I grew up in Toledo, Ohio and attended the University of Toledo (UT) which was located a few miles from where my parents lived. I majored in economics and after completing an MA degree in 1977, I spent a year teaching as an instructor at Bowling Green State University (BGSU). While teaching at BGSU, I lived in an older mansion in Toledo that had been converted to an apartment house and I met my future wife Mary Ellen who lived in the same apartment house. We moved to Boston in 1978 where I began work on a PhD in economics at Boston College, with fields in econometrics and industrial organization. While working on my dissertation, Mary Ellen received a job offer to teach art in Toledo, so we moved back. I ran into a faculty colleague from BGSU while shopping who said BGSU was looking to hire an econometrician, so I applied and landed the job. My work on time-series econometrics led me to discover the wealth of regional labor market data, and a BGSU colleague, J. David Reed, introduced me to regional science which was a nice outlet for applied econometrics research based on regional data. I attended the Mid-continent Regional Science Association meetings in 1986 and 1987 with David Reed, and we co-authored work that was published in Journal of Regional Science, Regional Science & Urban Economics and International Regional Science Review. Around the same time a former professor of mine from UT, Michael Magura recruited me to work on a payroll tax revenue forecasting model for the City of Toledo as well as a metropolitan area leading indicator model for the Ohio Bureau of Employment Services. Magura was also a graduate of Boston College with a specialization in industrial organization, but I convinced him that regional science was an excellent outlet for our regional labor market forecasting work. We published work in Journal of Regional Science, Growth and Change, and Regional Science Perspectives. I attended the Southern Regional Science Association meetings for the first time in 1988 to present work with David Reed, and in this same year, Mike Magura arranged a faculty position in the economics department at UT. After a few years of daily commuting to UT from Maumee, a Toledo suburb, I convinced Mary Ellen to move to a house within a few blocks walk of my office at the university. This was no small task as we had spent six years restoring a historic house in Maumee built in 1840, that included an art studio addition. My daughter Rachel was born in 1987, making the location close to my office important for family reasons. Left to right: Badi Baltagi (Distinguished Professor, Economics, Syracuse University), Jim LeSage, Kelley Pace, Paul Elhorst and Yuxue Sheng (a professor at the Business School of Guangxi University, in Nanning, China) taken at LSU, Baton Rouge. My first attendance at the North American meetings of RSAI was in New Orleans, 1991, where I met Luc Anselin and discovered spatial econometrics. Luc’s 1988 book Spatial Econometrics: Methods and Models was very intriguing for someone trained in econometrics, as was his Cornell University dissertation which was available in the UT library. In his dissertation, Luc discussed application of Bayesian methods to spatial regression models. I was working on Bayesian time-series econometric methods at the time and Arnold Zellner assisted me in obtaining a visiting scholar position at the Minneapolis FED bank in 1993 where John Geweke helped me understand new Bayesian Markov Chain Monte Carlo (MCMC) estimation methods. John shared his FORTRAN code which helped greatly in understanding implementation of these relatively new methods first presented in a 1990 article by Alan Gelfand and Adrian Smith. I began working on spatial econometrics in 1992, but my first publication in this area was a 1997 article in International Regional Science Review on MCMC estimation of spatial regression models. Luc Anselin expressed skepticism in 1997 about MCMC estimation because it was computationally much slower than maximum likelihood estimation, but advances in computing technology over time have made MCMC estimation competitive and useful in a great number of spatial regression settings. The Spatial Econometrics Toolbox By 1998, I was using MATLAB software for teaching econometrics and used a Sun Microsystems workstation in my office to provide a web site for students to download code and data. The website was publicly accessible, but I did not think anyone but my students would be interested in visiting the site. One day I received an e-mail asking questions about my MATLAB code from someone outside the US, which prompted me to think about the issue of having the code publicly available for a few minutes. Thinking about the generosity of others who shared their code and ideas with me over the years, and Luc Anselin’s early attempts to provide spatial regression software, I decided to make my code freely available, which gave rise to the Spatial Econometrics Toolbox. Th