Forecast evaluation report 2017
October 2017

CCS0917061442
ISBN 978-1-5286-0040-8

Office for
BudgetResponsibility

Forecast evaluation report

October 2017

Office for Budget Responsibility
Forecast evaluation report

Presented to Parliament pursuant to
Section 8 of the Budget Responsibility
and National Audit Act 2011

October 2017

© Crown copyright 2017
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ISBN 978-1-5286-0040-8
CCS0917061442 		10/17
Printed on paper containing 75% recycled fibre content minimum
Printed in the UK by the APS Group on behalf of the Controller of Her Majesty’s Stationery OfficeContents
Foreword.............................................................................................................................. 1

Chapter 1

Executive Summary.................................................................................................. 3

Chapter 2

The economy ........................................................................................................ 11
Introduction ...................................................................................................... 11
Forecast conditioning assumptions..................................................................... 11
The growth and composition of GDP ................................................................. 13
Developments by sector .................................................................................... 17
Box 2.1: Blue Book 2017 and dividend income .................................................. 18
Box 2.2: Fiscal policy and growth ...................................................................... 25
The labour market and productivity.................................................................... 27
Potential output................................................................................................. 32
Brexit-related judgements .................................................................................. 37

Chapter 3

The public finances ............................................................................................... 39
Introduction ...................................................................................................... 39
Forecasts since June 2010................................................................................. 39
2016-17 in detail ............................................................................................. 43
Box 3.1: Revisions to borrowing in 2016-17 ....................................................... 44
Box 3.2: The receipts to GDP ratio since 1986-87 .............................................. 48
Public sector net debt ........................................................................................ 67
Year-to-date borrowing in 2017-18 ................................................................... 68

Chapter 4

Refining our forecasts ............................................................................................ 71
Introduction ...................................................................................................... 71
Lessons learnt ................................................................................................... 71
Review of fiscal forecasting models .................................................................... 73
The 2017 review ............................................................................................... 76

Annex A

Detailed economy and fiscal tables ........................................................................ 85

Annex B

Comparison with past official forecasts ................................................................... 99

Index of charts and tables ........................................................................................................ 107

Foreword

The Office for Budget Responsibility (OBR) was created in 2010 to provide independent andauthoritative analysis of the UK public finances. Twice a year – at the time of each Budget and, until
2016, each Autumn Statement – we publish a set of forecasts for the economy and the publicfinances over the coming five years in our Economic and fiscal outlook (EFO). We use these forecasts
to assess the Government’s progress against the fiscal targets that it has set itself.
In each EFO, we stress the uncertainty that lies around all such forecasts. We compare our central
forecasts to those of other forecasters. We point out the confidence that should be placed in ourcentral forecast given the accuracy of past official forecasts. We use sensitivity and scenario analysis
to show how the public finances could be affected by alternative economic outcomes. And wehighlight uncertainties in how the public finances will evolve, even if one were to know withconfidence how the economy was going to behave – for example, because of uncertain estimates of
the cost or yield associated with new policy measures.
Notwithstanding these uncertainties – and the fact that no one should expect any central economic
or fiscal forecast to be met in its entirety – we believe that it is important to spell out our forecast in
considerable quantitative detail and then to examine and explain after the event how it compares tosubsequent outturn data. That is what we endeavour to do in this report.
We believe that it is important to publish the detail of our forecasts for two main reasons:•

The first is transparency and accountability: the whole rationale for contracting out the official
fiscal forecast to an independent body is to reassure people that it reflects dispassionate
professional judgement rather than politically motivated wishful thinking – even if people
disagree with the particular conclusions we have reached. The best way to do that is to ‘show
our working’ as clearly as we can.

•The second is self-discipline: the knowledge that you are going to have to justify your forecast
in detail forces you to make only those judgements you are willing to defend. You cannot hidethem in the knowledge that no one will ever know.

Assessing the performance of our forecasts after the event is also important for transparency andaccountability – and for helping users to understand how they are made and revised. Identifying andexplaining forecast differences also helps improve our understanding of the way in which theeconomy and public finances behave, and hopefully allows us to improve our judgements andforecast techniques for the future. We have taken that a step further this year through a systematic
review of key models that are used to help us construct individual lines of our fiscal forecasts. We
have also published a new briefing paper that describes how we evaluate our forecasts.

1

Forecast evaluation reportForeword

We describe the arithmetic divergence between our central forecasts and the subsequent outturns as‘differences’ rather than ‘errors’, because in many cases it would have been impossible to avoid
them given the information available when the forecast was made. Where we do find genuine
errors, which could have been corrected if we had spotted them, they are described as such. Errorsof this sort are inevitable from time to time in a highly disaggregated forecasting exercise like ours.
In judging our own performance – and in assessing the relative performance of different forecasters– it is important to remember that the current outturn data represent a relatively early draft ofeconomic history. The stories we have told in previous reports look different after subsequent datarevisions. So what appear to have been accurate or inaccurate forecasts today may look very
different in the wake of inevitable and often large statistical revisions. This was certainly theexperience of the recession and recovery of the 1990s and there continue to be significant revisions
to the history of the late 2000s recession and its aftermath.
We have continued the approach used in past reports of trying to understand the underlying
economic forces that have led outturns to diverge from our central forecast. But, as in previous
reports and the Treasury’s End of year fiscal reports that preceded them, we also present thedetailed decomposition of specific fiscal year forecasts. As with all our reports, we would be very
grateful for feedback on its content and for suggestions to improve future reports.
The forecasts we publish represent the collective view of the three independent members of the
OBR’s Budget Responsibility Committee (BRC). Our economy forecast is produced entirely by OBR
staff working with the BRC. For the fiscal forecast, given its highly disaggregated nature, we also
draw heavily on the help and expertise of officials from across Government, most notably in HM
Revenue and Customs and the Department for Work and Pensions. We are very grateful for thiswork and for the analysis that they have contributed to the production of this report. While
recognising these valuable contributions, we also stress that the BRC takes full responsibility for thejudgements underpinning the forecasts and for the performance of them presented in this report.
At the Treasury’s written request, and as provided for in the Memorandum of Understanding
between us, we provided the Chancellor and an agreed list of his special advisers and officials witha near-final draft of the Forecast evaluation report on 6 October. We also provided a full and final
copy 24 hours in advance of publication.

Robert Chote

Sir Charles Bean

The Budget Responsibility Committee

Forecast evaluation report

2

Graham Parker CBE

1

Executive summary

1.1

Twice a year at the OBR, we provide a detailed central forecast for the economy and the
public finances. These forecasts provide a transparent benchmark against which to judge
the significance of new economic and fiscal data and against which to estimate and explain
the likely impact of policy decisions. But since the future can never be known with precision,
all such ‘point’ forecasts are necessarily surrounded by uncertainty – the likelihood that any
given forecast will turn out to be accurate in all respects is essentially negligible.

1.2

We stress these uncertainties in every Economic and fiscal outlook (EFO) we publish. We
present probability distributions around our central forecasts based on past forecast
performance, sensitivity analysis of key assumptions and assessments of the fiscal
implications of different economic scenarios. And once a year, in our Forecast evaluation
report (FER), we compare the latest outturn data to our earlier central forecasts and seek toexplain the inevitable differences. This year we have stepped up our analysis of the risks
around our forecasts – and around long-term fiscal sustainability more generally – with the
publication of our first Fiscal risks report.

1.3

Throughout this report, we describe the arithmetic divergence between the central forecasts
and the subsequent outturns as ‘differences’ rather than ‘errors’, because in many cases it
would have been impossible to avoid them given the information available when theforecast was made. Where we do find genuine errors, which could have been corrected if
we had spotted them, they are described as such. Errors of this sort are inevitable from time
to time in a highly disaggregated forecasting exercise such as ours.

1.4

The backdrop to this report is:

1.5•

a real economy in which growth has slowed steadily over the past three years, withgrowth over the past year weakening as household real incomes and spending weresqueezed by higher inflation following the fall in the pound after the EU referendum;•a labour market that has continued to exhibit strong growth in employment, but weakgrowth in earnings and productivity; and•a falling budget deficit and a public debt to GDP ratio that has broadly stabilised once
allowance is made for the impact of the monetary policy easing following thereferendum, which has added to the headline public sector net debt measure.

This is our first FER to consider forecasts relative to outturn data that embody the initial
response of the economy to the Brexit vote and the start of exit negotiations. At this earlystage, it appears that the impact of a weaker pound on households’ real incomes andspending through higher inflation has been broadly in line with our post-referendum
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Executive summary

forecasts. Business investment data have been revised significantly – as is often the case –and now suggest that it slowed more sharply than previously thought in 2015 but has grown
at a moderate pace since then. There appears to have been a modest boost to net tradefrom sterling’s depreciation. Net inward migration has slowed, probably partly as the fall in
the pound reduced the value of UK wages in potential immigrants’ home currencies.

What questions do we seek to answer in this report?
1.6

The focus of this year’s report is an evaluation of our one- and two-year ahead forecasts for
2016-17. This means looking at our March 2015 forecast – the last under the Coalition
Government – and our March 2016 forecast – our last before the EU referendum. In termsof the economy, we explore why real GDP growth fell a little short of both forecasts andwhat we can learn from the composition of those differences – including what we can learn
about the initial effects of the referendum. In terms of the public finances, we ask why, on a
like-for-like basis, our March 2015 forecast proved to be optimistic – including the effect of
the higher public spending announced after the 2015 General Election – and why ourMarch 2016 forecast proved to be slightly pessimistic – despite the weaker real economy.

1.7

In Chapter 2, we also take a deeper look at trends in productivity growth and the labour
market. Once again we are faced with productivity performing more weakly than forecast,but employment and the average number of hours worked surprising to the upside. We also
draw some lessons for the judgement about the future path of potential output that we willneed to make in our forthcoming EFO, to be published alongside the Chancellor’s Autumn
Budget on 22 November.

Explaining 2016-17 forecast differences
1.8

Real GDP growth in the period up to mid-2017 was weaker than predicted in both ourMarch 2015 and March 2016 forecasts, but nominal GDP growth – which is the more
important driver of the public finances – fell short of our March 2015 forecast by a smaller
margin while it actually exceeded our March 2016 forecast. The composition of GDP is alsofiscally important because of the variation in which different elements are taxed:•

In expenditure terms, the shortfall in real GDP growth was dominated by the weakness
in business investment, which is fiscally favourable in the short term because it boosts
corporation tax receipts. But over longer horizons, weak business investment is fiscallydamaging since it reduces the productive capacity of the economy as a whole. Relative
to our March 2016 forecast, while consumer spending was a little weaker than
expected in real terms, that shortfall was more than offset by higher-than-expected
inflation to leave nominal spending – which drives tax receipts – higher than forecast.

•

In income terms, the nominal differences relative to both forecasts were broadly based
across the main components. Relative to both forecasts, average earnings growth was
weaker than expected while employment growth was stronger. Profits growth wasstronger than in both our March 2015 and March 2016 forecasts.

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Executive summary

1.9

On a broadly like-for-like basis – abstracting from the effect of classification changes – ourMarch 2015 forecast was too optimistic while our March 2016 forecast was too pessimistic:•

Relative to our March 2015 forecast, borrowing was £10.9 billion higher than
expected, with much higher-than-expected spending more than offsetting higher-thanexpected receipts. For spending, this was largely the consequence of significant
increases in departmental spending announced in the July 2015 Budget, which weretopped up further in the Spending Review in November 2015. Local authorities also
spent more than we forecast, drawing more than expected on their reserves andprudential borrowing to do so. Receipts were boosted by policy measures, including
raising rates of insurance premium tax and dividend tax, and the introduction of astamp duty surcharge on purchases of second homes and buy-to-lets. Corporation tax
receipts were also stronger than expected, but self-assessment income tax receipts
were significantly weaker.

•

Relative to our March 2016 forecast, borrowing was £2.8 billion lower than expected,
more than explained by higher-than-expected receipts. Unexpected economic
developments boosted receipts, as stronger profits and higher employment more thanoffset the effect of weak average earnings growth. Other receipts surprises werepositive too, including a variety of factors boosting onshore corporation tax receipts,
and smaller upside surprises in VAT and capital gains tax receipts. Spending was
higher than expected, with higher local authority spending and the effect of higher RPI
inflation on debt interest both raising spending compared with our forecast. A largerthan-expected departmental underspend and differences in the timing of EU payments
in calendar year 2017 were the largest factors acting in the opposite direction.

2016-17 data revisions and 2017-18 year-to-date outturns
1.10

Our FER analysis is carried out on the basis of the September vintage of the Office for
National Statistics (ONS) public finances data for 2016-17. One striking feature is the extent
to which it has been revised since the ONS published its initial estimate in April. The latest
estimate of the deficit is £7.0 billion lower than the initial one, with classification andmethodology changes accounting for £1.3 billion of that and the remainder attributable toa combination of higher central government receipts (£4.9 billion), lower central
government spending (£0.6 billion) and lower local authority borrowing (£0.2 billion).

1.11

On the latest estimate, borrowing in the first five months of 2017-18 was broadly flat
relative to the same period in 2016-17. Our March 2017 forecast predicted that borrowing
in the full year would be £58.3 billion, a £6.5 billion rise relative to our March estimate of
2016-17 borrowing but a £13.2 billion rise relative to the latest ONS estimate, following
the large downward revisions.

1.12

Our March forecast estimated that self-assessment income tax receipts would fall £3.9
billion on the previous year as a result of unwinding of the dividend income shifting that hadboosted 2016-17 receipts. As self-assessment is paid near the end of the fiscal year, thisexpected fall will not have affected the latest data. But some of the overall downward
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Executive summary

revision to the 2016-17 deficit over the past five months would, all else equal, be expected
to result in lower borrowing this year than forecast in March. The judgements we makeabout in-year receipts and spending are likely to be an important factor in our forthcoming
November forecast.

Productivity growth and the labour market
Productivity growth
1.13

One recurring theme in past FERs has been productivity falling short of our forecasts (Chart
1.1) while employment and average hours worked have exceeded them. That pattern isrepeated for both forecasts evaluated in this report and, based on revised GDP data andoutturns in the first half of 2017, will be repeated again for our March 2017 forecast.

Chart 1.1: Successive OBR productivity forecasts (output per hour)
120

Successive forecasts
June 2010

2009Q1 = 100

115

March 2017
Outturn

110

105

100

95
2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

2021

2022

Note: Solid lines represent the outturn data that underpinned the forecasts at the time (the dashed lines).
Source: ONS, OBR

1.14

Our rationale for basing successive forecasts on an assumed pick-up in prospective
productivity growth has been that the post-crisis period of weakness was likely to reflect a
combination of temporary, albeit persistent, influences. And as those factors waned, so it
seemed likely that productivity growth would return towards its long-run historical average.

1.15

The hiatus in productivity growth has now lasted for almost a decade, and some of theearlier explanations for its weakness seem less applicable today. For example, in theimmediate post-crisis period, labour hoarding in the face of temporarily weak demand wasa plausible hypothesis, but that became less appropriate once firms began hiring again.
Subsequently, we placed more weight on the hypothesis that an impaired banking system
had slowed the reallocation of resources to more productive uses. But the banking system is
now much better capitalised and more robust than it was in the immediate aftermath of theForecast evaluation report

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Executive summary

crisis, so this explanation no longer looks as relevant as it once did. More recently, as thelabour market has tightened, with the unemployment rate now at its lowest since the early
1970s, upward pressure on wage growth was expected to encourage firms to economise on
labour and to push through productivity improvements, but that has yet to happen. This
limited response of wage growth to emerging labour market tightness is an international
phenomenon that the IMF has addressed in its October 2017 World Economic Outlook.
1.16

Some other explanations remain relevant. For example, business investment has been very
weak since the crisis. Business investment today is just 5 per cent above its pre-crisis peakalmost a decade ago; in contrast, a decade after the 1980s and 1990s recessions,investment was 63 and 30 per cent higher than the pre-recession peaks respectively. This
sustained weakness in investment will have limited the contribution to labour productivity
growth from capital deepening.

1.17

The abnormally low level of interest rates could also be weighing on productivity growth byallowing weak and highly indebted firms to survive for longer than they normally would, byalleviating the burden of servicing their debts. This would lower productivity both through a‘batting average’ effect and by preventing the efficient reallocation of those resources tomore productive uses. Heightened uncertainty created by the Brexit vote may also haveencouraged firms to expand production by increasing inputs of relatively flexible labour
rather than less easily reversed investment in capital.

1.18

It is notable that the ‘productivity puzzle’ is not just a UK phenomenon. For instance, the US
Congressional Budget Office has made similar downward revisions to its productivity
forecasts, as have the IMF and the OECD in their forecasts for many advanced economies.
And weak investment and the impact of very low interest rates are plausible explanations formany countries. But it is also worth noting that some commentators have argued that theadvanced economies have entered an era of permanently subdued productivity growth forstructural reasons.

1.19

At the time of our March forecast, productivity growth had strengthened in 2016, averaging
0.4 per cent a quarter to leave productivity up 1.5 per cent in the year to the end of 2016,
but this has proved yet another false dawn. The renewed weakness of productivity so far in2017 may in part be a temporary effect of the Brexit vote and the uncertainty that it has
generated. But given the bigger picture – both over time and across countries – it is clearthat we will need to revisit our trend productivity growth assumptions again in November.

1.20

Our March 2017 forecast assumed that trend productivity growth would rise slowly to reach
1.8 per cent in 2021. Actual productivity growth averaged 2.1 per cent a year in the precrisis period, but has averaged just 0.2 per cent over the past five years. While we continue
to believe that there will be some recovery from the very weak productivity performance ofrecent years, the continued disappointing outturns, together with the likelihood thatheightened uncertainty will continue to weigh on investment, means that we anticipate
significantly reducing our assumption for potential productivity growth over the next five
years in our forthcoming November 2017 EFO.
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Executive summary

Labour market developments
1.21

The weakness of productivity growth has been accompanied by stronger-than-expected
employment growth, ongoing falls in unemployment (to 4.3 per cent of the labour force,compared with our March assumption of 5.0 per cent for the equilibrium, or sustainable,
rate of unemployment), and average hours rising a little rather than falling as assumed.
Strong growth in hours worked, alongside weak earnings growth, suggests that we will alsoneed to revisit our assumptions about potential labour supply. The Bank of Englandcurrently estimates that the equilibrium unemployment rate is around 4½ per cent. Given
the impact of weak earnings growth on people’s incomes, it may also be sensible to assume
that the long-term downward trend in hours worked takes longer to reassert itself.

1.22

We will be considering all the relevant evidence in detail as we prepare our November
forecast. Other things being equal a downward revision to prospective productivity growthwould weaken the medium-term outlook for the public finances, while a lower sustainable
rate of unemployment and more hours worked would strengthen it. The ONS’s downward
revisions to last year’s budget deficit would also be beneficial, to the extent that they feedthrough to future years. That said, the downward revision to productivity growth is likely tohave the largest quantitative impact.

Refining our forecasts
Lessons learnt
1.23

1.24

It is often the case that the lessons emerging from our FERs have already been acted upon
because they were identified during an EFO forecast process. In some areas, that has been
repeated this year. Lessons that have been reinforced include:•

the importance of the composition of labour income, in particular that employmentdriven growth has been less tax-rich than earnings-driven growth would have been;•savings associated with major reforms of the incapacity and disability benefits systems
had fallen short of expectations, due largely to challenges in delivering the reforms;•

the challenges in forecasting self-assessment (SA) income tax and capital gains tax
receipts, due to data limitations, the complex effects of behavioural responses to policychanges, the trend towards incorporations and shifts in the income distribution; and•the use of local authority reserves, which has been a repeated source of surprise
relative to our forecasts – in both directions – with the latest surprise being the extent towhich they were drawn down to support higher local authority spending in 2016-17.

There are also new issues and themes that have been identified in this year’s evaluation:•

The importance of corporation tax payment timing assumptions. The speed at which
companies pay off their liabilities arising from a particular year’s profits can have a

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Executive summary

marked effect on receipts. In addition, the surge in receipts from life assurancecompanies in 2016-17 suggests that we also need to look further at how the effect ofbond price movements on profits in the sector are modelled.
•

The unexplained downward trend in tax credits and in-work housing benefit caseloads.
In recent forecasts we have made successive and substantial downward revisions to tax
credits spending, with similar, if smaller, revisions to the in-work element of the
housing benefit caseload. This appears to be related to lower-than-expected inflows(rather than higher-than-expected outflows) and to average incomes across thecaseload rising faster than assumed. The underlying drivers of these forecast
differences remain under investigation.

•

The challenges and importance of the in-year estimates for receipts and spending thatform the basis of our fiscal forecasts. As most of our models are specified to forecast
the growth of a tax or spending stream from a starting point, any difference between
forecast and outturn for the year in progress when the forecast is made will compoundover the forecast period. We use the latest available data – including administrative
data – when making these estimates, but the pattern of receipts or spending throughthe year can change and subsequent revisions can change the picture significantly, as
has been illustrated clearly by the large revisions to 2016-17 since our March forecast.

Review of fiscal forecasting models
1.25

In preparing our fiscal forecasts we utilise more than 350 models of varying size andcomplexity. The outputs are scrutinised during forecast rounds and model development
work is undertaken between forecasts. This year we have introduced a more systematic
approach to following up our analysis of fiscal forecasting differences and the issues raisedin EFO forecasting rounds, working with our partners across government in doing so.

1.26

This review forms part of a broader process of model development. Over the past year, wehave moved to new models in a number of areas, including the incorporations model used
to adjust our income tax, NICs and corporation tax forecasts for the trend toward employees
and self-employed individuals incorporating, as well as the model we use to estimate theproportion of consumer spending subject to the 20 per cent rate of VAT. We plan to moveto a new North Sea revenues model in our November forecast.

1.27

We have reviewed 19 models in depth against the five criteria we set out last year (accuracy,
plausibility, transparency, effectiveness and efficiency). Informed by this, we have identified
some overarching issues that we plan to work on over the next year, including
supplementing our microsimulation models with top-down approaches, reviewing thebalance between short- and long-term dynamics in our econometric models and assessing
the impact of significant policy changes on the modelling approaches we use.

1.28

As well as these general conclusions, we have attached a high priority to development workon three forecasting models:9

Forecast evaluation report

Executive summary•

Onshore corporation tax: in recent forecasts we have repeatedly under-predictedonshore CT receipts. We will work with HMRC to review the main industrial,commercial and financial sector components of this model, including the econometricequations we use to project key income and deduction streams. We are also working
with HMRC to improve the transparency of the model and its outputs.

•

Self-assessment income tax: we have repeatedly over-forecast receipts in recent years.
This appears to be due to weakness in the effective tax rate, which has not been
captured by the model. We will therefore be considering alternative approaches tomodelling the effective tax rate. We will also work with HMRC and the ONS toinvestigate and better understand trends in the tax base and how these income
streams are captured in the National Accounts.

•

Universal credit (UC): as the rollout of UC accelerates over the next year, the spending
flowing through the system will rise significantly. We currently factor UC into ourforecasts as a marginal effect relative to the existing system rather than on a full-costbasis. This will become more problematic as outturn data will increasingly reflect UC
rather than the system that is being replaced. The shift to UC also involves a numberof complex changes in entitlement and the possibility that recipients’ behaviour willchange in response – e.g. take-up rates, error and fraud, and decisions about whether
and how much to work. Assumptions in all these areas will need to be reviewed as
evidence of actual effects becomes available. We will set out our latest UC modellingin detail in our next Welfare trends report, which will be published later in 2017-18.

Comparison with past official forecasts
1.29

In Annex B we compare the absolute size of our forecast differences to the average acrossofficial forecasts made in the 20 years before the OBR was created, although any
differences between our forecast record and that of the Treasury before us could be
influenced by many factors beyond the control of the forecaster in question. We have so far
produced 16 forecasts, but the sample that we can compare against outturns is still
relatively small – especially at longer time horizons. We can compare only seven of ourforecasts at a 4-year horizon and five at a 5-year horizon. And we have not yet had toforecast through a recession, which is typically when the largest differences arise – because
their timing and depth are so uncertain. For what it is worth, our forecasts for real GDP
growth and net borrowing have on average been more accurate than Treasury forecasts
were on average over the previous 20 years.

Forecast evaluation report102

The economy

Introduction
2.1

The focus of this year’s Forecast evaluation report (FER) is the performance of our March
2015 forecast (our last under the Coalition Government) and our March 2016 forecast (ourlast before the EU referendum). In this chapter we:•show how monetary policy and other market-derived assumptions have differed frommarket expectations at the time of our forecasts (from paragraph 2.2);•

explain how the rate and composition of real and nominal GDP growth have evolved
relative to our forecasts (from paragraph 2.5);•

assess developments in individual sectors of the economy (from paragraph 2.15),
including the impact of Blue Book 2017 changes on the household saving ratio (Box2.1) and the effects of fiscal policy on GDP growth (Box 2.2);•

consider movements in the labour market and productivity (from paragraph 2.31);•

discuss what these developments suggest for the level and growth of potential output(from paragraph 2.41) and consider the implications of this for our next forecast; and•evaluate the early evidence about judgements that we made about the effects of thevote to leave the EU on the economic outlook (from paragraph 2.57).

Forecast conditioning assumptions
Monetary policy
2.2

The Bank Rate assumptions underpinning our forecasts are based on market expectations at
the time, derived from the price of interest rate swaps. As Chart 2.1 shows, at the time of
our March 2015 forecast these implied that Bank Rate would rise gradually from 0.5 percent to around 1.2 per cent by early 2017. In the event – as has been the case repeatedly
since the financial crisis – Bank Rate was not increased during this period and these
expectations were pushed back. By March 2016, market participants had partially priced ina cut in Bank Rate, reflecting the possibility of a vote to leave the EU and the expectationthat that would prompt a monetary policy response. This proved to be the case.

2.3

In August 2016, the Bank of England loosened monetary policy to cushion the effects of an
expected weakening in GDP growth following the Brexit vote. The Bank’s Monetary Policy
Committee (MPC) judged that this would open up a margin of space capacity in the11

Forecast evaluation report

The economy

economy that would – after a temporary increase as the fall in the pound raised consumer
prices – have caused inflation to undershoot the 2 per cent target. 1 The MPC cut Bank Ratefrom 0.5 to 0.25 per cent and deployed a range of other tools: adding £60 billion in gilt
purchases and £10 billion in corporate bond purchases to its quantitative easing
programme and introducing a £100 billion Term Funding Scheme (TFS), which provides
relatively cheap funding to banks to encourage them to pass on the lower Bank Rate tocustomers. (The maximum size of the TFS has since been increased to £115 billion.)

Chart 2.1: Successive projections for Bank Rate
6

June 2010
March 2015

5

March 2016
March 2017

Per cent4

Latest3

2

1

0
Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
Source: Bank of England, OBR

Other conditioning assumptions
2.4

Our economy forecasts are conditioned on a number of other market-derived assumptions,
including oil, equity and government bond prices. These are important fiscal determinants.
Table 2.1 compares our March 2015 and March 2016 assumptions to subsequent outturns
for the second quarter of 2017:•

Oil prices fell in the second half of 2015 before recovering during 2016. Thesemovements were largely matched in the oil price futures curve. As a result, our March
2015 assumption was too high while our March 2016 assumption was too low.

•

Gilt yields have fallen well below the market expectations that we incorporated in both
forecasts, mainly reflecting subsequent expectations that monetary policy would remainlooser for longer. Lower long-term interest rates are also consistent with the market
pricing in weaker future UK growth prospects after Brexit.

1

The MPC’s full description of the trade-off it faced when setting policy at its August 2016 meeting is set out in its 4 August 2016
‘Monetary Policy Summary’.

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12The economy•

The sterling effective exchange rate index (ERI) started depreciating towards the end of2015 as market participants started to factor in the possibility of a vote to leave theEU. This would require a lower exchange rate to offset the loss of competivenessresulting from a less open trading relationship between the UK and the EU. Sterlingthen depreciated sharply immediately after the referendum as this possibility became a
reality. It has been relatively flat since then – fluctuating with changing expectations of
the form that Brexit, and the transition to it, will take.

•We assume that equity prices rise in line with nominal GDP from their value at the timeof each forecast. They fell between March 2015 and March 2016, but then rose quite
sharply in the second half of 2016 and early 2017, partly as the fall in the pound
boosted the sterling value of multinational corporations’ foreign-currency denominatedprofits. These companies make up a large share of the FTSE index.

Table 2.1: Conditioning assumptions for 2017Q2
Oil price($ per barrel)

Equity prices(FTSE All-share)

Gilt rate(per cent)

ERI exchange
rate (index)

March 2015 forecast
March 2016 forecast
2017Q2 average

71.4
41.5
50.3

4031
3419
4045

2.3
1.8
1.4

90.1
86.0
78.0

Difference1
March 2015
March 2016

-29.6
21.1

0.4
18.3

-1.0
-0.4

-13.4
-9.3

1

Per cent difference except gilt rate in percentage points.

The growth and composition of GDP
Real GDP
2.5

Chart 2.2 shows that we revised down our real GDP growth forecasts between March 2015
and March 2016, mainly as a result of weaker outturn data. GDP growth disappointed
relative to even this lower forecast over the first half of 2016, perhaps due to uncertainty inthe run-up to the EU referendum. In our November 2016 forecast, we expected GDP growth
to slow from the fourth quarter of 2016, as real incomes were squeezed by higher inflationon the back of the weaker pound. In our March 2017 forecast, we pushed this expected
slowdown back to the second quarter of 2017 as data at the time showed that growth wasstronger than we had expected in the two quarters following the referendum. On the latest
ONS data, the slowdown came in the first quarter – one quarter later than we thought inNovember 2016 but one quarter earlier than we thought in March 2017. By the second
quarter, the level of real GDP was 1.7 per cent below our March 2015 forecast and 0.9 percent below our final pre-referendum forecast of March 2016.

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Chart 2.2: Real GDP outturns and forecasts
107

March 2015
106

March 2016
2014Q4 = 100

105

November 2016
104

March 2017103

Latest
102
101
100
99
Q4
2014

Q1
2015

Q2

Q3

Q4

Q1
2016

Q2

Q3

Q4

Q1
2017

Q2

Note: Solid lines represent the outturn data that underpinned the forecasts at the time (the dashed lines).
Source: ONS, OBR

Nominal GDP
2.6

Public discussion of economic forecasts tends to focus on real GDP – the volume of goods
and services produced in the economy. But the nominal or cash value is more important forthe behaviour of the public finances. Tax receipts are driven more by nominal GDP and sois the share of GDP devoted to public spending, when a large proportion of that spending is
set out in multi-year cash plans (public services, grants, administration and capitalspending) or linked to consumer price inflation (social security and public service pensions).

