To organize thinking about how distance along multiple dimensions affects the relationships between any two countries, I have assembled these and other dimensions of difference flagged by research into the CAGE framework depicted in table 3-1. The columns group dimensions of difference into these four CAGE categories (cultural, administrative, geographic, and economic) and the rows track the distinction between external and internal distance cited earlier.
Perhaps most fundamentally, table 3-1 recasts differences—the focus of most of the prior discussion—into distances. This reflects the fact that it isn't enough just to register differences: leaving it at that would bog us down in the details of more than ten thousand country pairs. Rather, we need to appreciate degrees of difference or distance in order to distinguish what is near from what is far. This is a more complicated but ultimately more fruitful notion of distance than either World 1.0 (which sees foreign countries as equally far) and World 2.0 (which sees them as equally close). As we'll see in the next section, the multidimensional CAGE distance construct does such a good job of explaining bilateral trade patterns and other important cross-border flows that it even suggests a “law” (or, more modestly, a heuristic) of distance. This broadens geographer Waldo Tobler's First Law of Geography, “everything is related to everything else, but near things are more related than distant things” to also include cultural, administrative, and economic distance.40
Second, it is worth acknowledging that the columns do tend to blur into each other in some respects. Linguistic linkages from the cultural column are clearly correlated with colonial-era ties from the administrative column. And there is some ambiguity about whether to slot the availability/unavailability of transport and communications infrastructure into the geographic column or the economic one. The simple summary point that I would make is that the bullet points in table 3-1 remain relevant no matter which columns we place them in; the arrangement here represents just one possibility.
TABLE 3-1: The CAGE distance framework
Cultural distance
Administrative distance
Geographic distance
Economic distance
External distance (bilateral/
plurilateral/
multilateral attributes)
Different languages
Different ethnicities/lack of connective ethnic or social networks
Different religions
Differences in national work systems
Different values, norms, and dispositions
Lack of colonial ties
Lack of shared regional trading bloc
Lack of common currency
Different legal system
Political hostility
Physical distance
Lack of land border
Differences in climates (and disease environments)
Differences in time zones
Differences in consumer incomes
Differences in availability of:
Human resources
Financial resources
Natural resources
Intermediate inputs
Infrastructure
Supplier/distribution structure
Complements
Organizational capabilities
Internal distance (unilateral attributes)
Traditionalism
Insularity
Spiritualism
Inscrutability
Nonmarket/closed economy (home bias versus foreign bias)
Lack of membership in international organizations
Weak legal institutions/ corruption
Lack of government checks and balances
Societal conflict
Political/expropriation risk
Landlockedness
Geographic size
Geographic remoteness
Economic size
Low per capita income
Low level of monetization
Limited resources, inputs, infrastructure, complements, capabilities
Source: Adapted from Pankaj Ghemawat, “Distance Still Matters: The Hard Reality of Global Expansion,” Harvard Business Review 79, no. 8 (2001): 137–147.
Third, the last column in the list, concerning economic distances, deserves special comment both because discussion of it so far has been relatively limited and because it presents some particular complexities. The earlier discussions did suggest—and the results of the studies summarized in the next section confirm—that cultural, administrative, and geographic distances between countries tend to depress the interactions between them substantially.41 The same pattern holds up for the internal economic factors listed under economic distance in the figure: large countries with low levels of per capita GDP and monetization tend to trade proportionately less than others. But predictions around external economic distance are more mixed: thus, one kind of model suggests that trade should increase as a result of differences in per capita income, while another kind implies that it should decrease.42 I find it efficient to simply look and see.
The most obvious use of the CAGE framework is to force broad-based consideration of the many possible differences between countries instead of simply passing them over, as so often happens. I've seen firsthand that even large international companies are prone to miss out on cultural and administrative differences, in particular. Economists, too, probably share such biases. People gripped by technotrances are likely to overlook geographic differences. And so on.
The rows of the matrix provide a second kind of reminder: they call attention to the internal as well as external dimensions of distance, broadly defined. Faced with the same external realities, countries, companies, or individuals differ greatly in how well they engage with them. Internal distance is relevant at each of these levels—although it takes different forms—and will prove a particularly helpful construct in Part III of this book.
