The First China-REAL Meeting (CREAL 2015)
January 14-January 15, 2016, Beijing, China
PROGRAM
Organizer:
Center for Forecasting Science, Academy of Mathematics and
Systems Science, Chinese Academy of Sciences, Beijing, China
The 2nd International Conference on Forecasting Economic and Financial Systems, 2015
Address of venue:
Lecture Rooms N205, South Building, Academy of Mathematics and Systems Science,
Chinese Academy of Sciences (AMSS South Building), 55 Zhongguancun East Road,
Beijing, 100190. (See the local map below)
北京市海淀区中关村东路数学与系统科学研究院南楼，N205 会议室
Registration
The registration desk will be located in the hallway of the venue, next to the lecture
room N205. Registration desk will be open from 8:00-17:00 on January 14. Receipts
for registration fee payment can be obtained at the registration desk only during the
open time of registration desk. The regular registration fee for one teacher attendance
with Abstract & Presentation is 1500RMB, for simple attendance is 1000 RMB. There
is no registration fee for students.
The Regular Registration Fee Includes
1. Access to all technical sessions
2. Lunch and dinner during the conference
3. Coffee breaks during the sessions
4. One hard copy of the conference guide
5. One souvenir for the First China-REAL meeting
Late registration and any other questions about registration please contact: Qingrong
Zou: 15600601956
Presentation Instruction
The lecture rooms will be equipped with a PC and a computer projector. Presenters
must provide to the session chair with the files for the presentation in PDF (Acrobat) or
PPT (Powerpoint) format on a USB memory stick. This must be done five minutes
before each session. Chairs are requested to keep the sessions on schedule. (The
number of total presentations in each session may vary so the Chair should announce
the time for each presentation after session starts. Generally the presentation is 30
minutes including discussion.)
For any question concerning presentation, please contact:
Zhuo Tu: 18813189838
Internet Connection
WIFI: AMSS
Password: E5Y6U1Y0
Lunch Break & Coffee Break
Dinner of Jan.14 and all lunch breaks will be located at the 3rd floor, Wuke Restaurant.
Coffee breaks will be located at the coffee house, 1st floor, AMSS south building.
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The First China-REAL Meeting, 2016
Contact
General Information: Zhuo Tu: 18813189838
Scientific Programme: Qingrong Zou: 15600601956
Map of the venue and nearby area
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The 2nd International Conference on Forecasting Economic and Financial Systems, 2015
Contents
PROGRAM ............................................................................................................................................. 1
Sponsors ................................................................................................................................................... 1
Conference Committee ............................................................................................................................. 1
Time Table ................................................................................................................................................ 3
Abstracts ................................................................................................................................................... 6
[1] Evolution of Production Space and Regional Industrial Structures in China ..................................... 6
[2] China’s Position, Trade Revenue and Competitiveness on the Global Value Chains: An Analysis
Based on Trade in Value Added Accounting Framework ......................................................................... 6
[3] Is County-to-city Upgrade in China a Failed Urbanization Policy? ................................................... 7
[4] Identification and Dynamic Characteristics of Beijing-Tianjin-Hebei Mega-city Region：Based on 5th
and 6th Census in China ........................................................................................................................... 8
Yuyuan WEN ........................................................................................................................................... 8
School of Economics, Renmin University of China, Beijing 100872 ...................................................... 8
[5] PM2.5 and the Path Choices of Urbanization ..................................................................................... 9
[6] Regression—the probability foundation and approach to estimate..................................................... 9
[7]Collapse of City and Economic Horizon ........................................................................................... 10
