If I could predict crude oil prices, I wouldn’t be writing this, I’d be somewhere warm, writing a very different blog post. The Alaska Legislature finds itself in the same situation, except that they go someplace wet (Juneau) each year and build a budget in which (historically) around 90 percent of revenues come from the volatile commodity.
A couple months out from the 2016 session, we’re soon expecting the Alaska Department of Revenue’s Fall Revenue Sourcebook, one of the major tools we have for predicting oil prices and our future state budgets.
We’re halfway through FY2016 now, which ends June 30, 2016. Let’s see how the experts DOR uses did over the last decade predicting this exact year.
The estimates range from a spartan $25.50 to a dreamy $114.88 per barrel of Alaska North Slope at West Coast refineries. While we still have another seven months before FY2016 is done, oil prices would have to climb in a hurry to break $60 for the year’s average.
Where do these numbers come from? Why do they exist? Why bother predicting more than a few months ahead? Maybe I should ask myself the same questions. It’s either that or don’t plan at all?
The DOR currently brings together experts in a closed-door session each fall for a day based on “a modified Delphi Method” to produce the oil price predictions that guide revenue models. Dermot Cole last year outlined a few of the quirks of the process developed by the RAND Corporation.
37 people from state government, business, and academia took part in 2014, according to the state. They each scribbled down their forecasts after “a day of presentations by experts on oil price markets and market structure.”
Can you picture eight hours of PowerPoint presentations and a lot of pondering and furrowed brows? I’m picturing pretty good catering?
After a look at the last decade of forecasts, time and global markets have not been kind to the prognosticators. Digging through a trove of PDFs on the DOR website, I pulled forecasts going back to 2001.
The predictions can be wildly off, especially more than a couple years out. The lean years of the late ’90s were not far out of memory when the prediction team anticipated oil staying low.
In November of 2005, when prices hovered in the mid-50s, DOR assumed a long-term average of $25.50 in the years to come (At that time, rules restricted long-term changes to once every two years upon agreement from forecasting participants.)
In October/November of 2013, the group predicted FY2016 oil to be near $107.69. (It was at 42.34 on November 19th). Triple digits had been the norm for some time by 2013. (The state-funded $24 million Bethel pool was under construction in 2013 and we were holding Knik Arm Bridge hearings.)
The forthcoming glut of new American and cheaply-produced Saudi oil had yet to be reflected in prices. It makes total sense now.
Few predicted the(ongoing) collapse in prices that began a year ago. I might actually have enough cash in my wallet right now to buy a barrel of oil. That is rarely true.
The 2014 estimate for FY2016 (which for short term forecasts relied on a new internal probabilistic model based on “Jump Diffusion”) called for more modest $66.03. While it sounds close, that’s still 34% above the current FY2016 daily average of 49.18. That’s a difference this year of $400+ million dollars in unrestricted reveue, according to 2014 assumptions.
The estimated prices in the above graph begin at most about 6-9 months after the time of the forecast in the first year in which participants have no actual data, that is, only true predictions are included. For example, the November 2001 group worked in middle of FY2002, looking forward to FY2003 which was to begin a half year ahead in July of 2002.
The following chart shows these initial predictions of about seven to 18 months ahead.
Until the recent plunge in prices, the oil market consistently outperformed expectations, including a near doubling in 2008. It gets worse if you try to predict further back.
Two years isn’t any better, and five years isn’t good for much.
How large is the difference compared to the actual price? The Oracles consistently underestimated prices. Until they didn’t.
We would hope that these percentage difference lines would hover a bit closer to zero.
What’s to come? The 2015 Spring estimate looks forward to a surge. Oil hits $86.66 in FY2017, rises steadily to $109.54 by 2020, and is an attractive $124.34 in 2024. Never mind the forecast of just 320,300 barrels per day flowing down TAPS that year. Maybe we’ll have the first drops of LNG flowing by then.
Estimates are estimates. What happens in OPEC meetings, on the tar sands of Alberta, and within East Asian economies will ultimately determine the price. Right?
In any case, the state now makes more from appreciation and dividends from the $50 billion in the Permanent Fund than oil.
Dermot Cole said it best in his article:
“The future is uncertain.”
Alaska DOR said it second best on the cover of their cryptic 1989 Fall Revenue Sourcebook.
“Free Rides Die Hard.”
Notes: Data come from Alaska Department of Revenue sourcebooks. Price data are from DOR forecast documents and the DOR Tax Division ‘s records. This used nominal values from fall forecasts with the exception of 2015, which used the spring book.
I parsed data in Excel and charted in Plot.ly. Revenues to the state are based on the wellhead price, which subtracts costs and other items. I used ANS West Coast for consistency across tax regimes and to reflect DOR’s predictions on solely price instead of the many other factors it takes into account.
You can view data here.