Category Archives: Measures, Statistics & Technicalities

What we don’t learn from looking at exports/GDP

I’m afraid that I found “The Quiet Driver of Economic Growth: Exports“, a NYT Economix post by Binyamin Appelbaum, to be more confusing than illuminating. In this post, I’ll try to explain why one must be careful in interpreting a number of economic statistics.

Appelbaum writes:

The estimates of the nation’s economic performance last year, released Friday, highlight a striking trend: Exports have never been more important.

Foreign buyers purchased more than $2 trillion in goods and services, the first time exports have topped that threshold. And those exports accounted for almost 14 percent of gross domestic product, the largest share since at least 1929.

We usually talk about exports alongside its opposite number, imports, and since the United States buys much more than it sells – our “trade deficit” — the general impression is that foreign trade is a drag on the economy. But that tends to obscure the importance of exports, which have accounted for about 10 percent of G.D.P. over the last two decades and, since the recession, considerably more…

Much of the rise in exports is a consequence of domestic problems… This is a good thing on the whole. The ability of American companies to make money in foreign markets is helping to offset the pain of those domestic problems.

I found this confusing in three senses:

  1. In purely accounting terms, GDP depends on net exports, not gross exports.
  2. In compositional terms, the export-GDP ratio doesn’t tell you if international commerce is offsetting domestic problems.
  3. The key phrase “exports accounted for X% percent of GDP” is meaningless at best and misleading at worst.

National accounts

To the extent that gross domestic product is our measure of economic performance, should we think about net exports or gross exports? Recall the expenditure definition of GDP:

Y = C + I + G + X – M

If you want to talk about — in accounting terms, not causal terms — what’s happening to US GDP, then net exports are informative. They appear on the right-hand side. When you talk about gross exports while holding gross imports constant, you are losing information. If X and M both increased by the same amount, then GDP would not increase, but X/GDP would rise.

Suppose that I were describing a firm’s economic performance to you. If we had an accounting definition of our performance that said

corporate profits = revenues – costs,

would the following claim seem reasonable? “We usually talk about revenues alongside their opposite numbers, costs, and since the company buys much more than it sells — our ‘negative profits’ — the general impression is that doing business is a drag on the firm. But that tends to obscure the importance of revenues, which have accounted for 110 percent of (the absolute value of) net profits…”

If you care about the international component of GDP, you are losing information when you switch from looking at net exports to solely considering exports. If you look at the BEA press release, you learn that real exports grew 4.7% and real imports grew 4.4%. But recall that we run a trade deficit, so real imports are growing from a larger base. If we go to table 3 of the full BEA announcement (pdf), my reading is that net exports moved from -$562b in the third quarter to -$582b in the fourth quarter. If I’m reading the table correctly, then net exports actually fell. That means that the way we usually talk about trade, which looks at net exports, tells you something different than what is implied by looking at gross exports (implicitly holding imports constant).

Are exports offsetting domestic problems?

Exports as a share of GDP is a ratio. If exports stay the same while GDP shrinks, the exports-to-GDP ratio will rise. Is that a sign of exports offsetting domestic problems? I suppose that it is if the counterfactual is that exports would shrink at the same rate of GDP. But if net exports actually fell, then the increase in the trade deficit “reduced” US GDP (in accounting, not causal, terms), so exports/GDP seems like the wrong statistic to study.

What do exports “account for”?

Applebaum writes that “exports accounted for almost 14 percent of gross domestic product” and that we’ve negleted “the importance of exports, which have accounted for about 10 percent of G.D.P. over the last two decades.” I do not know what the phrase “accounts for” means in these statements.

It’s true that Y = C + I + G + X – M, so exports are a component of GDP. But when I read “accounts for”, I imagine a decomposition of GDP into pieces that sum to 100%. That’s not true when you talk about gross exports. We’re back to the distinction between gross values and value-added measures that I have repeatedly emphasized. What would it mean to say that “exports account for 223% of Hong Kong’s GDP“?

I would suggest that exports/GDP is meaningless as a measure of how international commerce has benefited the US economy during the last quarter. At worst, the “accounts for” language might cause readers to interpret the measure as representing a decomposition of GDP’s components.

Conclusions

Be careful with economic statistics! There are important differences between gross exports and net exports and between gross value and value added.

I’ve tried to be careful here, but I may have read Applebaum’s post or written my post too quickly, so if I’ve made an error in handling statistical definitions or the BEA data, please point it out in the comments. Thanks!

Caveats

I’ve tried to write carefully, but there’s a danger that readers might think I’m treating “net exports” as a scorecard for US economic performance. I am certainly not saying that exports are good and imports are bad. Remember that the current account deficit is the amount by which domestic investment exceeds domestic savings. These outcomes are jointly determined in general equilibrium. My story about “net profits” was an accounting analogy, not an economic analogy.

Addendum (28 Jan, 12pm): Here’s my Twitter exchange with Appelbaum. It doesn’t change anything I said above.

