Tag Archives: correlation

Turboprop market vs. oil price (ATR figures 2017 update)

Few days ago, the Toulouse-based aircraft manufacturer ATR (Avions de Transport Régional) published a press release [PDF, 139 kB] reporting some of its numbers for the year 2017 (being a private company, owned by Airbus and Leonardo, it does not publish a complete financial annual report). Some of the key figures were:

  • Revenues: 1.8bn$.
  • 80 deliveries (including 2 second hand aircraft).
  • Orders: 113 firm plus 40 options (112 of the orders for its ATR-72).

With this post I just wanted to log the latest data and update the graphic in which I compare ATR yearly deliveries profile with World GPD growth and most importantly oil price.

ATR figures 2017

ATR deliveries vs. GDP growth and oil price (2017 update).

It is interesting to note the drop of the oil price from around 90$ to below 50$ since 2015. ATR deliveries correlated well with oil price with a lag of a few years time. The correlation up to date continues to be quite high.

So far, through 2017 aircraft production has kept up around 80 deliveries a year. In 2017, the book-to-bill was 1.45 (with the above-mentioned 113 firm orders), so ATR should be able to cope with high production for another couple of years.

We will see later on whether the oil price raises again, whether the correlation deliveries/oil price holds or breaks, and whether ATR manages to keep up production in response to the market.

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Turboprop market vs. oil price (ATR figures 2014 update)

Few weeks ago, the Toulouse-based aircraft manufacturer ATR (Avions de Transport Régional) published a press release reporting some of its numbers for the year 2014 (being a private company, owned by Airbus and Alenia, it does not publish a complete financial annual report). Some of the key figures were:

  • Revenues increased 10% to 1.8bn$.
  • A new record of 83 deliveries (+12%).
  • A new record of sales with 160 firm aircraft orders (plus 120 options). (1)
  • A record backlog at year-end with 280 firm aircraft in the order book.

About 4 years ago, I wrote a post, “Turboprops market different dynamic“, in which I discussed:

[…] how civil turboprop market is unrelated to the larger and more known turbofan civil aircraft market and how its dynamics are completely unrelated to World GDP growth and thus world air traffic growth. […]

When calculating correlation between the different variables, I discovered that the correlation between GDP and deliveries is rather low, despite of the time lag applied (be it 2, 3, 4 years…). However I found that the oil prices and deliveries did correlate very well with a lag of 5-6 years, yielding coefficients of 0.55-.65, which are rather high.

I wanted to update the calculations I made then and last year, with the information of the 2014 exercise.

ATR deliveries vs. GDP growth and oil price (2014 update).

ATR deliveries vs. GDP growth and oil price (2014 update).

With the last years’ data, correlations are similar:

  • Between oil prices and deliveries: high, above 0.54 from 1 year time lag, increasing through 6 years time lag (when it reaches a maximum of 0.82).
  • Between GDP growth and deliveries: low, not more than 0.34, and negative correlations up from 1 to 5 years time lag.

If there was causality, we could infer that the from the moment that oil prices are computed, till they are taken into regional airlines’ models, the fleet planners identify the need for new turboprops, the case is approved by airlines’ management, discussions start with ATR, negotiations are closed between the airline and the manufacturer, the aircraft are built and delivered to the airline… it takes about 6 years. (2)

This year the prices of oil have abruptly decreased in the last quarter:

Oil prices drop Q4 2014.

Oil prices drop Q4 2014.

However, this large drop is not yet fully noticed in the comparison made before as the historical database I use (here) only reflects prices up to the end of November and thus the 2014 average is still 89$ vs. 92.4$ in 2013. Even so, taking into account the figures from December (~55$) the year average will drop only to about 86$, not changing much the result.

It would be interesting though to see if oil prices stay low (50-60$) for the full 2015 year. If so, we could check whether the correlation stands and ATR starts to notice it in the form of lower orders (more cancellations?) and this is translated into lower amount of deliveries in about 3 years time (2018?).

(1) Some 18 cancellations that took place in 2014 go untold in the press release, though they are easily deduced from the information of orders, and backlog from 2014 and 2013.

(2) About 3 of those 6 years are consumed from placing the firm order to getting the aircraft delivered, as we can see by the current figures of backlog (280 a/c) and yearly deliveries (83 a/c).

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Turboprop market vs. oil price (ATR figures 2013 update)

Few weeks ago, the Toulouse-based aircraft manufacturer ATR (Avions de Transport Régional) published a press release reporting some of its numbers from 2013 exercise (being a private company, owned by Airbus and Alenia, it does not publish full financial annual report). Some of the key figures were:

  • Revenues increased 13% to 1.63bn$.
  • A new record of 74 deliveries (+16%).
  • Sales of a total of 195 aircraft (89 firm orders and 106 options). (1)
  • Backlog at year-end of 221 firm aircraft orders.

About 3 years ago, I wrote a post, “Turboprops market different dynamic“, in which I discussed:

[…] how civil turboprop market is unrelated to the larger and more known turbofan civil aircraft market and how its dynamics are completely unrelated to World GDP growth and thus world air traffic growth. […]

When calculating correlation between the different variables, I discovered that the correlation between GDP and deliveries is rather low, despite of the time lag applied (be it 2, 3, 4 years…). However I found that the oil prices and deliveries did correlate very well with a lag of 5-6 years, yielding coefficients of 0.55-.65, which are rather high.

I wanted to update the calculations I made then with the information of the last years.

