Toilet Paper in a Pandemic

This probably isn’t the best use of my time right now,  but maybe there’s a teaching moment here.

In the face of the COVID19 pandemic, folks in the US (and apparently most developed nations) have gone on a toilet paper buying spree.  One result besides the appearance of empty shelves, has been a lot nasty commentary in social media and news media attacking people for alleged “hoarding” of TP. The comments have come complete with  all the cheap puns and childish humor talk of toilet paper invites. (I will probably fall prey to that too!)

In store after store, the shelves often appear empty and denuded of toilet paper. This is a rather sudden and unexpected development for most people accustomed to a first-world life where a fundamental fact of like is assumed to be: there will always be toilet paper.  People and pundits have proclaimed a shortage of toilet paper brought on by irrational “idiots”. Social judgements and pejoratives have been flying since.

Even economists are not exempt. Justin Wolfers has likened the toilet paper shortage to a classic run-on-the-bank (couldn’t resist the pun, eh, Justin?) which might be individually rational but becomes a systemic failure. Justin considered the possible need for a national strategic toilet paper reserve.

I’ve read several pyschologists speculate on the “meaning” and “underlying psychological needs” driving the “hoarding” of toilet paper. I’ve read that it’s a controllable first-world comfort when people are faced with a sudden, scary uncertainty. Maybe there’s a tiny bit of truth in that, but it’s not enough to IMO to move that much TP. Other psychologists have speculated that it’s herd behavior. Some people bought up some more TP than normal, so they did too. Soon the shelves were bare and panic has ensued. Again, maybe a little sliver of truth, but not enough.

I’m going to weigh in on the topic, too. I think I have a bit more experience with toilet paper than the average person and more so than the average economist. It’s not because of my diet. Not only am I an economist and things like “supply” and “demand” are my basic tools, but early in my career I was the business planner/strategist for a very large industrial distributor/wholesaler. A distributor that distributed – you guessed it – toilet paper.  A lot of it. We didn’t supply much to the retail channel. We supplied businesses, factories, restaurants, hospitals, schools, and hotels.  Thanks to us, the nether regions of millions of people from GM factories to Florida resorts were kept clean and hygienic. I learned a lot about the economics of toilet paper back then. I’m sure it’s changed some since, given the better inventory management tools available today, but the essence of analysis still holds.

I think what we’ve seen has been a fairly rational response, at least initially, and I don’t see any great toilet paper crisis of 2020.  Yes, there has been some individual hoarding behavior, but probably a lot less than people think. What I see is a sudden shock to one of the most incredibly stable supply chains around. You see, there really isn’t any toilet paper inventory as you think of it.  Let me explain some of the economics of getting dried squares of wood pulp from a mill to your butt without discomfort.

TP-nomics: More than you ever wanted to know

Consumption drives the demand toilet paper.  Even in a crisis, there is not really any speculative value to toilet paper, nor is there any value to just owning a bunch of it. There is no ongoing use value either. Use two squares, and it’s done. It’s not like paintings which give ongoing value just for having them. It’s not a good store of value like cash, or gold, or bonds. It’s not a capital asset like a house, furniture, or a car.  It’s a single use value.  True, the perceived use value is high (at least in non-bidet using developed countries), but it’s very utilitarian. It doesn’t even bring social status, despite all the Charmin advertising.

I can tell you this from having analyzed and modeled the consumption and demand for toilet paper all those many years ago. It’s stable. Rock stable. Easy to forecast. If you know how many butts you’re dealing with, you can predict the consumption. That’s it. (and no, local cuisine or tastes don’t matter). People x days = TP needed.

The second fact of TP economics is that there’s a giant distributional mismatch. It’s produced in vast quantities in a very small number of places (mills) but consumed in a mind-boggling number of very specific locations. There are two in my house alone. When the need for it arises, the inventory MUST be in each location. When I want TP in the downstairs bath, I’m going to be really annoyed if it’s not there and I have to go source it from the upstairs bath or the basement pantry. I’ll be even more annoyed and greatly discomfited if I have to go to the store before I can use the toilet. Know what I mean?

In contrast, toilet paper is produced in a small number of places called mills in very, very large quantities on very, very large machines. So while we might indeed know how much TP is used each day – and that’s pretty much how much TP will be produced each day – we still have a problem. We produce just enough each day, but it’s in giant quantities in a few places when what we really want is a few squares in billions of places.

The third fact about TP economics, is that despite whatever its use value is, the dollar value per cubic foot of space it occupies is very low. It’s bulky. That means for a store or distributor it takes up a LOT of shelf space but doesn’t generate that much sales revenue or profit margin compared to other higher-value, smaller items.  At home, you only keep a roll or three in the bathroom. Nobody builds a bathroom cabinet to accommodate the giant Costco carton. For the store, the only way to survive those economics is to turn-over the inventory rapidly. That means that relative to demand, there’s actually very little in inventory. The large bulk makes it look plentiful to the consumer, but it’s not really. It’s simply being restocked, re-ordered, and replenished faster than just about any item in the store.

