Felix Salmon wrote a post recently on the economics of driving for Uber. Following up on Uber’s recent claims that the “median small business income with uberX” in NYC is more than $90,766, Felix rightly asked Uber to clarify how they arrived at those numbers. In response, Uber sent over the following chart, laying out the annual costs of driving an uberX for 40 hours per week.
Ostensibly, we should be able to subtract $15,080 from $90,766, and arrive at an estimated net income of $75,686. This is exactly what Felix does, noting along the way that these numbers represent a “good-faith” estimate on Uber’s part and lead to the entirely intuitive conclusion that being a self-employed uberX driver is a pretty good gig, especially when compared with driving a Yellow Cab.1 Following some pushback from the Internets, Felix wrote a follow-up post on Uber’s claims, in which he dug deeper and emerged with a greater degree of skepticism. I’d like to continue that line of inquiry in even greater depth.
In the following analysis, I’m going to focus on the unit economics of being a full-time uberX driver in New York City. My goal is not to value the company, but rather to examine whether driving for Uber is as lucrative as Uber’s PR would indicate.2 That said, drivers are Uber’s only productive assets, and they will continue to produce revenue for Uber only if it makes economic sense for them to do so. If the unit economics of driving for Uber don’t work, then any claim to future dominance should be met with skepticism.
A full-time job
Felix asked Uber to come up with an estimate for miles traveled over a year’s worth of 40 hour work weeks. In response, Uber sent data for a driver who covers 40,000 miles per year. Assuming two weeks vacation — what’s the point of setting your own schedule if you can’t take vacation? — that means our hypothetical driver is covering 40,000 miles in 2,000 hours, for an average speed of 20 mph. Meanwhile, the average speed of Manhattan traffic is barely 10 mph, though taxis do a bit better than that, averaging about 11.5 mph.3 There are a few ways to reconcile these numbers:
- Uber defines an NYC work-week as 70-80 hours
- Uber defines a “small business” as a car owner, who may drive their own car, but more likely rents it to drivers
Personally, I think the second bullet makes the most sense. A quick check on Craigslist will reveal a number of postings for car owners looking for drivers. Given that Uber’s raison d’être is to increase asset utilization, I assume they fully support an asset-efficient business model. But of course, that’s not the same thing as being an owner-driver making $91k on 40 hours of work a week, which is the claim being made here. Therefore, for the purposes of this analysis, I’m going to assume that the numbers Uber promotes as “potential earnings” are intended to represent the income for a single driver-owner.
Gross fare revenue
Let’s assume that uberX drivers move at similar speeds to every other cab in Manhattan. Under that assumption, a driver would have to work 69.6 hours per week to hit his 40,000 mile target, which yields a gross fares estimate of $26.10 per hour.4
According to TLC data, average hourly revenues for yellow cabs in NYC range from a low of $26 on Wednesday mornings to a high of $44 on Thursday nights. That means that, if we take Uber’s 40,000 mile number as a given, then an NYC Uber driver grosses about as much in his average hour as a yellow cab grosses in his worst hour.
We can also use this information to make some inferences about utilization, i.e., the amount of time a cab spends with a paying customer inside. Intuitively, Uber’s app should cut down on the amount of time drivers spend searching for fares, thus increasing their utilization and, by extension, their hourly earnings. If we assume that yellow cabs and uberX’s are roughly substitutable, then it’s fair to assume that the average uberX trip is roughly similar to the average yellow cab trip. According to the Factbook, the average yellow cab trip runs 2.6 miles, takes 13.6 minutes, and spends 53% of that time stopped in traffic.5 Plugging these parameters into uberX’s published rates yields an average gross fare of $19.19.
Looking at these calculations, we can infer that an average uberX fare grosses $1.41 per minute. Multiplying that number by 60, we find that if an uberX were 100% utilized by average fares for an hour, it could gross as much as $84.60. By dividing the average gross fares of $26.10 (calculated above) into $84.60, we reach an estimated average utilization of 31%. Compared with yellow cab utilization of ~50%6, that doesn’t say a ton for Uber’s demand management system. However, I don’t actually believe the number is this bad. More likely, the utilization figure is depressed by the amount of time drivers spend “multihoming,” that is, leaving the Uber app open, but picking up fares either on the street or through a competitor’s app. For drivers, the name of the game is utilization; you want to make every minute as profitable as possible. By using multiple hail networks, the driver increases his chances of finding a fare close to his current location. The less time spent driving to a fare, the more time spent making money.
Remember that gross fares are not net fares. After Uber’s 20-30% cut, uberX drivers in NYC can expect to net around $19.58 per hour. And then, of course, you have to factor in costs. Since we’re talking about a full-time, 70-hour a week job here, I think it’s fair to classify all vehicle operating costs as business expenses. However, I don’t think that Uber’s representation of operating costs is as fair as Felix thinks. While they’re reasonable for a 15k/year personal car, they don’t add up for a vehicle that’s getting 40k commercial miles per year, nor do they include the costs of actually buying the car. But if we dig into Uber’s much heralded financing plans launched in late 2013, then perhaps we can get a better sense of the actual costs at play.
First, it’s worth noting that at least one of Uber’s financing partners (Santander) doesn’t offer loans to uberX drivers without good credit; instead, it offers what is effectively a “full purchase” lease, where the lessor can purchase the vehicle at the end of the 4-year lease term for $1. Let’s go out on a limb and assume that the median full-time uberX driver doesn’t have fantastic credit and would rather forego the credit check. In that case, our Camry driver will be paying at least $159 per week (before taxes) on his lease, which works out to $689/month, or $8,268 per year over the four-year lease term, plus a $2,000 upfront payment that’s half capital cost reduction and half security deposit.7
When you add it all up, if you take Uber’s financing option, you’re essentially paying $33,072 ($8,268 x 4) for a car you could buy for $24,750, which works out to an equivalent APR of 15%.8 Meanwhile, a trip to bankrate.com will reveal that today’s market rate for a 48-month loan is under 3%. At least you never have to worry about a late payment; under Uber’s plan Santander will deduct your lease payments from your weekly payouts.
Now that we know the monthly payments ($689), the expected mileage (40k, per both Uber’s communication to Salmon and the Santander microsite) and the lease term (4 years), we can start to see the true cost of being a full-time uberX driver. Below is a Kelly Blue Book estimate for the total cost of owning a 2014 Camry Hybrid LE driven 40,000 miles per year over a 4-year lease:
[Edit: It’s been pointed out to me that I erred in calculating depreciation expense. What KBB lists for depreciation in Year 1 is tax (rather than economic) depreciation, and it’s inappropriate to expense both the payment and an allowance for economic depreciation. In other words, I double-dipped. Instead of $16,909, first-year operating costs should be closer to $6,754. As a result, I understated net income in Year 1 by about $2.63 per hour, and $2.92 thereafter.]
In Year 1, this vehicle could be expected to cost its driver-lessor
$16,909 $6,754 in operating costs, plus $8,268 in lease payments, plus a $2,000 upfront payment, for a total hit of $27,177 $18,022. Over a year of 70-hour weeks, that works out to around or $7.81 $5.18 per hour. This means that, after expenses, a full-time uberX driver in NYC, driving 70-hour weeks in a 2014 Toyota Camry Hybrid leased under Uber’s promoted financing plan, can expect to bring in a pre-tax net income of $19.58 – $7.81 $5.18 = $11.77 $14.40 per hour ( $40,959 $50,112 annually) in their first year driving for Uber, and around $14.55 $16.36 per hour ( $50,634 $56,934 annually) thereafter.
I should point out that the insurance costs here are surely low — although Uber encourages its uberX drivers to find “standard vehicle insurance” as opposed to livery insurance, the coverages required are nearly impossible to find, especially for someone with poor or no credit working 70 hours a week as a cab driver. Meanwhile, taxi insurance in NYC can run $7,000 – 10,000 per year, which would knock our driver’s net income to an abysmal
$9.47 $12.39 per hour in Year 1 ( $32,956 $43,117) and $12.25 $15.17 per hour thereafter ( $42.630 $52,792).
Once we’ve actually taken all of our operating costs into account, it turns out that our uberX driver is actually middle of the pack, with earnings between the 25th and 75th percentile of his peers. Which, in normal times, is exactly where we’d expect a single-dispatch taxi driver to end up.9
The story of the for-hire vehicle industry (FHV) has been one long march toward commoditization, with drivers always getting the short end of an increasingly smaller stick. Since the early 1900s, taxi drivers have morphed from employees (prior to deregulation) to independent contractor-lessors (following deregulation) to sole proprietors (following Uber).10 With each transformation, the industry has shifted profits away from the drivers while pushing onto them a greater share of costs and liabilities. This is why drivers tend to push for medallion systems: because only by capping the supply of vehicles can full-time drivers be assured a living wage. Market equilibrium in a wholly deregulated taxi industry comes only when the desperate have driven out the good. The result is something that few cities would prefer to the imperfect gnarl that is a regulated taxi market.
I recognize that it’s not exactly in fashion to side with regulation over laissez faire, and in many instances, I wouldn’t. There are limits to markets, however, and the taxi industry presents an especially vivid example of that dynamic. We don’t need to have this discussion in the abstract — we actually have hard data. The US went through an era of taxi deregulation in the 1970s, only to follow it with an era of re-regulation. From transport scholar Paul Dempsey’s, Taxi Industry Regulation, Deregulation, and Reregulation: the Paradox of Market Failure (pg. 102):
[W]e need not rely on the theoretical assumptions of what unlimited entry will produce. We have empirical results which we can assess to determine what deregulation of the taxicab industry has produced.
