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have two effects: First, COB indexing tends to overstate prices for contracts to the north of the California border. Second, COB indexing gives the wrong price signal for contracts where energy use is highly dependent on price.
Plotting the Differential
Many market participants have a good anecdotal feel for price differentials between WSCC sub-regions, but lack of data up to now has made accurate calculations impossible.
To move from anecdote to evidence, a logical approach would rely on the Alberta, COB, and Palo Verde markets for pricing information, with adjustments to reflect geographic differentials. Economic Insight's data suit this purpose perfectly since they carefully map the whole of the WSCC. This approach also minimizes concerns about the use of survey data versus actual market data, since the fluctuations are taken directly from markets at COB, Palo Verde, or Alberta.
Table 1 estimates the average differentials between different indices throughout the WSCC, based on survey data from a variety of sources.
To read this table, take the index used in the power contract. For example, if the contract used the NYMEX COB index, look down the left column until you find the actual physical location of the transaction. If an industry bought indexed power at Four Corners, the adjustment to the COB index would be -.45 mills, which reflects the generally higher power costs at COB.
Highlighted rows and columns reflect a relatively poor market relationship between that index and the rest of the WSCC. Three locations tend to report a poor correlation with other WSCC prices. The first two (em the indices for "Canada" (primarily information from B.C. Hydro) and the Alberta power pool (em reflect the lack of market access in British Columbia. The generally poor results tend to substantiate the impression many market participants have of B.C. Hydro's efforts to monopolize transactions in their province. The other index showing a relatively poor correlation with WSCC markets is NYMEX Palo Verde. Perhaps that fact stems from the recent introduction of the Palo Verde index.
Table 2 shows the correlations
(R squared, or "coefficient of determination") for each of the WSCC indices. The statistical quantity, R², shows the percentage of the total variance explained by a relationship between price indices at the two locations. A perfect explanation posts an R² of 100 percent; a poor explanation shows a low R².
With the exception of the three indices mentioned above, correlations throughout the WSCC remain quite high, reflecting the excellent access to transmission throughout the region and the availability of a number of sophisticated marketmakers. Economic theory predicts a high correlation as brokers purchase from low-cost areas and wheel the power to meet high-cost opportunities. The exception of British Columbia is also consistent with economic theory: B.C. Hydro's market power logically appears as a lower correlation between market forces on the opposite sides of the province.
A More Exacting Approach
The high correlations in the preceding tables allow an exploration of a more sophisticated version of basis adjustment. Over the past several years, for example, prices in the Pacific Northwest have enjoyed a