So how does our vast national TP distribution system work? It’s a network of very high turnover inventory locations, each one serving to “break bulk” in the distribution from mill to your butt.  The mill produces today and puts it on trucks or rail cars immediately and ships it out.  As soon as the truck/trains can get to the distribution centers (like the ones my ex-employer owned), it’s unloaded. A train car load is split up and becomes stacks of pallets or stacks of cases but they don’t sit still. That inventory is turned over very fast -meaning the cartons are loaded onto trucks and delivered to stores, factories, hospitals, and smaller wholesalers. Even back in my day 40 years ago, we emptied and shipped out that whole rail car in less than week. I wouldn’t be surprised if these days, turnover in some distribution centers could be measured in hours.

There really isn’t any toilet paper buffer inventory anywhere. As a nation, we haven’t really had a reserve of TP to buffer fluctuations in demand or supply – because we don’t need it.  Forests keep making wood fiber at about the same rate every day. People keep wiping their butts at the same rate everyday. What appears to be inventory is only temporary spots of relocated stuff that we turnover as fast as a possible. We have just-in-time production.

To recap:
Made in mill by train load –> whse in cases/pallets –.>store in multipacks –> home by carton–> bathroom cabinet by the extra 1-2 rolls –>dispenser roll

As soon as the minimum viable quantity runs out at each stage, we replenish. It’s a TP flow, not a TP inventory.  In reality, the slowest moving inventory is at the household.  Most households tend to buy one to a few weeks worth of TP at a time. They don’t want to waste space storing more. Assuming they don’t wait till they totally run out, that means they may have, on average, let’s say 10 days worth of TP on hand. When it gets low, they buy more. The grocery or big box where they shop knows that thousands of customers are doing the same predictable thing and the store only stocks enough for maybe 2-3 days worth of sales in inventory, maybe even less, knowing they’ll get more shipments.  The shelves always look nicely stocked with TP, but it’s all fresh, new stuff – unlike that jar of pickles you bought that was actually produced a year ago and been sitting in the store ever since.

So What Happened?

Everything is fine, until the Centers for Disease Control or other public health authorities try to gently prod people to “prepare” for possible isolation and quarantine because of COVID19.  It’s rational and it’s needed. The point of the isolation, social distancing, and quarantines is to minimize social contact. That means being prepared to go awhile without going to the store.  A necessary implication is that everybody’s household supply of TP is inadequate. If they typically run a 10 day supply on average, they need to temporarily increase purchases to actually create what they haven’t had before: a buffer stock.  So people started buying more. Rationally buying more.

Buying a buffer stock is only a temporary increase in demand.  Once you have your buffer, you go back to buying just enough to match usage, keeping the buffer stock in place. You might think that having households add some buffer stock shouldn’t be a big deal, but it was – because that’s how fast TP inventory turns over.

Initially the guidance late last February was for households most at risk to prepare (buy buffer stock) and two weeks was suggested.  But the pandemic has spread faster than most people expected. We now know from Italy’s experience and China’s that extremely broad based and possibly longer  isolation  – meaning minimizing trips to store – is needed. So it’s been an unprecedented and unexpected bump up in purchasing.

But it’s temporary. It  may take weeks for the production chain to catch up, but  purchasing will slow down too. Mills will ratchet up production some.  Nobody is going to truly hoard TP. Contrary to Justin Wolfers’ analysis, TP isn’t like cash. People can keep hoarding cash without limit. TP has some physical limits. Remember it’s high bulk/low value. Where would they put it all?

The dynamics on some other products is a little different. But even with something like hand sanitizer, where the shortages reflect a large sudden increase in consumption and demand, I expect part of the sudden shortage is because we generally have a high-turnover product distribution system. In hand sanitizer, eliminating the shortages depends largely on the ability of manufacturers to switch production facilities away from other products and into more sanitizer production. I expect that to be feasible, but I don’t really know that industry well enough to predict how soon it will restore equilibrium.

There are products in an apparent irrational short supply due to hoarding/panic behavior. I attribute a lot of that to Americans’ fascination with zombie apocalypse movies.

But toilet paper?  It’s a temporary shock to a stable supply chain.

SO relax. Wash your hands and stop being so nasty and judgemental of people.   If you’re going to criticize people, try criticizing them for standing so close in line or not covering their cough.

 

 

What’s the LMS Worth?

Herein, against my better judgement, I wade into the Great Instructure social media wars of 2019.  Last week, Instructure Inc., the publicly traded (NYSE: INST) company  announced it had agreed to go private and sell itself to private equity firm Thoma Bravo.  For people who teach in higher education this is big news. Instructure, is the current name for the company founded in 2008 that created and sells the Canvas LMS. Canvas in the last decade has toppled the previous king-of-the-LMS’s, Blackboard. Canvas is now widely reported to have largest market share of higher ed LMS market at least in North America. Moodle, the open source system, appears to dominate outside North America.

The announcement triggered a great deal of, let’s call it discussion, on social media, particularly Twitter. A lot of has gotten nasty and heated.  On the surface, the discussion seems to be about questions regarding what Instructure (or Canvas, or the data Instructure has collected) is “worth”.  Specifically, is it worth the $2billion Thoma Bravo has valued it at and why would TB pay that?

