UNDERSTANDING DISCOUNT RATES CAN IMPROVE POLICIES

Discount rates are a key factor in informing future energy policy decisions and are used in energy and climate modelling and associated impact assessments. Why is that? Energy efficiency measures (e.g. in buildings) typically have relatively high upfront costs compared with less energy efficient technologies, which need to be recovered by savings over longer periods. Time discount rates are thus used to attribute a value to future cash flows. The higher the time discount rate, the lower the value we assign to future savings in today’s decisions. Consequently, using high discount rates make energy efficiency measures and supporting policies appear less attractive.

To assess energy policies or decide on targets, policy makers often rely on findings from energy-economic models, which use implicit discount rates (or subjective discount rates) to govern investment decisions by households or companies in energy-economic models. Higher implicit discount rates typically translate into lower investments in energy efficient technologies. Yet, the factors underlying these discount rates are typically blurred. Likewise, little is known about their magnitudes, how they vary across individuals, technologies or countries, and how they change in response to policy interventions addressing external barriers, for example. A better understanding of the implicit discount rates and their underlying factors will improve the modelling of energy-efficient investments and thus provide better guidance for energy efficiency policy making and target setting.

THERE'S LINK, BUT HOW DOES IT WORK?

BRISKEE and CHEETAH provide a comprehensive framework for understanding the underlying factors of the IDR for household adoption of energy efficiency technology, based on empirical findings. This understanding can be used to design better policies that lower the implicit discount rates, and it can be used for more accurate energy-demand and macro-economic modelling.

BRISKEE analysed the factors underlying IDR and grouped them into three categories:  Preferences, Predictable (ir)rational behaviour and External barriers. It analyses empirically how energy efficient technology adoption is related to these factors. It also investigates how these factors are related to individual and household characteristics. CHEETAH analyses in particular how policies affect external barriers to energy efficiency, and whether household response to policies differs by individual characteristics and attitudes.