Loading in 5 sec....

Heterogenous systematic risk in electricity distribution - The case of Sweden PowerPoint Presentation

Heterogenous systematic risk in electricity distribution - The case of Sweden

Download Presentation

Heterogenous systematic risk in electricity distribution - The case of Sweden

Loading in 2 Seconds...

- 125 Views
- Uploaded on
- Presentation posted in: General

Heterogenous systematic risk in electricity distribution - The case of Sweden

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Heterogenous systematic risk in electricity distribution - The case of Sweden

Jon Thor Sturluson

- Electricity distribution and transmission is a natural monopoly
- Regulation of prices requires:
- Estimate of cost of operation
- Historical
- Efficient benchmark

- Estimate of reasonable cost of capital
- Required return to capital
- Appropriate cost of debt

- Estimate of cost of operation

- Estimates of capital costs are often highly aggregate
- Two initial hypotheses
- Does size of operations affect cost of capital?
- Does geographic location affect cost of capital?

- Negative relationship between size and returns is often suggested
- Possiblereasons
- Wrongriskmeasure
- Wrongreturnmeasure
- Transactioncosts
- Vulnerablefirmstendtobe small
- Cost of andaccesstodebtfinancing/ creditrisk
- Economies of scaleandscope
- Concentrationandlack of competition

- Addingfirmsizemayrenderbetaaninsignificantpredictor of returns
- Measurement of firmsize (morelater)

- Operating a network in a rural area may be more risky
- Higher counterparty risk due to fewer customers
- Less diversified economy base
- Regional specific business cycles not diversified
- Economies of scale and scope
- Higher operating leverage?

- Data collected and published by the Energy Markets Inspectorate (EMI)
- Complete financial statements and extensive technical data
- Panel structure
- 1998 to 2008
- 176 / 166 cross sections
- Extensive adjustments due to mergers and changes in reporting

- ENERGY correlates with equity and conventional notions of size
- NETSIZE depends on geography and agglomeration
- Together these two variables capture variation in SPARSENESS of networks

- Estimate beta for each firm in turn
- Estimate a model with beta as a dependent variable
- Three possible sources of heterogeneity considered
- Spanor size of the network in km of wires (NETSIZE)
- Size Volume of energy distributed per year (mWh), alternatively total revenu from operations
- Sparseness or scope in relation to size
- Other variables consdiered but do not improve fit or change the outcome

Fixed-effects or betas for each firm estimated in a SUR regression

Wide range of betas (not display)

- Some are significant others are not

- Spareness effect is significant and nontrivial
- Parameter estimates are robust to changes in specification
- The hypothesis that a network with little distribution over a large network is more risky than on average is supported

- No significant relationship between cost of debt and size
- Average interest rate premium over 10 year government bonds estimated at 1.19%

- Accounting beta need to be translated to market beta
- Decomposition method (Mendelker and Rhee,1984)
- Scale w.r.t. existing benchmarks

- Example
- Two equally large groups of firms, classified by sparseness
- Beta scaled to an industry benchmark (0.40)*
- Sparse firms: b=0.274 rwacc = 4.6%
- Dense firms: b=0.533 rwacc =5.3%

- Other assumptions:
- Risk free rate = 4%
- Market risk premium = 5%
- Interest rate premium = 1.19%
- Marginal tax rate = 38%