Stijn Broecke (OECD and IZA)

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Presentation transcript:

Stijn Broecke (OECD and IZA) London Conference on Employer Engagement in Education and Training 2016 Skills and Inequality Stijn Broecke (OECD and IZA)

The gap between rich and poor is at its highest for 30 years, with the top 10% now earning 9.6 times more than the poorest 10%

Economic cost of inequality Earlier arguments: inequality = necessary evil in the pursuit of economic growth (Kaldor, 1957, Kuznets, 1955, Mirrlees, 1971; Lazear and Rosen, 1981) More recently: inequality reduces growth: Redistributive pressures (Persson and Tabellini, 1994; Alesina and Rodrik, 2014) Generates social conflict (Benhabib and Rustichini, 1996; Perotti, 1996) Prevents the talented poor from undertaking profitable investments in physical and human capital (Galor and Zeira, 1993; Banerjee and Newman, 1993) Catalyses financial crises (Rajan, 2010)

Social costs of inequality Lower social and inter-generational mobility (Krueger, 2012) Health and social problems (Pickett et Wilkinson, 2011) Higher crime (Fajnzylber et al., 2002) Weaker social cohesion and trust (Brown et Uslaner, 2002)

Causes of inequality Globalisation Technological change Regulations/institutions Skills Changing family structures Non-wage incomes Tax and benefit systems

Rich literature showing the link between inequality and changing skills needs Skills-biased technological change: rising inequality linked to the fact that the supply of educated workers has not kept pace with the rise in demand for them (Juhn, Murphy and Pierce, 1993; Juhn, 1999; Goldin and Katz, 2008; Autor, 2014) More recent theories of routine-biased technological change maintain a central role for skills in explaining rising wage inequality in the United States (Autor, Levy, and Murnane, 2003; Autor, Katz, and Kearney, 2006, 2008; Autor and Dorn, 2013; Autor, 2015) Other explanations for changing demand for skills: Offshoring (Blinder, 2009) Population ageing (Dwyer, 2013) Organisational changes (Acemoglu, 1999; Bresnahan et al., 2002; Caroli and van Reenen, 2001, Antràs et al., 2006)

But cross-country studies suggest skills matter little to inequality Cross-country differences in wage inequality: Paper Data Method Do skills matter? Devroye and Freeman (2001) IALS Variance decomposition No Blau and Kahn (2005) JMP decomposition Leuven et al. (2004) Katz and Murphy D&S analysis Yes Jovecic (2015) PIAAC Variance decomposition No Pena (2015) JMP decomposition Paccagnella (2015) Unconditional quantile regressions Machin et al. (2016) PIAAC  No 

Survey of Adult Skills (PIAAC, 2012) 166 000 adults (aged 16-65) from 24 countries Tested in literacy, numeracy and problem solving in technology-rich environments Also: individuals’ skills use in the workplace, labor market status, wages, education, experience, and a range of demographic characteristics Samples range from around 4 500 in Sweden to nearly 27 300 in Canada (5 100 in the UK)

Wage inequality varies across countries Wage inequality in PIAAC countries (wage ratio D9/D1)

Countries differ also in the level and dispersion of skills Mean numeracy, 10th and 90th percentile for the employed population

The relationship between skills inequality and wage inequality is not straightforward

Simulate wage distributions using reweighting techniques

The impact of skills inequality on wage inequality Percentage change in wage inequality (P90/P10) as a result of moving to the average PIAAC skills inequality

Differences in return to skill are far more important Percentage change in hourly wages for a one standard deviation increase in numearcy

And the return to skill has a far more important impact on wage inequality Percentage change in wage inequality (P90/P10) as a result of moving to the average PIAAC return to skill

The return to skill is determined in part by labour market institutions, policies and practices Minimum wage DiNardo et al., 1996 ; Lee, 1999 ; Wolff, 2008 ; Autor et al., 2014 ; Machin, 1997 ; Dickens et al., 1999; Koeniger et al., 2007 Collective bargaining coverage Braconier et Ruiz-Valenzuea, 2014 ; Blau et Kahn, 1996 ; DiNardo et al., 2007 ; Wolff, 2008 ; Firpo et al., 2011 Employment protection legislation OCDE (2015) Practices around bonus pay Lemieux et al., 2007 Size of the public sector Generosity of unemployment benefits

The return to skill (and inequality) also depend on the supply of, and demand for, skill

Countries with a higher net supply of skills have lower wage inequality Notes: BEL refers to Flanders; GBR to England and Nothern Ireland. For further information on definitions and data used, see source. Source: OECD. "Skills and wage inequality." In: OECD Employment Outlook 2015. Paris: OECD Publishing, 2015.

Skills also explain wage gaps between various socio-economic groups Raw Skills Return A. Individuals whose parents have tertiary education/non-tertiary education wage ratio B. Male/female wage ratio

Main conclusions for England/N.I. The level of skills is relatively low Skills inequality is relatively high Reducing skills inequality will have a non-negligeable impact on wage inequality High returns to skills are part of the explanation for higher wage inequality in the UK This will partly be driven by labour market institutions (e.g. low collective bargaining coverage) but also by supply & demand for skills High return should act as an incentive to invest in skills Need to understand the barriers that are preventing the UK from moving to a higher skills equilibrium

Read more about our work Follow us on Twitter: @OECD_Social Thank you Contact: Stijn.Broecke@OECD.org Read more about our work Follow us on Twitter: @OECD_Social Website: www.oecd.org/els/social Newsletter: www.oecd.org/els/newsletter