Underlying the valuation question though, is the real concern.  Can we discern the plans and future for Canvas (and thereby schools, instructors, students, the higher ed system, pedagogy, etc) from this transaction?  There’s roughly two camps. Both camps seem to think $2 billion is a big number.  I don’t but I’ll explain that later. One camp seems to be arguing that the $2 billion is perfectly justified as a valuation for Canvas as it is now and as an ongoing successful business and therefore there’s nothing to be concerned about here, nothing to see, just move along.  The other camp is seems to see $2 billion as a very big number and a clear indicator that Instructure’s new/future overlords will be monetizing the (relatively) massive database of user/student interactions (Instructure’s own claim as to it’s massiveness) and therefore putting students/faculty at risk from nefarious surveillance and profiling via AI (artificial intelligence and algorithms).

What I want to do is clarify some mistaken ideas/concepts that I see a lot of my education friends (and not so friends) arguing.  What’s been argued, by both camps at times, is not good economics or well informed finance. I’m not going to name folks here nor call out any one in particular. That’s not my intent. I’m hoping to clarify some thinking.

What’s a company worth?

Both camps seem to be arguing the “worth” (in precise economic/finance technical terms it is the “valuation”) of the company using the wrong theory or models of how valuation/worth is established.  The implicit model being used by all is familiar in economic/finance theory. It’s the idea that the current value of an investment (i.e. the purchase price of the company) should somehow be justified as expected present value of the future cash flows of the company from doing business.   That’s understandable. It’s a decent way to start evaluation of investment decisions – particularly inside companies when they decide to invest in something like a new machine or an expansion. It’s not the only consideration. There’s strategic considerations too.

So as an example  we’ve heard arguments that Instructure has been growing, generates cash, and has margins of 70%, so the value is just reasonable and therefore there’s nothing for the education community to worry about.

On the other hand, some have essentially argued that the only reason private  equity would pay this and/or the only pay they can recoup their money is if they monetize the data and that is presumed to lead to nefarious outcomes.

Let me clarify. The company was purchased, not the software and not an asset. The company. There is only one real-world way that valuations of companies are established: Will somebody pay a higher price later for this same company?  Let’s be very clear. This is a private equity deal. PE funds do not run companies. They do not sell things. They buy and sell companies. Period. That is all they do.  The only customers they have are the other PE firms or corporations or banks that they sell their  companies to.  Period. Thoma Bravo is not in the education or edtech business. They are in the buying-and-selling software companies business. That’s it. And no matter what they say about “being in it for the long run”, they aren’t. PE firms generally look to recoup and sell the business inside of 5 years, preferrably a lot sooner.

Conclusion #1:  No matter what any manager at Instructure or TB tells you, the needs of higher education are no longer the driving force.  The driving force is putting together a nice story supported by anecdotal financial data that leads to some future firm paying TB way more than $2b in a couple of years.

So is Instructure worth $2b?  We’ll find out if and when TB sells it. My guess is yes, TB will definitely flip this in a few years for substantial profit, assuming the bottom doesn’t totally drop out of the LMS market. (a small but real possibility).

Any argument you make about the deal based on business fundamentals is nonsense and fantasy. It’s part of popular econo-myths. Before you try to argue with me on that, do this one test: can your implied model of valuation explain why Uber went public at a valuation of ~$100 billion when Uber has never made money, is cash negative, and has no prospects of making money?  Can your model explain WeWork?  If you still don’t believe me, I suggest researching a little with Professor Scott Galloway (@profgalloway) about how valuations and funding happens real world these days.

What’s next?

What can we expect? Will the data be monetized? Will it be sold off piece-by-piece? Will Instructure/TB now invest heavily in all kinds of accelerated innovation? (Ok, I just threw that last question in for laughs. Of course they won’t. Real innovation costs money, time, and work). Really, we don’t know but there are some high probabilities based on the new capital structure and owners.

First off, there’s the possibility of some good old fashioned battle of the funds. We know very little about the specifics of the Instructure-TB deal. That’s how private equity works. It’s private. It’s not transparent. However, it seems that Instructure has 35 days (counting holidays) to find a better deal. Some other funds, hedge funds in this case, have taken positions in Instructure and they don’t think $2 is enough.  Typically the only people who come out ahead in these situations are lawyers, banks, and partners at the biggest funds. Little shareholders and the rest of the human race, not so much.

Once the deal closes, the priority at Instructure will be clear and it has two parts. First priority is get the money (cash) back to TB. I’ve heard it said on the Twitters that TB is putting out $2b of it’s money to buy Instructure. Again, we don’t know details for sure, but that’s almost certainly false. PE deals don’t work that way -especially with a company like Instructure that generates a healthy positive cash flow, is profitable, and has little debt (AFAIK).  Typically the playbook is that the PE firm buys the company largely with the target company’s own money.  In this scenario, the PE fund (TB in this case) puts up a relatively small amount of their own cash up front. They take a very short-term bridge loan from a friendly bank to get the total $2b in cash needed to buy out the shareholders. Once the deal closes, Instructure Inc. then is directed by their new owners, TB, to get a loan from a bank secured by the company’s assets. The proceeds of that loan are then paid as some kind of “special dividend” to the new owners to retire their loan. The PE fund has a small at-risk stake at that point. Management fees or sell-off of some assets in the first year can often pay back that cash. By maybe the end of the first year, the PE fund has gotten all it’s cash back and is playing with house money at that point. The target firm (Instructure in this case) is likely a lot more debt-laden than before with a lot less free cash flow.

