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

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Presentation on theme: "Transportation and the NEUJOBS global scenarios Christophe Heyndrickx (TML) Rodric Frederix (TML) Joko Purwanto (TML)"— Presentation transcript:

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 4/23/20152

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 4/23/20153

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 % 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): 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 4/23/20156

7 Overview Transport within Neujobs Main drivers and expected trends Scenario matrix definition Scenario analysis Conclusion 4/23/20157

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 4/23/20158

9 Environmental policy 4/23/20159 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

10 Fossil fuel scarcity 4/23/ 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 4/23/ 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 4/23/ 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 4/23/201513

14 Scenario matrix definition Based on scenario matrix by Fischer-Kowalski (2012) – Background scenario (six megatrends) – Main policy scenario FriendlyTough Strategy 1: Status Quo S1F ‘Careless and globalized world’S1T ‘Challenged and ignorant world’ Strategy 2: Ecological modernization and eco-efficiency S2F ‘Ecologically aware and globalized world’ S2T ‘Challenged, but ecologically aware world’ Strategy 3: Sustainability transformation S3F ‘Sustainable and globalized world’S3T ‘Challenged and sustainable world’ 4/23/ Background Policy

15 Background scenario Energy transition Resource security Climate change effects Economic development Population dynamics ICT & Knowledge No impact on fuel price No impact on materials Low probability for extreme weather events Population stable Exchange rate stable Efficient logistics sector Fuel prices +20% Metal ores +50% Decrease in capital returns transport Labour supply decreases with 10% Depreciation Lower efficiency in logistics FRIENDLYTHOUGH 4/23/201515

16 Background scenario Translation of background scenario in parameters, based on WP9 & 10 and other recent studies Change Friendly ToughComments/ Explanation Yearly GDP growthEU 15: 1.5% EU 12: 3.0% EU 15: 1.0% EU 12: 2.0% GDP growth is one of the main drivers of transport demand Price of coal+10%+15%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 +20%+50%Construction of transport equipment Other raw materials+20%+50%Fuel mix/resource scarcity Price of agricultural products on world market Stable+10%Impact on price of bio-fuels Exchange rateStable (around 1.3 $/euro) - 10% (around 1.2 $/ euro) Raw oil, primary energy inputs and others are mainly import products Efficiency of logistic sector / transport margins Stable-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. Population dynamics: Working population WP 10 The population dynamics in friendly and tough scenarios are based on WP10 by country results 4/23/201516

17 Background scenario (2) Change in work force by skill level (% change ) FriendlyTough LowMediumHighTotalLowMediumHighTotal AT BE BG CY CZ DK EE ES FI FR GR IT LV LT LU MT NL PL PT RO SK SI SE UK /23/201517

18 Scenario matrix definition Based on scenario matrix by Fischer-Kowalski (2012) – Background scenario – Main policy scenario FriendlyTough Strategy 1: No policy changes S1F ‘Careless and globalized world’S1T ‘Challenged and ignorant world’ Strategy 2: Ecological modernization and eco-efficiency S2F ‘Ecologically aware and globalized world’ S2T ‘Challenged, but ecologically aware world’ Strategy 3: Sustainability transformation S3F ‘Sustainable and globalized world’S3T ‘Challenged and sustainable world’ 4/23/201518

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 4/23/201519

20 Policy scenario Translation of policy scenario’s in parameters, based on recent transport studies Distinguish 3 intensities: Status Quo, Modernization, Sustainability SQ MOSU Change in behaviour / efficiency Low changeMedium changeHigh change EEEnergy efficiency increase / year 0.8%1.2%1.5% FEFuel efficiency of cars/year 1.0 %1.5 %2.0 % ELECElectrification of transport NonePartial electrification up to 10% of fleet Partial electrification up to 20% of fleet INTInternalization of external costs of transport TREMOVE Basecase 2030 IMPACT project scenario IMPACT project scenario 5A USEReduced use of own car transport in favour of public transit and car sharing NonePreference for private car transport – 10% Preference for private car transport -20% EFRReduction in administrative inputs to transport (e-Freight) NoneBased on e-Freight project (partial) Based on e-Freight project (full) 4/23/201520

21 Overview Transport within Neujobs Main drivers and expected trends Scenario matrix definition Scenario analysis Conclusion 4/23/201521

22 EDIP Computable General Equilibrium Model EDIP model (developed in REFIT FP6 project) EU 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 4/23/201522

23 EDIP CGE Model 4/23/ Rest of World Goods & services (G&S) FirmsHouseholds Labour, capital Government Investment revenuesbuy G&S wage, capital income hire capital, labour savings Transport module foreign investment/savings income, product taxes transfers hire capital, labour corporate taxes import/export buy intermediate G&S buy G&S

24 Detail of transport module 4/23/201524

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 4/23/201525

26 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 IMPACT BACKGROUND SCENARIO POLICY: STATUS-QUO POLICY: MODERNIZATION IMPACT BACKGROUND SCENARIO POLICY: SUSTAINABILITY Additional impact Sustainability Additional impact Modernization 4/23/201526

27 Methodology Indicators: not only employment 4/23/ IndicatorDescriptionDimension GDP per capita Relative change in Gross Domestic Product per capita, calculated from the demographic change and the expected average growth rate from 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 Measures the emissions of greenhouse gasses under the proposed changes in policy Unemployment Relative change (in percentage point) in unemployment rate from baseline unemployment rate Measures the amount of unemployment. WelfareRelative change in compensating variation 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 revenuesRelative change in total tax revenuesMeasures the government’s tax income

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 4/23/201528

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 4/23/ 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 4/23/ Friendly Tough Countryoutput_simΔMOΔSUΔMOΔSU ATTotal jobs created 9,10015,1008,30915,716 BETotal jobs created 8,1008,9587,7548,600 DETotal jobs created 59,297117,32756,994114,555 ESTotal jobs created 68,485120,03954,523127,457 FITotal jobs created 1,4651, GRTotal jobs created 14,95220,86512,26920,177 PLTotal jobs created 19,57829,60018,06828,150 BGTotal jobs created 5,44510,7308,50711,575 ATTransp eq jobs created-300-1, ,100 BETransp eq jobs created-700-5, ,000 DETransp eq jobs created-23,900-98,200-23,700-97,500 ESTransp eq jobs created-5,300-42,300-2,400-42,000 FITransp eq jobs created GRTransp eq jobs created PLTransp eq jobs created-500-5, ,100 BGTransp eq jobs created ATTransp serv jobs created4,70014,5004,70014,400 BETransp serv jobs created7,60018,1007,40017,800 DETransp serv jobs created152,800306,100152,000305,800 ESTransp serv jobs created44,60099,00044,10098,400 FITransp serv jobs created4,3006,5004,3005,900 GRTransp serv jobs created 11,57926,87812,11727,044 PLTransp serv jobs created13,30034,40012,90034,200 BGTransp serv jobs created6,80014,2006,70013,900

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 4/23/201531

32 Overview Transport within Neujobs Main drivers and expected trends Scenario matrix definition Scenario analysis Conclusion 4/23/201532

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. 4/23/201533

34 Thank you for your attention


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