Skip to main content

2020 | OriginalPaper | Buchkapitel

Skills, Productivity and Employment: An Empirical Analysis of Selected Countries

verfasst von : Suresh Chand Aggarwal

Erschienen in: Accelerators of India's Growth—Industry, Trade and Employment

Verlag: Springer Singapore

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Skills development is central to economic performance of the countries in the current milieu when ‘disruptive’ technology is evolving at a fast pace. The new technology—Internet Of Things (IOT), Artificial Intelligence (AI), machine learning, neural networks, digitization of manufacturing, etc.—is changing the face of how we work, and the skills we need to succeed in our jobs. While opening many new windows for investment and increase in productivity and employment, the new technology is simultaneously disturbing the existing technological complementarities and exerting a lot of pressure on the supply of the matching skills. Many jobs which exist today would disappear tomorrow and many new jobs will get created tomorrow which do not exist today. So there is a simultaneous creation and destruction of jobs. The net impact thus depends upon their respective pace. The shortages of ‘new’ skills put several constraints on growth and development by curtailing the prospects for increases in job creation and income. Coupled with mismatch between supply and demand of skills, it constrains productivity improvements and adds to production costs within firms, making it difficult for the domestic firms to compete internationally, adversely impacting growth prospects along the way through trade linkages. Such skill mismatches and skill shake-ups have increased the need for regular skilling, and up-skilling throughout a person’s career, because people with low skills are generally the first ones to lose jobs. But the speed at which jobs are transforming and the workers’ capacity to adapt to such changes are not uniform across industries and countries and are also influenced by access to education, availability and cost of ICT and the opportunities for lifelong learning inside and outside the workplace. Lifelong learning is needed to resolve both the immediate challenge and to add value through skills in the future. The association between skills, productivity and employment has long been discussed and empirically tested. Fields (Education and income: A background study for world development. The World Bank, Washington, DC, 1980) had concluding way back in 1980 that education (skills) have a positive impact on the level of income by paving new opportunities for many who acquire the skills. Skills thus help in employment and income. The survey of adult skills by OECD (OECD skills outlook 2013. First results from the survey of adult skills. Paris, OECD, 2013) also found a positive association between the mean skill level (measured by numeracy score) and the economic performance across countries (measured by PCI in PPP). Global Competitiveness Report (2016) also points out the significance of skills (talent) in an economy to reap the benefits of the tech revolution and achieve higher productivity and employment. But to meet the growing challenge of ‘new’ skills requirement, we have to recognize existing skills, understand skills demand; create right mix of expertise—especially on the job training and learning; and reach out to those firms and people who need it most—the small and medium enterprises(SME); the low skilled workers; and older workers. Since better skills are likely to lead to quick employment and higher income, for them acquiring and updating skills would be the best insurance against job losses. However, higher economic growth and income also, in turn, help a country with the resources to improve the opportunities for acquiring and developing skill base through the expansion of education and training, leading to a virtuous chain of growth in income, skills, productivity, and employment. There are still quite a few countries, including India which even though have achieved high economic growth, but struggle with low human capital scores (which is a composite score of different parameters and includes enrollment and quality of education; and skills distribution among others (World Economic Forum in The human capital report, 2016)); indicating their neglect in expanding education and imparting necessary skills. The paper aims to first map the industries, based on capital intensity and/or ICT produced/used, in which technology has changed rapidly resulting in change in skills requirements. It will then explore the linkage between skills distribution, (labour) productivity and growth in employment both at the disaggregated industry level as well as at national level for few selected countries like BRIC countries, Indonesia, Mexico, South Korea, etc. for the period 1995–2009; all of which have faced the similar challenges. The exercise would also be carried out separately for formal (organized) and informal (unorganized) sectors of the Indian economy, as it is expected that formal sector firms; especially in the modern sector of the economy are likely to pay higher average wages reflecting higher productivity, which in turn, is partially determined by their skills. These firms, which are also relatively large in size, are also likely to spend more not only in R &D but also on the job training, resulting in better skills proficiency which in turn is likely to lead to higher productivity and growth in employment. The last section would highlight the learning from the experience and focus on the policy challenges the countries would have to face in view of the changing technology landscape.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Anhänge
Nur mit Berechtigung zugänglich
Fußnoten
1
World Development Report (2019, page 47) has suggested “three ways to improve adult learning—more systematic diagnoses of the specific constraints that adults are facing, pedagogies that are customized to the adult brain, and flexible delivery models that fit well with adult lifestyles.”.
 