2.7

Nominal GDP growth has held up better relative to our forecasts than real GDP because theGDP deflator – a whole economy measure of prices – has risen by more than we expected.
Between the end of 2014 and the second quarter of 2017, cumulative growth in nominal
GDP was only 1.0 per cent below our March 2015 forecast and was 0.7 per cent above our
final pre-referendum forecast of March 2016.

The expenditure composition of GDP
2.8

The composition of nominal GDP is also important for the public finances, since theeffective tax rates on the different components of income and spending vary widely. So inorder to assess the differences between our forecasts and outturns for the budget deficit, it is
helpful to examine how the different components of GDP have evolved.

2.9

The largest source of real and nominal downside surprise relative to both our March 2015
and March 2016 forecasts was weaker-than-expected investment (Tables 2.2 and 2.3).
Business and other private investment have made only small contributions to GDP growthsince the end of 2014. Real private consumption growth has also fallen slightly short of both
forecasts. Relative to our March 2016 forecast, the shortfall was more than offset by faster

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consumer price inflation as the unexpected fall in sterling increased the cost of importintensive goods and services leaving nominal consumption growth stronger than expected.
2.10

Relative to our March 2015 forecast, stronger-than-expected government spending offset
part of the downside surprises in private demand growth. This reflected the very sharp cutsin departmental spending that the Coalition Government planned at the time but which theConservative Government that took office in 2015 decided not to implement (as describedin Chapter 3). Government spending growth was close to our March 2016 forecast.

2.11

Net trade has reduced real GDP growth by less than we expected. The fall in the pound
resulted in significant upside surprises in both export and import prices. The difference has
been greater for export prices, meaning that the terms of trade – the volume of imports thatcan be purchased for a given volume of exports – has boosted nominal GDP growth relative
to our forecasts (Table 2.4).

Table 2.2: Contributions to real GDP growth from 2014Q4 to 2017Q2
Percentage points
PrivateBusiness
consumption investment

Other
Total
privategovernment
investment

Net trade

Stocks andstatistical
discrepancy

GDP

March 2015 forecast
March 2016 forecast
Latest data

4.5
4.2
4.1

2.1
1.1
0.5

0.4
0.7
0.2

-0.2
0.5
0.4

-0.8
-1.0
-0.2

0.1
-0.3
-0.7

6.0
5.2
4.3

Difference1
March 2015
March 2016

-0.3
-0.1

-1.6
-0.6

-0.2
-0.5

0.6
-0.1

0.6
0.8

-0.8
-0.4

-1.7
-0.9

1

Difference in unrounded numbers.

Table 2.3: Contributions to nominal GDP growth from 2014Q4 to 2017Q2
Percentage points
Privateconsumption

Privateinvestment

Total
government

Net trade

Stocks andstatistical
discrepancy

GDP

March 2015 forecast
March 2016 forecast
Latest data

6.9
5.8
6.5

3.5
2.6
0.9

-0.7
1.1
1.0

-0.5
-0.5
0.7

1.1
-0.6
0.0

10.2
8.4
9.1

Difference1
March 2015
March 2016

-0.4
0.7

-2.5
-1.7

1.7
-0.1

1.2
1.2

-1.1
0.6

-1.0
0.7

1

Difference in unrounded numbers.

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Table 2.4: Growth in National Accounts deflators from 2014Q4 to 2017Q2
Per cent
PrivatePrivateconsumption investment

Total
government

Exports

Imports

Terms of
trade

GDP

March 2015 forecast
March 2016 forecast
Latest data

3.5
2.3
3.5

5.4
5.0
1.3

-2.4
2.5
2.5

-4.5
-0.6
7.2

-4.7
-1.7
3.9

0.1
1.2
3.2

3.9
3.0
4.6

Difference1
March 2015
March 2016

0.0
1.2

-4.1
-3.7

4.9
0.0

11.7
7.8

8.5
5.6

3.1
2.1

0.7
1.6

1

Difference in unrounded numbers.

The income composition of GDP
2.12

In addition to breaking down changes in GDP between different categories of spending, we
can also break them down between different categories of income. This is even more
important for the public finances, given the amount of revenue raised from taxes on labour
income and profits and because these components face different effective tax rates.

2.13

Table 2.5 shows that the differences in nominal GDP growth from both our March 2015
and March 2016 forecasts were fairly broad based across income components. Later in thischapter, we look at labour income in more detail as its composition has further implications
for tax receipts.

2.14

Table 2.5 also shows a large contribution to the difference between the March 2016
forecast and outturn from the statistical discrepancy, which is the difference between the
ONS headline measure of nominal GDP and the income measure of GDP. This reflects thefact that a large discrepancy was being reported in the data at the time we made ourforecast, which is no longer apparent in the latest data.

Table 2.5: Contributions to GDP income growth from 2014Q4 to 2017Q2
Percentage points
Compensationof employees

Corporations'gross operating
surplus

Other
incomeTaxes onproducts andproduction

GDP

Statistical
discrepancy

March 2015 forecast
March 2016 forecast
Latest data

5.1
4.7
4.8

1.6
1.2
1.6

2.8
0.6
1.7

0.6
0.8
1.0

10.2
8.4
9.1

0.0
1.2
0.2

Difference1
March 2015
March 2016

-0.3
0.1

-0.1
0.4

-1.2
1.1

0.3
0.1

-1.0
0.7

0.2
-1.0

1

Difference in unrounded numbers.

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Developments by sector
Households
Income, spending and saving
2.15

Labour income 2 has grown faster than we expected in both the March 2015 and March
2016 forecasts, mainly as a result of stronger growth in ‘mixed income’ (a measure of selfemployment earnings). Wages and salaries growth has been much closer to our forecasts,
but its composition has been different with weaker average earnings growth offset bystronger employment growth. Average earnings growth provides a larger boost to income
tax receipts than employment growth because it pulls more income into higher tax brackets(a process known as ‘fiscal drag’). Nominal disposable income growth has been lower thanlabour income growth, partly as social benefits income growth has been weak due to falling
unemployment and the cash freeze on most working-age benefits.

Table 2.6: Income and consumption growth from 2014Q4 to 2017Q2
Per cent, unless otherwise statedNominalIncrease
Real
Saving ratio Adjusted
LabourNominalRealsavingdisposable
in price disposable(change, perincome consumption
consumption
incomelevel
incomecent)ratio1March 2015 forecast
March 2016 forecast
Latest data

10.8
7.3
7.9

9.4
10.0
12.0

10.6
9.0
10.0

3.5
2.3
3.5

7.1
4.9
4.3

6.9
6.5
6.3

-2.0
-1.0
-2.4

0.2
-1.6
-1.8

Difference2
March 2015
March 2016

-2.9
0.7

2.5
1.9

-0.7
1.0

0.0
1.2

-2.8
-0.6

-0.6
-0.2

-0.4
-1.4

-2.0
-0.3

1

Change in the saving ratio, excluding the adjustment for pensions (per cent).

2

Difference in unrounded numbers.

2.16

2

Despite the shortfall in nominal disposable income relative to our March 2015 forecast,nominal consumption growth was closer to forecast as the household saving ratio fell by
more than we expected – particularly when the effect of the National Accounts adjustment
for equity in pension schemes is excluded. While the saving ratio has fallen more sharply
than either forecast predicted, its level is now actually higher than forecast due to large
revisions in the 2017 Blue Book (Box 2.1).

Here we define labour income as wages and salaries plus mixed income less households’ social contributions.

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Box 2.1: Blue Book 2017 and dividend income
In recent years there has been a significant increase in the number of people setting themselves
up as single-director companies (‘incorporations’) rather than working as an unincorporated
self-employed worker or an employee. This is likely to reflect the tax advantages of doing so, as
well as underlying trends in the nature of work, as discussed in Box 4.1 of our November 2016
EFO. One implication is that a rising share of households’ income will have been received as
dividends from their own business rather than as wages and salaries or the mixed income
measure of earnings from self-employment.
Dividend income is a component of household disposable income and, as such, affects estimatesof household saving and net lending. Prior to this year’s Blue Book, the Office for National
Statistics (ONS) estimated the dividend income received by households using historical
proportions of household income. In the Blue Book, it moved to using HMRC data and forecasts(which in turn are consistent with our tax forecasts), to derive an implied level of dividend
income. The revised estimates should better capture the rise in incorporations. They imply amuch higher level of household dividend income than previously estimated (Chart A) and, since
they do not affect estimates of household consumption, a higher saving ratio (Chart B) and
improved household net lending position. The upward revision to dividend income is offset in a
downward revision to corporate net lending. The upward trend in incorporations means that therevisions to dividend income and household saving are larger in more recent years.

Chart A: Household dividend income
25
20

Chart B: Household saving ratio
14

Latest estimates
Pre-Blue Book 20171215

Per cent£ billion

10

10

8
6
4

5

2

0
97 99 01
Source: ONS, OBR

0
03

05

07

09

11

13

15

17

97

99

01

03

05

07

09

11

13

15

17

The path of dividend income is more volatile in 2016 and 2017 than in earlier years due to thelarge amounts of income shifting that occurred ahead of the pre-announced dividend tax rise in
April 2016 (discussed in Box 4.3 of our March 2017 EFO). The effect has been to raise dividend
income significantly in the 2015-16 tax year, and to reduce it subsequently. Household
disposable income is also reduced by the tax paid on this dividend income, which is generally
paid with a lag of around a year through the self-assessment system. These tax payments arerecorded in the National Accounts when the tax is paid, rather than accruing it to the point when
the dividend income was received. This timing difference is a key factor in explaining the very
low saving ratio in the first quarter of 2017, at which point dividend income was subdued
because some had been brought forward into 2015-16 but tax payments were boosted by thelagged payment of self-assessed tax on that shifted dividend income.

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Consumer price inflation
2.17

In March 2015, the annual rate of CPI inflation stood at zero – significantly below the 2 percent target the Government has set the Bank of England’s Monetary Policy Committee. At
the time, we forecast that CPI inflation would pick up gradually over the remainder of 2015
and into 2016, to averages of 0.2 and 1.2 per cent in those years respectively. But inflation
across this period came in lower than expected, largely due to falls in global food and oil
prices, on top of a moderate appreciation of sterling. This was reflected in unexpected falls
in fuel prices and in the food and non-alcoholic beverages category of the CPI.

2.18

Differences from forecast in the latter half of 2016 and so far in 2017 have been driven
primarily by the unforeseen depreciation of sterling in the run-up to and since the EU
referendum. Relative to our March 2016 forecast, this has resulted in large upside surprisesin the import-intensive components of the CPI. The impact of sterling’s fall was exacerbatedby a rise in global commodity prices, with food and beverage prices having increased byroughly 10 per cent in dollar terms since March 2016, while Brent crude oil prices haveincreased by more than 50 per cent in dollar terms over the same period.

2.19

We forecast RPI inflation using our CPI forecast plus our expectation for the RPI-CPI wedge. 3
So the differences between RPI inflation and our forecast are largely in line with those for
CPI inflation. In March 2016, we forecast the RPI-CPI wedge to average 1.0 percentage
points in 2016. In the event it averaged 1.1 percentage points, with a slightly higher
contribution than expected from mortgage interest payments.

Chart 2.3: Forecasts and outturns for CPI
6

June 2010
March 2015

Percentage change on a year earlier

5

March 2016
March 20174

Outturn3
2
1
0-1
Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017

Source: ONS, OBR

3

See Box 3.3 from our March 2015 Economic and fiscal outlook for our latest assessment of prospects for the RPI-CPI wedge.

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Housing market
2.20

In June 2016, the ONS introduced a new house price index based on data from the Land
Registry. Relative to the previous series, on which our March 2015 and March 2016
forecasts were based, the new index generally shows slower post-crisis rises in house prices,
but the differences are not large. Both forecasts proved slightly too low relative to the latest
data (Table 2.7), but the margin of difference is relatively small by historical standards.

2.21

In March 2015, we expected near-term property transactions to be depressed by the
restrictive effects of the Mortgage Market Review on lending. In the event, this proved overpessimistic as transactions increased sharply from the second quarter of 2015. They havebeen subject to policy-induced volatility recently, most notably the surge in transactions inMarch 2016 as buyers of buy-to-let properties and second homes sought to avoid paying
the 3 per cent stamp duty surcharge that was announced in Autumn Statement 2015 forintroduction in April 2016. We adjusted for this in our November 2015 and March 2016
forecasts, but significantly underestimated the magnitude of this ‘forestalling’. 4 Transactions
since the second half of 2016 have been much more subdued than we expected, perhaps
partly due to the uncertainty that has followed the referendum result.

Table 2.7: Growth in housing market indicators from 2014Q4 to 2017Q2
Per cent, unless otherwise statedHouse price growth

Property transactions

March 2015 forecast
March 2016 forecast
Latest data

14.1
15.1
15.5

5.9
7.7
2.9

Difference1
March 2015
March 2016

1.4
0.4

-3.0
-4.8

1

Difference in unrounded numbers.

Corporations
2.22

4

In March 2015, we expected business investment to grow strongly and to rise as a share of
GDP as normally happens in the later stages of a recovery. We also noted, as we often do,that business investment data are subject to potentially large revisions. By the time of ourMarch 2016 forecast, recent business investment growth had been revised up. But
investment intentions surveys at that time suggested that uncertainty about the EU
referendum was already leading to some capital spending decisions being cancelled ordelayed, which prompted us to revise our forecasts down. We did not make any further
referendum-related judgements beyond those implied by those survey indicators. In
November 2016, we revised down our business investment forecasts significantly due to theadditional uncertainty about investment returns created by the vote to leave the EU. ThisFor more information see: Mathews (2016): Working paper No. 10: Forestalling ahead of property tax changes.

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downward revision initially proved too great, with business investment reported to havebeen fairly flat through 2016 in the data available at the time of our March 2017 forecast.
2.23

In Blue Book 2017 the path of business investment in the run-up to and after thereferendum has been revised significantly. The previous vintage of data showed it falling byaround 1 per cent in the year to the second quarter of 2016 and flat in the year to thesecond quarter of 2017. The latest data show it falling 2½ per cent in the year before thereferendum then rising 2½ per cent in the year since. This illustrates once again thatbusiness investment estimates are very volatile and prone to significant revisions. The mostrecent estimates are slightly at odds with the investment intentions surveys that informed ourpost-referendum forecasts. 5 Demand uncertainty generally makes firms wary of engaging inlarger investment projects, which might prove difficult or expensive to reverse if the economy
does not perform as hoped. A significant factor in the latest data revisions was the path ofinvestment in aircraft, where use of a new data source suggests a sharp fall in purchases inthe year prior to the referendum and a sharp rise since. Given the long lags between
ordering and taking delivery of aircraft, this may reflect decisions made further in the past.

Chart 2.4: Forecasts and outturns for business investment
130

March 2015
March 2016
November 2016

2014Q1 = 100

120

March 2017
Latest

110

100

90
Q1
2014

Q2

Q3

Q4

Q1
2015

Q2

Q3

Q4

Q1
2016

Q2

Q3

Q4

Q1
2017

Q2

Source: ONS, OBR

2.24

5

Even on the revised data business investment has been significantly weaker than our prereferendum forecasts. By the second quarter of 2017, the shortfall in business investment is
6 per cent relative to our March 2016 forecast and 15 per cent relative to our March 2015
forecast (Table 2.8). Residential investment growth has been much closer to both forecasts.

For example, see Deloitte, The CFO Survey, Q1 2016.

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Table 2.8: Growth in real private investment from 2014Q4 to 2017Q2

March 2015 forecast
March 2016 forecast
Latest data
Difference1
March 2015
March 2016
1

Business
20.3
11.4
5.3

Per cent
Residential
12.6
9.7
12.1

Total
17.4
12.5
5.3

-15.0
-6.1

-0.5
2.3

-12.1
-7.3

Difference in unrounded numbers.

The external sector and net trade
2.25

In March 2015, we forecast significant pick-ups in export and import growth oversubsequent quarters. With import growth expected to outpace export growth, we forecast a
substantial negative contribution to GDP growth from net trade. In March 2016, we revised
down the expected pick-up in export growth by slightly more than import growth, in line withthe latest outturn data and a weaker outlook for UK export market growth. This meant that
we expected a slightly larger negative contribution from net trade.

2.26

In the event, while net trade reduced GDP growth, it has done so by less than we expected.
Relative to our March 2015 forecast, this was because export growth fell short of our
expectations by less than import growth. Relative to our March 2016 forecast, it was
because export growth was higher than expected and import growth lower. The fall in thepound through 2016 may have contributed to these differences but it is too early to assess
the full impact of the depreciation on trade. While the forecast differences for exports andimports in value terms were greater because of the effect of the depreciation on prices, thenet effect was in the same direction as the real net trade contribution, with the trade deficit
in the second quarter of 2017 narrower than expected.

Table 2.9: Growth in trade from 2014Q4 to 2017Q2
Per cent, unless otherwise stated
Net trade contribution
Imports(ppts)March 2015 forecast
March 2016 forecast
Latest data

10.0
7.3
7.8

11.8
9.9
8.1

-0.8
-1.0
-0.2

Trade balance in
2017Q21
-1.4
-2.4
-1.3

Difference2
March 2015
March 2016

-2.2
0.5

-3.7
-1.7

0.6
0.8

0.1
1.1

Exports

1
2

Trade in nominal terms, as a per cent of GDP.
Difference in unrounded numbers.

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2.27

Chart 2.5 shows how the current account and its components have evolved relative to ourforecast from March 2015. At the time, we expected the current account deficit to narrowgradually, mainly due to a shrinking of the income deficit as the rates of return on the UK’s
overseas assets recovered and as the trade deficit narrowed a little. In data available at thetime of our March 2017 forecast, these judgements appeared to be on track as the tradeand income deficits gradually narrowed. However, revisions in the 2017 Pink Book dataset
mean that the current account deficit is now estimated to be wider than previously thought.
The ONS changed its method for calculating the rate of return on UK corporate bonds. As asignificant portion of these bonds are held by non-residents and the new methodology
implies higher rates of return, this revision results in a significantly wider income deficit.
Current account data are another area where estimates are often revised substantially –trade in goods is mostly covered by timely and comprehensive data, but trade in services
and cross-border income flows rely on less timely responses to surveys and other sources.

Chart 2.5: March 2015 current account forecast differences-1-2

IncomeTransfers

Trade balance

March 2015 current accountPre-Pink Book 2017 estimate

Latest estimate

Per cent of GDP

-3
-4
-5
-6
-7
-8
Q4
2014

Q1
2015

Q2

Q3

Q4

Q1
2016

Q2

Q3

Q4

Q1
2017

Q2

Source: ONS, OBR

Government
2.28

Our forecasts for the economy and public finances incorporate the tax and spending plansset out by the Government at the time. In the March 2015 Budget, the Coalition
Government published plans for a sharp real-terms cut in public services spending between
2015-16 and 2018-19, although many observers doubted that it would be implemented.
The planned year-on-year fall in 2016-17 was particularly striking. On this basis, our March
2015 forecast included a reduction in government consumption in both real and nominal
terms between the end of 2014 and the latest quarter. In the post-election July 2015
Budget, the new Conservative Government significantly eased the cuts in departmental
spending that had been pencilled in four months earlier. As a result, we revised up our
forecasts for government consumption growth. By March 2016, we expected a substantial
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rise in spending in nominal terms. But even these revised forecasts proved too modest, withgovernment consumption rising by almost 5 per cent in nominal terms between the end of2014 and the second quarter of 2017 (Table 2.10).
2.29

In March 2015, again reflecting the spending plans sketched out by the Coalition, we
forecast that government investment would be flat in nominal terms between the end of2014 and the latest quarter. We revised that up significantly following the November 2015
Spending Review, when the Government increased its departmental capital spending plans.
Following significant revisions in Blue Book 2017, it now appears that the path ofgovernment investment has been closer to our March 2015 forecast than to our postSpending Review forecast of March 2016.

2.30

The arithmetic contribution of these government consumption and investment differences toour overall GDP forecast difference does not factor in all the ways fiscal policy affects
growth or any offsetting factors (e.g. if faster growth in government spending wereassociated with faster growth in imports). We use ‘fiscal multipliers’ to assess the overall
effect of changes in fiscal policy on growth. Our latest assessment of the assumptions wehave made is set out in Box 2.2.

Table 2.10: Growth in general government spending from 2014Q4 to 2017Q2

March 2015 forecast
March 2016 forecast
Latest data

Consumption
Real
Nominal
-1.4
-0.8
2.3
3.6
2.0
4.7

Per cent
Investment
Real
Nominal
3.6
0.1
1.8
13.9
1.4
3.2

Total
Real
-0.9
2.3
2.0

Difference1
March 2015
March 2016

3.5
-0.3

-2.2
-0.4

2.9
-0.3

1

5.5
1.1

Difference in unrounded numbers.

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3.1
-10.7

Nominal
-3.3
4.8
4.5
7.8
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The economy

Box 2.2: Fiscal policy and growthOver the past six years there has been a large discretionary fiscal tightening in the UK. Chart C
shows estimates of the additional tightening or loosening in each fiscal year, relative to a Budget
2008 baseline, as set out by the Institute for Fiscal Studies (IFS). This approach is based on
summing announced changes in tax and spending plans, so is an ex ante measure of
discretionary fiscal policy changes. The chart shows the plans for consolidation as set out in theJune 2010 Budget, plus the IFS estimates produced after the most recent Budget in March 2017.
While the year-to-year profile of consolidation differed from the June 2010 plans, the averageannual tightening was close to those plans (1.3 per cent of GDP a year from 2010-11 to 201516 versus the 1.4 per cent of GDP a year that was planned) The IFS’s latest estimates show asmaller-than-average tightening in 2016-17 and modest one in 2017-18 before the paceincreases sharply again in 2018-19 and 2019-20 due to planned cuts in current spending.

Chart C: Fiscal consolidation relative to Budget 2008 baseline
3.0

June 2010
2.5

March 2017

Per cent of GDP

2.0
1.5
1.0
0.5
0.0
-0.5
-1.0
2008-092010-11

2012-132014-152016-172018-192020-21

Source: IFS

To assess the impact of the path of fiscal policy on GDP growth, we use estimates of fiscal
multipliers, which are drawn from the available empirical literature. The estimates we use imply
that a discretionary tightening of 1 per cent of GDP would reduce output by between 1 per cent(in the case of cuts to capital spending) and 0.3 per cent (for income tax and NICs increases) in
the first instance. These were discussed alongside our first forecast in June 2010 and have beenreviewed a number of times since then.a
There is significant uncertainty around fiscal multiplier estimates, with much debate over whether
slow post-crisis growth could reflect higher or more persistent multipliers and a greater negative
effect from fiscal tightening on actual or potential growth than we originally assumed. Looking at
our GDP forecast errors relative to the profile of fiscal tightening, the evidence of that is limited.
Our assessment has been, and remains, that other factors were more likely to explain these25

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differences – notably the fluctuations in confidence and credit availability associated with thewaxing and waning of the euro crisis. As Chart D shows, other than 2011-12 – when fiscal
tightening was greatest and real GDP growth fell well short of our forecast – there is little
correlation between the scale of fiscal tightening and GDP forecast differences. Most clearly, thelargest growth shortfall relative to our June 2010 forecast comes in 2012-13, when the euro
crisis intensified but fiscal tightening was somewhat less than in previous years.

Chart D: GDP forecast differences versus the scale of fiscal tightening
IFS estimate of discretionary fiscal tightening (per cent)

3.0

2.5
2011-122.0

1.5

2010-112013-142012-131.0

2015-16

2014-15

0.5

0.0
-2
Source: IFS, ONS

-1

0

1

Difference in GDP growth from June 2010 forecast (percentage points)

We assume that these multipliers fall to zero over the medium term as the economy adjusts tothe effect of policy changes through a number of processes – including, for example, theendogenous response of wages and prices to fluctuations in the degree of spare capacity in theeconomy, as well as possible changes in monetary policy.
An important consideration is the rate at which the effect of tightening (or loosening) in any given
year is assumed to decay. We generally assume that the effect of a change in fiscal policy on
GDP will unwind over a period of five years, which means that the effect of the multi-year
consolidation on GDP growth in any year will reflect both the effect of new tightening in the year
and, working in the opposite direction, the ‘unwinding’ of previous tightening effects. Chart E
shows the impact of discretionary fiscal policy on GDP growth in each year between 2008-09
and 2021-22 based on the estimates in Chart C and an assumption that the impact tapers fromthe year of implementation. It suggests that in 2016-17 and 2017-18 the unwinding of previous
years’ effects more than offset that from new tightening in each of these years. As the pace oftightening picks up again in subsequent years, the implied impact of policy moves to a drag on
GDP growth of 0.3 percentage points in 2018-19 and 0.2 percentage points in 2019-20.

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26

The economy

Chart E: Implied impacts of discretionary fiscal policy on GDP growth
1.0

0.5

Per cent of GDP

0.0

-0.5

-1.0

Unwinding of previous years' tightening/loosening-1.5

Impact of fiscal tightening/loosening in that year
Total effect on growth-2.0
2008-092010-11

2012-132014-152016-172018-192020-21

Source: IFS, OBR

As noted, the estimates set out above assume that the multipliers start to ‘taper’ from the point of
implementation – the approach we used in June 2010 when the initial consolidation plans wereset. But when those plans were subsequently adjusted we assumed the effect would taper fromthe point of announcement. Tapering from implementation assumes that the effect of preannounced fiscal tightening is not offset by monetary policy or other factors in anticipation of
implementation; tapering from announcement assumes that the effect is at least partly offset.ba

See pages 95 to 96 of our June 2010 Economic and fiscal outlook, Box 2.4 of our October 2012 Forecast evaluation report,
Chapter 2 of our October 2013 Forecast evaluation report and Chapter 5 of our March 2014 Briefing paper: Policy costings and ourforecast for more details on the size and persistence of the fiscal multipliers that we use.
b

See Box 3.2 of our July 2015 Economic and fiscal outlook for a fuller discussion of this distinction.

The labour market and productivity
2.31

Developments in the labour market are important for the public finances. The level andcomposition of labour income are both key determinants of tax receipts, while on a muchsmaller scale the level of unemployment influences welfare spending.

2.32

Unemployment had been falling steadily in the run-up to our March 2015 forecast. We
expected the rate of decline to slow on the assumption that productivity growth would pickup from historically-low rates, allowing firms to increase output without having to expand
their workforce at as fast a pace. But in fact, unemployment continued to fall at a similarpace. By March 2016 we had revised our unemployment forecast down in light of this, but it
still fell faster than expected. Employment growth mirrored this pattern, rising faster than we
expected in both March 2015 and in our upwardly revised March 2016 forecast.

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2.33

In both forecasts, we also expected the long-term downward trend in average hours worked
to reassert itself on the assumption that a productivity-driven pick-up in average earnings
growth would allow households to work fewer hours while maintaining desired rates ofincome growth. In fact, average hours increased slightly between the end of 2014 and thelatest quarter. The combined effect of higher employment and average hours meant that
total hours worked increased much more quickly than we expected.

Table 2.11: Labour market indicators from 2014Q4 to 2017Q2
Change in thousands, unless otherwise statedTotal Unemployment
Participation
employment(LFS)

Average
Population hours
(per
cent)

Total hours
worked(per cent)March 2015 forecast
March 2016 forecast
Latest data
Difference1
March 2015
March 2016

632
827
1,131

-103
-204
-388

529
623
743

800
861
902

-1.0
-0.7
0.1

1.0
1.9
3.7

499
304

-285
-184

214
120

102
41

1.1
0.8

2.7
1.8

Memo: 2017Q2 levels

32,073

1,484

33,55752,740

32.2

1,034

1

Difference in unrounded numbers.

2.34

The fact that employment and hours worked were stronger than expected, while real GDP
growth surprised to the downside, has meant that productivity has fallen well short of ourrecent forecasts on both the output-per-worker and output-per-hour measures. Chart 2.6
shows that we have had to revise down our productivity forecasts repeatedly. With outputper-hour actually falling in the first half of 2017 on current estimates, the level ofproductivity is now at the same level recorded at the end of 2014. Indeed, it is only 0.5 percent above the level reached at the end of 2007, before the financial crisis struck.

Chart 2.6: Successive productivity forecasts and outturns
108

June 2010
March 2015

2014Q4 = 100

106

March 2016
March 2017104

Latest

102

100

98

96
Q4
2014

Q1
2015

Q2

Q3

Q4

Q1
2016

Source: ONS, OBR

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28

Q2

Q3

Q4

Q1
2017

Q2

The economy

2.35

Both the March 2015 and March 2016 forecasts assumed that average earnings growthwould gradually pick up towards the rates seen before the crisis, thanks to productivity
growth recovering. But repeating the pattern of recent years, wage growth has remained
weak. Average earnings growth fell short of both forecasts by around 2 percentage points
between the end of 2014 and the second quarter of 2017. Real wage growth fromconsumers’ perspectives (as measured by the real consumption wage, which deflatesearnings by consumer price inflation) was slightly less disappointing relative to our March
2015 forecast, as inflation was lower than expected over most of the period. Real wage
growth from a firms’ perspectives (as measured by the real product wage, which deflatesearnings by the gross value added deflator) has been even weaker than from a consumers’
perspective. While the real product wage has been slightly stronger than growth inproductivity per worker – suggesting that the labour share of income has risen slightly overthis period – the common weakness of the two suggests that they are related issues.

Table 2.12: Earnings, productivity and real wage growth from 2014Q4 to 2017Q2
Averageearnings

Productivity perhour

Per cent
Productivity per
workerReal productwage

Real consumption
wage

March 2015 forecast
March 2016 forecast
Latest data

7.7
7.2
5.6

5.2
3.2
0.0

4.1
2.5
0.1

3.2
3.8
1.1

4.2
4.6
2.8

Difference1
March 2015
March 2016

-2.1
-1.7

-5.2
-3.2

-4.0
-2.4

-2.1
-2.8

-1.5
-1.8

1

Difference in unrounded numbers.

