Quantitative modelling of why and how homeowners decide to renovate energy efficiently

Understanding homeowners' renovation decisions is essential for policy and business activity to improve the efficiency of owner-occupied housing stock. This paper develops, validates and applies a novel modelling framework for explaining renovation decisions, with an emphasis on energy efficiency measures. The framework is tested using quantitative data from a nationally-representative survey of owner-occupied households in the UK (n=1028). The modelling advances formal representations of renovation decisions by including background conditions of domestic life to which renovating is an adaptive response. Path analysis confirms that three conditions of domestic life are particularly influential on renovation decisions: balancing competing commitments for how space at home is used; signaling identity through homemaking activities; and managing physical vulnerabilities of household members. These conditions of domestic life also capture the influence of property characteristics (age, type) and household characteristics (size, composition, length of tenure) on renovation decisions but with greater descriptive realism. Multivariate probit models are used to provide rigorous, transparent and analytically tractable representations of the full renovation decision process. Model fits to the representative national sample of UK homeowners are good. The modelling shows that renovation intentions emerge initially from certain conditions of domestic life at which point energy efficiency is not a distinctive type of renovation. The modelling also shows clearly that influences on renovation decisions change through the decision process. This has important implications for policy and service providers. Efficiency measures should be bundled into broader types of home improvements, and incentives should target the underlying reasons why homeowners decide to renovate in the first place

Energy Efficiency Choices and Residential Sector: Observable Behaviors and Valuation Models

Over the last decade, households’ preferences about energy efficiency measures in the residential sector have been the focus of a growing body research employing models based on revealed and stated preferences. Analysis of households’ energy consumption and demand elasticities were carried out before with the intent to forecast the potential of energy efficiency programs, but the recent concerns about climate change have drawn attention to the causes of this problem. As a result, the residential and renewable energy sectors have become strategic for the human being’s future. Different retrofit measures and technical solutions are now available for the new buildings, but the existing residential stock is more difficult to improve. More specifically, this implies the investment decision of heterogeneous groups of homeowners and landlords who differ in terms of the characteristics of their assets, their financial possibilities and time preferences. Valuation models have helped to forecast the demand of both market and public goods. Based on different approaches and theories, these applications have opened new avenues of research, but leaving some questions unanswered. This work tries to take stock of a debate that is still open by comparing experiments based on revealed and stated preferences in this specific field