Professor Alan Barrett:

Let me begin by thanking the Chair for the invitation to appear before the committee today. I am Alan Barrett, the director of the ESRI and I am joined by my colleagues Dr. Kelly de Bruin and Dr. John Curtis.

This committee is considering one of most important challenges that Ireland faces and it is critical that the policy response to the climate challenge is well designed along a number of dimensions. Policies must ensure that we reduce our emissions of greenhouse gases to a level and within a timeframe that is consistent with our international commitments. However, policies should be least-cost so as to minimise the economic disruption and distributionally fair, whereby those most able to bear the costs do so. Ideally policies on climate action should also generate public support in part because public engagement will be important in achieving climate objectives.

In this opening statement, I want to give members a sense of the current work being conducted at the ESRI on climate issues. As is always the case with ESRI work, our goal is to provide evidence to guide policy formation primarily in the socioeconomic domain. Rather than commenting on the specific proposals of the Citizens’ Assembly, we hope to show how the impacts of proposals can be measured and how proposed policy can be designed most effectively. In these opening remarks and in our subsequent answers, we will generally try to restrict our comments to areas where we are undertaking research ourselves or where we are familiar with relevant research from others. Climate change is a broad area and we do not pretend to be expert on all dimensions.

Our current work in this area can be seen as two strands: modelling greenhouse gas emissions and the link to economic activity and analysing household behaviour with respect to energy. This two-way categorisation does not capture everything but it is a useful way to organise these remarks. Although I have not written it in the opening statement, I wish to note that most of our work in this area is co-funded by the Department of Communications, Climate Action and the Environment. The ESRI works very closely in partnership with the Department.

Looking first at our work on modelling greenhouse gas emissions, Dr. de Bruin, my colleague on the right, and another colleague, Dr. Mert Yakut, have developed an energy social accounting matrix, ESAM, model and have used it most recently to analyse the impacts of carbon taxes for the Department of Finance, yet another of our research partners. We will say a few words about the model to give members some sense of what is involved but will say more on the results of the carbon tax analysis. The results are important in themselves but in discussing them we also want to provide an insight into what can be done with the ESAM model.

The ESAM model reproduces the structure of the Irish economy including production sectors, households and the government and quantifies the nature of all existing economic transactions among diverse economic agents. Furthermore, the ESAM includes the flows of energy and emissions, creating a framework that can examine how money, as well as energy and emissions, flow between production sectors, households and the Government. In this way the carbon content of different products and different household’s consumption is estimated.

The current carbon tax in Ireland stands at €20 per tonne of carbon and is levied to incentivise households and producers to reduce their use of carbon-intensive goods. The carbon tax is relatively low, however, and constitutes just 1.9% of total taxes levied on commodities in Ireland. In the case of petrol, carbon tax accounts for 7.6% of total excise duties and, in the case of diesel, 14%.

Dr. de Bruin and Dr. Yakut find that a doubling of the carbon tax to €40 per tonne of carbon will increase the prices of carbon commodities by on average 3.4%. The diesel price is expected to increase the most due to an increase in the carbon tax, where a €40 tax would result in a 7% increase in diesel prices. Putting this into a context, it can be noted that in 2018 alone, consumers have faced much greater fluctuations in diesel prices. Consumers are accustomed to relatively large fluctuations in fuel prices and may not react to increases in prices, assuming prices will fall again. This makes it extremely important to communicate a clear commitment to an increasing carbon tax by the Government.

To gain a better understanding of which production sectors are most vulnerable to increases in the carbon tax, Dr. de Bruin and Dr. Yakut estimate the impact of a carbon tax increase on the production costs across sectors. They find that the natural gas supply sector as well as the transportation sector are impacted the most. Impacts on other sectors are small. Notably, the production sectors which drive Irish exports are relatively insensitive to a carbon tax increase, suggesting that an increase in carbon tax will not have a significant impact on the international competitiveness of Irish exports.

An important issue concerning the implementation of a carbon tax is its distributional impact across different household types. Dr. de Bruin and Dr. Yakut estimated the impacts of a carbon tax increase across income deciles. They found that the impact on the consumer price index, CPI, of the different households is virtually uniform, where a €20 increase in the carbon tax leads to the CPI of all households increasing by approximately 0.5%.

To examine the potential implication of a carbon tax increase on fuel poverty, they also examine the changes in households’ energy CPI. They find that energy CPI increases more among richer households due to a carbon tax increase. While the poorest households face a 2.9% increase in energy CPI for a €20 increase in carbon tax, the richest households face a 4.5% increase.

Heating consumer price index, CPI, on the other hand, shows slightly higher increases for the poorest households compared to the richest.

In monetary terms, a €20 increase in carbon tax would cost the poorest household €1.87 a week and the richest household €9.63 a week. When these costs are expressed in terms of income, they are found to be regressive, that is, the poorest households would lose a higher share of their income compared with the richest. There is a lot of detail there but I am trying to illustrate as much as anything else the richness of this analytical tool and the sort of things one can do with it.