Before 1983, some twenty-one cities deregulated taxicabs in whole or part. The experiences of these cities reveal that taxicab deregulation resulted in:
1. A significant increase in new entry;
2. A decline in operational efficiency and productivity;
3. An increase in highway congestion, energy consumption and environmental pollution;
4. An increase in rates;
5. A decline in driver income;
6. A deterioration in service; and
7. Little or no improvement in administrative costs.
I recommend reading the whole paper, then reading this one from the Journal of Transport Economics and Policy (“In every city where the taxicab industry has been deregulated, there has been a significant decline in taxicab productivity as measured by the number of daily trips per cab and trips per shift.”) and finally this one from Price Waterhouse (“the effects of taxi industry deregulation have ranged from benign to adverse”). Theoretical models are important, but they should be shaped by data whenever possible.
I can’t think of any market with more distorted supply and demand curves than the taxi industry today. Billions of dollars are pouring into this industry, and they’re not going to capital investments like R&D or PP&E; instead, they’re covering massive incentive expenses for both drivers and passengers. You could look at what’s happening and plausibly call it a wealth transfer from investors to consumers, and you’d probably be more correct than if you had called it a well-functioning market. Knowing that, I’m not sure how you can take any number reported out of this industry at face value, let alone extrapolate future trends off of them.
What we’re seeing is the very definition of an artificial market environment subsidized by huge infusions of outside capital. But despite the obvious distortionary effects of that capital, we’re treating these trends like they’re secular. Massively profitable cash flow businesses don’t need billion dollar capital infusions every twelve months. Strong brands with differentiated products don’t engage in race-to-the-bottom price wars. And businesses with great unit economics don’t need to increase their unit sales by 5x to grow revenues by 2x.11
“Uber’s brand will support high margins” was a plausible story when the company was focused on the luxury segment, but clearly that focus has shifted to the lower end of the market. If Uber raised the price of uberX by 25%, do you honestly believe that its customers wouldn’t leave in droves? If drivers thought they could make more money on another dispatch network, do you honestly believe that they wouldn’t switch? Until a mass market taxi company demonstrates that it can raise fares over a sustained period without suffering an offsetting reduction in demand, I don’t see how it’s reasonable to believe that auto transport is any less a commodity than air travel. And yet, that’s exactly the assumption we’re making.
Ultimately, the most anyone can do is make reasonable assumptions and think rigorously, and I’ve tried to do that here. I’m sure I’m wrong about many things in this post. But from where I’m sitting, the math just doesn’t work.12
It would be easy to look at this post and say I don’t get it. That I’m anti-innovation and a known Uber bear and I can’t hear Jimi. I don’t really have a good response to that. All I can say is, when I do the math and make reasonable assumptions based on available research, I don’t see where the excess profits are supposed to come from. I don’t mean to reason defensively — quite the opposite, in fact — but the numbers and industry dynamics lead me to the same conclusions as before. You are, as always, free to disagree.
- I should point out that Felix is wrong to assume that most cab drivers are employees. In fact, most are independent contractors. Indeed, the taxi industry was decades ahead of Uber in realizing the benefits of shifting operating costs and liabilities as far away from the profit-taking organization as possible. [↩]
- If you are interested in a rigorous valuation, I’d suggest you read through Aswath Damodaran’s excellent analysis. [↩]
- 2014 Taxicab Factbook, pg. 7, fn. 1. [↩]
- 40k miles per year / 11.5 miles per hour / 50 weeks = 69.6 hours per week. $90,766 / (69.6 hours per week x 50 weeks) = $26.10 per hour. [↩]
- See this spreadsheet for the reasoning behind my stopped-time assumption. [↩]
- Factbook, pg. 8. [↩]
- See Santander’s FAQ. Funny enough, these awful terms are kind of a deal when compared with the terms laid out in the financing information sheet given out to drivers in Atlanta. [↩]
- You can work this out easily using Excel’s RATE function. If nper = 48, pmt = $689, and pv = -24,750, then RATE(nper, pmt, pv) returns a monthly interest rate of 1.25%. Multiply that by 12 and you’ve got your APR. [↩]
- This all assumes, of course, that Uber doesn’t further reduce the price of fares or raise its rake, or boot the driver from its system without process. [↩]
- If you’re curious about the history and evolution of the taxi industry, I suggest you pick up a copy of Taxi! Urban Economies and Social and Transport Impacts of Taxicabs. It’s a fantastic read, rich with data and historical detail. It will also disabuse you of a number of facile narratives that have dominated the conversation recently. [↩]
- This statement alone would set off alarm bells in a normal environment. [↩]
- If my math is wrong, please tell me! I strongly believe that being proven wrong is often the shortest path to being right. [↩]