SAM Table Dataset for Four Municipalities of
China (2012, 2015)
Zhang, Y.1 Ma, T. L.2*
1. School of Economics, Hunan University of Finance and
Economics, Changsha 410205, China;
2. Changsha Environmental Protection College, Changsha
410004, China
Abstract: The Computable General Equilibrium (CGE) model
is one of the important research methods in economics. In recent years, it has
been applied widely in the fields of tariff, trade barriers, resources, and
environment. The CGE model data come from the Social Accounting Matrix (SAM),
which is based on an input-output table. However, most input-output tables are
only prepared at national and provincial levels, which is not conducive to the
study of urban problems using the CGE model. This paper, based on input-output
theory, matches 41 industrial sectors in China to five types of state-owned
construction land, including land for transport, in the first-level classification
of landuse status. According to the latest input-output table, in combination
with the ??Land and Resources of China Yearbook??, ??Beijing Statistical Yearbook??,
??Shanghai Statistical Yearbook??, ??Tianjin Statistical Yearbook??, ??Chongqing
Statistical Yearbook??, and the Beijing, Shanghai, Tianjin, and Chongqing Social
Accounting Matrix (SAM) in 2012?C2015 are compiled and balanced using the direct
cross-entropy method. This dataset can provide data support for the
construction of an urban land use CGE model, and the study of urban land use
and urban economics.
Keywords: CGE model; Social Accounting Matrix; urban economics; municipalities of China
1 Introduction
The
economist Wassily Leontief proposed the input-output model, also known as the
Leontief model, which uses simultaneous linear equations to accurately describe
the interrelationship and interaction between economy and technology in various
sectors of the national economy[1]. The input-output method has
greatly promoted and influenced the development of modern economics. The full
name of the CGE Model is the Computable General Equilibrium Model; it involves
the deepening and development of input-output analysis. The traditional
input-output model only analyzes intermediate products/intermediate inputs,
factor inputs, final products, and other links without considering the economic
activities of residents, enterprises, governments, and other sectors, as well
as social and economic accounts such as savings, investments, imports, and
exports. Therefore, its role has certain limitations[1]. According
to Walras?? general equilibrium idea[2], the price variable is
solved, and the analysis result is more comprehensive and systematic.
Therefore, the CGE Model has played a huge role in international trade, government
taxation, resources and environment, public policy, and other fields, and has
been widely applied, gradually becoming an important tool in modern economic
research[1].
CGE model
data are derived from the Social Accounting Matrix (SAM). It reflects the relationship
between capital flow and proportion among various sectors of the social
economy, and describes social and economic activities in a more detailed way. Only
municipalities directly under the central government and provincial-level
administrative regions in China compile input-output tables at every mantissa
of 2, 7 years, with a preparation interval of 5 years. To keep the data
updated, the input-output extension table is prepared for every year with
mantissa 0 and 5. The input-output extension table updates the data based on
the input-output table. The department classification is completely consistent
with the input-output table, and the data are extendable. However, the data are
derived from statistical data, rather than from a direct survey, like the data
in the input-output table. Therefore, the input-output extension table is
consistent with the input-output table, and both can be used together. Since
the National Bureau of Statistics has not yet compiled the input-output table
for the municipalities directly under the central government in 2017, the
latest input-output table for the Chongqing municipality was the input-output
extension table for 2015. Therefore, a SAM table for Chongqing in 2015 was compiled
by taking Beijing, Tianjin, Shanghai, and Chongqing as examples and SAM tables
for Beijing, Tianjin, Shanghai, and Chongqing in 2012 according to relevant
data.
2 Metadata of the Dataset
The metadata of ??SAM
table dataset for four municipalities of China (2012, 2015)??[3] is
summarized displayed in Table 1.
