United Kingdom
Selected Issues Paper
Author: International Monetary Fund
Publication Date:
01 Aug 2011
eISBN:
9781462337521
Language:
English
Keywords:
ISCR; CR; rate; saving rate; saving; commodity price; wage-price inflation spiral; near-term inflation outlook; inflation model; inflation path; Output gap; Value-added tax; Commodity prices; Global
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In recent years, the IMF has released a growing number of reports and other documents covering economic and financial developments and trends in member countries. Each report, prepared by a staff team after discussions with government officials, is published at the option of the member country.

Abstract

In recent years, the IMF has released a growing number of reports and other documents covering economic and financial developments and trends in member countries. Each report, prepared by a staff team after discussions with government officials, is published at the option of the member country.

I. A Bumpy Road Ahead—The Near-Term Outlook for Inflation in the UK1

A. Introduction

1. Headline inflation in the UK is currently the highest amongst major advanced economies. CPI inflation has exceeded the official target of 2 percent since December 2009. These overruns have been largely unanticipated by most forecasters due in part to unexpected increases in international commodity prices. Despite constant upward revisions to the Bank of England (BoE)’s forecasts, inflation has continued to surprise on the upside. The average one-year ahead forecast error was close to 1¾ percentage points in 2010. These overruns have heightened attention on the inflation outlook.

Figure 1.
Figure 1.

UK: Recent Inflation Performance

Citation: IMF Staff Country Reports 2011, 221; 10.5089/9781462337521.002.A001

Sources: Haver, Bank of England, and IMF staff estimates.

2. Against this background, this chapter examines the main drivers of UK inflation, what they imply for the near-term inflation outlook, and risks surrounding this central scenario. The analysis in this chapter finds that transitory factors—spiking commodity prices and VAT rate hikes—have contributed substantially to recent inflation overruns. These same factors are expected to keep headline inflation well above 4 percent for most of 2011. As these transitory factors dissipate, inflation is expected to return close to the Bank of England’s 2-percent target by end-2012 as downward pressure on inflation due to the negative output gap becomes more evident. Upside risks to this central scenario include a lack of resumption in productivity growth, higher commodity prices, and an output gap that is narrower than currently estimated.

3. The rest of this chapter is structured as follows: Section B first analyzes recent inflation developments. Section C then presents the details that underpin staffs near-term inflation forecast. Section D discusses key risks around this central scenario. Section E concludes.

B. A Decomposition of Recent Inflation Developments

4. To quantify the effects of several key drivers of recent inflation, an inflation equation is estimated. The specification is motivated by the open-economy New Keynesian Philips Curve, which has been applied to the UK in various forms by Batini, Jackson, and Nickell (2005) and Dwyer, Lam, and Gurney (2010). A statistical significance criterion is used to determine a parsimonious lag structure. The specification, along with the description of the variables used, is as follows:

πt=α+β1πt−2+β2πt−1E+β3gapt−8+β4uwct−2+β5neert−1+β6commt+β7ΔVAT+ɛt(1)
article image

5. Most of the variables in equation (1) are fairly standard in single-equation models of inflation. Some less-standard variables are also included in equation (1) due to their potential importance in explaining recent movements in inflation. These variables include the following:

  • VAT rate changes. In December 2008 the standard VAT rate was cut by 2.5 percentage points. This rate cut was reversed in January 2010. The standard rate was hiked by a further 2.5 percentage points in January 2011. The estimated full impact of each of these changes—assuming firms fully pass-through the tax changes—on annual inflation is roughly 1.4 percentage points.7 The true impact, however, will be smaller if firms do not fully pass-through tax changes to final tax-inclusive prices.

  • Exchange rate. Sterling depreciated by 21 percent in nominal effective terms over the period 2008–2010. The effects of this large depreciation could potentially explain a non-trivial portion of recent inflation developments.

