HHPI: Scenario Analysis for UK
Regions Information relating to the effects of reduced mortgage volumes on HHPI regional data
Confidential | Copyright © 2020 IHS Markit Ltd HHPI: Scenario Analysis for UK Regions
1 Introduction 3
2 Confidence Intervals 3
3 Stress Scenarios 4 4 Summary and Proposed Approach for Q2 2020 6
Appendix 8
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HHPI: Scenario Analysis for UK Regions
1 Introduction
This paper builds on our previous assessment of the performance of the Halifax House Price Index (HHPI) from the perspective of markedly reduced volumes of approved mortgage data. Whereas our focus was previously on headline UK figures, both for the 1983 and 2019 versions, we now switch our attention to the regional all house all buyers (AHAB) indices. The approach remains similar, however, with regional performance considered from two similar angles. Firstly, focus is on the monthly residual data (i.e. the “errors”) from underlying regression models to construct confidence intervals around index point estimates. Secondly, the hypothetical stress test scenarios whereby quarterly mortgage volumes are lowered by specific amounts compared to a typical quarterly average over a year long period is repeated. The regions we have chosen for analysis are Northern Ireland, Yorkshire & Humberside and Greater London. These have been chosen as representatives of three distinct regional cohorts – small, medium and large contributors – that exist within the HHPI dataset.1
2 Confidence Intervals
In line with our previous work for the headline UK indices, as sample size decreases then regional index confidence intervals are wider than would typically by the case. The two tables below show this. These tables highlight the indicative results for both HHPI (1983) and HHPI (2019) under the scenarios of -80%, -85% and -90% cuts to sample size from typical levels. Note that, due to much lower sample sizes in general, for Northern Ireland the reductions were respectively -50%, -65% and -75%. We also include the UK results for comparison. As was the case with the UK indices, several stylised facts emerge from the analysis. Firstly, confidence intervals are negatively affected by lower sample size – as sample size declines then intervals increase and (in several cases) at a faster rate. This is in line with our previous assertation that the relationship between sample size and confidence intervals may be exponential in nature.
1 We have identified three groups of regions in terms of contribution to the HHPI sample.
For HHPI (2019): Small = Northern Ireland, North East and Wales Medium = East Midlands, South West, West Midlands, and Yorkshire & Humber Large = Eastern England, Greater London, North West, South East, and Scotland
For HHPI (1983): Small = East Anglia, Northern Ireland, North and Wales Medium = East Midlands, South West, West Midlands, and Yorkshire & Humber Large = Greater London, North West, South East, and Scotland
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HHPI: Scenario Analysis for UK Regions
1. HHPI (2019): 95% Confidence Intervals
Typical -80% -85% -90%
Greater London 1.20% 1.70% 1.80% 2.40%
Northern Ireland* 2.10% 2.80% 3.40% 3.60% Yorkshire & Humber 1.20% 2.30% 2.70% 3.10% UK 0.35% 1.10% 1.20% 1.40%
2. HHPI (1983): 95% Confidence Intervals
Typical -80% -85% -90%
Greater London 1.40% 2.90% 3.40% 4.10%
Northern Ireland* 3.20% 3.80% 4.50% 5.10%
Yorkshire & Humber 1.50% 3.80% 4.30% 5.90%
UK 1.00% 1.80% 1.90% 2.10%
*Northern Ireland reductions were -50%, -65%, and -75% respectively Secondly, confidence intervals are generally narrower – and more stable – for HHPI (2019) than those recorded for HHPI (1983). The differences in regional bands are a little tighter than at the UK level, but these tend to rise as we cut typical sample sizes to ever greater degrees. We continue to attribute these differences to the more parsimonious model specification and better explanatory power of HHPI (2019) models. Within the regions Greater London, with the higher sample size, records the tightest confidence intervals of the three regional representatives (typically around 25%-35% narrower for respective interval ranges). At the other end of the scale, the smallest region, Northern Ireland generally performs worst, although for HHPI (1983) the results at the more extreme levels of sample reductions are similar for both Northern Ireland and Yorkshire & Humber.2 Finally, all regions naturally recorded wider intervals than would be typically seen at the UK level across all bands.
3 Stress Scenarios
We now turn to the stress testing of the indices during a sustained period of markedly reduced transaction volumes. Again, as we did for the UK indices, three stress tests have been conducted.
2 As we effectively placed a floor on the number of mortgages we could realistically test for Northern Ireland, the absolute sample sizes at the extreme levels for both Northern Ireland and Yorkshire & Humber were broadly similar.
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HHPI: Scenario Analysis for UK Regions
In these scenarios, mortgage volumes were cut by approximately -80%, -85% and -90% compared to the typical quarterly average for both HHPI (2019) and HHPI (1983), although we again made smaller cuts to Northern Ireland given its typically much lower sample size. The analysis was also conducted over a 12-month period starting January 2019 and ending December 2019. Again, the aim is to understand how the respective indices would perform (in terms of annual inflation rates) compared to the actual published readings (see appendix for discussion on seasonally adjusted figures). Overall, there was limited evidence of model misspecifications across the regions compared to what we typically observe: coefficient p-values and model RSQ readings were overall broadly stable compared to those observed at the headline level. However, in some instances, postcode classification variables were seen to turn insignificant at the more extreme sample size levels. Estimations of the coefficients again showed variances on a period-to-period basis, and especially at the more extreme sample sizes for Northern Ireland and Yorkshire & Humberside. This helps to explain the increased volatility in the indices highlighted in the charts below: the determination of regression coefficients becomes increasingly challenging at lower sample sizes and can drive greater variance in the indices across periods. Comparing on a purely regional basis, those with the larger sample size i.e. Greater London appear to have tighter, less volatile readings when compared against the smaller regions. As was the case at the UK level, in several cases however volatility shows signs of offsetting with overall rates of inflation for 2019 relatively close to published levels.