Table 1 Metadata summary of ??SAM table dataset for four
municipalities of China (2012, 2015)??
|
Items
|
Discription
|
|
Dataset full name
|
SAM table dataset for four
municipalities of China (2012, 2015)
|
|
Dataset short name
|
SAM_4MunicipalitiesChina
|
|
Authors
|
Zhang, Y. 0000-0002-1633-2478, Hunan University of Finance and Economics, 520andylau@sina.com
|
|
Geographical region
|
Beijing, Tianjin, Shanghai,
Chongqing
|
|
Year
|
2012?C2015 Data
format .xlsx Data
size 25.2 KB
|
|
Data files
|
6 .xlsx worksheets: (1) SAM for Beijing in 2012; (2) SAM
for Shanghai in 2012; (3) SAM for Tianjin in 2012; (4) SAM for Chongqing in
2012; (5) SAM for Chongqing in 2015; (6) Code, meaning, and unit in SAM
|
|
Foundation
|
Hunan Education Department
(18C0964)
|
|
Data publisher
|
Global Change Research Data
Publishing and Repository, http://www.geodoi.ac.cn
|
|
Address
|
No. 11A, Datun Road, Chaoyang
District, Beijing 100101, China
|
|
Data sharing policy
|
Data from
the Global Change Research Data Publishing & Repository includes metadata,
datasets (data products), and publications (in this case, in the Journal of Global Change Data & Discovery). Data sharing policy includes: (1) Data
are openly available and can be free downloaded via the Internet; (2) End
users are encouraged to use Data subject to citation; (3)
Users, who are by definition also value-added service providers, are welcome
to redistribute Data subject to written permission from the GCdataPR Editorial
Office and the issuance of a Data redistribution license; and (4) If Data
are used to compile new datasets, the ??ten percent principal?? should be
followed such that Data records utilized should not
surpass 10% of the new dataset contents, while sources should be clearly
noted in suitable places in the new dataset[4]
|
|
Communication and searchable system
|
DOI, DCI, CSCD, WDS/ISC, GEOSS, China GEOSS, Crossref
|
3 Methodology
3.1
Definitions of Elements
The 10 elements in SAM table include industrial and mining
warehousing, transportation, housing, commercial services, public administration,
labor, capital, land, residents, and government. The corresponding relationship
between industrial land types and input-output departments is shown in Table 2.
Table 2 Comparison of land use types and
input-output departments in China
|
Land use types
|
Definition of land use types
|
Corresponding sections of IO
table
|
|
Land
for industry, mining, and warehousing
|
This
refers to the land mainly used for industrial production and warehousing
|
Mining and washing of coal products
|
|
Extraction of petroleum and natural gas products
|
|
Mining and processing of metal ores products
|
|
Mining and processing of non-metal ores products
|
|
Food and tobacco
|
|
Textiles
|
|
Clothing, hats, leather, feather, and related products
|
|
Processing of timber products and furniture
|
|
Paper, printing, culture, education, and sport products
|
|
Products of petroleum, coking, and processing of nuclear fuel
|
|
Chemical products
|
|
Products of non-metallic minerals
|
|
Products of metals smelting and pressing
|
|
Metal products
|
|
General equipment
|
|
|
|
Special equipment
|
|
|
|
Transportation equipment
|
|
|
|
Electrical machinery and apparatus
|
|
|
|
Communication, computers and other electronic equipment
|
|
|
|
Measuring instruments
|
|
|
|
Other manufactured products
|
|
|
|
Waste and flotsam
|
|
|
|
Repair services of metal products, machinery, and equipment
|
|
|
|
Electric power and heat production and supply
|
|
|
|
Gas production and supply
|
|
|
|
Water production and supply
|
|
|
|
Construction
|
|
Land
for transport
|
This
refers to the land mainly used for ground lines and stations for
transportation and passage. It includes land used for civil airports,
harbors, wharves, ground transport pipelines, and all types of roads
|
Transport, storage, and post
|
|
Land
for residential uses
|
This
refers to the land used for house sites and the affiliated facilities for
people??s daily life and dwelling
|
Real estate
|
|
Land
for commercial and services uses
|
This
refers to land mainly used for commerce and service use
|
Wholesale
and retail trades
|
|
Hotel
and catering services
|
|
Information
transmission, software, and information technology
|
|
Financial
intermediation
|
|
Leasing
and business services
|
|
Land
for public management and public services
|
This
refers to the land mainly used for government agencies and public
organizations, press and publication, science, education, culture and health,
scenic spots, historical sites, and public facilities
|
Scientific
research and technical services
Management
of water conservancy, environment, and public Facilities
Services
to households, repair, and other services
Education
Health
and social work
Culture,
sports and entertainment
Public
management, social security and social organization
|
Similar to the
input-output table, the SAM table is a matrix with rows and columns equal to
each other, and the same rows and columns correspond to a sector in the
national economy. Where the production/activity sector reflects the
relationship between intermediate demand and intermediate input among
industrial sectors, it can be divided into two departments of production and
activity, or one department can be combined as needed. As shown in Table 3, to
simplify the analysis, the two departments of production and activity should be
merged into the production/activity department.
