Trade and the greenhouse gas emissions from international freight transport

1. Trade and the greenhouse gas emissions from international freight transport Cristea, Hummels, Puzzello & AvetisyanJEEM 2013

2. Before this paper • Mostly just case studies

3. Saunders, Barber & Taylor 2006 http://researcharchive.lincoln.ac.nz/dspace/bitstream/10182/125/1/aeru_rr_285.pdf • prepared inventory of all energy and CO2 embodied in various agricultural products as produced in UK and New Zealand • included emissions associated with transporting products to UK consumers • includes fertilizers, agri-chemicals, seed, grazing, farm buildings, tractors, fences, irrigation, shipping and road transport

4. Results Table created using data from Saunders, Barber and Taylor 2006

5. Question • Trade and Environment literature looks almost exclusively at trade’s indirect effects • “how does trade liberalization affect a country’s industrial emissions via scale, composition and technique effects?” • Usually dismisses direct effects such as transport emissions

6. Question • Why? • As a fraction of total global emissions, transport’s share is quiet small • And international transport’s share of total transport emissions is small as well • In 2004, international transport’s share of global CO2 emissions was only 3.5%

7. Question • Begs the question as to whether indirect emissions associated with trade are any larger • Moreover, aggregating the data may obscure important variation across sectors

8. This paper • Calculates indirect emissions associated with trade • Emissions generated when producing goods that are traded • Calculates direct emissions • Emissions generated when goods are transported across borders • Compares direct to indirect emissions at sectoral level • Conducts thought experiments • By how much would total emissions rise (or fall) if • all countries produced domestically all the goods they currently consumed? • Doha round trade liberalizations implemented • Projected growth occurs

9. Data • Production and Trade • Global Trade Analysis Project (GTAP) 7 • use 2004 as base year • In principle, GTAP can accommodate • 57 “traded and non-traded sectors” • 113 countries • Requires too much computational power • So aggregate the data into • 40 regions (ofwhich 28 are individual countries) • 23 traded sectors, 6 non-traded service sectors

10. Calculating Weight • Three databases report trade by value and by weight • US Imports and Exports of Merchandise • Eurostats Trade • Aladi trade database • Data reported at 6 digit level of Harmonized system • Authors aggregate up to the 23 merchandise sectors used in this study • Calculate the weight of a particular sector’s products by “separately sum[ming] the weight of trade and volume of trade and express[ing] them as a ratio” (p.158) • “this is equivalent to a share-weighted average of the weight/value ratio for each HS6 product traded by that exporter” (p.158) • Then calculate weighted (by trade) average across all countries for which requisite data exists

11. Modal Shares • Same three databases report modal shares by product category • US Imports and Exports of Merchandise • Eurostats Trade • Aladi trade database • Supplement with • Transborder Surface Freight Data • But these databases only report bilateral trade data for a subset of countries • For 35% of trade no modal information is available • Solution: estimate modal shares using aformentioned data and independent variables such as geography and country and product characteristics • Use fitted coefficients to predict model shares for remaining trade

12. If measure trade by value • Road transport is very important (by value) for North America and Europe • For most regions (excluding North America and Europe) over 2/3 of shipments are by sea • If measure trade by weight-distance • Sea-freight clearly dominates for all regions • Simple explanation: heavy stuff going long distances goes by sea • And the high value shipments within North America and Europe that go by road only cover short distances, so won’t be very significant in a metric of trade by weight-distance

13. Emission Coefficients • Output • Source: GTAP 7 • Computes emission coefficients by product and country • Multiplies use of coal, oil, gas, petroleum products, electricity, gas distribution with CO2 coefficients for each • Also includes non-carbon CO2e based on IPCC methodology • Particularly important for agricultural products • GTAP assumes that emission coefficients • differ across countries • especially according to mix and quantities of fuels used) • Are static • no “technique” effects from trade or growth

14. Transport • Ocean Freight • Ship Emissions Study (National Technical University of Athens Laboratory for Maritime Transport) • Reports grams of CO2 per tonne-km for various vessel types • Air Freight • Various sources • LOWest estimate is 552grams of CO2/tonne-km shipped (based on Boeing 747) • HIGHest estimate is 950g/t-km based on fleet average as reported in Aircraft Economics 1999 • Rail & Road • As reported by European Environmental Agency 2005

15. State the obvious: • Ocean and Rail are considerably less polluting (per tonne-km) than Road or Air • Air is about 80 times as polluting as Ocean

16. Use the data

17. ETodg≡ GHG emissions associated with transporting good gfrom origin o to destination d. VALodg≡ value of good gtransported from origin o to destination d. eTodg≡ emission intensity associated with moving good g from o to d. WVog≡ weight to value ratio for g when produced by o. DISTmod≡ distance from o to d via mode m em≡ GHG emissions associated with mode m (when providing one kg-km of transport services) QSmodg≡ quantity share of good gshipped via mode m Assumed to be linear in distance (which fails in case of air transport) Assumes homogeneity within a mode; fails if old, polluting vehicles used for some shipments and newer equipment for others; example: drayage fleet that crosses US-Mexico border

