Labor Markets, Trade, and the China Shock


During this election season, trade protectionism has reared its head across the political spectrum; no candidate seems willing to believe (or admit to believing) that free trade is good for the country. The closest thing to a defense anyone can seem to muster is to claim that our current trade deals are in fact bad deals, which at least leaves the implication that good trade deals exist. While public polling suggests free trade is more popular than you might think given the political rhetoric, a substantial fraction of Americans are suspicious of trade, despite overwhelming support of free trade among economists.  A National Bureau of Economic Research paper from earlier this year sheds light on why this difference of opinion exists.


The China Shock: Learning from Labor Market Adjustment to Large Changes in Trade’, by David Autor, David Gorn, and Gordon Hanson, looks at the economic impact of trade with China on US manufacturing. To simplify immensely, they find that the costs of trade are higher than previously thought (but importantly, still a net benefit to both nations). To fully appreciate their findings we will need to set the stage with a simple model of trade impacts, but first I’d like to define what is meant by ‘the China shock’.


The example of China is basically without historical precedent in having a very large, cheap pool of labor enter the manufacturing sector in a very short period of time. After the death of Mao in 1976, China embarked on a series of reforms throughout the 80s and 90s that liberalized portions of the economy and which culminated in the country joining the World Trade Organization in 2001. This ensured the Most Favored Nation status China had enjoyed from the US and Europe throughout the 90s was made permanent, as well as opening other global markets to Chinese exports.  From about 1990 to 2000, China’s share of world manufacturing exports more than doubled from 1.9% to 5%, and in the decade and a half since joining the WTO has more than tripled again to almost 20%.  This veritable explosion of manufacturing capacity in just over two decades, coupled with low tariff access to most developed countries’ markets, is the China shock.


According to the authors, on the eve of China’s accession to the WTO, there was a rough consensus among economists on the impacts of trade: (1) Trade had not been a major contributor to the decline in manufacturing employment or rise in wage inequality in developed countries; these trends predated the era of trade liberalization and major deals like NAFTA seemed to have had little additional impact. (2) Workers in regions that specialized in hard hit areas of manufacturing (Pennsylvania steel, Detroit auto, etc.) could move to other regions without much trouble if trade eliminated jobs in their area. (3) Labor market impacts of trade would not be confined solely to trade exposed industries; due to the ‘law of one price’ for skill, these impacts would be spread across all similarly skilled workers.  


Under this set of assumptions (more or less the neoclassical model of trade), the concentrated impact of a particular trade shock is absorbed by the national labor market. Think of heating a pot of water with a flame; while in the instant the water closest to the flame is hotter than the rest, soon the heat is spread throughout the entire vessel evenly. In this simple model, labor of a particular skill level is like the water molecules: highly mobile and totally identical.


With this in mind, the impact of a trade shock at the regional level should be as follows (after allowing for some time for adjustment):





Manufacturing employment should decrease because the local industry is no longer competitive, leading to a pool of labor seeking work. They have two options: they can leave the area to find similar work elsewhere in the country and/or or reallocate to the local non-manufacturing sector in jobs with a similar skill level. As such, we would not expect any differences in the regional unemployment rate or labor force participation. Finally, the change in local wages (for all workers, not only manufacturing) relative to any changes in national wages should be zero (this follows from the assumption of one price for skill).


Now, as you might imagine, actually estimating the real world impacts of a trade shock on a region is very tricky. I’ll leave the complicated bits to the actual paper, but in a nutshell what the authors did was exploit the variation in regional manufacturing and the variation in exposure to Chinese manufacturing to make these estimates. For example, Tennessee has a large concentration of furniture producers, which is a sector where the Chinese had substantial exports. In contrast, much of Alabama has lots of heavy industry which did not experience much competition from China. Even within industry sectors, there a substantial amount of variation in exposure to the China shock, which gives the authors an additional level of control to make more precise estimates. (In econometrics, having such variation is crucial. Imagine trying to estimate the impact of an additional year of education on income with data that only specifies that an individual has completed high school or college). To compare with the table from earlier, qualitatively what the authors found was this (all non-zero results were highly statistically significant):





It should not be surprising that the employment in trade exposed manufacturing decreased; this jibes with the earlier prediction.  What is surprising, though, is every other factor did the opposite of what was expected. Workers did not leave the region or shift to the non-manufacturing sector. They remained in the area and joined the ranks of the unemployed or left the labor force altogether. And the average change in wages (again, for all workers) in trade exposed regions was negative, not zero. To return to the analogy of heating a pot of liquid, it’s as if instead of water the pot were filled with peanut butter.


What can account for this? One explanation could be that the because size of the China shock was orders of magnitude greater than any other previous trade shocks, we are still in an adjustment period. Under this view, the neoclassical model of trade is essentially correct and the findings here are due to an exceptionally long adjustment time required for the labor market to return to equilibrium.


Another possibility for long adjustment time is that the rise in the US trade deficit has reduced the demand for sectoral reallocation among US tradables. Implicit in the neoclassical trade model is the assumption that countries are engaging in balanced trade. Simply put, countries trade goods and services for currency, which is then used to buy back other goods and services. Money is neutral, desirable only as a medium of exchange. So if manufacturing sectors A, B, and C in the US shrink because China has a competitive advantage, we should expect sectors X,Y, and Z in which the US has an advantage to expand. But what has actually happened is that the US has consistently run a very large trade deficit that ballooned during the 90s.




On a yearly basis we import billions of dollars more than we export. And China is particularly responsible for this growth, as the figure below demonstrates.


We can think of the trade deficit as reallocating demand across time. For a variety of reasons, China is willing to give us lots of stuff without us giving them anything but dollars in return. Future US consumption has been pulled into the present, and eventually we will have to run a trade surplus with China to make up for it. In the meantime, the depressed demand for US goods has slowed the reallocation within the tradables sector that neoclassical theory would predict.

While this is an interesting idea, and probably plays some part in what’s been happening, I consider the most likely explanation (and the larger story here) to be that US labor markets are not as flexible as we once thought. The neoclassical assumption of ease of labor mobility seems to be particularly under fire in recent research. As with the China shock,, research regarding the aftermath of the Great Recession also suggests that people find it hard to leave economically depressed areas.  Furthermore, income convergence among US states has declined due to rising housing costs in the highest productivity areas. For the hundred years from 1880 to 1980, people in the US migrated from poor areas to rich areas. Nowadays, if people move at all, they tend to go to areas where housing costs are the lowest (which tend to be poorer). In this vein, I highly recommend Ryan Avent’s The Gated City and/or Matt Yglesias’ The Rent is Too Damn High. Other research regarding the aftermath of the Great Recession also suggests that people find it hard to leave economically depressed areas.


The transferability of human capital across industries is probably lower than assumed in the neoclassical model as well. Frictions like occupational licensing, in addition to reducing interstate mobility, make it harder for people to switch to other kinds of relatively low skilled labor without spending significant time and money on certification (jobs requiring a license in some states include florist, barber, and scrap metal recycler).  


To sum up, while the costs of trade are more concentrated and more intense than was previously thought, it is still unambiguously the case that trade with China has been a net good for humanity. Hundreds of millions of Chinese have been lifted out of poverty, and Americans have been able to enjoy substantially cheaper goods. The real issue here is how to deal with the distributional impact of trade to ensure everyone can benefit, which I hope to discuss in a later post.



3 thoughts on “Labor Markets, Trade, and the China Shock”

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s