Adverse Selection in Tax Credit Programs for Biotechnology and Other Technology Startups

Abstract

Politicians invest millions of public money in programs with the goal of creating new jobs in order to increase the overall wealth in their countries. While most State and Federal programs focus on small business without differentiating between high-potential startups and small businesses likely to remain small, the New Jersey Technology Business Tax Certificate Transfer Program (NOL) focuses on high-potential technology and biotechnology companies. Whilst there is recognition in business and research literature about the importance of early-stage companies in boosting economic growth and the necessity of government programs aimed at supporting them, in the literature there is little or no documentation of market failures occurring due to informational asymmetries. In this paper, we evaluate the effectiveness of the NOL program in creating high wage, high quality jobs in the state of New Jersey. Analyzing the level of wages and the number of jobs created by the beneficiary companies over a five-year interval, we focus on the difference in growth performance between biotechnology and other technology industries. Employing data provided by the New Jersey Economic Development Authority (NJEDA), we created a brand new panel database of beneficiary companies. Controlling per industry and per year, we find that the beneficiary biotechnology companies outperform the beneficiary other technology companies, pointing to an adverse selection bias due to asymmetric information in the pool of applicants.