Predicting the effects of climate policies on energy use and the economy requires understanding how they will affect innovation. Yet, little empirical research exists in this area. This study helps fill the gap, using the number of relevant academic journal articles published per month as a proxy for innovation in wind and solar energy. Tens of thousands of articles are counted using Bayesian logistic classification methods. The first of three essays finds that solar and wind innovation increase with U.S. research and renewable energy production subsidies. Production subsidies are represented by the Production Tax Credit and Investment Tax Credit for renewable energy, taken together, whose effect on innovation has not been measured before. Wind and solar patents give similar results with respect to research subsidies but are too coarse a measure to identify tax credit effects, as described in the second essay. The third and final essay identifies articles on monocrystalline silicon and thin film solar panels, the two main types of solar energy research. Together, these essays provide new methods for producing article count time series; new data describing solar and wind innovation; parameters enabling future climate policy models to incorporate effects on innovation; and results suggesting direct and indirect U.S. policies have encouraged solar and wind energy research.