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A trade matrix is a numerical table showing data on trade
between region blocks and between major countries, in matrix format. All
numerical data in the trade matrices stored on the CD has been converted into
weight units for uniformity. A trade-flow map shows world trade by means of
arrows on a map, and is created from trade matrices. This chapter describes the
method for creating trade-flow maps and trade matrices.
1. The Data
Every year, the United Nations tabulates trade
statistics from the trade data reported by various countries, and offers these
statistics on magnetic media (henceforth, the “United Nations Trade Statistics
Dataset”). In addition, the International Trade Center (ITC) offers a Personal
Computer Trade Analysis System (PC-TAS), which is derived from and processes UN
Trade Datasets since 1998. Data has been compiled for 5 years: 1983, 1988,
1993, 1998, and 2003.
Some of the original trade data is only reported in
monetary units, and different countries use different units of quantity
measurement for their trade data. For this reason, when creating a trade
matrix, it was not possible to simply tabulate the data for a given region; it
was also necessary to convert all transactions into units of weight. The
statistical method for doing this is described in detail in section 3. Below
are described the salient features of the data.
(1) Data Format
For each type of trade, the UN Trade Dataset contains
data on trade-flow type (import, export, or re-export), commodity, reporting
country, partner country, transaction amount, unit of quantity measurement,
quantity traded, and summation period. As there are both import and export
reports, if every country in the world correctly reports its trading, then all
trade data will be contained in the dataset twice, once as import data and once
as export data.
(2) Level of
Coverage of Total Trade
There are currently 165 reporting countries (94 in
1983, 84 in 1988, 91 in 1993, 100 in 1998, and 165 in 2003). Since the
developed countries, which consume the majority of resources, generally report
their trade, it is thought that most trading by non-reporting countries is
accounted for as well via their partners. It must nevertheless be noted that
trade between non-reporting countries is completely missed.
(3) Commodity
Categories and Category Codes
Commodities are classified according to the UN’s
Standard International Trade Classification (SITC). There are 3 versions of the
SITC: Rev. 1 (about 1,800 categories), Rev. 2 (about 2,600), and Rev. 3 (about
4,200). With each revision the classifications become finer, providing a more
detailed breakdown of commodities, while at the same time with each revision,
there are fewer reporting countries. Thus, in order to strike a balance between
granularity of classifications and number of reporting countries, the data from
Rev. 2 was used. Each commodity has a commodity code of up to 5 digits, with
each additional digit providing a finer-grained classification. For example:
0:FOOD AND LIVE ANIMAL / 01:MEAT AND PREPARATIONS / 011:MEAT
FRESH,CHILLD,FROZEN.
(4) Level of
Coverage of Quantity Data
Unlike monetary data, quantity data for trade
sometimes contains empty (blank) fields. In some cases, all fields for a given
commodity will be blank, while in others only some of them will be blank. Trade
quantity is measured using many different units, including weight, volume,
area, and count. Quantities of different commodities are reported using
different units, and in some cases different countries may report the same
commodity using different units.
2.
Commodities
Covered
As
shown below, the trade matrix contains resources taken from nature, and raw
materials with low levels of processing, which have relatively high trade
flows, and which are considered vital from an environmental standpoint. It
excludes resources with low trade flows, such as precious metals, and
commodities with high levels of processing, like machinery and chemicals. Lime,
gravel, and other non-metal minerals were also excluded.
·
Food
resources (meat, fish and grains)
·
Wood
resources (wood and products made from wood with little processing)
·
Metal
resources (ore and metal products)
·
Fossil fuel
resources (including converted fuels)
Fig.1
is a trade matrix showing the hierarchical relationships of these resources.
3.
