This paper studies consumers' sensitivity to energy costs at the moment of making a long-term energy technology investment. The analysis exploits withinregion variation in local, regulated electricity distribution prices that are very persistent over time and therefore a good measure of long-term price expectations. Price impacts are estimated on extensive administrative registry data of private persons acting as home builders in Finland during 2006-2011. The results show that electricity prices notably influence builders' heating choices, and price increases that are mostly due to taxation have induced demand for technologies based on renewable energy. However, the results on the comprehensive set of observable individual-level characteristics imply that issues related to information and credit availability may hamper price sensitivity.
This paper studies consumers' sensitivity to energy costs at the moment of making a long-term energy technology investment. The analysis exploits withinregion variation in local, regulated electricity distribution prices that are very persistent over time and therefore a good measure of long-term price expectations. Price impacts are estimated on extensive administrative registry data of private persons acting as home builders in Finland during 2006-2011. The results show that electricity prices notably influence builders' heating choices, and price increases that are mostly due to taxation have induced demand for technologies based on renewable energy. However, the results on the comprehensive set of observable individual-level characteristics imply that issues related to information and credit availability may hamper price sensitivity.
This paper studies consumer heterogeneity in the valuation of lifetime heating energy costs. The valuation is expressed as the willingness to pay higher upfront costs to obtain savings over the lifetime of the heating system. The analysis relies on administrative register data on new residential houses built by private persons in Finland during 2010-2011. The data allow estimating the WTP as a function of several observable household characteristics. The median WTP in the estimation sample is e8, with a range of e2 to e15. Households with higher income and education are estimated to have higher WTP. Other characteristics that impact the WTP are household debt, family type and size, current dwelling status and previous experience of building a house.
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