  • Unit wage costs. The decline in employment during the recession was relatively mild compared to the fall in output. As a result, productivity—measured as output per worker—declined substantially. This decline in productivity, along with a rise in unemployment and lower inflation expectations, led to a decline in the average growth rate of wages. This decline, however, was not commensurate with the drop in productivity, resulting in higher unit wage costs. To offset the resulting pressure on profits, firms would likely have had to raise prices.

6. Equation (1) is estimated using monthly data from January 1989 to December 2010.8 Table 1 shows the resulting estimated coefficients. All coefficients have the expected sign with regard to their theoretical impact on inflation and are statistically significant.9 Changes in the VAT rate have especially large effects on inflation. A1 percentage point increase in the VAT rate results in a 0.4 percentage point increase in the annual inflation rate. The output gap is also found to have an important influence on inflation. A negative output gap of 1 percent reduces inflation by 0.2 percentage points about two quarters later. The coefficients in Table 1 estimate the short-run impact of changes in the explanatory variables. The cumulative effects are slightly larger given that inflation is autocorrelated.

Table 1.

Estimated Coefficients 1/

article image

Standard errors in parentheses.

Source: IMF staff estimates

7. The estimated coefficients are used to decompose recent inflation developments (Figure 2). Exchange rate depreciation and higher unit wage costs contributed significantly to inflation in 2009, and somewhat moderately in 2010. The average impact of the exchange rate depreciation on annual inflation is estimated to be around 1.1 percentage points in 2009. By the third quarter of 2010, however, the impact had decreased to about 0.2 percentage points. The average contribution of unit wage costs during the period 2009–2010Q2 was 0.7 percentage points per quarter. Meanwhile, inflation expectations—and the internal dynamics of the inflation process—made a smaller-than-usual contribution to inflation during 2009. The subsequent rise in inflation expectations in 2010, however, has raised this contribution back to its pre-crisis average. The VAT rate hike of 2.5 percentage points in January 2010 increased headline inflation by about 1 percentage point.10 Meanwhile, commodity prices contributed about 0.5 percentage points to the headline inflation rate in the last two quarters of 2010.

Figure 2.
Figure 2.

Decomposition of Recent Inflation Developments

(percentage points of annual rate)

Citation: IMF Staff Country Reports 2011, 221; 10.5089/9781462337521.002.A001

Source: IMF staff estimates.

8. Excluding the impact of commodity prices and VAT tax hikes, underlying inflation is below 2 percent. The decomposition of headline inflation based on the coefficients in the estimated model above implies that the underlying inflation rate—once the impact of commodity prices and tax hikes are removed—averaged around 1½ percent in the third and fourth quarters of 2010. Similar results are also obtained when the estimated impact of VAT hikes is subtracted from a measure of core inflation, which excludes energy, food, tobacco, and alcoholic beverages. As this measure of core inflation excludes items that are largely not subject to VAT, the estimated impact of VAT hikes on its annual growth rate is roughly 1½ percentage points (inclusive of long-term effects). This adjusted measure of core inflation is currently below 1½ percent, bringing it much closer to rates in other advanced economies.

A01ufig01

UK: Inflation Developments

(annual rate, percent)

Citation: IMF Staff Country Reports 2011, 221; 10.5089/9781462337521.002.A001

Sources: Haver; IMF staff estimates.

C. Forecasting Inflation

9. Even after accounting for the factors included in the inflation equation, there were large positive surprises to inflation over the last two years, particularly in 2010. The cumulative unexplained portion of annual inflation for the last three quarters of 2010 averaged around 0.5 percentage point per quarter. This large unexplained component has raised some concern regarding the near-term outlook for inflation, which this section addresses.

10. Two broad approaches are used to forecast inflation. The first approach embeds the inflation equation specified above within a vector auto-regression (VAR) model that generates endogenous forecasts for the dependent variables. The forecasting performance of this “restricted VAR” model is compared to a suite of other standard inflation forecasting models and is shown to perform well. The second approach employed to forecast inflation is based on separate forecasts for disaggregated components of the CPI, namely the core, energy, and food subcomponents.

