Institute for Transport Studies FACULTY OF ENVIRONMENT CQC Efficiency Analysis Concepts and approach Dr Phill Wheat Senior Research Fellow 14 th October 2014

What is Good?

Consider trying to determine if an authority is maintaining it’s highway network efficiently using high level data on costs and cost drivers Some authorities will perform well against some criteria and badly against others Lack of a single measure which gives a handle on potential cost savings that could be made Cost per highway km Cost per head Different answers from different measures Which to use?

What is Good? Even if there is only one measure, it maybe the case that larger authorities have an implicit (scale) advantage over smaller authorities Also other factors which influence (characterise) cost: Customer perception and output quality An authority has high cost, high quality Another has low cost, low quality The question we really want to know is whether either can reduce cost and still maintain quality …. difficult to compare costs when nothing else is equal!

What is Good? Cost Highway Length Cost frontier (drawn for a given level of quality)... A B C O Notice not a straight line… Economies of Scale (unit costs fall with the size of the authority)

What is Good? Cost Highway Length Cost frontier (quality = high)... A B C O Cost frontier (quality = low). D E. The bottom line here is that authorities A, B, C, D and E are all achieving the minimum cost possible for their size and quality, even though their unit costs are quite different

Authorities X and Y are above the frontier and so are inefficient By adopting best practice Authorities X and Y can reduce costs without sacrificing output What is Good? Cost Highway Length Cost frontier (drawn for a given level of quality) Y..... X A B C. X’ O Cost efficiency (TE) = Minimum cost/ Actual cost TE A =OX’/OX 0<=TE<=1 TE shows the proportion of actual cost which is needed if the authority adopted best practice (all other things equal)

Approach Need to model the explicit relationship between cost and the various cost drivers –Include quality, physical outputs and citizen satisfaction Allows us to see the trade-off that exists between cost and quality and citizen satisfaction Do this by exploiting the rich dataset collected –Use of regression analysis to model minimum costs and then compute the efficiency gap for each authority –Gives clear indication as to the cost of incrementing quality and citizen satisfaction holding everything else equal Log(min cost) = a 0 + a 1. Log (cost driver 1) + a 2. Log (cost driver 2) + … … + a k. Log (cost driver k)

What we DO get from this analysis An estimate of the minimum cost for each authority tailored to its own characteristics, quality and citizen satisfaction A tool to conduct what if analysis e.g. How do (minimum) costs change if: –Authorities merged highway functions and increased network size for a given operation, –an Authority were to change quality (e.g. to improve average condition by 1%) –Authority was prepared to allow public satisfaction to reduce A potential cost saving for each LA (if they closed the gap) Identification of the best performing authorities which is useful to direct more process oriented analysis (to establish why there is a gap)

What we DO NOT get from this analysis An understanding of WHY there is a gap between actual observed cost and minimum cost –Analysis is useful to identify potential saving magnitude and identify which LAs look like they are performing close to minimum cost –But supplementary work is required to establish and disseminate best practice The ‘gap’ is what is left over once we control for the effects of cost drivers –We can only control for the cost drivers (variables) that we can collect –Thus there maybe other reasons (outside of an LA’s control) which may explain the gap The gap is likely to be a maximum possible saving rather than an absolute

Institute for Transport Studies Dr. Phill Wheat Senior Research Fellow Institute for Transport Studies University of Leeds We offer taught courses, bespoke training and research consultancy across a range of transportation policy, regulation and economics areas