Jacob T. Bradt

Consumer subsidies are a common policy tool for supporting the adoption of clean energy technologies. Policymakers often justify these programs as a means of stimulating infant industries, arguing that greater demand increases industry learning-by-doing, which in turn reduces costs for potential entrants. This requires learning spillovers between firms that make experience-based cost reductions a public good. However, spillovers can reduce firms' incentives to expand output and lower costs. To evaluate this tradeoff, I estimate a dynamic structural model of the market for solar panel installations in California that endogenizes firms’ entry and exit decisions and allows for learning-by-doing with knowledge spillovers. I find that a 1% increase in a firm’s cumulative production leads to a 0.7% reduction in installation-specific costs and that learning spills over across firms. Counterfactual analysis reveals that a state-level consumer subsidy program increased installer entry by 9%, indicating that industry cost reductions outweigh the decrease in firms' incentives to reduce costs by expanding output. While consumer subsidies may be effective at increasing industry size, I find that standard industrial policies such as entry subsidies provide greater welfare gains.

Flood protection infrastructure investments, such as Army Corps of Engineer levees, can enhance resilience to flood risks amplified by climate change. We estimate the benefits from levees by exploiting repeat residential property transactions. In areas protected by levees, home values increase 3 percent. Levees impose adverse spillover flood risks to nearby areas that reduce affected home values by 1 percent. Capitalized benefits in protected areas are progressive, but adverse spillover impacts are regressive. While there is little variation across race in capitalized benefits at levee construction, racial sorting occurs post-construction. Capitalized residential property benefits do not exceed levee construction costs.

Conventional recreation demand models assume that travel cost is exogenous. In reality, the costs that individuals face when choosing a recreation site to visit are the result of a spatial sorting equilibrium, which may be influenced by access to outdoor recreation sites and their environmental amenities. I explore the bias introduced by ignoring the potential for recreation sites and their attributes to determine travel cost in conventional recreation demand models and provide an instrumental variables approach to accounting for this endogeneity problem. I demonstrate the importance of accounting for the spatial non-uniformity of recreation sites and residences in a series of numerical simulations, finding that the instrumental variables approach ensures coverage of true parameter values. I implement the approach in a nationwide model of demand for overnight campground reservations as a function of price, water quality, and other observable site attributes. I find that not correcting for travel cost endogeneity via the instrumental variables approach nearly doubles estimates of consumers willingness-to-pay for improvements in water quality. This highlights the importance of relaxing the assumption of exogenous travel costs in real world applications.