Transportation and the NEUJOBS global scenarios Christophe Heyndrickx

Transportation and the NEUJOBS global scenarios Christophe Heyndrickx (TML) Rodric Frederix (TML) Joko Purwanto (TML)

Overview • • • Transport within Neujobs Main drivers and expected trends Scenario matrix definition Scenario analysis Conclusion 3/19/2018 2

Transport within Neujobs • Neujobs: future possible developments of the labour market given the upcoming transitions in different fields – – Socio ecological transition Societal transition Skills transition Territorial transition • Focus on transport – Which transitions? … – Ener 3/19/2018 3

Economic situation of transport sector • • € 533 billion in Gross Value Added (GVA) at basic prices Sector employed around 10. 6 million persons (5% total workforce) + around 2. 3 million people working in manufacturing sector 4. 6% of total GDP + 1. 7% in manufacturing sector Land transport (55%) Sea transport (2%) Air transport (4%) Warehousing / storage (22%) Postage /courrier (17%)

Private household transportation • € 904 billion (13% of total consumption) spent on transport-related items in 2010 • 30% on vehicle purchase • 50% on operation (fuel, maintenance, insurance) • 20% on transport services

Transport within Neujobs • Scope: what is the impact of expected trends in the transport sector on employment, given the upcoming socio ecological transitions (SET)? • Top down or bottom up approach? • Mobility is very much related to economic activities – Transport sector (+ vehicle manufacturing sector) – Home work relationship • Top down approach (instead of bottom up): 1. Identification of the main drivers of transport 2. Translation of SET to trends in drivers of transport 3. Estimation of effects of these trends on employment in transport sector, and on society in general with EDIP model 3/19/2018 6

Overview • • • Transport within Neujobs Main drivers and expected trends Scenario matrix definition Scenario analysis Conclusion 3/19/2018 7

Main drivers for changes in transport sector • Based on literature study, we identified 4 main drivers – – 3/19/2018 Driver 1: Environmental policy Driver 2: Fossil fuel scarcity Driver 3: New and more efficient propulsion technologies Driver 4: Developments in logistics 8

Environmental policy • EU target for 2050: 20% of current GHG emissions • Transport emits 23% of current GHG emissions, and share is increasing! → If EU holds on to this target, this implies environmental policy that will have a strong effect on transport 3/19/2018 9

Fossil fuel scarcity • Demand of crude oil: growth especially in Asia (China, India) • Supply of crude oil : more controversial Estimates of Energy Watch Group vs World Energy Outlook • Much uncertainty, but supply and demand suggest that crude oil prices on average will increase in the near future 3/19/2018 10

Propulsion technologies Fuel efficiency trend between 1995 and 2012 (source: TREMOVE) • Fossil fuel combustion engines are in conflict with GHG emission target and fossil fuel scarcity • Fuel efficiency for private cars has already increased • New transport technologies – Electrification – Biomassification 3/19/2018 11

Developments in logistics • e Freight Initiative: information sharing along freight transport chains, especially in the context of multimodal transport – Gain in cost efficiency – Increase in transport volumes • 3 D printing • e Commerce – Effect on transport volumes is small 3/19/2018 12

Overview • • • Transport within Neujobs Main drivers and expected trends Scenario matrix definition Scenario analysis Conclusion 3/19/2018 13

Scenario matrix definition • Based on scenario matrix by Fischer Kowalski (2012) – Background scenario (six megatrends) – Main policy scenario Background Friendly Tough Strategy 1: Status Quo Policy S 1 F ‘Careless and globalized world’ S 1 T ‘Challenged and ignorant world’ Strategy 2: S 2 F ‘Ecologically aware and globalized S 2 T ‘Challenged, but ecologically aware Ecological modernization world’ and eco-efficiency Strategy 3: Sustainability transformation 3/19/2018 S 3 F ‘Sustainable and globalized world’ S 3 T ‘Challenged and sustainable world’ 14

