AUSTIN, Texas, June 3, 2016 ­– Studying consumer energy behaviors and choices through the agent-based modeling (ABM) approach can inform the design of better policies and programs, according to new research from the LBJ School of Public Affairs at the University of Texas at Austin.

Varun Rai, an assistant professor at the LBJ School of Public Affairs, looked at ABM as a tool for representing complex systems including behaviors of energy consumers – such as individual households – to examine how these decisions can inform the design of more effective policies for limiting the impact of climate change. Results, published in Nature Climate Change, show that ABM is a promising approach in informing and estimating the effects of such policies.

“The adoption of energy technologies is not limited to monetary factors such as price and performance expectations,” Rai said. “Consumer, or agent, choices are impacted by social norms, past experiences, perceptions of quality and trust. By studying these micro factors and choices among agents, we can better design macro policies and programs around the global climate. Agent-based modeling is a perfect tool for helping do just that.”

In contrast to non-ABM approaches, the ABM approach accounts for behavior, social interactions and physical and economic environments. In the ABM approach, individuals, households, formal organizations and even entire governments can comprise agents. Agent-based models typically look at agent decisions, which vary over agents and time, at the micro-level and how those decisions lead to macro-level outcomes.

The study was published online first at: