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1 DANMARKS NATIONALBANK TECHNOLOGICAL CHANGE AND THE DANISH LABOUR MARKET Niels Lynggård Hansen, Head of Economics and Monetary Policy May 22, 218
2 Outline 1) Past trends 2) The Danish labour-market model (flexicurity) 3) Automation of job tasks in Denmark 4) Policy 2
3 Past trends
4 Technological advances have raised productivity, without causing structurally higher unemployment 21-kroner per hour worked (logarithmic scale) 1 Per cent of labour force; per cent of GDP Labour productivity Unemployment rate (right-hand axis) Wage share (divided by 1, right-hand axis) Note: The wage share of GDP has been divided by 1 in order to show it in the chart. It includes an imputed compensation per self-employed person corresponding to the average wage sum for wage earners. Source: Abildgren (218). 4
5 Past examples, Danish textile manufacturing Sectoral shifts in private employment Case study: Danish textile manufacturing Share of private sector employment, per cent Employment in manufacture of textiles and leather, no. 9, 75, 6, 45, 3, 15, Agriculture Manufacturing Service Other Source: Statistics Denmark and own calculations. 5
6 Transition costs Inequality of disposable income Gini coefficient Denmark Finland Sweden United Kingdom United States OECD average Note: There are several breaks and changes in methodology over the the period shown. Disposable income has been adjusted for household size. Source: OECD. 6
7 The Danish labour-market model (flexicurity)
8 The Danish labour-market model (flexicurity) 8
9 The Danish labour-market model (flexicurity) Labour turnover Expenditures on active labour-market policies Per cent of GDP 2.5 Newly hired, in per cent of total employment OECD average Latvia Slovak Republic Estonia United Kingdom Slovenia Lithuania Czech Republic Poland Italy Portugal Ireland Spain Germany Luxembourg Belgium Austria Netherlands Hungary Finland France Sweden Denmark Greece Czech Republic Poland Hungary Malta Italy United Kingdom Belgium Germany Slovakia Luxembourg Ireland Latvia Slovenia France Austria Netherlands Lithuania Portugal Estonia Cyprus Spain Denmark Finland Sweden Note: Left-hand chart: Annual average of quarterly observations from 217. Newly hired refers to employees hired within the last three months. Right-hand chart: Note: Data from 215, except for Estonia (214) and United Kingdom (211). Source: Eurostat (left) and OECD (right). 9
10 Most OECD countries have been spending less on worker training over the past 25 years Source: McKinsey Global Institute. 1
11 Actual and structural unemployment in Denmark Per cent of labour force Actual unemployment Structural unemployment Note: Structural unemployment as estimated by Danmarks Nationalbank. Source: Danmarks Nationalbank and Statistics Denmark. 11
12 Danish net replacement rates more dependent on income than the OECD median Per cent Lower income Average income Higher income Denmark OECD Median Note: Data for 215. Net replacement rates in case of unemployment for insured unemployed workers. Low-income workers earn less than 67 per cent of that of an average worker, while high-income workers earn more than 15 per cent of that of an average worker. Source: OECD. 12
13 Automation of job tasks in Denmark
14 Newly installed industrial robots in Denmark on the rise Number of newly installed industrial robots Source: Danish Industrial Robot Association. 14
15 Robot density is relatively high in the Danish manufacturing industry Note: Data from 216. Source: International Federation of Robotics. 15 Republic of Korea Singapore Germany Japan Sweden Denmark United States Italy Belgium Taiwan Spain Netherlands Canada Austria Finland Slovenia Slovakia France Switzerland Czech Rep. Australia United Kingdom China Portugal Hungary Norway New Zealand Thailand Malaysia Poland Mexico Israel South Africa Turkey Argentina Greece Romania Estonia Brazil Croatia Indonesia Russia Philippines India Number of installed industrial robots per 1, employees in the manufacturing industry World average
16 Danish firms plan to invest in IT in 218 Share of Danish firms planning to invest in Per cent IT (software and hardware) Other automation Special machinery Robots CNC construction/processing Other technology Small and medium-sized enterprises Large companies Source: The Confederation of Danish Industry, DI. 16