Background scenario Energy transition No impact on fuel price Fuel prices +20% Resource security No impact on materials Metal ores +50% Climate change effects Low probability for extreme weather events Decrease in capital returns transport Population dynamics Population stable Labour supply decreases with 10% Economic development Exchange rate stable Depreciation ICT & Knowledge Efficient logistics sector Lower efficiency in logistics 3/19/2018 FRIENDLY THOUGH 15

Background scenario • Translation of background scenario in parameters, based on WP 9 & 10 and other recent studies Change 2010 - 2030 Yearly GDP growth Friendly EU 15: 1. 5% EU 12: 3. 0% Tough EU 15: 1. 0% EU 12: 2. 0% Price of coal +10% +15% Comments/ Explanation GDP growth is one of the main drivers of transport demand Impact on fuel mix Price of gas +20% +50% Impact on fuel mix Price of petrol +20% +50% Impact on fuel mix Price of metal ores / metal products Other raw materials Price of agricultural products on world market Exchange rate +20% +50% Construction of transport equipment +20% Stable +50% +10% Fuel mix/resource scarcity Impact on price of bio fuels Stable (around 1. 3 $/euro) 10% (around 1. 2 $/ euro) 10% Raw oil, primary energy inputs and others are mainly import products Efficiency of logistic Stable sector / transport margins Population dynamics: Working population 3/19/2018 WP 10 We assume a reduction in efficiency of transport and an increase in the margin of transport in the consumer products due to congestion and climate change related extremes. The population dynamics in friendly and tough scenarios are based on WP 10 by country results 16

Background scenario (2) • Change in work force by skill level (% change 2010 2030) 3/19/2018 Friendly Tough AT BE BG CY CZ DK EE ES FI FR GR IT LV LT LU MT NL PL PT RO SK SI SE UK Low Medium High Total 31. 9 4. 3 55. 8 0. 86 25. 4 4. 8 6. 3 7. 74 28. 1 4. 6 44. 7 6. 26 25. 5 8. 1 22. 2 1. 50 38. 3 16. 4 32. 7 12. 33 32. 6 31. 0 16. 8 28. 65 34. 9 7. 5 62. 1 12. 44 27. 3 3. 2 30. 41 33. 8 11. 4 65. 2 3. 50 20. 8 14. 4 16. 3 10. 86 30. 3 11. 1 48. 3 0. 12 26. 6 4. 8 24. 0 3. 31 26. 3 11. 1 28. 4 2. 17 15. 1 28. 2 16. 5 22. 28 20. 5 3. 4 53. 6 5. 75 24. 6 0. 4 13. 7 8. 00 37. 1 13. 5 30. 8 5. 24 30. 6 5. 6 6. 9 7. 59 31. 7 8. 7 54. 2 0. 52 28. 9 3. 7 30. 4 2. 74 30. 2 0. 4 46. 8 1. 98 29. 9 1. 8 15. 3 7. 57 17. 1 5. 6 80. 1 4. 77 28. 0 13. 5 25. 8 4. 09 46. 5 18. 9 32. 8 12. 65 21. 8 34. 4 5. 7 25. 47 42. 6 29. 5 34. 7 14. 36 19. 9 36. 3 9. 3 21. 23 5. 3 7. 8 69. 5 22. 74 2. 8 8. 8 44. 6 16. 32 27. 2 0. 9 87. 1 7. 96 33. 0 0. 9 24. 7 19. 63 31. 2 5. 7 33. 0 2. 76 26. 4 3. 6 10. 4 6. 78 44. 8 23. 0 61. 8 10. 19 36. 7 24. 4 29. 6 15. 99 18. 6 7. 0 86. 0 1. 91 28. 6 31. 4 35. 1 8. 28 38. 1 2. 1 83. 8 2. 80 27. 8 22. 1 16. 1 19. 28 39. 8 11. 7 62. 7 5. 05 28. 3 12. 8 20. 5 10. 30 24. 9 12. 5 56. 9 1. 01 33. 8 10. 2 21. 9 8. 60 28. 4 0. 4 54. 4 8. 20 17. 5 1. 1 30. 0 3. 45 20. 9 1. 6 39. 0 5. 47 17. 8 2. 7 17. 8 1. 78 17