2.36

Comparing the latest estimates for GDP growth and the labour market in the first half of2017 to our most recent forecast from March 2017 suggests that, after productivity growth
averaging 0.3 per cent a quarter through 2016, the pattern of weak productivity and strong
growth in labour inputs is repeating itself once more. Table 2.13 shows how real GDP
growth in the first half of 2017, relative to the second half of 2016, fell short of our forecast
by 0.4 percentage points (largely due to unexpected weakness in the first quarter). Onceagain, employment growth and average hours have surprised on the upside, eachcontributing an additional 0.4 percentage points to GDP growth in that period. But that wasmore than offset by the contribution of GDP-per-hour falling short by 1.2 percentage points.

Table 2.13: Contributions to GDP growth between 2016H2 and 2017H1

March 2017 forecast
Latest data
Difference1
1

GDP
1.1
0.7
-0.4

Percentage points
GDP per hour
Employment
0.8
0.2
-0.4
0.7
-1.2
0.4

Average hours
0.0
0.4
0.4

Difference in unrounded numbers.

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2.37

Chart 2.7 puts these latest forecast differences into context by plotting them alongside thesame decomposition for each of our previous March forecasts and our first forecast from
June 2010. The differences between our growth forecasts and the latest outturns show no
consistent pattern: four were too pessimistic, three were too optimistic and our March 2016
forecast matched the latest ONS estimate. But in every case productivity growth has fallen
short of our forecasts, while in every case employment growth has exceeded them. And
average hours growth has exceeded every forecast but one.

Chart 2.7: Contributions to year-ahead annual GDP growth forecast differences
43

Percentage points

2

Output per hour
Employment
Average hours
GDP

1
0
-1
-2
-3
-4
June 2010

March 2011

March 2012

March 2013

March 2014

March 2015

March 2016

March 2017** Annualised growth between 2016Q4 and 2017Q2
Source: ONS, OBR

2.38

Chart 2.8 puts the recent productivity growth shortfall into international context bycomparing growth in output per hour in 2015 and 2016 across the G7 group of majoradvanced economies with the OECD’s forecasts for them from November 2014. In every
case, productivity growth was weaker than expected, suggesting that the recent forecast
surprises we have experienced are by no means a purely domestic phenomenon.

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The economy

Chart 2.8: Average annual growth in output per hour in the G7 in 2015 and 2016
2.0

November 2014 OECD forecast
1.5

Outturn

Per cent

1.0

0.5

0.0

-0.5
CanadaFranceGermany

Italy

Japan

United Kingdom

United States

Source: OECD

2.39

To take one example, the Congressional Budget Office (CBO) in the US has also seen
productivity growth disappoint repeatedly relative to its previous forecasts. It has respondedwith successive downward revisions, as shown in Chart 2.9. While the CBO thinks that there
are some cyclical factors at play, they, like us, note that they do not fully understand thereasons for why trend productivity growth has slowed to this extent. 6 But, unlike in the UK –where productivity has moved sideways since the crisis – in the US, output per hour has stillrisen by almost 10 per cent since 2008.

Chart 2.9: CBO forecasts and outturns for US output per hour80

August 2014
January 201575

August 2015
January 2016

2008Q1=10070

August 2016
January 201765

June 2017

60
55
50
45
2000

2004

2008

2012

2016

2020

2024

Note: Solid lines represent the outturn data that underpinned the forecasts at the time (the dashed lines).
Source: CBO

6

For more information about the CBO’s forecasts, see CBO’s Forecasting Record: 2017 Update, October 2017.

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2.40

The renewed weakness of productivity growth over the first half of 2017 will almost certainly
have been exacerbated by the Brexit vote, notably by the temporary hit to real consumption
and GDP growth resulting from the fall in the exchange rate. But we cannot ignore theincreasingly lengthy period of weak underlying productivity growth, which is clearly in part a
global phenomenon. For that reason, we are minded to revise down significantly ourassumption for trend or sustainable productivity growth over the next five years in ourforthcoming Economic and fiscal outlook in November. We discuss this further below.

Potential output
2.41

Potential output cannot be observed directly so has to be estimated. When we consider it ineach FER we therefore look at how our forecasts and judgements have evolved over timeand how they compare with the relevant data on actual output growth and its components.
Judgements about the growth in potential output are the most important – and among themost uncertain – in our economic forecasts.

Potential productivity growth
2.42

Within potential output, the outlook for potential productivity is most important of all. Up
until March 2016, we had conditioned our forecasts on the assumption that the factors that
had been holding back productivity growth in the post-crisis period (whatever they might be)
would be temporary and would have faded completely by the end of the forecast period.
Consequently we assumed that potential growth in output per hour would return to ourestimate at the time of its pre-crisis average (2.2 per cent a year) by the final year of theforecast. (Revisions in the 2017 Blue Book mean that that average is now 2.1 per cent).

2.43

In March 2016, faced with another shortfall in productivity growth relative to our then latest
forecast, we decided to place more weight on the evidence of the post-crisis period. We
assumed that potential growth in output per hour would rise back to 2.0 per cent by the endof our forecast period – equivalent to a time-weighted average of the pre- and post-crisis
periods (i.e. a historical average excluding the crisis years of 2008 and 2009).

2.44

In November 2016, we revised potential productivity down again – this time on the grounds
that the Brexit vote and the UK’s subsequent departure from the EU were likely to create
greater uncertainty over investment returns and that this would lead some firms to cancel orpostpone some productivity-enhancing capital investment projects (i.e. slowing ‘capital
deepening’). On this basis, we revised potential growth in output per hour down to 1.8 percent by the final year of the forecast period. We did not assume that this effect would persist
over the long term, sticking with a 2.0 per cent assumption beyond the medium term in ourJanuary 2017 Fiscal sustainability report.

2.45

We did not change our trend productivity assumptions in March 2017, so potential growthin output per hour was still expected to pick up slowly – from 1.4 per cent in 2017 to 1.8
per cent in 2021. At the time, the latest data suggested that output per hour had grown by
0.4 per cent per quarter on average in 2016 and was up 1.5 per cent on a year earlier by
the final quarter of the year. Calendar year growth in 2016 was lower – at 0.5 per cent –Forecast evaluation report32

The economy

because of the base effect from the sharp fall recorded at the end of 2015. But, afterrevisions in Blue Book 2017, productivity growth in the 2016 calendar year has beenrevised down to 0.2 per cent and, as Table 2.13 showed, the first half of 2017 has seen
productivity fall rather than continuing the positive quarterly growth rates recorded in 2016.
2.46

As a result, Chart 2.10 shows that – despite successive downward revisions to our
productivity growth assumptions – our latest forecast implies a significant pick-up in
productivity growth from the latest data and much higher rates than the post-crisis average.

Chart 2.10: Productivity growth
8

March
2017
forecast

Output per hour
7

Average

FSR 2017 projection

65

Per cent

4
3
2
1
0
-1
-2
1972 1976
Source: ONS

2.47

1980

1984

1988

1992

1996

2000

2004

2008

2012

2016

2020

2024

2028

2032

The ‘productivity puzzle’ has been with us for a number of years now and several possible
explanations have been put forward to help explain it.7 Given the scale of the productivity
shortfall relative to the pre-crisis trend – around 21 per cent on the ONS measure – it seems
likely that most of these factors will have contributed to some extent at one time or another.
But what has been striking in recent years has been the way in which productivity growth has
remained stubbornly weak despite the easing of many of the factors that have been put
forward to explain it. In particular:•

Labour hoarding: in the early post-crisis period, it seemed plausible that firms might
be holding onto labour at the expense of maintaining productivity in the face of thetemporary extreme weakness in demand and output. But as the economy began torecover and hiring picked up alongside rising demand, that explanation quickly
became less plausible.

7

For more information about the ‘productivity puzzle’ and some of the possible explanations of its size and persistence, see ‘The UK
productivity puzzle’, Bank of England 2014Q2 Quarterly Bulletin.

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2.48

•

The state of the financial system: banks’ need to repair their balance sheets after thecrisis meant that the banking system was less efficient in its role in reallocating capitalfrom weaker to stronger firms. This meant that weaker firms weighed on productivity
growth for longer while stronger firms were unable to grow as quickly to boost it.
While some legacy crisis-related issues remain at some banks, the system as a wholeappears to be in much better health and credit availability is no longer constrained(thanks also to the Bank of England’s interventions). So this explanation, upon which
we had placed considerable weight at one time, also seems less plausible today.

•

Highly accommodative monetary policy: some have suggested that monetary policy
itself may be depressing productivity growth by allowing weaker firms to soldier onthrough alleviating the burden of servicing their debts, thereby slowing the reallocationof resources across firms. Based on market expectations for Bank Rate at the end of
September 2017, any future tightening in monetary policy is expected to be modest, so
if there is merit to this explanation it appears set to persist. 8•

Tightness in the labour market: more recently, as unemployment has continued to fall,
it was thought that a tighter labour market would put upward pressure on wage
growth and force firms to seek productivity gains rather than further expanding labour
input. The jury is still out on this explanation, but it is striking that the unemployment
rate has reached a multi-decade low of 4.3 per cent – and a variety of other indicators
point to a tight labour market – while average earnings growth has remained subdued
and productivity flat. The lack of effect to date could reflect lags in the process rather
than the process itself having broken down.

•

Weak investment: the fall in business investment – in both intellectual property andphysical assets – during the financial crisis slowed the pace of capital deepening andweighed on productivity growth. Business investment rose by almost 40 per centbetween the end of 2009 and the second quarter of 2015, meaning that this
explanation has received less weight more recently. But even after this rise from thepost-crisis low, business investment today is just 5 per cent above its pre-crisis peakalmost a decade ago; in contrast, a decade after the 1980s and 1990s recessions,investment was 63 and 30 per cent higher than the pre-recession peaks respectively. Ifbusiness investment remains weak then this factor should continue to reduce
productivity growth relative to the pre-crisis period.

As the period of historically weak productivity growth lengthens, it seems less plausible toassume that potential and actual productivity growth will recover over the medium term to
the extent assumed in our most recent forecasts. Over the past five years, growth in output
per hour has averaged 0.2 per cent. This looks set to be a better guide to productivity
growth in 2017 than our March forecast of 1.6 per cent (although the cyclical-structural splitof the latest performance is uncertain).

8

For more information about the possible effect of monetary policy on UK productivity, see ‘Productivity puzzles’, Speech by Andy
Haldane, 20 March 2017.

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The economy

2.49

Looking further ahead, it no longer seems central to assume that productivity growth will
recover to the 1.8 per cent we assumed in March 2017 within five years. Indeed, it is worth
noting that some commentators have argued that advanced economies have entered an eraof permanently subdued productivity growth for structural reasons. 9 We will take a final
decision in our November forecast, based on all the information available at the time, but
we expect to lower our forecast for cumulative potential productivity growth significantly overthe next five years, without going so far as to assume that there is no recovery at all from thevery weak performance of recent years. It is important to emphasise that whatever revision
we make it will not have been driven by the most recent quarters of data – nor by a precise
calculation of the likely impact of Brexit – but by looking again at the weakness of
productivity growth over the whole post-crisis period and at the evidence that this is at leastin part a persistent global phenomenon. As such, the change would relate entirely to ourassessment of underlying prospects for potential productivity growth.

Potential labour market activity rates and equilibrium unemployment
2.50

The impact of repeated productivity disappointments on GDP growth have been partly offset
by upside surprises in labour input, at least some of which appears to be the result ofstronger underlying labour supply. Faster-than-expected employment growth has in partreflected higher rates of labour market participation, including among older workers. Low
interest rates have reduced the return on savings and made annuities more expensive,
which may have affected retirement decisions. Policy changes, including the removal of thedefault retirement age and ongoing and prospective increases in the state pension age arealso likely to have played a part in this. The reduced generosity of, and more onerous
conditions attached to, out-of-work benefits may have also played a part in stronger-thanexpected employment growth albeit at lower average productivity. 10

2.51

The unemployment rate has fallen more rapidly than we expected since mid-2013. Indeed,
it has continued falling when we expected it to stabilise and to start rising slightly in ourmore recent forecasts (Chart 2.12). Prior to our July 2015 forecast, we assumed that thesustainable equilibrium rate of unemployment would remain at 5.2 per cent across theforecast period, broadly in line with pre-crisis unemployment rates. In July 2015, we
assumed that it would rise slowly from 5.2 to 5.4 per cent by 2020 as firms reduced
employment as they adjusted to the costs of the new National Living Wage (NLW). 11

2.52

In March 2017 we reduced our assumption for equilibrium unemployment at the start of theforecast period to 5.0 per cent, rising to 5.2 per cent by its end. This reflected the fact thatunemployment had fallen below this rate with little apparent response from wage growth.
Since March, the unemployment rate has continued to fall and wage growth has once again
failed to rise to the extent we expected. On this basis it seems likely that the equilibrium rateof unemployment is lower than we assumed in March.

9

For example, see ‘The Rise and Fall of American Growth’, by Robert J. Gordon, and ‘US Economic Prospects: Secular Stagnation,
Hysteresis, and the Zero Lower Bound’, by Lawrence H. Summers.
10
See ‘The Labour Market’, Speech by Michael Saunders, 13 January 2017, for more on factors that may have lowered the equilibrium
rate of unemployment.
11
See Annex B of our July 2015 Economic and fiscal outlook.

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2.53

The Bank of England reduced its estimate of equilibrium unemployment to around 4½ percent in its February 2017 Inflation Report. We have previously noted conceptual differences
between our measure of equilibrium unemployment and the Bank’s – for example, due todifferences in the horizon over which they are evaluated and the way in which they take into
account factors such as the level of long-term unemployment. 12 But these differences areunlikely to be material at present, with long-term unemployment close to pre-crisis rates.

2.54

The implications of a change in the current estimate of equilibrium unemployment for our
forecasts of employment and GDP growth would depend on how it affected otherjudgements. Would it imply more spare capacity or that potential productivity was lower
than previously assumed and potential output unchanged? Given subdued wage growth,more spare capacity seems most likely. And would it have any implications for the small risein equilibrium unemployment we foresee over the next few years? This seems unlikely since
the basis of that judgement – that the NLW is set to rise faster than productivity growth overthat period – has not changed.

Chart 2.11: Unemployment rate forecasts and outturns
9

Per cent

87June 2010
March 2013
March 2014
March 2015
March 2016
March 2017
Latest

6

5

4
2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

Note: Solid lines represent the outturn data that underpinned the forecasts at the time (the dashed lines).
Source: ONS, OBR

Potential average hours
2.55

12

Chart 2.12 shows that the average hours that people work each week have risen in recent
years, contrary to our assumption that the long-term decline would soon reassert itself. This
could be related to the shortfall in productivity growth, with people choosing to work more
hours to support growth in their incomes in the face of weak productivity and earnings
growth. Weakness in savings income in a low-interest rate environment is also likely to haveplayed a role. To the extent that movements in productivity growth and average hours are
related, a weaker outlook for productivity growth would seem to make it less likely that thelong-term decline in average hours will reassert itself in the near term.

See Box 3.1 of our March 2014 Economic and fiscal outlook for more details.

Forecast evaluation report36The economy

Chart 2.12: Average hours forecasts and outturns
34.0

33.5

Hours per week

33.0

32.5

June 2010
March 2012
March 2013
March 2014
March 2015
March 2016
March 2017
Latest

32.0

31.5

31.0
1993

1995

1997

1999

2001

2003

2005

2007

2009

2011

2013

2015

2017

Note: Solid lines represent the outturn data that underpinned the forecasts at the time (the dashed lines).
Source: ONS, OBR

Conclusion
2.56

As in previous Forecast evaluation reports, we find ourselves looking back on a period inwhich productivity and earnings growth have been weaker than expected and growth inhours worked stronger. As the period of post-crisis weakness in productivity growth
lengthens, and not just in the UK, it seems less plausible to assume that the factors holdingback productivity growth will fade substantially over the forecast period. In light of this, we
expect to revise down our assumption for average potential productivity growth significantly
in our November forecast. Partly offsetting that, we are likely to assume a lower equilibrium
rate of unemployment and, at a minimum, less of a decline in average hours.

Brexit-related judgements
2.57

In November 2016, we made some key forecast judgements regarding the near-term
effects of the Brexit vote, some of which can be compared with the latest outturns:•

The fall in the pound would squeeze real incomes and real consumer spending. Thisjudgement seems broadly on track, with CPI inflation well above our March 2016
forecast and even above our November 2016 forecast. But real consumption held up
slightly better than expected as households ran down saving.

•

The referendum result generated uncertainty about investment returns that would
cause some investment to be postponed or cancelled. Business investment has indeed
been much weaker than our March 2016 forecast, although slightly above ourNovember 2016 forecast on the latest data. The quarterly data show it falling in theyear before the referendum and then rising thereafter, but this in part reflects
37

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The economy

investment in aircraft where the lags between orders and delivery are long. Moregenerally, the business investment data are so volatile and prone to significant revisionthat it is unwise to place much weight on the precise quarterly profile.
•

The depreciation of sterling would boost net trade in the short term. While the directionof the effect has been as expected, the extent has not. While net trade has not dragged
on GDP growth as we forecast in March 2016, it has provided less of a boost than we
expected in November 2016.

•

Exiting the EU would reduce medium-term export and import growth during thetransition to a less trade-intensive economy. It is too early to assess this judgment.

•

Exiting the EU would be associated with lower net migration than would haveotherwise been the case, both because of weaker ‘pull factors’ – for example, thevalue of UK wages in prospective migrants’ home currencies has fallen due to thedepreciation of the pound – and the likelihood of a tighter migration regime in future.
The latest data do suggest that net inward migration is slowing, consistent with the
expected weakening of pull factors, but the Government has given no clear indicationof the future migration regime at this stage.

Forecast evaluation report38

3

The public finances

Introduction
3.1

This chapter:•

gives an overview of our public sector net borrowing (PSNB) forecasts since June 2010
(from paragraph 3.2);•

discusses our March 2015 and March 2016 PSNB forecasts for 2016-17 and thereceipts (from paragraph 3.8) and spending (paragraph 3.37) forecasts that
underpinned them;•assesses our forecasts for public sector net debt in 2016-17 (from paragraph 3.62);
and•looks at the year-to-date path of borrowing in 2017-18 relative to our March 2017
forecast (from paragraph 3.65).

Forecasts since June 2010
3.2

3.3

1
2

The Office for National Statistics (ONS) has implemented some significant changes in thedefinition of key public finance statistics in recent years. These include:•

In September 2014, the ONS aligned the public sector finance statistics with the 2010
European System of Accounts (ESA10), as well as implementing other changes
following its own review of the statistics. 1 The ONS’s headline measure is now ‘public
sector net borrowing excluding public sector banks’. Our forecasts for government
borrowing have been produced on that basis since then, but some we are reviewing inthis section were for ‘public sector net borrowing excluding financial sector
interventions’ under the 1995 European System of Accounts.

•

A Government policy change announced in July 2015 prompted the ONS to review
the classification of housing associations and to decide that they should be consideredpublic rather than private corporations from a statistical perspective because of thedegree of control over them exerted by Government. 2

To ease comparability across forecasts and outturns, we have restated our earlier forecasts
to bring them in line with these current definitions. Tables A.13 to A.16 in Annex A provide

Chapter 4 of our December 2014 Economic and fiscal outlook detailed the effect of these changes on our fiscal forecasts.
Annex B of our November 2015 Economic and fiscal outlook detailed the effect of this change on our fiscal forecasts.

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details on those restated forecasts. In a new briefing paper, we set out this methodology inmore detail. 3 We have not restated our forecasts for every classification change given thetime that would take and because the effects of most other changes are relatively small.
These effects are separated out in our analysis of forecast differences. The largest change
not adjusted for relates to the accounting treatment of corporation tax receipts, where
restating past forecasts would be a highly resource intensive process.
Chart 3.1 shows that the deficit has not fallen as fast as our earlier forecasts predicted: 4

3.4•

PSNB fell by 2.8 per cent of GDP in the two years to 2011-12, less than the 3.6 percent of GDP decline that we forecast in June 2010 (on a comparable basis);•deficit reduction then slowed significantly in 2012-13, falling by 0.5 per cent of GDP
when the one-off transfer of Royal Mail’s historic pension fund is excluded andotherwise remaining flat as a share of GDP;•PSNB fell by 1.1, 0.6 and 1.1 per cent of GDP respectively in 2013-14, 2014-15 and2015-16 (from a 2012-13 level that excludes the Royal Mail transfer) broadly in linewith our forecasts from December 2014 onwards; and•PSNB fell by 1.6 per cent of GDP in 2016-17 on the latest ONS estimates, slower thanour earlier forecasts predicted, but faster than our more recent ones did.

Chart 3.1: Restated forecasts and outturns for public sector net borrowing
12

June 2010
March 201110

March 2012
March 2013

Per cent of GDP

8

March 2014
March 2015

6

March 2016
March 20174

Latest2
0-2
2009-10

2011-122013-142015-162017-18

2019-20

Source: ONS, OBR

3
4

See Briefing paper No.7: Evaluating forecast accuracy on our website.
The GDP denominator used here is consistent with the ONS Quarterly National Accounts release on 29 September 2017.

Forecast evaluation report40

2021-22

The public finances

3.5

Chart 3.2 sets out the drivers underpinning those forecast differences at a 2-year horizon.
•

The top panel shows that up to March 2012, our borrowing forecasts were too
optimistic, with underperforming receipts only partly offset by lower-than-expected
spending. Since then, our borrowing forecasts have been subject to smaller differencesthat have also been in both directions.

•

The middle panel shows that receipts forecast differences have been dominated byweaker-than-expected income tax and NICs – the result of productivity-related
weakness in earnings growth and a lower-than-expected effective tax rate. The latter islikely to reflect changes in the earnings distribution, including among the selfemployed, and subsequent policy changes (e.g. to the income tax personal allowance).
This has been offset in recent years by the strength in onshore corporation tax, which
partly reflects a change in ONS accounting treatment (discussed in more detail below).

•

The bottom panel shows that our early spending forecasts overestimated spending by
local authorities and non-interest spending by central government, while our more
recent forecasts overestimated debt interest spending and underestimated local
authorities’ spending. Despite more timely quarterly data on local authorities’
spending now being available, it has remained challenging to predict how they will
use reserves to adjust the path of spending relative to their local sources of finance(including council tax and business rates). Our early overestimates of spending cameas they built up reserves despite the pressure on local government budgets resulting
from fiscal consolidation. Our recent underestimates reflect the reversal of that pattern,with reserves being drawn down in order to maintain higher levels of spending. Large
underestimates of DEL spending in our December 2014 and March 2015 forecasts
reflected subsequent policy changes following the 2015 General Election.

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Chart 3.2: Two-year-ahead forecast differences: Borrowing, receipts and spending
40

Borrowing
30
20£ billion

10
0
-10
-20
-30
-40
40
30
20

Spending
Receipts
Overall net borrowing forecast difference

Other
Fuel duty
VAT
IT and NICs

SDLT and LBTT
Oil and gas
Onshore CT
Overall receipts

Receipts£ billion

10
0
-10
-20
-30
-40
40
30
20

£ billion

10

DEL
Debt interest
WelfareLASFE
Other AME
TME

Spending

0
-10
-20
-30
-40

Jun 10 Nov 10 Mar 11 Nov 11 Mar 12 Dec 12 Mar 13 Dec 13 Mar 14 Dec 14 Mar 15 Jul 15
Note: Forecasts have been adjusted for ESA10 and housing associations. Corporation tax forecasts have not been adjusted foraccounting treatment changes.
Source: ONS, OBR

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The public finances

2016-17 in detail
3.6

Table 3.1 sets out our March 2015 and March 2016 forecasts differences for public sector
net borrowing (PSNB) in 2016-17. It shows that:•

Against our March 2015 forecast, borrowing was around £2½ billion higher than
expected. That difference is more than explained by policy changes, in particular thelarge increase in departmental spending plans following the 2015 General Election.
Abstracting from policy changes and classification effects (in particular the change in
the accounting treatment of corporation tax), borrowing was slightly lower than our
forecast. Higher-than-expected receipts, particularly from onshore corporation tax, VAT
and capital gains tax, were partly offset by higher-than-expected spending, inparticular much higher self-financed spending by local authorities.

•

Our March 2016 forecast was too pessimistic. Abstracting from classification changes
and subsequent policy changes, borrowing was around £4 billion lower than expected.
That again reflected stronger-than-expected onshore corporation tax, VAT and capitalgains tax as well as lower tax credits spending and changes in the timing ofexpenditure transfers to the EU within the 2017 calendar year.

Table 3.1: 2016-17 receipts, spending and net borrowing forecasts£ billion
1

Forecast

Outturn Differenceof which:
Classification
changes

Memo:
FiscalPolicy Economic
forecasting like-for-likechangesfactors
difference difference 2

Borrowing (PSNB)
March 2015
March 2016
Receipts (PSCR)

42.7
55.9

45.0
45.0

2.4
-10.9

-8.5
-8.1

12.1
0.9

-1.5
-0.5

0.3
-3.2

10.9
-2.8

March 2015
March 2016
Spending (TME)

708.6
717.3

726.2
726.2

17.6
8.9

5.6
4.3

5.5
0.0

-0.5
1.9

7.1
2.7

12.0
4.6

March 2015
March 2016

751.3
773.3

771.3
771.3

20.0
-2.0

-2.9
-3.8

17.6
0.9

-2.0
1.4

7.4
-0.5

22.9
1.8

1
2

Forecasts have been restated to reflect the reclassification of housing associations to the public sector.
Excludes the effect of classification changes.

3.7

It is always important to stress that initial estimates of PSNB can be revised significantly oversubsequent months as more reliable data become available. Box 3.1 sets out how our mostrecent forecasts and outturns for 2016-17 have changed over time.

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Box 3.1: Revisions to borrowing in 2016-17
The September 2017 estimate of PSNB in 2016-17 is £45.0 billion. That is £7.0 billion lower
than the initial ONS estimate published in April and between £6.7 and £23.1 billion lower thanour three most recent forecasts. Chart A sets out how the public finances data and our forecasts
for 2016-17 evolved in the period after our March 2016 forecast was presented:•

Our November 2016 forecast was based on published ONS outturn data for the first six
months of 2016-17, which showed a 4.8 per cent fall in borrowing relative to theprevious year, much slower than was implied by our March 2016 forecast. So, on a likefor-like basis, we revised our 2016-17 forecast up by £12.2 billion to £68.2 billion.
Revised data for the first six months of 2016-17 now show a much larger year-on-year
fall of 19.9 per cent.

•Our March 2017 forecast utilised a further four months of outturns. By then, PSNB in thefirst half of the year had been revised down by £9.6 billion, of which £7.7 billion reflected
the move to recording corporation tax on a time-shifted accruals basis. Underlying
receipts growth from October to January was also stronger-than-expected. We revised
our PSNB forecast down by £13.4 billion on a like-for-like basis to £51.7 billion.

•

The initial ONS estimate of 2016-17 PSNB (released in April) was £52.0 billion, just
£0.3 billion above our March 2017 forecast produced the month before.

•

The latest ONS estimate of 2016-17 PSNB (released in September) has been revised
down by £7.0 billion relative to the initial estimate, to £45.0 billion.

Chart A: PSNB in 2016-1780

Forecast
Outturn: February to March 2017
Outturn: October 2016 to January 2017
Outturn: April to September 2016

70
60

£ billion

50
40
30
20
10
0
March 2016 forecast

November 2016
forecast

March 2017 forecast

Source: ONS, OBR

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44

First estimate of
2016-17

Latest estimate of
2016-17

The public finances

Table A sets out the drivers of the difference between our March 2017 forecast for 2016-17, thefirst ONS estimate released in April and the latest estimate (which will remain subject to revision
for some time). In this table we have adjusted our forecast up by £0.3 billion to account for theeffect of ONS classification changes that affect the recording of several small items of receipts
and spending. These have been announced (so we include them in our forecasts) but not
implemented (so they are not yet included in the outturn data).
On this basis, the difference between our March forecast and the initial estimate was just
£5 million. That reflected a number of offsetting factors, including higher local authority
borrowing but also higher income tax and NICs receipts and lower departmental spending.
Between April and September, the ONS revised PSNB in 2016-17 down by £7.0 billion.
Methodological and classification changes implemented in the September data release explain£1.3 billion of the revision (the bulk relating to public sector pension schemes). The remaining£5.7 billion revision has been broad-based, with central government receipts revised up, central
government spending revised down and local authority borrowing also lower. Only public
corporations’ borrowing – revised up £0.1 billion since April – has had an offsetting effect.
Relative to our March forecast, Table A shows that on the basis of the latest estimates:•

Income tax and NICs receipts were £3.5 billion higher last year than we thought inMarch. Around £2 billion reflects receipts on stronger-than-expected bonuses in thefinancial and business services sectors at the end of the year. On an unchanged
assumption about growth in bonuses, this would lead to higher receipts in each year of
the forecast. The remaining £1½ billion reflects alignment of outturn data with the latest
HMRC trust statement.

•

VAT receipts were £0.9 billion higher than expected. Most of this reflects timing effects on
cash receipts in the early part of 2017-18 that accrue back to 2016-17. On an
unchanged assumption about growth in the tax base, only part of this would be expected
to affect future years.

•

Corporation tax (CT) receipts were £0.8 billion higher than expected, reflecting strong
cash payments between April and June 2017. Under the new time-shifted accruals basis
for CT, all these cash receipts are accrued back to earlier years. The implications of thisfor future years depend on whether those higher cash receipts imply that previous years’
liabilities are being paid off more quickly – i.e. a timing effect – or that the liabilities
themselves have been higher than expected – i.e. that the underlying position is stronger,
which all else equal would boost the forecast.

•Central government spending was £1.9 billion lower than expected, largely reflecting
greater-than-expected underspending against departments’ plans. Given differentpressures on departmental budgets in different years of the Spending Review period,
there is no mechanical link between outturns in 2016-17 and the judgements that wewould make about future years.

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Partly offsetting those factors, local authority net borrowing was £1.8 billion higher than
expected, as spending exceeded local revenue by a greater extent than we had assumed, mainly
through higher than expected use of prudential borrowing. The implications of this for futureyears are not yet clear.

