At VoxEU, Shimelse Ali and Uri Dadush talk about the policy implications of how we measure trade flows of intermediate inputs, a topic I’ve been covering a lot recently. They say: “Bilateral trade balances are not appropriately measured, the costs of protection are higher than often understood, trade is more volatile, and the importance of exports as drivers of short-term demand is overestimated.”
Category Archives: Measures, Statistics & Technicalities
WTO: Measuring value added
The last panel of next week’s WTO Global Forum on Trade Statistics will focus on measuring trade in value added.
Discussing the US trade deficit
This paragraph from the Council on Foreign Relations blog is disappointing:
The yearly U.S. trade deficit peaked at 6.4% of GDP in August 2006. It improved significantly after the financial crisis, bottoming out at 3.6% in January 2010. This swing provided a boost to GDP and nudged the U.S. external balance toward a more sustainable level. The deficit then resumed an upward march, reaching 4.3% by November. A closer look at America’s bilateral trading relationships since the deficit high-point in 2006 reveals a significant improvement with many countries, and only a small deterioration with a few others. China – with which the U.S. has its largest deficit – is the conspicuous exception, as the figure shows. 2011 looks set to be a year of yet further-rising trade tensions between the two countries.
First, the discussion of the relationship between the trade deficit and the business cycle is rather unclear. The second and fourth sentences suggest that the business cycle might be driving the trade deficit (the deficit is smaller when growth is down), but the third sentence says that the shrinking trade deficit boosted GDP.
The third sentence is certainly misleading. While it is true in an accounting sense that a smaller trade deficit raises GDP (Y = C + I + G + NX is an accounting identity), that says nothing about a causal relationship. The trade deficit and national income are part of a general-equilibrium system — it’s folly to describe one as causing the other without a clear exogenous shock or a proper GE model. Accounting identities are not behavioral relationships. One could just as easily write NX = Y – C – I – G.
The claim that the dampening of the trade deficit in January 2010 represented a move towards a more sustainable level seems unlikely. Since the income elasticity of trade is greater than one, the drop in global GDP and associated plunge in global trade did flatten out global imbalances. As soon as growth resumed, the imbalances began growing too. This describes an equilibrium comovement, not a direction of causation, but that’s enough to suggest that the January 2010 “improvement” was business as usual, not a move towards smaller long-run imbalances.
Second, the discussion of bilateral trade deficits is misleading. Bilateral deficits do not matter (economically, though politicians seem to care). The canonical analogy for undergraduates is that the professor will have a bilateral deficit with his/her local grocer for the rest of his/her life without any problems (CEA 2004, pdf). Moreover, trade statistics measure gross flows, so China’s role as an assembler of products made by “Factory Asia” destines it to have a bilateral surplus with countries importing finished products. Value-added measures of China’s surplus are substantially smaller. For these reasons, and many more, the discussion should focus on multilateral imbalances.
Are iPhones “made in China”? Measuring value added in trade flows
If you found the Wall Street Journal‘s Wednesday story on gross value vs value added in trade statistics intriguing…
Trade statistics in both countries consider the iPhone a Chinese export to the U.S., even though it is entirely designed and owned by a U.S. company, and is made largely of parts produced in several Asian and European countries. China’s contribution is the last step—assembling and shipping the phones.
So the entire $178.96 estimated wholesale cost of the shipped phone is credited to China, even though the value of the work performed by the Chinese workers at Hon Hai Precision Industry Co. accounts for just 3.6%, or $6.50, of the total, the researchers calculated in a report published this month…Mr. Lamy said if trade statistics were adjusted to reflect the actual value contributed to a product by different countries, the size of the U.S. trade deficit with China—$226.88 billion, according to U.S. figures—would be cut in half.
To correct for that bias is difficult because it requires detailed knowledge of how products are put together.
… then you might enjoy Robert Johnson and Guillermo Noguera’s “Accounting for Intermediates: Production Sharing and Trade in Value Added“:
These adjustments imply that bilateral trade imbalances often differ in value added and gross terms. For example, the U.S.-China imbalance is approximately 30-40% smaller when measured on a value added basis, while the U.S.-Japan imbalance is approximately 33% higher. These adjustments point to the importance of triangular production chains within Asia.
Trade vs aid: Gross value vs value added
Bono and Ali Hewson: If Africa increased its share of world trade by one percentage point, that gain would dwarf all the aid it receives.
Shorter Owen Barder: We care about value added, but trade flows are measured in gross terms. The net benefit of exports is not equal to export revenue; it’s the value added that is some fraction (say, 10%) of the export revenue. The sum of development assistance to Africa will dwarf that number.
Me: Development assistance flows, as reported by their donors, are measured at gross value as well, so we’d need to estimate the value added of development aid before we really made any comparisons.
How big are the gains from trade?
From an interview of Ed Prescott: “People can quantify what gains there are from it [trade]. If you calibrate the models… most people want to get a big number, but a small number comes out.”
