Transaction costs analysis of low-carbon technologies

Abstract

Transaction costs (TCs) must be taken into account when assessing the performance of policy instruments that create markets for the diffusion and commercialization of low-carbon technologies (LCTs). However, there are no comprehensive studies on the development and application of transaction cost analysis to LCTs. In this meta-analysis, a wide-ranging evaluation of TCs associated with energy efficiency, renewable energy, and carbon market technologies is provided. There is a plethora of different definitions of, and measurement techniques to estimate, TCs. There is wide variation in the quantitative estimates, which can be attributed to factors such as the definition used, data collection, quantification methods, the type and size of technologies, the regulatory frameworks, the complexity of transactions, and the maturity of policy instruments. It is concluded that TCs are highly specific to both LCTs and policy instruments and that a common methodological approach is needed to avoid misleading policy analysis of the extant and future assessments.

Policy relevance

Transaction costs (TCs) accrued by, for instance, the search for information, due diligence, monitoring and verification (M&V) activities, must be considered in the design, implementation, and assessment of policy instruments. Such costs can have a negative effect on the performance of policy instruments aimed at the diffusion and commercialization of low-carbon technologies. It is shown here that TC analysis is mostly technology and policy context-specific and hence that it is not advisable to make generalizations about sources and estimates. The nature and scale of TCs are likely to differ due to a variety of endogenous determinants (e.g. size and performance of technologies), exogenous drivers (e.g. regulatory policy frameworks), and methodological aspects (e.g. quantification techniques). Several measures and strategies have the potential to reduce TCs, including standardized full cost accounting systems, an ex ante M&V approach, project bundling, and streamlining of procedures.

Keywords:

• carbon markets
• energy efficiency
• GHG emissions
• low-carbon technologies
• renewable energy
• transaction costs

Acknowledgements

We thank three anonymous reviewers for helpful comments and suggestions on an earlier version of the manuscript. Luis Mundaca would like to thank the AES Research Programme of the Swedish Energy Agency for financial support through grant no. 33684-1. The usual disclaimers apply.

Notes

‘Technological optimism’ is understood to mean that a growing number of technological improvements are sufficient to mitigate climate change by means of large-scale reductions in GHG emissions.

A recent bottom-up modelling study carried out by McKinsey & Co (2009) estimated that energy-efficiency improvements could reduce GHG emissions by up to 14 GtCO₂e per year – or nearly 40% of the global GHG abatement potential by 2030 – at negative net costs for investors. However, this study overlooks long-standing critiques of conventional bottom-up models, in particular the treatment of market and behavioural failures that impede the materialization of such potentials (e.g. negative externalities not reflected in energy prices, asymmetric and imperfect information about the performance and risks of mitigation technologies). The study does not discuss the rate of adoption or diffusion of new technologies and assumes that technologies deliver the estimated potential within ten years. A significant methodological aspect of the study relates to ‘full’ GHG abatement costs: initial equipment and operating costs (including energy saving costs) represent full costs. Transaction costs, however, are completely omitted. Compared to modelling studies that incorporate diffusion obstacles and market imperfections, the study overestimates efficiency improvements and resulting GHG emissions reductions (Murphy & Jaccard, 2011). Indeed, many of the differences between modelling studies – and much of the debate among technologists and economists – is related to the way that market and behavioural failures are treated (Hourcade et al., 2006; Huntington, Schipper, & Sanstad, 1994).

It should be stressed that no attempt is made here to revive the ‘market-failure debate’ about TCs, i.e. the stylized academic debate on whether TCs are an additional source of market failure and whether government intervention is required (e.g. Howarth & Sanstad, 1995; Jaffe & Stavins, 1994). A ‘market failure’ is defined as a flaw in the market that does not allow efficient or optimal allocation of goods and services. A behavioural failure is defined as a decision-making action by firms and consumers that leads to a divergence from utility/profit maximization goals.

‘Economic Agents’ or ‘Parties’ refer to the actors involved, e.g. government bodies, firms, consumers/households, public organizations.

Although TCs borne by public authorities are outside the scope of this analysis, it should be noted that TCs related to policy design and implementation (e.g. when searching for technical information) may be borne by authorities and not (entirely) by individual agents of parties. For instance in Great Britain, the Department for Environment Food and Rural Affairs (DEFRA) developed the ‘target-setting model’ to determine various energy-related aspects attributed to eligible energy-efficiency measures and supported the design and implementation of the Energy Efficiency Commitment (now known as the ‘Carbon Emission Reduction Target’ scheme; see Section 3.1.1). The model parameters used to develop the needed technical data included the number of electricity and gas customers, domestic fuel mix, fuel prices, estimated number of measures to be implemented, housing stock, current technological specifications, unit cost of measures, lifetime of measures, fuel carbon content, related carbon savings, and discount rate. All related TCs were borne by DEFRA.

