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Introduction The previous chapter provided an array of evidence that income inequality has been rising for some time in many OECD countries, including in those where it was formerly relatively low, and that it remains high, and is even rising, in many developing countries and emerging market economies. In all countries, there are also major differences in non-material outcomes between different socioeconomic groups. Everywhere, those at the upper end of the income distribution have a greater probability of obtaining a job, having a high level of education, being healthy and having a high life expectancy, and of living in an unpolluted environment, or, more generally, in a place where access to jobs and the benefits of society lead to a higher quality of life. In general, worse outcomes along the non-income spectrum are correlated with being in the lower levels of the income distribution.
This chapter discusses the main drivers of rising income inequalities in most OECD countries, as well as in several developing countries and emerging market economies, and proposes a multidimensional policy framework for Inclusive Growth building on the OECD’s work on wellbeing, income inequality and pro-growth structural policies.
2.1. Why have inequalities risen?
Drivers of inequalities in OECD countries In OECD countries, the single most important driver of rising income inequality has been greater dispersion in wages and salaries. Earnings account for about three quarters of household income among the working-age population (OECD, 2011a). In most cases, as discussed in Chapter 1, the earnings of the richest 10% of employees have increased more rapidly than those of the poorest 10%.
There are a number of factors behind this trend:
Globalisation is often said to be the main culprit for rising wage inequality and unemployment, but data suggest that its effect has been limited, at least in the OECD area (Box 2.1). Some feared that low-income workers were disproportionately affected by import competition, and that the offshoring of activities in the tradable goods and services sectors had decreased the demand for less-skilled labour. Increased imports from low-income countries tend to heighten wage dispersion, but only in countries with weaker employment protection legislation (OECD 2011a). OECD analysis (OECD, 2013a, and OECD, 2011a) suggests that rising trade integration has had a limited impact on wage inequality and employment. The impact of globalisation on inequality has been minor compared with that of changes in technology (Jaumotte et al., 2008).
Box 2.1. Global Value Chains (GVCs): a new optic for studying trade and inequality?
The consensus view in the inequality literature is that globalisation contributed to about 20% of rising wage inequality and that technological change has been more important than trade in causing changes in income distribution (WTO, 2008; and Newfarmer and Sztajerowska in OECD, 2012e). Yet the conclusion on the modest impact of trade is being increasingly questioned in the context of the rise of emerging economies and the growing international fragmentation of production (e.g. Krugman, 2007).
Differences in productivity and preferences drive international trade and result in efficiency gains and higher aggregate income, whereas trade distortions can be a source of both economic inefficiency and inequality. They lead to inequality within and across countries through the effects of tariffs, non-tariff barriers (NTBs) and traderelated regulations which are unevenly distributed across different economic sectors and activities; differences in market entry barriers and incentives to rent-seeking along different sectors and segments of Global Value Chains (GVCs); and policies that discriminate by geographical origins of trade, such as is the case with some regional trade agreements (RTAs). In all cases, the intention is to generate or preserve rents.
Kaplinsky (2001) argues that when segments or actors within a value chain are protected from competition they will enjoy higher rents and thus capture a higher share of value added. Additionally, value chains usually involve some degree of ‘governance’ with certain key actors within the chain taking responsibility for the division of labour across different segments of the chain, and for its evolution. Thus, it is important how and on what terms a producer participates in the global economy (e.g. buyer-driven chains in textiles and clothing or producer-driven chains in motor vehicles manufacturing). Finally, the effectiveness of value chains arises from systemic efficiency;
namely closer cooperation between links in the chain rather than improving the efficiency of individual links.
These characteristics of GVCs affect the distribution of value added along the chain and thus the distribution of income across and within countries. According to Kaplinsky (op. cit.) barriers to entry and competition are key determinants of the distribution of rents, with those who command rents (e.g. associated with their brand name recognition or copyrights), or who have the ability to create new domains of rent, tending to gain, and those stuck in activities with low barriers to entry tending to lose out. The ability to identify rent-rich activities along the whole chain of value-added then provides the key to understanding the global appropriation of the returns to production.
Along the same lines, Brewer (2011) stresses important links between the GVC and the analyses of global income inequalities. The traditional application of the GVC approach was to investigate the geographical dispersion, governance and institutional context of a given chain to illuminate the ways in which the most powerful actors and agencies organise the chain for their own benefit. More recently however, GVC analysis has focused on the concept of “upgrading” namely ways of improving the competitive position of particular value chain participants and capturing higher shares of value added, with an implicit assumption that such upgrading can aid national development. Such upgrading can involve moving into more technologically demanding manufacturing processes, but also the processing of agricultural and metal and mineral products with higher value-added.