Household recycling and behavioural biases
Recycling of household waste generates a host of benefits including lower greenhouse gas emissions from landfill, reduced depletion of scarce resources (land inclusive) and less of the unpleasant odours, sound pollution and visual intrusion associated with landfill sites.
Encouraging households to recycle more is also an important strand of the UK’s current waste management strategy. As per the Waste Framework Directive, the UK’s current target is to achieve a household recycling rate of 50% by 2020, with the UK having recently committed to recycling 65% of municipal waste by 2035 in line with the EU Action Plan for the Circular Economy.
Despite these targets, England’s current household recycling rate of 43.5% remains well below the 2020 target level and a significant upward deviation from trend will be required to achieve the longer-term ambition. The headline figure also masks significant disparities across local authorities (see chart) with England’s best performing local authority in 2018/19 (East Riding of Yorkshire Council) as high as 64.9% and its worst performer (Newham LB) as low as 16.9% for 2018/19.
So what factors influence household recycling performance? Traditional economic theory suggests that the decision to recycle may not even be rational; the opportunity cost – that is the cost in terms of time foregone and effort spent sorting and disposing of recyclable waste - is likely to be large relative to any personal environmental or monetary benefit a household receives in doing so. If households do in fact recycle then something else must therefore be at play.
Abbott et al (2013), in an empirical study using English local authority waste management statistics, focus on the role of two behavioural biases in the household decision to recycle:
Social norm - when individuals derive utility (pleasure) from converging to the behavioural patterns of a peer group e.g. local neighbourhood.
Warm glow – when individuals derive utility (pleasure) purely from the act of doing a perceived “good deed” (in this case recycling).
The study explored three measures of social norm, each of which were found to be a significant contributor to the household recycle rate; a higher household recycling rate for a local authority’s peer group predicts a higher household recycling rate for that local authority. Interestingly, the social norm effect was stronger when the peer group measured was constructed based on average age and ethnicity as opposed to geographic proximity.
The warm glow effect was also found be prevalent in household behaviour, with higher quality recycling provision increasing the time households spend recycling (one might expect better provision to make recycling more efficient and less time intensive).
The implication of this for local authorities is therefore that those which are best at activating social norm and warm glow behaviour in their constituent households may experience higher household recycling rates.
The existence of the social norm effect means that “visible” household recycling methods - such as kerbside collections - may be more effective in activating a social norm toward recycling than less visible methods. Additionally, raising awareness of the prevailing social norm could also be particularly effective at nudging people to change their behaviour – for example a targeted email from local authorities along the lines of “70% of people in your local authority aged 28-35 recycle 50% or more of their household waste”.
To activate warm glow behaviour in households, local authorities must work to limit the costs and frictions involved in the activity of recycling; be it through educating households on how to use facilities or improving the quality of recycling arrangements – for example optimising the combination of bin size, frequency of collection and number of recyclable materials collected.
Sources:
Abbott, A., Nandeibam, S., & O'Shea, L. (2013). Recycling: Social norms and warm-glow revisited. Ecological Economics.
Defra. Local Authority Collected Waste Statistics - Local Authority data