What is the potential for substitution from fossil fuels to electricity? I answer this question with microdata from the German manufacturing sector, where fossil fuels account for 70% of primary energy consumption. I document large heterogeneity in the shares of fossil fuels and electricity across plants even within narrow categories of plants. This variation is difficult to explain with observable plant characteristics including location, industry, or products produced, which suggests plants have flexibility in the mix of energy sources. Fossil fuels and electricity respond differently to transitory plant-level demand shocks: For a given change in output, the response of electricity is three times larger than that of fossil fuels. To reproduce this finding, I develop a dynamic model of production with an adjustment cost for fossil fuels. In such a model it is not optimal for plants to fully adjust to transitory shocks, leading to a downward bias in estimates of the elasticity of substitution with canonical methods. I estimate the model using the simulated method of moments, and find an elasticity of substitution of 5, substantially higher than the literature. This implies that a tax on fossil fuels is more effective: A given reduction in fossil fuel use can be achieved at half the cost in foregone output compared to a model with an elasticity from the literature. German plants can, thus, turn green.

Elasticity estimates are central to applied economics. A robust empirical finding is that long-run estimates exceed short-run ones. Under adjustment costs and stationary prices, agents optimally respond only partially to price shocks, attenuating short-run elasticity estimates below the structural long-run parameter. I derive a closed-form correction factor linking the two. It depends on three parameters: a calibrated discount factor, the persistence of the relative price, and the persistence of the input mix, the latter two estimable without additional data requirements. The persistence of the choice variable is a sufficient statistic for the adjustment friction, obviating structural estimation. I apply the method to intermediate input substitution in Indian manufacturing, and estimate a correction factor of 2.

I study the welfare effect of preemptive industrial policy against aggregate supply chain risk when entrepreneurs choose technologies subject to a collateral constraint and the government lacks commitment. Laissez-faire is constrained efficient: without intervention, technology choices are socially optimal given the collateral constraint. When the government cannot commit to a redistribution rule before agents choose, agents anticipate the planner's response and distort their technology choices, generating welfare losses that offset the direct benefit of redistribution. A welfare decomposition confirms that this distortion cost dominates the redistribution gain in a majority of empirically relevant parameterizations, so no-commitment intervention reduces welfare relative to laissez-faire. This reverses only for the case of an almost complete supply cutoff.