Cross-country wage comparisons

On Saturday, I listened to Orley Ashenfelter’s AEA presidential address about cross-country wage comparisons. For a few years, Ashenfelter has been collecting data on “McWages“, so as to “to measure wages for virtually identical jobs, producing identical products in firms with identical technology.” In making these comparisons, he deflates the McDonald’s wage by the price of a Big Mac, thereby calculating the real producer wage.

Yesterday, the Atlantic’s Richard Florida had a post titled “Which Countries Pay Blue Collar Workers the Most?” It featured this BLS table:

Country Pay for Time Worked Total Hourly Compensation
1. Norway NA $57.53
2. Switzerland $34.29 $53.20
3. Belgium $24.01 $50.70
4. Denmark $34.78 $45.48
5. Sweden $25.05 $43.81
6. Germany $25.80 $43.76
7. Finland $22.35 $42.30
8. Austria $21.67 $41.07
9. Netherlands $23.49 $40.92
10. Australia $28.55 $40.60
11. France $21.06 $40.55
12. Ireland $26.29 $36.30
13. Canada $24.23 $35.67
14. United States $23.22 $34.74
15. Italy $18.96 $33.41
16. Japan $18.32 $31.99
17. United Kingdom $21.16 $29.44
18. Spain $14.53 $26.60
19. Greece $13.01 $22.19
20. New Zealand $17.29 $20.57

What does this table mean? Florida writes:

A quick look at the table above suggests that the level of compensation provided to manufacturing workers reflects a nation’s overall level of economic, social, and human development. And that is indeed the case, according to a simple statistical analysis by my colleague Charlotta Mellander.

Manufacturing compensation is closely related to productivity (measured as economic output per capita), global economic competitiveness and overall human development as well as my own Global Creativity Index. This is all in line with basic economics. And manufacturing compensation and wages are higher in nations with higher levels of education and where greater shares of the workforce are employed in knowledge, professional and creative jobs. In other words, manufacturing compensation and wages rise as nations become more post-industrial. Higher manufacturing compensation is also related to lower levels of inequality and higher levels of happiness.

Manufacturing workers are paid the best in the most advanced nations, places that boast advanced safety nets, generous benefit systems and high productivity. Post-industrial economies might not have the most manufacturing jobs, but their workers are the best paid. Instead of adopting a low-road strategy of trying to reduce manufacturing costs and wages in order to compete with China or other emerging economies, the U.S. would be better off with a high-road one, promoting policies that improve innovation, skills and productivity.

I think that we learn a lot about cross-country wage comparisons by thinking about what this table does not mean.

Does this table rank countries by the welfare of their blue-collar workers? No. Welfare depends on real consumer wages, not nominal wages, so a welfare comparison would necessitate deflating these nominal wages by local prices. For example, Switzerland is a notoriously expensive place to live; its price level is about 1.5 times that of the US. Those interpreting the table as saying that a US-to-Switzerland migration would raise their wages by 50% would be disappointed when they discovered the accompanying 50% price increase. So this table isn’t about workers’ welfare.

Does this table rank countries by their manufacturing TFP? No, for many (potential) reasons. For example, worker quality may differ considerably across countries. Suppose that all these countries are producing the same goods using the same technology, but different countries’ workers embody different numbers of efficiency units of labor. You’ll then observe substantial wage variation even if the unit cost of labor and manufacturing TFP are identical across countries.

Does this table rank countries by their labor productivity in manufacturing? It would if you believe we’re in a world of factor price equalization so that differences in wage rates must reflect differences in workers’ labor productivity. But are these workers making the same product using the same technology? Are enough factors of production sufficiently mobile to put us in the FPE set? Can large trade costs support differences in unit costs? And so forth.

[By the way, manufacturing employees aren’t all “blue-collar workers”. There is cross-country variation in the white-collar-blue-collar ratio of manufacturing, which will move the average hourly compensation measure.]

The BLS measure “hourly compensation costs in manufacturing” is a straightforward number, but cross-country wage comparisons are not a straightforward economic concept. Richard Florida suggests that we understand something about it by looking at its correlates. I would suggest that teaching students what this table does not mean may convey even more economic lessons.

When trade raises welfare and lowers measured GDP

This nifty note by Bajona, Gibson, Kehoe, and Ruhl points out that there may be little connection between real GDP and welfare; in fact, welfare-improving trade liberalization may lower measured real GDP. Here’s a simple example in the Heckscher-Ohlin setting:

The intuition behind the decrease in measured real GDP for the autarky to free trade scenario is simple: given factor endowments, the base-year production pattern in country i is the optimal production pattern for country i at the base year prices among all feasible production plans… Any deviation from that production pattern will lower the value of production at those prices.

