2018 OECD ECONOMIC SURVEY OF GERMANY
Sustaining strong and inclusive growth
Berlin, June 12th 2018
@OECD @OECDeconomy
http:/ / www.oecd.org/ eco/ surveys/ economic-survey-germany.htm
2018 OECD ECONOMIC SURVEY OF GERMANY Sustaining strong and - - PowerPoint PPT Presentation
2018 OECD ECONOMIC SURVEY OF GERMANY Sustaining strong and inclusive growth Berlin, June 12 th 2018 http:/ / www.oecd.org/ eco/ surveys/ economic-survey-germany.htm @OECDeconomy @OECD Wellbeing is high OECD Better Life Index, 20 17 Germany
@OECD @OECDeconomy
http:/ / www.oecd.org/ eco/ surveys/ economic-survey-germany.htm
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Source: OECD (2017), OECD Better Life Index, w w w .oecdbetterlifeindex.org.
0.0 2.0 4.0 6.0 8.0 10.0 Income and wealth Jobs and earnings Housing Work and life balance Health status Education and skills Social connections Civic engagement and governance Environmental quality Personal security Subjective well- being
OECD Better Life Index, 20 17
Germany OECD
90 95 100 105 110 115 120 90 95 100 105 110 115 120 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Real GDP, Index 20 0 7= 10 0
Euro Area Germany
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Source: OECD (2018), OECD Econom ic Outlook: Statistics and Projections (database).
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Note: The poverty line is 60% of median household income. Household income is adjusted to take into account household size. Source: OECD (2018), OECD Social and Welfare Statistics (database).
5 10 15 20 25 30 5 10 15 20 25 30 CZE ISL DNK SVK FIN NOR FRA AUT NLD SVN LUX DEU HUN CHE SWE IRL BEL GBR POL OECD PRT KOR NZL ITA AUS GRC CAN JPN EST ESP LVA CHL USA MEX TUR ISR
Population with disposable incom e below the poverty line, % of population, 20 15
5
Source: Statistisches Bundesamt.
2 4 6 8 10 12 2 4 6 8 10 12 1991Q1 1992Q1 1993Q1 1994Q1 1995Q1 1996Q1 1997Q1 1998Q1 1999Q1 2000Q1 2001Q1 2002Q1 2003Q1 2004Q1 2005Q1 2006Q1 2007Q1 2008Q1 2009Q1 2010Q1 2011Q1 2012Q1 2013Q1 2014Q1 2015Q1 2016Q1 2017Q1 2018Q1
Unem ploym ent rate, % of labour force
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Source: OECD (2017), "Education at a glance: Educational attainment and labour-force status", OECD Education Statistics (database).
5 10 15 20 25 30 5 10 15 20 25 30 ISL LUX NLD DNK SWE CHE NOR DEU JPN AUT NZL AUS SVN CZE BEL CAN GBR FIN ISR OECD USA LVA EST POL HUN PRT SVK IRL FRA CHL ESP MEX GRC ITA TUR
Youth not in em ploym ent, education or training (NEET), % of 15-29 year-olds, 20 16
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0.5 1.5 2.5 3.5 4.5
0.5 1.5 2.5 3.5 4.5 2010Q1 2010Q3 2011Q1 2011Q3 2012Q1 2012Q3 2013Q1 2013Q3 2014Q1 2014Q3 2015Q1 2015Q3 2016Q1 2016Q3 2017Q1 2017Q3 2018Q1
Nom inal wage growth and inflation Year-on-year growth rates, %
Inflation Nominal wage rate
Note: Inflation is that of the Harmonised consumer price index (HICP). Source: OECD (2018), OECD Economic Outlook: Statistics and Projections (database).
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Source: OECD calculations based on OECD (2018), OECD National Accounts Statistics (database) and OECD (2018), OECD Economic Outlook: Statistics and Projections (database ).
0.0 2.0 4.0 6.0 8.0 10.0
0.0 2.0 4.0 6.0 8.0 10.0 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Current account and saving-investm ent balance, % of GDP
Current account balance Saving-investment balance of corporations
9
10
Note: Average annual grow th in trend labour productivity. Source: OECD (2018), "OECD Economic Outlook No. 102 (Edition 2017/ 2)", OECD Economic Outlook: Statistics and Projections (database).
