For Official Use DSTI/EAS/IND/WPIA(2016)1 Organisation de Coopération et de Développement Économiques Organisation for Economic Co-operation and Development 15-Feb-2016 ___________________________________________________________________________________________ English - Or. English DIRECTORATE FOR SCIENCE, TECHNOLOGY AND INNOVATION COMMITTEE ON INDUSTRY, INNOVATION AND ENTREPRENEURSHIP For Official Use Official For DSTI/EAS/IND/WPIA(2016)1 Working Party on Industry Analysis SKILLS AND GLOBAL VALUE CHAINS: A FIRST CHARACTERISATION Paris, OECD Headquarters, 7-8 March 2016 This paper offers some preliminary results of the work jointly carried out by STI and the Directorate for Education and Skills (EDU) aimed to characterise the distribution of skills across countries, industries and occupations, and to investigate the relationships that exists between the skills composition of the workforce and the generation of value added from trade. The study has been prepared by Mariagrazia Squicciarini (STI/EAS), Stéphanie Jamet (EDU), Robert Grundke (STI/EAS) and Margarita Kalamova (EDU) as part of the “GVCs, jobs and skills” horizontal project. It is proposed under item 6 of the CIIE agenda, for information and discussion. For further information, please contact : Mariagrazia SQUICCIARINI (STI/EAS); [email protected] Stéphanie JAMET (EDU); [email protected] English JT03390128 Complete document available on OLIS in its original format - Or. English This document and any map included herein are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. DSTI/EAS/IND/WPIA(2016)1 EXECUTIVE SUMMARY This paper offers some preliminary results of the work jointly carried out by the Directorate for Science, Technology and Innovation (STI) and the Directorate for Education and Skills (EDU). This work aims to characterise the distribution of skills across countries, industries and occupations, and to investigate the relationships that exist between the skills composition of the workforce and the generation of value added from trade. While existing studies agree on the importance of skills for trade patterns, they very seldom specify which skills matter for which type of GVC-related measures of participation or performance, or add an industry or occupation perspective to it. Uncovering these relationships, though, is needed for the design of effective policies in many areas, including industry, education and trade policies. The present work contributes to address such shortcomings by identifying the skills that existing studies suggest being key for workers' performance on the job and for firm performance. Skills are selected based on an extensive survey of the literature, including economics, management, organisation science and psychology, and according to their prospect relevance in shaping the creation of value added in domestic markets as well as international production. The continuum of cognitive skills and personal traits (i.e. non- cognitive skills) identified as being relevant for economic performance is crystallised in a taxonomy grouping skills in a homogeneous fashion, with the aim to generate skill-related indicators that reflect the findings of the literature. The proposed taxonomy is operationalised on data from the OECD Programme for the International Assessment of Adult Competencies (PIAAC) survey, as it provides a wealth of employee-level information about workers' skills, frequency of the performance of various tasks, as well as information about the industry where they work and does so for more than twenty OECD countries. For cognitive skills, indicators of both assessed skills (through tests) and frequency of the performance of cognitive tasks are considered. For skills that combine cognitive and personality traits aspects (e.g. management, interacting and communicating) and physical skills, indicators are built from information on the frequency of performance of related tasks. In the absence of directly relevant questions, some personality traits' indicators are constructed using replies to self-reported questions on related issues. A number of stylised facts emerge from the skills indicators proposed and highlight the extent to which skills endowments and the frequency with which some tasks are performed differ across countries, industries and occupations. • Large cross-country differences emerge in terms of shares of workers with high and low literacy and numeracy skills, with Finland and Japan having a large group of workers with high literacy and numeracy skills in both the services and manufacturing and Italy having a large group of workers with low skills along these two dimensions. • Within countries, the distributions of skills in services and in manufacturing appears relatively similar, although in most countries there is a higher (lower) share of workers with relatively high (low) literacy skills in services (manufacturing). 2 DSTI/EAS/IND/WPIA(2016)1 • Large differences emerge in terms of skills endowment of the different occupational categories, with professionals and managers having the highest skills, on average. Large variations emerge across countries in terms of skills of workers in the same occupations, especially in manufacturing. • In terms of problem solving skills, large heterogeneity emerges in the distribution of skills between countries and within countries, between manufacturing and services sectors, although no clear pattern arises across industries. • In line with expectations, workers perform less complex ICT tasks more frequently than complex ones, in all industries. Data show large variations between countries in the use of ICT skills, especially for less complex skills, and for a group of industries a lower use of ICT skills at work emerges, as compared to the extent to which such skills are used at home. This may signal that the potential of employees is not fully exploited, although to different extents in different countries and industries. • The frequency of the performance of tasks that require skills combining cognitive and personality traits components, such as interacting and communicating is low for a number of countries and sectors, despite these skills being found to be crucial for firm performance. Heterogeneity between countries is especially large for the frequency of the performance of managing tasks and to a lesser extent for self-organising tasks, suggesting that some countries have a large potential to better use and further develop the related skills. • In terms of physical skills, a lot of heterogeneity emerges between sectors, with finance being the industry showing the lowest level of use of physical skills and agriculture the highest level. This large heterogeneity across industries can reflect differences in the production process but also in the types of goods that are produced and thereby, in the positioning in the GVC. • A comparison of the use of skills between workers and non-employed (measured in the last job for the non-employed) shows a higher use by workers of all types of skills, with the exception of physical ones. In all countries, non-employed exhibit higher levels of skills use at home than workers in at least two out of the six skills considered. These statistics could point to the possible existence of untapped potential, which can come for instance from young people not yet in the labour force or unemployed having lost their jobs recently. However, the statistics might as well reflect that the non-working population can dedicate more time to those activities at home. 1. Skills indicators have been related to labour productivity and to selected indicators of Trade in Value Added (TiVA), and to shed some light on how different types of skills relate to economic performance and countries’ engagement in GVCs. These TiVA indicators account for countries and sectors participation and positioning in GVCs. They include a basic measure of value added, two indicators of the value added content of gross exports, one indicator of the direct industry value added and a measure of final demand. The following features emerge from these exploratory correlations: • The correlation of productivity with skills' median values, both cognitive skills and personality traits, is always significant, and almost always positively so, with the strongest correlations found with the frequency of the performance of complex numeracy tasks (0.42). In the case of the frequency of the performance of physical tasks the coefficients of the correlations between median skills and productivity turns out to be negative (-0.36) likely signalling a possible low productivity of tasks entailing physical work. 3 DSTI/EAS/IND/WPIA(2016)1 • The correlation of productivity with the 10th percentile of with the 25th percentile (i.e. the left hand part) of the skills distributions exhibits higher coefficients than that of the 75th or 90th percentile, and often also of those of mean values. While it is premature to draw any conclusion based on such a general descriptive exercise, data seem to support the intuition of the resource based view of the firm, whereby it is broad workforce skills that matter. • Cognitive skills indicators, both assessed skills and the frequency of the performance of cognitive tasks, show generally significant positive correlations with the selected TiVA indicators. Correlations between skill indicators and the domestic value added embodied