17 Danish workers do not fear automation Denmark USA Per cent 1 8 Agree/predominantly agree that automation and digitalisation Per cent of US adults 1 8 Worried 6 Agree Enthusiastic 2 Disagree 2 creates new jobs/keeps jobs in Denmark replaces routine work tasks with new and more interessting results in better working processes creates a better working environment Future where robots and computers can do many human jobs Development of algorithms that can evaluate and hire job candidates Development of driverless vehicles Development of robot caregivers for older adults Source: The Danish Confederation of Trade Unions, LO (left) and PEW Research Center (right). 17
18 and optimism is shared across industries To which extent do you agree in the following statements concerning automation and digitalisation? Agree/predominantly agree that it Per cent Total Manufacturing and agriculture Construction Wholesale and retail trade Transportation Business services and finance Public administration Health and social creates new jobs/keeps jobs in Denmark replaces routine work tasks with new and more interessting tasks Source: The Danish Confederation of Trade Unions, LO. 18
19 which may reflect that Denmark is a highly digitalised country DESI Index DK FI NL SE BE LU UK IE EE AT DE ES PT FR SI CZ LV HU PL HR IT EL RO Note: DESI is an abbreviation of The Digital Economy and Society Index. Source: European Commission. 19
20 OECD: 34 per cent of jobs at high or significant risk of automation Per cent KOR FIN EST ISR BEL JPN FRA SWE CHL IRL TUR AUS DNK CAN NOR ESP USA OECD GBR NZL NLD POL SVN GRC AUT DEU ITA CZE SVK Jobs at high risk of automation Jobs at risk of significant change Note: Jobs are at high risk of automation if the likelihood of their job being automated is at least 7 per cent. Jobs at risk of significant change are those with the likelihood of their job being automated estimated at between 5 and 7 per cent.. Source: OECD Employment Outlook 217, chapter 3, box
21 During the last 2 years, the share of middle-skilled jobs have decreased Change in share of total employment, 1995 to 215 Percentage points AUT CHE IRL ESP GRC DNK FRA SWE PRT GBR NOR NLD FIN Total ITA DEU BEL USA SVN CAN SVK JPN HUN CZE Low skill Middle skill High skill Source: OECD Employment Outlook 217, chapter
22 Are all workers prepared for the new world of work? Share of and year-olds performing at Level 2 or 3 in problem solving in technology-rich environments Per cent FIN SWE JPN DNK NOR SGP NLD NZL BEL CZE DEU AUS AUT CAN KOR ENG OECD EST NIR USA ISR SVN IRL SVK POL LTU CHL GRC TUR Aged 25 to 34 Aged 55 to 65 All age groups Note: Individuals in Level 2 or Level 3 have more advanced ICT and cognitive skills to evaluate problems and solutions than those in Level 1 or below. Source: OECD Employment Outlook 217, chapter 3. 22
23 Policy
24 Challenges Legal issues Moral and ethical issues Distributional consequences Cyber robustness 24
25 Cyber robustness 64 per cent of Danish firms were hit by a cyber attack in 217 Per cent 1 AUGUST 16, Moller-Maersk puts cost of cyber attack at up to $3m
26 Policy Framework conditions Flexible labour-market structures Education and life-long learning, also for the low-skilled Social security The Danish labour-market model (flexicurity): Balance between flexibility and security must be continuously monitored 26
27 The Danish labour-market model: Protecting workers, not jobs»we insist on seeking collective solutions to common challenges. This is why Danish trade unions work with employers and the Danish government to manage disruption. We need to ensure that everybody is prepared for the future.«lizette Risgaard, President of The Danish Confederation of Trade Unions (LO), in Financial Times, 21 March, 218 On unemployment insurance benefits:»you might be able to increase the labour supply at the margin. But doing so would start a process where we change our labourmarket model. This would be very costly for us.«karsten Dybvad, CEO of The Confederation of Danish Industry (DI) Own translation of Karsten Dybvad quote.
Supplementary figures
Supplementary figures Source: OECD (211d, p. 8). Figure S3.1 Business enterprise expenditure on R&D, 1999 and 29 (as a percentage of GDP) ISR FIN SWE KOR (1999, 28) JPN CHE (2, 28) USA (1999, 28) DNK AUT
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