Frank Troch, Thierry Vanelslander, Hilde Meersman, Christa Sys BRAIN-TRAINS Macro-economic impact of rail freight in Belgium What can be the future added value? Frank Troch, Thierry Vanelslander, Hilde Meersman, Christa Sys BELSPO project 06/10/2016 – ETC, Barcelona Good morning everyone, thank you for joining me at this early hour. I hope you had a good cup of coffee to wake you up  Today I will present to you the work that we have been performing in the BRAIN-TRAINS project, and more specifically the part on macro-economic impact of rail freight in Belgium.

Agenda Introduction: Project context and research objective Part 1: Methodology Part 2: Data Part 3: First results Conclusion and next steps Part 1 Part 2 Part 3 The results of this presentation are very recent and not fully validated yet, so what I will present to you has to be interpreted with care and I will make clear during the presentation how we obtained these results, what are the constraints of the calculations and how we are planning to continu the research. Conclusion 2/18 2/15

Introduction – Project objective Starting point Weak usage of rail EC (2011) White Paper goals Scope Scenario's & SWOT Part 1 Part 2 Part 3 BRAIN-BE Objective The Brain-Trains project is part of the BRAIN-BE program which is initiated by BELSPO, the Belgian Science Policy Office for scientific research. It is an interdisciplinary project in which five different partners from the University of Antwerp and the University of Liege, two universities in Belgium, are working together to perform research on rail freight strategies and developments in five different fields. The starting point of the project is the current relative weak usage of rail freight transport in Belgium and the ambitious goals set in the European Commissions White Paper of 2011, striving for a 30% shift of road transportation above 300km towards rail and inland waterways by 2030. Despite this goal the modal share of rail freight continues to decline over the years. Although the main focus or scope will be on Belgium, due to its small geographical territory and the international character of rail transportation, the European context has to be taken into account as well. The research objective of this project in general is to develop a blueprint or a model in which the necessary conditions and criteria for an effective and attractive rail freight are set. This model can then be used by both rail freight users and decision makers, to measure the impact of possible decisions and developments, and define strategies that can be applied to make rail freight transport development a success story. Operational framework with criteria and conditions Define indicators and strategies to achieve success story Conclusion Share of rail freight ↗↗ 3/18 2/15

Introduction – Project structure Part 1 Part 2 Part 3 This figure is showing the overall structure of the BRAIN-TRAINS project in a schematic way. The project started off with the development of a general SWOT analysis in each of the five different fields shown, from which three possible future development scenarios have been explored. This was finished and presented on the ETC conference last year in Frankfurt. Now the project has moved into its second phase, the quantification methodologies. Each partner is focussing on their field within the disciplinary research in order to perform the necessary calculations.This presentation will handle the third task, dealing with the macro-economic impact of rail freight transport on the national belgian economy. Outpput: indactors and synthesis Conclusion 4/18 2/15

Introduction – Macro-economic impact Context (Rail) freight transport Rest of the economy Direct Indirect Economic value Strategic significance Research objective for this task Develop a methodology to quantify direct and indirect economic impact and strategic significance of rail freight transport in Belgium Research approach Input-Output analysis (Coppens et al., 2007) Part 1 Part 2 Part 3 Imapct of rail freight on the rest of the economy Direct impact = each additional investment or demand increases directly the output of the sector and as such the output of the economy  Indirect impact = each sector requires input from other sectors, due to which the output in these sectors also increases, which impacts the national economy. This continues, where a chain reaction of input-output triggers is given within the national economy, creating indirect effects. Economic value = the monetary value Strategic significance = why is a sector active in a certain region, and as such contributing to the economy of this region or country ? Conclusion 5/18 2/15

Methodology (1/5) Starting point: supply & demand tables Introduction Starting point: supply & demand tables Example supply table (OUTPUT) Example demand table (INPUT) Part 1 Part 2 250 Part 3 = 150 Conclusion 6/18 = 85  Added value = 150 – 85 = 65 2/15

Methodology (2/5) Step 1: correct demand table Introduction Step 1: correct demand table Supply table = basic prices (product value) Demand table = commercial prices (incl. taxes, subsidies, transport margins, handling margins) Step 2: Combine tables (sector – sector) Compare supplies and demands Calculate ratios: (Supply of each product made by sector A) x (Relative use of each product by sector B) Part 1 Part 2 Part 3 Conclusion 7/18 2/15

Methodology (3/5) - example Introduction CHEMICALS – PLASTICS 100 PVC supplied by CHEMICALS* 20 out of 100 PVC used by PLASTICS = 20 50 Plastics supplied by CHEMICALS * 25 out of 250 plastics used by PLASTICS = 5 20 + 5 = 25 Part 1 Part 2 Part 3 Conclusion 8/18 2/15

Methodology (4/5) How to read the INPUT-OUTPUT table? Introduction How to read the INPUT-OUTPUT table? Top – bottom = INPUT reading: Column sector is using x from row sector Left – right = OUTPUT reading: Row sector is supplying x to column sector “The car industry is using 90 inputs, of which 2 from chemicals, 8 from the plastics sector, 35 from the machines sector, 17 from the car sector, 25 energy and 3 import” “ For each 200 outputs created by the car industry, 17 are going to the car industry, 158 are exported and 25 are final demand” Part 1 Part 2 Part 3 Conclusion 9/18 2/15

