We construct our forecast for PCs’ capital spending and gross operating surplus (GOS) based on the latest outturn data, which are provided to us in detail for each individual PC, under a restrictive data access agreement from the Office for National Statistics (ONS). The data for individual PCs are disclosive, which means that we can only publish outturns and forecasts at an aggregate level.
The largest elements of the capital spending and gross operating surplus forecasts are for housing associations (HAs), the housing revenue account (HRA) and Transport for London (TfL). The HAs forecast is produced for us by the Department for Communities and Local Government (DCLG) and is scrutinised by the OBR (more detail will be made available in due course on a separate page for the HAs forecast). In the case of the HRA, DCLG produces the forecast for the elements of locally financed capital expenditure (capital LASFE) that are financed from HRA sources. DCLG also forecasts HRA GOS and HRA asset sales. These DCLG forecasts are then scrutinised by the OBR, as part of the process for producing the forecast for capital LASFE. The TfL forecast is based on its latest published business plan. TfL assist us in scrutinising these plans before we produce our own central forecasts for TfL capital spending. For instance, we may include additional timing adjustments on TfL’s capital spending if we feel it would be central to assume some slippage, consistent with the general tendency in spending on large capital projects.
The remaining, smaller elements of the forecast are produced by us in-house. For different elements of the forecast, different methodologies are used (discussed in more detail in the main forecast judgements section below). These assumptions are reviewed each year to ensure they remain reasonable, although capital spending by public corporations – as with capital spending more generally – is difficult to forecast given volatility in the year-to-year spending profiles.
A number of elements of this forecast are driven by assumptions or business plans. The largest elements that are model-driven (excluding HAs) are:
- HRA spending and the imputed subsidy for equity injection by local authorities into the HRA (which is neutral for the public finances, being offset in GOS and National Accounts adjustments). The HRA spending model is owned and operated by DCLG and is largely driven by the latest outturn data, our economy forecast and any policy measures determining rents received and future house building programmes. We estimate the imputed subsidy in-house. The forecast is driven by the HRA spending model and a series of simple assumptions about how outturn will evolve for the other items that determine the subsidy.
- HRA asset sales (which nets off HRA gross capital spending). The model is split into proceeds from Right to Buy (RtB) and non-RtB sales. The model for RtB is again provided by DCLG, with the forecast driven by similar factors to the HRA model. The non-RtB forecast is driven by outturn and a slightly narrower set of determinants.
Main forecast determinants
For the HRA forecast, the main economic determinants are GDP growth, house prices and rental values, which affect income to and spending from the HRA via demand for social housing and the levels of rental income received by the operating local authorities. (The HRA is regarded as a public corporation, meaning this is where the final receipts and spending score in the National Accounts). The main components making up the HRA forecast – and the economic determinants driving them – are as follows:
- HRA GOS: this forecast is driven by the growth in the council rented housing stock, nominal GDP and social sector rents (with these rents being driven by CPI inflation from 2020);
- major repairs reserve (MRR): this forecast is driven by the growth in the council rented housing stock and nominal GDP; and
- HRA capital expenditure from revenue account (CERA): this forecast is driven by past trends, which are used in adjusting the jumping-off point. The forecast rises in line with our forecast for HRA GOS.
For the asset sales forecast, the main economic determinants are those that affect the demand for housing purchases via the price of the property and the purchasing power of the eligible population. They are:
Also reflected is the effective level of discount offered on the purchase of social properties by existing tenants.
Meanwhile, the non-RtB elements are driven by outturns and our forecasts for property transactions and house prices.
The most common assumptions used in other forecasts for PCs are to start from the latest outturn data on in-year estimates and grow the forecast in line with:
We utilise quarterly in-year information to test whether these assumptions seem to be producing a sensible view for the current year, and whether they therefore constitute reasonable assumptions for later forecast years. (These data are however subject to limitations and potentially subject to significant revision by the time quarterly outturns are finalised.)
Main forecast judgements
Capital spending can be subject to significant year-to-year fluctuations. Since we typically do not know in advance whether such fluctuations are likely to be upward or downward, our forecasts tend to assume the year-to-year pattern is fairly smooth (albeit with occasional step changes when the timing and size of one-off events can be predicted with sufficient confidence). Other year-to-year fluctuations that materialise but were not forecast often reflect unforeseen, and sometimes unforeseeable, events or timing effects. Our central forecasts are largely built on simple judgements about the evolution of certain spending and GOS items, in the knowledge that outturns will typically show much greater year-to-year volatility – in both directions – than our forecasts. (At the latest forecast, around a quarter of total PC GOS in 2016-17 came from forecast elements that are solely assumption-driven.)
The main forms of assumption we use include:
- grow in line with recent trends;
- grow in line with related items (for example, some HRA spending items increasing in line with projected HRA GOS and the council rented housing stock);
- grow in line with latest business plans;
- remain flat in cash terms;
- grow in line with nominal GDP; or
- grow in line with CPI inflation (thereby remaining flat in real terms).
A judgement is taken using recent data on which of the above methods seems most appropriate for each individual public corporation capital spending or GOS line that is forecast in this manner. These are reviewed ahead of each forecast.
Our asset sales forecast assumes recent trends in housing sales serve as a reasonable proxy for future years, although allowance is made for the effect of future interest rates, house price inflation and the general state of the economy (all of which contribute to demand).