In examining another important issue, the potential impacts of an increase in carbon tax on emissions reduction in Ireland, Dr. de Bruin and Dr. Yakut find that a doubling of the carbon tax will result in less than a 5% decrease in greenhouse gas emissions. This indicates a strong need for a more stringent carbon tax policy in combination with other policy levers.

I will now turn to the second strand of research, which is on household behaviour. Until somewhat recently, economists tended to focus on carbon taxes and similar policies in the belief that the price mechanism could solve environmental problems. This approach has a rich tradition in economics, starting in the 1920s with the Cambridge economist Arthur Cecil Pigou and continuing through the Nobel prize-winning Chicago economist Ronald Coase. Economists today continue to believe that incentives to encourage pro-environmental or carbon-friendly behaviours are important. However, they also tend to believe that financial incentives or prices are not the only things that matter.

Research undertaken by the ESRI on the Better Energy Homes energy efficiency grant scheme for residential buildings operated by the Sustainable Energy Authority of Ireland, SEAI, affords insights that are relevant to other areas of consumer behaviour. The research is based on more than 160,000 homes for which grant applications were made between 2009 and 2015 for the installation of cavity and attic insulation, boiler upgrades, heating controls and solar panels. Lessons from the research include the following. Financial incentives work; the very simple evidence for that is the 190,000 applications to the Better Energy Homes scheme between 2009 and 2018. It seems reasonable to state that many of those energy efficiency retrofits would not have occurred without the financial incentive. However, setting the right price is only one important element when encouraging changes in behaviour and other components are also important. For instance, over 15% of SEAI grant applications are abandoned, with this three times more likely to occur with deeper, more complex energy retrofits compared with simpler applications.

Increasing the financial incentive does not compensate for other barriers to behavioural change. In March 2015 the SEAI revised the grant scheme structure and offered bonus payments totalling up to €400 for households that opted for deeper retrofits, that is, installing three or four energy efficiency measures. The research found that the bonus payments had no measurable impact on grant applications.

Further research found that the structure of the financial incentives matters to households, that is, how the payment is made is important, for example, whether it is a cash payment or via a tax credit. Households strongly prefer cash payment subsidies rather than other indirect methods of financial support, roughly by a 70:30 ratio. However, the research also highlighted that households at different life stages have different views on what are the best types of support schemes.

Most policy focus in residential energy efficiency and carbon intensity is on owner-occupiers rather than the rental sector. The absence of measures targeted at the rental sector is often attributed to the split incentive, whereby the benefits of the investment in energy efficiency do not accrue to the person who pays for that investment, that is, the landlord. Our research on this issue found that rental tenants are willing to pay higher rents for homes with a higher building energy rating, BER. However, tenants’ understanding of BER and associated potential energy cost savings could be better, which in turn could influence their housing decisions and increase the demand for more energy-efficient properties.

These points are made in the context of energy retrofits but the same principles apply in other areas, such as incentives for electric vehicles. Policy interventions must be mindful of ensuring that financial incentives are complemented by other features of the programme which facilitate take-up.

I now wish to make some brief remarks on other policy themes where lessons from ESRI research apply. The Citizens’ Assembly, along with many others, made proposals on environment-related taxes which involve ring-fencing revenues and exempting lower income groups. Both approaches have typically not been favoured in ESRI research. In the case of ring-fencing revenues - or hypothecation - the argument has often been made that tax revenues should simply be added to the pool of State revenue and then spent in the area with the greatest yield. By limiting the scope of expenditure, which could include tax reductions, the usefulness of the revenues is reduced. Generally, hypothecation is proposed as a way to increase the public acceptance of a tax but in the case of many environmental taxes, the onus should be on policymakers to explain the purpose of the tax. That remark is partly directed at committee members as it is one of the responsibilities of the committee.

In regard to exemptions for low-income groups, ESRI researchers have argued that it is preferable to compensate lower-income households through the social welfare system. As environmental taxes are primarily aimed at providing an incentive to reduce certain activities, the effect of the tax is weakened if large groups are exempted. However, it is still important for some groups to be compensated. By increasing social welfare rates in line with environmental taxes, the compensation can be achieved while maintaining the incentives.

I also wish to comment on the proposal of the Citizens’ Assembly to prioritise spending on public transport over new road infrastructure. This may be a good idea but the ESRI would like to see careful appraisal work before endorsing the precise proposal of a 2:1 split. The key issue for us is that climate-related considerations be factored into the types of appraisal conducted by the Department of Public Expenditure and Reform in a way that fully captures the costs of inaction. If that is done properly, all public investment will have climate policy automatically embedded. An analysis may suggest that the ratio should be 3:1, 5:1 or 10:1 rather than the proposed 2:1 split but the ESRI would like to see the appraisal work.

I will conclude by making two observations. The cost of action in this area will almost certainly be greater under two conditions, namely, if we delay and if we exempt some sectors. Delaying will mean even greater actions are needed in the future, which will tend to be more costly. The exemption of sectors would put a great onus elsewhere, which again is likely to lead to greater cost.

The ESRI wishes the committee every success in its deliberations. We will be happy to assist the committee through our answers today and also in the coming months.