Association for Public Policy Analysis & Management

Widespread adoption of solar photovoltaic (PV) is important as part of a portfolio of strategies to mitigate climate change, but it also has substantial impacts on a wide range of factors including grid regulation, utility cost-recovery, and land-use requirements. Agent-based models (ABMs) that are both empirically-grounded and that use rules derived from theory have great potential to explain macro-scale phenomena – such as spatiotemporal patterns of solar PV adoption – as the result of many interacting micro-scale decisions. The choice of theoretical lens has ramifications both in specifying the set of potential interventions and in identifying valuable targets for intervention. However, there is a plethora of options for theoretical lenses that serve to explain individual decision-making and it is not obvious what works best.

Rather than choose a single theoretical lens, we compare three ABMs with rulesets derived from different theoretical foundations. We examine the sensitivity of modeling outcomes and policy implications to these choices of theoretical lens, and uncover areas of overlap – where the substance of a policy recommendation derived from the model is similar across lenses, as well as blind spots – high-value intervention targets that appear through one lens but not through another. Understanding solar PV adoption as an emergent, evolving phenomenon allows policy-makers to anticipate future needs and impacts related to the energy transition; accounting for the choice of theoretical lens that leads to that understanding facilitates the design and implementation of robust policies in support of that future.