by Yves Zenou, Department of Economic, Monash University, Australia (This email address is being protected from spambots. You need JavaScript enabled to view it. ) We are the product of the choices we make but also of the people we meet. This is particularly true for me and for my research interests. Indeed, in August 1987, when I finished my Master’s Degree in Economics and Econometrics at the Université de Paris 10 (Nanterre), I was looking for a possible dissertation topic for a PhD. I had the chance to meet Gerard Ballot, professor at the Université Pantheon-Assas (Paris 2), who suggested that the analysis of spatial labor markets could be an interesting and challenging topic. I decided to embark on this journey, having for sole reference the seminal paper of Harris and Todaro published in American Economic Review in 1970. In my dissertation, I studied the spatial aspects of labor markets, both from theoretical and empirical perspectives. I defended my dissertation in December 1991. I then met Jacques Thisse, professor at CORE in Belgium, who really taught me how to do research. My intellectual debt to him is immense. We wrote several articles together on the theory of local and regional labor markets. Jacques introduced me to Masahisa Fujita and Tony E. Smith, the leaders of the regional science group at the University of Pennsylvania. For me as a junior researcher in 1995, working with Masa and Jacques, two well-established urban economists, was a very challenging experience. I learned a great deal from this collaboration. My meeting with Tony Smith was also decisive. He taught me the rigor of mathematics and the way to prove theorems. Simplicity, kindness, and complexity are certainly good ways of describing Tony. At that time, I also worked with Marcus Berliant who taught me mathematical tools I had never heard of before: differential topology. Diving into the world of general equilibrium with its infinite dimensions and manifolds was a very important experience. It helped me understand the way a general equilibrium is calculated and how one proves its existence and uniqueness. I then collaborated with Jan K. Brueckner who helped me fathom the way to write simple models in order to capture complex economic situations. After having had these different mentors, I was able to work on my own and collaborate with younger researchers. A large part of my research in Regional Science and Urban Economics has been to study the links between urban economics and labor economics. I believe that many key issues in urban economics can be analyzed in a new and deeper way when the labor market is introduced. In particular, the emergence of urban ghettos and its consequences for the labor-market outcomes of ethnic minorities is difficult to understand if the land and the labor market are not integrated. For example, there is an important empirical literature, revolving around the “spatial mismatch hypothesis”, which states that, because ethnic minorities are physically distant from job opportunities, they are more likely to be unemployed and to obtain low net incomes. Surprisingly, the numerous empirical works which have tried to test the existence of a causal link between spatial mismatch and the adverse labor-market outcomes of minorities are usually not based on any theory. In different papers, I could provide different mechanisms for the spatial mismatch hypothesis. My book, Urban Labor Economics, published by Cambridge University Press in 2009, summarizes all my contributions to this area of research. In 1998, while I was actively working on urban-labor-market issues, I had the chance to meet a young researcher, Antoni Calvó-Armengol, who was working on a new field in economics, namely network economics. I had to invest a lot in new mathematical tools, such as graph theory and discrete mathematics, to be able to enter this new area of research. Thanks to him I learned relatively quickly these tools and started to apply them to different aspects of the economy. Indeed, network economics analyses the economy not in isolation, but as part of the social structures that support it. Network economics looks not only at direct interactions between two people, but the ripple effect of interconnected links between their friends, friends-of-friends and so on. Topics such as crime sound more like sociology than economics. But a crucial difference is that network economics provides a mathematical model to interpret behavior and test relationships, allowing for predictions. Indeed, economics has always struggled to explain crime and that’s exactly the kind of problem network economics is designed to tackle. With Antoni Calvó-Armengol and Coralio Ballester, I have developed a concept called the “key player” that is useful in understanding and targeting criminal networks. Who is the criminal you want to remove from the network so you will reduce total crime the most? We have a mathematical model that can solve this question. To