Major infrastructural investment, accelerated technology adoption and systemic societal changes do not occur without cost. Those costs may fall on the State, businesses, individuals, or indeed some combination of all. The allocation of resources at the State level to finance actions will ultimately then require a redistribution from other cost categories. These trade-offs are all too often ignored when calling on the State to invest and act. As a thought exercise consider whether a children’s hospital is more important than a safe road network, or a reduction in carbon emissions is more important than reliable water infrastructure. Decisions do not necessarily come down to these direct choices, and often the action is one of compromise and balance, however, these resource constraints cannot be ignored. As a solution, some will call on the State to introduce new taxes and charges, or to redesign existing ones. The former will involve a redistribution from the citizens – which is rarely popular. The latter can be a particularly powerful tool, however, the net resources available for investment will still face competition within the broader context of Government decision making.
Similarly, citizens may acknowledge the environmental merits of an electric vehicle, however, such an investment must be weighed up carefully against available resources, and the opportunity for a far cheaper vehicle to serve the same role, albeit with higher running costs and emissions. In the same vein, a business owner may recognise the value of buying new energy efficient lighting and computers, however, the available access to capital may be more productive if invested in a new team member, or a new tender proposal. In these ways, the costs, opportunities and present financial stability of the firm may be the dominant factors in a business owners mind, and the reason why other investments are deferred.
Indeed, an issue when rationalising cost and actions, is that quite often environmental costs are not fully priced into decision making activities. Thus, the savings associated with impact reduction may not carry adequate weight in the thought process of the decision makers. And whilst it is also true that many of the investments (e.g. energy efficiency) and actions (e.g. walking and cycling) can deliver savings and return benefits over time, the opportunity costs, short-term priorities and other transaction costs facing decision makers can serve to limit action. In brief, cost constraints can be overcome, but to ignore them when designing and calling for policy change, is to simply debase the credibility of the associated proposal.
Scale and Speed
The proliferation and penetration of new technologies into the marketplace can occur rapidly, however, there is no historical precedent for the breadth and scale of transformation required across sectors and societies to meet our myriad environmental goals under themes of climate, air, waste and water. In simple terms, whilst we might reasonably believe that in 100 years, all vehicles and home heating will be electric, and all power generation carbon free, we do not have 100 years to wait. Actions to displace polluting activities today, will deliver more in terms of emission reductions than those which happen tomorrow. Our current environmental targets and ambitions are generally defined in time horizons to 2030 and beyond, with annual objectives that would see us gradually transition to the target.
As such the timing, speed and scale of actions will have a substantial bearing on their impact and outcome. As an example, adding one million electric vehicles into the fleet in place of one million diesel vehicles in the year 2030, will deliver considerably less emission reductions than displacing 100,000 diesel vehicles a year from 2021. The national challenge then in this regard is how can we realistically accelerate technology and behavioural change to realise the benefits of change sooner.
Issues in relation to achieving the scale and speed of transition include the financial constraints for investment, the investment horizons of those required to act (e.g. those planning on moving are less likely to invest in their home), the ready availability of technology (e.g. access to electric vehicles) and labour (e.g. availability of experienced retrofitting professionals) to implement the change, and indirect constraints (e.g. limited electric vehicle charging infrastructure) which may dissuade rapid early adoption at scale.
The capacity to implement change can be considered under headings of political capacity, administrative capacity and operational capacity. In regard to political capacity, it must always be remembered that in our democratic society, Governments are elected to represent the interests of their electorate. Whilst certain sections of society may demand action on specific issues, these are not the only issues and demands facing elected officials. As such, the political capacity to implement change will depend somewhat on the political will and political capital available to drive through a given change in Government.
In terms of administrative capacity, it is also important to recognise that not all policy changes or measures can be easily managed and monitored. As an example, placing a ban on the burning of a certain fuel in the home is quite possible, but where similar fuels are OK to burn, the implementation and enforcement of such a restriction becomes more problematic.
Finally, there is the operational capacity to implement changes. In this regard we can consider national retrofitting targets, whereby a major constraint even after convincing householders to invest, is simply whether or not there are experienced professional teams available to deliver the work. In a case where the market moves from retrofitting 5,000 homes a year to 50,000 homes a year, there is certainly a skilled labour constraint to address in parallel.
Behavioural barriers can constrain individual pro-environmental behaviour and the uptake of policies aimed at reducing emissions and improving environmental outcomes. Peoples preferences aren’t always compatible with a welfare maximizing theory of behaviour. Indeed, actual behaviour deviates from expected behaviour in several systemic ways with the behavioural barriers imposed by present bias and prospect theory having significant implications for environmental policy.
Present bias describes the situation in which things that happen now are considered more important and given preferential weighting to things that happen in the future. This bias can lead to inertia and procrastination where there are immediate actions required for the individual to engage in pro-environmental behaviour. Transaction costs, such as researching, contacting contractors and applying for grants, which are tedious in the present may be over weighted when compared to the future benefits of making an energy efficient investment. The value imposed on these transaction costs can skew cost-benefit analyses, leading to investment being delayed or abandoned.
Kahneman and Tversky’s (1979) alternative to expected utility theory – prospect theory – implies a reference dependence to the individual decision-making process. Gains and losses from this reference point are assessed differently leading to people adopting a status quo bias or a preference for their current situation. In the context of environmental policy, and in particular the uptake of electric vehicles, this barrier can perpetuate range anxiety and the fear that electric vehicles are less reliable alternatives than the incumbent technology (petrol/diesel cars). Individuals will be less sensitive to the benefits of adoption than they are to the perceived losses and as such adoption can be constrained.
As a simplistic example, in a notional case where we expect the metro to have a 20% share of trips in Dublin … we must have a metro in place. On a less extreme level, where we seek substantial transitions to mass transit, we must recognise the capacity and constraints of those services and how quickly they can respond to the demand. The situation is the similar across other sectors. In order to maintain a stable electricity grid, we must manage the addition of renewable sources such that the power system has adequate capacity and coverage to operate. Similarly, the capacity for environmental performance improvements in the waste sector is heavily linked to the local and industrial infrastructure. Improvements in labelling regulations, individual recycling practices, waste collection and end of life processing infrastructure are all linked to performance on waste targets.
Complexity is yet another constraint in this context. As indicated under the headings above, there are many interlinked constraints that can present challenges to delivering change. Communicating the need for change to politicians, businesses and citizens, as well as explaining the underlying scientific and technological trade-offs can be difficult. As an example, in the agricultural sector there can be trade-offs between actions to curtail ammonia emissions (air pollution) over actions to address methane emissions (greenhouse gas emissions).
Consider also the reality of a cross-sectoral response to the threats posed by climate change. Throughout the world, the relationship between emissions and economic growth can be observed, the obvious inference being that increased growth increases the demand for energy and the amount of money individuals have to spend on consumer goods. Such increases in emissions correspond to rebound effects. These occur when improvements in energy efficiency are offset by changes in customer or producer behaviour. These happen both directly, where improvements in energy efficiency lead to the cost saving being spent on more energy and indirectly where this cost saving is spent increasingly on leisure or consumer goods which increase the individuals carbon footprint indirectly.
Thus, changes made to reduce emissions in one sector can lead to increases in another sector. Such affects are accounted for in emissions projections however making policies compatible with these long-time horizons is difficult. With numerous divergent paths, independent agents and cross sectoral implications, designing policy aimed at achieving targets, is a complicated process.