At that point, we consider the other priority (don’t worry, these folks can multi-task so you’l hear this one right away). Namely, the big priority is to develop a story that leads to another big pocket putting out well more than $2 in a few years. Tell the story and tell it hard. Once they’re private, that becomes a bit easier. Less real data has to disclosed since they’re no longer public, so it’s easier to be selective with the data and put your own spin on it without fear of those pesky shareholder suits and the SEC (is anyone actually still afraid of the SEC?).

PE firms, like Venture Capitalists or hedge funds, aren’t looking for nice safe returns on their money. You and I would be ecstatic to get annual returns of 10-20% on our retirement funds. These funds look for more. They want multiples of the initial investment. So they’re looking for deep pocket buyers that can and will spend not $2b, but maybe $4b or $6b or more in just a couple years.  The PE fund wants a big exit and once the deal closes the only thought is the exit. Running the business is only important to the degree it helps tell a story that helps them exit.

Why would anyone pay that in a couple years from now?  Go back up to the section on “What’s it Worth?”.  There aren’t that many routes for exit for a PE firm:

  • do an IPO (initial public offering) -not likely here since they just took it private – obviously the public market wouldn’t value it high enough
  • find a bigger sucker PE fund – the story of why there are untold, untapped riches becomes critical
  • find a really big, deep pockets corporation that wants to add to it’s portfolio of businesses thinking this will add that magical “synergy” to its other businesses.  This is a possibility for Instructure, but the likely candidates are:
    • Google, FB, MSFT, Amazon, or Apple – the people trying to collect everybody’s data about everything in the hope of controlling/monetizing everything.  A story of the value of the data and the ability to predict the future lives of students could lead them to write a big check.
    • Textbook publishers – OK, there are only two left, Pearson and Cengage-McGraw Hill.  They could fall in love with a story of becoming the single source books-homework-courseware-LMS provider. In fact, they’ve tried the LMS before, but couldn’t do it themselves. They might choose to buy in. I’m not sure their pockets are deep enough though.
    • When all else fails, merge. Instructure could merged with Bb or Brightspace using some other PE fund’s money.

Whatever route leads to the exit, that’s the priority now at Instructure. In my opinion, all those avenues are fraught with very good reasons why colleges, professors, and students should be concerned.

Where will the money come from?

Another thing I read on the Twitter was the suggestion that Instructure is somehow impervious to the all-too-common private equity strategy of carve-it-up and sell off the parts.  Nonsense. That tweet came from somebody who purports to know and advocate for private equity but apparently, judging by their tweet, thinks Hollywood movies about whores are primers about finance.  I won’t deal with that aspect of the tweet other than to say that misogynistic tweet was all the evidence to convince me the dude has spent too much time in either tech or finance culture. Unfortunately, he’s not very skilled at the private equity portion. It takes little imagination to see how Instructure could be carved up and pieces sold off. I’m not saying they will. I’m just saying it’s a piece of cake. They’ve made 2-3 acquisitions in recent years. Reverse those and sell. They’ve already told everyone they’re positioning for a possible split-off. They’ve stated they’re separating the codebase for Bridge from Canvas.  Add to that, any business with multiple services, even when sold to the same segment, can be carved up. It doesn’t even take much imagination to do it. All it takes is a willing buyer. And all that takes is a plausible story about the riches at the end the rainbow.

Education is not THE Story Anymore

We in higher education have a tendency to think we’re important as a market. We’re not. For a long time, edtech companies and Silicon Valley have fed that fantasy. We think in terms of the edtech “market” and think it’s attractive. In truth, it’s largely failed to meet to meet SV expectations.  The LMS market is mature. Very mature. Most LMS’s are really based on 1990’s architectures ported to the Web. Canvas was an innovation in 2008 by being cloud based. But product wise, all of them are still largely the same conception of the product as 20+ yrs ago. Everybody who needs an LMS has one.

Yes, Instructure has had decent growth numbers (not sterling by SV standards, but good) in recent years. But finance is all about how are you going to top that going forward. Finance doesn’t look back. Truth is, Instructure or any of the LMS’s are going to have a hard time finding big new sources of revenue. There just isn’t much left in the higher ed budget for their stuff. Even the data analytics for learning part has failed to take off revenue wise. That’s why data mining for AI/Algorithms, monetizing the data to non-education folks, is so tempting.

Yes, any of these LMS firms, or publishers for that matter, could have had decent solid, satble, modestly profitable businesses that were mature. But that’s not how finance capitalism works.  Instructure isn’t an education tech company anymore. It’s just a software company and data processing service that happens to get its data from college and university students.  It will likely be managed that way.

FUD for thought?

I should put a word in about FUD.  Not sure if I introduced it into the conversations on Twitter or somebody else did. I didn’t realize the term was new to so many.  It’s an acronym that stands for Fear, Uncertainty, and Doubt.  The original usage that I’m familiar with dates back to software deals and business deals in the 90’s. FUD was something some firms tried to create in the market about their competitors. For example, back in those days, Microsoft was often accused of putting out PR releases and statements trying to create FUD about whether Linux or open source software was any good.  A more recent example in edtech world would be a few years ago when for-profit publishers would spread stories casting doubt (FUD) about whether OER was any good. They helped perpetuate doubts about the quality of OER in order to justify their high priced books. Nowadays, those publishers have tried to enclose (“embrace and extinquish” – another old Microsoft strategy) OER instead of spreading the FUD.

The thing about FUD is that it usually isn’t specific or justified.  It’s an attempt to cause people to feel uncomfortable about things.