The “Law” of Distance
I have mentioned the research base of the CAGE framework several times now. It consists for the most part of empirical studies—probably more than one thousand have been executed by now—that use “gravity models” to study bilateral interactions. Such models resemble Newton's law of gravitation in linking interactions between countries to the product of their sizes (usually their gross domestic products) divided by some composite measure of distance that incorporates some of the factors listed in table 3-1. I tend to think of them as distance models because what is most interesting about them resides in the denominator term: which types of distance really matter, and how much? Either way, such models explain not only why the U.S.-Canadian trading relationship is so large, but also one-half to two-thirds of all variation in bilateral trade flows between all possible pairs of countries. As a result, they have been described as providing “some of the clearest and most robust empirical findings in economics.”43
To present an example that is based on some of the same information that is relied on elsewhere in this chapter, let me describe the results of a study I undertook. After controlling for economic size, I estimated the sensitivity of trade between all country pairs for which data were available to various types of distance, both at the (cross-industry) country level and at the level of individual industries. I report here the results at the country level.44
To start with geographic or physical distance, a useful stylized fact is that a 1 percent increase in the geographic distance between two locations leads to about a 1 percent decrease in trade between them. Put another way, the distance sensitivity is -1.45 This particular value simplifies the calculations: it implies that trade intensity is inversely related to geographic distance. Applying this coefficient to the U.S.-Canada example, for instance, recall that Ottawa and Washington are only one-tenth as far from each other as the capitals of a randomly selected country pair. So, with a distance coefficient of -1, trade between Canada and the United States should be expected to be ten times as intense for that reason compared to the typical country pair. To say the same thing from a differen
t perspective, U.S. trade with Chile is only 6 percent of what it would be if Chile were as close to the United States as Canada.
Then there are the other dimensions of distance/proximity. I found that two countries with a common language trade 42 percent more on average than a similar pair of countries that lack that link. Countries sharing membership in a trade bloc (e.g., NAFTA) trade 47 percent more than otherwise similar countries that lack such shared membership. A common currency (like the euro) increases trade by 114 percent. And if a country has ever colonized the other, the two countries trade 188 percent more on average (even though many colonial ties were dissolved decades or even centuries ago). Differences in levels of corruption and political stability tend to depress trade volumes. Countries like the United States and Canada that share a common land border typically see 125 percent more trade than two nonadjoining countries—above and beyond the geographic proximity effect discussed earlier. And the baseline estimates indicate that differences in per capita income generally have a positive effect on trade intensities, although that gets reversed in other specifications.46
Interested readers can go to my Web site (www.ghemawat.org) and play around with implications of these and other estimates. One way of summarizing them is, once again, to exclude the continuous geographic distance measure and focus on the five dichotomous ones for which coefficients are reported above. Based on those coefficients, a country pair that matches perfectly across all five should trade twenty-nine times as intensely as a country pair that differs across all five.47 So the difference between near and far matters a great deal as far as trade is concerned—especially when one reckons with the direct effects of physical distance, which were excluded from the calculation.
Scholars have fitted similar gravity/distance models to other flows, including foreign direct investment, cross-border equity trading, sovereign lending, patent citations, phone calls, and migration patterns (not to mention remittances, e-commerce, international air traffic, and even the incidence of wars). None of these flows has been studied nearly as intensively as trade, the traditional focus of international economics, and in some cases, all we have is a study or two to rely on. That said, there are some broad headlines here that I group under the law of distance.
First, geographic distance matters across the board. It was probably obvious—except to World 2.0 extremists—that geographic distance would affect trade (although probably less obvious that the effect would be so large). But it isn't obvious that weightless financial and informational flows should decay as distance increases: one might expect FDI, at least, to increase with geographic distance as it substitutes for trade. Yet decay they generally do.
The estimated sensitivity of financial flows to geographic distance varies between -0.5 and -1.0,48 with FDI and bank lending typically falling off faster with distance than portfolio investment.49 In fact, some studies estimate FDI to be more distance-sensitive than the usual benchmark of -1 for trade. Perhaps even more surprisingly, phone traffic's distance sensitivity also seems comparable to or a bit greater than trade's!50 The distance sensitivity of immigration does turn out to be lower in absolute terms, about -0.25 in one study,51 presumably because of the large interregional flows from East Asia, Latin America, and the Middle East and North Africa to OECD countries (other flows tend to be more intraregional).52 The distance sensitivity of knowledge flows, variously measured, may be slightly lower yet.53 The implications of these variations for how much intensity drops as physical distances increase are quite large.54
The second headline is that other dimensions of distance discussed earlier in the specific context of the trade, particularly cultural and administrative distance, typically reduce FDI, knowledge, and other cross-border flows as well. Thus, one study found that a common language led to 43 percent more bilateral FDI, colonial links to 118 percent more, and common legal origins to 94 percent more.55 In fact, when FDI does take place in spite of significant cultural and administrative distance, it often involves not a solo venture but a joint venture with a local. The discussion of Google in the last chapter, which involved FDI rather than trade, points in the same direction: we saw it wrestling with cultural and administrative differences in particular. Another illustration of sensitivity: if you look at all U.S. companies that operate in just one foreign country, that country is Canada 60 percent of the time (and 10 percent of the time, the United Kingdom).56 This suggests that cultural and administrative commonalities loom even larger for FDI than they do for trade.
