LP#47: Ro Khanna and the Nightmare Chart
Author: Gary Winslett
Ro Khanna is a roller coaster. He has some great ideas and then he says some things that are truly baffling. He’s also an important roller coaster. He may run for the Senate seat that Dianne Feinstein currently occupies and so could be the next California Senator. He’s pretty young (46), worked on an early Obama campaign in Illinois, was an intellectual property lawyer, then Deputy Secretary of Commerce, now a Congressman from Silicon Valley, he may have presidential ambitions, and he is one of the thought leaders on economic policy in the Democratic Party, so it’s important to understand what he thinks.
Let me put my cards on the table here. I am more ambivalent about Ro Khanna than any other American politician. Sometimes, he makes me want to stand up and cheer. Other times, he leaves me gobsmacked, and not in a good way. Sometimes when I’m in a political economy disagreement with someone I like to imagine us as two doctors standing over a patient who is having a health problem and we disagree on what’s causing the problem and what to do about it. That’s where I think we are here. Though I have some serious disagreements with his trade policy ideas, having read his books and articles, I have come away absolutely convinced that Ro Khanna cares deeply about Americans in left behind places. I don’t think it’s an act. Truly. Despite growing up in Philadelphia and representing Silicon Valley, Ro Khanna gives a damn what happens in Indiana, and I have a lot of respect for that.
What I am going to try to do here is lay out what Khanna thinks, what I see as especially strong about it and what I see as less strong about it. The reader can then decide for themselves what they think about Ro. I’ve divided this essay into four parts: Part I (the Nightmare Chart), Part II (manufacturing), Part III (technology), and Part IV (the Democratic Party’s traffic light coalition).
I- The Nightmare Chart
Including graduate school, I’ve been studying and writing about the intersection of markets and politics for more than a decade and, in that time, I have seen hundreds, maybe thousands, of charts, but there is one that haunts my thoughts the most. It’s from this 2016 report by the Economic Innovation Group. Let me walk you through it the way I walk my students through it in my “International Political Economy” course.
What we’re looking at is net business establishment. So, if 100 businesses open in an area but 20 close, that’s a net gain of 80. It’s a measure of economic health in a given area. During economic recoveries, more businesses open than close. This chart is looking at the division of that recovery gain across different county class sizes. So, to use simplified numbers, if in a given recovery there were 1000 net business openings, what percentage went to rural areas (counties with under 100k people), what percentage went to relatively small places (100k-500k people), what percentage went to larger places (500k to 1 million), and what percentage went to the biggest urban areas (more than 1 million)? This chart looks at that question across three recoveries: 1992-1996, 2002-2006, and 2010-2014. In the first bar above, for the 92-96 recovery, 32 percent of net business establishment went to rural areas, 39 percent went to smaller places, 16 percent to larger places, and 13 percent to the largest urban areas. That’s a geographically well-dispersed recovery.
Now check out what happens in the 2002-2006 recovery.
Everything has shifted over. In that recovery, the share of net business establishment (i.e. economic health) that went to the largest urban areas more than doubled, larger places also saw a gain, smaller places basically held steady, but the rural share was essentially halved. If you’re concerned about America’s urban-rural divides, that’s not good, at all.
Now watch what happens in the 2010-2014 recovery.
I once had a student accidentally blurt out “oh shit” when they saw that bottom bar. Instead of admonishing her for swearing in class, I told her that was the exact right answer. This chart merits an “oh shit” response. Look at that. In the 2010-2014 recovery, more than half of all net business establishment went to the largest urban areas and another 23 percent went to the next largest county class size (they were almost all counties right next to those booming urban areas), the smaller places got less than a fifth of net business establishment, and rural areas got literally nothing. Everyone got a Great Recession, but larger places got a recovery while rural places didn’t. For rural America, things got bad and they never got better.
The political fury of rural America in 2016 did not come from nowhere economically. While there are many factors that caused Trump and Trumpism (some far less excusable than others), it is vital to recognize that rural Americans’ economic grievances are not built on myth. They are valid and they are worth taking seriously. For a hot minute in 2017, Democrats did that. Then the moment faded and many Democrats, regrettably, started to write off rural America politically and economically. They would say that rural America was too culturally conservative for Democrats to win there and so the new path to electoral success lay in the suburbs, particularly well-educated well-off suburbs. According to this view, if you combine those suburbs with big margins in urban areas, you get a winning coalition even if Democrats get annihilated in rural areas. Along with that analysis, this mentality also sees increasing urbanization as a way to fight climate change since urban lifestyles are less carbon-intensive. A usually sottovoce addition is to say that economic concentration is just the way things are now and so anyone in rural America who wants to prosper needs to move to the city.
That mentality is politically disastrous. It makes it very challenging for Democrats to hold the Senate and statehouse governments. At least as importantly, it is toxic, just plain toxic, to write off rural people and rural places as if they do not matter. Some people have connections to places (family obligations, immobile jobs, deep emotional attachments to ‘home’, etc.) that keep them where they are. They are not going to move to a loft apartment in Brooklyn. They just aren’t. It is also un-American. These are our fellow countrymen. They are people with names who live in places with names. Nationalism can often go way, way too far but we do have some obligation to our fellow Americans.
