International Trade Data: Classification, Sources, and Applications Prepared for NABE

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International Trade Data Classification,
Sources, and ApplicationsPrepared for NABEs
5th AnnualProfessional Development SeminarJune
16-18Federal Reserve Bank of Dallas
Global Economic Consulting Associates, Inc.1437
Country Club Drive Springfield, PA 19064 Phone
[phone]Fax [phone]Email
allens_at_gecainc.com

• Allen Shaw
• Chief Economist

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Discussion Outline

• International Data Classifications
• Sources
• Applications
• 3.1 Forecasting
• 3.2 Potential Market Analysis
• 3.3 International Trade Analysis

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1. International Trade Data Classifications

• Three commonly used classifications
• 1. Broad economic category (BEC)
• Equivalent to BEAs end-use category
• 2. Standard international trade classification
  (SITC)
• 3. Harmonized system (HS)

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1. International Trade Data Classifications
(Continued)

• 1.1 Broad Economic Category (BEC)

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1. International Trade Data Classifications
(Continued)

• 1.1 Broad Economic Category (BEC)
• The BEC was originally designed to serve as a
  means for converting external trade data compiled
  on the SITC into end-use categories that are
  meaningful within the framework of the System of
  National Accounts (SNA), namely categories
  approximating the three basic classes of goods in
  the SNA capital goods, intermediate goods and
  consumption goods. Specifically, the
  subcategories of the BEC can be aggregated to
  approximate these three classes of goods.

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1. International Trade Data Classifications
(Continued)

• This aggregation permits external trade
  statistics to be considered jointly with other
  sets of general economic statistics, such as
  national accounts and industrial statistics, for
  national, regional or world level economic
  analysis.

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1. International Trade Data Classifications
(Continued)

• 1.2 SITC
• SITC was developed by the UN with the intention
  of classifying traded products not only on the
  basis of their material and physical properties
  and stage of processing but also their economic
  functions in order to facilitate economic
  analysis.
• Rev. 1 from 1962,
• Rev. 2 from 1976,
• Rev. 3 from 1988, and
• Rev. 4 from 2007

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1. International Trade Data Classifications
(Continued)

• Advantages
• Classifies all commodities into headings suitable
  for economic analysis
• Longer historical data
• Disadvantages
• Lack of newer products

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1. International Trade Data Classifications
(Continued)

• Rev. 4 has
• 10 one-digit sections,
• 67 two-digit divisions,
• 262 three-digit groups,
• 1,023 four-digit groups, and
• 2,970 five-digit headings

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1. International Trade Data Classifications
(Continued)

• SITCs 10 Sections
• 0 - Food and live animals1 - Beverages and
  tobacco2 - Crude materials, inedible, except
  fuels3 - Mineral fuels, lubricants and related
  materials4 - Animal and vegetable oils, fats and
  waxes5 - Chemicals and related products, nes6 -
  Manufactured goods classified chiefly by
  material7 - Machinery and transport equipment8
  - Miscellaneous manufactured articles9 -
  Commodities and transactions not classified
  elsewhere in the SITC

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1. International Trade Data Classifications
(Continued)

• 1.3 Harmonized System (HS)
• HS has a more precise breakdown of the products'
  individual categories and is widely used by
  customs authorities.
• HS1988,
• HS1996,
• HS2002, and
• HS2007
• Has about 6,000 commodities

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1. International Trade Data Classifications
(Continued)

• HSs 96 Chapters
• 01-05  Animal Animal Products06-15  Vegetable
  Products16-24  Foodstuffs25-27  Mineral
  Products 28-38  Chemicals Allied Industries
  39-40  Plastics / Rubbers 41-43  Raw Hides,
  Skins, Leather, Furs44-49  Wood Wood
  Products50-63  Textiles 64-67  Footwear /
  Headgear68-71  Stone / Glass 72-83  Metals
  84-85  Machinery / Electrical86-89
   Transportation 90-97  Miscellaneous 98-99
   Unspecified, Reserved for National Use

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Discussion Outline

• International Data Classifications
• Sources
• Applications
• 3.1 Forecasting
• 3.2 Potential Market Analysis
• 3.3 International Trade Analysis

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2. Sources

• 2.1 Annual Data
• 1. United Nations - Commodity Trade Statistics
  Database (Comtrade) (http//comtrade.un.org/db/)
• Has all three classifications in various
  revisions
• Small lunch is free and all you can eat is
  5,775/yr.
• 2. Statistics Canada - World Trade Analyzer
  (http//www.statcan.ca/bsolc/english/bsolc?catno6
  5F0016X)
• Adjusts and simplifies UNs Comtrade
• Uses SITC Rev. 2 for trade data for over 180
  partners and over 800 commodities from 1985

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2. Sources (Continued)

• 1-3 Users 4,155 initial purchase, 2,070
  subsequent update
• 3. Individual countries customs or
  statisticalagency (see IMFs SDDS or GDDS
  websites)
• 4. Global Economic Consulting Associates,
  Inc. (http//www.gecainc.com)
• Carries Comtrade with analytical indicators

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2. Sources (Continued)

• 2.2 Monthly Data
• 1. Individual countries customs or statistical
  agency (see IMFs SDDS or GDDS websites)
• EU countries, Japan, etc. are free. Others
  cost as much as 10,000 per month.
• Difficult to establish right contacts because
  of language and technical problems
• 2. IMF Direction of Trade Statistics
  (http//www.imfstatistics.org/DOT/)
• Contains only total merchandise
• 525/yr.

