Maria Claudia Lopez

Maria Claudia Lopez
  • Associate Professor
  • Feed the Future Innovation Lab for Food Security Policy
  • Community Sustainability

WEBSITE

https://www.canr.msu.edu/people/maria_lopez


BIOGRAPHY

Maria Claudia Lopez is an associate professor in the Department of Community Sustainability. Her research uses multiple methods, including field experiments from behavioral economics, institutional analysis, econometrics, ethnography, and participatory research, to understand how rural communities can collaborate successfully in the management of commonly held natural resources. She has done research in Colombia, Spain, Peru, Costa Rica, USA, Bolivia and Uganda. Before coming to MSU she was a Research Associate in the Institute of Behavioral Science at the University of Colorado Boulder. While there, she worked with an interdisciplinary group of researchers (ecologist, psychologists, economists and political scientists) developing a project aiming to understand how knowledge about how human decision making affects and is affected by changing forest conditions.  Before that, Maria Claudia was an assistant professor in her home country, Colombia. While in Colombia, she taught various classes at the undergrad and grad level. She also supervised several thesis (undergrad and grad level) in natural resource management, tourism, conservation and collective action.  Maria Claudia is an economist specializing in natural resources managment, environmental economics, experimental economics and collective action with a master's in rural development from the Universidad Javeriana in Colombia, and a PhD in Resource Economics from the University of Massachusetts, Amherst. She also completed a two year postdoctoral fellowship working with Elinor Ostrom at the Workshop in Political Theory and Policy Analysis at Indiana University on issues of governance, common property, and institutional analysis.


AREA OF EXPERTISE

  • Food Security Policy
  • Feed the Future Innovation
  • Urban Food systems in Flint, Michigan