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| 1 |
ID:
150370
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| Summary/Abstract |
This paper applies a multi-criteria analysis (MCA) to evaluate public policy mechanisms that foster energy efficiency and renewable energy sources in the Greek building sector, based on stakeholders’ understanding and perceptions of the functionality of policy instruments. The objective is to shed light on the implementation of currently employed policy mechanisms that aim to achieve the 2020 energy savings targets and beyond, providing useful information to policy makers for future policy (re-) formulations. In this framework, policy instruments were evaluated against process-related criteria, such as implementation costs, distributional effects, and coherence of policy processes, so as to highlight successful policy practices during their implementation phase as well as to unveil cases of policy underperformance or unintended policy outcomes. To hedge uncertainties related to policy instrument selection, the method employs probabilistic evaluations of every alternative against each criterion. The MCA results showed that the country is still missing significant energy saving opportunities that could be reached through more streamlined implementation practices and political support. In times of fiscal crisis, the Greek government should also revitalize the implementation of alternative funding mechanisms and support policy alternatives such as green public procurement, voluntary agreements, and energy performance contracting.
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| 2 |
ID:
176724
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| Summary/Abstract |
This article explores technology ownership patterns to reveal adoption trends for energy efficiency measures (EEMs) in the Greek residential sector. To do so, we couple observational survey data with discrete choice modeling. Household preferences are revealed through EEMs owned by Greek householders, after having been questioned for a variety of end-use measures and details about their specification. Our results confirm prior evidence on traditional determinants οf technology adoption and extend those by validating that households familiar with information and communication technologies (ICTs) are more likely to own EEMs with smart features. We were also able to highlight the positive influence of participation in subsidy, as well as other support programmes for vulnerable consumers in households’ ownership of EEMs. Our results are then used to simulate the change in technology ownership rates, under no and full participation in a subsidy programme, for three income levels. Simulation outcomes suggest that, for almost all EEMs, the probability for technology ownership is greater for higher-income households benefitting from a subsidy. Nevertheless, the change in the probability of technology ownership due to the subsidy is larger for low- and medium-income households participating in the programme, further encouraging, thus, support for financial policies targeting lower-income households.
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