The ironic part now is that I don’t think the concerns expressed on Twitter about the Intructure deal are FUD.  What the concerns have shown is there’s reason to be uncertain – the details aren’t disclosed and won’t be. There’s good reason to be doubtful: private equity deals very often do end up butchering or hampering the core business.

And there’s reason to be fearful:  that giant database of student data has value to big players in the surveillance capitalism industry. There’s the big obvious ones: Google, MSFT, Apple, Amazon, and FB. But there’s a host of other hidden players – data brokers, Palantir, banks, and many others, the lords of the algorithm cults. They often have deep pockets or they’re backed by funds with deep pockets. All Instructure/TB needs to do is convince them of a story about how Instructure’s data can add value to their existing trough.

A Final Lesson

I’ve argued extensively that higher education (perhaps all education, but I’m not expert in K-12) is best organized as a commons. The boundary between commons and the market-oriented capitalist economy is tricky. Capitalists and market-thinkers inevitably seek to enclose the commons, privatizing benefits and externalizing costs onto society.

This boundary is particularly tricky in the edtech world. If there’s one lesson I hope to impart to people in education, it’s the need to do your due diligence on your vendors and “partners”.  Current product offerings aren’t enough. Product roadmaps matter. Plans matter.

But most of all, capital structure matters. No matter how nice the people at the vendor, no matter how good the values of the hired managers are at that edtech “partner”, ultimately it’s capital that calls the tune.  That’s why it’s called capitalism.

Scale and Scope

Note: A couple of friends have asked why I say “A commons doesn’t scale, it scopes”. This is a relatively quick note to explain some thinking on why. It’s a topic I’m deep into researching now and developing my thinking as it applies to higher education as a commons, so with the caveat that I may alter some stuff later, here’s my thinking right now. This is part one of a two part answer. Typo in paragraph about Facebook now corrected.

I’ve been saying for awhile now in discussions of the commons, OER, and higher education that a “commons doesn’t scale, it scopes”. Before I explain why I think a commons doesn’t scale very well, I probably need to briefly clarify what’s meant by scale and scope. Like many terms in economics, they’re both commonly used terms in both business and everyday life, but in economics they may carry a subtly different, more precise, or richer meaning. Both terms refer to the production of an increasing volume of output of some kind. Enthusiasts of particular good(s), be they an entrepreneur producing the a product they hope will make them rich or an open educator advocating for more open licensed textbooks because it will improve education, generally want to see their ideas scale. And by scale, they generally mean “be produced in larger and larger volumes”. Larger volume of output, of course, brings a larger volume of benefits to more users. More output –> more users –> more benefits. But it’s the behavior of costs that really intrigues us when we think of “scaling” as a way to increase output. More benefits is nice, but if more benefits also means an equal increase in costs, then it’s not so attractive.

The era of mass production has brought a popular expectation that increased output should bring an increased total cost, yes, but with decreasing average costs. In other words, as you produce more it, the product (or service, or activity) becomes cheaper. This is what we call economies of scale and it’s why scale seems to be such an attractive idea for things we want more of. The idea of economies of scale goes back to Adam Smith.

But since at least the work of Panzar and Willig (see Wikipedia footnotes 3, 4 for links and full citation) around 40 years ago, economists have added a richer explanation. We (well not all economists, but IO and institutional types do) now distinguish between economies of scale and economies of scope.

Scale is to produce to the same thing in larger and larger volumes. It’s doing the same thing over and over again. A lot. There’s little variety, just volume. Scope on the other hand is a way to get to large volume by adding variety to the mix. Scope means doing a lot of things that are different by share some apects. The more aspects shared, either in final form or in production process, the closer you get to scale. The more variety you have, the more scope you have.

For some simple examples, think Ford Motor Company’s Model T. That’s scale in action. Enormous volumes of the same car – even down to the same color. Mass production generally involves scale. Standardization is a virtue in scale. Standardized inputs, processes, and outputs, all enable the great of economies or efficiencies we associate with scale. Massive scale can be managed within a hierarchical structure. The hierarchy adds costs, but it more than makes up for it by through an ability to control and standardize inputs, processes, and outputs. Hierarchical management achieves enough economies of scale to more than offset its added overhead costs.

Scope can bring economies, too. This was part of the Panzar and Willig contribution. Economies of scope are more difficult and complex than economies of scale. They’re less automatic and less obvious. Variety, whether it’s variety of location, product, inputs, processes, or outputs complicates things greatly. However, economies of scope are possible through shared services or other aspects. There are lots of examples of scope economies in the business world, although not so many in real life as business people imagine (I speak from experience). When you hear an executive make the case for merging two different businesses and say they’ll achieve cost savings through “synergies”, that’s economies of scope they’re chasing (and likely not getting, but the investors won’t know that until management has fled the scene). When a school district operates a multiple types of schools (pre-K, elementary, middle, high school, specialty) in multiple locations but insists on centralized purchasing and accounting, that’s an attempt at economies of scope.

When businesses, industries, or products first start to grow, they usually scale. But eventually there are limits to scale. When firms hit the limits of scale in growth, they begin to scope. They usually start with product differentiation and geographic expansion. Then comes segmentation of the market and multiple brands. Variety and variation bite back. Remember Henry Ford’s famous quote about “the customer can get it in any color they want as long as it’s black”? Economies of scale talking there. Unfortunately for Henry, his quote came just as Sloan and Durant at General Motors were pioneering ways of adding product differentiation and segmentation – variety.

