Larry S. Karp

International environmental agreements

In his research, Larry Karp has built a dynamic model of international environmental agreements (IEAs) where countries cannot make long-term commitments or use sanctions or rewards to induce cooperation. Countries can communicate with each other to build endogenous beliefs about the random consequences of (re)opening negotiation. If countries are patient, an effective agreement can be reached after a succession of short-lived ineffective agreements. This eventual success requires “sober optimism:” the understanding that cooperation is possible but not easy to achieve. Negotiations matter because beliefs are important. Mr Karp’s results help explain heterogeneous outcomes and also provide a counterweight to prevailing pessimistic views about the prospects for IEAs. An empirical application illustrates the importance of sober optimism in alleviating the problem of climate change, and it shows how a reduction in the fragmentation of the global polity makes it easier to coordinate on beliefs that support a good equilibrium.

Mr Karp’s current research interests focus on environmental policy, with an emphasis on climate policy. His previous research includes topics in trade policy, industrial organization and dynamic games. His three major current research projects involve: overlapping generations models (with Armon Rezai); instrument selection under asymmetric information (with Christian Traeger) and international environmental agreements (with Hiroaki Sakamoto).

Larry Karp is Professor in Agricultural and Resource Economics at University of California at Berkeley. Previously he was Assistant Professor of Agricultural Economics at Texas A&M University. He received a BA in Economics from UC Berkeley and a PhD in Agricultural Economics from the University of California, Davis. He is a member of the Editorial Board of the Review of International Economics and Associate Editor of the Journal of Economic Dynamics and Control. He is also a CESifo Research Network Fellow.