[8] The effects of vertical specialization on regional carbon transfer and allocation within China ........ 12
[9] What matters in measuring domestic value added in exports by international or single country model
................................................................................................................................................................ 12
[10] Administrative Monopoly, Ownership and Wage differentials across Time and Space in China ... 13
[11] Using a Grey-Markov model optimized by Cuckoo Search algorithm to forecast the annual foreign
tourist arrivals to China .......................................................................................................................... 14
[12] Impact of recycled water price adjustment on price level in China ................................................ 15
[13] Using Average Propagation Lengths to Identify the Structural Change in the Chinese Economy .. 15
[14] Prediction and Analysis of Beijing’s Population Structure Based on the PDE Model .................... 16
[15] Uncovering the Structural Transformation of the Chicago Economy Using Feedback Loop Analysis
and APL .................................................................................................................................................. 17
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The First China-REAL Meeting, 2016
Sponsors
Center for Forecasting Science，CAS
Academy of Mathematics and Systems Science, CAS
Conference Committee
General Chairs：
Geoffrey J. D. Hewings, Regional Economics Applications Laboratory, University of
Illinois, 607 S. Mathews, #318, Urbana, IL, USA, 61801
Shouyang Wang, Academy of Mathematics and Systems Science, Chinese Academy
of Sciences, China
Xikang Chen, Academy of Mathematics and Systems Science, Chinese Academy of
Sciences, China
Program Chair:
Geoffrey J. D. Hewings, Regional Economics Applications Laboratory, University of
Illinois, 607 S. Mathews, #318, Urbana, IL, USA, 61801
Organizing committee Chair:
Xiuli Liu, Academy of Mathematics and Systems Science, Chinese Academy of
Sciences, China
Program committee members:
Canfei He, College of Urban and Environmental Sciences, Peking University, Beijing,
100871, China
Ping Lei, School of Humanities & Economic Management, China University of
Geoscience
Tang Wei, School of Economics, Fudan University
Wen Chen, Department of International Trade and Business, School of Economics,
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The 2nd International Conference on Forecasting Economic and Financial Systems, 2015
Xiamen University, Xiamen
Wang Zhenquan, Beijing Institute of Petrochemical Technology
Hongxia Zhang, School of Economics, Renmin University of China. Beijing, China,
100872
Yuyuan Wen, Renmin University
Zinan Zhang, China Economics and Management Academy (CEMA), Central
University of Finance and Economics, Beijing, China 100081
Xu Sun, School of Statistics, Dongbei University of Finance and Economics, Dalian
116025, China
Jianhua Li, Beijing Institute of Petrochemical Technology School of Economics and
Management
Fei Chen, Nanchang University
Contacts:
xiuli.liu@amss.ac.cn
No. 55, Zhongguancun East Road, Haidian District, Beijing,100190, China
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The First China-REAL Meeting, 2016
Time Table
8:00-17:00
Registration
Lobby
Open Session (Chair : Xikang Chen)
N205
9:00-9:05
Opening Address: Shouyang Wang, General Chair
Keynote Speech (Chair: Xikang Chen)
9:05-10:05
Speaker: Prof. Geoffrey Hewings
N205
Title: Ageing Population and Shrinking Labor Force:
Will Enhanced Productivity or Migration Solve the
Problem Facing Regional Economies?
10:05-10:15
Photograph & Coffee Break
Lobbby
10:15-12:15
Session 1 (Chair : Geoffrey Hewings)
N205
Speaker: Qi Guo
10:15-10:45
Qi Guo, Canfei He, Evolution of Production Space and
Regional Industrial Structures in China
Speaker: Tang Wei
10:45-11:15 Tang Wei, Is County-to-city Upgrade in China a Failed
Urbanization Policy?
Speaker: Zinan Zhang
11:15-11:45 Zinan Zhang, Administrative Monopoly, Ownership and
Wage differentials across Time and Space in China
Speaker: Xiuli Liu
Xiuli Liu, Geoffrey J. D. Hewing, Uncovering the
11:45-12:15
Structural Transformation of the Chicago Economy
Using Feedback Loop Analysis and APL
12:15-13:30
14：00-15:30
Lunch/Rest
Session 2 （Chair: Xiuli Liu）
Speaker: Yuyuan Wen
Yuyuan Wen, Identification and Dynamic Characteristics
14:00-14:30
of Beijing-Tianjin-Hebei Mega-city Region：Based on
5th and 6th Census in China
Speaker: Jianhua Li
14:30-15:00
Jianhua Li, Collapse of City and Economic Horizon
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Wuke
Restaurant
N205
The 2nd International Conference on Forecasting Economic and Financial Systems, 2015
