For decades operators and speculators in the natural gas industry have looked to Wall Street for indications of short- and long-term growth to help them make business decisions.

But how accurate are those forecasts?

One undergraduate student researcher at West Virginia University has the answer.

Before even setting foot onto WVU’s campus, Stephen Sullivan, a senior environmental and natural resource economics student in the Davis College of Agriculture, Natural Resources and Design, knew he wanted to carve out a career in the energy industry.

Over the period of several years, however, he noticed there seemed to be a slowing of hiring – especially when it came to student internships in the industry.

“I started asking why, which led me to look more into the business and economic aspects of the energy industry,” Sullivan said. “What I quickly learned was that there was a steep decline in prices and that had led to a scaling back of operations due to the enormous amount of capital required to drill a well, do the site preparations or hire the labor. Therefore, my assumption was that hiring was being dialed back until prices rebounded.”
And that’s when the idea for his research project began to evolve.

“If companies are better able to predict what prices are going to do in the near future, they can better anticipate – not only their hiring needs – but their property acquisition strategies or divestment strategies,” he said.

Sullivan examined the forecast performance of the Energy Information Administration monthly Short-Term Energy Outlook and the New York Mercantile Exchange futures contracts – two widely accepted models within the energy industry – to see which performed better.

Both reports forecast at least 24 months out with the NYMEX extending several months beyond; however, for consistency, Sullivan looked at the 24-month horizons over a 10-year period.

He collected data from August 2005 to October 2014; however, after spending months categorizing and cleaning data sets, he realized neither the STEO reports nor NYMEX forecasts were particularly good at long-range forecasting.

“What I found was that forecast prices beyond three months were not meeting statistical significance criteria of 95 percent confidence,” he said.

After eliminating the excess data, Sullivan was able to determine that the STEO reports slightly outperformed the NYMEX forecasts – a reversal from findings in previous research.

Sullivan notes there were several major events – the 2007-08 recession, an increase in natural gas supply and improvements in technology that allow for more cost-effective extraction of gas – that could have contributed to the change.

However, the most significant event was the beginning exploration of the Marcellus and Utica shale beds.

“Hydraulic fracturing and horizontal drilling have been used for years, but previous research pre-dated the exploration of those techniques on the Marcellus shale,” he explained. “Once the potential for this huge play became realized it was a game changer. Our domestic production reserves shot through the roof.”

Those factors, Sullivan said, created volatility and chaos in the markets which intrigued him with respect to long-term forecasting.

Prior research examined the time period of 1998 to 2004 and found that the NYMEX did a better job forecasting what natural gas prices would be at the two-, three-, four- and 10-month points.

“I wanted to look at these two models based on these new factors,” he said. “When I narrowed the research data to a three-month horizon, it wasn’t close. The STEO clearly predicted better at the one, two and three month horizons.”

At the end of the day, Sullivan’s research points to one major concern that owners, operators and policymakers alike need to take into consideration – it’s extremely difficult to make long-range decisions in the natural gas industry.

He had the opportunity to talk with several West Virginia legislators about the issue during Undergraduate Research Day at the Capitol in February.

“I told them this research can give an appreciation to those outside the industry how difficult it is for operators to make long term decisions based on these forecasting models,” he said. “With an industry that is critical to this state’s economy, I think it’s important for policy makers to realize the challenges they face. I think it would behoove them to keep that in mind when they are crafting legislation that would inhibit or foster a pro-business climate.”

-WVU-

law/04/28/15

CONTACT: Lindsay Willey, Public Relations Specialist
304.293.2381, Lindsay.Willey@mail.wvu.edu

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