ATR deliveries vs. GDP growth and oil price (2013 update).

ATR deliveries vs. GDP growth and oil price (2013 update).

With the last years’ data, correlations are similar:

  • Between oil prices and deliveries: high, above 0.54 from 1 year time lag, increasing through 6 years time lag (when it reaches a maximum of 0.77).
  • Between GDP growth and deliveries: low, not more than 0.26, and negative correlations up from 1 to 4 years time lag.

If there was causality, we could infer that the from the moment that oil prices are computed, till they are taken into regional airlines’ models, the fleet planners identify the need for new turboprops, the case is approved by airlines’ management, discussions start with ATR, negotiations are closed between the airline and the manufacturer, the aircraft are built and delivered to the airline… it takes about 6 years. (2)

(1) 15 cancellations (4 ATR-42 & 11 ATR-72) that took place in 2013 go untold in the press release, though they are easily deduced comparing orders and backlogs for 2013 and 2012.

(2) About 3 of those 6 years are consumed from placing the firm order to getting the aircraft delivered, as we can see by the current figures of backlog (221 a/c) and yearly deliveries (74 a/c).

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Turboprops market different dynamic

In the last post I discussed about the dynamics of commercial aircraft orders and its correlation with air traffic growth and GDP growth.

In the previous post, I had discussed about turboprops. Today, I want to connect the two dots in a particular way.

I want to show how civil turboprop market is unrelated to the larger and more known turbofan civil aircraft market and how its dynamics are completely unrelated to World GDP growth and thus world air traffic growth.

For this purpose I studied the numbers of ATR (using the info available in its website from yearly news releases discussing results).  I proceeded in the same way as before, analysing the correlation between the different variables.

In order to take a larger time span, I used ATR deliveries instead of orders, as I found a larger data set for deliveries (obviously aircraft delivered were previously ordered, lag in between is not that obvious, today’s backlog is about 3 years production).

In the following graphic I plotted ATR deliveries, GDP growth and oil price:

ATR deliveries vs. GDP growth and oil price.

When calculating correlation between the different variables, I discovered that the correlation between GDP and deliveries is rather low, despite of the time lag applied (be it 2, 3, 4 years…). However I found that the oil prices and deliveries did correlate very well with a lag of 5-6 years, yielding coefficients of 0.55-.65, which are rather high.

This different behaviour of the turboprop market compared to the bigger turbofan market could be explained by the oil price forecasts that airlines shall make each time the oil price goes up.

Again, I can imagine some C-suite executive of a regional airline demanding an oil price forecast/report with which to substantiate his gut-feeling that prices will continue to go up and thus turboprops,  which are more fuel-efficient than turbofans, will be best suited for their short-haul routes.

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Air traffic growth vs. aircraft orders

Taking the topic of the headline of this post I want to share some reflections on the commercial aircraft market.

The first is how closely air traffic growth is correlated to world economic growth. This sentence and the following graphic are taken directly from the Global Market Forecast [PDF, 7.9MB] produced by colleagues at Airbus.

Air traffic growth vs GDP growth (source: Airbus).

You may see in the graphic the correlation (correlation coefficient above 0.7) and how the air traffic growth is however much more volatile than the economic growth. This is very intuitive. The better the economic situation the more business trips, family visits and holiday trips will take place. Nevertheless Airbus explains that in some situations and regions this is not enough to forecast traffic and thus they produce hybrid models.

Then, I wondered: how do airlines translate this growth in traffic into airplane orders?

I made some numbers and played with them. I gathered aircraft orders for both Boeing and Airbus in the last ~20 years, plus air traffic and GDP growth over the same period of time. Then, I tried to connect one with another and see how best they would correlate with each other. Even though correlation does not imply causation, it may indicate existence of such causal relations that it’s why I searched for such results.

Here I plotted GDP growth (IMF), traffic growth (ICAO) and aircraft orders:

Aircraft orders vs. air traffic and GDP growth.

One could expect that airlines, after collecting first hand data of traffic growth plus the aggregate demand from industry sources (IATA, ICAO) and after applying their complex planning models would order aircraft from manufacturers. Thus, a correlation might be expected between traffic growth and aircraft orders. What we don’t know is whether airlines would place orders in the same year where the traffic growth actually takes place or there would be a lag (due to the airline analysis process, the negotiation with the manufacturer, arranging the financing, waiting for the next air show…).

The correlation results I got between these 2 variables are satisfactory though not that high. Matching data of the same year yields a 0.35 correlation coefficient. If however, we apply a 1-year lag in between air traffic growth data and orders the correlation is better, 0.44 (a lag of 2 years would worsen it down to 0.27 and so forth).

I found it curious that correlation between orders and GDP growth is much better! Matching data of the same year yielded a 0.61 correlation coefficient (which is rather high). A lag of a year would produce a still high 0.56 (2-year lag, 0.41; 3-year, 2.6…).

This was a striking result for me. After all, even though individual airlines do have complex models and experienced analysts behind them, taking the aggregate of the market, it seems that orders are placed less on data of traffic and more relying on data of economic growth, and rather soon, acting within the same year or a year later!

Who knows how the process within the airlines actually works… I can imagine thoroughly thought and thick studies coming from planning & analysis departments being put aside in the board room where one or two directors (more assertive than the average) convince the rest of the soundness of an operation based half in broad economic prospects (world GDP growth) and half in gut-feeling… wouldn’t surprise me much.

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