Taiwan and Supply Chain Frenmity

Plus! Airline Green Zones; Short Sellers and the Supply Chain of Information; Housing and Pull-Forward Demand; Facebook and Visa Arbitrage

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Taiwan and Supply Chain Frenmity

One of the most economically important cities in the world is  Hsinchu. Where Hsinchu is located depends on who you ask: if you’re  booking a hotel, Marriott will let you narrow it down to “Mainland China  and Hong Kong, Macau, Taiwan,” while your United Airlines flight can get you to  “Taipei” (no country listed). If you try to ask the World Health Organization  about the country Hsinchu is located in, they will encounter  unfortunate technical difficulties. Hsinchu is, of course, located in  Taiwan, a country whose formal existence is actively questioned and  whose practical existence is undeniable.

In yesterday’s post, I wrote about the history of Taiwan  Semiconductor Manufacturing from a microeconomic perspective: why a chip  company that didn’t design chips was a nonsensical proposition for  decades, why it became workable, how it grew essential, and what its model means today. Today’s post looks at the same phenomenon from a  different angle: why did the business start in Taiwan, and what does it mean today?

Taiwan’s history as a major economy starts after the end of the  Chinese Civil War; the Communists conquered the mainland, and the  Nationalists retreated to Taiwan. While Taiwan was certainly not  communist, it wasn’t especially capitalist, either. Like other  successful East Asian countries, the Taiwanese government broke up large  estates and encouraged local farming—in Taiwan’s case, mostly as an  effort to a) weaken non-state power, and b) make the country  self-sufficient in the event of a blockade. Taiwan did want some exports  to generate hard currency, but with a particular purpose in mind: the  country had one of the largest armies in Asia in the 50s and 60s, and  had active discussions with the US about what to do about China in the early 60s.

Japan and South Korea developed their economies in a state-directed,  banking-heavy way: large companies got loans in exchange for promoting  exports, and the initial focus was on heavy industry: steel, chemicals,  machinery, and later cars. Taiwan’s model was almost the exact opposite,  with a large array of tiny companies, mostly targeting labor-intensive  exports. Each country’s industrialization was promoted by a few big  secular trends—higher consumption and rising wages in the US and Europe,  and the growth of the container ship industry, particularly the one-way  shipment of military supplies to Vietnam that made rates from Asia to  the US low. But the exact timing of their growth led to different  development models. (For much more on this, see my piece on the East Asian economic miracle and this one on containerization.)  US consumption in particular benefited from an accident of tax policy:  Congress passed a law in 1954 offering a tax credit for investing in  business, which was meant to support manufacturers. It was written  vaguely enough that it applied to malls and shopping centers, and the  growth of the Interstate Highway System made those businesses more  viable. So a law designed to promote domestic manufacturing ended up  creating demand for cheaper foreign manufacturing instead.[1]

Taiwan’s growth coincided with three important trends: first, wages  in Japan started rising, which made the country’s lowest value-adding  industries, like footwear and electronics assembly, less profitable.  Second, American retailers started using bar codes and computers to  manage their inventory better. Third, American retailers had to adhere  to fair-pricing laws, which prohibited large companies from selling  brand name products at low prices. Retailers responded by creating house  brands, which they could price any way they wanted. Sears, for example,  asked American TV manufacturers to build them an off-brand TV set in  1964. The American companies said no, but Toshiba said yes.[2]

As it turns out, these unrelated trends combined in a way that  massively benefited Taiwan’s export sector. Japanese trading companies  had good relationships with American retailers, and started offshoring  their production to Taiwan. (Since Taiwan was a former Japanese colony,  there were some cultural and linguistic ties.) The trading companies  could move their equipment from Japan to Taiwan, and take advantage of  much lower wage scales: in the mid 1960s, US textile workers earned $333  a month, Japanese textile workers made $69/month, and Taiwanese workers  made $23/month.

