DANMARKS NATIONALBANK TECHNOLOGICAL CHANGE AND THE DANISH LABOUR MARKET
Niels Lynggård Hansen, Head of Economics and Monetary Policy May 22, 2018 Outline
1) Past trends
2) The Danish labour-market model (flexicurity)
3) Automation of job tasks in Denmark
4) Policy
14. maj 2018 2 Past trends Technological advances have raised productivity, without causing structurally higher unemployment
2010-kroner per hour worked (logarithmic scale) Per cent of labour force; per cent of GDP 1000 14
12
10
8 100 6
4
2
10 0 1900 1905 1910 1915 1920 1925 1930 1935 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 Labour productivity Unemployment rate (right-hand axis) Wage share (divided by 10, right-hand axis)
Note: The wage share of GDP has been divided by 10 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 (2018).
14. maj 2018 4 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. 100 90,000 90 75,000 80
70 60,000 60 50 45,000 40 30,000 30 20 15,000 10
0 0 66 71 76 81 86 91 96 01 06 11 16 66 70 74 78 82 86 90 94 98 02 06 10 14 Agriculture Manufacturing Service Other Source: Statistics Denmark and own calculations.
14. maj 2018 5 Transition costs
Inequality of disposable income Gini coefficient 0.40
0.35
0.30
0.25
0.20 85 87 89 91 93 95 97 99 01 03 05 07 09 11 13 15
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.
14. maj 2018 6 The Danish labour-market model (flexicurity) The Danish labour-market model (flexicurity)
14. maj 2018 8 The Danish labour-market model (flexicurity)
Labour turnover Expenditures on active labour-market policies
Newly hired, in per cent of total employment Per cent of GDP 9 2.5 8 7 2.0 6 5 1.5 4 3 1.0 2 OECD average 0.5 1 0 Sweden Finland Denmark Spain Cyprus Estonia Portugal Lithuania Netherlands Austria France Slovenia Latvia Ireland Luxembourg Slovakia Germany Belgium Kingdom United Italy Malta Hungary Poland RepublicCzech Greece 0.0 Denmark Sweden France Finland Hungary Netherlands Austria Belgium Luxembourg Germany Spain Ireland Portugal Italy Poland RepublicCzech Lithuania Slovenia Kingdom United Estonia RepublicSlovak Latvia
Note: Left-hand chart: Annual average of quarterly observations from 2017. Newly hired refers to employees hired within the last three months. Right-hand chart: Note: Data from 2015, except for Estonia (2014) and United Kingdom (2011). Source: Eurostat (left) and OECD (right).
14. maj 2018 9 Most OECD countries have been spending less on worker training over the past 25 years
Source: McKinsey Global Institute.
14. maj 2018 10 Actual and structural unemployment in Denmark
Per cent of labour force 16
14
12
10
8
6
4
2
0 85 87 89 91 93 95 97 99 01 03 05 07 09 11 13 15 17
Actual unemployment Structural unemployment
Note: Structural unemployment as estimated by Danmarks Nationalbank. Source: Danmarks Nationalbank and Statistics Denmark.
14. maj 2018 11 Danish net replacement rates more dependent on income than the OECD median
Per cent 100
90
80
70
60
50
40
30 Lower income Average income Higher income
Denmark OECD Median
Note: Data for 2015. 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 150 per cent of that of an average worker. Source: OECD.
14. maj 2018 12 Automation of job tasks in Denmark Newly installed industrial robots in Denmark on the rise
Number of newly installed industrial robots 800
700
600
500
400
300
200
100
0 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Source: Danish Industrial Robot Association.
14. maj 2018 14 Robot density is relatively high in the Danish manufacturing industry
Number of installed industrial robots per 10,000 employees in the manufacturing industry 700
600
500
400
300
200 World average 100
0 Italy India Israel Brazil Spain China Japan Russia France Turkey Austria Poland Greece Taiwan Mexico Croatia Finland Estonia Canada Norway Sweden Belgium Slovakia Slovenia Portugal Hungary Thailand Malaysia Australia Romania Germany Denmark Indonesia Argentina Singapore Czech Rep. Czech Philippines Switzerland South Africa South Netherlands New Zealand New United States United United Kingdom United Republic of of Korea Republic
Note: Data from 2016. Source: International Federation of Robotics.
14. maj 2018 15 Danish firms plan to invest in IT in 2018
Share of Danish firms planning to invest in… Per cent 70
60
50
40
30
20
10
0 IT (software and Other automation Special machinery Robots CNC Other technology hardware) construction/processing
Small and medium-sized enterprises Large companies
Source: The Confederation of Danish Industry, DI.
14. maj 2018 16 Danish workers do not fear automation
Denmark USA Per cent Per cent of US adults 100 Agree/predominantly agree that automation and 100 digitalisation… 80 80 Worried
60 Agree 60 Enthu- 40 40 siastic Disagree 20 20
0 0 … creates new … replaces … results in … creates a Future where Development Development Development jobs/keeps routine work better working better working robots and of algorithms of driverless of robot jobs in tasks with new processes environment computers can that can vehicles caregivers for Denmark and more do many evaluate and older adults interessting human jobs hire job candidates
Source: The Danish Confederation of Trade Unions, LO (left) and PEW Research Center (right).
14. maj 2018 17 …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 80
70
60
50
40
30
20
10
0 Total Manufacturing and Construction Wholesale and Transportation Business services Public Health and social agriculture retail trade and finance administration
… 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.
14. maj 2018 18 …which may reflect that Denmark is a highly digitalised country
DESI Index 0.75
0.70
0.65
0.60
0.55
0.50
0.45
0.40
0.35
0.30 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.
14. maj 2018 19 OECD: 34 per cent of jobs at high or significant risk of automation
Per cent 50
45
40
35
30
25
20
15
10
5
0 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 70 per cent. Jobs at risk of significant change are those with the likelihood of their job being automated estimated at between 50 and 70 per cent.. Source: OECD Employment Outlook 2017, chapter 3, box 3.3.
14. maj 2018 20 During the last 20 years, the share of middle-skilled jobs have decreased
Change in share of total employment, 1995 to 2015 Percentage points 20
15
10
5
0
-5
-10
-15
-20 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 2017, chapter 3..
14. maj 2018 21 Are all workers prepared for the new world of work?
Share of 25-34 and 55-64 year-olds performing at Level 2 or 3 in problem solving in technology-rich environments
Per cent 80
70
60
50
40
30
20
10
0 FIN SWE JPN DNK NOR SGP NLD NZL BEL CZE DEU AUS AUT CAN KOR ENGOECD 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 2017, chapter 3.
14. maj 2018 22 Policy Challenges
• Legal issues
• Moral and ethical issues
• Distributional consequences
• Cyber robustness
14. maj 2018 24 Cyber robustness
64 per cent of Danish firms were hit by a cyber attack in 2017
Per cent 100 AUGUST 16, 2017
80
60 Moller-Maersk 40 puts cost of cyber 20 attack at up to $300m
0 2015 2016 2017
14. maj 2018 25 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
14. maj 2018 26 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, 2018
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 labour- market model. This would be very costly for us. « Karsten Dybvad, CEO of The Confederation of Danish Industry (DI)
Own translation of Karsten Dybvad quote.