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2. Sources (Continued)

• 3. Global Economic Consulting Associates, Inc.
  (http//www.gecainc.com)
• 6-10 digit HS commodity details for about 60
  countries.
• With analytical software
• Affordable

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Discussion Outline

• International Data Classifications
• Sources
• Applications
• 3.1 Forecasting
• 3.2 Potential Market Analysis
• 3.3 International Trade Analysis

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3. Applications

• 3.1 Forecasting
• Use end-use classification that can link imports
  to final demand

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3. Applications (Continued)

• 3.1 Forecasting
• Analysis focuses on
• Exchange rate pass-through
• Relative price and income elasticities between
  exports and imports

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3. Applications (Continued)

• 3.2 Potential Market Analysis
• Use HS classification that gives commodity
  details
• Analysis focuses on market size or market share

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3. Applications (Continued)

• 3.3 International Trade Analysis
• Use annual data in SITC for longer historical
  data and HS for the latest periods
• Analysis focuses on
• A. Exports
• Market share
• Export concentration as measured by Herfindahl
  indices
• Similarity
• Balassas revealed comparative advantage
• Export decomposition

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3. Applications (Continued)

• B. Imports
• Import distribution
• Import concentration as measured by Herfindahl
  indices
• Shaw-Kilpatrick-Lees revealed symmetric import
  concentration
• C. Intra-industry Trade
• Grubel-Lloyd index
• Vona index

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3. Applications (Continued)

• D. Overall International Trade Analysis
• Trade openness ratio
• Trade complementarity
• Shaw-Kilpatrick-Lees revealed symmetric
  competitiveness index
• Mirror trade data discrepancies as an indicator
  for customs evasion
• Cross-sectional unit price variation as an
  indicator for trade-based laundering or customs
  evasion

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3. Applications (Continued)

• Question Does China compete with the US in the
  world export markets?
• We could address the question by
• Analyzing the degree of overlapping in top 40
  commodities in exports
• Examining similarity index (SI), 0 lt SI lt 100
• 0 not similar at all
• 100 identical export distribution
• Comparing revealed comparative advantages

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3. Applications (Continued)

• Table 3 compares Chinese and US exports to the
  world (the top 40 products) in terms of export
  distribution at HS2002 6-digit level in 2006. It
  is interesting to note that among the top 40
  products (in terms of export distribution), only
  11 products overlap.

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3. Applications (Continued)

• Similarity index is defined by Finger and Kreinin
  as
• S(ab,c) ? Min X i (ac), X i (bc)
• 0 lt S(ab,c) lt 100
• Where
• S(ab,c) similarity between exports of
  countries a and b to a
  common market c
• X i (ac) share of commodity i in as
  exports to c X i (bc) share of commodity
  i in bs exports to c

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3. Applications (Continued)

• Table 5 shows the similarity index between
  Chinese and US exports at the HS2002 6-digit
  level. The similarities between Chinas exports
  to the world and US exports to the world were
  also relatively low.

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3. Applications (Continued)

• Revealed Comparative Advantage (RCA), developed
  by Bela Balassa1 in his 1965 paper, is a commonly
  used indicator to show (reveal) export
  competitiveness
• RCA of a commodity or sector is defined as a
  countrys share in total world exports of that
  commodity or sector relative to the countrys
  overall share of world trade.
• 1. Balassa, B. (1965), Trade Liberalization and
  Revealed Comparative Advantage, The Manchester
  School of Economic and Social Studies, Vol. 32,
  pp. 99-123.

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3. Applications (Continued)

• RCA ranges from 0 to infinity with 1 as the
  break-even point. An RCA value of less than 1
  means that the sector has no export comparative
  advantage, while a value above 1 indicates that
  the sector has a revealed comparative
  advantage. However, RCA is not symmetrical in the
  sense that one cannot compare both sides of the
  break-even point.

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3. Applications (Continued)

• Laursen2 modified RCA to make the indicator
  symmetric, with the value ranging from -1 to 1
  (zero is the break-even point). He named the
  modified indicator Revealed Symmetric
  Comparative Advantage (RSCA).
• RSCA (RCA -1) / (RCA 1)
• 2. Laursen, Keld. (1998), Revealed Comparative
  Advantage and the Alternatives as Measures of
  International Specialization, Danish Research
  Unit for Industrial Dynamics, Working Paper No.
  98-30.

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3. Applications (Continued)

• Table 7 shows a symmetric version of Balassas
  RCA. It clearly demonstrates that as of 2006,
  China was still not competing with the US in the
  same product space. There are 1,339 out of 5,225
  6-digit commodities in which China and the US
  both have RSCA gt 0, or 25.6 percent of the total.
  Overall, the correlation between RSCAs for the
  two countries is -0.40, suggesting that the two
  countries are competitive (or uncompetitive) in
  quite different commodities.

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3. Applications (Continued)

• Chinas comparative advantage as an exporter
  still lies in relatively low value-added products
  which require higher labor inputs. I should note
  that compared to other exporting countries China
  has not shown comparative advantage in high
  value-added manufacturing products, but Chinas
  export shares and RSCA values in this respect are
  rising.

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3. Applications (Continued)

• Question Does China compete with the US in the
  world export markets?
• Answer As of 2006, China was still not
  competing with the US in the same product space,
  but the overlapping product space is getting
  bigger every year.

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Thank You!

• Questions?
• allens_at_gecainc.com