0.0 0.5 1.0 1.5 2.0 2.5 0.0 0.5 1.0 1.5 2.0 2.5 DEU GBR JPN FRA CAN SWE USA 1996-2006 2006-16
Average annual rate of labour productivity growth,
9 18 27 36 45 9 18 27 36 45 Total Low skilled Medium skilled High skilled Women Men
Em ployees earning low wage, % of all em ployees
Germany EU
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Note: employees earning low wage are those earning less than two thirds of the median gross hourly earnings. Source: Eurostat (2018), Employment and working conditions (database).
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Source: OECD (2016), Education at a Glance 2016: OECD Indicators.
40 50 60 70 80 90 100 40 50 60 70 80 90 100 AUT CAN DEU FRA OECD NLD AUS GBR FIN DNK SWE
Wom en's earnings as % of m en's earnings, Tertiary education graduates, 20 14
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8.0 8.5 9.0 9.5 10.0 10.5 11.0 8.0 8.5 9.0 9.5 10.0 10.5 11.0 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
CO2 em ission, tonnes per capita
Germany OECD
Note: Emission is production based. Source: OECD (2018), Green Growth Indicators (database).
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12 13 14 15 16 17 18 19 12 13 14 15 16 17 18 19 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Mean annual concentration of PM2.5, µg/ m ³
Germany OECD
Source: OECD (2018), Green Growth Indicators (database).
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10 20 30 40 50 10 20 30 40 50 CHL NZL ISR MEX CHE KOR IRL AUS CAN GBR LUX USA ISL NLD JPN OECD NOR TUR DNK POL ESP PRT GRC FIN EST SVK SVN ITA CZE SWE FRA AUT DEU HUN BEL
Labour incom e tax and social security contributions, as % of labour costs, 20 17
Average tax wedge Personal income tax Social security contributions
16
Note: Income tax plus employee and employer social security contributions less cash benefits for single person, no child, earning 67% of average earnings. Source: OECD (2018), Taxing Wages Statistics (database).
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1 2 3 4 5 1 2 3 4 5 MEX USA CAN CHL NZL JPN SVK CHE ESP AUS DEU FRA LUX ISL BEL NOR IRL PRT SWE GBR KOR EST HUN CZE GRC FIN AUT ISR NLD TUR ITA SVN DNK
Environm ental tax revenue, % of GDP, 20 14
Source: OECD (2018), "OECD Instruments used for environmental policy", OECD Environment Statistics (database).
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4 8 12 16 20 4 8 12 16 20 FRA NZL IRL AUS NLD DEU OECD FIN JPN CAN SVN KOR BEL SWE AUT ISL USA GBR DNK NOR CHE LUX
Annual public expenditure in prim ary education, Per student, USD thousand, PPPs, 20 14
21.2
Source: OECD (2017), Education at a Glance 2017: OECD Indicators.
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Source: European Commission (2015), "The 2015 ageing report: Economic and budgetary projections for the 28 EU Member States (2013-2060)". Based on the reference scenario.
5 10 15 20 25 5 10 15 20 25 2020 2035 2060 % %
Projections on ageing related spending, % of GDP
Pensions, net Health care Long-term care
More in the Key Policy Insights of the Econom ic Survey of Germ any 2018
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More in the Key Policy Insights of the Econom ic Survey of Germ any 2018
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Multifactor productivity level of Germ an firm s, index 20 0 6 =10 0
Note:The Best performers are the top 5% firms with highest productivity within each 2-digit sector . Source: OECD calculations based on ORBIS dataset.
60 70 80 90 100 110 120 130 2006 2007 2008 2009 2010 2011 2012 2013
The rest Best performers 60 70 80 90 100 110 120 130 2006 2007 2008 2009 2010 2011 2012 2013
The rest Best performers
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Note: Large firms are firms with more than 250 employed persons. Source: OECD calculations based on OECD (2017), Entrepreneurship at a Glance 2017.
20 40 60 80 100 120 140 20 40 60 80 100 120 140 DEU DNK CHE SWE FRA ITA FIN ESP BEL AUT GBR NLD
Value added per person em ployed in SMEs, % of the level of large firm s, 20 14
Small (20-49 persons) Medium (50-249 persons)
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Source: OECD (2017), OECD Science, Technology and Industry Scoreboard 2017: The digital transform ation.