Restricted VAR model

11. The central forecast for inflation in the UK builds on the single equation presented in the previous section. Specifically, equation (1) is embedded in a 5-variable VAR(8) model with changes in global commodity prices and the VAT rate included as exogenous variables. The coefficients in the inflation equation of the VAR are restricted such that lagged values of variables that are not included in equation (1) are set to zero. The coefficients in the inflation equation in the VAR, therefore, have roughly the same magnitudes as in the previous section, such that the equation is not over-parameterized. In addition to these restrictions, the impact of VAT changes on the other variables in the system (apart from inflation) is set to zero.

Historical forecasting performance of inflation models

12. The usefulness of the restricted VAR model in forecasting inflation is tested using its historical forecasting performance. To determine the model’s relative forecasting performance, the forecasting performance of 10 different models (including the baseline restricted VAR model)—ranging from relatively naïve models, such as the unconditional mean and a random walk, to a model that incorporates dynamic factors—are compared. Table 2 describes the models.

Table 2.

Description of Forecasting Models

article image
Source: IMF staff analysis.

13. The three other VAR models included in the exercise represent robustness checks to the baseline model. The VAR2 model is set up as a more conventional VAR model where no constraints are imposed on the inflation equation. The VAR3 and VAR4 models are analogous to the VAR1 and VAR2 models, but with trend output measured using a Hodrick-Prescott filter rather than the multivariate filter used in the baseline model.

14. Inflation is forecast using monthly data over four forecast horizons—3 months, 6 months, 12 months, and 24 months. Over each of these forecasting horizons, average inflation rates are forecasted rather than point estimates at individual horizons. Specifically, the inflation forecast over horizon h is computed as

π^t+h=1hΣs=1hπt+sf

where πft+s is the monthly inflation rate forecast.11 The inflation forecasting performance of these models over longer horizons are therefore judged based on whether or not they can adequately predict average inflation over that horizon. This approach is similar to that used in Stock and Watson (1999, 2002), with the exception that inflation is modeled as an I(0) process rather than an I(1).

15. The models are estimated on monthly data that range from January 1988 to September 2010. The out-of-sample forecasts are based on a rolling estimation with the first estimation window covering January 1989 to December 1999 (1988 values are used as presample values). The last 24-month forecast, therefore, is based on an estimation from January 1989 to September 2008. This approach yields 108 individual forecasts for each model which are subsequently compared to actual inflation outturns.

16. The forecasting performance of these models is assessed based on the squared distance between the forecasted and realized values. Specifically, the root mean-squared error (RMSE) criterion is applied where

RMSEh=1TΣt=1T(πt+1−π^t+h)2.

with πt+h being the actual average monthly inflation rate between period t and t+h.

17. Table 3 lists the relative forecasting performance of the various models. The RMSE of each model is shown relative to the RMSE of the AR model, which serves as a benchmark.13 In general, the VAR models perform fairly well relative to the AR benchmark. The baseline restricted VAR model (VAR1) does particularly well with a one-year-ahead forecasting performance that is about 15 percent better than the AR model. The unrestricted version of the baseline model (VAR2) performs just as well, with slightly better forecasting performance over the longer horizons.

Table 3.

Relative Root Mean Squared Forecast Errors

article image
Source: IMF staff calculations.

Central inflation forecast

18. Based on their relatively strong forecasting record, VAR models 1 and 2 are estimated using the most recent available data to obtain forecasts for the next two years. In order to do so, however, projections for the exogenous variables—global commodity prices and VAT changes—are required. In the case of oil prices, futures prices are used as the expected oil price in the central scenario. Based on the average futures price for Dubai, Brent, and West Texas Intermediate, the average petroleum spot price is expected to stay broadly flat over the next two years. For global food prices, however, data for equivalent contracts are not readily available. Instead, global food prices are assumed to increase by 0.4 percent per month—similar to the rate of increase during 2000–2006 (a relatively “normal” period). Meanwhile, future VAT changes are assumed to be zero.

