Essays on dynamic adoption, demand estimation and survival analysis: Application to the U.S. seed Industry

Biotechnology has brought dramatic changes to the U.S. seed industry. This dissertation examines U.S. farmers' adoption decisions on genetically modified (GM) seed, their valuation of major GM traits in the market, and the product survival pattern of both GM and conventional seeds in the market.;The first chapter presents a dynamic adoption model with Bayesian learning. With application of my model to a sample of U.S. soybean farmers from 2000 to 2004, I find that farmers in my sample are more likely to be forward-looking decision makers and they tend to rely more on learning from their own experience than learning from their neighbors.;The second chapter provides a demand estimation on the U.S. corn seed. Using a hedonic approach, I estimate the demand for and supply of U.S. corn hybrids in 2007. The results show that farmers value GM traits positively, and they are more likely to switch to those corn hybrids with the same or similar GM traits when seed price increases.;The third chapter is a survival analysis on the U.S. corn seed market between 2000 and 2007. Applying an extended Cox Proportional Hazard model to all the corn hybrids in the U.S. market, I find that product characteristics and market structure variables have significant impacts on the survival rates of corn hybrids.