2
OECD (2015) identifies mismatch by field of study as the most common form of mismatch, followed by qualification mismatch.
 
3
World Development Report (2019) has identified and defined three types of skills—cognitive skills, job-specific skills, and socio-emotional skills.
 
4
The short time period is a serious limitation of the study and may not fully capture the impact of recent technological changes. However, the study may show the preliminary results.
 
5
WIOD (2012). Socio-Economic Accounts (SEA): Sources and Methods.
 
6
See Appendix for details of methodology to estimate organized and unorganized employment.
 
7
Agriculture has been excluded from this exercise.
 
8
Double deflated RVA means both output and inputs are deflated by their separate price deflators.
 
9
However, the development of skills is required not only for better productivity but also for better well being. Education by providing access to more opportunities also facilitates upward income mobility.
 
10
While Korea was exporting 47% of its GDP in 2009, the ratio was just 11% for Brazil; around 21–24% for China, India, Indonesia, and Turkey; and 28% for Mexico, Russia and South Africa (World Bank 2018).
 
11
Agriculture has been dropped as, in most of the countries it is low-skill intensive with hardly any change in skill composition.
 
12
It is observed that in all the selected nine countries, average labour productivity during 1995–2009 is higher in high capital intensive industries than the medium and low-skill intensive industries (Table 2).
 