Table 3 Components
of the SAM table
|
Item
|
Production/activities
|
Production factors
|
Households
|
Government
|
Total
|
|
Production/activities
|
Intermediate
input/Use Part
|
|
Household
consumption
|
Government
consumption
|
|
|
Production
factors
|
Value-added
|
|
|
|
Factor income
|
|
Households
|
|
Resident
factor income
|
|
|
Total resident income
|
|
Government
|
|
|
Individual
income tax
|
|
Total
government revenue
|
|
Total
|
Total inputs
|
Factor
expenditure
|
Household
spending
|
Government
consumption
|
|
It can be
found that the 42 industrial sectors analyzed by input-output analysis in China
basically correspond to five types of state-owned construction land, such as
transportation land, industrial and mining land, and storage land, in the
classification of land use status in China[5] (Table 2). According
to the division of construction land and the definition of the industry in the
land classification, five industries, including information transmission, software,
and information technology services in the input-output table can correspond to
commercial service land. 27 industries were compared with industrial and mining
storage land. Seven industries, including scientific research and technical
services, water conservancy, environment, and public facilities management,
will be matched with public management and public service land. The real estate
industry could be matched with residential land. 42 sections in the table have
some overlapping fields, so it cannot fully correspond to the classification of
land use status, such as the classification of warehousing. Since the warehousing
industry and the transportation industry are merged into the transport, storage
and post industry (code 30) in the input-output table of China, they cannot be
separated. Here, warehousing industry refers to goods transportation, transit
warehousing, and goods distribution mainly engaged in warehousing. Its main
business belongs to the same category as transportation, so the transportation
and storage industry were matched with transportation land. The special land in
the state-owned construction land includes the land for military facilities,
embassies, and consulates; the water area and water conservancy facilities in
the construction land include the water surface of reservoirs, coastal beaches,
and other land including idle land. Taking Beijing as an example, in 2012, the
special land, water and water conservancy facilities land, and other land in
Beijing were 3.33, 6.83, and 0 hm2, respectively[6],
which accounted for a small proportion and were not closely related to the
city??s social economy, so they were not included in the research scope. Since
this dataset is mainly used to study the structure of urban construction land,
the data for agriculture, forestry, animal husbandry, fishery, and
corresponding agricultural land data in the input-output table are excluded.
Other departments[1] and match the standard CGE model, including
elements, residents, government, and summary departments.
3.2 Statistical Approach
According to
the above analysis, the original data in the input-output table for Beijing,
Shanghai, Tianjin, and Chongqing municipality[7?C10] in 2012 and the
input-output extension table for Chongqing[9] in 2015 were first
combined horizontally and vertically according to the classification of
departments in Table 2, and then the other data in the SAM table were
supplemented according to the statistical yearbook of each city. Data on land
for industry, mining, warehousing, transport, residential uses, commercial and
services uses, public management and public services of Beijing, Shanghai, and
Tianjin in 2012 and Chongqing in 2012 and 2015 come from the references[6,11]; data on value
added for SAM come from the IO table for Beijing, Shanghai, and Tianjin in 2012
and Chongqing in 2012 and 2015[7?C10,12]; data on resident factor income for
SAM come from the ??People??s life and price?? section in the ??Beijing statistical yearbook,?? the
??Shanghai statistical yearbook,??
the ??Tianjin statistical yearbook?? for
2013, and the ??Chongqing statistical
yearbook?? for 2013 and 2016[13?C17];
data on Household Consumption and Government Consumption of SAM come from the
IO table for Beijing, Shanghai, and Tianjin in 2012 and Chongqing in 2012 and
2015[7?C10,12]; data on individual income tax for
SAM come from the ??Government finance?? section in the ??Beijing statistical yearbook??, the
??Shanghai statistical yearbook,?? the
??Tianjin statistical yearbook?? for
2013 and the ??Chongqing statistical
yearbook?? for 2013 and 2016[13?C17].
