Private Equity Research Consortium (PERC) is an assemblage of academic researchers and industry professionals dedicated to advancing research on private equity and credit. Our core mission is to develop a better understanding of how private capital investments affect both financial results and broader economic outcomes.
PERC, organized through IPC, was established in 2012 by scholars from the business schools at The University of Chicago, Duke University, UNC-Chapel Hill, University of Oxford, and The University of Virginia as well as other institutions who recognized challenges facing empirical research on private equity. PERC supports academic studies by researchers all over the world by facilitating access to data for scholars. For example, PERC has an exclusive arrangement with Burgiss to provide access to data for academic research. The Burgiss dataset includes 7,000 funds with over $5.5 trillion in assets. It is sourced directly from limited partners and contains full performance histories of cash flows at the fund level. The Burgiss dataset represents the largest and most in-depth dataset of its kind on venture, buyout, and real estate funds available for academic research.
PERC periodically accepts applications from academic researchers for access to Burgiss private equity fund data. The next deadline for proposal review is July 31, 2018 with a response date of August 30, 2018.
Latest Private Equity Research
Financial Intermediation in Private Equity: How Well Do Funds of Funds Perform?
This paper focuses on funds of funds (FOFs) as a form of financial intermediation in private equity (both buyout and venture capital). More
How Do Private Equity Investments Perform Compared to Public Equity?
The merits of investing in private versus public equity have generated considerable debate, often fueled by concerns about data quality. More
What Do Different Commercial Data Sets Tell Us About Private Equity Performance?
This paper examines private equity (both buyout and venture funds) performance around the globe using four data sets from leading commercial sources. More