Partner
Orrick, Herrington & Sutcliffe LLP
Matthew's practice focuses on complex and innovative social, transportation and infrastructure projects across the United States, particularly alternative delivery projects (public-private partnerships (P3), design-build (DB) and progressive design-build. Matthew is recognized nationally and globally by Chambers USA, where clients describe him as “smart, organized and responsive and offers really good insight on key issues” and “he is an encyclopedia of PPP and he does an excellent job of leading tricky conversations and getting to a point where all parties agree.” Prior to practicing law, Matthew worked as a hedge fund analyst and chief of staff in New York State government. Matthew's prior experience in finance and government enhances his ability to deliver legal advice through a commercial lens for private and public sector clients. Matthew has advised clients across a full spectrum of energy and infrastructure assets, including telecoms, rail, highways, airport, intermodal transit, combined heat and power, social infrastructure, and waste to energy. In Matthew's capacity as outside counsel to the Association for the Improvement of American Infrastructure (AIAI) Matthew has also provided input on various key pieces of federal, state and local governments on the sufficiency of their laws to produce P3 projects in their jurisdictions.
From small projects to mega airport revamps, public-private partnerships are growing. As one more tool in the issuer toolbox, are there new opportunities to tap private capital given the priority shifts – and the continued support of private-activity bonds – in Washington?
Identifying what goes into the project delivery decision making process for owners is important. With the adoption of new alternative models to accommodate fluctuating market conditions, the number of delivery model options are growing. This session will engage in a conversation about how legal issues, schedule, finance, cash flow and long-term operations all play into the complex challenging decision-making process and help identify when certain delivery models are optimal.