Economies of scale in homeless camp cleanups with some fishy results

Eric Fruits —  12 December 2018

“Our City has become a cesspool,” according Portland police union president, Daryl Turner. He was describing efforts to address the city’s large and growing homelessness crisis.

Portland Mayor Ted Wheeler defended the city’s approach, noting that every major city, “all the way up and down the west coast, in the Midwest, on the East Coast, and frankly, in virtually every large city in the world” has a problem with homelessness. Nevertheless, according to the Seattle Times, Portland is ranked among the 10 worst major cities in the U.S. for homelessness. Wheeler acknowledged, “the problem is getting worse.”

This week, the city’s Budget Office released a “performance report” for some of the city’s bureaus. One of the more eyepopping statistics is the number of homeless camps the city has cleaned up over the years.

PortlandHomelessCampCleanups

Keep in mind, Multnomah County reports there are 4,177 homeless residents in the entire county. But the city reports clearing more than 3,100 camps in one year. Clearly, the number of homeless in the city is much larger than reflected in the annual homeless counts.

The report makes a special note that, “As the number of clean‐ups has increased and program operations have stabilized, the total cost per clean‐up has decreased substantially as well.” Sounds like economies of scale.

Turns out, Budget Office’s simple graphic gives enough information to estimate the economies of scale in homeless camp cleanups. Yes, it’s kinda crappy data. (Could it really be the case that in two years in a row, the city cleaned up exactly the same number of camps at exactly the same cost?) Anyway data is data.

First we plot the total annual costs for cleanups. Of course it’s an awesome fit (R-squared of 0.97), but that’s what happens when you have three observations and two independent variables.

PortlandHomelessTC

Now that we have an estimate of the total cost function, we can plot the marginal cost curve (blue) and average cost curve (orange).

PortlandHomelessMCAC1

That looks like a textbook example of economies of scale: decreasing average cost. It also looks like a textbook example of natural monopoly: marginal cost lower than average cost over the relevant range of output.

What strikes me as curious is how low is the implied marginal cost of a homeless camp cleanup, as shown in the table below.

FY Camps TC AC MC
2014-15 139 $171,109 $1,231 $3,178
2015-16 139 $171,109 $1,231 $3,178
2016-17 571 $578,994 $1,014 $774
2017-18 3,122 $1,576,610 $505 $142

It is somewhat shocking that the marginal cost of an additional camp cleanup is only $142. The hourly wages for the cleanup crew alone would be way more than $142. Something seems fishy with the numbers the city is reporting.

My guess: The city is shifting some of the cleanup costs to other agencies, such as Multnomah County and/or the Oregon Department of Transportation. I also suspect the city is not fully accounting for the costs of the cleanups. And, I am almost certain the city is significantly under reporting how many homeless are living on Portland streets.

Eric Fruits

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Eric Fruits, Ph.D. is Chief Economist at the International Center for Law & Economics and Economics International Corp. He is the Oregon Association of Realtors Faculty Fellow at Portland State University. He has written peer-reviewed articles on initial public offerings (IPOs), the municipal bond market, real estate markets, and the formation and operation of cartels. His economic analysis has been widely cited and has been published in The Economist and the Wall Street Journal. Dr. Fruits is an antitrust expert who has written articles on price fixing and cartels for the top-tier Journal of Law and Economics. He has assisted in the review of several mergers including Sysco-US Foods, Exxon-Mobil, BP-Arco, and Nestle-Ralston. He has worked on many antitrust lawsuits, including Weyerhaeuser v. Ross-Simmons, a predatory bidding case that was ultimately decided by the United States Supreme Court. As an expert in statistics, he has provided expert opinions and testimony regarding market manipulation, real estate transactions, profit projections, agricultural commodities, and war crimes allegations. His expert testimony has been submitted to state courts, federal courts, and an international court.