Here I should note, for any reader who is new to this series, I grew up in a mobile home in rural central Alabama. My father worked in a steel mill for 30 years until illness forced him to retire. I live in Vermont now. Yes, I’m a college professor in New England but I can assure you that I’m not the haughty elitist that right-wing populists might try to portray someone like me as. Part of the reason the nightmare chart haunts my thoughts so much is because I know the kinds of people who are on the sharp end of it. I’m them in a tie.
There’s a second mentality though, and Khanna’s thinking seems very much steeped in it, that does better than the first at taking rural American’s economic grievances seriously but then slides into a counterproductive populism that decries big business and indulges in far too much nostalgia for the economy of the New Deal era (late 30s to late 70s). This view implies that if only we could go back to the Wonder Years and localism and unions and factories providing mass employment, the good ol’ days would come back. You can hear this mentality particularly clearly in Elizabeth Warren’s near constant refrains about what life was like for her and her family in Oklahoma in the 50s and 60s.
Though this nostalgia may give some people the warm fuzzies, it has all kinds of analytical problems. It is backward-looking smokestack chasing rather than having any set of ideas about how to leverage technological improvements to create inclusive growth. It ignores the fact that the 50s and 60s economy in the United States was facilitated by a set of global circumstances that are unlikely to be repeated and that we should not want to be repeated: Europe and East Asia had been shattered by World War II, the Global South was just getting on its feet after centuries of colonialism, and the Soviet Union and China were under brutal communist dictatorships. Of course American manufacturing dominated in that context. But we don’t want that world back. This nostalgia also ignores the fact that in the United States, economic opportunities for women and minorities were horribly curtailed and it ignores the fact that technology was still rudimentary enough that you needed humans to perform all kinds of menial drudgery tasks that machines do today. And these are just the beginnings of the analytical shortcomings in the populist nostalgia perspective.
Here it is important to understand what did and did not happen in American manufacturing. First of all, even back the olden days of the New Deal Era, most workers were not manufacturing workers and over time, service sector jobs grew much faster than manufacturing jobs.
The United States has now, and for a long time has had, a services-based economy. Even in the Midwest in 1990, manufacturing was a pretty small minority of jobs.
That doesn't mean those jobs don't matter. They do, but let's not get carried away thinking everyone worked in manufacturing in the halcyon days. They didn’t. Why did that decline happen? Long story short, automation meant that we got better at making more things with fewer people. Manufacturing employment began falling in the United States and many countries including Germany and Japan in the 1970s, i.e. well before the ‘China Shock.’
From the mid 1980s to the late 1990s, manufacturing employment hit something of a plateau overall though with the continued growth of service sector jobs, that did mean is continually comprised a smaller and smaller share of overall employment.
At the same time, a combination of economic forces (increasing returns to scale, network effects, product differentiation, oligopolistic competition, greater intra-industry trade) concentrated production into fewer places. Increasing globalization opened greater opportunities to the most efficient firms but subjected less efficient firms to withering competition. What this means was that certain locations would dominate the production of certain goods and services, think Hollywood for movies and New York for finance. This affected manufacturing too. It got less spread out. There were now bigger but fewer factories. This has continued ever since. Believe it or not, the largest factory in the world today is in the United States; it's the Boeing Everett factory in Washington.
Here’s where Khanna’s story picks up. Khanna does a version of the nostalgia story, though he is savvier and more measured about it than Warren is, and smartly, doesn’t go as far back in time as Warren and her ideological brethren tend to do. Whereas Warren implicitly says “I want the New Deal Era back”, Khanna is smart enough, and young enough, to mostly say “I want the 90s back.”
In an essay in Foreign Affairs, he says “For many citizens, the American dream has been downsized. In recent decades, the United States has ceased to be the world’s workshop and become increasingly reliant on importing goods from abroad. Since 1998, the widening U.S. trade deficit has cost the country five million well-paying manufacturing jobs and led to the closure of nearly 70,000 factories. Small towns have been hollowed out and communities destroyed. Society has grown more unequal as wealth has been concentrated in major coastal cities and former industrial regions have been abandoned. As it has become harder for Americans without a college degree to reach the middle class, the withering of social mobility has stoked anger, resentment, and distrust. The loss of manufacturing has hurt not only the economy but also American democracy.”
He goes on “Americans should embrace a new economic patriotism that calls for increasing domestic production, bringing jobs back from overseas, and promoting exports. An agenda focused on regional revitalization will offer hope to places that have endured decades of decline as policymakers watched haplessly and offered little more than Band-Aids to people laid off as a result of automation and outsourcing. A commitment to rebuild the U.S. industrial base does not mean the country should turn its back on the world and adopt the kind of insular economic nationalism that powered the 2016 Brexit vote in the United Kingdom.”