When Facebook burst on the scene and seemingly everybody in America (and elsewhere) started signing up, that was scale. But when FB added What’s App and Instagram and Messenger to the corporate portfolio in order to keep the growth going, that was scope.

How does scale and scope apply in education? Scale seems to me to be the impossible dream. We’ve achieved very tiny little scale efforts. When a large flagship university (itself a shining example of wide scope) runs 600 seat lecture classes in principles of economics supplemented with smaller discussion/lab sessions taught by TA’s, that’s a scale effort. It’s tiny though. 600 is only 20x the size of the principles class I teach at the community college. In contrast, business world scale usually means thousands-times larger. We’ve tried to scale by producing textbooks and that has had some positive effect in that it enabled hiring more instructors (adjuncts in particular) at lower costs. But it’s limited too.

Society has for much of the past century been trying to “scale”. Society needs more college-educated people, yet, for many reasons, it is reluctant to pay more them. The idea of scaling education is tempting. If only we could scale up education like we did cars, or clothing, or beer, or music, then we could have more college educated folk and not have to pay the full costs. It hasn’t really happened.

I’d argue it can’t. Scale economies require standardization from inputs to process to outputs. That’s not education. Every learner is different – that’s variety and scope there. What works for one doesn’t work for another. Processes are different. Despite all our efforts in recent decades to define “learning outcomes”, they still defy definition let alone control and standardization. Education requires scope.

There’s more to why a commons won’t scale, but that’s in part two.

Micro, Macro, and the Minimum Wage

Meme showing man in office with coffee mug looking skeptical saying "Yeah, I'm going to have to go ahead and disagree with you there."Economists disagree. It’s so common that there are jokes about.  For example,

If all of the economists in the world were laid end-to-end they would scarcely reach a conclusion.

and

Economics is the only field in which two people can get a Nobel Prize for saying the opposite thing.

Why?  I can’t explain all of economists’ disagreements here (I don’t have enough pixels!), but I can explain some of the disagreement over questions of raising the minimum wage.  There are numerous calls for Congress to raise the minimum wage, yet Congress has remained bitterly divided on the issue. Their disagree to a large extend reflects the disagreement among economists. To non-economists, the disagreement seems to either indicate that there really isn’t any science in economics and it’s all opinion, or that some economists must be lying or deliberating obfuscating.  In truth, though, there’s another reason for the apparent disagreement: the difference between micro and macro level economic analyses.

First, let’s establish some historical perspective on the debate. I want to clarify the difference between “normative” and “positive”.  Positive arguments are statements or conclusions about what the predicted effects of a proposal will be without taking a stand on whether those effects are desirable or tolerable. (note that the word “positive” here denotes “factual or likely”, not “good”) Normative arguments are when someone argues whether a proposal should be done. Normative arguments typically are based upon a combination of predicted outcomes and a value judgement as to whether those outcomes are desirable or tolerable compared to the alternative.  For a long time in economics, economists were actually largely in agreement on the positive science, or the predicted effects, of a rise in the minimum wage.  It was generally agreed that raising the minimum wage would give larger incomes to those who continued to work at minimum wage (i.e. low skilled) jobs but that the rise would decrease the numbers of those jobs and thus raise unemployment rates among those seeking low-skilled jobs. Historically the disagreement over minimum wage hikes was over the normative aspects: was the rise in unemployment and loss of jobs worth the increased incomes to others.

The agreement over the predicted positive effects wasn’t always unanimous. There have always been some dissenters. But in the early 1990’s Card and Krueger studied a “natural experiment” by comparing fast food restaurants on two sides of a state line when one state raised the minimum wage and the other didn’t. Their results started a fierce debate that still rages over the predicted effects of rises in minimum wages.  On one side there are now many economists who side with Card & Krueger in saying that raising the minimum wage, even if raised very significantly such as to $15 per hour from less than $8, will not decrease employment and will have a very large increase incomes. On the other side, maintaining the older stance are those such as Don Boudreaux who doggedly argue that any rise in minimum wage must increase unemployment significantly.  Like most topics in economics the practicality of measuring and analyzing the empirical data is somewhat equivocal.  Although there have been numerous studies since Card and Krueger that have buttressed their results, the empirical data along always leaves enough room for some argument.  So what does the theory say?

Don Boudreaux and others of the “increases in minimum wage MUST increase unemployment” camp, would have use believe that theory is unequivocal. The essence of their argument is that low skilled labor is a commodity sold in a market. It has a demand (firms want to buy it) and a supply (low skill workers want to sell it and get paid).  The wage that gets paid is the price of this labor commodity. The most basic supply-and-demand analysis tells us that if the government forces the price up somewhat artificially by setting a price floor (i.e. a minimum wage) below which transactions cannot occur, then there will a smaller quantity of hours of labor demanded. In other words, firms will hire and pay fewer workers. There’s often an appeal to the concept that if the price (cost) of an input or resource goes up, then the firm’s profits will go down and the firm will be less inclined to produce that good or service and therefore will buy less (hire fewer workers).

