Using the geographical distance as a single independent variable in
our first model, we find an explained variance of 17 percent in 1994. The
negative estimate for b = -.8274 indicates that distance and transportation
costs still matter in the world trade of 1994. A closer look at the visualization
of the errors reveals, that especially the large trade flows are heavily
underestimated in this model. For the large traders (symbolized with the
size of their spheres, respectively the pies for their total imports (top)
and exports (bottom), we find, that almost all of their trade is underestimated:
large countries trade more than can be estimated with the knowledge of
the distance of their trading partners. The reverse is true for small countries.
Model 2 corrects this wrong specification be introducing country size into the
model. We additionally take the GNP of both trading partners into account.
Such a model usually creates the core of a gravity model: "Flows in
human geography are often termed spatial interactions, and a spatial interaction
model is an equation that predicts the size and direction of some flow
(the dependent variable) using independent variables which measure some
structural property of the human landscape." (Thomas/ Huggett 1980).
The basic principle of a gravity model is Newton's law of gravity. They commonly assume that large objects exhibit a greater `pulling power' than small objects and that close objects are far more likely to be attracted by each other. Gravity models are known to produce good fit when estimating the amount of goods traded between countries. They assume that the trade flows rise with the size of the GNP of both countries: while two large neighboring countries are expected to have the largest amount of trade, the volume is expected to decrease with the growing distance by a factor b as estimated in the model.
We have experimented with the size of exporting/importing countries and larger/smaller countries respectively without finding any significant differences. Hence, size differentials and especially the size of the smaller country may be less influential on actual trade flows than economists usually seem to believe. The effects of the GNP are given by the parameters c and d.
Including the GNP of all countries to estimate the trade flows dramatically
improves the explained variance to 60 percent for the 1994 model and increases
the number of (almost) correctly estimated flows from 238 to 325 (as can
be read from the distribution in the upper right). While the quality of
estimates has improved for many countries, we find the trade between the
US and Japan still to be underestimated with this second model. This is
also true for much of the trade in the Asian region and for the trade from
Asia to the USA. Therefore, the third model includes a dummy for all bilateral
trade occurring between countries located on the same ocean: either the
Pacific or the Atlantic. This allows to estimate the beneficial effect
of maritime trade routes and their lower transportation cost. For both
variables we expect the signs of the coefficients to be positive, indicating
higher trade volumes to occur between countries that profit from maritime
The inclusion of maritime trade improved the model further to 62.8 percent of explained variance and improves especially the estimates for flows that were miscalculated in model 2. A separate estimate of the two major oceans displays that the parameter estimate for the trade in the Pacific Rim is higher than the estimate for the Atlantic (0.5072 versus 0.3811). Most of the shipping costs seem to be a result of loading and unloading.
While the estimate for the trade between Japan and the US is now only moderately misrepresented (to low), the trade between Hong Kong and China and somewhat more surprisingly also the trade between Korea, Singapore and Malaysia are consistently estimated too low. We correct further imperfections by including a border dummy for all dyads of countries sharing a common border. The coefficients are expected to be positive. It is more likely that neighboring countries have higher trade volumes. Taking the increased trade volumes between neighboring countries into account, the overall model improves to 64 percent of the explained variance. While the increase in trade for neighboring countries is found to be quite strong, it is, however, much smaller than the estimate for the impact of the overall distance. Looking at the errors after removing the common border effect from the errors, we still find that the trade in Asia is underestimated to a considerable degree, namely between Hong Kong and China but also the trade between and with Malaysia and Singapore.
Our final approximation also includes dummies for different world regions and allows us to access the degree to which regional trade integration exists in different geographical areas, discounting all explanations that we have introduced through the use of the less complex models. The estimates for the different regions provide information about the extent local economic integration leads to more trade in specific world regions than would be expected form the pure knowledge of distance, size of GNP, maritime and common borders alone. Such an estimate of local integration slightly differs from studies that simply relate to the growth of local trade only. The degree of local integration as it is expected for regional economic areas, the EU, the NAFTA, and the Asian members of APEC respectively denoted by FTA-dummies leads us to expect positive parameter estimates.
We find a further improvement of our model. 69 percent of all variance in world trade is now explained and a correct estimates for more than 339 flows is given.
The intraregional trade estimates are strongest for Asia (0.4851), and are not significant for North America (0.2085) and Europe (-0.1706). Evaluating the error terms of this fifth model, in which now all regional effects are discounted, almost all flows are estimated with modest distortions only. Though this is the most improved model advanced in this article, there still exist some systematic errors as the visualization shows.
As the estimate for the trade between Hong Kong and China has improved by treating it as intra-Asian trade, most of the imperfections of the fifth model are still connected to Hong Kong. This effect of Hong Kong's harbor function for mainland China diminished with the Chinese unification. Furthermore, underestimation also occurs for the flows between the countries of the old British Empire, respectively the Commonwealth countries, namely Great Britain, Hong Kong and Australia. This leads us to suspect a language effect of international trade: Trade between countries of a single language trade more, an effect that seems to last even in a `globalized' world economy (language is controlled in Plümper 1998).
The results calculated from the data is exhaustively discussed in another paper (Plümper 1998). We nevertheless present the estimated coefficients in the following table to show that the model leads to fairly reasonable and interesting results. The reported results are by no means trivial.
Table 1 shows that all three theories of global economic integration
discussed in section 2 help to explain some aspects of global economic
processes, while others remain unexplained.
Globalization theory nicely explains the decline in the estimated parameter of logDISTij between 1984 and 1992. However, it is unable to explain why the trade limiting effect of sheer distance declines as rapidly as it does and is even less well-equipped to specify why the negative effect of distance increases between 1992 and 1994. Globalization theorists face a crucial challenge in explaining this aspect. If economic processes were truly global in their character and were the effect of an exogeneous easing of international economic transaction, the estimated coefficients of the three dummies for interregional trade, EU-AS, AS-NA, NA-EU, should be increasing, thereby indicating that interregional trade is growing (in relative terms), simply because the negative impact of distance on trade diminishes.
Regionalization theory also explains some aspects and ignores others. The rapid increase in the estimated coefficient for intra-North.American trade, the growing importance of trade between neighboring countries between 1980 and 1992 supports the regionalization hypothesis. However, the results remain puzzling. The degree of Asian integration sharply declines after 1990, western European integration peaks in 1986 and - most puzzling - the estimated coefficient of EUROPE is much smaller than the ASIA coefficient. This seems to indicate that the assumed superiority of European integration is partly misleading, at least if one controls for country size, distance and borders. Only if we add the border effect to the regional integration effect the estimated coefficient reaches the size of the ASIA coefficient.
Economic imbalances theory perfectly predicts the sharp increase in the AS-NA coefficient. Trade between Asian and North-American countries increases as the American twin deficit worsens. Moreover, since European saving figures are below its Asian counterparts, economic imbalances also nicely predicts that a similar increase does not take place between Europe and North-America.
Tu sum up, we gain somewhat mixed results. Each of the three existing theories explains only very small parts of the story of global economic integration. Hence, we should be far from being satisfied with existing reductionistic theories.
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