact, California is likely the only State in the world to comply with carbon emission reduction goals (by installing renewables) as per the Paris Agreement targets for the year 2020. All other States and Countries in the world are reluctant to incur any costs to pay for carbon reductions. That’s why we have seen 30 years of political inaction on climate change (Losing Earth). It’s money…

We study the returns to leasing a New York Stock Exchange (NYSE) seat during 1995–2005 and find that these returns are a weighted average of past leasing returns and a set of fundamental factors such as average NYSE quoted spreads, the dollar value of NYSE trading volume, and the return on the overall stock market. Our partial adjustment model explains 70–80% of the variation in leasing returns and 80–85% of this explanatory power is attributable to a simple AR(1) process. Quoted spreads, trading volume, and stock market returns are all significant factors that positively affect leasing returns, albeit to a lesser extent than past returns to leasing. In addition, NYSE seat lessors rely more heavily on past values of these fundamental factors rather than coincident or forward-looking values of spreads, volume, returns, etc. This is in contrast to previous results on exchange seat prices which find that only unexpected changes in fundamental factors such as those noted above have a significant impact on exchange seat prices. In addition, unlike previous research on seat prices, which report that these prices follow a random walk, we do not find that leasing returns behave in this manner.

We examine sales and leasing of a durable good in an asymmetric duopoly. We show that the inefficient firm leases more than the efficient firm, and that an increase in unit costs implies a higher ratio of leased units to sales.