0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 GBR LUX ITA GRC NOR USA ESP DEU PRT NLD EST DNK CZE FIN FRA AUT BEL SWE
Contribution of KBC to labour productivity growth, Percentage points, business sector, 20 0 0 -14
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80 90 100 110 120 130 80 90 100 110 120 130 2010Q1 2010Q3 2011Q1 2011Q3 2012Q1 2012Q3 2013Q1 2013Q3 2014Q1 2014Q3 2015Q1 2015Q3 2016Q1 2016Q3 2017Q1
Num ber of new enterprises, index 20 12=10 0
Belgium Netherlands Germany
Note: the number of new enterprises is adjusted for business cycle components. Source: OECD (2017), Entrepreneurship at a Glance 2017.
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Source: OECD (2017), Entrepreneurship at a Glance 2017.
5 10 15 20 25 5 10 15 20 25 NOR JPN DNK SWE EST DEU USA IRL ISL SVN LUX FRA HUN LTU AUT FIN ISR LVA CHE BEL GBR TUR ROU OECD SVK PRT CAN ZAF ESP CZE NLD AUS POL NZL KOR ITA BRA GRC CHL MEX
The share of self-em ployed wom en, % of total active wom en, 20 16
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 GBR JPN DEU PRT ESP USA CHE FRA ISR IRL GRC CHL FIN SVN NZL ITA CZE POL MEX LVA AUT NOR SVK TUR SWE AUS CAN BEL NLD HUN EST
OECD indicator of insolvency regim e, From least (0 ) to m ost (1) restrictive, 20 16
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Note: The OECD insolvency regime indicator capture (1) personal costs to failed entrepreneurs, (2) lack of preventative and streamlining measures and (3) barriers to restructuring. Higher values of the composite indicator correspond to more inefficiency. Source: Adalet McGowan, M., D. Andrews and V. Millot (2017), "Insolvency regimes, zombie firms and capital reallocation", OECD Economics Department Working Papers, No. 1399.
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Note: The subcomponent captures the stringency of the restrictiveness on the insolvency procedure on failed entrepreneurs, including the length of discharge period. Source: Adalet McGowan, M., D. Andrews and V. Millot (2017), "Insolvency regimes, zombie firms and capital reallocation", OECD Economics Department Working Papers, No. 1399.
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 CAN TUR USA AUS CHL GBR JPN LTU RUS AUT CHE CRI DNK ESP FIN FRA GRC IRL ITA LVA MEX NOR NZL SVK SVN BEL DEU EST HUN ISR KOR NLD POL PRT SWE CZE
The subcom ponent of the OECD insolvency indicator on personal costs of failed entrepreneurs, from least (0 ) to m ost (1) restrictive, 20 16
30
20 40 60 80 20 40 60 80
JPN MEX ITA CHL CZE SVK DEU SVN CAN POL TUR HUN GRC PRT LVA ESP AUT LTU GBR BEL LUX CHE SWE IRL FRA NLD FIN NOR EST DNK
Individuals subm itting form s to authorities online, % of individual surveyed, 20 16
Source: OECD (2017), OECD Digital Econom y Outlook 2017.
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Source: OECD (2015), OECD Product Market Regulation Database.
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 SWE FIN GBR DNK CHE AUS NOR NZL NLD IRL MEX CHL EST OECD ITA JPN KOR FRA CZE ESP BEL SVN ISR DEU AUT SVK PRT GRC HUN CAN POL LUX TUR
Indicator of regulation in professional services, From least (0 ) to m ost (6) stringent
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Source: Akamai (2017), “Akamai’s state of the Internet report: Q1 2017 report”, https:/ / www.akamai.com.
30 60 90 120 30 60 90 120 GRC MEX FRA TUR ITA AUS LUX SVN EST LTU AUT CHL DEU POL PRT SVK IRL NZL DNK GBR FIN CZE HUN CAN LVA NLD ESP BEL NOR USA CHE JPN SWE KOR
Average peak connection speed, Megabits per second, Q1 20 17
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10 20 30 40 50 60 70 10 20 30 40 50 60 70 NOR NZL FIN SWE USA GBR DNK NLD CAN BEL IRL EST KOR ISR AUT CZE FRA POL ITA ESP SVN CHL DEU JPN GRC TUR SVK
Jobs at high risk of autom ation and significant change, % of all jobs
Jobs at high risk of automation Jobs at risk of significant change
Source: Nedelkoska, L. and G. Quintini (2018), "Automation, skills use and training", OECD Social, Employment and Migration Working Papers, No. 202, OECD Publishing, Paris.
