The role of risk aversion in coal contracting behavior of US power plants – Watts Up With That?

news7g01/15/2022

8 3 minutes read

The role of risk aversion in coal contracting behavior of US power plants - Watts Up With That?

UNIVERSITY OF CHICAGO PRESS JOURNEY

A new paper was published in Journal of the Association of Environmental and Resource Economists provides empirical evidence that risk aversion plays an important role in the coal contract behavior of US power plants.

In “Regulatory risk aversion to coal use in US power plants: Implications for environmental policy, author Akshaya Jha notes that between 1983 and 1997, US power plants bought most of their coal inputs from long-term contracts, continuously paying contract prices higher than prevailing spot coal prices. . Jha proposes a regulatory mechanism as to why power plants in particular may appear to be risk averse in purchasing inputs, arguing that regulators are in fact less likely to put the determination input costs are high on the output prices they set for utilities. Utilities respond to this regulatory practice by taking costly actions to reduce the variance of input costs.

Jha specifies an illustrative model in which a profit-maximizing firm is expected to receive a regulated revenue stream. This adjusted revenue stream only reimburses the company for total costs below a specific “conservative” threshold. Jha demonstrates that the firm pricing within this framework does not minimize total expected costs, but instead exhibits preference for both lower total expected costs and lower total variance.

Jha estimates the risk aversion of US power plants using transactional data on coal purchases for almost every US power plant from 1983–97. The spot price uncertainty faced by each plant in each month is estimated using a panel data version of the cubic autoregression model for spot price growth; Both the mean and the variance of this growth rate are allowed to vary depending on the region where the plant is located and the month of the year.

Jha finds that power plants experiencing a lot of volatility in spot coal prices will enter into longer-term coal contracts that buy coal from a larger number of counties of origin and pay the average contract price for coal. higher. To come up with his estimates, Jha notes, “if every power plant bought all of their coal from the spot market, the average total annual cost savings would be $2.9 billion.”

The results indicate that a 10% increase in spot price uncertainty is associated with a 0.9% increase in contract coal prices, and both risk aversion and investments are specifically related. important factors determining the coal contracting behavior of US power plants. “This suggests that any empirical analysis of contracting should take into account the roles of both transaction costs and risk aversion,” Jha writes. His estimated effect of spot price uncertainty on contract prices implies that mills are willing to trade off a $1.62 increase in their total expected cost for a decrease of 1. dollars in the standard deviation of total costs. “This is much larger than the risk premium paid traditionally in the commodity markets, suggesting that price-regulated electric utilities have a particularly low risk tolerance.”

Jha uses his estimate of risk aversion to perform a simple simulated analysis of the cost-effectiveness of a carbon tax versus cap and trade. The inputs to this simulation analysis are the plant’s risk aversion, the average price of the license, the volatility of the license price, and the correlation between the license price and the spot coal price. The carbon tax is set equal to the average license price, noting that the conditional variance of the carbon tax is zero. At the central parameter values, the ratio of total costs incurred by sub-limited and commercial plants to the carbon tax is 1.27. When the risk aversion parameter was set to 50% of his estimate, the relative cost-effectiveness ratio was 1.13. Therefore, this relative cost-effectiveness ratio is very sensitive to the assumed degree of risk aversion. “The results of my simulation analysis highlight that risk aversion should play an important role in the decision about which of these two policy tools to implement,” he concludes.