Note that if the policy instrument(s) encouraging a LCT does not involve the trading of certificates, this potential category of TCs is not needed. In our taxonomy, we attempt to draw a distinction between TCs (e.g. search for information) that originate from technology implementation as such (i.e. search for project-based technical information) and TCs that originate from the trading of certificates in particular (e.g. search for trading partner).

In their study, ‘product information cost’ referred to the costs of making consumers aware of potential energy savings and establishing the amount of those savings; ‘vendor information cost’ referred to the cost to the vendor of informing the client; and ‘consumer preference’ referred to consumers’ limited cognitive ability to assess and gather information.

Under the FCEA, grid companies are obliged to conduct audits of organizations that consume more than 20 MWh of electricity annually. Audits are financed by end-users. The FCEA includes (1) a general overview, (2) analysis of findings, (3) development of savings plans, (4) follow-up, (5) report to the audited company, and (6) report to a common database. In 2003, expenditure on the programme amounted to €22 million (of which more than half was spent on energy savings measures; see Mundaca & Neij, 2006).

The EEC (now replaced by the ‘Carbon Emissions Reduction Target’ scheme) imposed an energy-saving quota on suppliers (gas and electricity) to the residential sector. The scheme allowed participants to trade certified energy savings as a means of cost-effectively reaching energy-saving targets set up by the authorities.

This was highly critical as insulation measures (100% subcontracted) delivered the most cost-effective energy savings, representing nearly 60% of total delivered energy savings.

Ostertag (1999) distinguishes between transaction costs as (1) ‘base price’, which includes administrative costs such as contract negotiation, information collection, monitoring of new installations, investment costs, fuel and electricity costs, repair, maintenance, insurance and rent costs, (2) ‘operating price’, which represents fuel delivery and electricity costs , and (3) ‘metering price’, which includes costs associated with the measurement and control of emissions, and the cost of standardizing metering equipment.

Note that under the EEC there was no M&V of energy savings. Energy savings, associated with well-known technologies in the residential sector (e.g. CFLs, cavity wall insulation), were estimated on an ex ante basis.

MRC (2004) estimated M&V-type TCs to be CA$3000–10,000 for the first year, and CA$2000–5000 for subsequent years.

In Sweden, the TGC scheme was introduced in 2002 and was more generally accepted than other economic instruments (Oikonomou & Mundaca, 2008). In the Netherlands the scheme was introduced in three phases, starting in 1998, on a voluntary basis for distribution companies.

Note that the initial design of the Swedish TGC scheme allowed electricity retailers to charge customers for the certificate-handling service they provided. However, it was found that a significant amount of money paid by end-users to suppliers did not in fact reach electricity producers (Kåberger et al., 2004; Nilsson & Sundqvist, 2007).

A project activity is defined as ‘a measure, operation or an action that aims at reducing greenhouse gases (GHG) emissions’ (CDM EB, 2003, p. 5). The Kyoto Protocol and the CDM modalities and procedures use the term ‘project activity’ rather than ‘project’. A project activity can therefore be a component or aspect of an undertaken or planned project.

Before ratification, some countries launched a pilot phase commonly referred to as ‘Activities Implemented Jointly’ (AIJ) in order to test the provisions of the Protocol.

Joskow and Marron's (1992) model compares the costs and savings of demand-side management programmes against known projections for the same types of costs and savings. Nilsson and Sundqvist's (2007) model measures TCs using the margin between the price electricity retailers pay for green certificates and what they actually charge to the end-user for the certificate service. The price–cost margin is defined as a function of risk, returns, and TCs. Krey's (2005) method estimates marginal carbon emissions reduction costs in relation to TCs. Mundaca's (2007b) analysis focuses on the cost of energy savings. Although similar to the approach taken by Joskow and Marron (1992), Mundaca's (2007b) method aims to quantify aggregated TCs based on the life cycle of energy-efficiency projects. However, unlike them, Mundaca (2007b) used actual residential energy prices to estimate net financial benefits for end-users.

Joskow and Marron (1992) discuss the limitations of their study and the impact on results in detail. They argue that costs are likely to be underestimated because of internal accounting problems and that energy savings (a critical factor in cost estimations) are likely to be overestimated. This provides an interesting insight into the factors that must be taken into account when carrying out studies in which the data collection and analytical methods present serious challenges.