3. HHPI (2019): Sample Size Reduction Scenarios
London Yorkshire & Humber
Northern Ireland
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HHPI: Scenario Analysis for UK Regions
4. HHPI (1983): Sample Size Reduction Scenarios
London Yorkshire & Humber
Northern Ireland
4 Summary and Proposed Approach for Q2 2020
Our latest analysis provides insight into the possible impact on HHPI indices of the sharp drop in mortgage volumes that is currently being experienced in the UK housing market due to the COVID- 19 pandemic. As expected, index readings for the regions inevitably suffer from both greater uncertainty and higher levels of quarter-to-quarter volatility at lower sample sizes – and to greater degrees than we saw at the UK level. Statistical performance may also show a modest deterioration at extreme sample sizes. Transaction Volumes in Second Quarter of 2020 Looking towards the second quarter of 2020, during April and May average transaction volumes have been down across the UK by approximately -80% for HHPI (2019) data and approximately -85% for HHPI (1983). However, during the final days of May an emerging upward trend in daily transaction volumes has been observed, which has continued into the first 10 days of June. Growth has largely been centred on the English regions, in line with the easing of restrictions compared to the Northern Ireland, Scotland and Wales, but overall – based on current trajectories – HHPI (2019) transaction volumes are likely to be down around -35% compared to typical levels. For HHPI (1983) the overall decline
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HHPI: Scenario Analysis for UK Regions
is set to be roughly -40%.3 Over the quarter as a whole, HHPI (2019) will likely see a fall in transaction volumes of somewhere between -65% and -70% compared to typical levels, whereas for HHPI (1983) the decline will probably be in the range of -70% and -75%. Based on transactions volumes for April and May, plus June projections, our expectations are that transaction volumes will be approximately be reduced, as a percentage of typical levels, by the following amounts:4
5. Expected Regional Sample Size Reductions for Q2 2020 HHPI(1983) HHPI(2019) England -65% to -70% -60% to -65% Scotland -80% -80% Wales -80% -80% N.Ire -90% -90%
Proposed Approach for Second Quarter of 2020 Given the analysis of the effects on lower sample sizes on the HHPI indices, and our current projections for Q2 mortgage approval totals, we anticipate providing direct support for HHPI (1983) regional models in the second quarter of 2020. For HHPI (2019) regional models, we are expecting to support the Northern Ireland indices only. The different approaches to HHPI (1983) and HHPI (2019) primarily reflects the variance in general sample size across the two sets of indices: HHPI (2019) typically enjoys around a third more mortgage approvals than equivalent HHPI (1983) indices. Based on the projections for the second quarter, HHPI (2019) indices are set to retain enough absolute level of mortgages to ensure acceptable model stability without the need for additional support (Northern Ireland excepted). For those indices in need of direct support this will be performed via a boost to sample sizes through the addition of March approved mortgage transactions in the Q2 calculations. Without such support several indices would face insufficient data for actual calculation or risk being produced with a considerable degree of uncertainty. The effects on the HHPI transaction volumes of including additional March data would be expected to result in following reductions to regional sample sizes:
6. Expected Regional Sample Size Reductions (March 2020 + Q2 2020) HHPI(1983) HHPI(2019) England -50% to -55% n/a Scotland -60% to -65% n/a Wales -60% to -65% n/a N.Ire -75% to -80% -75% to -80%
3 The difference between HHPI (1983) and HHPI (2019) with regards sample size reductions reflects the use of AVM and remote desktop valuation procedures – which HHPI (1983) indices cannot include due to the requirement of a much wider range of house characteristic data than typically provided by AVM and desktop approvals – and general sample differences. For instance, HHPI (1983) indices do not include mortgage approvals on properties related to shared ownerships or government schemes (such as Help to Buy). 4 Note that England refers to the average for the nine English regions covered by the HHPI.
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HHPI: Scenario Analysis for UK Regions
Finally, based on estimated transaction volumes for the regional indices and the historical relationship with sample sizes, indicative confidence intervals are provided in the table below for the three regional tiers:
7. Approximate Confidence Intervals for Q2 2020 Regional Data HHPI(1983) HHPI(2019) Tier1 +/- 2.0% +/- 1.3% Tier2 +/- 2.4% +/- 1.4% Tier3 +/- 3.6% +/- 1.7%
For further details related to the information and analysis in this paper, please send any queries to [email protected] or [email protected]
Appendix
Stress Scenarios: Seasonal Adjusted Indices The following charts provide the implicit quarterly rates of change in the three regions chosen for the analysis in the main part of this paper for both HHPI (1983) and HHPI (2019). Note that annual rates of change in the seasonally adjusted and non-seasonally adjusted indices are (theoretically) broadly equivalent: as seasonality over a year by definition will cancel itself out the process of seasonal adjustment is designed purely to remove any influences related to seasonality on a quarter-to-quarter basis. From the charts below, as would be expected based on the trends in the annual rates of change, quarterly inflation levels would likely be more volatile across all regions and by version of the HHPI if sample sizes are reduced. Again, the greater the reduction in sample size, the more volatile the movements in the indices. In general, HHPI (2019) indices show better stability than HHPI (1983) equivalents.
8. HHPI (2019): Sample Size Reduction Scenarios (Seasonally Adjusted Indices)
London Yorkshire & Humber
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HHPI: Scenario Analysis for UK Regions
Northern Ireland
9. HHPI (1983): Sample Size Reduction Scenarios (Seasonally Adjusted Indices)
London Yorkshire & Humber
Northern Ireland
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