RPI-X: Forecasting costs Regulation and Competition John Cubbin

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  • Slide 1
  • RPI-X: Forecasting costs Regulation and Competition John Cubbin
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  • Overview How do we work out financing requirement for a regulated natural monopoly?
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  • Elements of cash flow model Operating expenditures Maintenance, repairs, operation, customer transactions, central operations Capital expenditures Initial and closing regulatory asset base Future values discounted at cost of capital, avoiding accounting rates of return These are forward-looking costs, so costs need to be modelled
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  • Modelling costs Starting point is existing costs. Are they correct? Are they temporarily high or low for specific reasons? => initial adjustments Future costs depend on future events Need for forecasting elements Especially cost drivers
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  • Cost drivers: generic Capital ExpendituresOperating Expenditures Revenue requirement Cost of capital Demand growth Efficiency improvements Improved quality Risk Financial environment Environmental regulation Put in arrows to show main effects
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  • Demand growth Assumptions based on: Econometric analysis esp. income elasticities Surveys Other forecasts Impact on: New Capital expenditure Fixed operating cost Variable operating cost
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  • Specific cost drivers: electricity distribution impact of growth Electrical system costs: optimal layout given demand patterns number and distribution of customers maximum demand at various points provision for responding to faults, repairs, damage, etc. deviations of actual from optimal growth, churn, etc. Non system costs Billing, finance, regulation some fixed elements, other related to customer numbers Some of these are related to number of customers, some to demand or network complexity/length, some to overheads
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  • Quality The produce itself: Water purity, compliance of electricity with standards Gas calorific value (Wobbe Index), water content, etc. The quality of service: Response times Problems, billing, etc Interruptions to service Frequency, length, warnings, compensation Some related to environmental considerations:
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  • Environmental regulation Examples: CO 2 and SO 2 from power stations Water discharged from sewage treatment stations Pesticide and nitrates in drinking water
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  • Efficiency Requirement is usually to allow an efficient form to finance its activities What if a firm is inefficient? (and what do we mean by this anyway?)
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  • The frontier Minimum possible costs, given the cost drivers Cost Cost driver Theoretical frontier Empirical frontier
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  • Investigating the frontier Engineeering investigation of practices: intrusive, subjective Comparative analysis limited by paucity of observations transco, NGC: no real comparators but some use of inter-zonal comparisons in gas dist. Distribution companies: 14 observations per year International benchmarking? Difficulties (Make deductions about relative importance of cost drivers from foreign studies?)
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  • Types of comparative data analysis Simple cost ratios Regression analysis Data envelope (DEA) and other frontier techniques Combination of cross section and time series? (panel data) Some scope for international comparisons, limited by data definition issues.
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  • Dep var = log(delivery costs)OLS Stochastic Frontier (Half- normal) Variable (in logs usually)Coefft-ratioCoefft-ratio Constant-2.78-6.71-2.63-10.45 Wage rate paid1.0910.691.0310.67 Local Wage level0.121.580.11.36 Volume/Delivery point0.6718.150.6634.32 No delivery points (log)1.0251.521.01135.76 Road length per delivery point0.085.660.085.89 DELZONE1-0.1-1.28-0.1-1.95 DELZONE2-0.13-1.99-0.13-2.58 DELZONE3-0.1-1.57-0.09-2.19 DELZONE4-0.11-1.88-0.11-2.87 Business delivery points0.117.340.17.43 REDIRECTIONS0.031.590.0412.41 FRAMES-0.002-1.41-0.001-1.29 Example of econometric analysis of costs: postal delivery services
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  • Movement of the frontier Total factor productivity analysis compares movements of outputs and of inputs long term trend Energy industry plus other similar industries Overseas industries
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  • Example: Distribution costs
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  • Composite output 1999 Component Relative weight Customers 1.00 kWh 0.25 Network length 0.25
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  • Engineering analysis 1 In order to assess the potential savings available to each PES, a number of techniques were applied as follows: a cost per network kilometre benchmark of 575 per km, based on costs from four "top" PESs; "engineering cost" based on a profile of its network assets using a best practice cost per asset; comparison of historic savings achieved -- four of the top PESs achieved savings in engineering costs of up to 40 per cent from 1994/95 to 1997/98: in addition, the extent of savings in costs from 1990/91 to 1994/95 was also considered; a review of each PESs engineering organisational structures, field efficiency and operating practices;
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  • Engineering analysis 2 1) methods of cost reduction in past 2) plans for future Examples: new terms and conditions of employment increased condition monitoring of assets staff multi-skilling => range of estimated savings feeding into targets
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