Ed explained that the importance of the difference between openness and free trade lies in explaining the big gains that “trade” generates. Empirically we know that periods of openness coincide with periods of strong economic growth and periods of protectionism coincide with recession. Yet the traditional models of trade don’t bear those big-gains results.
There are three theories traditionally used to explain trade, Ed explained:
The first is the Heckscher-Ohlin factor endowments model. China has a lot of low-skill workers so they produce goods that are labor-intensive, and since the U.S. has a lot of skilled workers, we produce goods that are skill-intensive. But the gains according to that model turn out to be small.
The second model is David Ricardo’s comparative advantage. It’s the textbook example: England had a comparative advantage in wool and Portugal had a comparative advantage producing wine, so England produces wool and trades for wine and Portugal produces win and trades for wool. But that model also yields small gains from trade.
Then there is the increasing returns to scale model from Paul Krugman, who use the Dixit-Stiglitz monopolistic competition model to explore the potential gains from increasing returns. Yet that, too, turned out small gains.
So clearly there’s got to be some other reason that trade yields big gains for the economies that engage in it. The answer is that “trade” is about much more than the exchange of goods. With openness, there is diffusion of knowledge.
[This isn’t a transcript, but it’s an accurate paraphrasing of the original audio.]
For two examples of such calculations, I’d look at Bernhofen & Brown (AER, 2005) and Broda & Weinstein (QJE, 2006). The former uses the minimal framework of putting an upper bound on the equivalent variation by looking at autarky prices and a counterfactual import vector. The latter impose more structure by using a CES demand system and look at the gains from new imported varieties.
Now, I won’t dispute that technological spillovers and knowledge diffusion are additional channels offering more gains from economic exchange. But how does Prescott know that the gains from trade are bigger than those estimated using the theories above? What is his benchmark? How could one quantify the gains from trade without using some theory?
WITS is now web-based
Good news for trade researchers! WITS, the World Bank’s World Integrated Trade Solution software used to access Comtrade and TRAINS, is now fully web-based. No software installation required. It used to be Windows-only, which was a bit of a pain for people like me.
Did AGOA work? Identification and export incentives
The former USTR-Africa who designed the African Growth and Opportunity Act (AGOA) preferential trade scheme declares it a “phenomenal success“:
Rosa Whitaker: I think it’s been a phenomenal success. Has it been a panacea for everything in Africa? No, it wasn’t designed to do that. But if you look at the return on the investment, it’s been amazing. It costs the American taxpayer very little – about $2 million a year. In under a decade, exports from AGOA-eligible countries grew over 300% from $21.5 billion in 2000 to $86.1 billion in 2008…
AGOA helped develop an automobile industry in South Africa. In 2000, that industry was exporting about $148 million; it has increased to $1.9 billion in 2008. Car parts exported to the U.S. had an 18-25% tariff. When those tariffs came off for Africa, the assembly part of that manufacturing process moved to South Africa. There are plenty of other examples. Lesotho was exporting $139 million in apparel in 2000; now it’s over $340 million: a 143% increase. Kenya’s cut flower industry expanded from $34 million in 2001 and to exports over $240 million now. Swaziland was exporting $85,000 in jams and jellies in 2000; today it’s $1.6 million. For a small country like Swaziland, that’s important. Then you have Tanzanian coffee and other products. I could go on and on.
Policymakers frequently evaluate programs using this approach — they compare circumstances before and after legislation passed and judge the program based on the difference in outcomes over time. But of course, correlations aren’t very informative about causal relationships.
Economists are interested in the counterfactual — what impact did the program make relative to what would have happened without the program? The most obvious problem with a before-and-after comparison is that steady growth creates improvements over time, regardless of policy changes. For example, Singapore’s Business Times touted that US-Singapore trade had grown nearly 20% since the US-Singapore preferential trade agreement took effect, but US-Malaysia trade grew the very same amount during that period without any US-Malaysia PTA.
Similarly, telling us that African export volumes grew from 2000 to 2008 isn’t very informative, because we naturally expect exports to grow over time as economies grow. (If one wants to suggest that AGOA encouraged greater African openness, the appropriate measure would be the exports-to-GDP ratio.) Identifying the causal impact of AGOA requires a method that distinguishes the increase in exports due to the trade preferences from the counterfactual scenario. (A 300% increase in exports is big, so I’m not suggesting that AGOA necessarily had zero impact. The question is: what share of the increase was due to AGOA?)
In such circumstances, economists often turn to an identification strategy known as “differences in differences“. This involves comparing differences across countries in their differences across time. For example, only some African nations are AGOA-eligible. If African economies receiving preferential tariff treatment from the United States experienced export volume growth that was faster than export volume growth in ineligible economies, we might think that this suggests that AGOA spurred greater exports. However, such a comparison doesn’t constitute valid causal inference in the case of AGOA, because AGOA eligibility was determined according to governance and policy criteria that likely make a difference in economic and export growth. Countries with characteristics making them AGOA-eligible may grow faster than their neighbors due to those characteristics, even without any preferential market access.
