Inequality as a brake on technological progress, productivity and growth

Technology and trade: two interconnected drivers of inequality

As mentioned above, inequality is the result of a mixture of factors that overlap over time and that, by stratifying and interacting with each other, characterize a society. Among these drivers, we clearly define the terms of technology, but a little mention to trade is essential since these two determinants are intricately woven in this context. What is more, it is important to highlight that the study of technology has been approached by many economists also as an alternative hypothesis to free trade which has not always been able to explain much of inequality.
To introduce the topic, a famous economist for his studies on trade theory and international economics should be mentioned: Paul Krugman. He argues that market liberalization has had a measurable effect on the growth of inequality in the United States. In particular, he attributes this tendency to increase in trade with poor countries and the fragmentation of the means of production, resulting in increased mobility of unskilled labour. For example, according to findings in one of its main papers (“Globalization and the Inequality of Nations”), when transport costs are high in a certain economy, all countries tend to autonomously produce what they need through their technological resources. On the other hand, a difference in income is spontaneously created at the territorial level when costs come down until a certain threshold: the periphery undergoes a decline in real income. If the decrease in costs is even greater, there is a convergence of real incomes, so that gains are received by the peripheral nations and losses by the core ones (Krugman, Venables, 1995). However, Krugman and Venables have always been aware that inequality depended on other factors as well and that other kinds of inequality can be affected by trade. Two years later, Katz, Freeman and Borjas studied the effects of trade from a different point of view. They focused also on immigration and found that it has had a marginal negative impact on the economic condition of low-skilled workers. Trade has had small effects on the overall implicit labour supply of the less skilled, but its impact is greater if the economic activities replaced by imports are assumed to employ technologies comparable to the less skilled structures of US manufacturing industries (Borjas, Freeman, Katz, 1997). Even on this occasion, they speculated that the rest of the inequality seemed to be due to other factors. In any case, it is necessary to start from two milestones as the Heckscher – Ohlin model and the correlated Stolper-Samuelson theorem to fully understand how trade can affect inequality and why many economists preferred to analyse technology as an alternative factor in explaining the change in income distribution. Differences between countries in work equipment, physical capital and land (factors of production) create production differences in this model. By hypothesis, two countries with the same technology and the same preferences are considered. This means that by having the same technology, each country will have a comparative advantage in producing the commodity whose production is relatively intensive of the relatively abundant factor. As regards with same preferences, the two countries consume equally. Openness to trade generates inequality: trade increases the relative price of the good of comparative advantage. As a result, there is an increment in the relative production of this commodity and a simultaneous reduction in its relative consumption. So, according to the Stolper-Samuelson theorem, in the long run, when all factors are mobile3, an increase in the relative price of a good causes the real income of the factor employed intensively in the production of that good to increase and the real income of the other factor to decrease. The country where a factor is relatively abundant exports the goods whose production is relatively intensive in that factor. Conversely, it imports goods that are relatively intensive in the relatively scarce factor of production in the country. Over the past 40 years, countries such as South Korea, Mexico and China have exported unskilled labour- intensive goods to the United States. At the same time, income inequality in the United States has grown, as the wages of unskilled workers have increased more slowly than those of skilled workers. However, a direct causal link between the two events cannot be taken for granted.

The Heckscher-Ohlin model predicts that owners of relatively abundant factors will gain from purchase and sale of goods, while owners of relatively scarce factors will lose, but the evidence in its favour does not seem to support all these aspects (Leamer, 1995). First of all, under this framework, a between industry phenomenon is covered, but the real results show that the rise in the proportion of skilled workers is within the industry. Secondly, the fact that the drop in skill differentials occurs in less-developed countries has also not been verified. Third, price trends across different industries did not suggest that trade was important for falls in skill demand. Fourth, the magnitudes of the increase in trade with less-developed nations were too small to account for much of the change in wage inequality. Finally, even if the model were correct, trade represents only a limited fraction of the US economy and therefore its effects on prices and wages should be limited. Moreover, technology is strongly correlated with the growth in demand for more skilled workers in just about every country. Despite numerous criticisms of this model, some empirical evidence has demonstrated that trade and technology are jointly fundamental determinants of inequality. In this respect, Feenstra and Hanson had two objectives: illustrating the rise in the share of wages paid to skilled workers in the US manufacturing sector in the period 1979-1990; also, they examined the augmentation of the relative wages of skilled workers by having 447 observations. To do this, a regression relating to offshoring has been carried out and the intermediate inputs imported from each sector have been used as explanatory variables4. The independent variables that refer to technological progress are the high-tech capital5 in relation to the total installed capital and the fraction of the capital investment in high-tech computers or tools. As for the evidence on the share of skilled labour wages, the variation in the share of wages paid to skilled workers in the period under consideration has been set as the dependent variable. Instead, the other part of the regression is characterized by offshoring, the ratio between capital and production, the production itself and skill-biased technological change. The results report that offshoring and new technologies are both important. Regarding the evidence on relative wages, the assessment of the functional relationship existing between variables has been divided into two phases to answer the research question. First, the impact of offshoring and technology on prices has been estimated. In the second step, the estimate of the variation in the prices of the factors attributable to the various components has been presented. Then, the difference between the impact on skilled wages and the impact on unskilled wages has been calculated. Even in this case, results prove that the growing inequality between skilled and unskilled labour can be explained by both offshoring and skill-biased technological change (Feenstra, Hanson, 1999).
Furthermore, emphasis has been given to another interesting aspect of the relationship between trade, technology and inequality: technology, innovation and their spread are partly endogenous because they are stimulated by trade. Therefore, trading is indirectly significant for changes in the labour market: it is the technological change that modifies the structure of the labour market. It particularly can be seen as a cause of the shift in the demand for more skilled workers. The differential growth of Chinese imports between different sectors in 12 European countries between 1996 and 2007 has been analysed by Bloom et al. to develop this topic. It has been possible to look at the impact of trade in low- wage countries on technological change by processing data on that sample. Meticulous work, which included an in-depth investigation of the regressions of technological indicators in relation to the normalized growth of Chinese images has been carried out for each country. The greatest positive correlation is that concerning the sectors most exposed to the competition of these images and technological changes. The statistically significant effects are also economically relevant to the extent that trade with China has been shown to cover about 15% of the European technological update between 2000 and 2007. The result describes a reality in which approximately half of the effect of trade on technology has been a sort of reallocation where low-tech firms have failed to scale and have been forced to abandon the market because of Chinese import competition; but, at the same time, the latter reallocated employment between firms towards more technologically advanced firms. The other half of the impact has been caused by the same companies that have faster technical changes, such as greater investment in research and development or the production of more patents: there has been an increase in technological change within firms. In essence, trade from developing countries, such as China, creates additional dynamic benefits through increased productivity, but it also has major indirect effects on the labour market (falls in employment, profits, prices and the share of unskilled workers) thanks to its impact on technological change (Bloom et al., 2011; Van Reenen, 2011).