There is some stuff in there that is pretty good. The acknowledgment that automation is a challenge is spot-on and the rejection of “insular economic nationalism” is encouraging to hear as well. Still there’s a lot in his piece that isn’t right. Much of Khanna’s arguments there and elsewhere draw on the China Shock literature, but that argument has a lot more problems with than most people realize.
The China Shock argument went as follows. China’s economic policies were calamitous under Mao. That meant that once China adopted better policies there was a lot of room to grow, especially given its population size. China’s comparative advantage was in labor-intensive manufacturing. China’s manufacturing growth thus constituted a large global supply shock for labor-intensive manufacturing and a large demand shock for raw materials. Different industries tend to cluster in different places; this is true in the United States as it is anywhere else. Because of that, different places in the United States experienced different levels of vulnerability to that supply shock in labor-intensive manufactured goods. As some of Autor, Dorn, and Hanson’s earlier work shows, labor intensive manufacturing is particularly trade exposed and particularly concentrated in a cluster of mostly southern states. The places that were more exposed to this supply shock saw larger declines in manufacturing employment and wages. These negative effects had big local spillovers, i.e. when that labor-intensive manufacturing declined, it undermined demand for other goods and services in that area, corroded tax bases, and contributed to a whole range of other social ills in those areas.
Not only that, but contrary to economists’ conventional wisdom, people did not tend to move; they stayed put and suffered rather than leaving for greener pastures. In other words, the adjustment costs to this shock were deeper and more scarring than was typically appreciated. The negative impacts were felt most strongly by the least-educated, lowest paid workers; those with higher incomes (implying more education and skills) were better able to transition than those with less income, education, and skills. When taken at face value and especially when weaponized by populist politicians, this story painted a damning picture of trade’s impact on middle America.
There are however a number of important caveats to this. The first is that the job losses are probably an overestimation. Autor himself has acknowledged that their estimates are the upper-bound. Other studies, such as this one, have found much smaller effects. Some studies, such as this one, even find that liberalized trade with China likely had a positive impact on wages and employment. Additionally, in terms of mobility, Autor, Dorn, and Hanson’s model assumes literally zero geographic mobility. Even if they’re correct that prior research overestimated mobility, assuming zero mobility is an inaccurate representation of reality and inflates the estimate of jobs lost. The second caveat is that, even if everything about the China Shock is correct, it's inaccurate to attribute Chinese imports to capital-intensive manufacturing decline. As ADH point out, some industries like apparel, textiles, and leather are particularly labor-intensive. Even in areas that are manufacturing oriented, there is a lot of variation in terms of industry exposure to imports; Tennessee was a lot more exposed to trade with China because its manufacturing was disproportionately in furniture while Alabama was less exposed because its manufacturing was in heavy industry. Third, the China Shock arguments ignore the benefits of imports from China. According to one Federal Reserve study, for every lost job due to the China Shock, there were approximately $400,000 in consumer benefits. From 2000 to 2006, the peak years of the China Shock, the price of manufactured goods fell by 7 percent. This was not only good for consumers. Because over a third of Chinese imports were intermediate goods, it was good for producers too.
Additionally, the United States does not just import from China, it also exports goods and services to China as well. Many of the producers of those goods and services would not have had access to the Chinese market were it not for China’s integration with the global economy. Moreover, discussions around trade shocks often ignore the costs that accompanied the United States’ reactions to it. When President Trump raised tariffs on China and the EU, China and the EU predictably retaliated. American farmers paid the price; agricultural exports targeted by those retaliation were $8 billion lower in 2018 than they had been in 2017, a 27 percent drop. The damage was wider than just farmers. Just for 2020, President Trump’s trade war with China was estimated to cost the average American family over $1200 in higher prices and lost productivity. According to the IMF, the trade war lowered global GDP by 0.8 percent. Antidumping measures on China hurt industries that imported those targeted products (and thus workers) as they raise the cost of production. In other words, they negatively impact employment and wages and don’t actually help the protected industries all that much.
The better explanation for the fall in manufacturing employment is automation, which really ramped up around 2000. Michael Hicks and Srikant Devaraj’s research suggests that trade only accounted for about 13 percent of manufacturing job losses between 2000 and 2010. Of the 18 industries they look at, trade was responsible for more jobs lost than productivity increases in none of them and was responsible for more than a quarter of job losses in only two of them (apparel and furniture).
As they say in their paper, “had we kept 2000 levels of productivity and applied them to 2010-levels of production, we would have required 20.9 million manufacturing workers. Instead, we employed only 12.1 million.” So even if every word of the China Shock literature is true, the bulk of manufacturing jobs that went away did so because we got better at making more stuff with fewer people, not trade shocks, and that statement becomes even more true if one excludes apparel and furniture. Geographically speaking then, even if it makes sense to attribute the decline of furniture and textile towns in the South to the China Shock, it makes no sense to blame the China Shock for the decline of manufacturing jobs in capital-intensive industry.