For some products, fragmented production is a major cost. It’s hard  to coordinate thousands of ten-person companies to put together a car.  But for other products, it’s a benefit, because it means that the lowest  value-added parts of the process can be outsourced piecemeal, while the  most valuable ones can stay behind. Assembling TVs is a low value-added  task, but some of the components require proprietary technology.  Japanese TV companies could outsource the easy work to small Taiwanese  contract manufacturers, while keeping the most valuable parts domestic.  In bicycle manufacturing, Taiwan’s distributed manufacturers were able  to respond faster to changes in consumers tastes; Korean chaebol conglomerates tried to compete, and they had unbeatable costs for large product  runs—but couldn’t handle the diversity of products consumers wanted.  (Japanese companies continued to make components like derailleurs, which  were a) harder to get right, and b) much less sensitive to the whims of  consumers.) In shoes, Nike contracted its high-volume product lines to  Korea, and specialty products to Taiwan.

The PC market came later, but was an even more extreme example: the  product cycle for PCs was extraordinarily fast in the 80s and 90s, and  the business was scaling rapidly. Some components could be reused across  many product lines, while others were product-specific. Taiwan’s original equipment manufacturers—contractors who built generic PCs for brands like Dell and Gateway—responded in their usual fashion, and the country turned into a key  supplier for US-based companies.

At this point, a problem developed: Taiwan was reaching the classic  middle-income trap of getting richer by competing on price, and ending  up too rich to compete on price. Fortunately, a solution presented  itself: China slowly opened its economy. It’s a testament to how  entrepreneurial these firms were that the beginning of large-scale  outsourcing from Taiwan to China predates the legalization of travel and  investment there; apparently many of them reached arrangements with  Hong Kong’s banking and border control authorities that would allow them  and their money to travel from Hong Kong to China without fully  informing Taiwanese authorities.

By this point, Taiwanese contract manufacturers had expertise in  managing complex supply chains, deep relationships with retailers and  distributors, and a keen understanding of how to react to consumers'  whims. All they needed was affordable labor. China, with a population in  1990 of 1.14bn people and a GDP per capita at the time of $320, had  both. So, industry by industry, Taiwanese manufacturers moved to China.  Sometimes, this happened incredibly quickly—Taiwan was 30% of US shoe  imports in 1987 and 3% in 1992; the suppliers mostly didn’t change, but  the factories moved. In other cases, it took longer.

It’s around this time that Taiwan Semiconductor Manufacturing enters  the picture. TSM is in some ways a counterpoint to the general story of  independent, small-scale entrepreneurial Taiwanese companies; it was  founded as a joint venture with the government. On the other hand, it’s  very much in the spirit of the Taiwanese exporter ecosystem; Taiwan  didn’t have many globally recognizable brands, but they did have a  comparative advantage in meeting the needs of companies that did. TSM,  as a chip foundry that didn’t design chips, had exactly the same  mercenary agnosticism as other local manufacturers: a shoe factory could  work with Adidas or Nike; a bike company could brand its products as Schwinn or Huffy; TSM can fab chips that will go into anyone’s  devices. As Taiwan’s economy matured, the country generated enough  savings to fund ambitious investments (in fact, Taiwan’s vast savings create substantial distortions in global bond and currency markets).  A capital-intensive business like chip fabbing is exactly appropriate  for a country like Taiwan, with a rich, high-savings population and no  comparative advantage in labor-intensive businesses.

TSM is over half the foundry business, with 3x the market share of its nearest competitor.  And chips are, like oil, dollars, and widebody aircraft, one of those  products that basically every country wants to consume but that many  aren’t able to produce. A paper I once read said that oil is “the most  efficient way to turn economic risk into geopolitical risk,” and  semiconductors fall into that category, too: a crucial global industry—more than 1/200th of all economic activity, and growing—has  its de facto headquarters in a country that is treated, by the country  with the world’s largest active-duty military, as a rebellious breakaway  province that must be reunited with the mainland by whatever means necessary.

