Dani Rodrik discusses one simple economic theory which suggests that more open trade has contributed to inter-national inequality. Here’s another.
In ‘Shifts in Economic Geography and Their Causes’ (pdf, html), Anthony Venables explains the key concepts of economic geography and some straightforward implications. The core insight, to put it very simply, is that there are increasing returns to proximity in terms of productivity, but also some increasing costs - which is why cities tend to be highly productive and diverse but also frequently more unpleasant, unhealthy or dangerous. ‘First nature’ geography creates exogenous differences between places in terms of productivity, and these “become amplified, as firms move into locations with good geography, and the proximity-productivity relationship causes further increases in productivity”.
This amplification therefore creates much more spatial inequality than is ‘justified’ by natural geography alone. In terms of inter-national differences, Venables argues that these differences are borne mostly by wages, as labour is the immobile factor compared to capital: “Since labor may be a small share of the costs of production there can be a large multiplier effect here. If labor is 10 percent of gross costs, then a 50 percent difference in the productivity of all inputs will translate into a 500 percent wage difference”. Thus economic geography seems to explain a large part of international inequality, though Venables is careful to stress that there are other causes and amplifying factors, such as the endogeneity of institutions.
What about the theoretical case of identical countries? Here, Venables argues that the existence of trade costs means geography can create large international differences out of almost nothing.
Equilibrium outcomes are summarized in Chart 2 [below], which has trade costs on the horizontal axis and real wages on the vertical axis. At very high trade costs the economies have identical economic structures and identical real wages, as indicated. This is because when trade in goods is expensive, supply and demand in each country’s product market (one of the dispersion forces of section II) are the dominant forces which determine the location of activity.
As trade costs fall (moving left on the chart) so the possibility of supplying consumers through trade rather than local production develops, and the productivity-proximity relationship becomes relatively more important. Below some level of trade costs, t* these forces come to dominate, and one of the countries (N in the chart) gains most of manufacturing, and consequently has a high real wage. This clustering deindustrializes the other country (S), which experiences a fall in its real wage. The important point to note is that following this there is a range of trade costs in which the world necessarily has a dichotomous structure. Wages are lower in S than in N, but it does not pay any firm to move to S as to do so would be to forego the benefits of the productivity-proximity relationship arising from the large market and proximity to suppliers that are found in N.
In this model the productivity-proximity relationship derives just from the costs of trading intermediate goods. This means that as trade costs fell further, so the clustering force becomes weaker, and location comes to be determined by factor prices, a dispersion force. This is the era of globalization, in which manufacturing starts to move from N to S and the equilibrium wage gap narrows. Factor price equalization is attained when trade is perfectly free-the death of distance. Of course, the model goes all the way to factor price equalization simply because the only productivity-proximity mechanism captured in the model is trade in intermediates, a mechanism which is switched off once trade is free. If other mechanisms were included, then inequalities would persist.
Also, while trade costs have fallen there is no prospect of them disappearing so that incomes equalise in this kind of (highly stylized) model.
Something else worth thinking about is what these insights from economic geography mean for that treasured tool of many of today’s economists, the cross-country growth regression. If very large disparities in income can result from little or no initial differences in the geography (or policies or institutions) of countries, then the results of analyses regressing growth against these factors might be telling us even less than we thought.