At the same
time, similar to the input-output table, the total number for each column of
the SAM table is equal to the total number for each row, thereby achieving
??balance?? in the SAM table. However, primary SAM tables are not balanced in the
usual sense, so they need to be balanced in different ways. The cross-entropy
method is a more balanced method adopted in the modern CGE model, including a
direct cross-entropy method and a coefficient cross-entropy method, in which
the coefficient the cross-entropy method is mainly used to update the existing
SAM table data. Therefore, to retain the idea of economics and overcome its
subjectivity, this dataset is adopted to balance the SAM table with a direct
cross-entropy method as the primary method and a manual balance method as the
supplement. The cross-entropy method builds the model according to the entropy
information proposed by information economics, and its objective function is:
(1)
??
??
(2)
where 
is the original data of the SAM table. 
is the balanced data, and
all are positive.
4 Data Files
The files
consist of one Excel file with six worksheets, respectively: (1) SAM for
Beijing in 2012; (2) SAM for Shanghai in 2012; (3) SAM for Tianjin in 2012; (4)
SAM for Chongqing in 2012; (5) SAM for Chongqing in 2015; (6) Code, meaning,
and unit in SAM. The dataset is archived in .xlsx format and consists of one
file with a data volume of 25.2 KB.
5 Discussion and Conclusion
The SAM table is not only the
basic data of the CGE model but also a further development of the input-output
table. Based on the input-output table, government, savings-investment, import
and export, and other departments and modules are added to reflect the capital
flow and proportion relationship between various sectors of the social economy
and describe social and economic activities in a more detailed way.
Taking the SAM table for Beijing
as an example, the general equilibrium analysis analyzes the changes in prices
and the total amount for various factors such as GDP increase, labor force,
capital and land, and predicts the impact on various sectors of Beijing??s economy
and society, to make more accurate policy evaluations and adjustments. For
example, when GDP increased by 6.5%, land prices rose 20% and the total labor
force increased by 20%. The SAM table data was input to GAMS (general algebraic
modeling system) software, to set up a corresponding CGE model.
With economic development, the
structure of new construction land in Beijing changed significantly under three
scenarios (Table 4), including a steady increase in GDP, a rising price for
land, and a significant increase in labor supply caused by the two-child
policy.
Table 4 Structural
changes in optimal construction land in Beijing under three scenarios
|
Item
|
Industry,
mi-
ning,
and warehousing
|
Transport
|
Residential
|
Commerce
and services
|
Public management and services
|
|
Area
(km2)
|
Change
(%)
|
Area
(km2)
|
Change
(%)
|
Area
(km2)
|
Change
(%)
|
Area
(km2)
|
Change
(%)
|
Area
(km2)
|
Change
(%)
|
|
Actual value
|
5.31
|
-
|
0.33
|
-
|
6.14
|
-
|
1.49
|
-
|
3.00
|
-
|
|
Scenario 1
|
0.03
|
-99.48
|
24.42
|
7,398.97
|
86.26
|
1,305.85
|
0.01
|
-99.08
|
28.82
|
861.16
|
|
Scenario 2
|
0.48
|
-90.88
|
0.66
|
103.22
|
5.78
|
-5.88
|
0.15
|
-90.25
|
0.21
|
-92.85
|
|
Scenario 3
|
0.38
|
-92.87
|
0.62
|
89.89
|
5.02
|
-18.17
|
0.12
|
-92.13
|
0.18
|
-94.06
|
When GDP is expected to grow steadily by 6.5%, the supply of land
for transport, residential use, public management, and public services should
be effectively increased compared to the actual value. When the price of land
increases by 20%, due to the apparent increase in land use cost, in addition to
land for transport, the approval and supply of land for industry, mining and
warehousing, residential uses, commercial and services uses, public management,
and public services should be strictly controlled. When the total labor force
is expected to increase by 20%, the simulation results are similar to Scenario
2. Therefore, the preparation of a SAM table for Beijing, Shanghai, Tianjin,
and Chongqing, using the CGE model, is conducive to a more comprehensive and
in-depth analysis of the social and economic problems of each municipality
directly under the central government.
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