Reducing Swiss household energy demand: Modeling and assessing non-monetary incentives


Summary/Abstract

The Swiss Energy Strategy 2050 envisions a reduction of energy consumption per capita by 43% till 2035. This is an important but also highly ambitious element of the strategy. To achieve the reduction, influencing household energy demand will be important, as households decide about a substantial part of residential and mobility-related energy use (about 2/3 of final Swiss energy consumption). Household behavior can be influenced by monetary incentives but (potentially) also by individuals’ information levels and perceptions of (and responsiveness to) social norms, so-called “soft incentives”Two questions need to be answered in this context. First, what aggregate effects can be expected from soft incentives and, second, how can soft incentives be used in the most efficient way; is it, e.g., advisable to tailor such incentives to specific types of households or specific types of energy use. To answer these questions, two connected tasks are essential: (a) assessing the effects of soft incentives on behavior and on the performance of monetary instruments on the household level and (b) aggregating these effects to the national level. Both are non-trivial tasks, that require substantial research.In this project we will take up these challenges. First, we will provide an empirical assessment of the effects of social norms and information on different types of energy use for different types of households. This work will be based on SHEDS data and on municipal data for the specific fields of mobility and electricity demand. It will identify to what extent soft incentives can influence which type of energy demand for which type of household. Second, we will use the empirical results to develop a numerical model of household energy use that describes the influence of soft instruments on aggregate energy use and (where data permits) the interactions with monetary instruments. This model will cover feedback effects (formation of norms, diffusion of information) as well as the influence of policy measures. It will be based on a detailed description of energy use and household types and will be used to assess the aggregate effects of non-monetary measures in detail (i.e., effects on different types of households and energy use) and to design and analyze tailored measures that address specific household groups.


Project Report

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Related Publications/Research

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