Paul Collier and Tony Venables tackled this by taking what is akin to a differences-in-differences-in-differences approach: they looked at the value of a country’s apparel exports to the US relative to its apparel exports to the EU (World Economy, 2007). The thrust of their story is captured by their Figure 1:
Collier & Venables (2007) Figure 1.
African apparel exports to the US increased dramatically faster than such exports to the EU in the early 2000s (even though the EU’s Everything But Arms initiative, which is similar to AGOA, launched in 2001). Collier and Venables also present econometric results in which AGOA apparel eligibility is associated with significantly greater relative exports to the US. A glance at the data on South African automobile exports also suggests that Rosa Whitaker’s story is meaningful in comparative terms: auto exports to the US jumped while exports to the UK and Germany fell slightly.
| Period | Trade Flow | Reporter | Partner | Code | Trade Value | |
| 2000 | Export | South Africa | Germany | 87 |
$538,728,295
|
1
|
| 2000 | Export | South Africa | USA | 87 |
$190,767,522
|
1
|
| 2000 | Export | South Africa | United Kingdom | 87 |
$158,073,103
|
1
|
| 2008 | Export | South Africa | USA | 87 |
$1,867,615,402
|
1
|
| 2008 | Export | South Africa | Germany | 87 |
$485,841,841
|
1
|
| 2008 | Export | South Africa | United Kingdom | 87 |
$139,980,048
|
1
|
Yet such evidence need not imply that AGOA caused a significant increase in exports by eligible countries. The AGOA trade preferences raised both the incentive to export and the relative incentive to export to the US. It is possible that AGOA-eligible countries would have experienced significant export increases even in the absence of the preferential program and the tariff advantages of AGOA only induced them to direct their sales to the US instead of the EU. Such a claim is compatible with the two pieces of evidence discussed thus far: (1) African exports to the US increased significantly after AGOA came into force and (2) AGOA-eligible economies export more to the US relative to the EU.
Collier and Venables (2007) and Frazer and Van Biesebroeck (2007) address such concerns to some degree. For example, the latter show that:
The impact of AGOA on E.U. imports is in column (6). The effects for most product categories are not significantly different from zero. Perhaps surprisingly, where the effect is significant, it is positive. For example, E.U. imports of GSP-Manufactured products, are found to increase by 4%. A potential explanation (among many) could involve spillover effects from the increased U.S. imports.
Note that though this evidence makes the alternative story about export diversion suggested in my previous paragraph rather unlikely, it cannot completely rule it out (perhaps the relative magnitudes aligned so that the size of the total export increase offset the change in relative shares, leaving exports to the EU constant). This demonstrates one of the difficulties of doing causal inference in a non-experimental setting. We have highly suggestive evidence, but, with enough effort, one can conceive of an alternative explanation.
So was AGOA a success? Probably. Economists have both theoretical reasons to expect it would improve African exports and empirical evidence that suggests that it did. Policymakers and other commentators would be more persuasive if they cited comparisons (in the spirit of Figure 1 from Collier and Venables) rather than just presenting the time series of US imports from Africa – say something like “AGOA-eligible countries’ exports to the US grew 300% in the last eight years, substantially more than their exports to Europe”. Better (if imperfect) efforts at identifying the counterfactual distinguish the studies analyzing AGOA from meaningless statistics cited in support of other trade policies.
[I’ve tried to informally convey some ideas about empirical identification issues in the context of AGOA. For a proper introduction to the topic, start with a paper or book that mentions the Rubin causal model, such as Angrist and Pischke’s Mostly Harmless Econometrics or Imbens and Wooldridge (JEL, 2009).]
How big is China?
If you want to think about urban bias in price indices, index number problems, measuring GDP from the expenditure side vs the output side, and the relative size of nations, check out “How Big is China? And Other Puzzles in The Measurement of Real GDP” by Feenstra, Ma, Neary, and Rao.
“Terms-of-Trade Gains, Tariff Changes, and Productivity Growth” (NBER 15592)
The NBER Digest on the work of Robert C. Feenstra, Benjamin R. Mandel, Marshall B. Reinsdorf, and Matthew J. Slaughter:
In the past decade, the U.S. economy clearly enjoyed faster productivity growth than in previous time periods. The authors suggest that the magnitude of this acceleration has been overstated, with a sizable share of the gains actually being accounted for by the benefits of international trade. Their findings indicate that from 1995 through 2006, the actual average growth rates of the price indexes for U.S. imports are 1.5 percent per year lower than the growth rate of price indexes calculated using official methods. Thus, properly measured terms-of-trade gains can account for close to 0.2 percentage points per year, or about 20 percent, of the apparent increase in productivity growth for the U.S. economy over this period.
Trade Diversion 