Table A: March 2017 PSNB: outturn versus forecast£ billion

First estimate1
Revised outturn
Differenceof which:
Classification and methodological changes 2

March 2017
March 2017
April to September
forecast to April
forecast torevision
outturn
September outturn
52.0
52.0
52.0
52.0
45.0
45.0
0.0
-7.0
-7.0

of which:
CG and LA pension schemes
Previously unrecorded income
Revisions to outturn dataof which:
IT and NICs receipts
VAT receipts
Corporation tax receipts
Other CG receipts
CG spending
LA net borrowing
PC net borrowing

-

-1.3

-1.3

0.0

-1.0
-0.3
-5.7

-1.0
-0.3
-5.7

-1.4
1.2
-0.6
-0.4
-1.2
2.0

-2.1
-2.1
-0.2
-0.5
-0.6
-0.2

-3.5
-0.9
-0.8
-0.9
-1.9
1.8

0.5

0.1

0.5

Note: This table shows impacts on PSNB, i.e. higher-than-expected receipts reduces net borrowing.
1
Adjusted for various classification changes that were anticipated in our March 2017 forecast, but have not yet been implemented.
Our November 2015 Economic and fiscal outlook discusses some of these items in further detail.
2

Reflects changes that the ONS included in the Public Sector Finances Statistical Bulletin released in September 2017, as part ofwider revisions included in Blue Book 2017. In some cases the distinction between whether these revisions were methodologicalor classification changes, or other forms of data changes is not clear cut.

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The public finances

Receipts
3.8

Receipts were around £17½ billion above our March 2015 forecast for 2016-17, withnearly two-thirds of the surplus explained by onshore corporation tax (CT). Nearly half thatonshore CT surprise reflects a change in the ONS accounting treatment, meaning the likefor-like receipts surplus against forecast was around £12½ billion. The sources of thisdifference – including stronger-than-expected capital gains tax and VAT receipts – aredetailed below. They were partly offset by self-assessment income tax (reflecting continued
weakness in the effective tax rate) and interest and dividend receipts (largely reflecting
lower-than-expected interest rates) falling short of our forecasts.

3.9

The receipts surplus was smaller against our March 2016 forecast, with overall receipts
coming in around £9 billion above forecast and the like-for-like difference £4 billion, again
reflecting strength in onshore corporation tax, VAT and capital gains tax.

Table 3.2: 2016-17 receipts forecast differences

Income tax (gross of tax credits)of which:Pay as you earn (PAYE)
Self assessment (SA)National insurance contributions
Value added tax
Business rates
Council tax
Onshore corporation tax (cash)
UK oil and gas revenues (cash)
Capital gains tax and inheritance tax

Forecast
March 2015 March 2016
182.0
182.1

Stamp duties1
Fuel, alcohol and tobacco duties
Interest and dividends
Other taxes
Other receipts
Like-for-like current receipts 2
Corporation tax accruals adjustment
Current receipts
1
2£ billion
Outturn

Difference
March 2015 March 2016
177.2
-4.7
-4.9

153.6
29.3
123.9
117.7
29.0
28.8
42.9
0.6
11.9
15.2
47.0
7.8
53.7
48.1
708.6

153.4
30.2
126.5
120.1
28.4
30.1
43.4
-1.1
11.8
15.9
47.7
5.7
60.2
46.5
717.3

149.7
28.5
125.9
121.6
29.4
30.4
49.2
-0.3
13.2
15.6
47.7
6.0
57.6
47.5
721.1

-3.9
-0.8
2.1
3.9
0.4
1.5
6.3
-0.9
1.3
0.4
0.8
-1.8
3.9
-0.6
12.5

-3.6
-1.6
-0.5
1.6
1.0
0.3
5.8
0.8
1.5
-0.3
0.0
0.3
-2.7
1.0
3.8

0.0
708.6

0.0
717.3

5.1
726.2

5.1
17.6

5.1
8.9

Excludes Scottish LBTT.
Excludes corporation tax accruals adjustment.

3.10

Strong overall receipts growth in 2016-17 took receipts as a share of GDP to their highest
since 1986-87. Box 3.2 describes how the composition of the public sector’s income haschanged over the three decades since receipts were last at the latest share of GDP.

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Box 3.2: The receipts-to-GDP ratio since 1986-87
Public sector receipts rose to 36.7 per cent of GDP in 2016-17, their highest level since 1986-87.
National Accounts taxes (which exclude non-tax revenues, such as interest paid on thegovernment’s assets and the operating surpluses of public corporations) reached 34.0 per cent ofGDP, the highest level since 1981-82. Chart B illustrates these historical trends.

Chart B: Taxes and receipts as a share of GDP
46

Receipts

44

National Accounts taxes

42
40

Per cent of GDP

38
36
34
32
30
28
26
24
48-49 52-53 56-57 60-61 64-65 68-69 72-73 76-77 80-81 84-85 88-89 92-93 96-97 00-01 04-05 08-09 12-13 16-17
Source: ONS

Chart C shows the different factors that have contributed to the fall and subsequent rise in thereceipts-to-GDP ratio since 1986-87. Factors pushing the ratio higher include:•

VAT receipts have risen by 2.2 per cent of GDP. This largely reflects policy-driven rises inthe effective tax rate: the standard rate of VAT was raised from 15 to 17½ per cent in
1991, cut to 15 per cent in late 2008 to support the economy through the recession,
returned to 17½ per cent in 2010 and then raised again to 20 per cent in 2011. A
disproportionate rise in the tax base has also helped, with consumer spending rising as ashare of GDP by around 3.0 percentage points over the period.

•

National Insurance contributions have risen by 0.5 per cent of GDP. This is more than
explained by largely policy-driven increases in the effective tax rate. Over this period, themain employee rate has risen from 9 to 12 per cent and the employer’s rate has risen
from 10.45 to 13.8 per cent. Receipts were actually below their 1986-87 level until 200203, but moved above it as Budget 2002 rises were implemented in 2003-04. Removing
the NICs contracting out rebate boosted receipts by a further 0.3 per cent of GDP in 201617. Wages and salaries fell by less than half a per cent of GDP over the period, partly
offsetting the contribution from a higher effective tax rate.a•

Onshore corporation tax receipts have risen by 0.4 per cent of GDP, despite the headline
rate having been cut from 35 to 20 per cent. The effect of this lower rate has been offset tosome extent by policy changes that restrict the use of reliefs and allowances, increasing theamount of profits subject to tax. Non-oil, non-financial profits have risen by 2.7 per cent of
GDP from 2009 to 2016, boosting receipts despite the lower headline tax rate. Some of
the rise will reflect the upward trend in incorporations. In 2016-17, receipts topped their

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48

The public financespre-crisis level as a share of GDP for the first time, but remain below the peak theyreached in 1989-90.
•

Income tax receipts, although below their recent 2007-08 peak, are 0.3 per cent of GDP
higher than in 1986-87. Again, this is explained by a higher effective tax rate, partly
reflecting the fact that average earnings have risen faster than the higher rate thresholdover the period, so that a rising proportion of earnings have been taxed at the higher rateof income tax. The recent weakness in earnings growth has placed greater downward
pressure on income tax than NICs because of its more progressive rate structure.

Partly offsetting those positive contributions to leave total tax receipts 1.5 per cent of GDP higher
than in 1986-87 were:•

Offshore corporation tax and petroleum revenue tax (PRT) receipts have fallen by 0.8 percent of GDP. This fall mainly reflects declining oil and gas production from around 2000
onwards, as well as cuts to the main rates of tax. The PRT rate was cut to zero in 2016-17,
having been as high as 75 per cent in 1986-87. More recently the drop in oil prices has
further reduced receipts.

•

Tobacco duty receipts have fallen by 0.6 per cent of GDP, reflecting a steady decline intobacco consumption. The proportion of adults in Great Britain who smoke halved
between 1986 and 2016 (from 33 to 16 per cent).

Despite higher tax receipts, overall receipts were 0.6 per cent of GDP lower than in 1986-87. This
reflects central government interest and dividend receipts (excluding the intra-public sector receipts
from the Bank of England) having fallen by 1.4 per cent of GDP. Interest rates have fallen
significantly over the past three decades. For example, Bank Rate averaged 10.4 per cent during
1986-87, but was cut to 0.25 per cent mid-way through 2016-17. And receipts from nonfinancial public corporations have fallen by 0.8 per cent of GDP. This largely reflects privatisationsin the late 1980s and early 1990s, reducing both public sector receipts and public spending.

Chart C: Change in the receipts-to-GDP ratio since 1986-87
10

Cumulative change since 1986-87(per cent of GDP)

8
6

Other taxes and receipts
CG interest and dividend receipts (ex. BoE)
Offshore CT and PRT
VAT
Income tax

Tobacco duties
Non-financial PC receipts
Onshore CT
NICs
Total cumulative change in receipts-to-GDP

4
2
0
-2
-4
-6

-8
1986-87 1989-90 1992-93 1995-96 1998-99 2001-02 2004-05
Note: Income tax and corporation tax reflect cash data prior to 1999-00.
Source: ONS, HMRC

2007-08

2010-112013-142016-17aPre-1997 estimates of some income components of GDP consistent with the latest Quarterly National Accounts release were notavailable at the time of publication. For pre-1997 data, we have created an estimate using the previous vintage of data.

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Income tax and NICs
3.11

PAYE income tax and NICs receipts fell short of our March 2015 forecast by £1.8 billion.
That shortfall is more than explained by two factors:•

Labour market developments explain nearly two-thirds of the shortfall. Growth inaverage earnings was again weaker than expected, reducing receipts by around£3½ billion. Employment growth was stronger than expected, offsetting around£2½ billion of the earnings weakness.

•

Policy changes in the July 2015 Budget. These include 2016-17 increases in the
personal allowance (to £11,000), the higher rate threshold (to £43,000) and the NICs
employment allowance (to £3,000). The original costings of the July 2015 Budget
measures estimated that they would together reduce receipts by around £1½ billion in
2016-17, with the personal allowance rise accounting for around three quarters of
that.

3.12

Relative to our March 2016 forecast, receipts fell short of our forecast by £4.2 billion. The
effect of weaker earnings growth was offset by strength in employment. Around half thisshortfall relates to the starting point for the forecast, as we overestimated PAYE and NIC1
receipts in 2015-16 by £2.0 billion. While our March 2016 forecast was produced close to
the end of the 2015-16 fiscal year, we did not have information on accrued receipts in
February and March. As these are large bonus-paying months, receipts tend to be morevolatile than the rest of the year. The surprise in February and March 2016 receipts reflected
weaker-than-expected bonuses in both the financial and non-financial sectors. Changes inthe effective tax rate explain most of the remaining shortfall.

3.13

Self-assessment (SA) income tax receipts in 2016-17 also fell short of our March 2015 andMarch 2016 forecasts – by £0.8 and £1.6 billion respectively. A combination of subsequent
policy changes with uncertain effects and the assumptions factored into our forecastingmodel appear to explain the bulk of the difference.

3.14

On the policy side, the July 2015 Budget reforms to the taxation of individual dividend
income were a source of upside surprise in 2016-17. The reform included raising the basic,
higher and additional rates by 7.5 percentage points with effect from April 2016 andintroducing a tax-free dividend allowance. As has been the case with other recent measuresannounced ahead of implementation, we expected taxpayers to bring forward dividend
income to before April 2016 to have it taxed at the lower existing rates. Since the tax is paid
through SA with a lag, that would boost 2016-17 receipts at the expense of lower receipts in2017-18 and 2018-19. We assumed that £7.6 billion of dividend income (worth £2.6
billion of dividend tax) would be brought forward. Analysis of SA tax return data presented
in our March 2017 EFO suggested that in fact £10.7 billion of dividend income (worth £4.0
billion of dividend tax) had been brought forward. 5 Adjusting our March 2015 and March

5

See Box 4.3 of our March 2017 EFO.

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The public finances

2016 forecasts for this policy costing (and the subsequent revision to it) increases thereceipts shortfalls to £4.8 and £3.0 billion respectively.
3.15

The bulk of these shortfalls appear to reflect continued weakness in the effective tax rate
paid on SA liabilities. Initial analysis of HMRC tax return data suggests that a continued shift
in the self-employment income distribution towards the bottom end is behind this weakness.
Growth in self-employment among unincorporated businesses and sole traders who pay tax
via SA seems to be concentrated among lower-income individuals, while the trend towards
incorporation among those with higher incomes reduces the amount of tax they pay on agiven income and shifts much of it to the corporation tax system.

3.16

Our SA receipts forecasts include the estimated effect of several anti-avoidance measures. In
our latest evaluation of the relevant costings, we have found that outturn yield has fallen
short of expectation more often than not. 6 This has contributed to the overall shortfalls
relative to our March 2015 and March 2016 forecasts.

3.17

Our SA forecast model uses a time-series econometric approach to generate an effective tax
rate which is then applied to different sources of SA income. We then adjust the results to try
to capture recent trends and policy effects not reflected in the model. Due to the number ofpolicies announced in recent years, the uncertain effects of above-inflation increases in the
personal allowance and higher rate threshold interacting with changes in the selfemployment earnings distribution, and income shifting caused by pre-announced policychanges, these assumptions have been a repeated source of fiscal forecasting differences.
This approach no longer seems satisfactory and we have prioritised this component of the
SA model in our review of fiscal forecasting models, as detailed in Chapter 4.

3.18

Other income tax receipts were £0.1 billion below our March 2015 forecast and£0.4 billion higher than we forecast in March 2016. This reflects large offsetting differences.
The adjustment to align outturn data with the latest HMRC trust statement added£1.1 billion to 2016-17 receipts, but this is largely offset by shortfalls in other receipts
streams.

6

For more detail see Working Paper No.11: Evaluation of HMRC anti-avoidance and operational measures available on our website.

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Table 3.3: 2016-17 income tax and NICs forecasts
Forecast

Outturn£ billion
Differenceof which:
PolicychangesMarch 2015 forecast
Income tax (gross of tax credits)of which:Pay as you earn (PAYE)
Self assessment (SA)National insurance contributions
March 2016 forecast
Income tax (gross of tax credits)of which:Pay as you earn (PAYE)
Self assessment (SA)National insurance contributions

FiscalEconomic
forecasting
factors
difference

182.0

177.2

-4.7

1.9

0.2

-6.9

153.6
29.3
123.9

149.7
28.5
125.9

-3.9
-0.8
2.1

-1.1
2.7
-0.3

-0.8
1.2
-0.6

-2.0
-4.7
2.9

182.1

177.2

-4.9

0.0

-0.1

-4.8

153.4
30.2
126.5

149.7
28.5
125.9

-3.6
-1.6
-0.5

0.0
0.0
0.0

-0.1
0.0
-0.1

-3.6
-1.6
-0.4

VAT
3.19

Relative to our March 2015 forecast, VAT receipts were £3.9 billion higher despite weakerthan-expected growth in consumer spending. This reflects two key factors:•

The composition of household spending has been more favourable for VAT receipts
than we expected, boosting them by £1.6 billion. The latest HMRC analysis suggests
the ‘standard-rated share’ (SRS) of household spending has risen by nearly
1 percentage point over the past two years, compared with our assumption of a stableshare over that period. This largely reflects strong growth in spending on durable
goods (particularly motor vehicles). In our March 2017 forecast, we moved to a new
SRS model that places more weight on trends in spending on durable goods.

•

The error in our VAT deductions forecast that was identified in our 2015 FER andcorrected in our November 2015 forecast explains £1.6 billion of the surplus.
(Exploring fiscal forecast differences for our 2015 FER revealed that the VAT deductions
model was using historically derived growth rates rather than reflecting cuts to public
spending that reduce deductions relating to the government sector. This had resulted
in us over-forecasting deductions and thus under-forecasting receipts.)

3.20

Policy changes also contributed to the surplus, including the boost to VAT receipts on carpurchases brought forward ahead of the April 2017 vehicle excise duty reforms that werepre-announced in the July 2015 Budget. VAT receipts were also higher than expected in
2014-15, the base year from which this forecast applied expected receipts growth.

3.21

Relative to our March 2016 forecast, there was a smaller surplus of £1.6 billion. This reflects
similar factors, in particular a £1.0 billion boost from a higher-than-expected standardrated share. By this forecast, the VAT deductions model had been corrected, so it was nolonger a source of underestimate in our VAT receipts forecast.

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Table 3.4: 2016-17 VAT forecasts
Forecast

Outturn£ billion
Differenceof which:
PolicychangesMarch 2015 forecast
March 2016 forecast

117.7
120.1

121.6
121.6

3.9
1.6

0.4
0.0

FiscalEconomic
forecasting
factors
difference
0.3
3.2
-0.1
1.6

Onshore corporation tax
3.22

On a simple comparison of forecasts and outturn, onshore corporation tax (CT) receipts
exceeded our March 2015 and March 2016 forecasts by £10.6 and £10.1 billion
respectively. On a like-for-like basis, the differences, while still large, fall to £6.3 and£5.8 billion respectively. That is because the ONS has moved from recording CT receipts inthe public finances data on a cash basis (when the tax is received by HMRC) to using atime-shifted cash basis that proxies for a true accruals basis (moving the scoring closer towhen the activity generating the CT liability was generated). This change was implemented
in February 2017 and we incorporated it in our March 2017 forecast.

3.23

This accounting treatment change boosted measured onshore CT receipts by £4.3 billion in
2016-17, reflecting the fact that the strong growth in cash receipts in 2017 (largely basedon HMRC’s monthly profiling of our latest forecasts) is accrued back to earlier periods. To
allow for like-for-like comparisons between the forecasts being assessed in this FER and thelatest outturns, we have focused on our cash forecasts and presented this accounting
treatment change separately from the other components of the forecast difference.

3.24

The large like-for-like surpluses against our March 2015 and March 2016 forecasts reflect
the fact that cash onshore CT receipts in 2016-17 increased by 12.6 per cent on a year
earlier, well above our forecasts of 1.5 and minus 0.5 per cent respectively. Several factors
contributed to these higher-than-expected CT receipts:•

Relative to our March 2015 forecast, the effect of subsequent policy changes explains£0.8 billion of the surplus. These include the Budget 2016 measure to further restrict
the amount of losses banks can use to offset against their taxable profits. Policychanges had no effect relative to our March 2016 forecast.

•

If we had known the outturns for the economic determinants of CT receipts, then thatwould have boosted our March 2015 forecast by £0.9 billion and our March 2016
forecast by £1.4 billion. In particular, that reflects higher-than-expected non-financial
company profits and lower-than-expected business investment (which reduces thevalue of capital allowances available to offset against taxable profits).

•

A higher 2014-15 starting point relative to our March 2015 forecast, when we hadaccess to outturn data up to January 2015 and some administrative data for February
2015. By the time of our July 2015 forecast, the receipts estimate for 2014-15 wasalready £0.5 billion higher than our previous forecast. On the latest estimates, it is53

Forecast evaluation report

The public finances£0.7 billion higher. Adjusting for that higher starting point would have boosted ourforecast for 2016-17 receipts by around £0.7 billion. This effect is small relative to ourMarch 2016 forecast.
•

Payment timing assumptions. The speed at which companies pay off their liabilities fora particular year is an important forecast assumption. Companies appear to have paida higher proportion of their liability in instalment payments before the end of 2016-17
than we expected, boosting cash receipts by £1.2 billion relative to our March 2015
forecast and £1.0 billion relative to March 2016.

•

Life assurance receipts were £0.4 billion higher than our March 2015 forecast, after
accounting for policy changes and outturn economic determinants, and £0.8 billion
higher than our March 2016 forecast. These differences suggest there is a problem
with the way our model factors in the effect of bond price movements on life assurancecompanies’ tax liabilities. We are reviewing this with HMRC analysts.

•

Autumn Statement 2015 announced a special 45 per cent corporation tax rate on‘restitution payments’ resulting from litigation against HMRC. The original costing –factored into both our March 2015 and March 2016 forecasts – expected this to raise£55 million in 2016-17, but the latest analysis from HMRC suggests that it actuallyraised £0.6 billion. Interim litigation payouts made by HMRC in 2016-17 were
substantially higher than expected.

3.25

These factors together explain around two-thirds of the ‘like-for-like’ surplus against ourMarch 2015 and March 2016 forecasts. The remainder is likely to reflect movements intaxable income and deductions in 2016-17, although HMRC will only publish data on thesein August 2018, so we will not have a full picture until then. Analysis of the 2015-16 datasuggests that the use of group relief has fallen faster than we expected, which may be afactor in this year’s surplus.

3.26

In a new briefing paper on forecast evaluations, we have used our March 2015 onshore CT
forecast to illustrate the steps we take when analysing forecast differences. Annex A of thebriefing paper, available on our website, provides a more detailed step-by-step guide tounderstanding the differences summarised in Table 3.5.

Table 3.5: 2016-17 onshore corporation tax forecasts£ billion
Forecast

March 2015 forecast
March 2016 forecast

Forecast evaluation report

42.9
43.4

Outturn

53.5
53.5

Difference
Accounting
treatmentchange
10.6
4.3
10.1
4.3

54

of which:
Policychanges
0.8
0.0

FiscalEconomic
forecasting
factors
difference
0.9
4.7
1.4
4.4

The public finances

Capital taxes
3.27

Capital gains tax (CGT) receipts in 2016-17 outperformed both our March 2015 andMarch 2016 forecasts, increasing by 19 per cent on the previous year relative to forecasts of
12 per cent and little change respectively. This was despite a 5 per cent fall in the FTSE Allshare index in 2015-16 – the year in which the relevant CGT liabilities were generated,since CGT is paid in the financial year following the period when the disposal took place.
Initial HMRC analysis suggests that around two-thirds of CGT receipts in 2016-17 related tothe sale of shares and equity. Within that, around two-thirds came from unlisted company
equity rather than the major (and often multinational) companies listed in the FTSE.

3.28

Inheritance tax receipts were £0.2 billion higher than expected in our March 2015 forecast.
This largely reflects higher-than-expected deaths in 2016-17 (at 609,000 versus the548,000 we had assumed on the basis of ONS projections). Relative to our March 2016
forecast, receipts were £0.1 billion higher than expected. This partly reflects strong equity
price growth in 2016-17.

Stamp taxes
3.29

Stamp duty land tax (SDLT) receipts were close to our March 2015 forecast, as subsequent
policy changes offset a shortfall in our underlying forecast. Receipts were £0.9 billion lower
than our March 2016 forecast. The underlying forecasting shortfalls largely reflected
weakness in the commercial sector, which reflected uncertainty in the run-up to andfollowing the EU referendum and possibly a larger-than-expected behavioural response to
the commercial SDLT ‘slab-to-slice’ reform announced in March 2016.

3.30

These were partly offset by higher-than-expected receipts from the additional properties
surcharge that was announced in November 2015 to take effect from April 2016. This wasanother policy announcement that prompted taxpayers to shift the timing of activity – in thiscase property transactions – to avoid being subject to the forthcoming tax rise. This boosted
2015-16 receipts at the expense of 2016-17. At the time we assumed that around 10,000
transactions would be brought forward, reducing receipts by £50 million. In the event, weestimate around 40,000 transactions were brought forward, reducing 2016-17 receipts bya further £250 million. 7 We have treated this as a fiscal forecasting difference. Despite thisforestalling, the measure has raised much more than originally expected – our latest
estimate for 2016-17 is £1.6 billion compared to £0.7 billion in the original costing.
However, taxpayers can claim a refund if they sell their main residence within 36 months, so
we will not know the final net impact in 2016-17 for nearly three years.

3.31

While stamp duty on shares is a relatively small receipts line, it has recently been subject torelatively large fiscal forecasting differences – of 18 and 12 per cent relative to our March
2015 and March 2016 forecasts respectively. One reason for this has been the higher-thanexpected yield from the ‘schemes of arrangement’ measure that removed the option forcompanies to cancel and reissue shares during a takeover, avoiding a stamp duty liability,

7

It should be noted that the magnitude of forestalling itself is subject to considerable uncertainty. See Mathews (2016): Working paper No.
10: Forestalling ahead of property tax changes.

55

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The public financesrather than simply transferring them. A number of very large takeovers have been affected,
adding around £0.4 billion to 2016-17 receipts relative to these forecasts.

Table 3.6: 2016-17 capital and stamp taxes forecasts
Forecast

Outturn£ billion
Differenceof which:
PolicychangesMarch 2015 forecast
Stamp duty land tax1
Stamp duty on shares
Capital gains tax
Inheritance tax
March 2016 forecast
Stamp duty land tax1
Stamp duty on shares
Capital gains tax
Inheritance tax
1

FiscalEconomic
forecasting
factors
difference

11.8
3.4
7.3
4.6

11.9
3.7
8.4
4.8

0.1
0.3
1.1
0.2

1.1
0.0
0.2
0.0

0.0
-0.3
-1.0
0.0

-1.0
0.6
1.9
0.2

12.9
3.0
7.0
4.8

11.9
3.7
8.4
4.8

-0.9
0.7
1.4
0.1

0.0
0.0
0.0
0.0

-0.4
0.3
0.2
0.2

-0.6
0.4
1.2
-0.1

Excludes Scottish LBTT.

Fuel, alcohol and tobacco duties
3.32

Fuel duties outperformed both our March 2015 and March 2016 forecasts, despite thecancellation of the planned April 2016 RPI-linked rise at Budget 2016 and ongoing
improvements in vehicle efficiency. This appears to be due to rising demand for fuel fromlight commercial vehicles (LCVs), where mileages have increased sharply, probably
reflecting deliveries of goods purchased online. Over the past five years, LCV mileage
driven has risen by 21 per cent, whereas car and taxi mileage increased by just 5 per cent. 8

3.33

Our forecasts are based on a model that relates miles driven to GDP growth and the cost ofdriving. In our November 2016 forecast, we revised the parameters in this model toincrease the sensitivity of miles driven to GDP growth, as a proxy for the effect of increased
mileage delivering online goods purchases. This added increasing amounts to receipts
relative to our March 2016 forecast, reaching around £1 billion a year by 2020-21.

3.34

Tobacco duties were weaker than expected in 2016-17, reflecting a faster-than-expected
fall in taxable consumption – known as ‘clearances’. This may reflect a faster decline inunderlying consumption as well as one-off effects relating to the introduction of several new
regulations in early 2017 (such as outlawing smaller cigarette and hand-rolling tobacco
pack sizes and the introduction of plain packaging). In light of these recent trends, we
moved to assuming a steeper downward trend in clearances in our November 2016
forecast (revising it from 3 to 4 per cent a year). This took increasing amounts off receipts
relative to our March 2016 forecast, reaching £0.5 billion a year by 2020-21.

8Department for Transport, Provisional Road Traffic Estimates: Great Britain July 2016 – June 2017, September 2017.

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The public finances

3.35

Alcohol duties were a little higher than expected in 2016-17 relative to both forecasts. This
reflected stronger-than-expected consumption of products liable to spirit and beer duty, inpart due to the recent popularity of gin and craft beer.

Table 3.7: 2016-17 fuel, tobacco and alcohol duties forecasts
Forecast

Outturn£ billion
Differenceof which:
PolicychangesMarch 2015 forecast
Fuel duties
Tobacco duties
Alcohol duties
March 2016 forecast
Fuel duties
Tobacco duties
Alcohol duties

FiscalEconomic
forecasting
factors
difference

27.2
9.0
10.8

27.9
8.7
11.1

0.8
-0.3
0.3

-0.4
0.0
-0.1

0.3
0.0
0.0

0.9
-0.3
0.4

27.6
9.2
10.9

27.9
8.7
11.1

0.3
-0.5
0.2

0.0
0.0
0.0

-0.2
0.0
0.0

0.5
-0.5
0.1

Other receipts
3.36

Other notable forecast differences in 2016-17 include:•

North Sea oil and gas revenues in 2016-17 were close to zero, as repayments ofpetroleum revenue tax offset net corporation tax payments. This fell short of themodest revenues expected in March 2015, but outperformed our March 2016
forecast, which expected repayments to exceed payments. The differences largely
reflect gyrations in the oil price and associated fluctuations in the oil price futures that
we use as conditioning assumptions for the first two years of each forecast.

•Business rates receipts were higher than expected (by £0.4 and £1.0 billion versus ourMarch 2015 and March 2016 forecasts respectively). In October 2016, the ONS
revised outturn data higher for recent years, in particular higher estimates of Scottish
business rates were included. This helps explain the positive fiscal forecasting
difference relative to both forecasts.

•

Council tax receipts were £1.5 billion above our March 2015 forecast but only
£0.3 billion above our March 2016 forecast. 9 Part of that reflects the £0.4 billion boost
to council tax receipts from the Spending Review 2015 decision to allow some local
authorities to raise council tax rates more quickly to meet some of the costs associatedwith adult social care and policing. This is discussed in more detail in the local
authority spending section below.

•

Relative to our March 2015 forecast, insurance premium tax (IPT) receipts wereboosted by £1.5 billion as a result of successive policy measures that increased the9Differences in the council tax forecast do not fully reconcile to differences in local authority council tax receipts (see Table 3.10) because
they are measured on a different basis.

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The public finances

standard rate from 6 to 10 per cent by October 2016 (based on the costing estimates
made at the time). The standard rate was raised again to 12 per cent in June 2017.
•

We include all environmental levies in our forecast where the ONS has announced
classification decisions, but some are yet to appear in ONS outturn data. We treat
these differences between forecast and outturn as classification effects in the summary
tables shown in Annex A. The larger levies (such as feed-in tariffs) have a neutral effecton the public finances, increasing both receipts and spending by the same amounts.

•

Scottish taxes cover receipts from land and buildings transaction tax (LBTT) and Scottish
landfill tax that were introduced by Scottish Parliament from April 2015. These came inclose to forecast, with the tables in Annex A showing no differences large enough toround to £0.1 billion. We discuss our forecasts for Scottish taxes in detail in a Devolved
taxes forecast publication alongside each EFO. The Scottish Fiscal Commission – ourequivalent in Scotland – has recently taken responsibility for forecasting these taxes for
the Scottish Government. It has published its own detailed evaluation of the Scottish
Government’s forecasts of these taxes for 2016-17. 10•Interest and dividend receipts came in £1.8 billion below our March 2015 forecast.
£1.0 billion of this reflects economic factors. Notably, Bank Rate was 0.7 percentage
points lower than implied by market expectations at the time of our forecast.