A New View of Economic Geography?
Given the broad law of distance, remapping or reimagining the world along those lines seems important—and certainly more important than it would be if just trade were involved, or if flows didn't mostly tend to decay over different types of distance. Of course, a call for a remapping is strong stuff. Yet Paul Krugman, whose seminal work on economic geography won him the Nobel Prize, has argued for just such a shift.
About twenty years ago, Krugman relates, views of the world split harshly between those seeing countries as “discrete economic points, whose location in space is irrelevant”; those who thought “location in space is all and borders are irrelevant”; and those who believed in “the vision of a spaceless, borderless world in which distance had been abolished—not a world that yet exists, but possibly one just over the horizon.” Krugman's conclusion, based on empirical research:
Distance matters a lot, though possibly less than it did before telecommunications. Borders also matter a lot, though possibly less than they did before free trade agreements. The spaceless, borderless world is still a Platonic ideal, a long way from coming into existence. The compromise view isn't as radical as some would like. But it's a significant change from the way most of us viewed the world economy not too long ago.57
I generally agree with this: World 3.0 involves taking an integrative perspective in which both borders and distance matter. More specifically, World 3.0 treats flows as typically declining with distance—and also being subject to discontinuous drop-offs at borders of various sorts. I would, however, place a bit more of an emphasis than Krugman does on distance effects, and not just for their novelty (to traditional trade theory). Figure 3-1 summarizes just one of several studies showing that border effects have decreased substantially over the last few decades, whereas geographic distance sensitivity actually seems to have increased! Shorter average shipping distances for exports point in the same direction.58 In fact, a meta-analysis over a longer time frame suggests that geographic distance effects may actually have gone up relative to a hundred years ago!59 Distance seems to be in robust good health rather than dead.
Figure 3-1: Distance sensitivity and border effects
Source: Thierry Mayer, “Market Potential and Development,” Centre d'Etudes Prospectives et d'Informations Internationales (CEPII) working paper no. 2009-24 (October), 13.
Krugman suggests that this represents a changed view of economic geography if not a new one. World 3.0 certainly distinguishes itself in this regard from World 1.0 and World 2.0, neither of which takes geography seriously: World 1.0 emphasizes national borders while giving short shrift to distance effects and World 2.0 ignores both with its focus on a borderless, spaceless world. But it is useful to remind ourselves that the distinction extends beyond geography to encompass the other dimensions of the CAGE framework as well. And while differences along these dimensions are often (weakly) correlated with geographic distance, there is little to be gained and much to be lost by collapsing them all down to just geography.
Chapter Four
ADDING Value by Opening Up
THE LAST TWO chapters explained why the world isn't as globalized as many people think and analyzed how sensitive actual levels of cross-border integration are to the cultural, administrative, geographic, and economic differences between countries. This chapter explores the case for further integration given such headroom. It looks at how much we might gain by reducing the barriers between countries and further o
pening up.
Of course, thinking about gains from more openness only makes sense within the context of World 3.0. Believers in World 1.0 tend to either ignore cross-border interactions or focus on restricting/reversing them. And those still true to World 2.0 presumably see integration as having proceeded so far that relatively little is to be gained through more openness.
Adopting a World 3.0 perspective, then, let's begin by considering previous estimates of the gains from liberalizing trade. Standard estimates of the gains from the proposals on the table in the stalled Doha round of world trade talks tend to fall in the $50–100 billion range, and gains from complete liberalization of merchandise trade range from less than $100 billion up to $300 billion.1 While those are a lot of billions, even that last estimate appears modest when we recall that in the wake of the financial crisis, banks such as Citigroup and Royal Bank of Scotland individually transferred larger amounts of “toxic” assets into “bad banks,” and trillions were spent on stimulus programs.
More precisely, the estimated gains from the Doha proposals represent roughly 0.1 percent of a $60 trillion world economy, or about $10 for every person on the planet, and even the estimates for complete liberalization amount to only 0.5 percent of world GDP or about $50 per capita. Note that these are also much smaller than estimates based on similar models suggesting that the United States, for instance, could add 8 to 10 percent to its GDP by reforming its tax code.2 Finally, the estimated gains from liberalizing merchandise trade have shrunk since the early 1990s because of rapid tariff reductions in general and growth in relatively open East Asian economies in particular.
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