Modeling supply-demand for Elderly-care Homes spurred Govt to defer unworkable changes, imposed with no idea how the market actually works.
Strategy in public policy, as in business is simply “What to do, when, how much, to get desired outcomes” but is often more complex because there is rarely one authority ‘in charge’. Legislation facing 136 Local Authorities (LAs) in England and Wales, was to impose additional responsibilities to finance the care of frail elderly people who cannot themselves afford it. Those responsibilities would also include minimising costs to local tax-payers (whose taxes finance this care) and ensuring “a viable market” for the provision of Residential Homes and Nursing Homes.
‘A market’ consists of demand arising from potential customers (numbers of frail elderly) and the capacity offered by Providers to serve that demand (places in Care Homes). Work with Care-system experts Laing-Buisson looked at how changing demand had driven Care-home revenues from 2005-2014 in a sample of LAs. Escalating fees during the good times of 2005-2008 mostly led to rising capacity (opening some 3 years after good ROI triggered the build decision – a standard business decision for Providers. ) … but severe fee-reductions during 2009-2014 mostly killed new construction. The situation across the sample Counties varies considerably with a few having – just about – a viable market, while many Providers in other Counties cannot afford to keep operating, let alone open new Homes.
Once validated across multiple LAs over 10 years, the model anticipates what would happen to supply/demand under a complex set of demand and fee-rate scenarios out to 2025. The perfectly reasonable aim that “no elderly person should be impoverished by paying for their own care” turns out to be entirely unfeasible. Either prices paid by Councils have to be so low that Homes close and no new capacity opens, or else swingeing tax increases are needed to ensure capacity continues to grow adequately.
… just goes to show it might be a good idea to model policy first, before adopting it – rather than adopting policy, based on results using crude econometric tools that can’t give the right answer, then (as in this case) having to back-track.
Interestingly, this is a perfect example of industry cyclicality … slowly rising demand, when capacity comes in large ‘lumps’ with a construction delay. Where next? … the model is a perfect long-range planning tool for LAs and Providers jointly to anticipate likely supply-demand changes, and test alternative policies. (Transparency of data is one of the key factors to limit the damage of industry cyclicality).Share