Spending
3.37

In cash terms, our spending forecasts have been far more stable than our receipts forecasts– and the aggregate forecast differences have tended to be smaller. That in part reflects thefact that much public spending is insulated from short-run economic fluctuations. One key
exception is debt interest, which is sensitive to changes in inflation, interest rates and theamount of gilts held in the Bank of England’s Asset Purchase Facility, which returns much of
the interest received on them to the Exchequer. Policy changes can also be significant, as
has been the case this year.

3.38

Table 3.8 summarises the sources of spending forecast differences relative to our March
2015 and March 2016 forecasts for 2016-17:•

10

Relative to our March 2015 forecast: the £20.0 billion underestimate is dominated by
the large increase in departmental spending announced in the Conservative
Government’s post-election July 2015 Budget relative to the sharp fall that had been
pencilled into the Coalition’s final Budget in March 2015. Local authorities’ selffinanced current expenditure was also much higher than expected as they borrowed
more than we expected and drew down reserves to support higher spending, incontrast to our assumption that, as in preceding years, they would continue toconstrain spending to build up their reserves. These upside surprises were partly offset
by lower-than-expected spending on debt interest (due to lower interest rates) and

Forecast evaluation report: September 2017, Scottish Fiscal Commission, 2017.

Forecast evaluation report58The public finances

welfare spending (due to policy measures and lower-than-expected tax credits andpensioner benefits caseloads, more than offsetting higher incapacity and disability
benefits spending).
•

Relative to our March 2016 forecast: the £2.0 billion overestimate reflects a number ofoffsetting factors. Local authorities’ spending was higher than expected for the same
reasons noted above, while expenditure transfers to the EU were lower than expected
due to timing effects that pushed more of calendar year 2017 contributions into 201718 than we had assumed. Personal tax credits spending was again lower than
expected.

Table 3.8: 2016-17 spending forecast differences

PSCE in RDEL
Locally financed current expenditureWelfare spending
Net debt interest payments
Expenditure transfers to EU institutions
Net public service pension payments
Other current expenditure
Current expenditure
PSGI in CDEL
Other capital expenditure
Gross investment
Less depreciation
Net investment
Total spending

Forecast
March 2015 March 2016
293.2
313.8
40.0
40.8
219.5
218.3
40.4
35.4
9.4
11.8
11.2
11.2
60.7
63.2
674.4
694.5
45.4
46.0
31.4
32.8
76.8
78.8
42.2
41.7
34.6
37.1
751.3
773.3

£ billion
Outturn

Difference
March 2015 March 2016
312.5
19.3
-1.3
45.1
5.1
4.3
216.9
-2.6
-1.3
35.5
-4.9
0.1
8.8
-0.6
-3.0
11.2
-0.1
0.0
62.6
1.9
-0.6
692.6
18.2
-1.9
45.8
0.4
-0.2
32.8
1.4
0.1
78.6
1.8
-0.1
40.8
-1.4
-0.9
37.9
3.2
0.8
771.3
20.0
-2.0

Departmental expenditure limits (DELs)
3.39

The Government sets departmental current and capital spending budgets at Spending
Reviews – these budgets are known as departmental expenditure limits (DELs) and are split
between current (or resource) spending (RDEL) and capital spending (CDEL). These plans
tend to be adjusted in subsequent Budgets and Autumn Statements. Departments typicallyunderspend against the limits they have been set, so that actual DEL spending – which iswhat matters for our borrowing forecast – is usually below the final plans. Our main
forecast judgement in relation to DEL spending is an assumption about the extent ofunderspending against plans in the years for which they have been set.

3.40

In evaluating our DEL spending forecasts, we first remove the effect of classification
changes. We then calculate the difference between our underspend assumptions and an‘outturn’ relative to plans as they stood after the Autumn Statement of the year in question. 11
This leaves a residual that reflects policy changes to plans on a broadly like-for-like basis.

11

For 2016-17, we show differences relative to plans set out in the Treasury’s Public Expenditure Statistical Analyses (PESA) 2016
document, adjusted for DEL policy measures announced in Autumn Statement 2016.

59

Forecast evaluation report

The public financesThis ordering is different to the rest of our evaluation work, where policy effects arecalculated first and fiscal forecasting differences inferred by residual.
3.41

A number of relatively small classification changes, most of which are neutral for spending
overall, are relevant to our March 2015 and March 2016 forecasts. Some previously
unaccounted for income (such as fees for services, which are treated as negative DEL
spending) has been included in the public finances data and has reduced RDEL spending
and PSNB. Larger classification changes have affected earlier forecasts, as detailed in thetables in Annex A.

3.42

Abstracting from these classification changes, DEL spending in 2016-17 was much higher
than our March 2015 forecast (due to subsequent policy changes) and a little lower thanour March 2016 forecast (due to greater-than-expected underspending).

3.43

Our March 2015 forecast preceded the 2015 General Election, at which point detailed DELplans had not been set out beyond 2015-16. Our DEL spending forecast was derived byresidual from the Coalition Government’s policy assumption on total spending and ourforecast for annually managed expenditure (AME). On that basis, the Coalition’s final
Budget would have required a £14.8 billion year-on-year cash-terms cut in RDEL spendingin 2016-17 (around 6 per cent in real terms) and allowed CDEL spending to rise by £0.5
billion in cash terms on the previous year (roughly flat in real terms).

3.44

In the post-election Budget of July 2015, the new Conservative Government raised the pathfor DEL spending significantly. In the Spending Review that followed in November 2015, it
increased DEL spending further in every year covered by the plans. At this event, RDEL
spending increased by £5.7 billion in 2016-17 (roughly flat in real terms) and CDEL
spending by £3.2 billion (a real terms rise of 7 per cent).

3.45

In March 2015, we did not present an illustrative path for implied DEL plans andunderspending relative to them that would have been consistent with the forecast path for
DEL spending. Other than classification changes, we have therefore shown all the £19.7
billion difference in DEL spending as the result of policy changes. Even if we had produced
an illustrative underspend assumption that could be compared with the outturn, it would
undoubtedly have been swamped by the size of the policy change.

3.46

Our March 2016 forecast reflected the new departmental budgets for 2016-17 that had
been set in the Spending Review. We assumed departments would underspend these plansby £2.5 billion (comprising £0.5 billion versus RDEL plans and £2.0 billion versus CDEL).
The latest data suggest that they underspent by £5.0 billion in total, with spending a muchlarger-than-expected £3.7 billion below RDEL plans but only a £1.3 billion below CDEL
plans. Underestimating underspending explains the majority of the £1.5 billion overestimateof total DEL spending. Subsequent policy changes largely shifted planned spending between
current and capital, notably for the Department of Health.

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Table 3.9: 2016-17 DEL forecast differences£ billion
Forecast

March 2015 forecast
TME in DELof which:
PSCE in RDELPSGI in CDEL
March 2016 forecast
TME in DELof which:
PSCE in RDELPSGI in CDEL

Outturnof which:

Difference
Classification
changes

Policychanges

FiscalEconomic
forecasting
factors
difference

338.6

358.3

19.7

-0.3

20.0

0.0

0.0

293.2
45.4

312.5
45.8

19.3
0.4

0.0
-0.3

19.3
0.7

0.0
0.0

0.0
0.0

359.8

358.3

-1.5

0.2

0.8

0.0

-2.5

313.8
46.0

312.5
45.8

-1.3
-0.2

0.2
0.0

1.7
-0.9

0.0
0.0

-3.2
0.7

Locally financed current and capital expenditure
3.47

Table 3.10 shows that we underestimated local authorities’ locally financed current andcapital expenditure by substantial amounts in both our March 2015 and March 2016
forecasts. With only small effects from subsequent policy announcements, these differences
almost entirely reflect fiscal forecasting differences related to the assumptions underpinning
our forecasts. The table breaks down the differences by the source of local finance.

3.48

For local authorities’ locally financed current spending, it is important to distinguish between
differences that relate to forecasting the income streams that finance this spending, such ascouncil tax and retained business rates, and those that relate to our assumptions about how
much authorities will spend relative to that income, which are embodied in our assumptions
about their use of current reserves or repayment of debt. It is only spending relative toincome that affects net borrowing, so in our forecasting framework we place particularemphasis on understanding and evaluating the evolution of reserves and debt repayments,
and the underlying drivers of those changes.

3.49

Our March 2015 and March 2016 forecasts underestimated self-financed current
expenditure by £5.1 and £4.3 billion respectively. Within those overall differences:•£3.2 and £2.9 billion reflects higher-than-expected spending relative to income, fromlocal authorities’ use of their current reserves and repayment of debt, implying higher
public sector net borrowing. Our earlier forecasts assumed that local authorities wouldease the downward pressure on their spending from tighter financial settlements bydrawing down reserves. This was consistent with local authorities’ own budgets. But
they surprised us repeatedly by spending less than budgeted and thereby adding toreserves. Our March 2015 and March 2016 forecasts both assumed that reserves
would continue to build up, more so in March 2016, although both forecasts assumed
that this build-up would cease within the forecast horizon. In fact, data released sincethese forecasts suggest that the trend was reversed in 2015-16, when reserves inaggregate were drawn down for the first time since 2009-10 and by £0.4 billion in
61

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The public finances

total. Provisional outturn data for current spending in 2016-17 show that English andScottish local authorities drew down a much larger £1.7 billion from their reserves.
This accounts for around £2½ billion of the forecast difference relative to both
forecasts. While the reserves drawdown exceeded our forecasts, debt repayments werelower than forecast, which increased spending and borrowing by £0.8 and £0.4
billion relative to our March 2015 and March 2016 forecasts respectively.
•£1.1 and £0.8 billion reflects higher-than-expected income from council tax andretained business rates financing higher expenditure (implying no effect on public
sector net borrowing). Local authorities’ council tax income was higher than expected,
particularly relative to our March 2015 forecast. At Autumn Statement 2015, local
authorities’ spending power was increased by giving them flexibility to raise council tax
further to finance adult social care and police services. This was expected to add £0.4
billion to spending power in 2016-17. Even after allowing for that, our March 2015
forecast underestimated council tax revenue by £1.0 billion (a larger-than-average
difference, driven largely by higher council tax base growth, which we reflected insubsequent forecasts).

•

In both forecasts we also overestimated the amount of capital expenditure that local
authorities would finance from their revenue accounts. This meant that, for a given
income, local authorities’ current spending was higher than expected and their capitalspending was lower by an offsetting amount. This accounted for £0.6 and £0.4 billionof the higher current spending relative to March 2015 and March 2016 respectively.

3.50

Our March 2017 forecast reflected the more recent data on local authorities’ net current
expenditure and the latest sector intelligence by forecasting a drawdown of reserves in
2016-17, although the provisional outturn is higher than this forecast predicted. We will be
exploring the drivers and forecast implications of the latest data ahead of our forthcoming
November forecast. Initial analysis suggests that social care spending pressures (which
relate to both adults and children) may have been a contributing factor: English local
authorities with social care responsibilities drew down £1.4 billion from their reserves while
those without such responsibilities increased them by £0.2 billion.

3.51

Table 3.10 shows that we also underestimated local authorities’ locally financed capitalspending in both forecasts, by £0.7 and £1.9 billion respectively. This was despite there
being less capital spending financed from revenue accounts. Within those differences:•

Prudential borrowing was much higher than expected in 2016-17. This accounts for£2.7 and £2.8 billion of the difference relative to each forecast. This was flagged as apotential risk in our Fiscal risks report in July, following reports that some of thisborrowing was being used for commercial property investments rather than activities
directly related to local authorities’ provision of public services.

•

The additional capital spending was reduced by an offsetting error on the adjustmentthat we make to switch spending between sectors for the net capital spending of local
authorities’ Housing Revenue Accounts (HRAs). HRAs are treated as public corporations

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62

The public financesin the National Accounts, and so we switch their net capital spending between the local
authority and public corporation sectors in our forecast. We underestimated thisspending in 2016-17 by about £0.6 billion in both forecasts, which reduced ouroverall forecast difference on local authority self-financed capital spending but
increased it for public corporations’ capital spending.

Table 3.10: 2016-17 locally financed current expenditure forecast differences

March 2015 forecast
Locally financed current expenditureof which:
Net use of current reserves
Funds set aside to repay debt
Council tax
Retained business rates
Other 1
Locally financed capital expenditureof which:
Prudential borrowing
Adjustment to remove HRA net capital spending
Other 1March 2016 forecast
Locally financed current expenditureof which:
Net use of current reserves
Funds set aside to repay debt
Council tax
Retained business rates
Other 1
Locally financed capital expenditureof which:
Prudential borrowing
Adjustment to remove HRA net capital spending
Other 1

Forecast£ billion
Outturn

Difference

40.0

45.1

5.1

-0.7
-3.2
28.2
15.7
-0.1
8.1

1.7
-2.4
29.5
15.5
0.8
8.8

2.4
0.8
1.3
-0.3
0.9
0.7

5.6
-2.6
5.1

8.3
-3.2
3.7

2.7
-0.6
-1.3

40.8

45.1

4.3

-0.8
-2.8
29.4
14.8
-3.4
6.9

1.7
-2.4
29.5
15.5
0.1
8.8

2.5
0.4
0.1
0.7
3.5
1.9

5.6
-2.7
4.0

8.3
-3.2
3.7

2.8
-0.5
-0.3

1

Includes capital expenditure financed from local authorities' revenue accounts, which increases local authorities' capital expenditureand reduces their current expenditure by offsetting amounts.

Welfare cap and other welfare spending
3.52

Total welfare spending was lower than we forecast in both March 2015 and March 2016.
Unpicking the precise sources of these forecast differences is made more challenging by thefact that our forecasts include estimates of the marginal effect of universal credit (UC)relative to the existing benefits and tax credits systems, whereas all spending in outturn is ona full-cost basis. But since UC spending largely offsets spending on existing benefits in
2016-17, this does not alter the broad explanations of the £2.6 and £1.3 billion forecast
differences for March 2015 and March 2016 respectively.

3.53

In both cases, the main source of difference was spending subject to the welfare cap. Our
March 2015 forecast was made before the Conservative Government’s announcement of
63

Forecast evaluation report

The public financeslarge cuts in welfare spending in the July 2015 Budget, some of which were reversed before
implementation in the subsequent Autumn Statement. Even so, the original estimates ofpolicy changes announced after our March 2015 forecast account for £2.5 billion of theforecast difference. The remaining fiscal forecasting difference reflects a number of partly
offsetting factors, with spending on incapacity and disability benefits higher than expected
but spending on tax credits significantly lower than expected. Relative to our March 2016
forecast, the fiscal forecasting difference shows a larger unexpected shortfall in spending.
The same partly offsetting factors were at play but balanced differently because we hadrevised up our incapacity and disability benefits forecasts by then.
3.54

Tax credits spending has been consistently lower than our recent forecasts and we havebeen exploring the source of these differences for some time. Relative to our March 2015
and March 2016 forecasts, the shortfalls were £2.3 and £1.1 billion respectively. Around£½ billion reflects an overestimate of net tax credit overpayments in both forecasts. The
methodology used here has already been reviewed and refined. Another £½ billion reflects
lower-than-expected caseloads, mainly due to a sharply declining number of new claimants,
where higher-than-forecast earnings among the relevant population led to fewer awards.
This issue remains under review for our November forecast. The out-of-work caseload has
also been affected by the faster-than-expected decline in unemployment.

3.55

Spending outside the welfare cap was closer to our forecasts. For March 2015 in particular
this reflected offsetting sources of forecast difference, as state pensions spending wasaffected by higher-than-expected triple-lock uprating but a lower-than-expected caseload
due to a higher-than-expected number of deaths.

Table 3.11: 2016-17 welfare spending forecast difference£ billion
Forecast

March 2015 forecast
Welfare spendingof which:
Welfare cap
Non-welfare cap
March 2016 forecast
Welfare spendingof which:
Welfare cap
Non-welfare cap

Outturn

Differenceof which:
Classification
changes

Policychanges

FiscalEconomic
forecasting
factors
difference

219.5

216.9

-2.6

0.0

-2.5

0.5

-0.5

121.0
98.5

118.7
98.2

-2.2
-0.3

0.0
0.0

-2.5
0.0

0.0
0.4

0.2
-0.7

218.3

216.9

-1.3

0.0

0.1

0.3

-1.7

119.8
98.4

118.7
98.2

-1.1
-0.2

0.0
0.0

0.1
0.0

0.1
0.2

-1.4
-0.4

Central government debt interest (net of the APF)
3.56

Debt interest payments were significantly lower than we expected in our March 2015
forecast, but close to our March 2016 forecast. Relative to our March 2015 forecast,differences in assumptions about the key underlying determinants reduced spending.
Interest rates – both short- and longer-term – have been lower than market expectations (onForecast evaluation report

64The public finances

which we base our assumptions) at the time. This was partly offset by a higher RPI inflation,
which raised accrued payments on index-linked gilts. Relative to our March 2016 forecast,the RPI effect dominated the effect of lower interest rates.
3.57

A higher-than-expected interest saving associated with the Bank of England’s Asset Purchase
Facility reduced spending relative to both forecasts. Neither anticipated the August 2016
package of monetary policy measures that resulted in a significant increase in the APF’s gilt
holdings relative to the assumptions underpinning both forecasts. The Monetary Policy
Committee also cut Bank Rate from 0.5 to 0.25 per cent, reducing the cost of financing the
APF. These factors have led to larger interest savings for Government. We treat differences
relating to the size of the APF as fiscal forecasting ones since it is a judgement that we feed
into our debt interest models rather the one we derive from market expectations.

Table 3.12: 2016-17 debt interest forecast difference£ billion
Forecast

March 2015 forecast
March 2016 forecast

40.4
35.4

Outturn

35.5
35.5

of which:

Difference

-4.9
0.1

Classification
changes

Policychanges

0.0
0.0

0.0
0.0

FiscalEconomic
forecasting
factors
difference
-3.2
-1.7
1.1
-1.0

Expenditure transfers to EU institutions
3.58

The forecasts considered in this report were produced before the EU referendum, while theoutturns have not been directly affected by its result. But even abstracting from thereferendum, forecasting EU contributions has always been challenging due to uncertainties
around EU budgets and associated negotiations, as well as the implicit need to forecast
gross national incomes for 27 other member states, as well as the UK.

3.59

EU contributions in 2016-17 were slightly lower than forecast in March 2015 (by £0.6
billion) but significantly lower than our March 2016 forecast (by £3.0 billion). Both forecasts
were affected by the European Commission’s unexpected and unusual decision not to draw
forward future months’ contributions into the first quarter of 2017. (It has typically requested
five months’ contributions in the first quarter.) This more than explains the March 2015
difference and accounts for half the overestimate in our March 2016 forecast.

3.60

The reasons for revising the forecast up between March 2015 and March 2016, and thus
the larger overestimate of spending in that forecast, were largely related to the EU budget
and its implementation – key drivers of the amount that the UK needs to contribute eachyear. In November 2015, we revised up assumed EU spending in line with the 2016 EU
budget proposal, in which additional funding was allocated to deal with the migration crisis.
We retained this assumption in March 2016 in the absence of new information. In theevent, actual spending on areas unrelated to migration was significantly lower than
expected, reducing the amount to be covered by member states’ contributions.

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Forecast evaluation report

The public finances

Table 3.13: 2016-17 EU expenditure transfers forecast differences£ billion
Forecast

March 2015 forecast
March 2016 forecast

9.4
11.8

Outturn

8.8
8.8

of which:

Difference

-0.6
-3.0

Classification
changes

Policychanges

0.0
0.0

0.0
0.0

FiscalEconomic
forecasting
factors
difference
0.0
-0.6
-0.1
-2.9

Other spending
3.61

Other points of note in our analysis of spending forecast differences this year include that:•

Although our overall forecasts for public service pensions in 2016-17 have been close
to outturn, there have been offsetting movements across individual pension schemes.
Factors driving this have included differences between assumptions and outturns on
early retirements and mortality rates, as well as the response of scheme members torecent policy changes that permit those approaching retirement to ‘opt out’ of changes
in membership terms. Lump sum payments are particularly volatile as retirement
behaviour can be difficult to predict, and even small differences in average values or
the number of awards can create sizeable deviations from forecast. In addition, thetiming and the size of bulk transfers in and out of the schemes – e.g. the movement of
Public Health England’s members into the civil service pension scheme – can often
lead to relatively large one-off differences.

•

General government depreciation was lower than we forecast in both March 2015 andMarch 2016, as the average rate of depreciation across the government capital stock
appears to have been lower than expected. Depreciation does not affect total spendingor net borrowing, but does affect the current budget deficit.

•

Tax litigation costs were higher than expected at £1.8 billion, but their statisticaltreatment in outturn differed from their treatment in our forecasts. In March 2015, we
included £0.8 billion as negative tax in 2016-17, while in March 2016 we included£0.9 billion as positive spending. In the event, the ONS has treated all the payments
made by HMRC in 2016-17 as financial transactions (not affecting receipts, spending
or borrowing, but counting against debt since the cash has left the public sector)
because they are ‘interim’. Consistent with National Accounts guidance, they will only
be recognised in spending and borrowing after final decisions on the relevant cases
have been made and the value of associated payments finalised. It is difficult toforecast when that might occur given the many options HMRC has for appealing
judgements even after making interim payments.

•

On the latest data there are large differences between forecast and outturn foraccounting adjustments, with large upside surprises on current spending only partly
offset by downside surprises on capital spending. Across both, the differences amountto around £4 billion and £3 billion relative to our March 2015 and March 2016
forecasts respectively. Thanks to analysis of similar differences in last year’s FER, part

Forecast evaluation report

66

The public financesof these differences have already been reflected in our most recent forecasts. But asignificant amount remains unexplained, reflecting unallocated differences between
the outturn estimates we are using for the various detailed components of spending
and the latest total spending outturns included in the September ONS public finances
release. These could reflect temporary timing differences when comparing the latest
OSCAR and other source data with the data underlying the ONS estimates, but there
could also be genuine underlying factors that would affect our future forecasts. We will
be working further with the Treasury and the ONS to understand the sources of thesedifferences more fully as we prepare our November forecast.

Public sector net debt
3.62

In this section we focus on the year-on-year change in debt, rather than its level at the endof the year. This allows us to abstract from differences between forecast and outturn that
result from the starting level assumed in each forecast.

3.63

Our March 2015 and March 2016 forecasts did not reflect the August 2016 monetary
policy package, which has added to PSND in 2016-17 as a result of the purchases ofadditional gilts and corporate bonds by the Bank of England Asset Purchase Facility (APF)
and the lending to commercial banks under the Bank’s Term Funding Scheme (TFS). Our
March 2016 forecast included the reclassification of most English housing associations into
the public sector but neither forecast reflected the subsequent reclassification of the Scottish,
Welsh and Northern Irish housing associations. We have restated our forecasts to beconsistent with the latest treatment of housing associations in the outturn data, so as to focus
on like-for-like forecast differences.

3.64

The August 2016 monetary policy package meant that the APF added around £75 billion
more to PSND than the relatively small amounts we had factored into forecasts made before
that package had been announced. Abstracting from this, PSND increased by less than we
expected in our March 2015 forecast, but more than we expected in our March 2016
forecast. Table 3.14 compares each forecast against the latest estimates. It shows that:•

Relative to our March 2015 forecast, higher-than-expected gilt premia were the main
factor contributing to the smaller-than-expected rise in PSND. We assumed that gilts
would continue to be sold at a premium to their face value, at which they are valued in
PSND, but that this would be more than offset by the accounting impact of premia
related to earlier years’ sales unwinding. But further falls in gilt yields caused muchhigher premia on new gilts than we had expected. 12 Movements in sterling also affectthe value of the unhedged component of the international reserves that are netted off
PSND. The fall in the pound also contributed to the smaller-than-expected increase in
PSND. Offsetting upward contributions included higher borrowing and other accruals
adjustments (e.g. the new accounting treatment for corporation tax receipts).

12

PSND rises by the nominal value of gilts issued, rather than their market value, so the prices obtained in gilt auctions have an
accounting impact on public sector net debt.

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Forecast evaluation report

The public finances•

Relative to our March 2016 forecast, PSND increased a little more than expected.
Lower-than-expected proceeds from UKAR and other asset sales were the main factor
behind this larger-than-expected rise. This forecast reflected UKAR’s decision to begin
a major sale programme of Bradford & Bingley (B&B) mortgages, but the sale wasdelayed following the referendum. It was completed in April 2017, so reduced PSND
in 2017-18 instead. Our forecast also included the expected proceeds from starting tosell the student loan book in 2016-17 and the sale of £5.4 billion of RBS shares. The
sale of student loans was also delayed, while RBS share sales were put on hold after
the referendum result. Lower-than-expected borrowing and higher-than-expected gilt
premia were the main offsetting factors. Other accruals adjustments, including thoserelated to corporation tax receipts, again raised debt by more than expected.

Table 3.14: The change in public sector net debt in 2016-17
1

Net borrowing
Lending
Asset sales
UKAR
Gilt premia
International reserves
Other non-APF factors
Non-APF related change in net debt
Asset Purchase Facility effects
Change in net debt
1

Forecast
March 2015 March 2016
42.7
55.9
17.2
18.6
-2.8
-11.7
-5.7
-14.3
-6.4
-8.0
0.0
-0.4
7.0
5.1
52.1
45.2
-1.5
3.1
50.6
48.2

£ billion
Estimates
45.0
19.6
-3.5
-4.9
-18.8
-4.4
14.5
47.5
76.6
124.1

Difference
March 2015 March 2016
2.4
-10.9
2.4
1.0
-0.8
8.2
0.8
9.5
-12.5
-10.9
-4.4
-4.0
7.5
9.4
-4.6
2.3
78.2
73.5
73.5
75.8

Forecasts have been restated to reflect the reclassification of housing associations to the public sector.

Year-to-date borrowing in 2017-18
3.65

The September 2017 estimate of PSNB in 2016-17 is £45.0 billion, £6.7 billion below ourMarch forecast and, as set out in Box 3.1, £7.0 billion lower than the initial ONS estimate
from April. Relative to both our forecast and the initial estimate, this reflects the combined
effect of classification and methodology changes and higher-than-expected receipts acrossa range of taxes, plus other smaller effects. Some of these elements are likely to lead tolower borrowing than we expected in 2017-18 too (e.g. from the methodological changes
and, assuming no change in expected bonus growth, the higher tax from bonuses at theend of 2016-17). Others may or may not feed through (e.g. higher VAT and corporation tax
receipts could be timing effects rather than signalling stronger ongoing performance).

3.66

On the latest estimate, borrowing in the first five months of 2017-18 was broadly flat
relative to the same period in 2016-17. Our March forecast predicted that borrowing in thefull year would be £58.3 billion, a £6.5 billion year-on-year rise relative to our March
estimate of 2016-17 borrowing but a £13.2 billion rise relative to the latest ONS estimate,following the large downward revisions.

Forecast evaluation report

68The public finances

3.67

Growth in central government receipts over the first five months of 2017-18 of 3.7 per centhas been higher than our full-year forecast of 2.4 per cent. We would expect receipts
growth to outpace our full-year forecast until later in the fiscal year because the negative
contribution from lower self-assessment receipts (where the boost to 2016-17 receipts from
dividend income shifting (described in Box 4.3 of our March EFO) will be reversed this year)
will only be seen in the data in early 2018. Looking at specific taxes, PAYE income tax and
NICs receipts have risen faster in the first five months of 2017-18 than our full-year forecast(4.0 versus 2.9 per cent). This may be because PAYE receipts were subdued in the first halfof 2016-17 rather than signalling stronger-than-expected performance this year. VAT
receipts so far this year are close to our full-year forecast (3.1 versus 2.9 per cent).

3.68

Central government spending (excluding grants to local authorities) over the first fivemonths of 2017-18 was up 4.4 per cent on the same period in 2017-18, slightly slower
than our full-year forecast of 4.9 per cent. Our March forecast assumed a large rise in debt
interest payments (reflecting the effect of higher RPI inflation on index-linked gilts) and
expenditure transfers to the EU (reflecting the timing of calendar year 2017 payments). Thishas been borne out in the data for the year to date, with debt interest payments up 17 percent (against a full-year forecast of 14.6 per cent) and expenditure transfers to the EU up 28
per cent (in line with our full-year forecast).

3.69

There is still considerable uncertainty around prospects for the rest of 2017-18 – and, asrevisions to 2016-17 have shown, it is quite possible that the latest estimates could change
significantly over time. The judgements we make about in-year receipts and spending are
likely to be an important factor in our next forecast, which will be published alongside theChancellor’s Autumn Budget on 22 November. These will depend on many factors,
including the extent to which we expect better 2016-17 outturns to be repeated in 2017-18
or to reflect either one-off developments or timing effects, any further news in the monthly
data flow, and any changes to our economy forecast for the rest of the fiscal year.

69

Forecast evaluation reportForecast evaluation report70

4

Refining our forecasts

Introduction
4.1

We strive to provide the greatest possible transparency around our forecasts, to facilitate
understanding and to ensure that we can be held to account for the judgements we make.
Transparency also permits us to scrutinise our own forecasts in detail, examining andexplaining the inevitable differences from outturns. We hope that this will reassure users that
our forecasts are based on impartial professional judgement, rather than politicallymotivated wishful thinking, even if they disagree with our conclusions. The process also
affords an opportunity to learn lessons that can be applied in future forecasts.

4.2

In this chapter we:•

Identify lessons that have emerged from the evaluation described in Chapters 2 and 3.
As tends to be the case, these include a number that echo lessons from previous
evaluations or that have already been addressed during a forecast process.

•Describe the systematic review of fiscal forecasting models that we have carried out toenhance our ongoing work to refine forecast judgements and methodologies. Thesemodels are tools – typically operated on our behalf by analysts in other departments –used to help us construct each line of our fiscal forecasts.

Lessons learnt
4.3

The lessons highlighted in our Forecast evaluation reports (FERs) have often been acted
upon already, because they were identified during the preparation of our Economic andfiscal outlook (EFO) forecasts. In some areas, that has been repeated this year. Lessons thathave been reinforced include:•

The importance of the composition of labour income, noting that employment-driven
growth has been less tax-rich than earnings-driven growth would have been.