Methodology (5/5) Step 3: calculate Leontief multiplier Introduction Step 3: calculate Leontief multiplier Direct + indirect economic value of a sector How? Matrices! L = [I – (X * x-1)]-1 (1) L = Leontief matrix X = Input-Output matrix x-1 = Inverted diagonal matrix with total output values I = Identity matrix Leontief = impact of ∆ final demand F.ex. Leontief multiplier 1,06 for Car Industry: “For each additional EUR (input) in final demand of the car industry, the total output of the economy will increase by 1,06” Part 1 Part 2 Part 3 Each input-output value is multiplied by the inverted total output of a sector. The identity matrix is then deducted by this value in order to avoid double counting direct effects. To reach the multiplier, the final matrix is again inverted. Multipliers obtained show the total impact on the output of a national economy for a change in final demand. Conclusion 10/18 2/15

Idea is to filter “rail freight transport” out of national data Introduction Data challenges National input-output table: 60 sectors “Land transportation and communication” Time delay Confidentiality of data Inseparable data for intermodal analysis Cross-border sales (European transport) Data solution Direct data from the national incumbent operator Idea is to filter “rail freight transport” out of national data Use of NACE-codes for sector division Integration in national supply – demand tables Part 1 Part 2 Part 3 National input-out table => 60 sectors = passenger & goods Time delay: 2010  every 5 years. So in 2015 input output of 2010, In 2020 input output of 2015 will be published. Use and demand tables are released every year with a time delay of 4 years (2011 released in 2015). Confidentiality (big companies, know about who it is handling) Intermodal data is included in the total data, not kept seperatly in the accounts of the rail operator companies Cross border sales (European/internatioinal character) STUCK Solution  data from B Logistics (incumbent operator, 70-80% market share): all supplier and customer data of 2011, Filtering these data out of the land transport sector in the national input output table, splitting this sector into 2 different columns in the demand and supply table, and with these data recalculate the input output matrix for 2011 and as such also the multipliers. To do this, the customer and suppier data was linked to the corresponding NACE code, in order to link all transactions to the corresponding sectors. Conclusion 11/18 2/15

Context for interpretation of the first results Data Introduction Data assumptions (for first analysis) Context for interpretation of the first results Data only representing incumbent rail operator (market share of +/- 80%) No correction for handling margins, subsidies and taxes Data of 2010 Multiple NACE codes for a company: Primary code Total output of rail freight is unknown (final demand): relative value  Not a final true multiplier, but a first draft of a “best estimation multiplier” for the rail freight market in Belgium Part 1 Part 2 Part 3 Preliminary analysis, very recent first results, further validation and testing needs to occur. Data 2011: structure of B Logistics changed, also economy changed Primary code = main activity Conclusion 12/18 2/15

First results – Actor relations Introduction Actor relations (rail company as central point) Equipment leasing Regulator Part 1 Freight forwarder Rail freight organizer Government Part 2 Shipper Rail company Infrabel Part 3 Terminal operator Rail supplier Hinterland transport Conclusion 13/18 2/15

First results – Actor relations Introduction The case of B-Logistics (Belgium territory) Equipment leasing Regulator Detailed sector relations ?  I/O analysis ! Part 1 Freight forwarder Xpedys / COBRA 54 % 7 % Government Part 2 Shipper < 1 % B Logistics Infrabel Which suppliers?  I/O analysis ! Part 3 38 % IFB Rail supplier Hinterland transport Conclusion 13/18 2/15

First results – Input-output table Introduction 65 x 65 - matrix Transport sectors Main input & output from and to ‘land transport’ & ‘transport support’ Low absolute values (1% of ‘land transport’) Part 1 Part 2 Part 3 Conclusion 14/18 2/15

First results – Leontief multiplier Introduction Relative importance per additional euro final demand Sector Multiplier 2010 (national) Multiplier 2010 (data analysis) Land transport (excl. rail) 1,66 1,60 Rail freight transport 2,03 Inland waterways 1,63 Air transport 1,72 1,73 Storage and transport services 1,67 1,69 Construction industry 2,06 Car industry 1,48 Part 1 Part 2 Part 3 Big indirect effects with land transport and transport service activities Spread smaller effect with multiple other sectors Multiplier values of non-related sectors (constr, car, …) remain identical under the used assumptions, which indicates a first validity of the model. Howeever should be further tested and validated. Conclusion 15/18 2/15

First results – “Rail Freight” sector relationships Introduction Input-output table: Multipliers: Strongest input links Land transport (excl. Rail) Storage and transport services Business supporting activities Strongest output links Land transport (excl. Rail) Metal industry Construction industry Part 1 Part 2 Part 3 Strongest links Weakest links Land transport (excl. Rail) Fishery and forest farming Storage and transport services Furniture manufacturing Legal and accounting services Art and amusement sector Legal and accounting services = taxes, duties, accounting services Other indirect effects spread equally over all other sectors 0,44 < 0,01 Conclusion 0,22 < 0,01 0,05 < 0,01 16/18 2/15

Conclusion Rail Freight might have high indirect economic effects Introduction Rail Freight might have high indirect economic effects Multiple connections with all national sectors. Main economic link with land transport and supporting activities. Further research: Validate first results Refine the model (release assumptions) Create a link with employment Implement different exploration scenarios Part 1 Part 2 Part 3 Conclusion 17/18 2/15

Thank you for your attention. Questions? BRAIN-TRAINS BELSPO project