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Recent years have seen a rapid expansion of interest in behavioural economics, which draws on ideas from psychology to shape economic theory. A burgeoning body of evidence – both from experimental laboratory studies and out in the field – suggests that behavioural insights can help to better explain observed behaviours. This observation considers three ways in which behavioural economics might be important for the design, implementation and reform of tax and benefit policy.
First, as we discuss in much more depth in new research funded by the Nuffield Foundation,* behavioural insights help in thinking about how people respond to policy. The way taxes and benefits are presented (even in seemingly trivial ways like their name) can have an effect on their impact: previous IFS research has demonstrated that Winter Fuel Payments are much more likely to be spent on gas and electricity than unlabelled income. People may also respond differently as policies become more complicated, perhaps because they resort to simpler rules of thumb to guide decisions when things become hard to process. For example, there is evidence that people confuse marginal tax rates (how much of the next pound earned will be taken in tax) with average tax rates (how much of everything earned is taken in tax) when deciding how much to work, perhaps because average rates are easier to understand if the structure of marginal rates is complicated.
Second, behavioural insights could help explain why tax reform is often hard to implement, despite the evidence set out in the recent Mirrlees Review of the likely benefits of sensible reforms. The Review made the case that policymakers should think about reform in the context of the whole tax and benefit system, when thinking about issues like progressivity or work incentives for example. However, experimental evidence has found that people suffer from a phenomenon known as ‘disaggregation bias’: a tendency to focus on individual components of something rather than the whole. Since taxes and benefits interact in a number of ways, reforms to the system inevitably involve changes to different component parts amongst which the big picture effects can be lost. For example, expanding the base of VAT and using other taxes and benefits to compensate low income households could help improve the overall efficiency of the tax system and leave it as progressive as before on average. But the regressive nature of the VAT reform in isolation would almost certainly be the focus of attention of such a change and make the package of reform less acceptable. Governments may respond to disaggregation bias on the part of voters, but policymakers may well suffer the same bias themselves since their attention is often focused on a single aspect of the wider system.
Behavioural factors can also mean that even small tax changes are sometimes hard to implement. The model of prospect theory suggests that people feel a loss much more acutely than a gain of equivalent size, and that the additional pain caused by larger losses gets smaller and smaller. As a result, lots of small tax increases could be perceived as more costly than a single big rise. This could help explain why tax escalators, which increase tax rates by a small amount year after year, have often not been implemented as planned. Similar issues might even have some resonance for why recent attempts to impose the full rate of VAT on (amongst other things) takeaway pasties and fixed holiday caravans (raising probably less than £100 million) failed, whereas a £12 billion increase in the VAT rate went ahead.
Finally, as the IFS has long argued, tax and benefit policy should be based as far as possible on good evidence. This is equally true in thinking about what behavioural insights mean for policy, and our research looks in detail at the evidence base. Some recent evidence has come from policy trials looking at the impact of ‘nudges’ which relate to aspects of tax policy. For example, HMRC and the Behavioural Insights Team at the Cabinet Office conducted an experiment with the wording of letters sent to people asking them to pay outstanding taxes. People receiving a letter telling them about compliance rates in their local area were much more likely to respond quickly than those sent a generic letter, suggesting a role for ‘social norms’ affecting behaviour. Such findings help us to understand the usefulness of behavioural insights in making aspects of tax policy more effective, and we applaud the growing use of controlled experiments in this way.
However, behavioural economics is not just about developing ways to nudge people, and our research makes it clear that these wider insights are important for tax and benefit policy more generally. The most pressing evidence gap relates to measuring the welfare costs of getting policy ‘wrong’ by not taking behavioural insights into account. For example, how much higher are optimal cigarette taxes if people cannot commit to giving up? Are back-to-work bonuses or benefit sanctions more effective to stop people procrastinating when searching for work and how large should they be? What will the new system of Universal Credit mean for people’s perception of stigma in the benefits system and take-up rates?
The challenge going forward therefore seems to be developing the evidence base to answer these sorts of questions. This will involve three elements: 1) carefully considering how behavioural issues might impact on policy at the design stage 2) ensuring that policy evaluation (as far as possible) allows us to disentangle potentially conflicting behavioural factors that might drive people to respond to interventions in different ways and 3) using the results to develop and refine theories of behaviour.
*The Nuffield Foundation is an endowed charitable trust that aims to improve social well-being in the widest sense. It funds research and innovation in education and social policy and also works to build capacity in education, science and social science research. The Nuffield Foundation has funded the project on which this observation is based, but the views expressed are those of the authors and not necessarily those of the Foundation or the Institute for Fiscal Studies. More information is available at http://www.nuffieldfoundation.org.
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Cutting the deficit: three years down, five to go?
The UK is in the fourth year of a planned eight-year fiscal tightening. Following further announcements made in Budget 2013, this fiscal consolidation is now forecast to total £143 billion by 2017–18. The UK is intending the fourth largest fiscal consolidation among the 29 advanced economies for which comparable data are available. By the end of this financial year, half of the total consolidation is expected to have been implemented. However, within this tax increases and cuts to investment spending have been relatively front-loaded, while cuts to welfare spending and other non-investment spending have been relatively back-loaded.
The March Budget forecast that borrowing would fall by £0.1 billion from £121.0 billion in 2011–12 to £120.9 billion in 2012–13. On Tuesday, the Office for National Statistics is due to release its first estimate of public sector net borrowing in March 2013 and, therefore, for the whole of 2012–13. Borrowing could easily end up being higher or lower than it was in the previous year, either due to backwards revisions, the uncertainty inherent in forecasting borrowing even a month in advance, or both. However, whether borrowing is slightly up or down in cash terms is economically irrelevant. Either way, the bigger picture is that having fallen by roughly a quarter between 2009–10 and 2011–12, borrowing is forecast to be broadly constant through to 2013–14.
Women working in their sixties: why have employment rates been rising?
Employment rates through the recession have been remarkably robust, with today’s ONS figures showing employment remaining close to 30 million. The young have experienced historically low employment rates and high unemployment rates but the employment rate of women aged 60 to 64 has increased as fast since 2010 as it did during the 2000s. An important explanation is the gradual increase in the state pension age for women since 2010, which has led to more older women being in paid work. Without this policy change, the employment rate for 60 to 64 year women would have been broadly flat since 2010.