STRUCTURAL MODEL OF RENEWABLE ENERGY DIFFUSION: THE CASE OF SOLAR PHOTOVOLTAIC PANELS

Abstract

I STUDY THE DIFFUSION OF SOLAR PHOTOVOLTAIC PANELS AMONG HOUSEHOLDS. MORE SPECIFICALLY I INVESTIGATE WHY DIFFERENT HOUSEHOLDS ADOPT AT DIFFERENT POINTS IN TIME AND HOW UNCERTAINTY AFFECTS THEIR DECISIONS. I USE MICROMODELING APPROACH TO SHED LIGHT ON THE UNDERLYING ADOPTION MECHANISMS. I MODEL SOLAR PANEL ADOPTION BY FORWARD LOOKING HOUSEHOLDS AS AN INVESTMENT DECISION IN A TECHNOLOGY WITH UNCERTAIN PAYOFF. USING THE VISIBILITY OF ROOFTOP SOLAR PV PANELS FROM OUTSIDE, I INCORPORATE OBSERVATIONAL LEARNING AS THE MECHANISM FOR INFORMATION SPILLOVER ACROSS TIME AND ACROSS HOUSEHOLDS. I ESTIMATE THE MODEL USING A UNIQUE HOUSEHOLD-LEVEL DATA SET ON THE ADOPTION TIMINGS OF THE SOLAR PV PANELS IN GERMANY. I DEMONSTRATE THAT BY LEVERAGING THE OBSERVATIONAL LEARNING PHENOMENON, POLICY MAKERS CAN ADJUST THE TIMING OF THE INCENTIVE POLICIES IN ORDER TO MAXIMIZE THE DIFFUSION OF SOLAR PV PANELS. THE PROPOSED FRAMEWORK CAN BE ADAPTED TO OTHER SUSTAINABLE TECHNOLOGIES AND TO DIFFERENT GEOGRAPHICAL C