A01ufig02

Oil prices

(APSP, USD; dashed segment indicates projection)

Citation: IMF Staff Country Reports 2011, 221; 10.5089/9781462337521.002.A001

Source: IMF staff estimates.

19. Inflation projections based on the two VAR models point to a hump-shaped forecast, with inflation exceeding 4 percent for most of 2011 (Figure 3). As the base effect of the VAT increase wears off, inflation moderates close to the 2 percent target by end-2012. Forecasts based on some of the other better-performing models point to a similar hump-shaped forecast. The inflation path based on the DF model, for example, has a fairly similar path to the average of the two VAR models.

Figure 3.
Figure 3.

Inflation Projections using Various Models

(percent, annual rate)

Citation: IMF Staff Country Reports 2011, 221; 10.5089/9781462337521.002.A001

Sources: IMF staff estimates.

A “disaggregated” approach to forecasting inflation

20. The second approach to forecasting inflation is based on a disaggregated approach that forecasts three broad subcomponents of the CPI—core, food, and energy prices.14 The forecasts for core, energy, and food inflation are done in a relatively straightforward way. For core inflation, an AR(3) model based on monthly inflation—with the inclusion of changes in VAT—is used.15 Monthly changes in the energy and food sub-indices, on the other hand, are assumed to respond to global oil and food prices in the same way as they have in recent history.16 The future paths of global oil and food prices are assumed to be the same as in the previous section.

21. Forecasts for the individual subcomponents are then aggregated to produce a forecast for headline inflation. To account for second-round effects, half of the contribution of the energy and food sub-indices experienced in any given three-month period is assumed to affect core inflation in the following three months.

22. The forecast for inflation based on this approach results in a forecast that is similar to the restricted VAR model, albeit with slightly lower inflation rates in 2011 and a more rapid disinflation in 2012. Food and energy price inflation are expected to peak in the second and fourth quarters of 2011, respectively, and then gradually decline. Following the lapse of the base effects due to the VAT increase, core inflation is expected to fall to 1.6 percent.

A01ufig03

Comparison of inflation projections

(percent, annual rate)

Citation: IMF Staff Country Reports 2011, 221; 10.5089/9781462337521.002.A001

Sources: IMF staff estimates.
A01ufig04

Projections for individual components of CPI

(annual growth, percent)

Citation: IMF Staff Country Reports 2011, 221; 10.5089/9781462337521.002.A001

Comparison of forecasts

23. The resulting inflation forecasts are comparable to forecasts by other institutions, as well as market consensus. Forecasts for inflation during 2011 by the BoE, the independent Office for Budget Responsibility (OBR), the OECD, and market consensus are all above 4 percent. Apart from the OECD (which has the lowest inflation forecast in 2012), forecasts for average inflation in 2012 by all these institutions continue to remain above the 2 percent target, though most forecasters expect inflation to return very close to the 2 percent target by end-2012.

A01ufig05

Comparison of Inflation Forecasts

(average annual rate, percent)

Citation: IMF Staff Country Reports 2011, 221; 10.5089/9781462337521.002.A001

Sources:1/ Inflation Report, May 2011.2/ Average of VAR1, VAR2, and the disaggregated models.3/ Consensus Forecasts, June 2011.4/ Economic and Fiscal Outlook, March 2011.5/ OECD Economic Outlook, May 2011.

D. Risks to the Central Scenario

24. The forecasts above paint a relatively benign picture for inflation. After a bumpy period in 2011, inflation is expected to return close to the 2 percent target level by end-2012. In this section, we consider the risks around the central scenario. Three specific risks are considered: a rise in unit wage cost, a smaller output gap than is currently estimated, and higher commodity prices.