The Golden Arches Theory of Conflict Prevention  holds that countries with close economic ties (e.g. McDonald’s) will  not fight a war. The Chinese/Taiwanese equivalent is the Local Province  Conflict of Interest Theory: even if national-level policy dictates that  China and Taiwan should be politically reunited, local officials in China only  hit their GDP and employment growth numbers because the  two countries are so economically  united, and political action is a threat to that. Earlier in China’s  development, this was because the factories were literally owned and  operated by people from Taiwan, which is still the case, albeit less so than it used to be ($, Economist).

But China’s reliance on the consumer electronics industry, and that  industry’s reliance on TSM, makes conflict murderously expensive, at  least for now. But it also means that if you’re worried about future  conflict, the scariest statistics to look at aren’t troop counts, or the  speed of hypersonic missiles, or other indicators of combat capability.  The really scary numbers are semiconductor capital equipment billings by country,  which show that Chinese manufacturers are now investing substantially  more in chip manufacturing capacity than Taiwanese ones are. There is a  large gap between spending money on chip manufacturing capacity and  actually making competitive bleeding edge chips—if you don’t believe me,  ask an Intel shareholder. But it’s a worrisome sign, because Taiwan’s  paradoxical existence makes sense in light of commercial ties, and those  ties are weakening.

Further reading: This writeup owes a great deal to the book Making Money, a history of Taiwan’s industrialization. For much more background, see the “sources” section of this post.

[1] Stay tuned for a future Diff writeup on one of the other  surprising beneficiaries of that law, the notorious Leasco.  Leasco has it all: a bit of technology, a lot of financial engineering,  rejections of B-school dogma, and class conflict. It closes with one of  the all-time greatest quotes from someone who earned millions of  dollars, but also millions less than he thought he was about to: “I  always knew there was an Establishment. I just used to think I was part  of it.”

[2] These fair trade rules may be familiar to readers from my Costco writeup a few months ago.[3]

[3] This is a good time to note that The Diff itself  operates much like the Taiwanese export sector, with a large number of  modular components, each of which sources key inputs from sites like  FT.com and SEC.gov, and which link together to deliver the finished  product.

A Word From Our Sponsors

Here’s a dirty secret: part of equity research consists of being one  of the world’s best-paid data-entry professionals. It’s a pain—and a  rite of passage—to build a financial model by painstakingly transcribing  information from 10-Qs, 10-Ks, presentations, and transcripts. Or, at  least, it was: Daloopa uses machine  learning and human validation to automatically parse financial  statements and other disclosures, creating a continuously-updated,  detailed, and accurate model.

If you’ve ever fired up Excel at 8pm and realized you’ll be doing  ctrl-c alt-tab alt-e-es-v until well past midnight, you owe it to  yourself to check this out.

Elsewhere

Airline Green Zones

Last week, I cited Delta and Alitalia’s plan to implement their own Covid-safe travel corridor through frequent testing. Delta has elaborated on this plan in an internal memo to employees on testing. Airlines have unique motives and opportunities to deploy test-and-trace procedures:

  1. Unlike many other businesses, all of their employees and customers  have to be identified, and have to pass through specific chokepoints.  Testing changes the degree of inconvenience for air travel, but not the  kind. And since airlines need their passengers' identities and contact  information already, they can actually inform them of test results or  past exposures.
  2. Airlines also have a stronger than usual economic incentive to  return to normal as quickly as possible. One way to view the airline  industry is that it’s a classic finance story: time-weighted returns  look better than the dollar-weighted returns, because airlines always  deploy capital at the worst possible time, and then have to raise  expensive funding to stay in business.

(Via Tyler Cowen.)

Short Sellers and the Supply Chain of Information

Institutional Investor has an alarmist article with some shocking news: apparently, some investors pay for research! And then they trade on it!