Scenario matrix definition • Based on scenario matrix by Fischer Kowalski (2012) – Background scenario – Main policy scenario Friendly Tough Strategy 1: No policy changes S 1 F ‘Careless and globalized world’ S 1 T ‘Challenged and ignorant world’ Strategy 2: S 2 F ‘Ecologically aware and globalized S 2 T ‘Challenged, but ecologically aware Ecological modernization world’ and eco-efficiency Strategy 3: Sustainability transformation 3/19/2018 S 3 F ‘Sustainable and globalized world’ S 3 T ‘Challenged and sustainable world’ 18

Policy scenario • Consider 6 relevant transport policy scenario’s, related to the identified main drivers (environmental policy, fossil fuel scarcity, propulsion technology, logistics developments) – – – increase in energy efficiency (EE) increase in fuel efficiency (FE) introduction of electric mobility (ELEC) internalization of external costs (INT) increased use of public transport (USE) e Freight (EFR) • 3 main policy scenario’s (Status Quo, Modernization, Sustainability) indicate the intensity of the transport policy • Note: other scenario’s possible, selection based on likelihood and data availability 3/19/2018 19

Policy scenario • Translation of policy scenario’s in parameters, based on recent transport studies • Distinguish 3 intensities: Status Quo, Modernization, Sustainability SQ MO SU Low change Medium change High change Change in behaviour / efficiency 2010 2030 EE Energy efficiency increase / year 0. 8% 1. 2% 1. 5% FE Fuel efficiency cars/year Electrification of transport 1. 0 % 1. 5 % 2. 0 % None Partial electrification up to 10% of fleet up to 20% of fleet ELEC of INT TREMOVE Basecase 2030 IMPACT project scenario 2 2030 USE Reduced use of own car transport in favour of public transit and car sharing None Preference for private car transport 20% – 10% EFR 3/19/2018 Internalization of external costs of transport IMPACT project scenario 5 A 2030 Reduction in administrative inputs to transport (e Freight) None Based on e Freight project (partial) Based on e Freight project (full) 20

Overview • • • Transport within Neujobs Main drivers and expected trends Scenario matrix definition Scenario analysis Conclusion 3/19/2018 21

EDIP Computable General Equilibrium Model EDIP model (developed in REFIT FP 6 project) EU 27 + 4 countries (CH, NO, TR, HR) Strong disaggregation of transport sector Integrated with SILC micro data for analysis of social effects Detailed specification of labour market (several skill levels and occupations) • Follows 2 digit NACE classification • Calibrated on recent input output tables • CES – functions with econometrically estimated elasticities of substitution • • • More complex, but more realistic representation of economy • Caveat: model results indicate the order of magnitude and the direction of change following from a certain policy measure 3/19/2018 22

EDIP CGE Model import/export Rest of World foreign investment/savings Investment savings Goods & services (G&S) buy G&S Households Transport module revenues buy intermediate G&S wage, capital income Labour, capital Firms hire capital, labour income, product taxes transfers 3/19/2018 Government corporate taxes buy G&S 23

Detail of transport module 3/19/2018 24

Methodology • 8 countries from macro regions in Europe – – Western-European countries: Belgium, Germany, Austria Nordic countries: Finland Eastern-European countries: Bulgaria, Poland Southern-European countries: Spain, Greece • Base year, reference year and status quo scenario – Base year: EDIP 2010 – Reference year: EDIP 2010 with constant growth rate till 2030 respective for friendly and tough background scenario – Status quo: EDIP 2010 with constant growth rate till 2030 respective for friendly and tough background scenario + Status Quo policy scenario 3/19/2018 25

Methodology • 8 countries from macro regions in Europe – – Western-European countries: Belgium, Germany, Austria Nordic countries: Finland Eastern-European countries: Bulgaria, Poland Southern-European countries: Spain, Greece • Base year, reference year and status quo scenario Additional impact Sustainability Additional impact Modernization POLICY: STATUS-QUO IMPACT BACKGROUND SCENARIO 3/19/2018 POLICY: MODERNIZATION IMPACT BACKGROUND SCENARIO POLICY: SUSTAINABILITY IMPACT BACKGROUND SCENARIO 26