And theirs is not the only research that points in this automation direction. There’s a lot of economic research that backs up this automation thesis. See this paper on Acemoglu and Restrepo and this paper by Autor and Salomons on automation’s displacement of labor. There’s also this paper by Graetz and Michaels that shows that automation improves productivity and accelerates growth but finds some evidence that it reduces demand for low and medium-skilled work. Here’s a study showing that automation negatively impacts manufacturing employment but more than makes up for that by increasing productivity and boosting employment outside of manufacturing. This isn’t just an American phenomenon. Dauth, Findeisen, Südekum, and Wößner find a similar pattern in Germany. Notably, as is the case in the United States, the observed manufacturing job losses there are more than made up for in aggregate.
These trends are likely to continue. Look inside car factories today. Yes, there are still some workers there, but the factories do not have nearly as many people in them as they once did, and that’s because of automation. In the auto sector in 2015, once all of the costs are factored in, a spot welder earned about $25 an hour whereas it only cost about $8 an hour for a robot. That kind of automation is now coming to industries like electric equipment and even to furniture which (as the Hicks/Deveraj work above shows) was long a very difficult industry to automate.
Between 2021 and 2031, the Bureau of Labor Statistics expects manufacturing employment to decline by about 140,000 jobs but expects manufacturing output to increase by more than $1 trillion (in 2012 dollars). Meanwhile, the U.S. economy is expected to add more than 8 million service sector jobs.
Again, it is important to note that these labor-displacing effects in manufacturing are typically far outweighed by the overall increase in labor that automation brings. In contexts as varied as Canada, Spain, Finland, and Japan, more automation has increased overall employment. A meta-analysis literature review found the same. It is worth saying this very clearly: consistent with the historical trends, automation today creates more jobs than it kills. It may be the case that automation negatively affects particular segments of the labor market, but the narrative that automation is going to eat all the jobs or even the milder claim that it will lower overall employment do not seem to be rooted in fact. That is good news!
The bad news though is that particular parts of the labor market really are being hit hard by automation. The same meta-analysis that found an overall employment also said “low-skill, production, and manufacturing workers have been adversely affected by technological change, and effective up- and reskilling strategies should remain at the forefront of policy making along with targeted social support systems.” Moreover, the speed of technological progress may present significant challenges for certain workers, particular given how much change is now happening over the course of a single career. Technologies like AI and machine learning will fundamentally alter how many jobs get done even if they do not eliminate them.
This was also the case for NAFTA specifically. J. Bradford Delong has an excellent explanatory piece on Vox about this. As he says “Did NAFTA drive the fall in the manufacturing employment share? No…. The trend preceded NAFTA, and it would have continued with or without NAFTA.” One thing that DeLong correctly emphasizes is that while trade has bigger benefits than costs, for those who lose out, it is much, much better for them if the overall labor market is tight because that means that they can more easily find a new job. It’s that mobility that’s the key. There’s a reason I wrote a whole essay earlier in this series on labor mobility.
This is obviously a very different explanation than the China Shock argument described above. If the technology explanation is correct, then the protectionism advocated for by the China Shock-oriented explanations will hurt citizens as consumers without actually helping them as workers. What a policy tragedy that would be. We should want to help those workers who have been displaced out of manufacturing, but understanding what caused that displacement is key to getting the policy intervention right. If it was automation rather than trade, then the effective policy response is to help those workers gain new skills, not protectionism.
Now there may be other reasons to root for manufacturing to do well, and this graphic from McKinsey succinctly captures some of them, but manufacturing is simply not going to be the big driver of jobs the way it once was.
The problem is that, here again, Khanna gets too nostalgic. He says “Manufacturing workers are also more likely to belong to unions, receiving protections that secure their membership in the American middle class; a solid industrial base and strong union participation expanded the middle class by leaps and bounds from the 1940s to the 1970s. The replacement of U.S. manufacturing jobs with service-sector jobs is, in truth, the erasure of reliable well-paying jobs in favor of more precarious low-paying ones.” He is missing a couple of really important things there. First, many service sector jobs pay quite well. He’s implying that service work is all precarious and poorly paid and that simply isn’t true. Second, he’s missing that much of what manufacturing employment did remain in the United States shifted toward right-to-work states in the Southeast and Sun Belt. South Carolina, Georgia, and Alabama all saw enormous growth in their automotive industries starting the mid-1990s. They are now 3 of the top 5 states in auto exports (South Carolina is #1). Those three states, like much of the South, are right-to-work states. South Carolina has the lowest unionization rate in the country at 1.7 percent.
Today, a lot of the investment in green technologies like EV batteries and turbine manufacturing is going to red states, in part because of the right-to-work laws and in part because they have far less cumbersome regulatory processes. Both of these dynamics complicate the picture for Ro Khanna and Democrats like him. They would like to sell themselves as the party of manufacturing, organized labor, and strict environmental standards. They don’t want there to be this politically unhelpful but obvious tension between their goals. Meanwhile, for totally understandable reasons, it became no longer politically palatable for a state as white as Iowa to go first in their party’s primary elections and so, since South Carolina is much more diverse and was already an early state in the process, South Carolina got moved into that first position. So, Democrats want to perform better in the South, they want to say that they can deliver prosperity to rural areas and to communities of color but they are at extreme pains to not acknowledge that right-to-work laws were an important part of drawing manufacturing investment and thus jobs into places like South Carolina, Georgia, and Alabama and are also loath to advocate for deregulation to spur green energy investment, and they have just, probably inadvertently, put the least unionized state in the country first in their primary process.