Speaker: Zengkai Zhang
15:00-15:30 Zengkai Zhang, The effects of vertical specialization on
regional carbon transfer and allocation within China
15:30-15:40
Coffee Break
Lobby
15:40-17:10
Session 3 (Chair: Zhenquan Wang)
N205
Speaker: Zhenquan Wang
15:40-16:10 Zhenquan Wang, Regression—the probability foundation
and approach to estimate
Speaker: Qingrong Zou
16:10-16:40
Xiuli Liu, Qingrong Zou, Impact of recycled water price
adjustment on price level in China
Speaker: Hongxia Zhang
Hongxia Zhang, Geoffrey J.D. Hewing, What matters in
16:40-17:10
measuring domestic value added in exports by
international or single country model
17:30-18:30
Dinner
Wuke
Restaurant
January 15, 2016(Friday)
9:00-12:00
Session 4 (Chair: Ping Lei)
N205
Speaker: Ping Lei
Ping Lei, PM2.5 and the Path Choices of Urbanization
Speaker: Qing Liu
9:30-10:00
Xiuli Liu, Qing Liu, Prediction and Analysis of
Beijing’s Population Structure Based on the PDE Model
Speaker: Xu Sun
Xu Sun, JianzhouWang, YixinZhang, YiningGao, Using
10:00-10:30 a Grey-Markov model optimized by Cuckoo Search
algorithm to forecast the annual foreign tourist arrivals to
China
9:00-9:30
10:30-10:50
Coffee Break
Lobby
10:50-12:20
Session 5 (Chair: When Chen)
N205
Speaker: Zhuozhuo Tu
10:50-11:20
Zhuozhuo Tu, Xiuli Liu, Using Average Propagation
Lengths to Identify the Structural Change in the Chinese
Economy
11:20-11:50
Speaker: Wen Chen
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The First China-REAL Meeting, 2016
Wen Chen, Ping Zhao, Jingjing Fang, China’s Position,
Trade Revenue and Competitiveness on the Global Value
Chains: An Analysis Based on Trade in Value Added
Accounting Framework
Speaker: Fei Chen
Fei Chen, Xiangwei Sun, A Neoclassic Model on
11:50-12:20
Regional Economic Growth: Spatial Evidence from
China
12:20-13:20
Lunch/Rest and conference close
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Wuke
Restaurant
The 2nd International Conference on Forecasting Economic and Financial Systems, 2015
Abstracts
[1] Evolution of Production Space and Regional Industrial Structures in China
Qi GUIO Canfei HE
College of Urban and Environmental Sciences, Peking University, Beijing, 100871
Abstract: A growing literature on evolutionary economic geography concludes that
regional industrial evolution is path-dependent and is determined by the preexisting
industries. This study more accurately calculates the industry relatedness based on the
co-occurrence approach to portray the production space of China’s manufacturing
sectors and then examines the impact of industry relatedness on regional industrial
evolution. The findings report that industry relatedness does underscore the regional
structure change in China but shows significant regional differences in the evolution
path. The coastal region has strong tendency of path dependence in its industrial
evolution, while North West and South West break the path-dependent trajectory and
transition into high productive sectors distant from their own production network. The
estimation results suggest that governmental policies can play its crucial role in
creating new paths in the West. Institutions matter to allow the significant role of
industry relatedness in driving regional industrial evolution.
Key words Production Space, Industry Relatedness, Regional Industrial Evolution,
Path Dependence, China
[2] China’s Position, Trade Revenue and Competitiveness on the Global Value
Chains: An Analysis Based on Trade in Value Added Accounting Framework
Wen CHEN Ping ZHAO Jingjing FANG
Department of International Trade and Business, School of Economics, Xiamen
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The First China-REAL Meeting, 2016
University, Xiamen
Abstract: Based on the value added trade accounting method，this paper tries to employ
1995-2011 WIOD data to measure the degree of China’s participation in the global
value chains (GVC) and to analyze its GVC position, value added competence, trade
revenue and competitiveness on GVC. The results show that China kept specializing in
downstream activities. In the first few years after entering into the WTO, China’s GVC
position was getting lower and value added competence getting weaker due to a greater
share of processing trade. In recent years, China has seen an increase in its GVC
position and value added competence. With deepening of its participation in the GVC,
China has gained more trade revenue. The results also show that China has stronger
competence in manufacturing sector compared with service sector, and has also gained
more trade revenue from the manufacturing sector.
Key words: global value chains (GVC), trade revenue, competitiveness, trade in value
added
JEL codes: F10, F14, F40
[3] Is County-to-city Upgrade in China a Failed Urbanization Policy?