Boost entrepreneurship and resource allocation
maintaining adequate safeguards for creditors.
consumer interests.
postal services.
Strengthen digital infrastructure through com petition
Expand social protection for the self em ployed
by old-age pension insurance.
More in Chapter 1 of the Econom ic Survey of Germ any 2018
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PIAAC m ean proficiency scores in literacy
Note: The data refer to 15-65 year-olds Source: OECD (2016), Skills Matter: Further Results from the Survey of Adult Skills.
240 250 260 270 280 290 300 240 250 260 270 280 290 300 FRA OECD AUT USA DEU DNK GBR CAN EST SWE AUS NLD FIN JPN
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PIAAC m ean proficiency scores in literacy, by educational attainm ent
Note: The data refer to 15-65 year-olds Source: OECD (2016), Skills Matter: Further Results from the Survey of Adult Skills.
200 230 260 290 320 350 200 230 260 290 320 350 JPN OECD DEU Less than upper secondary Tertiary Upper secondary
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Population with above basic ICT skills, % of total population, by age cohort, 20 17
Source: Eurostat (2018), Individuals' level of digital skills (database).
15 30 45 60 75 90 15 30 45 60 75 90 EU28 FRA DEU SWE GBR AUT FIN DNK NLD 16-24 year-olds 25-54 year-olds 55-64 year-olds
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Note: Gender differences in problem solving skills at work is captured as the difference in of the mean use of skills between men and women. Source: OECD (2016), Skills Matter: Further Results from the Survey of Adult Skills.
5 10 15 20 25 5 10 15 20 25 FIN GBR(Eng.) SWE USA DNK AUS CAN OECD FRA NLD DEU AUT JPN
Gender difference in PIAAC problem solving skills at work, % of the m ean use of skills by wom en
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Note: The share of students achieving level 3 or above in all three PISA domains (reading, mathematics and science) among the 25% most disadvantaged students in their country according to the PISA index of economic, social and cultural status. Source: Agasisti, T., et al. (2018), "Academic resilience: What schools and countries do to help disadvantaged students succeed in PISA", OECD Education Working Papers, No. 167.
10 20 30 40 50 60 10 20 30 40 50 60 USA AUT FRA SWE OECD GBR AUS DNK DEU NLD FIN CAN JPN
Students with m id-level or higher PISA attainm ent, as % of disadvantaged students
2016 2006
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Note: Difference in PIAAC literacy scores between individuals aged 25-65 with one parent educated to tertiary level and no parent educated to upper secondary level. The adjusted differences take into account differences in age, gender, education, immigrant and language background. Source: OECD (2016), Skills Matter: Further Results from the Survey of Adult Skills.
10 20 30 40 50 60 10 20 30 40 50 60 AUS JPN SWE KOR CAN DNK NLD OECD AUT FIN GBR FRA DEU
Difference in PIAAC literacy scores between individuals with parents with high and low educational attainm ents
Unadjusted Adjusted for socio-economic background
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20,000 40,000 60,000 80,000 100,000 20,000 40,000 60,000 80,000 100,000 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65
Yearly earnings of 25-6 5 year-olds m en, euros
Vocational upper secondary Vocational tertiary education General tertiary education age
Source: Economic Survey of Germany 2018.
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5 10 15 20 25 30 35 5 10 15 20 25 30 35 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Participation in life-long learning, % of population aged 26-6 4 , 20 17
Germany Sweden European Union
Source: Eurostat (2018), Education and training (database).
Im prove equity in education
Reduce skill m ism atch
current 2 months, for the couple to receive the maximum leave entitlement.
Im prove upskilling opportunities in the vocational education system
Boost participation in life-long learning
and foster the recognition of skills acquired on-the-job.
More in the Chapter 2 of the Econom ic Survey of Germ any 2018
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Disclaimers: The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law. 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.