The Impossible Promise of Yesterday’s Return
A big part of Khanna’s pitch, around manufacturing and otherwise, is the nostalgia itself. As much as that might not make for good economic strategy, there is a reason that nostalgia sells so well politically. The most politically powerful group of voters and the group workers most fearful of change just so happen to have a ton of overlap. Who is the median voter? It is a 50-something person who did not go to college. Those kinds of people tend to be very skittish about economic change. There’s a fascinating study by Thomas Kurer showing that fearing economic adversity has a different effect than actually experiencing economic adversity. Kurer divides the workforce into those doing routine work (hurt by automation- think factory workers), those doing nonroutine cognitive work (helped by automation- think engineers), and those doing nonroutine manual work (unaffected by automation- think janitors). Given these three job positions, for those currently doing the kind of routine work that is negatively affect by automation, there are four possible career trajectories. There are those who ‘upgrade’ by moving to cognitive work (the factory worker becomes an engineer), those who ‘survive’ by staying in routine work, those who ‘downgrade’ by moving into nonroutine manual work (the factory worker becomes a janitor), and those who ‘dropout’ by becoming unemployed. Routine workers fear automation both for material reasons (it may negatively impact their wages) and for social reasons (it may negatively impact their place in the social hierarchy). For dropouts, the experienced economic hardship leads them to support more redistributive policies. The factory worker who now has no job at all wants a helping hand from the state. For survivors however, the fear of potential hardship leads them to disproportionately support right-wing populists who they believe will fight against change and uphold their place in the status hierarchy. The factory worker still in work, but fears losing that work, doesn’t want state-redistribution so much as he or she wants the state to stymie anything coded as ‘change.’
For that kind of worker/voter, nostalgia is very attractive whereas more future-oriented messaging (however economically superior that may be) feels vaguely threatening. Make Manufacturing Great Again is thus responding to a broader set of anxieties. The problem is that promising yesterday’s return is a promise that cannot be fulfilled. Because of all the reasons I mentioned above, manufacturing will NEVER again be a major source of mass employment the way it was in the mid-1950s and it certainly won’t usher in a society based around unions and hard hats. According to BLS data, only 7.8 percent of all workers work in manufacturing and only 8 percent of workers in durable goods manufacturing are union members. In other words, unionized manufacturing workers comprise just 0.62% of the overall labor force. Now, if policymakers like Ro Khanna want to help that 0.62% of workers, that’s great, but we should not trick ourselves into believing that protectionist policies like steel tariffs that benefit narrow slices of workers within this already narrow slice, at great costs to other workers, are "pro-worker" policies. It may be good on a “vibes” level -that’s debatable but it is at least possible- but it doesn’t make sense as an economic strategy.
Here's the good news: all of this automation won't lead to a jobs apocalypse. We're good at finding new stuff for people to do. But....those won't be the same jobs as those that existed before. The manufacturing work that remains will be fewer in number and more intellectual. We should care about people having good jobs, but we shouldn’t have especially strong commitments to them having those good jobs in one particular sector over others. We can have great jobs in America, but not if we pretend 2023 is 1993 or 1973. At his best Khanna gets this, one point he makes in his Foreign Affairs piece that I strongly agree is the need for more apprenticeships; he points out that “Germany has also invested heavily in apprenticeship programs and in training its workforce for the high-tech future; the United States has not.” That’s right. Along those lines, smokestack chasing and protectionism are the wrong strategies for this challenge. Public-private partnerships, jobs training, hot labor markets, housing abundance, Medicare buy-in, occupational licensing reform, ending noncompetes, and mid-career skill transitions are the right strategies.
As misguided as his protectionism around manufacturing is, Khanna’s views on technology more broadly are often very good. The first chapter of his newest book “Dignity in a Digital Age” has one banger line in it after the next. Whether it’s graciously acknowledging that some people may be skeptical of politicians’ tech competence given Members of Congress’ sometimes cringe-inducing questions at hearings or calling out enragingly patronizing talk of “just learn to code” or balancing an understanding of why some people, for any number of personal reasons, genuinely want to leave rural places (and that’s fine) whereas some people are quite rooted in those places but feel they have no choice but to leave in order to prosper (and that’s bad), again and again Khanna demonstrates a deep and nuanced understanding of the emotional and psychological contours of rural America’s economic realities. He may have never seen the nightmare chart before, but he’s talked to plenty of people who have lived that chart, and it shows. You read “Dignity in a Digital Age” and you say to yourself “This guy gets it.”
From page 16, “It no longer makes sense to speak of a stark distinction between the old and new economies.” Thank God someone in Congress understands this. Technological progress is a foundational part of how we create inclusive growth.
From page 17, “We achieve national excellence when every individual reaches their highest potential. The progressive framework for our era can be both pro-dignity and pro-growth.” Preach.