13
See Table 3. The score is not available for Taiwan.
 
14
The author believes that it has led to a widening inequality of income between the high-skill and low-skill workers.
 
Literatur
Zurück zum Zitat Das, D. K., Sen, K., & Das, P. C. (2015). Labour intensity in Indian manufacturing. In K. V. Ramaswamy (Ed.), Labour, employment and economic growth in India. Delhi: Cambridge University Press. Das, D. K., Sen, K., & Das, P. C. (2015). Labour intensity in Indian manufacturing. In K. V. Ramaswamy (Ed.), Labour, employment and economic growth in India. Delhi: Cambridge University Press.
Zurück zum Zitat Fields, G. S. (1980). Education and income distribution in developing countries: A review of the literature [Electronic version]. In T. King (Ed.), Education and income: A background study for world development (pp. 231–315). Washington, DC: The World Bank. Fields, G. S. (1980). Education and income distribution in developing countries: A review of the literature [Electronic version]. In T. King (Ed.), Education and income: A background study for world development (pp. 231–315). Washington, DC: The World Bank.
Zurück zum Zitat Goldar, B. (2000). Employment growth in organised manufacturing in India. Economic and Political Weekly, 35(14), April 1–7. Goldar, B. (2000). Employment growth in organised manufacturing in India. Economic and Political Weekly, 35(14), April 1–7.
Zurück zum Zitat Goldar, B., & Aggrawal, S. C. (2012). Informalization of industrial labor in India: Effects of labor market rigidities and import competition. Developing Economies, 50(2), 141–169.CrossRef Goldar, B., & Aggrawal, S. C. (2012). Informalization of industrial labor in India: Effects of labor market rigidities and import competition. Developing Economies, 50(2), 141–169.CrossRef
Zurück zum Zitat Greatz, G., & Michaels, G. (2017). Is modern technology responsible for jobless recoveries? American Economic Review Papers and Proceedings. Greatz, G., & Michaels, G. (2017). Is modern technology responsible for jobless recoveries? American Economic Review Papers and Proceedings.
Zurück zum Zitat Kapoor, R. (2016). Technology, jobs and inequality: Evidence from India’s manufacturing sector (Working Paper 313). New Delhi: ICRIER. Kapoor, R. (2016). Technology, jobs and inequality: Evidence from India’s manufacturing sector (Working Paper 313). New Delhi: ICRIER.
Zurück zum Zitat Mehrotra, S., Parida, J., Sinha, S., & Gandhi, A. (2013). Explaining employment trends in the Indian economy: 1993–94 to 2011–12. Economic and Political Weekly, 49(32), 49–57. Mehrotra, S., Parida, J., Sinha, S., & Gandhi, A. (2013). Explaining employment trends in the Indian economy: 1993–94 to 2011–12. Economic and Political Weekly, 49(32), 49–57.
Zurück zum Zitat NCEUS. (2007). Report on conditions of Work and Promotion of Livelihoods in the Unorganized Sector. National Commission for Enterprises in the Unorganized Sector, Government of India, New Delhi, 2007. NCEUS. (2007). Report on conditions of Work and Promotion of Livelihoods in the Unorganized Sector. National Commission for Enterprises in the Unorganized Sector, Government of India, New Delhi, 2007.
Zurück zum Zitat OECD. (2013). OECD skills outlook 2013. First results from the survey of adult skills. Paris: OECD. OECD. (2013). OECD skills outlook 2013. First results from the survey of adult skills. Paris: OECD.
Zurück zum Zitat OECD. (2015). Getting skills right: Assessing and responding to changing skill needs. Paris: OECD. OECD. (2015). Getting skills right: Assessing and responding to changing skill needs. Paris: OECD.
Zurück zum Zitat OECD. (2018). OECD compendium of productivity indicators. Paris: OECD. OECD. (2018). OECD compendium of productivity indicators. Paris: OECD.
Zurück zum Zitat Sastry, N. S. (2004). Estimating informal employment and poverty in India. Discussion Paper Series, 7, Human Development Resource Centre, UNDP, India. Sastry, N. S. (2004). Estimating informal employment and poverty in India. Discussion Paper Series, 7, Human Development Resource Centre, UNDP, India.
Zurück zum Zitat Sundaram, K. (2008). Employment, wages and poverty in the non-agricultural sector: All-India, 2000–05. Economic and Political Weekly, 43(22), 91–99. Sundaram, K. (2008). Employment, wages and poverty in the non-agricultural sector: All-India, 2000–05. Economic and Political Weekly, 43(22), 91–99.
Zurück zum Zitat The Conference Board. (2019). Total economy data base. The Conference Board. (2019). Total economy data base.
Zurück zum Zitat The Economist Intelligence Unit Limited. (2018). The automation readiness index: Who is ready for the coming wave of automation? The Economist Intelligence Unit Limited. (2018). The automation readiness index: Who is ready for the coming wave of automation?
Zurück zum Zitat Timmer, M. P., Dietzenbacher, E., Los, B., Stehrer, R., & de Vries, G. J. (2015). An illustrated user guide to the world input–output database: The case of global automotive production. Review of International Economics, 23, 575–605. Timmer, M. P., Dietzenbacher, E., Los, B., Stehrer, R., & de Vries, G. J. (2015). An illustrated user guide to the world input–output database: The case of global automotive production. Review of International Economics, 23, 575–605.
Zurück zum Zitat WIOD. (2012). Socio Economic Accounts (SEA): Sources and methods. WIOD. (2012). Socio Economic Accounts (SEA): Sources and methods.
Zurück zum Zitat World Bank. (2018). World economic indicators. World Bank. (2018). World economic indicators.
Zurück zum Zitat World Development Report. (2019). The changing nature of work. World Development Report. (2019). The changing nature of work.
Zurück zum Zitat World Economic Forum. (2016a). The human capital report 2016. World Economic Forum. (2016a). The human capital report 2016.
Zurück zum Zitat World Economic Forum. (2016b). Global competitiveness report: 2016–17. World Economic Forum. (2016b). Global competitiveness report: 2016–17.
Zurück zum Zitat World Economic Forum. (2017). Global competitiveness report: 2017–18. World Economic Forum. (2017). Global competitiveness report: 2017–18.
Metadaten
Titel
Skills, Productivity and Employment: An Empirical Analysis of Selected Countries
verfasst von
Suresh Chand Aggarwal
Copyright-Jahr
2020
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-32-9397-7_15

Premium Partner