March 19, 2019 Reading Time: 4 minutes

I have a confession to make. Remember when Wall Street got off easy after that whole mess in 2008? That was my fault. You see, I spent months, years even, poring over those bankers’ books and trades, looking for every way I could get them off the hook. What can I say, I was fresh out of grad school, living in New York City — I had to pay the rent, didn’t I? My bad.

This story is an example of what happens when we gloss over the complexity of the real world. We end up losing far more understanding than we often realize, and with strangely skewed perspectives on what happened and what to do about it.

A slightly more detailed version of the story is that fresh out of grad school, I consulted for lawyers preparing economic expert testimony in large financial cases. My start date of January 2008 was something of a Forest Gump moment, accidentally in the right place at the right time to witness history. I worked on several matters where my direct clients were partners in large law firms. Their immediate clients were in-house lawyers or other department heads. They in turn worked under the same CEO and board as a few dozen traders, whose records from the craziest day of their lives in October 2008 I was now trying to piece together.

The lesson one draws from the story changes drastically when we add just a little complexity. Wikipedia, whose definition likely emerged from a complex process of hundreds of decentralized writers and editors, says: “Complex systems are systems whose behavior is intrinsically difficult to model due to the dependencies, competitions, relationships, or other types of interactions between their parts or between a given system and its environment.”

“Intrinsically difficult to model,” yes, but we do it anyway because we have to. Our brains weren’t built to think through the billions of dependencies and interactions in our economy, so we necessarily apply heuristics, often thinking of markets or entire economies as a narrative involving a few people. “Government” does this. “Buyers” do that in response.

Trouble is, due to the vexing way that all of the elements of a system interact, when we apply these shortcuts we often end up with a simple truth that is at odds with a complex reality. This dilemma is at the heart of why it’s often so difficult to explain to people the virtues of free markets and the dangers of planning.

A Guaranteed Trainwreck

When I wrote my critique of the job guarantee, I kept getting stuck on a question that, while mundane to Ph.D. economists, was the crux of the entire proposal: how does one actually assign 15 million people jobs? I pored over the types of work suggested by the proponents. I estimated how many jobs various local and state governments would have to fill. I suggested someone draft a proof-of-concept showing this was really possible.

Here’s what the folks at the Levy Institute, the job guarantee’s most vocal proponents, had to say on the matter:

Jobs can include: cleaning up vacant properties, reclaiming materials, restoration, and other small infrastructure investments; setting up school gardens, urban farms, co-working spaces, solar arrays, tool libraries, classes and programs, community theaters, and oral history projects; building playgrounds, pedestrian areas, and bike lanes; and organizing carpooling, recycling, reuse, and waste collection programs.

The Levy economists’ mental model was closer to finding jobs for a hundred people than for millions. But add all that complexity back in and you end up somewhere very different. Another term at the heart of complexity theory is “nonlinearities.” As the size of a system grows all those interdependencies don’t just add up, they multiply.

In an economy of a few hundred people, a job guarantee might not be such a bad idea. But finding jobs, monitoring workers and employers, administering programs, fighting corruption all become difficult in a way that we just can’t capture when we apply our hundred-worker shortcut. It’s not just a matter of scaling up; the system becomes difficult to manage in entirely new ways.

Tariff Man vs. Captain Piracy

Simplified narratives of complex events are also at the heart of why our president and much of our media catastrophically misunderstand international trade. I recently wrote:

President Trump’s aggressive use of tariffs in 2018 made clear that he did not view international trade through the lens of commerce, where thousands or even millions of individuals and firms do business. Instead, world trade was about negotiation, with world leaders using carrots and sticks to regulate commerce between their citizens and the strongest and shrewdest leaders coming out on top.

How do we talk about trade? “The U.S. slapped tariffs on China.” No. The Trump administration created a tax that thousands of U.S. firms must pay to import Chinese goods, some of which they absorb as lost profit, some of which they pass along to consumers. Chinese firms are also harmed through lower demand.

But isn’t this necessary so that “China” stops pirating our goods? Again, unpack the statement. Who is pirating the products of American firms? Is it Chinese firms, tucked away in a country of over a billion people, that would be prohibitively costly even for a regime as powerful as the Chinese to stop? Or are there bad actors in the Chinese government, an immensely complex organization itself, who have limited accountability to whomever is negotiating trade deals on the government’s behalf.

Taking complexity even a little seriously leads us to vastly different conclusions about trade than when “America” and “China” are imagined to be two poker players staring each other down in a smoke-filled room.

Respecting Complexity

These oversimplifications become more dangerous in the context of socialism or widespread economic planning, where millions of workers and thousands of firms become “labor” and “capital.” But libertarians should reflect on how often they’ve imagined “government” to be one or a few nefarious plotters.

Our brains are inherently limited when thinking about complex systems, so our shortcuts and narratives aren’t going anywhere. How can we minimize the damage? First, we can pay attention to economists who take complexity seriously, from Hayek to today’s Santa Fe Institute. Second, we can be aware of the shortcuts we take and approach conclusions with a degree of caution. We would be wise to mind the ever-widening gap between the evolution of our technology and society and that of our ability to understand it.

Max Gulker

Max Gulker

Max Gulker is a former Senior Research Fellow at the American Institute for Economic Research. He is currently a Senior Fellow with the Reason Foundation. At AIER his research focused on two main areas: policy and technology. On the policy side, Gulker looked at how issues like poverty and access to education can be addressed with voluntary, decentralized approaches that don’t interfere with free markets. On technology, Gulker was interested in emerging fields like blockchain and cryptocurrencies, competitive issues raised by tech giants such as Facebook and Google, and the sharing economy.

Gulker frequently appears at conferences, on podcasts, and on television. Gulker holds a PhD in economics from Stanford University and a BA in economics from the University of Michigan. Prior to AIER, Max spent time in the private sector, consulting with large technology and financial firms on antitrust and other litigation. Follow @maxg_econ.

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