The global trade surplus

The Economist on Exports to Mars: “The world exported $331 billion more than it imported in 2010, according to the IMF’s World Economic Outlook… Either the current-account deficits of countries such as America are being understated or the surpluses of countries like China are being overstated, and by a rising amount… Indeed, the global “surplus” now exceeds China’s.”

Made in a series of places

What fraction of your good was made in China when the label says “Made in China”? From the FRB-SF:

Goods and services from China accounted for only 2.7% of U.S. personal consumption expenditures in 2010, of which less than half reflected the actual costs of Chinese imports. The rest went to U.S. businesses and workers transporting, selling, and marketing goods carrying the “Made in China” label. Although the fraction is higher when the imported content of goods made in the United States is considered, Chinese imports still make up only a small share of total U.S. consumer spending…

Table 1 shows that, of the 11.5% of U.S. consumer spending that goes for goods and services produced abroad, 7.3% reflects the cost of imports. The remaining 4.2% goes for U.S. transportation, wholesale, and retail activities. Thus, 36% of the price U.S. consumers pay for imported goods actually goes to U.S. companies and workers.

This U.S. fraction is much higher for imports from China. Whereas goods labeled “Made in China” make up 2.7% of U.S. consumer spending, only 1.2% actually reflects the cost of the imported goods. Thus, on average, of every dollar spent on an item labeled “Made in China,” 55 cents go for services produced in the United States. In other words, the U.S. content of “Made in China” is about 55%. The fact that the U.S. content of Chinese goods is much higher than for imports as a whole is mainly due to higher retail and wholesale margins on consumer electronics and clothing than on most other goods and services…

If we take into account imported intermediate goods, about 13.9% of U.S. consumer spending is attributable to imports, including 1.9% imported from China. Since the share of PCE attributable to imports from China is less than 2% and some of this can be traced to production in other countries, it is unlikely that recent increases in labor costs and inflation in China will generate broad-based inflationary pressures in the United States.

Previous installments:

A non-linear revisiting of Rose (2004)

Pao-Li Chang and Myoung-Jae Lee look at the WTO’s impact on trade flows without assuming linear functional forms for trade frictions. This is forthcoming in the JIE:

This paper re-examines the GATT/WTO membership effect on bilateral trade flows, using nonparametric methods including pair-matching, permutation tests, and a Rosenbaum (2002) sensitivity analysis. Together, these methods provide an estimation framework that is robust to misspecification bias, allows general forms of heterogeneous membership effects, and addresses potential hidden selection bias. This is in contrast to most conventional parametric studies on this issue. Our results suggest large GATT/WTO trade-promoting effects that are robust to various restricted matching criteria, alternative GATT/WTO indicators, non-random incidence of positive trade flows, inclusion of multilateral resistance terms, and different matching methodologies.

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Things I’m reading

Richard Baldwin & Simon Evenett, Next Steps: Getting Past the Doha Round Crisis, VoxEU eBook, May 28: A number of former ambassadors to the WTO present suggestions for how we might get out of the Doha dilemma in which negotiators neither make progress nor are willing to kill the round. The task is identifying a way to make a “Doha down payment” and then head for the exits.

Susan Houseman, Christopher Kurz, Paul Lengermann, and Benjamin Mandel, “Offshoring Bias in U.S. Manufacturing“, Journal of Economic Perspectives, Spring 2011: In short, the authors say price indices for imported intermediate inputs do not fully reflect the cost savings achieved through offshoring, which means that the real growth of imported intermediates has been understated. Underestimating inputs means overestimating productivity, so that’s bad news for the growth of value added in US manufacturing.

“Made in the world”

In line with my suggestion that labels simply say “made in a series of places”, the WTO has announced a “Made in the world” initiative. It aims “to support the exchange of projects, experiences and practical approaches in measuring and analysing trade in value added.” “Made in the world” should be a valuable initiative, at least until the arrival of interstellar trade.

"Made in the world"

In line with my suggestion that labels simply say “made in a series of places”, the WTO has announced a “Made in the world” initiative. It aims “to support the exchange of projects, experiences and practical approaches in measuring and analysing trade in value added.” “Made in the world” should be a valuable initiative, at least until the arrival of interstellar trade.

Comtrade data in Stata

Markus Eberhardt describes how to pull Comtrade data straight into Stata:

11/03/2011 UN COMTRADE data in Stata: Mitch Abdon of the Stata Daily blog recently suggested a way of combining the UN ComtradeTools and Stata. Comtrade is the International Merchandise Trade Statistics (IMTS) of the UN, which records item-level trade for all countries in the world and contains around 1.8 bn observations from 1962 onwards. Access to this data is free, but for technical reasons a maximum of 50,000 observations per query (even more reason to use the Stata Daily application). Having installed the software which allows one to download Comtrade data (registration/subscription required for access) there are a number of simple steps to pull this data directly into Stata and save it. In fact, the entire process is run from within Stata once everything is installed. Since I had some minor trouble setting up and getting this tool to work I’ve written a simple Stata 10 do-file with additional information.