•

Savings associated with major reforms of the incapacity and disability benefits systems
had fallen short of expectations, due largely to challenges in delivering the reforms.
This has been a theme of recent FERs and is an issue that we have explored in depth in
EFOs and our Welfare trends reports. We revised up our forecasts for spending onthese benefits in 2016-17 by £1.6 billion between March 2015 and March 2016, but
in the event that still proved too little. We have revised these forecasts up further sincethen – in particular disability benefits, where the reforms are further from completion.

71

Forecast evaluation reportRefining our forecasts•

The challenges in forecasting self-assessment (SA) income tax and capital gains tax
receipts. Thanks to data limitations, these forecasts rely on inputs that are less closelyaligned with the true tax base than we would like. The assumptions that need to be fed
into the forecasting models are therefore a significant source of uncertainty around theforecasts themselves. Forecasting SA tax receipts is further complicated by large
behavioural responses to policy changes (e.g. forestalling ahead of last year’s dividend
tax rise), trends towards incorporations and changes in the income distribution.

•

The use of local authority reserves has been a repeated source of surprise relative to
our forecasts. Against our earlier forecasts, this was because local authorities
underspent against their budgets and added to their reserves when we had expectedbudget cuts to prompt them to draw on those reserves. Relative to the forecasts
evaluated in this report, local authorities have utilised more of their reserves than wewere expecting. Prudential borrowing in 2016-17 was also higher than expected.

4.4

One persistent theme in the evaluation of our economy forecasts – and which has beenaddressed in repeated, though seemingly inadequate, revisions in past EFOs – is the
weakness of productivity growth and the strength of employment growth. This pattern has
been repeated at a one-year horizon relative to every one of our spring forecasts, and it
held regardless of whether GDP growth as a whole exceeded or fell short of our forecast.
Considering the first half of 2017 relative to our most recent forecast from March, the same
pattern has been repeated more forcefully.

4.5

In the light of this and in preparation for our November forecast we have reviewed the latest
evidence against our March forecast judgements and the explanations of the productivity
puzzle that informed them. It seems clear that we will need to revise down trend productivity
growth again, but also that our equilibrium unemployment assumption is too high and thatassuming the historical downward trend in average hours worked will resume in the shortterm is not justified. We will review all the available evidence as we prepare our November
forecast, but it is highly likely that the downward revision to productivity growth will
dominate in terms of its effect on cumulative GDP growth over the forecast horizon and theassociated consequences for the budget deficit.

4.6

While most of the major issues that we have identified in this year’s evaluation havefeatured in previous reports, we have identified some new issues that include:•

The importance of corporation tax payment timing assumptions. The speed at which
companies pay off the liabilities arising from a particular year’s profits can have amarked effect on receipts. In addition, the surge in receipts from life assurancecompanies in 2016-17 suggests that we need to look further at how the effect of bondprice movements on profits in the sector are modelled.

•

The unexplained downward trend in tax credits and in-work housing benefit caseloads.
In recent forecasts we have made successive and substantial downward revisions to tax
credits spending, with similar, if smaller, revisions to the in-work element of the
housing benefit caseload. In tax credits this appears to be related to lower-than-

Forecast evaluation report72Refining our forecasts

expected inflows (rather than higher-than-expected outflows) and to average incomes
across the caseload rising faster than assumed. The underlying drivers of these
forecast differences remain under investigation.
•

The challenges and importance of the in-year estimates for receipts and spending thatform the basis of our fiscal forecasts. As most of our models are specified to forecast
the growth of a tax or spending stream from a starting point, any difference between
forecast and outturn for the year in progress when the forecast is made will compoundover the forecast period. We use the latest available data – including administrative
data – when making these estimates, but the pattern of receipts or spending throughthe year can change and subsequent revisions can change the picture significantly, as
illustrated by the large revisions to 2016-17 since our March forecast.

Review of fiscal forecasting models
4.7

In preparing our fiscal forecasts we utilise more than 350 individual models of greatly
varying size and complexity. We start the forecast process by considering how our mostrecent forecast has performed against the flow of monthly data and any other relevant
information. In doing so, we frequently identify issues that prompt us to refine ourjudgements or the parameters of our models.

4.8

In line with the recommendations of the Treasury’s September 2015 review of the OBR, wehave introduced a more systematic approach to following up our analysis of fiscal
forecasting differences and issues raised in EFO forecasting rounds. We have been working
closely with our partners across government in doing so. This has been guided by the broad
criteria set out in our 2015 FER and refined last year and the fiscal forecasting accuracy
metric that we described in our 2016 FER. 1

4.9

In this year’s FER we set out our initial results and the associated priorities for model
development over the next 12 months. To put that in context, we start by reviewing recent
and ongoing modelling work that has affected, or is expected to affect, our forecasts.

Modelling work over the past year
4.10

The process of refining our models and the judgements underpinning our fiscal forecasts is
a continuous one that draws on analysis prepared in forecasting rounds and for our FERs.
This review builds on existing processes and helps to ensure they are more consistent andfollowed up more systematically. Over the past year, some of the more significant modellingchanges that have already been factored into our forecasts include:•

1

Incorporations model: our tax forecasts include modelled adjustments to reflect thetrend towards employees and the self-employed choosing to incorporate and to workand pay tax as company owner-managers instead. In our November 2016 forecast,
we moved to a new model to estimate the effect of that trend on our receipts forecast.

HM Treasury review of the Office for Budget Responsibility, HM Treasury, September 2015.

73

Forecast evaluation reportRefining our forecasts

The modelling and its implications were detailed in Box 4.1 of that EFO. The overall
effect was to reduce receipts by £1.6 billion in 2020-21 relative to the previous model,
with incorporations estimated to reduce receipts by £2.5 billion in that year relative tothem growing in line with total employment from the start of the forecast period.

4.11

•

VAT standard-rated share (SRS) model: our VAT receipts forecast uses the SRS model
to convert our forecast for consumer spending into the theoretical VAT yield one would
expect from it. The proportion of spending subject to the 20 per cent standard rate of
VAT is the most important element of that modelling. In our March EFO, we moved tousing a new SRS model that better reflected recent trends – in particular those related
to spending on consumer durables – and that improved consistency between our
economy and VAT forecasts. The effect was to reduce VAT receipts by around £0.4
billion in 2021-22.

•

Excise duties models: our fuel and alcohol duties models each use time-series
econometric models to generate forecasts for taxable consumption – known asclearances – of each product. The underlying equations were updated for our
November 2016 and March 2017 forecasts respectively. The overall effect was toboost fuel duty receipts by £1.2 billion in 2021-22, but to reduce alcohol duty receipts
by £0.2 billion in that year.

•

Housing associations model: since the ONS’s October 2015 decision to reclassify
housing associations into the public sector we have been refining our approach toforecasting their effects on the public finances. In our March EFO, we made changes toreflect properly the routing of some central government capital grants to housing
associations via local government. We also introduced new models to forecast theeffects of housing associations in Scotland, Wales and Northern Ireland, wherepreviously we had simply grossed up our forecast for England.

•

Asset Purchase Facility (APF) model: the Bank of England’s APF holds over £400 billionof gilts and currently replaces any that mature by reinvesting the proceeds in new gilts.
As well as affecting debt interest flows between public sector entities, it has anaccounting effect on public sector net debt (PSND) that is driven by the difference
between the market value paid for the gilts that are purchased and their nominal orface value. In our March EFO we corrected the way the model captured changes in thisaccounting effect as the APF is assumed to make future gilt purchases as existingholdings mature, where the market premium had been overestimated. This change
reduced PSND by £20 billion in 2021-22.

Modelling work completed since March that we plan to incorporate in our November 2017
EFO includes:•

North Sea revenues model: over the past year we have been working with HMRC tobuild a new model for projecting oil and gas revenues. The previous model was
opaque, making it difficult to scrutinise the forecast outputs effectively, and timeconsuming for HMRC officials to operate and maintain. While developing the new

Forecast evaluation report74Refining our forecasts

model, HMRC identified an issue in the way that company-level losses were being
carried forward to be set against future profits. This was corrected in our March
forecast, reducing receipts by around £1 billion a year. We do not expect the full moveto the new model in November to have further material effects on the forecast,although it will inevitably deliver different results to those that the old model would
have using the same determinants. Such effects will be set out in the EFO.

4.12

•

Property transaction taxes: we have been working with HMRC and the Scottish Fiscal
Commission (SFC) to develop, respectively, our stamp duty land tax (SDLT) and
Scottish land and buildings transaction tax (LBTT) models. The most significant change
will be to factor in a negative effect on transactions from the rising effective tax rate
through the forecast period that results from house prices rising relative to thethresholds in the progressively structured SDLT and LBTT systems. The extent of thiseffect will be calibrated using initial HMRC analysis of the transactions response to thechanges in effective tax rates across the house price distribution from the reform of
residential SDLT announced in December 2014. This points to effects almost twice
those factored into the costing of that policy change. 2 This change will reduce theextent of fiscal drag over the forecast, with the effect concentrated among higherpriced properties where marginal tax rates are much higher. If we had included thisadjustment in our March 2017 SDLT forecast, it would have been lower by around£0.7 billion in 2021-22. We have also developed a new ‘log-normal’ LBTT model toreplace our previous microsimulation approach. This is similar to the approach usedby the SFC. It is not expected to have a significant effect on our next forecast.

•Depreciation model: we have been working with the Treasury to build a new modelthat is more transparent and that addresses the systematic over-prediction of outturn.
The constraining factors that are applied to link the underlying forecast model to theoutturn data are also being reviewed as part of this process. Moving to this model willaffect the split of net borrowing between the current budget deficit and net investment,
but will have no effect on net borrowing itself.

There are a number of other model development projects that are close to completion, butwhere we cannot yet quantify the effects with confidence. These include:•

Index-linked gilts accrued debt interest model: our debt interest models include
separate treatment of different forms of debt. The most complex of these relates toindex-linked gilts, where accrued debt interest reflects the real coupon, an RPI-linked
coupon payment, an RPI-linked uplift to the value of the gilt and the amortisation of
the premium (or discount) at which it was sold relative to its par value. With realinterest rates currently negative, but real coupons subject to a lower bound of 0.125
per cent, modelling these various effects is more complicated. We have identified anissue whereby the current model appears to overestimate spending on index-linked
gilts by using stylised calculations that do not capture accurately the effects of negative2

We provided detailed information on these behavioural responses in Box 4.5 of our December 2014 Economic and fiscal outlook and a
supplementary release in January 2015. A supplementary release detailing the new elasticities is available on our website.

75

Forecast evaluation reportRefining our forecasts

real rates and the large auction premia that result. We are not yet in a position toquantify the downward revision precisely, but it appears to be material and is likely to
exceed £½ billion a year by the end of the forecast period.
•

4.13

Landfill taxes: we have been working with HMRC and DEFRA to improve our model for
projecting UK Government landfill tax receipts. The model has been changed to focus
more on forecasting the amount of waste paying the higher ‘standard rate’ of tax,
which accounts for over 95 per cent of receipts, rather than the total amount of waste
generated. DEFRA has also re-estimated the profile of waste that is exported orincinerated rather than sent to landfill. By the end of the forecast period these changes
are expected to lower receipts slightly. All else equal this would have proportional
effects on our forecasts for devolved landfill tax receipts in Scotland and Wales.

This is not an exhaustive list of potential modelling changes that will affect our futureforecasts. One important issue that we will revisit is the modelling of disability benefits
spending, where our forecast currently includes a top-down adjustment to caseload growththat aims to capture the updated trend in the proportion of the population claiming thesebenefits. And as always we can expect issues to arise as we update and scrutinise ourmodels through the usual challenge process. In some cases we will be able to adjust ourmodels relatively quickly. In others, the necessary development work will be incorporated
into future plans. We will highlight prospective changes in future FERs where possible.

The 2017 review
4.14

4.15

In carrying out the first review this year:•

We have selected 19 separate tax and spending forecast models to look at in greater
detail. Our choices were based on the amount of tax or spending that they cover, theirperformance against the forecast accuracy metric developed last year, and a review ofissues raised during past challenge and scrutiny processes.

•

We have codified a set of questions that allow us to benchmark fiscal forecast models
against our ideal requirements for them. These have ensured consistency when
considering how individual models perform relative to the five broad criteria describedlast year. They are detailed in the next section.

•

We have assessed each model against these criteria and identified priorities fordevelopment work over the coming year. These are based on our assessment of theimportance of each issue in relation to the tax or spending stream itself and, reflecting
its absolute size, to our overall fiscal forecasts.

Table 4.1 at the end of this chapter summarises the models that we have reviewed this year
and the priorities attached to future development work.

Forecast evaluation report76Refining our forecasts

4.16

It is important to note that the results of this review do not capture every potential issue that
may arise and that the appropriate conclusions may evolve over time. For example, thesuitability of a modelling approach may change as economic factors and policy develop.
This is illustrated by the modelling changes made to our SDLT forecast. Prior to December
2014 we used a time-series econometric approach. At that point significant changes to thepolicy regime meant that relationships estimated from historical data were no longer
relevant to the future. We therefore moved to a microsimulation approach. This calculates
the tax due under the new policy regime on a distribution of property transactions derived
from administrative tax data, which is projected forward in line with our assumptions abouthouse price inflation and the total number of transactions.

Assessment criteria
4.17

There are five criteria against which we assess our fiscal forecast models: accuracy,
plausibility, transparency, effectiveness and efficiency. To consider models against thesecriteria in a consistent way, we codified a set of questions often asked during our usual
challenge and scrutiny processes. As the review progressed, we expanded the list as otherthemes arose. For example, it became apparent that the approach to setting ‘in-year’
forecasts varied across models and was sometimes a key source of differences between
forecast and outturn. We can expect further questions to be added in future reviews.

4.18This section sets out the questions we asked of each model under each assessment criterion.

Accuracy
4.19

How big or consistent are the fiscal forecasting differences? As part of our annual FER
process, we assess the performance of our fiscal forecasts by identifying and explaining thedifference between our forecasts and outturn. We decompose these forecasting differences
into four categories:•classification and accounting treatment changes made by the ONS or the Treasury;•

subsequent Government policy changes;•

economy forecast differences; and•a residual ‘fiscal forecasting difference’.

4.20

We investigate the underlying factors explaining the fiscal forecasting element, which
typically relate to assumptions we feed into our models but can also reflect problems withthe models themselves. In each FER we analyse our one- and two-year ahead fiscal forecast
differences for relevant March forecasts. This gives us a consistent dataset that can be used
to measure the relative accuracy of the components of our fiscal forecasts.

4.21

Our 2016 FER sets out how we calculate the one- and two-year ahead mean absolute
percentage errors (MAPE), and how we adjust them for the volatility of the underlying tax orspending stream. This allows us to identify the forecast models that should be subjected to77

Forecast evaluation reportRefining our forecasts

extra scrutiny because the associated forecasts have diverged from outturns by more than
the average model if it were faced with a constant degree of underlying volatility. We also
consider the mean average error (MAE) – a measure of bias rather than accuracy – as acheck on whether we are systematically over- or under-forecasting outturns.
4.22

Chart 4.1 shows the two-year ahead MAEs for our tax and spending forecasts since March
2012. As with the accuracy analysis, this is used to calibrate a ‘RAG’ rating for each model.
The green area reflects differences below the (absolute) average in either direction, amber
reflects differences that are less than 2 percentage points above the average and redreflects differences that are more than 2 percentage points above the average.

Chart 4.1: Mean average fiscal forecasting errors
30

Higher borrowing/higher spending/lower receipts

Bias (2 year ahead MAE)

20

CCL and CPF
Bank levy

10

Incapacity benefits

Capital LASFEDisability benefits

Self-assessment IT

0

Onshore CT

-10

-20

Aggregates levy

Lower borrowing/lower spending/higher receipts

-30

1

10

100

Size index (log scale)

4.23

Are we able to explain fiscal forecasting differences? Care is needed when drawing
conclusions from analysis of fiscal forecasting differences, because they can reflect a wide
range of factors. Most will fall into one of two categories: factors directly related to themodel (such as its specification) and factors related to use of the model (such as theassumptions and judgements fed into it).

4.24

The forecast models set out in Chart 4.1 provide examples of both cases. In particular, theconsistent over- and under-predictions from our self-assessment income tax and onshore
corporation tax models appear to reflect modelling issues. Our priorities in tackling theseissues are set out in the results section below. By contrast, the consistent over-prediction ofclimate change levy and carbon price floor (CCL and CPF) receipts reflects a change in thecomposition of the tax base (in particular away from coal-based energy generation towards
renewables) relative to the assumptions that were fed into the model. Similarly, theconsistent under-prediction of aggregates levy receipts appears to reflect underestimating
the tax base – specifically the buoyancy of the tax base relative to real GDP growth.

Forecast evaluation report78Refining our forecasts

4.25

To understand the drivers of the fiscal forecasting difference, we ask a number of questions
in order to draw appropriate conclusions. These are described in more detail in a newbriefing paper that we have published alongside this report – Evaluating forecast accuracy –which is available on our website.

Plausibility
4.26

Is the model specified in the appropriate way? Several factors need to be considered whenchoosing the type of model to forecast a stream of tax or spending. For example, a timeseries econometric approach can be useful when there is a clear and reasonably
straightforward relationship between determinants that can be drawn from our economy
forecast and elements of the tax or spending stream. But consideration should be given toother factors, such as the historical stability of the tax or spending regime, which could alter
the relationships over time and introduce biases into their estimated values. This is one
reason why in some cases a microsimulation or more disaggregated approach may be
more suitable.

4.27

Do model assumptions meet nine key plausibility requirements? The specification of amodel gives an analytical framework in which to analyse trends in tax and spending. The
assumptions applied to that model reflect the judgement of the forecaster and should begrounded in both theory and evidence. All assumptions and judgements in our fiscal
forecasts are the responsibility of the Budget Responsibility Committee (BRC), who draw on
the analysis and expertise of officials in other government departments in order to reachthose decisions. In general, we require that assumptions should:•

have a theoretical underpinning: for example, there should be an economic rationale
behind an econometric model;•

reflect the structure of the underlying tax or spending system: for example, a linear
growth rate should not be applied when modelling a tax system that does not movelinearly over time (e.g. a receipts stream that grows faster than the underlying tax basedue to fiscal drag);•

be consistent with recent experience: clear trends or patterns in the outturn data should
be reflected in forecast assumptions, unless there is firm evidence to suggest otherwise;•

be central: Parliament requires us to judge whether the Government has a better than
50/50 chance of achieving its fiscal targets on current policy, so we aim to produce
central (median) forecasts with equal probability of outcomes being above or below
them (i.e. we do not seek to be deliberately cautious or to include contingencies forunlikely events);•

be well-evidenced: we draw on the expertise and experience of analysts in othergovernment departments, asking that assumptions proposed to us for use in theforecast should be informed by operational information, external estimates, economic
literature, market research, and so on;
79

Forecast evaluation reportRefining our forecasts•

be reviewed frequently: at least every year for those that are most material to ouroverall fiscal forecast and at least once every three years for all assumptions;•be as stable as possible: our fiscal forecasts are produced twice a year (andoccasionally more frequently) and assumptions should not lead to large or erraticchanges from forecast-to-forecast unless that is required by the evidence (e.g.
econometric models should not include complex lag structures that introduce volatility);•reflect the latest data: for example, where a microsimulation model draws on annual
survey or administrative data, it should be updated as soon as possible after a newyear of information becomes available; and•reflect current Government policy: as required by the remit set by Parliament.

4.28

Is the in-year forecast set using a systematic process and justified using the best
information? Most of our fiscal forecast models are designed to forecast growth in receipts
or spending from a starting point, rather than the level itself. Rather than using the previous
year’s outturn as that starting point, we produce an ‘in-year forecast’ for the year inprogress that supplements our model outputs with a range of administrative andoperational information on monthly receipts and spending. This ‘jumping-off’ point isextremely important since any difference between forecast and outturn here will becompounded over the forecast period. It is therefore vital that departments provide us withthe best available information and use a systematic approach in order for us to make an
informed central forecast.

4.29

Is the model consistent with the rest of the forecast? Given the disaggregated andinterdependent nature of our fiscal forecast, it is important that the overall fiscal andeconomy forecasts are internally consistent on four levels. Each element should beconsistent with:•

our overall economy forecast: for example, our forecast for the VAT tax base must be
consistent with the forecast for consumer spending that is a component of our overall
GDP forecast;•other aspects of the fiscal forecast: this can be more challenging where there arecommon or interlinked effects that should feature in models operated for us bydifferent departments (e.g. tax credits, modelled by HMRC, include disability premia
that are directly linked to the disability benefits modelled for us by DWP);•

ONS accounting treatment: e.g. for many receipts streams, the ONS time-shifts cash
receipts back to proxy for the point at which the tax liabilities were accrued; and•current Government policy: as required by the remit set by Parliament.

Forecast evaluation report80Refining our forecasts

Transparency
4.30

To what level of detail can OBR staff scrutinise the workings of the model? The models that
underpin our fiscal forecast are typically owned and maintained by other parts ofgovernment that are responsible for administering the element of tax or spending. In manycases, it is not possible for departments to open up the full model for OBR staff to scrutiniseon the BRC’s behalf. Most commonly this will be due to data protection issues (e.g. the‘personal tax model’ that underpins our PAYE IT and NICs forecast contains confidential
taxpayer information that cannot be shared). Subject to these important restrictions, we aim
for OBR staff to get as close as possible an understanding of the workings of the models.
Having satisfied ourselves that a model is working as intended, we then rely on summary
outputs and analysis to help inform our forecast judgements and assumptions.

4.31

A good example of this is the new North Sea model that we plan to adopt in our next EFO.
The microsimulation model developed by HMRC over the past year projects individual
taxpayer liabilities forward using specialist statistical software, so it would not be possible for
OBR staff to view all its workings. Instead, we have worked with HMRC to develop a rangeof diagnostics that will be used during each forecast process.

4.32

Does the model documentation provide everything the BRC needs? Model documentationneeds to be clear and comprehensive in order to allow the BRC to use the model effectively
to produce a central forecast. Some of the items we require include a full list of model inputs
and key modelling assumptions. For many lines of tax and spending, we set out thisinformation on the Forecasts in depth section of our website.

4.33

Do forecast notes provide everything the BRC needs? It is important for the BRC tounderstand how and why model outputs change in response to new policies, changes in
economic determinants and other factors. Forecast-to-forecast diagnostics are key inunderstanding the effect of new information and judgements, so each model needs to beable to generate these effectively. We explain these forecast-to-forecast diagnostics in each
EFO and look at them between forecast rounds to ensure that our fiscal forecast evolves
appropriately as we refine our economy forecast and make other judgements.

Effectiveness
4.34

Is the model structured in the best way? There are clear benefits to keeping forecast models
as simple as possible so that their outputs can be readily understood and scrutinised. But
there are also benefits to having models that are sufficiently disaggregated to capture thedynamics of the tax or spending stream being modelled. The trade-off between theseobjectives is a judgement ultimately made by the BRC. One aspect of that trade-off is that
greater disaggregation often requires the forecasting of a greater number of inputs to run
the model, so while it may model outturns effectively as a forecasting tool it becomes too
cumbersome and reliant on too many uncertain judgements about inputs.

4.35

Are the best available data being used? Our forecasts should be based on the best andmost timely data available, so it is important that the models underpinning it are frequently
updated and that the potential benefits of new or supplementary sources are considered.
81

Forecast evaluation reportRefining our forecasts

4.36

Are effective quality assurance processes in place? It is important that the models
underpinning our public finances forecasts are of high quality and free of error. We expect
departments to follow the quality assurance guidelines and recommendations of the 2013
Macpherson Review. 3

Efficiency
4.37

Can the model be run and quality assured in a short time span? Our fiscal forecasts areprepared in a time-pressured environment in which models are used in iterative forecastrounds ahead of a Budget or other fiscal statement. The final rounds of this process are
particularly short. It is important that models can be run and quality assured, and that theforecast outputs and any accompanying documentation (such as forecast notes anddiagnostics) can be delivered to the OBR sufficiently far in advance of challenge meetings toallow us to scrutinise them effectively.

Results of the review
4.38

3

We have identified some overarching issues that we plan to work on over the next year:•

Supplementing our microsimulation models with top-down approaches: the bottom-up
methodology used to model complex tax and spending systems such as state pension
spending and SDLT is often necessary in order to capture fully the interaction of the
population with the tax or spending system. But these approaches involve a trade-off,as the volume of underlying data and complexity of the process mean it is sometimes
difficult to unpick the key drivers and trends in the modelling. We have concluded that
there would be value in developing simple, top-down representations of thesemicrosimulation models as a cross-check against the full bottom-up modelling and to
improve our understanding of the underlying processes being simulated.

•

The balance between short- and long-term dynamics in our econometric models: thetrade-off between the weight placed on recent experience and longer-term trends is aconstant challenge faced by forecasters. Where forecasts are produced using error
correction models, it is important to review the long-term element to ensure that it isplausible in the light of recent evidence that will be given less weight by aneconometric approach. For example, the error correction model we use to forecast
distances travelled in our fuel duty model is estimated over 15 years of data. The
strong growth of recent years in distances travelled by light goods vehicles means thatit has been under-predicting outturns. Factoring changes in historical trends into a
forecast often requires judgemental adjustments to be made to raw model outputs.

•

The impact of policy changes on the modelling approaches we use: significant policychanges can require fundamental changes to the way in which we model a tax orspending stream. As was the case following the residential SDLT reforms in December
2014 described in paragraph 4.16. In this review, we have identified a number of

See Review of quality assurance of Government analytical models: final report, HM Treasury, March 2013.

Forecast evaluation report82Refining our forecasts

models that require further development in light of recent policy changes, notably the
self-assessment income tax model, as described below.
4.39

4.40

As well as these general conclusions, we have attached a high priority to development workon three forecasting models:•Onshore corporation tax: in recent forecasts we have repeatedly under-forecast
onshore CT receipts. We will work with HMRC to review the main industrial,commercial and financial sector components of this model, including the econometricequations that are used to project key income and deduction streams. We are also
working with HMRC to improve the transparency of the model.

•

Self-assessment income tax: we have repeatedly over-forecast receipts in recent years.
This appears to be due to weakness in the effective tax rate that has not been capturedby the model. We will therefore consider alternative approaches to modelling theeffective tax rate. The effective tax rate has been volatile as well as weak, probably
reflecting a combination of policy changes, movements in the income distribution andthe trend towards incorporation. We will also be working with HMRC and the ONS toinvestigate and better understand trends in the tax base and how these income
streams are captured in the National Accounts.

•

Universal credit (UC): as the rollout of UC accelerates over the next year, the amountof spending flowing through the system will rise significantly. We currently factor UC
into our forecasts as a marginal effect relative to the existing system rather than on afull-cost basis. This will become more problematic as a growing share of outturn data
will reflect UC rather than the existing system that is being replaced. The shift to UC
also involves a number of complex changes in entitlement and the possibility thatrecipients’ behaviour will change in response – e.g. take-up rates, error and fraud,and decisions about whether and how much to work. Assumptions made in all theseareas will need to be reviewed as evidence of actual effects becomes available. We will
set out our latest UC modelling in detail in our next Welfare trends report, which will
be published later in 2017-18.

A summary of the conclusions of our review in relation to each model are available in a
new database on our website. We will continue to report on model developments in future
EFOs and FERs. Table 4.1 sets out the priority that we have attached to development workfor each model under each criteria.

83

Forecast evaluation reportRefining our forecasts

Table 4.1: Priorities for future model development work
Priorities for future model development work
Accuracy Plausibility Transparency Effectiveness Efficiency Ove r all

Onshore corporation tax (main industrial,commercial and financial components)

H

H

H

M/H

L/M

H

Self-assessment income tax

H

H

M/H

H

L/M

H

Universal credit marginal cost

H

H

L/M

M

M

H

Capital gains tax

M

L/M

L/M

M/H

H

H

Civil service pension scheme

M

M/H

H

H

L/M

M/H

Council tax

M

L/M

M

M

L

M

Customs duties

H

H

L

L

L

M

M/H

M/H

L/M

L

L

M

M

M/H

L/M

L/M

L

M

H

M

L/M

L

M

Fuel duties
General government depreciation
Insurance premium tax

L/M

PAYE and NIC1 integrated model Personal

L/M

L/M

M

L/M

L

M

tax model (PTM)

L/M

M/H

M

L

L

M

SDLT

L/M

M

M

L/M

L

M

M

M

L

L

L

M

CG debt interest (main gilts model)

L/M

M

L/M

L

L

L/M

PENFORM model

L/M

L/M

L

L

L

L/M

VAT (VTTL and SRS models)

L/M
L/M

L/M
L/M

L
L/M

L/M
L

L
L

L/M
L/M

L

L/M

L

L/M

L

L

Tobacco duties

VAT refunds
North Sea revenues

4.41

Over the coming year, we will review a different set of models, but will also revisit ourconclusions about the larger streams of tax and spending. This year’s FER results havehighlighted a number of possible areas for future review, including the life assurancecomponent of the onshore corporation tax model, the personal tax credits model,
accounting adjustments within total spending and other components of our local authorities’
self-financed expenditure forecast. We will also continue to review those models most likely
to be affected by Brexit – for example, the modelling implications arising from any change
to the membership or structure of tax systems for which there are common EU rules, such as
VAT or customs duties.

Forecast evaluation report84

A Detailed economy and fiscal tables

A.1

This annex contains further details of our March 2015 and March 2016 forecast differences
for the economy and public finances, including:•our calendar year GDP growth and deflator forecast differences (Tables A.1 to A.4);•

forecasting differences for the key economic determinants that underpin the fiscal
forecast (Tables A.5 to A.6);•

forecast differences for total receipts (Tables A.7 to A.8), overall spending (Tables A.9
to A.10) and welfare spending (Tables A.11 to A.12). These forecast differences arebroken down into components that are due to ONS methodological or classification
changes, subsequent policy changes, economy forecast differences and the residual‘fiscal forecasting difference’; and•restated forecasts and the adjustments required within the fiscal forecast to account for
the ESA10, public sector finances (PSF) review and housing associations classification
changes (Tables A.13 to A.16).