Creating the
Trade Matrix
Fig.2 shows the trade-matrix
compilation process, while Table 1 lists
the commodities included in the matrix. The trade matrix covers 50 commodities
over 3 years, and thus contains 150 items. Note that in cases where commodities
covered by the matrix corresponded to commodities in Japanese Ministry of
Finance (MOF) trade statistics, it was confirmed that the data on Japanese
imports (the section corresponding to column 9 of the trade matrix) matched the
MOF trade statistics nearly exactly. Below is a description of the process used
to create the trade matrix.
(1) Convert 1998 Trade Data (PC-TAS)
After extracting necessary 1998 and 2003 trade data
from PC-TAS, it was converted to United Nations Trade Statistics Dataset record
format. Additionally, as PC-TAS uses the SITC Rev. 3 commodity codes, a
correspondence table provided by the United Nations was used to convert the
codes to SITC Rev. 2. Data for 1983, 1988, and 1993 is trade data taken from
United Nations sources and left unchanged.
(2) Extract Corresponding Commodity Records
(create Workfile 1)
Records matching the commodities described in 2 were
extracted from a set of several million trade-data records.
(3) Adjust
Import/Export Data (create Workfile 3)
As described in 1-(1), the UN Trade Dataset consists
of import data and export data; if both are used, trade between reporting
countries will be double counted. It is therefore necessary to use one or the
other. For the present tabulation, it was decided to use the import data, and
discard the export data. This discarded export data, however, includes data on
trade with non-reporting countries, which is not contained in the import data.
Thus, data on exports to non-reporting countries was converted to import data,
and used in lieu thereof. Additionally, in the case of trade with Japan, the
values reported by Japan to the UN are used in all cases; namely, out of the
values extracted from the import data of the UN Trade Dataset, the data showing
imports from Japan was removed, and replaced by Japan’s export values to the
country contained in the discarded export data. It further must be noted that
trade between non-reporting countries is completed unaccounted for.
In addition, when it was judged by an outside
viewpoint that data which was obviously incorrect had been used, the import
data was removed, and the discarded export data replaced with import data.
(4) Statistically
Extrapolate Quantity Data
(create Workfile 3)
As described in 1-(4), the transaction quantity
fields of some of the records in the United Nations Trade Statistics Dataset
are blank, and in some cases units of quantity measurement other than weight
are used. For these records, it is necessary to statistically extrapolate the
transaction quantities in units of weight. Before conducting this
extrapolation, the reporting of quantity units for each commodity was reviewed;
this review showed that weights were reported in a large number of cases for
all commodities except “Saw-, Veneer-logs” for 1988. Thus, the following method
was used to statistically extrapolate the weight units for all records:
・
First,
records for which weights were reported were extracted, and transaction amounts
and weights tabulated. This information was used to calculate an average price
per unit of weight.
・
The average
price per unit weight was then used as the divisor in dividing transaction
amount of records where a non-weight unit of measurement quantity was used, or
where the quantity field was blank, in order to obtain estimated transaction
weight.
However, for those of the following commodities whose
records had quantities in terms of volume as weight, volumes were converted to
weights by applying a conversion coefficient obtained from another source, and
then the method described above was applied.
・
Saw-Veneer
Logs: 0.50t/m3
・
Propane
(liquid): 0.55t/m3
・
Natural gas:
0.754kg/m3
In addition, during the course of the check, the unit
price of each record for a given commodity was calculated. When these calculations
were compared, it was found that in a small number of records, the prices were
off by several orders of magnitude from the other records. Although it was
believed that in most cases, the discrepancy was due to simple input error
during reporting, it was hard to decide which cases were actually mistakes.
Thus, it was decided to compare the price of each record with the median value,
and if there was a difference of 2 digits or greater, to treat the quantity for
that transaction as an empty field.
(5) Convert to
Matrix Format
Commodity codes with few digits, i.e. high-level
commodities, represent several different lower-level commodities as a single
category. Thus a high-level commodity may subsume items with substantially
different unit prices, due to different levels of processing and different
qualities. The statistical method used here, however, converts all monetary
amounts for given commodity to weights using the same unit price, which in the
case of these commodities would cause the calculated weights to be too high for
expensive commodities, and too low for inexpensive commodities, significantly
degrading the accuracy of the statistical extrapolation. In order to avoid
these problems, the method described in (4) was not used for high-level commodities.