How can good theory-toting economists dispute this?  Isn’t it supply-and-demand, the most basic micro economic concept as taught in the first few chapters of any principles of econ text?  It’s easy actually. The key is that this supply-and-demand theory as argued against a rise in minimum wage has three major flaws. Two flaws are the result of the theory as applied being too simple (there’s more chapters in the micro text!) and the other  flaw reflects the difference between micro and macro in economics.

The first flaw in the simple supply-and-demand model application to minimum wage type jobs is that there’s really very little evidence that labor markets behave like commodity markets or that they conform to the assumptions necessary to use a supply-and-demand model.  Most jobs, including minimum wage jobs, are more like long-lasting relationships. They aren’t commodity, transaction based like a market for selling widgets or apples or even theatre tickets.  There are dramatic transaction costs involved. Put another way, it’s expensive to hire people (and to fire them and then replace them). Minimum wage jobs aren’t homogenous (they aren’t all the same) the way the theory requires.  Further, the wage paid affects the productivity of the worker, which in turn affects the value of that worker’s output to the firm. When the wage is boosted, workers work harder, stay longer on the job, quit less often, and gradually acquire more productivity and skills. Firms often find that when forced to pay the higher wage, the firm’s total costs, including hiring costs, etc, stays level or even declines.  This is the essence of Arindajit Dube’s studies.

The second flaw is in focusing on the cost of the worker’s wages as if it were the sole consideration in the firm’s decision of how much to produce. The standard theory of the firm and production, which is covered in-depth just a few chapters later in the same economics textbooks after the supply-and-demand model makes it clear:  a firm will produce whatever quantity makes it the most profit. The primary constraints on the output are the demand for the end product, the pricing of the end product, and the core technology used. In other words, if the firm can still sell the output to consumers, it will produce it and the technology (means of production) will require it to hire the necessary labor. A rise in the price of a particular input does not necessarily mean a drop in the quantity produced.

The other two flaws in the arguments against minimum wage increases require shifting to a macro perspective. Micro economics is often described as studying individuals and individual products/markets.  That’s only partially true. Actually micro is a methodology. It’s more properly called “comparative statics using partial equilibrium analysis”.  Micro theories and models explicitly focus on only one particular shifting variable (the wage in this case) and it assumes that all other variables or influences are held constant or unchanged. (Economists call this the ceteris paribus assumption).  In contrast, macro theories are often described as focusing on large aggregate phenomena such gross national product or the inflation rate or the national unemployment rate.  But again, there’s actually a methodological difference. Macro theories require a general systems approach accounting for multiple effects and ripples of many variables that are interrelated.  Let’s look at minimum wage increases as an example of these differences in methodology between macro and micro.

In micro, there’s really only the price (i.e. the wage itself), the quantity of jobs offered, and the quantity of workers available, all of it in the low skill arena.  That’s it. So the micro analysis sees that when the minimum wage is boosted, the firm pays more per worker and each employed worker gets more. End of story.  The only micro question is how it all affects the quantities of jobs.

Macro, however, recognizes that nothing happens in isolation in the economy. There’s a circular flow. Workers are also simultaneously customers. So when the minimum wage goes up, yes, the workers get paid more and firm pays out more money. But what do those workers do with the additional money income? They buy things. Who do they buy them from? Firms that sell and produce products. So the firms not only pay out more money to workers, the firms also get to collect more money by selling more to the increased consumer demand.  But, you say, Acme’s newly enriched minimum wage workers don’t buy that much stuff from Acme. Doesn’t matter. The workers spend it somewhere. And that firm uses the additional money and additional demand to buy more inputs and pay more profits. And those firms and workers then experience income increases and so on and so on as the money circulates throughout the economy. Eventually even Acme sees an increase in sales and revenue collected which in turn helps pay for the wage boosts.  Macro looks at the whole system.

In recent years, many cities and some states have taken it on themselves to raise the minimum wage, often to a so-called “living wage”.  The empirical results have pretty clearly supported the macro analysis. Rises in minimum wages tend to not depress employment and actually tend to stimulate the local economy.  This is the macro analysis.

Sometimes economists just disagree and sometimes they let their ideological and political biases color their professional arguments. Some of that happens in the debates on minimum wage increases.  However, much of apparent disagreement arises from the choice of whether to view the issue through a micro lens or a macro lens.

To read more about the economic analysis of minimum wage increases see these earlier posts:

 

 

Some Links on Economics of Immigration

These are some links and key points on the economics of immigration for a guest talk I’m giving to a class tomorrow.

Links on Minimum Wage

A few minimum wage links to use in my guest lecture/discussion with Professor Reglin’s classes tomorrow:

 

Taxes, Incentives, and Being Poor

Now Updated with proofreading!

Political debates about taxes and tax rates in the U.S. often focus on the rich and claims about the incentive effects of different tax rates. Rarely mentioned these days are the poor.  Indeed, the Republican demands in the last few years that tax rates should be cut  for the high-income rich are primarily about claims of incentive effects. And, no, high-income rich isn’t redundant; it’s precise.  There are at least two types of “rich”: High-income rich, which pay income taxes, and the high-asset, low income rich which pay much less. (I suppose there’s another type, the spiritually-rich, but that’s the domain of some other blog.) The claim is made that if tax rates are raised or raised too high, then that provides a disincentive to work and the rich will not work as much. It is often asserted that this is simple micro-economics–that people respond to incentives–and should be obvious.

