Transportation and the NEUJOBS global scenarios

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

2. Overview • Transport within Neujobs • Main drivers and expected trends • Scenario matrix definition • Scenario analysis • Conclusion

3. 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

4. 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

5. 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

6. 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): • Identification of the main drivers of transport • Translation of SET to trends in drivers of transport • Estimation of effects of these trends on employment in transport sector, and on society in general with EDIP model

7. Overview • Transport within Neujobs • Main drivers and expected trends • Scenario matrix definition • Scenario analysis • Conclusion

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

9. 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 tothis target, thisimpliesenvironmental policy thatwill have a strong effect on transport

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

11. Propulsion technologies • 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 Fuel efficiency trend between 1995 and 2012 (source: TREMOVE)

12. 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 • 3D printing • e-Commerce • Effect on transport volumes is small

13. Overview • Transport within Neujobs • Main drivers and expected trends • Scenario matrix definition • Scenario analysis • Conclusion

14. Scenario matrix definition • Based on scenario matrix by Fischer-Kowalski (2012) • Background scenario (six megatrends) • Main policy scenario Background Policy

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

16. Background scenario • Translation of background scenario in parameters, based on WP9 & 10 and other recent studies

17. Background scenario (2) • Change in work force by skill level (% change 2010-2030)

18. Scenario matrix definition • Based on scenario matrix by Fischer-Kowalski (2012) • Background scenario • Main policy scenario

19. 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

20. Policy scenario • Translation of policy scenario’s in parameters, based on recent transport studies • Distinguish 3 intensities: Status Quo, Modernization, Sustainability

21. Overview • Transport within Neujobs • Main drivers and expected trends • Scenario matrix definition • Scenario analysis • Conclusion

22. EDIP Computable General Equilibrium Model • EDIP model (developed in REFIT FP6 project) • EU27 + 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

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

24. Detail of transport module

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 • 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

26. POLICY: STATUS-QUO POLICY: SUSTAINABILITY POLICY: MODERNIZATION Methodology IMPACT BACKGROUND SCENARIO IMPACT BACKGROUND SCENARIO IMPACT BACKGROUND SCENARIO • 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

27. Methodology • Indicators: notonlyemployment

28. 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 × 7 = 336 scenario’s, and 7 indicators for each scenario

29. Results • 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 Employment effects in friendly scenario, by transport policy scenario, absolute numbers (FTE’s)

30. Results • Increase of employment in transport services, decrease in transport manufacturing

31. 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

32. Overview • Transport within Neujobs • Main drivers and expected trends • Scenario matrix definition • Scenario analysis • Conclusion

33. 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.

34. Thank you for your attention