ABSTRACT
Over the last several decades, the combination of critical fuel buildup and concomitant population growth in the wildland-urban interface (WUI) has made wildfire risk an emergent public policy issue across the West and elsewhere in the United States. Analyzing household risk mitigation behavior, including both averting actions and insurance decisions, requires microlevel data, which is of en difficult to obtain. For potentially catastrophic risks such as wildfire, large-scale policy experiments may be prohibitively expensive or politically unacceptable. To help fill in this information gap, experimental economics using laboratory markets with real payoffs can provide a low-cost way to examine how alternative institutional arrangements affect decision-making (McKee et al. 2004). As others have noted, economic experiments can provide a kind of “wind tunnel” for design and rapid evaluation in a fluid policy setting (Bergstrom 2003, 182).
