We live in a truly globalized economy, where an item of clothing made in Bangladesh and shipped from Ohio can arrive at our doorstep in Los Angeles within two days. The only way to facilitate this mind-bogglingly rapid on-demand economy is through a giant network of logistics companies that ship, track, and manage our precious new tee shirt at every step of it’s journey. For this network to remain intact, we need airlines. The Federal Aviation Administration reported that aviation accounted for more than 5% of American GDP in 2016, coming out to a staggering $1.6 trillion in economic activity. While this number may sound enormous, it understates the true influence of aviation. Aviation props up many other major sectors. On a national level, online shopping in 2019 accounted for approximately 601.75 billion dollars. On a local level, tourism in New York City accounted for 24 percent of all credit card sales at restaurants as well as 18 percent of all Visa transactions at retail stores. Without airplanes, the vehicles that moves both people and things around the country at rapid speeds, a large portion of this revenue vanishes.
So far, everything I’ve said is probably obvious. In fact, this whole article will be. There’s nothing groundbreaking or surprising about the necessity for aviation to fuel the global economy. The only thing I plan on doing today is emphasizing just how crucial air travel is. Using PyPlot and Yahoo’s Stock API (explained in this article), I created some quick graphs that show the disparity between the overall stock market and airline stocks as well as the sheer force with which coronavirus has ravaged the airline sector at large.
First, I graphed the year over year 2019 versus 2020 airport throughput data provided by the TSA. This data provides a clear view of just how shocking the coronavirus-induced airport closures have been. In 2019, an average of almost 2.5 million people per day passed through American airports. Over the same time frame in 2020, that average fell drastically, dipping to below 250,000 daily travelers at the peak of the pandemic. (One thing that is worthwhile to note is the consistency of local minima and maxima on this graph. These spikes and dips correspond with the days of the week that are the most and least popular for travel.)
While this graph is useful, I still don’t think that it displays the sheer scope of the crisis. Next, I looked at the percentage-wise year over year changes in daily passengers on airlines. As you can see on the graph below, these trends correlate almost identically with the green trendline for the 7 day moving average above. At the height of the crisis, air travel was down 95% from normal volume! This means that if you were to board a Boeing Dreamliner (not that I advise that, but that’s a different story entirely) with a 290 person capacity, you could expect to share the plane with just 14 other people.
Finally, I decided to look at the recovery charts for Delta and American airlines, two of the biggest air carriers in the United States. Here, I was expecting to find a disconnect between the stock price and the air travel data, based on the disconnect between the stock market and the economy at large. However, I found the opposite. Within the aviation sector, there is an extremely strong correlation between stock price and number of daily passengers, as illustrated below. As of now, I think that airline stocks are more representative of how coronavirus has halted the economy than the $SPY is.
Based on the 30 day moving average (shown in red), airline stocks have just begun recovering and (in the absence of a vaccine for coronavirus) continue their slow recovery for years. Of course, this is all obvious. Without aviation, the global economy is injured. The only (even remotely) novel thing in this article is the notion that the economy has been hurt more than we seem to realize. The global economy has not been stunted, but crippled. Airline data merely provides a barometer for the extent of the damage that has been inflicted. I believe that this barometer is more accurate than historic bellwethers stock indices such as the $SPY.