Unit wage costs

25. The central forecast for inflation is implicitly based on moderate growth in unit wage costs. From the third quarter of 2011, unit wage costs are expected to increase at an annual rate of 1 percent, which is lower than the pre-crisis average annual growth rate of 2.2 percent. More subdued near-term growth in unit wage costs is plausible given the negative output gap and evidence of labor hoarding during the downturn, the unwinding of which should raise productivity.

26. The implications of these projections for wage growth depend in part on the outlook for productivity. Labor productivity—measured as output per worker—declined sharply during the past recession. Since then, growth in productivity has resumed at rates close to its historical average. If this fall in productivity is permanent, the implicit forecast of a 1 percent increase in unit wage costs implies wage growth of about 2.6 percent (assuming that productivity growth stays at its pre-crisis trend). Higher wage growth would lead to higher inflation than forecast in the central scenario. A more optimistic scenario is one where productivity growth is higher in the near-term such that its gap relative to trend is reduced. Under this scenario, the implicit forecast of a 1 percent growth in unit wage costs would be consistent with wage growth of over 3½ percent.

27. There are both upside and downside risks to the central forecast for inflation arising from wage developments. On the downside, there is a risk that unemployment rates remain high, or even increase, if the recovery in output turns out to be more sluggish than expected. In this scenario, wage growth will remain moderate with commensurate downward pressure on inflation. On the upside, increases in inflation expectations could give rise to higher wage growth, potentially leading to a wage-price inflation spiral. Recent measures of inflation expectations, however, remain well-anchored.

Spare capacity measures

28. A particularly important upside risk to the central inflation projection is that the output gap is not as large as is currently estimated. In the central forecast, the output gap is a significant deflationary factor in both 2011 and 2012. The output gap contributes a deflationary impact to annual inflation of about 0.5 and 0.4 percentage points in 2011 and 2012, respectively. While a variety of estimates—including by the OBR and the OECD—forecast output gaps to remain negative at end-2012, survey indicators of spare capacity suggest that the gap is narrowing at a faster rate. The upside risk to inflation of an output gap that is much smaller than currently estimated will be larger than just the direct impact stated above. A smaller degree of spare capacity will also place upward pressure on wages, all else remaining equal, thus contributing to further increases in inflation.

A01ufig06

Contribution of output gap to annual inflation forecast

(percentage points)

Citation: IMF Staff Country Reports 2011, 221; 10.5089/9781462337521.002.A001

Source: IMF staff estimates.

Commodity prices

29. Higher commodity prices pose a considerable upside risk to the central forecast. In the restricted VAR model, commodity prices contribute 0.6 percentage points to annual inflation in 2011. The importance of energy and food prices is individually taken into account in the disaggregated approach. Ignoring second round effects, a 10 percent increase in oil is estimated to increase headline inflation by 0.1 percentage points. The impact of an equivalent increase in global food prices, on the other hand, is estimated to be about 0.2 percentage points. While predictions based on futures contracts suggest a broadly stable outlook for oil prices, risks are tilted to the upside.17

E. Conclusion

30. Recent inflation overruns have largely been driven by temporary factors. Shocks to the price level arising from VAT and global commodity prices have kept inflation above target in recent months. Exchange rate depreciation and the impact of labor hoarding during the recession on unit wage costs were significant contributors to inflation during 2009–10.

31. As temporary factors dissipate, inflation is expected to return close to the 2-percent target by end-2012. The inflation model presented in this chapter—which takes the aforementioned factors into account—points to a moderation in the inflation rate in 2012 based on relatively stable commodity prices and an output gap that gradually narrows. The path to the target, however, is a bumpy one. Inflation is expected to remain well above 4 percent during 2011 before the base effect due to the VAT increase disappears and the disinflationary forces due to the negative output gap become more evident.

32. However, leading inflation indicators should be monitored closely. The evidence in this chapter suggests that movements in unit wage costs, inflation expectations, and other variables help predict future inflation. If the paths of these variables begin to deviate from the central scenario, inflation projections should be adjusted accordingly. If the shock to inflation is expected to be persistent, macroeconomic policy will also likely need to adjust.