Table A.1: Contributions to real GDP growth
Privateconsumption

Business
investment

1.6
1.8

0.5
0.8

0.1
0.2

0.2
-0.1

-0.1
-0.4

0.1
0.0

2.5
2.3

1.6

0.2

0.3

0.0

-0.4

0.3

2.0

1.7
1.8

0.3
0.0

0.2
0.4

0.0
0.2

-0.1
-0.9

0.2
0.3

2.3
1.8

0.0
0.1

-0.2
-0.8

0.0
0.1

-0.2
0.3

0.0
-0.6

0.2
0.3

-0.1
-0.5

0.2

-0.3

0.1

0.2

-0.5

0.1

-0.2

Forecasts
March 2015
2015
2016
March 2016
2016
Latest data
2015
2016
Difference1
March 2015
2015
2016
March 2016
2016
1

Percentage points
Other
Stocks andTotal
Net trade
privatestatistical
Government
investment
discrepancy

GDP

Difference in unrounded numbers.

85

Forecast evaluation reportDetailed economy and fiscal tables

Table A.2: Contributions to nominal GDP growth
Percentage points
Privateconsumption
Forecasts
March 2015
2015
2016
March 2016
2016
Latest data
2015
2016
Difference1
March 2015
2015
2016
March 2016
2016
1

Total
PrivateNet tradeinvestment Government

StocksGDP

Statistical
discrepancy

2.4
2.7

1.1
1.3

0.1
-0.3

0.1
-0.2

0.2
0.0

4.1
3.5

0.3
0.0

2.4

0.7

0.1

-0.5

0.3

3.1

0.1

2.1
2.7

0.7
0.6

0.1
0.5

0.2
-0.6

-0.3
0.0

2.8
3.8

-0.1
1.6

-0.3
0.0

-0.4
-0.7

0.0
0.8

0.1
-0.4

-0.5
0.0

-1.3
0.3

-0.4
1.6

0.4

-0.2

0.4

-0.1

-0.3

0.7

1.5

Difference in unrounded numbers.

Table A.3: Growth in National Accounts deflators
Per cent
Privateconsumption

Privateinvestment

Total
Government

Exports

Imports

GDP

1.1
1.4

2.5
1.6

-0.5
-1.2

-4.5
-1.1

-4.8
-1.3

1.6
1.1

1.2

1.4

0.3

1.2

1.6

1.1

0.6
1.4

1.1
1.7

0.4
1.2

-5.1
4.7

-5.9
3.0

0.5
2.0

-0.5
-0.1

-1.3
0.0

0.9
2.3

-0.6
5.7

-1.1
4.3

-1.1
0.9

-0.1

0.0

2.3

5.7

4.3

0.9

Forecasts
March 2015
2015
2016
March 2016
2016
Latest data
2015
2016
Difference1
March 2015
2015
2016
March 2016
2016
1

Difference in unrounded numbers.

Forecast evaluation report86Detailed economy and fiscal tables

Table A.4: Contributions to nominal GDP (income) growth
Corporations'Compensation
gross operatingof employees
surplus
Forecasts
March 2015
2015
2016
March 2016
2016
Latest data
2015
2016
Difference1
March 2015
2015
2016
March 2016
2016
1

Percentage points
Taxes onOther
products andincomeproduction

GDP

Statistical
discrepancy

2.1
2.1

0.9
0.2

-0.4
1.0

0.2
0.3

4.1
3.5

1.2
0.0

1.6

-0.2

-0.1

0.6

3.1

-0.4

1.5
2.0

0.1
0.5

0.9
0.7

0.3
0.5

2.8
3.8

0.0
0.1

-0.6
-0.1

-0.9
0.4

1.3
-0.3

0.1
0.2

-1.3
0.3

-1.2
0.1

0.4

0.7

0.8

-0.1

0.7

0.5

Difference in unrounded numbers.

87

Forecast evaluation reportDetailed economy and fiscal tables

Table A.5: March 2015 fiscal determinant forecast differences for 2016-17
Percentage change on a year earlier, unless otherwise stated
Forecast
Outturn
Difference
GDP and its components
Real GDP

2.3
1943
3.5
3.8
3.5

1.8
1981
4.2
4.0
6.8

-0.5
38
0.7
0.2
3.3

4.2

4.4

0.2

1.2
2.2
1.2
3.1

2.3
2.0
1.0
2.9

1.1
-0.2
-0.2
-0.2

0.74
31.4
9.9

0.78
31.8
9.7

0.0
0.4
-0.2

3937
3.5
5.3
1211
1.0
2.7

3700
4.1
6.2
1155
-12.0
6.1

-237
0.6
0.9
-56
-13.0
3.4

Oil prices ($ per barrel)3
Oil prices (£ per barrel)3
Gas prices (p/therm)3
Oil production (million tonnes)3
Gas production (billion therms)3
Interest rates

69.2
44.9
50.3
36.7
11.9

44.0
32.5
34.6
47.4
14.5

-25.2
-12.4
-15.7
10.7
2.6

Market short-term interest rates (per cent)9Market gilt rates (per cent)10Euro/Sterling exchange rate

1.2
2.3
1.36

0.4
1.2
1.19

-0.8
-1.1
-0.17

Nominal GDP (£ billion)1
Nominal GDP 1
Wages and salaries2
Non-oil PNFC profits2,3
Consumer spending2,3
Prices and earnings
GDP deflator
RPI (September)
CPI (September)
Whole economy earnings growth
Other key fiscal determinants
Claimant count (millions)4
Employment (millions)
VAT gap (per cent)5
Financial and property sectors
Equity prices (FTSE All-share index)
1,3,5,6

HMRC financial sector profits
Residential property prices7
Residential property transactions (000s)
Commercial property prices8
Commercial property transactions8
Oil and gas

1

6

2

7

Not seasonally adjusted.
Nominal.
3
Calendar year.
4
UK seasonally-adjusted claimant count.
5
No outturn available, latest forecast from March 2017

Forecast evaluation report

HMRC Gross Case 1 trading profits
Outturn data from ONS House Price Index.
8
Outturn data (ex. Scotland) from HMRC Annual stamp tax statistics .
93-month sterling interbank rate (LIBOR).
10Weighted average interest rate on conventional gilts.

88Detailed economy and fiscal tables

Table A.6: March 2016 fiscal determinant forecast differences for 2016-17
Percentage change on a year earlier, unless otherwise stated
Forecast
Outturn
Difference
GDP and its components
Real GDP

2.0
1943
3.6
3.9
3.8

1.8
1981
4.2
4.0
6.8

-0.2
38
0.6
0.1
3.0

3.6

4.4

0.8

1.5
1.7
0.6
3.0

2.3
2.0
1.0
2.9

0.8
0.3
0.4
-0.1

0.74
31.6
11.5

0.78
31.8
9.7

0.0
0.2
-1.8

3337
3.5
5.7
1257
2.1
-0.9

3700
4.1
6.2
1155
-12.0
6.1

363
0.6
0.5
-102
-14.1
7.0

Oil prices ($ per barrel)3
Oil prices (£ per barrel)3
Gas prices (p/therm)3
Oil production (million tonnes)3
Gas production (billion therms)3
Interest rates

35.5
24.9
29.9
43.2
13.0

44.0
32.5
34.6
47.4
14.5

8.5
7.6
4.7
4.2
1.5

Market short-term interest rates (per cent)9Market gilt rates (per cent)10Euro/Sterling exchange rate

0.5
1.7
1.28

0.4
1.2
1.19

-0.1
-0.5
-0.09

Nominal GDP (£ billion)1
Nominal GDP 1
Wages and salaries2
Non-oil PNFC profits2,3
Consumer spending2,3
Prices and earnings
GDP deflator
RPI (September)
CPI (September)
Whole economy earnings growth
Other key fiscal determinants
Claimant count (millions)4
Employment (millions)
VAT gap (per cent)5
Financial and property sectors
Equity prices (FTSE All-share index)
1,3,5,6

HMRC financial sector profits
Residential property prices7
Residential property transactions (000s)
Commercial property prices8
Commercial property transactions8
Oil and gas

1

6

2

7

Not seasonally adjusted.
Nominal.
3
Calendar year.
4
UK seasonally-adjusted claimant count.
5
No outturn available, latest forecast from March 2016

HMRC Gross Case 1 trading profits
Outturn data from ONS House Price Index.
8
Outturn data (ex. Scotland) from HMRC Annual stamp tax statistics .
93-month sterling interbank rate (LIBOR).
10Weighted average interest rate on conventional gilts.

89

Forecast evaluation reportDetailed economy and fiscal tables

Table A.7: Breakdown of March 2015 receipts forecast differences for 2016-17£ billion
Forecast Outturn Difference

182.0

177.2

-4.7

0.0

1.9

Fiscalforecast
difference
0.2
-6.9

153.6
29.3
123.9
117.7
43.6

149.7
28.5
125.9
121.6
54.1

-3.9
-0.8
2.1
3.9
10.5

0.0
0.0
0.0
0.0
4.6

-1.1
2.7
-0.3
0.4
0.7

-0.8
1.2
-0.6
0.3
0.9

-2.0
-4.7
2.9
3.2
4.3

42.9
0.7
-0.1
27.2
29.0
28.8
13.2
7.3
4.6
15.2

53.5
0.6
-0.7
27.9
29.4
30.4
13.8
8.4
4.8
15.6

10.6
-0.1
-0.5
0.8
0.4
1.5
0.6
1.1
0.2
0.4

4.3
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0

0.8
-0.1
-0.1
-0.4
-0.6
0.4
0.0
0.2
0.0
1.1

0.9
0.0
0.1
0.3
0.0
0.0
0.8
-1.0
0.0
-0.3

4.7
-0.3
-0.5
0.9
1.0
1.1
-0.2
1.9
0.2
-0.4

11.8
3.4
9.0
10.8
3.2
3.1
2.0
6.6

11.9
3.7
8.7
11.1
3.2
4.9
1.9
7.4

0.1
0.3
-0.3
0.3
0.0
1.8
0.0
0.7

0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0

1.1
0.0
0.0
-0.1
0.0
1.5
0.5
0.0

0.0
-0.3
0.0
0.0
0.0
-0.1
0.0
0.2

-1.0
0.6
-0.3
0.4
0.1
0.4
-0.5
0.5

0.8
0.3
2.6
3.0
5.6
3.8
0.0
3.1
6.8
0.3
0.6
5.4
652.7
-2.2
7.8
48.8
1.5
708.6

0.8
0.4
2.7
3.4
5.8
3.0
1.6
3.2
5.2
0.4
0.6
7.2
672.7
-3.4
6.0
47.2
3.7
726.2

0.1
0.1
0.1
0.4
0.2
-0.8
1.6
0.1
-1.6
0.0
0.0
1.8
20.0
-1.2
-1.8
-1.6
2.2
17.6

0.0
0.0
0.0
0.0
0.0
0.0
0.5
0.0
-1.4
0.0
0.0
1.0
4.8
0.0
0.0
0.0
0.8
5.6

0.0
0.0
0.0
0.0
0.0
-0.5
0.9
0.0
0.0
0.0
0.0
0.0
5.6
0.0
-0.2
0.0
0.0
5.5

0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.1
0.0
-0.2
0.5
0.0
-1.0
0.0
0.0
-0.5

0.1
0.1
0.2
0.2
0.2
-0.3
0.2
0.1
-0.3
0.0
0.0
0.9
9.1
-1.2
-0.6
-1.5
1.3
7.1

Classification
changes
Income tax (gross of tax credits)of which:Pay as you earn (PAYE)
Self assessment (SA)National insurance contributions
Value added tax
Corporation taxof which:
OnshoreOffshore
Petroleum revenue tax
Fuel duties
Business rates
Council tax
VAT refunds
Capital gains tax
Inheritance tax
Stamp duties1of which:
Stamp duty land tax1
Stamp duty on shares
Tobacco duties
Alcohol duties
Air passenger duty
Insurance premium tax
Climate change levy
Other HMRC taxes2of which:
Landfill tax2
Aggregates levy
Betting and gaming duty
Customs duties
Vehicle excise duties
Bank levy
Bank surcharge
BBC licence fee receipts
Environmental levies
EU ETS auction receipts
Scottish taxes3
Other taxes
National accounts taxes
less own resources EU contributions
Interest & dividends
Gross operating surplus
Other receipts
Current receipts
1

Excludes Scottish LBTT.
Excludes Scottish LFT.
3
Consists of Scottish LBTT and LFT but not the Scottish rate of income tax or AGL.
2

Forecast evaluation reportof which:

90

Policy Economicchangesfactors

Detailed economy and fiscal tables

Table A.8: Breakdown of March 2016 receipts forecast differences for 2016-17£ billion
Forecast Outturn Difference

182.1

177.2

-4.9

0.0

0.0

Fiscalforecast
difference
-0.1
-4.8

153.4
30.2
126.5
120.1
43.5

149.7
28.5
125.9
121.6
54.1

-3.6
-1.6
-0.5
1.6
10.7

0.0
0.0
0.0
0.0
4.6

0.0
0.0
0.0
0.0
0.0

-0.1
0.0
-0.1
-0.1
2.0

-3.6
-1.6
-0.4
1.6
4.0

43.4
0.1
-1.1
27.6
28.4
30.1
14.7
7.0
4.8
15.9

53.5
0.6
-0.7
27.9
29.4
30.4
13.8
8.4
4.8
15.6

10.1
0.5
0.5
0.3
1.0
0.3
-0.9
1.4
0.1
-0.3

4.3
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0

0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0

1.4
0.6
0.3
-0.2
0.0
0.0
-0.1
0.2
0.2
-0.1

4.4
-0.3
0.2
0.5
1.0
0.3
-0.8
1.2
-0.1
-0.2

12.9
3.0
9.2
10.9
3.2
4.6
2.1
7.0

11.9
3.7
8.7
11.1
3.2
4.9
1.9
7.4

-0.9
0.7
-0.5
0.2
0.0
0.3
-0.2
0.4

0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0

0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0

-0.4
0.3
0.0
0.0
0.0
-0.3
0.0
0.0

-0.6
0.4
-0.5
0.1
0.0
0.6
-0.2
0.3

0.9
0.4
2.6
3.1
5.5
2.9
0.8
3.1
7.3
0.5
0.6
7.9
665.1

0.8
0.4
2.7
3.4
5.8
3.0
1.6
3.2
5.2
0.4
0.6
7.2
672.7

-0.1
0.1
0.1
0.3
0.3
0.1
0.8
0.1
-2.2
-0.1
0.0
-0.7
7.6

0.0
0.0
0.0
0.0
0.0
0.0
0.5
0.0
-1.9
0.0
0.0
0.2
3.4

0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0

0.0
0.0
0.0
0.1
0.0
0.0
0.2
0.0
0.0
0.0
0.0
-0.1
2.0

-0.1
0.1
0.1
0.2
0.3
0.1
0.1
0.1
-0.3
-0.1
0.0
-0.8
2.2

-3.3

-3.4

-0.1

0.0

0.0

0.0

-0.1

5.7
47.8
2.0
717.3

6.0
47.2
3.7
726.2

0.3
-0.6
1.7
8.9

0.0
0.0
0.8
4.3

0.0
0.0
0.0
0.0

0.0
0.0
0.0
1.9

0.4
-0.6
0.8
2.7

Classification
changes
Income tax (gross of tax credits)of which:Pay as you earn (PAYE)
Self assessment (SA)National insurance contributions
Value added tax
Corporation taxof which:
OnshoreOffshore
Petroleum revenue tax
Fuel duties
Business rates
Council tax
VAT refunds
Capital gains tax
Inheritance tax
Stamp duties1of which:
Stamp duty land tax1
Stamp duty on shares
Tobacco duties
Alcohol duties
Air passenger duty
Insurance premium tax
Climate change levy
Other HMRC taxes2of which:
Landfill tax2
Aggregates levy
Betting and gaming duty
Customs duties
Vehicle excise duties
Bank levy
Bank surcharge
BBC licence fee receipts
Environmental levies
EU ETS auction receipts
Scottish taxes3
Other taxes
National accounts taxes
less own resources EU
contributions
Interest & dividends
Gross operating surplus
Other receipts
Current receipts

of which:
Policy Economicchangesfactors

1

Excludes Scottish LBTT.
Excludes Scottish LFT.
3
Consists of Scottish LBTT and LFT but not the Scottish rate of income tax or AGL.
2

91

Forecast evaluation reportDetailed economy and fiscal tables

Table A.9: Breakdown of March 2015 spending forecast differences for 2016-17£ billion
Forecast Outturn Differenceof which:
Classification
Policy Economicchanges changes
factors

Public sector current expenditure (PSCE)
PSCE in RDEL
PSCE in AME, of which:Welfare spending, of which:Inside the Welfare Cap
Outside the Welfare Cap
Company and other tax credits
Net public service pension paymentsof which:
CG unfunded pension schemes
LG police and fire pension schemes
National lottery current grants
BBC current expenditure
Network Rail other current expenditure
Other PSCE items in departmental AME
Expenditure transfers to EU institutions
Locally financed current expenditure1
CG net debt interest, of which:
CG gross debt interest
less APF holdings of CG debt
General government depreciation
Current VAT refunds
Public corporations' debt interest
Single use military expenditure
Environmental levies
Local authority imputed pensions2
CG imputed pensions2
Other National Accounts adjustments
Total public sector current expenditure
Public sector gross investment (PSGI)PSGI in CDELPSGI in AME, of which:
National lottery capital grants
Network Rail capital expenditure
Other PSGI items in departmental AME
Locally financed capital expenditure
Public corporations' capital expenditure
Other National Accounts adjustments
Total public sector gross investment
Less public sector depreciation
Public sector net investment
Total managed expenditure1
1

Fiscalforecast
difference

293.2
381.2
219.5
121.0
98.5
2.5
11.2

312.5
380.1
216.9
118.7
98.2
3.0
11.2

19.3
-1.1
-2.6
-2.2
-0.3
0.5
-0.1

0.0
-2.7
0.0
0.0
0.0
0.0
0.0

19.3
-2.3
-2.5
-2.5
0.0
0.0
0.1

0.0
-2.0
0.5
0.0
0.4
0.0
-0.1

0.0
5.9
-0.5
0.2
-0.7
0.5
0.0

9.2
2.1
1.3
3.8
0.7
1.1
9.4
40.0
40.4
50.7
-10.4
31.2
10.9
3.9
0.2
6.7
2.1
0.0
-3.8
674.4

8.8
2.4
1.4
3.7
0.8
0.5
8.8
45.1
35.5
48.7
-13.2
29.9
12.0
3.4
0.0
5.3
0.5
0.9
1.2
692.6

-0.4
0.3
0.1
-0.1
0.1
-0.6
-0.6
5.1
-4.9
-2.1
-2.8
-1.4
1.1
-0.4
-0.2
-1.4
-1.6
0.9
5.0
18.2

0.0
0.0
0.0
0.0
-0.2
-0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
-0.2
-1.4
-1.7
0.9
0.0
-2.7

0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
17.0

-0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
-3.2
-2.2
-1.1
0.1
0.8
0.0
0.0
0.0
0.0
0.0
0.0
-2.0

-0.3
0.3
0.1
-0.1
0.3
-0.5
-0.6
5.0
-1.7
0.1
-1.7
-1.5
0.3
-0.4
0.0
-0.1
0.1
0.0
5.0
5.9

45.4
31.4
0.5
5.9
0.4
8.1
16.2
0.3
76.8
-42.2
34.6
751.3

45.8
32.8
0.5
6.6
0.7
8.8
17.1
-0.8
78.6
-40.8
37.9
771.3

0.4
1.4
-0.1
0.7
0.3
0.7
0.9
-1.1
1.8
1.4
3.2
20.0

-0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
-0.3
0.0
-0.3
-2.9

0.7
-0.1
0.0
0.0
0.0
-0.1
0.0
0.0
0.6
0.0
0.6
17.6

0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
-0.1
-0.1
-2.0

0.0
1.5
-0.1
0.7
0.3
0.8
0.9
-1.1
1.5
1.6
3.1
7.4

All spending outturns are provisional and subject to change.

2

Imputed employer pension contributions related to funded public sector pension schemes. The classification changes include
fundamental changes in methodology, which ONS introduced in the September 2017 release of the Public Finance Statistics.

Forecast evaluation report92Detailed economy and fiscal tables

Table A.10: Breakdown of March 2016 spending forecast differences for 2016-17£ billion
Forecast Outturn Differenceof which:
Classification
Policy Economicchanges changes
factors

Public sector current expenditure (PSCE)
PSCE in RDEL
PSCE in AME, of which:Welfare spending, of which:Inside the Welfare Cap
Outside the Welfare Cap
Company and other tax credits
Net public service pension paymentsof which:
CG unfunded pension schemes
LG police and fire pension schemes
National lottery current grants
BBC current expenditure
Network Rail other current expenditure
Other PSCE items in departmental AME
Expenditure transfers to EU institutions
Locally financed current expenditure1
CG net debt interest, of which:
CG gross debt interest
less APF holdings of CG debt
General government depreciation
Current VAT refunds
Public corporations' debt interest
Single use military expenditure
Environmental levies
Local authority imputed pensions2
CG imputed pensions2
Other National Accounts adjustments
Total public sector current expenditure
Public sector gross investment (PSGI)PSGI in CDELPSGI in AME, of which:
National lottery capital grants
Network Rail capital expenditure
Other PSGI items in departmental AME
Locally financed capital expenditure
Public corporations' capital expenditure
Tax litigation3
Other National Accounts adjustments
Total public sector gross investment
Less public sector depreciation
Public sector net investment
Total managed expenditure1

Fiscalforecast
difference

313.8
380.7
218.3
119.8
98.4
2.6
11.2

312.5
380.1
216.9
118.7
98.2
3.0
11.2

-1.3
-0.6
-1.3
-1.1
-0.2
0.4
0.0

0.2
-3.2
0.0
0.0
0.0
0.0
0.0

1.7
0.2
0.1
0.1
0.0
0.0
0.0

0.0
1.4
0.3
0.1
0.2
0.0
0.0

-3.2
1.0
-1.7
-1.4
-0.4
0.4
0.0

9.0
2.2
1.4
3.8
0.8
0.9
11.8
40.8
35.4
47.8
-12.4
31.1
12.4
3.6
0.2
7.3
1.9
0.0
-2.8
694.5

8.8
2.4
1.4
3.7
0.8
0.5
8.8
45.1
35.5
48.7
-13.2
29.9
12.0
3.4
0.0
5.3
0.5
0.9
1.2
692.6

-0.2
0.2
0.0
-0.2
0.1
-0.4
-3.0
4.3
0.1
0.9
-0.8
-1.3
-0.3
-0.2
-0.2
-2.0
-1.4
0.9
4.0
-1.9

0.0
0.0
0.0
0.0
-0.2
-0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
-0.2
-1.9
-1.7
0.9
0.0
-2.9

0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.8

0.0
0.0
0.0
0.0
0.0
0.0
-0.1
0.0
1.1
0.9
0.1
0.3
-0.1
0.0
0.0
0.0
0.0
0.0
0.0
1.4

-0.2
0.2
0.0
-0.2
0.3
-0.4
-2.9
4.3
-1.0
-0.1
-0.9
-1.6
-0.2
-0.2
0.0
-0.1
0.3
0.0
4.0
-2.2

46.0
32.8
0.5
6.9
0.6
6.9
17.0
0.9

45.8
32.8
0.5
6.6
0.7
8.8
17.1
0.0

-0.2
0.1
0.0
-0.3
0.1
1.9
0.1
-0.9

0.0
-0.9
0.0
0.0
0.0
0.0
0.0
-0.9

-0.9
0.0
0.0
0.0
0.0
0.0
0.0
0.0

0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0

0.7
1.0
0.0
-0.3
0.1
1.9
0.1
0.0

0.0
78.8
-41.7
37.1
773.3

-0.8
78.6
-40.8
37.9
771.3

-0.8
-0.1
0.9
0.8
-2.0

0.0
-0.9
0.0
-0.9
-3.8

0.0
-0.9
0.0
-0.9
0.9

0.0
0.0
-0.4
-0.4
1.4

-0.8
1.7
1.3
3.0
-0.5

1

All spending outturns are provisional and subject to change.
Imputed employer pension contributions related to funded public sector pension schemes. The classification changes include
fundamental changes in methodology, which ONS introduced in the September 2017 release of the Public Finance Statistics.
3
In our July 2015 forecast, we switched our tax litigation payments forecast from negative receipts to spending, in line with ESA10
National Accounts guidelines. See Box 4.1 of our July 2015 EFO for more information.
2

93

Forecast evaluation reportDetailed economy and fiscal tables

Table A.11: Breakdown of March 2015 welfare spending differences for 2016-17£ billion
Forecast Outturn Differenceof which:
Classification
Policy Economicchanges changes
factors

Fiscalforecast
difference

Welfare cap 1
DWP social security2of which:
Housing benefit (not on JSA)
Disability living allowance andpersonal independence payments

75.3

76.0

0.7

0.3

-1.6

0.0

2.0

22.5

21.3

-1.2

-0.2

-1.1

0.0

0.1

14.9

16.7

1.8

0.0

0.0

0.0

1.8

14.7
5.6
5.8
2.5
2.3
2.6
2.1
4
-0.1
Universal credit
Other DWP in welfare cap
2.4
Personal tax credits
29.8
Child benefit
11.6
Tax free childcare
0.7
3.4
NI social security in welfare cap5
Paternity pay
0.1
Total welfare cap
121.0
Welfare spending outside the welfare cap 1
96.1
DWP social security2of which:
State pension
92.0
Jobseeker's allowance
2.4
Housing benefit (on JSA)
1.7
4
0.0
Universal credit
5
2.4
NI social security outside welfare cap
Total welfare spending outside the98.5
welfare cap
Total welfare
219.5

15.1
5.5
5.6
2.7
2.2
2.3
2.0
0.5
2.2
27.4
11.6
0.0
3.5
0.1
118.7

0.4
-0.1
-0.2
0.1
-0.1
-0.3
0.0
0.6
-0.2
-2.3
0.0
-0.7
0.1
0.0
-2.2

-0.1
0.0
0.0
0.0
0.0
-0.1
0.0
0.8
0.0
-0.2
0.0
0.0
0.0
0.0
0.0

0.0
-0.1
-0.1
0.0
0.0
0.0
0.0
-0.3
0.0
-0.2
0.0
-0.7
0.0
0.0
-2.5

0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0

0.5
0.0
-0.2
0.1
-0.2
-0.2
0.0
0.1
-0.2
-2.0
0.1
0.0
0.1
0.0
0.2

95.9

-0.2

0.0

0.0

0.4

-0.6

91.6
1.9
1.6
1.1
2.3

-0.4
-0.5
-0.2
1.1
-0.2

0.0
-0.6
-0.4
1.1
0.0

0.0
0.0
0.0
0.0
0.0

0.2
0.1
0.1
0.1
0.0

-0.6
0.1
0.1
0.0
-0.2

98.2

-0.3

0.0

0.0

0.4

-0.7

216.9

-2.6

0.0

-2.5

0.5

-0.5

Incapacity benefits3
Attendance allowance
Pension credit
Carer's allowance
Statutory maternity pay
Income support (non-incapacity)
Winter fuel payments

1

Forecasts include estimates of the marginal effect of universal credit relative to the existing benefits and tax credits systems, whereas
all spending in outturn is on a full-cost basis.
2
Provisional outturns for some DWP benefits use different sources to the aggregate totals.
3
Incapacity benefits includes incapacity benefit, employment and support allowance, severe disablement allowance and income
support (incapacity part).
4
Universal credit additional costs not already included against other benefits (i.e. UC payments that don't exist under current benefit
structure).
5
An allocation of error between categories is not available, so we assume all errors are fiscal forecasting errors.

Forecast evaluation report94Detailed economy and fiscal tables

Table A.12: Breakdown of March 2016 welfare spending differences for 2016-17£ billion
Forecast Outturn Differenceof which:
Classification
Policy Economicchanges changes
factors

Fiscalforecast
difference

Welfare cap 1
DWP social security2of which:
Housing benefit (not on JSA)
Disability living allowance andpersonal independence payments
Incapacity benefits3
Attendance allowance
Pension credit
Carer's allowance
Statutory maternity pay
Income support (non-incapacity)
Winter fuel payments

76.1

76.0

0.0

0.4

0.0

0.0

-0.4

21.7

21.3

-0.4

-0.2

0.0

0.0

-0.2

16.4

16.7

0.3

0.0

0.0

0.0

0.3

14.9
5.5
5.8
2.7
2.4
2.4
2.1
-0.1
Universal credit4
Other DWP in welfare cap
2.4
Personal tax credits
28.5
Child benefit
11.7
Tax free childcare
0.0
5
3.5
NI social security in welfare cap
Paternity pay
0.1
Total welfare cap
119.9
Welfare spending outside the welfare cap 1
96.0
DWP social security2of which:
State pension
91.7
Jobseeker's allowance
2.5
Housing benefit (on JSA)
1.8
4
0.0
Universal credit
2.4
NI social security outside welfare cap5
Total welfare spending outside the98.4
welfare cap
Total welfare
218.3

15.1
5.5
5.6
2.7
2.2
2.3
2.0
0.5
2.2
27.4
11.6
0.0
3.5
0.1
118.7

0.2
0.0
-0.1
-0.1
-0.2
-0.1
0.0
0.6
-0.3
-1.1
0.0
0.0
0.0
0.0
-1.1

-0.1
0.0
0.0
0.0
0.0
-0.1
0.0
0.8
0.0
-0.2
0.0
0.0
0.0
0.0
0.0

0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.1

0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.1

0.4
0.0
-0.1
-0.1
-0.2
0.0
0.0
-0.2
-0.3
-1.1
0.0
0.0
0.0
0.0
-1.4

95.9

-0.1

0.0

0.0

0.2

-0.2

91.6
1.9
1.6
1.1
2.3

-0.1
-0.6
-0.3
1.1
-0.2

0.0
-0.7
-0.4
1.1
0.0

0.0
0.0
0.0
0.0
0.0

0.0
0.1
0.1
0.0
0.0

-0.1
0.0
0.1
-0.1
-0.2

98.2

-0.2

0.0

0.0

0.2

-0.4

216.9

-1.3

0.0

0.1

0.3

-1.7

1

Forecasts include estimates of the marginal effect of universal credit relative to the existing benefits and tax credits systems, whereas
all spending in outturn is on a full-cost basis.
2
Provisional outturns for some DWP benefits use different sources to the aggregate totals.
3
Incapacity benefits includes incapacity benefit, employment and support allowance, severe disablement allowance and income
support (incapacity part).
4
Universal credit additional costs not already included against other benefits (i.e. UC payments that don't exist under current benefit
structure).
5
An allocation of error between categories is not available, so we assume all errors are fiscal forecasting errors.