From page 9, “People do not simply want to be taken care of; they want to be agents of their own lives and productive members of society.” Yes, this is what dignity and liberty are all about.
Khanna’s book is chock full of passages that make you want to stand up and clap. In my professional work, I am currently working on a book on political economy and Big Tech. I’ve read all the leading books on the topic and many secondary ones. Khanna’s “Dignity in a Digital Age” is one the best books out there right now on political economy and technology, certainly one of the best by a politician. If you’re interested in this topic, it’s worth your time to read it.
And much of Chapter 2 in “Dignity in a Digital Age” that explains how technological shifts contributed to the urban-rural divides represented in the Nightmare Chart are spot-on. This is actually one of the focuses of my current research. Here is how I explained this trend in an academic book chapter that came out a few months ago:
“Technological advances are driving economic concentration. One of Steve Jobs’ favorite stories went something like this: there was a chart in a scientific magazine in which different animals were compared in terms of how much energy they needed to cover a mile (Jobs 2006). The author of the chart had the insight to not just look at a human by themselves (which was in the middle of the pack) but to also look at a human on a bicycle. Once the human and their invention the bicycle were considered, the human was by far the most efficient animal. Jobs said that computers could be like this for cognitive distance covering- they could be bicycles for the mind, and Indeed, that is exactly what computers have done. They have made brainy work more productive. That kind of work has historically been located in cities because cities facilitate the generation of ideas and the flow of information. Ergo, the ascent of computers, the internet, more advanced telecommunication and all of the other bicycles of the mind have benefitted cities, especially those cities at the leading edge of technology…….
The economic clustering seen over the last three decades was fueled by a feedback loop between computerization and skills. The cities where computers were adopted most quickly in the workplace saw increases in wages, which drew in talent; these places, now abundant in computer-complementary skilled labor, would then adopt computers even faster, further boosting wages (Beaudry et. al. 2006, Hendrickson et. al. 2018, 11). Once these cities possessed greater wealth and tax bases, they had more amenities and more new firms which attracted still more skilled workers (Hendrickson et. al. 11). This meant that the cities with the largest share of digital workers saw their share of digital workers grow faster than others (Muro 2017). Again, it bears pointing that this happened in only a relatively small share of places. As a 2016 World Bank report notes, “in the United States, the adoption of advanced internet applications by firms led to substantial wage growth in the 6 percent of counties that were the wealthiest, the most educated, and had an IT-intensive industry, with no effect elsewhere” (The World Bank 2016, 118).
All of this all had an effect on productivity and growth. Starting in the early 1990s, the firms that were the heaviest IT users, which were already somewhat clustered in a few major cities, became much more productive than their more analog counterparts (Brynjolffson and Hitt 1996, 541-548; Stiroh 2002). This trend became even stronger over subsequent years (Jorgenson et. al. 2011, Brynjolffson and Hitt 2003). Not only that, but when highly-skilled, ambitious employees of innovative technology-oriented firms left those businesses to start their own companies, they tended to do so in the same geographic locations (Moretti 2012, 80-81). With these advantages in hand, new jobs that did not exist until recently tended to show up first in these most educated places, reinforcing those advantages (Lin 2011). Not only that, but whereas manufacturing jobs generate an estimated 1.6 additional jobs in the local economy, jobs in the innovation sector generate an estimated 5 jobs in the local economy and so the local economy in the cities that the tech sector clustered in have boomed (Moretti 2012, 13, 24).
Large cities thus became more productive and saw nearly twice as much private employment growth and greater wage growth as compared to smaller metropolitan areas and non-metro areas (Parilla and Muro 2017, Porter 2017, Hendrickson et. al. 8). These areas gained an increasing share of investment, particularly venture capital. In 2016, 75 percent of all venture capital went to just three states: California, New York, and Massachusetts (Townsend 2017). This tech-driven clustering of opportunity into large, dense urban areas is in marked contrast to the geography of manufacturing that took place in large cities, smaller cities, and exurbs (Porter 2017). According to one estimate, across the developed world, for every one job the Internet has destroyed, it has created 2.6 jobs but, importantly, the job losses have been geographically spread out while the job gains have most been geographically concentrated (Moretti 2012, 65). Superstar firms and superstar cities compete well in and integrate well with global markets and so tend to see greater benefits from international economic integration than other areas and so the same places that benefit from technological advancement also benefit from globalization (Grossman and Rossi-Hansberg 2008, Donaldson 2015 Cosar and Falgelbaum 2013). The very troubling flipside is that other areas, i.e. smaller metros and rural areas, have largely been left out.”
Khanna’s explanation is more or less in line with this. He uses some different studies and examples, but he gets what’s going on here. He also has some really interesting thoughts on work-from-home and, to my pleasant surprise, he even has a short section on challenging NIMBYism (though I wish there were more there). There are other strong sections of the book too such as the chapters on racial and gender equity and on workers; I don’t agree with everything in them but there are some solid ideas there too- I’m going to have to leave that to the side for now as this essay is already running long enough).
