Estimation and inference of willingness to pay for whale watching in the California coast

The central focus of this dissertation is on addressing unresolved problems with censored data in household-level nonmarket valuation surveys. We extend the literature on combining multiple data sources in order to better estimate models of willingness to pay for environmental improvements. We introduce a censored least absolute deviation estimator to estimate preference parameters consistently in the presence of pervasive censoring. We analyze household survey data on gray whale watching along the California coast and people's willingness to pay for increases in the stock of migrating whales.