95

Forecast evaluation reportDetailed economy and fiscal tables

Table A.13: Adjustments to receipts and spending forecasts for ESA10, PSF review
and housing associations classification decisions£ billion
10-11 11-12 12-13 13-14 14-15 15-16 16-17 17-18 18-19 19-20 20-21
Receipts
June 2010
November 2010
March 2011
November 2011
March 2012
December 2012
March 2013
December 2013
March 2014
December 2014
March 2015
July 2015
November 2015
March 2016
Spending
June 2010
November 2010
March 2011
November 2011
March 2012
December 2012
March 2013
December 2013
March 2014
December 2014
March 2015
July 2015
November 2015
March 2016

20.3
20.2
20.1

20.0
19.9
19.8

21.5
20.2
20.3
20.3
21.2

20.5
19.2
19.3
19.3
19.2

23.8
22.2
22.2
22.0
22.9
22.9
22.0

29.2
27.6
27.6
27.4
27.3
27.2
26.3

25.0
23.4
23.4
23.3
24.3
23.9
22.9
22.9
22.7

18.7
17.1
17.1
17.0
16.9
16.4
15.4
15.5
15.3

26.4
24.9
24.8
24.7
25.8
24.7
23.8
23.9
24.3
7.7
7.7
7.7

27.6
26.1
25.9
25.9
27.0
24.5
24.0
25.1
25.2
8.1
8.1
8.1
0.9
0.9

26.0
27.2
23.6
23.5
24.4
24.5
7.7
7.7
7.7
0.9
0.9

23.4
23.7
23.6
23.7
7.5
7.5
7.5
0.9
0.9

23.9
24.0
7.4
7.4
7.4
0.8
0.8

7.2
7.2
7.2
0.8
0.8

7.7
0.9
0.9

22.4
20.9
20.8
20.8
20.7
19.6
18.7
18.8
19.2
11.3
11.3
11.3

21.7
20.3
20.1
20.1
20.0
17.5
17.0
18.1
18.2
9.2
9.2
9.2
0.9
0.9

21.1
21.1
17.5
17.4
18.3
18.4
11.0
11.0
11.0
1.3
1.3

16.2
16.6
16.5
16.5
11.4
11.4
11.4
1.3
1.3

18.2
18.3
11.7
11.7
11.7
1.3
1.3

11.1
11.1
11.1
1.2
1.2

11.5
1.3
1.3

Our forecasts from June 2010 to March 2014 have been restated for ESA10 and PSF review classification changes.
Our forecasts from June 2010 to March 2016 have also been restated for the reclassification of ‘private registered providers’ of social
housing from the private to the public corporations sector. See chapter 3 for more detail.

Forecast evaluation report96Detailed economy and fiscal tables

Table A.14: Restated receipts and spending forecasts for ESA10, PSF review andhousing associations classification decisions£ billion
10-11 11-12 12-13 13-14 14-15 15-16 16-17 17-18 18-19 19-20 20-21
Receipts
June 2010
November 2010
March 2011
November 2011
March 2012
December 2012
March 2013
December 2013
March 2014
December 2014
March 2015
July 2015
November 2015
March 2016
Spending
June 2010
November 2010
March 2011
November 2011
March 2012
December 2012
March 2013
December 2013
March 2014
December 2014
March 2015
July 2015
November 2015
March 2016

568.0 605.7 645.8 686.8
569.8 606.4 642.5 682.5
568.6 608.9 641.9 683.7
595.7 616.3 646.8
591.6 614.5 646.8
605.2 632.2
602.4 623.1
629.5
630.3

716.8 720.4 740.2 740.7
718.1 722.9 738.9 736.5
714.2 729.7 747.8 747.2
721.9 741.9 740.1
715.6 738.7 736.9
729.5 736.3
727.6 735.5
733.3
730.7

726.4
722.8
722.2
682.1
684.2
657.1
645.8
658.4
660.8
653.5
654.6
654.0

764.5
760.7
760.4
719.4
719.0
687.9
673.1
690.4
693.4
678.4
675.5
681.0
683.1
682.7

761.2
762.4
723.1
711.5
729.6
732.5
713.5
708.6
718.8
724.3
717.3

757.6
745.3
763.9
766.6
744.2
738.7
751.2
763.6
746.7

800.7
801.7
776.7
771.8
785.3
797.4
780.4

810.2
811.5
821.5 863.8
831.9 872.8
821.7 853.1

760.0
753.9
764.5
757.1
754.2
750.5
749.1
749.3
751.2
748.4
748.4
746.9

779.2
773.2
783.9
766.7
764.0
762.2
761.7
762.2
761.6
755.4
751.9
751.5
756.6
754.8

779.8
777.4
772.6
772.3
774.5
770.9
757.6
751.3
765.3
774.7
773.3

781.4
780.8
780.2
776.0
762.6
755.3
779.4
788.8
785.9

792.8
791.2
777.0
770.9
796.0
802.4
802.2

791.0
808.4
815.5 856.0
822.2 858.6
811.7 842.5

Our forecasts from June 2010 to March 2014 have been restated for ESA10 and PSF review classification changes.
Our forecasts from June 2010 to July 2015 have also been restated for the reclassification of ‘private registered providers’ of social
housing from the private to the public corporations sector. See chapter 3 for more detail.

97

Forecast evaluation reportDetailed economy and fiscal tables

Table A.15: Adjustments to PSNB forecast for ESA10, PSF review and housing
associations classification decisions£ billion
10-11 11-12 12-13 13-14 14-15 15-16 16-17 17-18 18-19 19-20 20-21
Public sector net borrowing
June 2010
-0.2
-1.0
5.4
-6.4
-3.9
-5.8
November 2010
-0.2
-1.0
5.4
-6.4
-3.9
-5.8
March 2011
-0.2
-1.0
5.4
-6.4
-3.9
-5.8
November 2011
-1.0
5.4
-6.4
-3.9
-5.8
-4.9
March 2012
-2.1
4.4
-7.5
-5.1
-7.0
-6.1
December 2012
4.4
-7.5
-5.1
-7.0
-6.1
-7.1
March 2013
4.4
-7.5
-5.1
-7.0
-6.1
-7.1
December 2013
-7.5
-5.1
-7.0
-6.1
-7.1
-5.7
March 2014
-7.5
-5.1
-7.0
-6.1
-7.1
-5.7
December 2014
3.7
1.1
3.3
3.9
4.3
3.9
March 2015
3.7
1.1
3.3
3.9
4.3
3.9
July 2015
3.7
1.1
3.3
3.9
4.3
3.9
3.9
November 2015
-0.1
0.4
0.4
0.4
0.4
0.4
March 2016
-0.1
0.4
0.4
0.4
0.4
0.4
Our forecasts from June 2010 to March 2014 have been restated for ESA10 and PSF review classification changes.
Our forecasts from June 2010 to July 2015 have also been restated for the reclassification of ‘private registered providers’ of social
housing from the private to the public corporations sector. See chapter 3 for more detail.

Table A.16: Restated PSNB forecast for ESA10, PSF review and housing associationsclassification decisions
10-11 11-12
Public sector net borrowing
June 2010148.9 114.6
November 2010 148.3 116.4
March 2011145.7 120.8
November 2011
126.1
March 2012
123.9
December 2012
March 2013
December 2013
March 2014
December 2014
March 2015
July 2015
November 2015
March 2016

£ billion
12-13 13-14 14-15 15-16 16-17 17-18 18-19 19-20 20-21
94.5
53.7
33.5
96.4
53.8
31.1
106.0
63.5
42.3
125.6
93.1
75.0
124.3
90.0
69.9
124.3 104.0
93.5
125.3 112.3 103.3
103.7
90.9
100.3
90.4
94.9
93.8
92.8

14.6
12.4
23.5
47.3
45.0
74.3
88.6
71.7
68.2
77.0
76.4
70.6
73.4
72.1

18.6
15.0
49.5
60.9
45.0
38.4
44.2
42.7
46.4
50.4
55.9

23.8
35.5
16.3
9.4
18.5
16.7
28.2
25.2
39.2

-7.9
-10.5
0.3
-0.9
10.7
5.0
21.9

-19.2
-3.1
-6.1
-9.7
-10.0

-7.7
-14.3
-10.6

Our forecasts from June 2010 to March 2014 have been restated for ESA10 and PSF review classification changes.
Our forecasts from June 2010 to July 2015 have also been restated for the reclassification of ‘private registered providers’ of social
housing from the private to the public corporations sector. See chapter 3 for more detail.

Forecast evaluation report98B Comparison with past official
forecasts

B.1

This annex compares the difference between the OBR’s various fiscal forecasts and the latest
outturns with the average differences in official forecasts over the previous 20 years.

B.2

This exercise provides some guide to relative forecast performance, but with significant
limitations. Most fundamentally, these comparisons are often influenced by factors beyond
those under the control of the forecaster in question. For example, we may be looking at
periods in which the underlying behaviour of the public finances was inherently more or lesspredictable, in which the size and distribution of unforeseeable shocks was different, or inwhich policymakers responded differently when the public finances diverged fromexpectations. And we have not yet had to forecast through a recession, which is often when
the largest forecast differences arise – because their timing and depth are so uncertain.

B.3

We have so far produced 16 forecasts, but the sample that we can compare against
outturns is still relatively small – especially at longer time horizons. We can compare only
seven of our forecasts at a 4-year horizon and five at a 5-year horizon.

B.4

In addition to the public finances, we also undertake this comparison for our forecasts ofreal GDP growth. As we have emphasized throughout this report, real GDP is not the mostimportant economic determinant of the public finances, but it is the measure that mostoutside commentators focus on when judging the performance of macroeconomic forecasts.

B.5

For what it is worth, our forecast differences for real GDP and net borrowing have, more
often than not, been smaller than the average differences in official forecasts over the 20
years before the OBR was created.

Real GDP growth
B.6

Table B.1 shows our forecast differences for real GDP growth. Not surprisingly, whencomparing the absolute difference between forecast periods, the expected difference forforecasts two years ahead is greater than for one year ahead, and for one year ahead isgreater than in-year estimates. One would expect forecasts to be more accurate at shorthorizons than long ones – the closer the forecaster is to the event, the more data are
available and the easier it should be to forecast. However, this information advantage canbe complicated by data revisions, which are often substantial, multiple, and continue longafter the event.

99

Forecast evaluation reportComparison with past official forecasts

B.7

When measured in percentage point terms as in Table B.1, the accuracy of real GDP growthforecasts will also be affected by the path of GDP growth itself. In periods of relatively stable
growth, forecast differences are likely to be smaller. For example, GDP growth was roughly
in line with the final years of our June 2010 forecast despite the long time horizon, because
output growth in those years (2014 and 2015) was relatively stable and relatively close to its
assumed potential growth rate in those years.

B.8

Relatively few years in the 15 forecasts evaluated in Table B.1 show large differences
between our real GDP growth forecasts and outturn. Those that do include:•

Our June 2010 and November 2010 forecasts were both over-optimistic regarding
GDP growth in 2012, failing to foresee the intensification of the euro crisis and thedampening effect on real GDP growth at a time when those forecasts assumed agathering pace of recovery. Only by late 2011 did we (and most other forecasters)
significantly revise down our expectations for GDP growth in 2012.

•

Our November 2011 forecast proved particularly optimistic regarding GDP growth in2016. It assumed that growth would be boosted by significant amounts as sparecapacity was brought back into productive use on top of an assumed potential growthrate of 2.3 per cent. In the event, 2016 saw GDP growth slow to 1.8 per cent, withboth potential output and cyclical factors weaker than assumed in that forecast.

•

Our December 2012 forecast was too pessimistic relative to the latest estimate of
growth in 2012. That was despite the fact that initial estimates of GDP growth wereavailable for the first three quarters of 2012 at the time. Much of the in-year forecast
difference reflects data revisions. For example, data at the time reported threeconsecutive quarters of falling GDP between the end of 2011 and the second quarterof 2012, whereas the latest data report only one quarter of falling output.

•

Our March 2013 forecast was too pessimistic regarding growth in 2013 and 2014. As
well as the latest data showing more momentum in the economy than was evident in
the data available at the time, there were a number of policy developments that may
have supported output growth by more than we had assumed – including, forexample, the President of the European Central Bank’s confidence-boostingcommitment to ‘do whatever it takes’ to protect the euro.

Forecast evaluation report100Comparison with past official forecasts

Table B.1: Forecast differences for real GDP growthJune 2010
November 2010
March 2011
November 2011
March 2012
December 2012
March 2013
December 2013
March 2014
December 2014
March 2015
July 2015
November 2015
March 2016
November 2016

In-year
0.5
-0.1
-0.2
0.6
0.7
1.6
1.5
0.7
0.4
0.1
-0.2
-0.1
-0.1
-0.2
-0.3

One
-0.8
-0.6
-1.0
0.8
0.1
0.9
1.3
0.7
0.0
-0.1
-0.5
-0.5
-0.6

Per cent
Calendar years ahead
Two
Three
-1.3
-0.8
-1.1
-0.8
-0.8
0.2
0.0
0.4
0.4
-0.7
1.1
0.0
0.0
-0.9
0.1
-0.8
-0.8
-0.4

Four
0.4
0.3
-0.5
-0.7
-1.2
-0.9

Five
-0.4
-0.4
-1.2

Average absolute differences over the 20 years preceding the creation of the OBR
Spring/summer
0.8
1.1
1.3
1.1
1.3
n/a
Autumn
0.7
1.0
1.1
1.2
1.2
1.0
Smaller than average absolute difference
Average sized difference
Bigger than average absolute difference

Public sector net borrowing
B.9

B.10

Nominal GDP has been revised up significantly in recent years, in particular in the 2014
Blue Book that brought the National Accounts into line with the 2010 European System of
Accounts (ESA10). Changes to the level of GDP do not greatly affect our interpretation of
how the public finances have evolved, but the revisions have reduced the ratios of fiscal
measures expressed as a share of GDP. This makes comparisons of forecasts expressed onthat basis hard to interpret, so in this annex we:•compare cash borrowing (Table B.2) and cash spending (Table B.3) forecast
differences normalised by the latest GDP estimates; and•present our forecasts for the change in receipts as a share of GDP against outturns
over time, which abstracts from changes in the level caused by revisions to thedenominator (Table B.4).

Less than a fifth of our PSNB forecasts show larger forecast differences than the averageover the preceding 20 years (Table B.2). These larger differences include:•

Our first three forecasts for 2012-13 to 2015-16 were too optimistic, with November
2010 particularly so. This largely reflected lower-than-expected tax receipts. In
particular, the productivity-related weakness in earnings growth, as well as policychanges to raise the income tax personal allowance faster than inflation, put
downward pressure on the effective tax rate.

•

Our in-year forecasts for 2010-11 and 2011-12 were too pessimistic. This reflected anumber of factors, in particular local authority net borrowing. Relative to our forecasts
101

Forecast evaluation reportComparison with past official forecasts

at the time, local authorities added to their reserves rather than running them down,
but this only became apparent much later when solid data became available. Moretimely quarterly data are now available to inform our forecasts.
•

Our recent forecasts for 2016-17 have been too pessimistic. This was partly related tosignificant revisions to in-year data, as set out in Box 3.1 in Chapter 3.

B.11

Cash spending forecast differences have consistently been smaller than the average of theprevious 20 years (Table B.3). The larger under-estimates for spending in 2016-17 in some
forecasts – particularly December 2014 and March 2015 – reflect the Conservative
Government’s Summer Budget 2015 decision not to carry out the sharp cuts todepartmental spending that had been pencilled in by the Coalition Government before the2015 general election. The larger over-estimates for 2012-13 in some earlier forecasts –notably March 2011 – reflect the Treasury’s decision to clamp down on departmental
spending late in 2012-13 in order to ensure that borrowing fell in cash terms that year.

B.12

More of our receipts forecast differences have been relatively large by historical standards,
with around a quarter of the years shown in Table B.4 recording above-average forecast
differences. These have tended largely to reflect weakness in income tax and NICs receipts,
where a less tax-rich composition of labour earnings (through higher employment but
weaker average earnings) and policy changes (including successive increases in the income
tax personal allowance) have reduced effective tax rates. As set out above, our recent
receipts forecasts for 2016-17 have tended to be too pessimistic.

B.13

The fact that forecast differences in our receipts and spending forecasts have often been
partly offsetting, but with larger differences in receipts than spending, is consistent with theanalysis of our fiscal forecast revisions presented in Annex B of our March 2016 Economic
and fiscal outlook (EFO). In it, we noted that:•

Revisions to receipts forecasts tend to be bigger than revisions to spending forecasts. In
absolute terms, receipts revisions have averaged 0.5 per cent of GDP, more than twice
the average spending revision of 0.2 per cent of GDP. That is as one might expect,since most receipts are linked to the performance of the economy, whereas aroundhalf of public spending (i.e. DELs) is in effect fixed in cash terms.

•

Revisions to receipts forecasts are typically offset to some extent by revisions to debt
interest spending forecasts. There have only been three forecasts where changes inreceipts and debt interest have contributed in the same direction to the overall revision
to borrowing. It should come as no surprise that receipts and debt interest forecastchanges tend to offset each other since both are likely to be driven by the sameunderlying factors. In particular, market expectations of future interest rates, which
drive our debt interest forecast, will tend to fall/rise when market participants’
expectations of future growth prospects are lowered/raised. If we share thatinterpretation – as will often be the case – we are likely to revise down/up our nominal
GDP growth and receipts forecasts.

Forecast evaluation report102Comparison with past official forecasts

Table B.2: Forecast differences for cash PSNB

June 20101
November 2010
March 2011
November 2011
March 2012
December 2012
March 2013
December 2013
March 2014
December 2014
March 2015
July 20151
December 2015
March 2016
November 2016
March 2017

In-year
0.1
-0.6
-0.4
-0.6
-0.6
-0.1
-0.2
-0.3
-0.1
-0.1
-0.1
0.0
0.1
0.1
-0.9
-0.3

One
-0.6
0.0
-0.3
-0.1
-0.1
-0.3
-0.7
0.1
0.1
-0.1
-0.1
0.2
0.0
-0.3

Per cent of outturn GDP
Fiscal years ahead
Two
Three
0.0
1.7
1.6
2.6
1.0
2.1
0.4
1.0
0.5
1.2
-0.1
0.0
-0.6
-0.8
0.1
0.3
0.3
0.6
0.3
0.4
0.2
0.0

Average absolute differences over the 20 years preceding the creation of the OBR
Spring/summer
0.3
0.9
1.9
Autumn
0.5
1.3
2.0

2.9
2.2

Four
2.6
3.4
2.8
1.5
1.5
0.0
-0.5

Five
3.3
3.3
2.8
1.6
1.8

3.2
2.8

3.6
3.2

1

For comparability, 'in-year' is assumed to be 2009-10 and 2014-15 for the June 2010 and July 2015 forecasts respectively.
Note: Forecast differences have been adjusted to reflect major ONS classification changes. This includes the 2014 changes related to
ESA10 and the PSF review, the reclassification of 'private registered providers' of social housing into the public sector and the 2017change to the accounting treatment of corporation tax receipts.

Smaller than average absolute difference

Average sized difference

Bigger than average absolute difference

Table B.3: Forecast differences for cash spending

June 20101
November 2010
March 2011
November 2011
March 2012
December 2012
March 2013
December 2013
March 2014
December 2014
March 2015
July 20151
December 2015
March 2016
November 2016
March 2017

In-year
0.5
-0.1
0.2
-0.3
0.0
0.2
0.3
0.0
0.2
0.1
0.1
0.2
0.0
0.1
-0.4
-0.1

One
0.0
-0.4
-0.8
-0.5
-0.3
-0.1
-0.1
0.1
0.0
0.1
0.2
0.3
-0.2
-0.1

Per cent of outturn GDP
Fiscal years ahead
Two
Three
-0.2
-0.3
-0.3
-0.1
-0.9
-0.7
-0.3
-0.3
-0.1
-0.1
0.0
-0.3
0.1
-0.3
-0.3
-0.2
-0.3
0.0
0.7
1.0
0.3

Four
-0.2
-0.1
-0.6
-0.4
-0.3
-0.1
-0.1

Five
-0.3
-0.8
-1.3
-0.3
-0.2

Average absolute differences over the 20 years preceding the creation of the OBR
Spring/summer
1.1
1.0
1.1
1.5
1.8
Autumn
0.9
0.7
0.9
1.1
1.7
1
For comparability, 'in-year' is assumed to be 2009-10 and 2014-15 for the June 2010 and July 2015 forecasts respectively.
Average sized difference
Bigger than average absolute difference
Smaller than average absolute difference

103

2.0
2.3

Forecast evaluation reportComparison with past official forecasts

Table B.4: Forecast differences for changes in receipts as a share of GDP

June 20101
November 2010
March 2011
November 2011
March 2012
December 2012
March 2013
December 2013
March 2014
December 2014
March 2015
July 20151
December 2015
March 2016
November 2016
March 2017

In-year
-0.1
0.6
0.4
0.0
0.3
-0.7
-0.8
0.3
0.3
0.2
0.1
0.1
0.2
-0.4
0.5
0.5

One
0.4
0.4
0.0
-0.7
-0.5
-1.1
-1.0
0.0
0.1
0.4
0.6
-0.2
0.0
-0.5

Per cent of GDP
Fiscal years ahead
Two
Three
0.1
-1.1
-0.7
-1.0
-0.8
-1.2
-0.8
-1.0
-0.8
-1.1
-1.3
-1.2
-1.1
-1.0
-0.1
0.0
-0.1
0.2
0.4
0.6
-0.2

Four
-1.5
-1.3
-1.5
-0.8
-0.7
-0.7
-0.8

Five
-1.8
-1.0
-1.2
-0.2
-0.3

1.0
0.9

1.0
0.9

Average absolute differences over the 20 years preceding the creation of the OBR
Spring/summer
Autumn

0.5
0.5

0.8
0.7

1.0
1.0

1.1
0.9

1

For comparability, 'in-year' is assumed to be 2009-10 and 2014-15 for the June 2010 and July 2015 forecasts respectively.
Note: Forecast differences have been adjusted to reflect major ONS classification changes. This includes the 2014 changes related to
ESA10 and the PSF review, the reclassification of 'private registered providers' of social housing into the public sector and the 2017change to the accounting treatment of corporation tax receipts.
Smaller than average absolute difference

Average sized difference

Bigger than average absolute difference

Using historical forecast differences to illustrate uncertainty
B.14

In our forecast publications, we routinely illustrate the uncertainty surrounding our central
forecast using fan charts. These fan charts do not represent our assessment of specific risks
to the central forecast. Instead, they use the analysis set out above to show the outcomesthat someone might anticipate if they believed that forecast differences in the past offered areasonable guide to likely differences in the future.

B.15

Charts B.1 and B.2 set out the fan charts we presented in our March 2012 EFO, our first
March forecast for which the fifth year of the forecast period was 2016-17. The probability
distributions underpinning those fan charts would have implied:

B.16

•

around a 1-in-3 chance of real GDP growth in 2016 being as low as it was in outturn
or lower; and•similarly, around a 1-in-3 chance of PSNB in 2016-17 being as high as it was in
outturn or higher.

In line with the approach we use elsewhere in our evaluation, we have adjusted our original
PSNB forecast for fiscal classification changes and revisions to the level of nominal GDP.
The unadjusted forecast is also shown in Chart B.2, illustrating the scale of these changes.

Forecast evaluation report104Comparison with past official forecasts

Chart B.1: Real GDP fan chart
6

March 2012 forecast
5

Percentage change on a year earlier

Latest outturn
4
3
2
1
0
-1
-2
2011

2012

2013

2014

2015

2016

Source: ONS, OBR

Chart B.2: PSNB fan chart
108Per cent of GDP

6

4

2

0

-2

-4
2010-11

March 2012 forecast (unadjusted)
March 2012 forecast (adjusted)
Latest outturn
2011-12

2012-132013-142014-152015-16

2016-17

Source: ONS, OBR

105

Forecast evaluation reportForecast evaluation report106Index of charts and tables
Chapter 1

Executive summary

Chart 1.1: Successive OBR productivity forecasts (output-per-hour) ................................... 4
Chapter 2

The economy

Chart 2.1: Successive projections for Bank Rate ............................................................. 12
Table 2.1: Conditioning assumptions for 2017Q2 ......................................................... 13
Chart 2.2: Real GDP outturns and forecasts................................................................... 14
Table 2.2: Contributions to real GDP growth from 2014Q4 to 2017Q2 ......................... 15
Table 2.3: Contributions to nominal GDP growth from 2014Q4 to 2017Q2 ................... 15
Table 2.4: Growth in National Accounts deflators from 2014Q4 to 2017Q2 .................. 16
Table 2.5: Contributions to GDP income growth from 2014Q4 to 2017Q2 .................... 16
Table 2.6: Income and consumption growth from 2014Q4 to 2017Q2 .......................... 17
Box 2.1: Blue Book 2017 and dividend income.............................................................. 18
Chart 2.3: Forecasts and outturns for CPI ...................................................................... 19
Table 2.7: Growth in housing market indicators from 2014Q4 to 2017Q2 ..................... 20
Chart 2.4: Forecasts and outturns for business investment .............................................. 21
Table 2.8: Growth in real private investment from 2014Q4 to 2017Q2 .......................... 22
Table 2.9: Growth in trade from 2014Q4 to 2017Q2 ................................................... 22
Chart 2.5: March 2015 current account forecast differences ........................................... 23
Table 2.10: Growth in general government spending from 2014Q4 to 2017Q2 ............. 24
Box 2.2: Fiscal policy and growth .................................................................................. 25
Table 2.11: Labour market indicators from 2014Q4 to 2017Q2 .................................... 28
Chart 2.6: Successive productivity forecasts and outturns ................................................ 28
Table 2.12: Earnings, productivity and real wage growth from 2014Q4 to 2017Q2........ 29
Table 2.13: Contributions to GDP growth between 2016H2 and 2017H1 ....................... 29
Chart 2.7: Contributions to year-ahead annual GDP growth forecast differences ............. 30
Chart 2.8: Average annual growth in output per hour in the G7 in 2015 and 2016 ........ 31
Chart 2.9: CBO forecasts and outturns for US output per hour ....................................... 31
Chart 2.10: Productivity growth..................................................................................... 33
Chart 2.11: Unemployment rate forecasts and outturns.................................................. 36
Chart 2.12: Average hours forecasts and outturns ......................................................... 37
107

Forecast evaluation reportChapter 3

The public finances

Chart 3.1: Restated forecasts and outturns for public sector net borrowing ...................... 40
Chart 3.2: Two-year-ahead forecast differences: Borrowing, receipts and spending ......... 42
Table 3.1: 2016-17 receipts, spending and net borrowing forecasts ............................... 43
Box 3.1: Revisions to borrowing in 2016-17 .................................................................. 44
Table 3.2: 2016-17 receipts forecast differences............................................................ 47
Box 3.2: The receipts-to-GDP ratio since 1986-87 ......................................................... 48
Table 3.3: 2016-17 income tax and NICs forecasts ....................................................... 52
Table 3.4: 2016-17 VAT forecasts................................................................................. 53
Table 3.5: 2016-17 onshore corporation tax forecasts ................................................... 54
Table 3.6: 2016-17 capital and stamp taxes forecasts ................................................... 56
Table 3.7: 2016-17 fuel, tobacco and alcohol duties forecasts ....................................... 57
Table 3.8: 2016-17 spending forecast differences ......................................................... 59
Table 3.9: 2016-17 DEL forecast differences ................................................................. 61
Table 3.10: 2016-17 locally financed current expenditure forecast differences ................ 63
Table 3.11: 2016-17 welfare spending forecast difference ............................................. 64
Table 3.12: 2016-17 debt interest forecast difference .................................................... 65
Table 3.13: 2016-17 EU expenditure transfers forecast differences ................................. 66
Table 3.14: The change in public sector net debt in 2016-17 ......................................... 68
Chapter 4

Refining our forecasts

Chart 4.1: Priorities for future model development work ................................................. 84
Annex A

Detailed economy and fiscal tables
Table A.1: Contributions to real GDP growth ................................................................. 85
Table A.2: Contributions to nominal GDP growth........................................................... 86
Table A.3: Growth in National Accounts deflators .......................................................... 86
Table A.4: Contributions to nominal GDP (income) growth ............................................. 87
Table A.5: March 2015 fiscal determinant forecast differences for 2016-17 .................... 88
Table A.6: March 2016 fiscal determinant forecast differences for 2016-17 .................... 89
Table A.7: Breakdown of March 2015 receipts forecast differences for 2016-17.............. 90
Table A.8: Breakdown of March 2016 receipts forecast differences for 2016-17.............. 91
Table A.9: Breakdown of March 2015 spending forecast differences for 2016-17 ........... 92
Table A.10: Breakdown of March 2016 spending forecast differences for 2016-17 ......... 93

Forecast evaluation report108

Table A.11: Breakdown of March 2015 welfare spending differences for 2016-17 .......... 94
Table A.12: Breakdown of March 2016 welfare spending differences for 2016-17 .......... 95
Table A.13: Adjustments to receipts and spending forecasts for ESA10, PSF review andhousing associations classification decisions ....................................................... 96
Table A.14: Restated receipts and spending forecasts for ESA10, PSF review and housing
associations classification decisions.................................................................... 97
Table A.15: Adjustments to PSNB forecast for ESA10, PSF review and housing associationsclassification decisions ...................................................................................... 98
Table A.16: Restated PSNB forecast for ESA10, PSF review and housing associationsclassification decisions ...................................................................................... 98
Annex B

Comparison with past official forecasts
Table B.1: Forecast differences for real GDP growth..................................................... 100
Table B.2: Forecast differences for cash PSNB.............................................................. 103
Table B.3: Forecast differences for cash spending ........................................................ 103
Table B.4: Forecast differences for changes in receipts as a per cent of GDP ................. 104
Chart B.1: Real GDP fan chart .................................................................................... 105
Chart B.2: PSNB fan chart .......................................................................................... 105

109

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Forecast evaluation report

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