There’s a problem with the claim, though.  Actually there are two problems. First, there’s very little empirical evidence of higher tax rates on the highest end, the rich, actually reducing their efforts to earn income.  Indeed, numerous studies (I don’t have time at the moment to look for citations) have found in “natural experiments” that the rich really don’t respond to higher tax rates by working less and earning less. Several studies have found that in situations where a large metropolis straddles two or more states, such as NYC, and different neighboring states changed their tax rates on the rich, the rich did not in fact do what they threatened or what would appear “rational”: move to the lower tax state in the same metro area.  There’s also substantial longitudinal evidence in the U.S. and other countries that shows when tax rates on the rich were a lot higher, such as in the 60’s and 70’s, effort and incomes were no less than in more recent times.

The other problem is the whole idea that the “rational” response to higher tax rates is to reduce one’s effort and income actually doesn’t hold microeconomic water.  It’s actually irrational to respond that way unless the marginal tax rate is truly so high that it approaches or exceeds 100%. The average tax rate, the percents you normally hear on TV, isn’t what affects incentives. Instead, it’s the marginal rate, or how much an extra dollar earned is taxed, that changes how we behave. Even then, a raising a marginal tax rate might reduce the incentive or attractiveness of additional effort and gross income, but won’t become a true dis-incentive until it becomes very, very high. An example:  Let’s suppose someone makes $1,000,000 a year and is taxed $400,000. Such a person is said to pay a 40% average tax rate or effective tax rate. But averages and effective rates tell us nothing about incentives.  Incentives deal with changes in behavior at the margins – the incremental changes.  If micro is clear about one thing and has been since the 1870’s, it’s that decisions and changes in behavior depend on changes in marginal costs and marginal benefits.  What matters is the taxes on the marginal, the incremental, change in income.  What matters is the marginal tax rate.  The only reliable way to figure the marginal tax rate is to compare two different amounts of income, preferably with only a small difference between them, the taxes paid and the after-tax-income that results.  What people work for is to get after-tax, spendable income.

So let’s continue the example.  Suppose the existing tax code, with all of its exemptions, deductions, rates, credits, etc, says that $1,000,000 income pays $400,000, but that $1,010,000 income pays $405,000 in taxes, then we have an increase in income of $10,000 of which $5,000 is used to pay the additional taxes. After-tax income rises from $600,000 to $605,000, leaving a net increase in after-tax income of $5,000. This means we have a marginal tax rate of 50%.  There be a disincentive effect only if opportunity cost (usually leisure) of the additional time/effort needed to generate the higher income is judged to be greater than the $5,000 increase in after-tax income.  Empirical evidence indicates that is not likely.  On the other hand, if the marginal tax rate were 100%, it would mean that $1,010,000 in income requires $410,000 in taxes. At a 100% marginal tax rate none of the additional effort results in more after-tax spendable income, so obviously it doesn’t make sense to exert the extra effort.

So what are the marginal tax rates for the highest brackets in the U.S.?  Even if all income comes from wages, the highest marginal rate is now around 38%.  Even if you include state or city income taxes, the marginal rates faced by the rich aren’t greater than 50% even in the most onerous tax-happy states. For the really rich, most income comes from capital gains and not wages.  Capital gains have a much lower marginal tax rate of close to 23-24% (including the 2013 Medicare tax on capital gains).  Evidence is pretty clear that such marginal rates do not provide a disincentive to additional work.

But, now I want to return to the poor.  We often assume that the poor don’t pay much in taxes.  That’s true in total  since they’re poor–there’s not much there to tax. But, marginal tax rates still exist. And they affect incentives.  In fact, it’s the working poor that face the most serious disincentives to work and earn income.  Our tax code is actually set up to make it rational for the poor to not try to earn more income!  As University of Southern Cal Professor Edward McCaffery notes on CNN.com,

…some of the working poor face marginal tax rates “approaching 90% as they lose benefits attempting to better themselves.”

Readers were incredulous, asking how it could be that in a nation with a top federal income tax rate of 39.6% on individuals making more than $400,000 a year, anyone could face a 90% rate.

It is true. Marginal tax rates, especially for those below the top rate brackets, are chaotic, confusing, and all over the map.

As a result, some of the working poor face extremely high rates on their next dollar earned. Tax scholars and economists have long known this. Dan Shaviro of NYU published a study in 1999 showing marginal tax rates above 100% on the working poor; specifically, he illustrated that a single parent earning $10,000 would lose over $2,500, after taxes, by earning another $15,000, pushing her income to $25,000.

Obviously, this is a policy failure.  We want to support the working poor, but we want them to be able to increase their incomes, join the middle class, and leave dependency behind.  Yet the way most welfare and aid to working poor programs are structured, a working poor person can find themselves in a situation where working additional hours or getting a modest raise in wage will actually result in less after-tax spendable money.

The problem is even worse, as Professor McCaffery points out.  The tax code exerts a genuine disincentive to getting married or to staying married if you are among the working poor.  Yet, we know that stable marriages and two-income households are often the key to escaping poverty for both the present and next generations .

It’s appropriate to talk about the incentive effects of tax rates.  Incentive effects should be part of the thinking when writing the tax code, just as reasons for government revenue should be a part.  But when we talk about incentive effects of tax rates, we must focus on the marginal rates and we really should be talking about the poor.  Not the rich.