Dr. Bill LaFayette is owner of Regionomics, a consulting firm focused on helping clients thrive in small-area economies. Services include economic development and workforce strategy, economic impact analysis, economic and demographic analysis, and fiscal analysis.
Prior to founding Regionomics in 2011, LaFayette spent 12 years as vice president of economic analysis for the Columbus Chamber of Commerce and four years with Rickenbacker Port Authority. He previously taught finance and real estate at Ashland University and the University of North Texas.
LaFayette serves on the boards of Employment for Seniors, the Affordable Housing Trust for Columbus and Franklin County, and the Mid-Ohio Regional Planning Commission. He is a member of the Columbus Metropolitan Club Program Committee.
A recognized authority on the Ohio and Columbus economies, LaFayette earned a doctorate in real estate economics from The Ohio State University in 1994. He also holds an Master in Business Administration in investment management and a Bachelor of Science, summa cum laude, in finance and accounting, both from Wright State University. He is a 2004 graduate of Leadership Columbus and the 2018 inductee into the Leadership Columbus Hall of Fame.
In his off hours, LaFayette enjoys 20th century concert music and collects popular, jazz and country recordings from the dawn of the talking machine more or less to the present.
In July 2020, Columbus City leaders commissioned an independent, outside after-action review of the City’s response to protests that took place last summer. Former U.S. Attorney for the Southern District of Ohio Carter Stewart and the John Glenn College of Public Affairs were named the lead investigative team.
In this study, published in Economic Development Quarterly, the authors present a statistically valid typology of high-growth firms, also known as gazelles, to determine if payroll and job growth patterns differ between groups or clusters.
This study, published in the Bulletin of the American Meteorological Society, presents an experimental design that overcomes the counterfactual problem present in all prior published experiments by relying on an actual storm with a known outcome.