“Predicting is very difficult, especially if it’s about the future.”

– Niels Bohr

“Weather forecast for tonight: dark.”

– George Carlin

Residual Values: the Third Rail of aircraft ownership discussions. Currently, they are bad and unpredictable. Previously, they were better and unpredictable. But the question of “what will my plane be worth in 5 years” remains an illusive challenge and one that, as an industry, we have to admit we are very poor at answering.

Perhaps the first problem is that the question itself is a fool’s errand. The industry can be no better at forecasting the value of an aircraft over time than we as humans are at forecasting anything else over time. Most owners understand uncertainty and volatility. They face the same issues in their business. They don’t expect a crystal ball. So, when they ask for a forecast of residual value, what they are really asking for is some level of guidance based on historical data.

And that’s where the industry runs into a problem with business jets. Simply stated: their is no historical data to work from.

Ok, that’s not entirely true. Many people have some data. OEM’s, aircraft brokers and banks all track certain information over varying periods of time with varying degrees of coverage and accuracy. So we have small subsets of data in a zillion different places. Privacy and confidentiality concerns stand in the way of any formalized approach to data collection. While our industry may have effective and pervasive “human intelligence” about new and used aircraft prices (the grapevine), almost all actual prices are considered confidential. While routinely violated, almost every aircraft purchase agreement says so.

To develop residual forecasting models, the industry needs Big Data about the past; and this means a comprehensive data set covering the broadest possible time period, which includes the broadest possible collection of new and pre-owned transaction prices. Even better would be accurate transaction prices.

Only then can meaningful and valid statistical analysis be performed. The type of analysis which provides an understanding of how our markets correlate with each other; with external indices; and, with overall economic conditions. These are the building blocks of modeling. Think of it this way: folks who try and forecast the stock market have perfectly accurate historical data and still can’t model it with much precision. Compared to them, we are IMC with no instruments.

Let’s dream big for a moment. Perhaps there’s a way around this. Perhaps, as an industry, we can create a sort of UN for data collection. A trusted intermediary to collect information directly from the sources, keep it in a lockbox, and make sanitized summaries available. NARA, NAFA, GAMA and even NBAA could all bring their constituent groups together on this idea. Remember, we would all benefit from a better understanding of this subject.

Back in the real world, the question is- what can we do about forecasting future values given the information we have? Enter the dusty set of old Bluebook and Vref price guides in the file cabinet. These resources serve as a historical proxy in lieu of real data. Whatever their inaccuracies, they provide a suitable approximation for use with certain methods of analysis. As for the analysis itself, we will talk about IAG’s approach in an upcoming edition of theJetWatch.

Finally; a point about expectations. The cosmos will never permit forecasting the future with a high degree of precision, so we need to live with ranges and probabilities. But that’s better than nothing. As theJetWatch staff golf pro reminds us – stop worrying about being in the middle of the fairway, when your main goal is to stay out of the woods!