The best way to respond to these technological challenges and opportunities is to embrace remote work and international trade in services. If people only need to go into the office once or twice a week, it is easier for them to spread out, which makes the satellite radius around cities bigger. If people can work entirely remotely, that opens up their opportunities to live in cheaper, more rural places, and given the extremely high property prices in cities and in places like California, that’s pretty attractive. Remote workers could be a real boon for rural America. This is intimately connected to the digital trade in services internationally, another topic that I’ve written about professionally. Once a person is doing their professional work at home and delivering it digitally to whomever pays them, it doesn’t really matter whether that payer is domestic or international and so any dynamic that promotes work from home at least implicitly promotes the digital trade in services. Likewise, anything that makes it easier to digitally trade services internationally is going to benefit freelancers who work from home since now they have many more potential clients. This is a newly emerging form of globalization that looks very different from ships carrying stacks of cargo containers but it is nonetheless a very real and potentially very beneficial form of globalization. As the 2019 World Trade Report notes, “Globalization is not slowing or stalling. Rather, it is evolving, driven by trade in human skills, knowledge, and ingenuity.”
These trends will likely be particularly helpful to rural areas and smaller metros. Rural areas have thinner markets and so all kinds of services can be difficult to access. That is not only inconvenient for people who live in those areas, it discourages people from moving to them. If however it is easy to get access to those services, whether it’s a spin class or a doctor’s visit, because it can be delivered digitally, that shifts some of the calculus in the cost-benefit analysis of whether to move to that rural area or not. Digital services may also be especially helpful to rural small businesses by obviating the need to set up a physical location abroad.
IV- The Traffic Light Coalition
In European politics, they tend to have more than two parties and different parties are usually represented by different colors. Red has long been associated with socialists and labor. The environmentalists are, unsurprisingly, green. There are often centrist parties that are socially modern but pro-market. Macron’s party’s color in France is yellow as is the Free Democratic Party in Germany. In the European context, when people say that a person or party is “liberal”, this is what they usually mean. Depending on the country, the center-right parties are usually blue (the UK’s Tories) or black (Angela Merkel’s party). The far right is usually associated with the color brown.
Here in the United States, we have a two-party system but you can still see aspects of this ideological colors in the parties’ coalition. You can make a case, I think, that the Democratic Party is, ideologically, a ‘traffic light’ coalition that unites the reds (socialists and organized labor), the greens (environmentalists), and the yellows (market-friendly moderates like me). Holding that coalition together is something of challenge politically. These factions frequently disagree on a great many topics including the ones this essay has focused on. The yellows would like more free trade deals; the reds are adamantly opposed to that. The greens want to defend seemingly every environmental regulation; the yellows want permitting reform. The reds want to promote manufacturing; the greens are wary of anything that seems to promote fossil fuels. The yellows want an abundance agenda; the reds are more concerned with distribution and the greens think sacrifice is necessary for the climate so abundance isn’t really their thing either.
Different Democratic Party leaders have united these factions in different ways. Bill Clinton was a yellow faction president who reached out to the green faction in various policy ways and kept the red faction happy by the simple fact of being president during an economic boom. Barack Obama had different policies for different groups. Though leftists now deride the Affordable Care Act as milquetoast, it was a big win for red faction. He advances climate action fairly well, especially that Republicans were in charge of at least one chamber of Congress for six of his eight years, and he was also, in both his personal style and in matters like trade policy, friendly with the yellow faction. In terms of keeping the party together, it certainly did not hurt that he was the most politically talented Democrat in generations. Joe Biden, as candidate, was favored by a lot of yellow faction types. We voted for him to keep Sanders and Warren at bay. And, as a folksy white guy in his 80s, he has a very moderate affect. But he has governed like a red faction president. He has continued Trump’s protectionism, leaned hard in favor of labor unions and industrial policy, and his most recent State of the Union address was the most avowedly left-populist State of the Union in decades. The Inflation Reduction Act was, in a lot of ways, the Green New Deal but with a more strategically adept name. Every leader, or would be leader, of the Democratic Party has to find a way to make that coalition work. What helps Biden keep the yellow faction in the tent is that Republicans under Trump have become the party of being aggressively weird. If there’s one thing political moderates in suburbs don’t like at a gut level, it’s political parties that do weird stuff and Republicans do weird stuff all the time.
Still, there are fractures in that Democratic coalition, particularly between the reds and the yellows and, at this point, much of what duct tapes it together is common disgust with Trump’s Republican Party. The red faction would honestly prefer the yellow faction disappear. The Sanders and Warrens of the world do not like people who are business-friendly or have business connections. THey don’t want them to be welcome in the party at all. The yellows are aghast at the policy direction the reds are dragging the party. What makes the situation even more fraught is that each faction can credibly threaten to bolt the party if they don’t get their way. If the reds think the Democrats are getting too yellow, they can just stay home and not vote or vote for a third party candidate like Ralph Nader or Jill Stein. The yellow faction is not the largest, but their kind of voters (politically moderate, market friendly, not hostile to the social safety net but not clamoring for a revolution either) are particularly prevalent in the suburbs that swing elections and they are the voters who, if Republicans nominate candidates who aren’t insane, can credibly say that they’ll vote Republican if the Democratic candidate is too red.