Instead, it was necessary to sum up the data created for lower-level
commodities.
Additionally, it was necessary to create a trade
matrix of commodities not contained in the SITC, as in the case of biomass
where a new trade matrix was created by combining the food resource and wood
resource trade matrices (see Fig.1).
Trade matrices were first created for commodities
relatively low on the hierarchy, as “base” commodities. Next, these trade
matrices were summed, in order to create trade matrices for higher-level
commodities, and commodities not in the SITC. If, however, there are cases
where only higher-level commodities are reported, and lower-level commodities
are not reported, then there is a chance that some trade will be missed. For
this reason, the monetary amounts of commodities summed for estimation purposes
were compared with the monetary amounts of the higher-level commodities, in
order to make sure that there were no problems with this process.
Table 2 shows the
correspondence relationship when totaling and recombining commodities. The
commodity codes for trade matrices created via this summation process are
determined as follows:
・ Commodity codes starting with “T” indicate that the
commodity has been uniquely defined here, due to the fact that it represents a
broad category of major resources.
・ Commodity codes ending with “A” exist in the SITC
except for the “A,” but indicate that the commodity has been recombined into a different
makeup.
・ Commodity codes ending in “0” indicate that the
commodity was created by summing lower-level commodities.
a) Creation of Base-commodity Trade Matrices
Base-commodity trade matrices were created from Workfile
3 using a trade-matrix creation program (a program that creates trade matrices
from data in OD pair-record format, and outputs them in spreadsheet format)
developed by the National Institute for Environmental Studies. The commodities
in the trade matrices created by this program include commodities not
containing a “T”, “A”, or “0” in Table 1. Tables 4 and 5, respectively, list the names of the region
block classifications (Country/Region Block Tabulation Codes), and the names of
each country in each region, used for the tabulation.
b) Commodity Summation and Recombination
A commercial spreadsheet application was used to sum
and recombine the trade matrices created in a).
4. Creating the Trade-flow Map
A trade-flow map was created using Acclaim, a system
developed by the National Institute for Environmental Studies that shows the
international trade balance of environmental resources. Table 6 lists the items contained in the map.
5.
Notes on
Interpreting the Trade Matrix and Trade-flow Map
Below
are notes on interpreting the trade matrix and trade-flow map.
(1) The Trade Matrix
・ The rows of the matrix are the exporters,
and the columns the importers.
・ An ID code is assigned to each trade
matrix. The ID has the format YY-XXXXX, where YY is the two-digit data year,
and XXXXX is the (up to 5-digit) commodity code.
・ It must be noted that this data has been statistically
derived from the United Nations Trade Statistics Dataset.
(2) The Trade-flow Map
・ The arrow flows show the net trade
quantities (balances) between two countries/regions.
・ Due to the nature of the trade-flow map,
flows within a single region (e.g. between European countries) are not shown.
Refer to the trade matrices for this information.
・ Due to the nature of the trade-flow map,
trade with Other East/South Asia is not shown. Refer to the trade matrices for
this information.
・ For ease of viewing, the Asian Region
version does not show trade between non-Asian region blocks.
(3) Re-export
・ The UN Trade Datasets from 1983 to 1993
carried trade data on re-exports. Here, the data on re-exports was counted as
export data.
・ Note that the PC-TAS from 1998 to 2003
does not deal with data on re-exports.
Fig.1 Hierarchical
Tree of Commodities Covered by Trade Matrix
Fig.2 Trade
Matrix Creation Process
Table 1 Commodities Covered by Trade Matrix
Table 2 Commodities Aggregated for Trade Matrix
Table 4 Country/Region Blocks for Trade Matrix
Table 5 Country/Region Block Tabulation Codes for Trade Matrix
Table 6 List of Items in Trade-flow Map
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