Facebook LinkedIn Twitter
Energy Journal Issue

The Energy Journal
Volume 35, Number 1

IAEE Members and subscribers to The Energy Journal: Please log in to access the full text article or receive discounted pricing for this article.

View Cart  

The Perils of the Learning Model for Modeling Endogenous Technological Change

William D. Nordhaus

DOI: 10.5547/01956574.35.1.1View Abstract

Modeling of technological change has been a major empirical and analytical obstacle for many years. One approach to modeling technology is learning or experience curves, which originated in techniques used to estimate cost functions in manufacturing. These have recently been introduced in policy models of energy and climate-change economics to make the process of technological change endogenous - that is, allow technologies to vary with economic conditions. It is not widely appreciated that using learning in modeling raises major potential problems. The present note has three points. First, it shows that there is a fundamental statistical identification problem in trying to separate learning from exogenous technological change and that the estimated learning coefficient will generally be biased upwards. Second, we present two empirical tests that illustrate the potential bias in practice and show that learning parameters are not robust to alternative specifications. Finally, we show that an overestimate of the learning coefficient will provide incorrect estimates of the total marginal cost of output and will therefore bias optimization models to tilt toward technologies that are incorrectly specified as having high learning coefficients. Keywords: Learning by doing, Climate change, Technological change

The Incidence of an Oil Glut: Who Benefits from Cheap Crude Oil in the Midwest?

Severin Borenstein and Ryan Kellogg

DOI: 10.5547/01956574.35.1.2View Abstract

Beginning in early 2011, crude oil production in the U.S. Midwest and Canada surpassed the pipeline capacity to transport it to the Gulf Coast where it could access the world oil market. As a result, the U.S. "benchmark" crude oil price in Cushing, Oklahoma, declined substantially relative to internationally traded oil. In this paper, we study how this development affected prices for refined products, focusing on the markets for motor gasoline and diesel. We find that the relative decrease in Midwest crude oil prices did not pass through to wholesale gasoline and diesel prices. This result is consistent with evidence that the marginal gallon of fuel in the Midwest is still imported from coastal locations. Our findings imply that investments in new pipeline infrastructure between the Midwest and the Gulf Coast, such as the southern segment of the controversial Keystone XL pipeline, will not raise gasoline prices in the Midwest.

The Effects of Oil Price Shocks on Stock Market Volatility: Evidence from European Data

Stavros Degiannakis, George Filis, and Renatas Kizys

DOI: 10.5547/01956574.35.1.3

View Executive Summary
View Abstract

The paper investigates the effects of oil price shocks on stock market volatility in Europe by focusing on three measures of volatility, i.e. the conditional, the realized and the implied volatility. The findings suggest that supply-side shocks and oil specific demand shocks do not affect volatility, whereas, oil price changes due to aggregate demand shocks lead to a reduction in stock market volatility. More specifically, the aggregate demand oil price shocks have a significant explanatory power on both current-and forward-looking volatilities. The results are qualitatively similar for the aggregate stock market volatility and the industrial sectors' volatilities. Finally, a robustness exercise using short-and long-run volatility models supports the findings.

Nonlinear Pricing and Tariff Differentiation: Evidence from the British Electricity Market

Stephen Davies, Catherine Waddams Price, and Chris M. Wilson

DOI: 10.5547/01956574.35.1.4View Abstract

Liberalisation of the British household electricity market, in which previously monopolised regional markets were exposed to large-scale entry, is used as a natural experiment on oligopolistic nonlinear pricing. Each oligopolist offered a single two-part electricity tariff, but inconsistent with current theory, the two-part tariffs were heterogeneous in ways that cannot be attributed to explanations such as asymmetric costs or variations in brand loyalty. Instead, the evidence suggests that firms deliberately differentiated their tariff structures, resulting in market segmentation according to consumers' usage.

Stochastic Mixed-Integer Programming for Integrated Portfolio Planning in the LNG Supply Chain

Adrian Werner, Kristin Tolstad Uggen, Marte Fodstad, Arnt-Gunnar Lium, and Ruud Egging

DOI: 10.5547/01956574.35.1.5View Abstract

We present a new model to support strategic planning by actors in the liquefied natural gas market. The model takes an integrated portfolio perspective and addresses uncertainty in future prices. Decision variables include investments and disinvestments in infrastructure and vessels, chartering of vessels, the timing of contracts, and spot market trades. The model accounts for various contract types and vessels, and it addresses losses. The underlying mathematical model is a multistage stochastic mixed-integer linear problem. Industry-motivated numerical cases are discussed as benchmarks for the potential increases in profits that can be obtained by using the model for decision support. These examples illustrate how a portfolio perspective leads to decisions different than those obtained using the traditional net present value approach. We show how explicitly considering uncertainty affects investment and contracting decisions, leading to higher profits and better utilization of capacity. In addition, model run times are competitive with current business practices of manual planning.