Which gets us back around to Ro Khanna. I mentioned earlier that he’s a Congressman, was an intellectual property lawyer, and was Deputy Secretary of Commerce. He’s also written two books on economic policy and he represents Silicon Valley. I think he thinks he’s got enough credibility with yellow faction and I think he understands that yellow faction has some good policy ideas.
Furthermore, to his credit, he knows that red faction is far too easily tricked into making unnecessary mistakes if it means they can make a point or feel like they stood on principal. Once Republicans took back the House, one of the first bills they forced a vote on was denouncing the horrors of socialism. This was such obvious bait for Democrats. The Republicans wanted as many Democrats as possible to vote against that denunciation and thus implicitly for socialism. Khanna understood that this was obvious bait and refused to take it, voting Yes along with 108 other Democrats to denounce the horrors of socialism. You know who did take the bait, who did vote against the bill and thus for socialism? Katie Porter, Elizabeth Warren’s protégé, who is running for the California Senate seat Dianne Feinstein is finally leaving, a seat that there’s a good chance Khanna wants to win himself.
Khanna also probably does have a lot of affinity with the red faction too. To give one example, he worked with Bernie Sanders on the STOP BEZOS Act. Some workers at large businesses have incomes low enough that they qualify for public assistance programs like food stamps and Section 8 housing vouchers. The STOP BEZOS would have added a surtax to those companies based on the extent to which this is true of their workers. The idea behind is that these companies are currently offloading the costs of supporting those workers from themselves to taxpayers and so this bill it would force these companies to pay their workers more. On one level this sounds great and making sure that taxpayers are not being taken advantage of is certainly a laudatory goal. The problem though is that this bill would have created a clear disincentive for these large firms to hire workers that might qualify for those public assistance programs. Those are the exact kind of low-wage workers that we want to have lots of job options; creating a huge disincentive to hiring them is not helpful to that at all. Additionally, the bill, in true populist fashion, only targeted large firms but didn’t apply this surcharge to smaller businesses even though, from a helping workers standpoint, there is no real reason to do that. On top of these problems, the bill did not seem to consider that higher labor costs would simply be passed onto consumers in the form of higher prices thus hurting other workers, how benefits eligibility works, or just how difficult it would have been to administer as well. So, you can see where the problem is. Sanders and Khanna started with perfectly reasonable goals (wanting workers to get paid more and wanting to safeguard taxpayers’ interests) but pursued it in a manner that substituted oversimplified, the good ‘people’ versus the ‘bad’ elite moral narratives for careful tradeoffs-oriented thinking and so would almost certainly have created more harm than good.
If Khanna is at his best in his book Dignity in a Digital Age, he’s at his worst when he’s trying to latch onto populism. If he’s getting into a populism contest with Katie Porter, that’s going to be a race to the bottom and may lead him to saying a whole bunch of things that disqualify him to moderates down the road. Here’s a good example, and it’s far from the only one.
This kind of stuff makes sane people want to tear their hair out. In this tweet, Khanna is honest-to-God blaming ‘corporate greed’ for deaths that any reasonably normal person understands are because of the COVID pandemic, and he’s doing that while arguing for the red faction’s favorite policy, Medicare for All, and doing that even while the biggest heroes of the pandemic were the private-sector businesses that invented COVID vaccines in under a year. This is madness, sheer bloody madness.
All of this comes back around to the Nightmare Chart. A yellow faction response to it would be to accept that even if manufacturing in America goes gangbusters, most of the “jobs” will go to robots, and of the jobs that do go to humans, most will be non-unionized jobs in right-to-work states in the South, and those jobs will depend on fossil fuels, and the people who work them will live in car-oriented suburbs. And all of that is fine. It would also focus a lot more on economic growth as an end in itself and on services. It would promote remote work and other technological advances that will reinforce global capitalism and promote the growth of exurbs. To people like me, that sounds like a great idea. The green and red factions would be horrified by various aspects of that though. The red faction wants nostalgia and unions and industrial policy even though those won’t work. They actually don’t like a lot of aspects of modernity. They have almost nothing future-oriented to say about how to unleash technology or markets. The green faction wants urbanism even though that does nothing for rural America. They have almost nothing future-oriented to say about how to help rural America grow out of bucolic underdevelopment. We need someone who can convince the red and green factions to get on board with the yellow faction’s ideas on this, for the good of the country, and it is going to need to be someone with credibility with all three factions.
I don’t know if Ro Khanna is the right person to fix this conundrum. He cares a lot and that’s always a good first step. His technology assessments are very sound. His protectionism and manufacturing-as-jobs source focus borrows way too much from red faction and his willingness to indulge in crazy populism to try to win red faction support is stomach-churning. But who knows, maybe he’ll embrace to smartest parts of his platform and jettison the rest, or maybe not.
Like I said, Ro Khanna is a roller coaster.