18. Another consideration • Domestic production also requires transport • Authors treat this as part of output emissions (on next slide) • “If production for external transport uses domestic transport to the same extent as production for domestic use” then there is no problem • Fails if production for export occurs near seaport/border/airport

19. Production emissions EY Emission intensity of o’s g production (grams of CO2e per dollar of output) o‘s output of g (measured in dollars) Share of good g in o’s production Country o’s total output emissions

20. Analysis

21. Dirtiest Industries • Aggregate transport emissions for each industry by summing over all country pairs. • Divide by value of trade • Yields “weighted average transport emission intensity for that industry”

22. “fraction a given sector contributes to the world-wide CO2 emissions from international transport” (p.163)

23. “Fraction of a sector’s transport emission intensity in that sector’s total trade-related CO2 emission intensity” i.e. = eTg/(eTg+eYg) Sectors for which transport emissions are more than half of total trade-related emissions

24. North America is ranked fourth in terms of output emissions but first in terms of export-transport emissions Only refers to traded output Reason: US exports are disproportionately by air Problem: this graph obscures intensitybecause doesn’t control for size (US is very large)

25. =grams of CO2e per dollar of trade Notable: eTo > eYo for all these countries Canadian production is fairly CO2e intensive Some countries with low eYo have quite high eTo -i.e USA Other comparisons: ‘India’s production has 143% more emissions (per dollar of trade) than US, but after incorporating transportation, its exports are less emission intensive in total’ (p.165)

26. Thought Experiment #1 • What if there wasn’t any trade? • Assume everyone continues to consume what they do now • But have to produce it themselves using current technology • Ignore input shortages and/or possible scale economies • Would total emissions rise or fall? • On the one hand, there won’t be any transport emissions • On the other hand, some goods currently produced by low eYog countries will be produced by high eYog countries

27. Horizontal Axis: change in embodied emission intensity of a country’s consumption • A negative value means that trade reduces this country’s “embodied” emissions • 26.5% of trade reduces emissions (31% of world trade by value) • For the mean and median country in the sample, a move to trade raises (embodied) emission intensity of current consumption

28. Highly variable • 41.6% of trade reduces emissions (34.4% by value) • Variability reflects both differences in production techniques: hot houses versus field grown • and freight modes: air for cut flowers versus ocean for commodity grains Special Cases Not much dispersion By value, “80 percent of trade in wearing apparel raises emissions’ (p.165)

29. Thought experiment #2 • Suppose Doha round is successful • Use CGE simulation to predict how emissions will change • By total output • By exports • By imports • By mode

30. “LOW” assumes aviation emission intensity is that associated with most efficient long range planes • “HIGH” corresponds to emission intensity of current US air cargo fleet)

31. Doha scenarios 4 & 5: • Increased access to agricultural markets • Tariff cuts of • 40% to 60% (developed countries) • 20% (developing countries) • See • global output emissions rise • Global transport emissions fall • except under “LOW” scenario

32. Doha scenario 9: • Increased access to agricultural markets • Plus progressive cuts in non-agricultural tariffs • “peak tariffs are cut more than lower tariffs” (p.167) • See • global output and transport emissions rise

33. All tariffs eliminated: • global output falls • Exports rise • Output and transport emissions rise • Rail and road transport falls • Why? • Current system of preferential tariffs (via FTAs and Customs Unions) favours trade between proximate regions. • Much of trade between proximate regions is by land • The tariffs that fall the most will be between distant nations, which will need to use sea or air

34. Growth occurs • Expected at 3.57%/annum • More rapid in China and India than in N.Am & Europe • Predict: • Exports to rise faster than output • Sea and Air transport to increase more than rail and road • Why? • The countries that are expected to grow the most are India and China • These countries are not adjacent to European and North American markets • Will need to use ocean and air freight

35. Final thought experiment • Suppose all countries adopted $50/ton carbon tax • Levied it on transport emissions • What would be the tariff equivalent? • (Expressed as a percent of the value of traded goods)

36. Highest (transport) tariff would only be 4% • For reference: Average current rate ~ 3% • (Current average tariff on minerals = 1.56%)

37. Conclusions & Other Take Away Points • “Two-thirds of trade-related emissions in U.S. exports are due to international transportation” (p.170) • “Worldwide over 75 percent of the trade-related emissions of transport equipment, electronic equipment, machinery, and manufactures NEC come from transportation” (P.170) • Trade & Environment economists should not be ignoring transport emissions!

38. Unanswered questions • How do they calculate DISTmod? E.g. use Chicago or LA or New Jersey? • For countries that are bundled into one of the aggregated regions, are they including exports from one country within that region to another country in that region? • What fraction of global emissions comes from output of traded goods? is it similarly tiny (i.e. on the order of ½%? • If so, then why T&E economists worrying so much about it? • Is it because those trade-exposed industries seem to care, and if you consider the tariffs that are implicit in a 50$ carbon tax, you’d see that these tariffs are non-negligible. • But, really, they are still small. The largest implicit tariff that Cristea et al find is still only 4%, and typical tariffs are around 1%. That seems inconsequential. • Any sense of how direct and indirect emissions compare for other pollutants, e.g. Sulphur emissions?

39. Caveats • Local distribution • French wine consumed in NYC has fewer transport emissions than Californian wine consumed in NYC