References

  • Batini, N., B. Jackson, and S. Nickell, (2005), “An Open-Economy New Keynesian Phillips Curve for the UK,” Journal of Monetary Economics, Elsevier, vol. 52(6), pp. 1061-1071, September.

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  • Dwyer, A., K. Lam, and A. Gurney, (2010), “Inflation and the Output Gap in the UK,” Treasury Economic Working Paper No. 6.

  • Kapetanios, G, V. Labhard, and S. Price (2007), “Forecast Combination and the Bank of England’s Suite of Statistical Forecasting Models,” Working Paper No. 323, Bank of England.

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  • Stock, J., and M. Watson, (1999), “Forecasting Inflation,” Journal of Monetary Economics, Elsevier, vol. 44(2), pp. 293-335, October.

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    • Export Citation

  • Stock, J., and M. Watson,, (2002), “Macroeconomic Forecasting Using Diffusion Indexes,” Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.

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1

Prepared by Prakash Kannan (EUR).

2

Monthly inflation is computed as 1200*ln(CPIt/CPIt-1).

3

Implied inflation expectations based on 5-year zero-coupon inflation-indexed gilts. Implied RPI inflation rates from these gilts are multiplied by the average ratio of CPI to RPI inflation during the previous year to obtain CPI expectations.

4

Estimated using a multivariate filter; see United Kingdom—Selected Issues (IMF, 2010).

5

Typically, measures of the cost of labor to produce one unit of output take into account wages, salaries, pension contributions, social security payments, and benefits in kind. In the UK, only wages and salaries are used, hence the use of the terminology “unit wage cost” instead of the more common “unit labor cost”.

6

Available from the IMF’s International Financial Statistics.

7

Bank of England, Inflation Report, February 2011.

8

Monthly observations for data series that are only available at a quarterly frequency are based on interpolation.

9

The statistical significance of the variables is partly by construction, as a significance criterion was used to determine the lag structure.

10

The cumulative effect after 1 year would be about 1.2 percent.

11

Given the definition of monthly inflation in footnote 1, the inflation forecast over a horizon h can equivalently be stated as

π^t+h=1200hIn(CPIt+h/CPIt)
12

The set of indicators comprise more than 50 data series covering a broad range of categories that include indicators of activity, trade, financial conditions, the labor market, housing conditions, and income.

13

As shown in Kapetonis et al. (2007), the AR model typically yields the best forecasts.

14

The measure of core used here excludes energy, food, alcoholic beverages, and tobacco. The prices of tobacco and alcoholic beverages are assumed to follow the same inflationary pattern as for food.

15

The lag-length was selected based on the Bayesian Information Criterion. The relatively short time series of core inflation precludes a more elaborate specification.

16

Specifically, the following two equations are estimated:

ΔEnergyt = 3.64 + 0.15* ΔEnergyt-1 +.03* Δoilt + .07* Δoilt-1 ΔFoodt = 2.56 + 0.15* ΔaGlobal Foodt

17

The implied probability distribution of oil prices for 2011 (estimated based on options prices) indicate a positive skew coefficient of 0.4.

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Cover IMF Staff Country Reports
United Kingdom: Selected Issues Paper
Author: International Monetary Fund
Volume/Issue:
Volume 2011: Issue 221
Publisher:
International Monetary Fund
ISBN:
9781462337521
ISSN:
1934-7685
Pages:
60
DOI:
https://doi.org/10.5089/9781462337521.002

UK: Recent Inflation Performance

Decomposition of Recent Inflation Developments

(percentage points of annual rate)

UK: Inflation Developments

(annual rate, percent)

Oil prices

(APSP, USD; dashed segment indicates projection)

Inflation Projections using Various Models

(percent, annual rate)

Comparison of inflation projections

(percent, annual rate)

Projections for individual components of CPI

(annual growth, percent)

Comparison of Inflation Forecasts

(average annual rate, percent)

Contribution of output gap to annual inflation forecast

(percentage points)