Methodology • Indicators: not only employment Indicator Description Dimension GDP per capita Relative change in Gross Domestic Product per capita, calculated from the demographic change and the expected average growth rate from 2010 2030 Measures economic activity and production. Includes taxes on final consumption and taxes on income. GHG per capita Relative change in Greenhouse Gas Emissions per capita, calculated from the expected increase in fuel efficiency and the demographic change from 2010 2030 Measures the emissions of greenhouse gasses under the proposed changes in policy Unemployment Relative change (in percentage point) in unemployment rate from baseline unemployment Measures the amount of unemployment. rate Welfare Measures total consumption of the population Transport serv Relative change in employment in public transport services Measures employment in the public transport sector Transport eq Relative change in employment in the transport equipment and related manufacturing sectors Measures employment in the automobile manufacturing sector. Tax revenues 3/19/2018 Relative change in compensating variation Relative change in total tax revenues Measures the government’s tax income 27

Results • Many dimensions: – – Background scenario (friendly, though) Main policy scenario (status quo, modernization, sustainability) Countries (AT, BE, BG, ES, FI, GR, PL) Transport policies (EE, FE, ELEC, INT, USE, EFR, FULL) • In total 2 × 3 × 8 × 7 = 336 scenario’s, and 7 indicators for each scenario 3/19/2018 28

Results Employment effects in friendly scenario, by transport policy scenario, absolute numbers (FTE’s) • • Total employment and GDP increases in all countries due to transport policies, but differences in magnitude between countries due to different economic structure Certain policies have negative effect on employment – Decrease of fuel tax revenues leads to less employment • • Different main policy scenario has impact on magnitude of change Different background scenario does not influence the impact of the transport policies very much 3/19/2018 29

Results Country AT BE DE ES FI GR PL BG output_sim Total jobs created Total jobs created Transp eq jobs created Transp eq jobs created Transp serv jobs created Transp serv jobs created Friendly Tough ΔMO ΔSU 9, 100 15, 100 8, 309 15, 716 8, 100 8, 958 7, 754 8, 600 59, 297 117, 327 56, 994 114, 555 68, 485 120, 039 54, 523 127, 457 1, 465 1, 166 161 764 14, 952 20, 865 12, 269 20, 177 19, 578 29, 600 18, 068 28, 150 5, 445 10, 730 8, 507 11, 575 300 1, 100 700 5, 200 800 5, 000 23, 900 98, 200 23, 700 97, 500 5, 300 42, 300 2, 400 42, 000 200 500 940 768 469 949 500 5, 400 300 5, 100 200 4, 700 14, 500 4, 700 14, 400 7, 600 18, 100 7, 400 17, 800 152, 800 306, 100 152, 000 305, 800 44, 600 99, 000 44, 100 98, 400 4, 300 6, 500 4, 300 5, 900 11, 579 26, 878 12, 117 27, 044 13, 300 34, 400 12, 900 34, 200 6, 800 14, 200 6, 700 13, 900 • Increase of employment in transport services, decrease in transport manufacturing 3/19/2018 30

Results • … • The employment rate increases about 0. 25%, with a range between 0. 02% and 0. 57%. • Transport polices increase GDP by around 0. 5% , with a range between 0. 04% and 1. 19%. • Transport policies reduce emissions of greenhouse gasses and related pollutants by around 1 9% – increase in energy efficiency – reduction in the use of private mobility 3/19/2018 31

Overview • • • Transport within Neujobs Main drivers and expected trends Scenario matrix definition Scenario analysis Conclusion 3/19/2018 32

Conclusion • Transport is being influenced by multiple drivers – we focus on a few that are important in the near future • In the SET we see employment shifting from transport manufacturing towards transport services • Transport policies increase total employment and GDP in all countries, while at same time GHG emissions are reduced – important because one of the main obstacles for introducing policies that reduce emissions is fear for loss of employment and reduced GDP. 3/19/2018 33

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