Market Design with Centralized Wind Power Management: Handling Low-predictability in Intraday Markets

Arthur Henriot

DOI: 10.5547/01956574.35.1.6View Abstract

This paper evaluates the benefits for an agent managing the wind power production within a given power system to trade in the intraday electricity markets, in a context of massive penetration of intermittent renewables. Using a simple analytical model we find out that there are situations when it will be costly for this agent to adjust its positions in intraday markets. A first key factor is of course the technical flexibility of the power system: if highly flexible units provide energy at very low prices in real-time there is no point in participating into intraday markets. Besides, we identify the way wind production forecast errors evolve constitutes another essential, although less obvious, key-factor. Both the value of the standard error and the correlation between forecasts errors at different gate closures will determine the strategy of the wind power manager. Policy implications of our results are the following: low liquidity in intraday markets will be unavoidable for given sets of technical parameters, it will also be inefficient in some cases to set discrete auctions in intraday markets, and compelling players to adjust their position in intraday markets will then generate additional costs.

Dynamic Adjustment of Crude Oil Price Spreads

Atanu Ghoshray and Tatiana Trifonova

DOI: 10.5547/01956574.35.1.7

View Executive Summary
View Abstract

This paper examines the dynamic adjustment of crude oil price differentials formed by a wide range of popularly traded crude oils which include non-benchmark crudes of different quality. Recent studies have pointed out the fact that the adjustment of oil price spreads is asymmetric in nature. This paper makes a contribution in many ways. Employing econometric procedures that are more powerful than recently applied methods, and on a much wider selection of crude oil pairs than previous studies we establish that the results obtained for price differentials between benchmark crudes are not representative of the behaviour of non-benchmark pairs. Further, our results show that the adjustment of price differentials cannot be fully explained by the quality differentials which are commonly approximated by the difference in API gravity. Finally, we find that short run and long run dynamics do not show a pattern that could be linked to quality differentials.

The Impact of Dynamic Pricing on Residential and Small Commercial and Industrial Usage: New Experimental Evidence from Connecticut

Ahmad Faruqui, Sanem Sergici, and Lamine Akaba

DOI: 10.5547/01956574.35.1.8

View Executive Summary
View Abstract

Among U.S. households, a quarter have smart meters but only one percent are on any form of dynamic pricing. Commissions and utilities continue to study the potential benefits of dynamic pricing through experimentation but most of it involves the residential sector. We add to that body of knowledge by presenting the results of a pilot in Connecticut which included small commercial and industrial (C&I) customers in addition to residential customers. The pilot featured a time-of-use rate, two dynamic pricing rates and four enabling technologies. Customers were randomly selected and allocated to these rates, to ensure representativeness of the final results. The experiment included a total of around 2,200 customers and ran during the summer of 2009. Using a constant elasticity of substitution model, we find that customers do respond to dynamic pricing, a finding that matches that from most other experiments. We also find that response to critical-peak pricing rates is higher than response to peak-time rebates, unlike some other experiments where similar results were found. Like many other pilots, we find that there is virtually no response to TOU rates with an eight hour peak period. And like the few pilots that have compared small C&I customer response to residential response, we find that small C&I customers are less price responsive than residential customers. We also find that some enabling technologies boost price responsiveness but that the Energy Orb does not.

Voluntary Programs to Encourage Diffusion: The Case of the Combined Heat-and-Power Partnership

Andreas Ferrara and Ian Lange

DOI: 10.5547/01956574.35.1.9View Abstract

In the last decade, voluntary environmental programs have increased considerably in number and scope. A novel use of these programs is to diffuse new technology in industry as means to improving their environmental outcomes. This paper tests whether the U.S. Environmental Protection Agency's Combined Heat-and-Power (CHP) Partnership has encouraged the diffusion of CHP systems. Using a nearest neighbor matching estimator with electricity plant data and conditional logit estimation for electricity and manufacturing plants in the U.S., we find evidence that the program has helped CHP systems spread, controlling for the selection of firms into the partnership. On average partner firms have a 3% higher probability of installing CHP.