Renegotiation, Learning and Relational Contracting

This paper empirically examines contract renegotiation and learning in the movie industry under long-term business relationships. The paper develops a theory of renegotiation and learning with incomplete contracts. This theory shows how renegotiation as an ex-post mechanism to adjust participation constraints, together with learning, allows agents to maximize the value of the contractual relationship in the presence of incomplete contracts and long term relationships. The theory defines clear testable implications that I test in the paper. For this purpose, I use a new dataset of revenuesharing contracts and renegotiation outcomes in the Spanish movie industry. I find that movies that perform overall below expectations are renegotiated 20% more often. I find as well that movies are 6 to 8% more likely to be renegotiated in theaters where movie revenues are below the movie average revenues. Following this, I find evidence that economic agents learn across periods about the real movie audience appeal and use the new information to adjust their beliefs and make daily decisions. Finally, I conclude that contractual incompleteness is optimal in this case as long as learning allows firms to cut movie runs optimally.