The economics of short-selling research work like this: finding a  good short idea takes lots of time, and it takes a highly variable  amount of time. Sometimes, the idea is simple; sometimes, it requires labor-intensive research, or even rolling a car down a hill. Because of this uncertainty, it’s hard for dedicated short-selling funds to make money—they can  do it, but the payoff of short selling doesn’t line up well with  standard hedge fund structures. Instead, short sellers often work  independently and sell their research to funds. This presents a tricky  information asymmetry problem: pay upfront, and there’s a market for  lemons. Pay only after reviewing the idea, and it’s easy for a fund to  get the gist of the thesis and recreate the trade itself without paying.  (Allegedly, one of the investors who was pitched John Paulson’s  subprime-shorting fund thought the idea was good and ran with it himself.  The problem of piracy is not confined to the media business!)

Aligning incentives is hard and imperfect, but in this case it’s  socially beneficial. Liquidity makes fraud easier, and fraudulent  companies compete with legitimate ones for capital. Even an imperfect  system of rewarding people for spotting dubious companies is better than  a system that lets those companies get away with it.

Housing and Pull-Forward Demand

The last time an economic recession led to interest rate cuts and a  housing price boom, it did not end especially well for the world  economy. But one of the upsides to a catastrophic once-a-century  pandemic is that we can, in fact, say this time is different and mean  it. One difference between today’s housing market and the market circa  2006: it’s much more convenient to evaluate a house and make a purchasing decision. This has a few long-term effects:

  1. It means that the underlying cause of housing’s outperformance—a  decrease in the desirability of cities and an increase in the  desirability of extra bedrooms and home offices—gets reflected in the  market faster.
  2. It improves the unit economics of ibuyers (for more on them, see my writeup here). They charge a percentage  fee and pay interest as a function of time, so anything that reduces  their holding period increases their profits.
  3. A shorter lag between deciding to make a purchase and closing on a  new house shifts the move in housing prices earlier in time relative to  the change in demand. So any historical model that predicts housing  demand based on external factors like interest rates, inflation, and  unemployment will have to adjust its lags.

Facebook and Visa Arbitrage

The DOJ has sued Facebook for favoring H-1B workers over US-based workers.  This lawsuit illustrates how tricky it is to write a coherent  immigration policy, especially one that balances the desire for skilled  workers with the desire not to depress wages:

Rather than conducting a genuine search for qualified and  available U.S. workers for permanent positions sought by these  temporary visa holders, Facebook reserved the positions for temporary  visa holders because of their immigration status, according to the  complaint. The complaint also alleges that Facebook sought to channel  jobs to temporary visa holders at the expense of U.S. workers by failing  to advertise those vacancies on its careers website, requiring  applicants to apply by physical mail only, and refusing to consider any  U.S. workers who applied for those positions. In contrast, Facebook’s  usual hiring process relies on recruitment methods designed to encourage  applications by advertising positions on its careers website, accepting  electronic applications, and not pre-selecting candidates to be hired  based on a candidate’s immigration status, according to the lawsuit.

From Facebook’s perspective, it looks like this: an employee was  worth hiring, and works well with the team. Facebook would like to keep  employing this person. However, there’s some paperwork, so Facebook does  the minimal level of paperwork necessary. if the job were an  interchangeable, unskilled position, a policy requiring them to  advertise it to US workers would not materially harm the company, but  would increase US workers' wages. That’s not the nature of these jobs:  the workers in question are already at the company, and presumably  already working on projects with existing teammates. Replacing them with  another worker who has similar but not identical skills, but isn’t used  to working with the team, is close to a pure deadweight loss for both  Facebook and the H-1B worker.

A visa for workers who have skills that aren’t available locally is  mostly an exercise in artfully parsing definitions. In some fields, the  half-life of skills is short enough that, over the course of a six-year  visa the skills they’re hired for will be obsolete and the work they’re  doing will be completely new. Facebook’s technical compliance  illustrates how hard it is to write straightforward policy that makes  qualitative judgments about workers' skills and employers' needs; easier  to set a quantity, hold an auction (with long-term payment plans, to  encourage low-cash-flow/high-potential jobs), and let employers quantify  how irreplaceable any potential visa holder is.