Analyzing Relationships between Global Trade Patterns and Domestic Freight Operations

Transcription

1 Analyzing Relationships between Global Trade Patterns and Domestic Freight Operations Matthew Roorda, Chris Bachmann, Chris Kennedy Integrating Innovative Solutions in Goods Movement Moving Ahead - York University June 20, 2014

2 Outline Background and motivation Conceptual framework Modelling Validation and applications Future work 2

3 Motivation 3

4 Research Objective: Analyze the effects of changing global trade patterns on domestic freight operations Method: Create a joint model of trade and transportation Applications: Scenarios/shocks to trade and/or transportation 4

5 Spatial economic and transport interaction (SETI) process Activities Components Interactions Transport System Spatial Economic System Travel Demand Activity Generation Transport Supply Activity Location Accessibility 5

6 Different types of flows Goods Production Producers Consumers Terminal Dollars Stop Distribution Center Stop Consumption Depot Stop Vehicle Commodity Indirect Flow Direct Flow Region Boundary 6

7 Multi-scale perspective Trade transcends scales 7

8 Conceptual framework - Trade Consumption by Sector and Region Trade Choices Model From Freight Model Global Economic Model Provincial Economic Model Regional Economic Model Trade Choices Economic Variables (e.g., GDP) Trade Flows Transport Costs Other Attributes (e.g., Trade Agreements) To Freight Model 8

9 Conceptual framework - Freight Value to Quantity Transformation Trade Flows Mode Choice Model From Economic Model To Economic Model Shipments Between Zones Macroscopic Traffic Simulation Transport Costs 9

10 Input-output (IO) models Used for Economic Impact Analysis (EIA) I.e., how a price or demand shock trickles through economies Industries are linked through technical coefficients or recipes Motor Vehicles Tires Steering Wheels Rubber Metal Plastic 10

11 Multi-region IO (MRIO) models A spatial extension to IO models Regions are linked through trade coefficients creating supply chains Canadian Demand Chinese Supply United States Supply 11

12 Random utility based MRIO (RUBMRIO) RUBMRIO Trade coefficients are functions of transportation and economic variables Trade Coefficient Transport Variables Economic Variables Transport Cost Transport Distance Price Market Size 12

13 Accounting for different sectoral representations Sub-region Sector 1 Region Sector 1 Region Sector 2 Region Sector 3 Sub-region Sector 2 Sub-region Sector 3 Sub-region Sector 4 Sub-region Sector 5 13

14 Accounting for different IO table configurations Industry-by-Industry Approach Commodity-by-Industry Approach 14

15 Estimating make and use tables for economic regions (ERs) of Ontario Population Data Employment Data Commercial Vehicle Survey Data Optimized Make and Use Tables 15

16 Current trade model details Spatial scales 47 countries Canada s 13 provinces and territories Ontario s 11 economic regions Ontario Canada Quebec United States Sector representations Global: 37 industrial sectors Provincial/regional: 25 industrial sectors and 50 commodities Toronto Ottawa 16

17 Outputs (US dollars x 1,000,000,000) Outputs (US dollars x 1,000,000,000) Validation results Gross output Motor Vehicles Statistics Canada Commodity Ontario MADP: 7.81% Statistics Canada MSMRIO Mineral Fuels Alberta MADP: 9.48% Statistics Canada Commodity Statistics Canada MSMRIO 17

18 Example application: US food products shock 1st, 2nd, and 3rd largest commodity production effects 1 st % ($x10 6 ) 2 nd % ($x10 6 ) 3 rd % ($x10 6 ) Shock: Food products, beverages and tobacco (OECD #3) = $47, (2005 US Import Final Demand) 2 (double) = $95, Ontario Alberta British Columbia Fruit, vegetables i Meat, fish ii Meat, fish 13.9% (1,724.1) 21.2% (966.7) 15.1% (360.3) Soft drinks iii Fruit, vegetables Fruit, vegetables 9.3% (575.8) 11.1% (209.5) 11.1% (182.4) Meat, fish Soft drinks Soft drinks 7.4% (727.1) 4.9% (62.4) 5.5% (97.3) [i] Fruit, vegetables and other food products, feeds (Statistics Canada Commodity #10) [ii] Meat, fish and dairy products (Statistics Canada Commodity #9) [iii] Soft drinks and alcoholic beverages (Statistics Canada Commodity #11) 18

19 Continuing Research Trade model Develop elastic trade coefficients Freight model Conversion of commodity values ($) into multi-modal freight flows Vehicle flows are not necessarily the same as commodity flows (e.g., vehicle tours, transshipment centers, etc.) Integration with traffic simulation 19

20 Potential applications Freight demand modeling E.g., what is the influence of a European trade agreement on travel patterns in southern Ontario? Economic impact analysis Transportation project and policy analysis 20

21 Questions 21