Tang Wei
School of Economics, Fudan University
Abstract: Economic development is often accompanied by large scale of
rural-to-urban migration the increase of the amounts of cities. This paper investigates
one major policy of creating new cities in China—county-to-city upgrade and its
impacts on local economic development and urbanization. Based on nighttime light
data between 1992 and 2012 and Difference-in-Difference method, the research finds
that county-to-city upgrade policy implemented between 1992 and 1997 significantly
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The 2nd International Conference on Forecasting Economic and Financial Systems, 2015
promotes later economic development of counties. However, the average policy effects
are significant only after the year of 2004. In addition, the effects display significant
heterogeneity, with the positive impact higher in eastern regions and counties with
higher level of initial population density and economic development; it has
insignificant impact in middle and western regions. Finally, I discusses potential
sources and mechanisms of the positive effects, arguing that the interactions between
economic decentralization process embedded in the policy and local development
potential can help explain the dynamic effects of the policy and its heterogeneity. This
research has important policy implications on future reform of city creation policy
design and urban development strategy in China.
Keywords: County-to-city upgrade; Urbanization; DID; Land market; Nighttime light
data
[4] Identification and Dynamic Characteristics of Beijing-Tianjin-Hebei
Mega-city Region：Based on 5th and 6th Census in China
Yuyuan WEN
School of Economics, Renmin University of China, Beijing 100872
Abstract: This paper, employing mega-city region (MCR) theory and population
census of 2000&2010 in China, delineates Beijing-Tianjin-Heibei (BTH) MCR, and
analyzes the characteristics of BTHMCR in polycentricity, functions of advanced
producer services (APS) and inter-city network connectivity. The findings are: (1)
BTHMCR grew fast and became more spatial polycentric in the past decade. (2)
Polycentric structures of population and employment are formed in BTHMCR scale
while concentration and deconcentration processes co-exist in the capital scale. (3)
Different APSs present different spatial patterns. On the whole, BTHMCR is
undergoing a pattern of functional polycentric division of labor and complementarity.
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The First China-REAL Meeting, 2016
(4) Inter-city network connections and thus functional connectivity has formed in
BTHMCR although Beijing absolutely dominates the connectivity.
Key words: mega-city region (MCR), Beijing-Tianjin-Hebei (BTH), advanced
producer services (APS), identification criteria, polycentricity and network
connectivity
JEL classifications: L2,L8,R1,R3
[5] PM2.5 and the Path Choices of Urbanization
Ping LEI
School of Humanities & Economic Management, China University of Geoscience
Abstract: This article investigates how the characteristics of a city influence its PM2.5
in 112 key cities in China from 2001 to 2010. By empirical testing using the
MA(1)-system-GMM method, we find that the scale of human activities, measured as
population and urban population density, will increase a city’s PM2.5 significantly.
However following the environmental Kuznets theory, the shape between PM2.5 and
strength of human activities is an inverted-U curve. To reduce PM2.5, cities on different
development levels should choose different paths. Contrary to cities in eastern China,
cities in less developed central and western China should raise their industrialization
and urbanization rate, but decrease their green space percentage in urban areas.
Key words: PM2.5, urbanization, urban density, industrialization, path
[6] Regression—the probability foundation and approach to estimate
Zhenquan WANG
Beijing Institute of Petrochemical Technology
Abstract: It is well known that the operation of partial derivative is employed to derive
the estimation of regression coefficients in almost all of the textbooks of Econometrics.
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The 2nd International Conference on Forecasting Economic and Financial Systems, 2015
Although the estimate is correct, this approach is illegal, which comes into being a
blind point in the introduction education of econometrics. This work is aimed to reveal
this blind point, and investigate the foundation of regression analysis.
The illegality of the approach employing partial derivative is illustrated mathematically,
at first, and a legal and simple approach to derive the estimate in linear regression is
introduced which would shine some light on the primary education of econometrics. A
probability foundation for regression is then proposed, i.e. the regression of random
variable(s) y on x is actually the conditional expectation of y on x, which is exactly a
Borel function of x. Derived in the axiomatic probability, this result would be
contributory to econometrics and its applications as well, because the principle, and the
definition as well, of regression is not clear. In fact, although Haavelmo(1944)
discussed the relations between random variables and economic data, stochastic
equations and exact equations, and the parameter estimates in probability, the principle
of regression is not mentioned1.
After the discussion of its implications in practice, the modeling and application of this
result are investigated. These could be attributed to the problems of statistics, e.g. the
expression of the Borel function of x, and the conditions for linear regression, etc.
Key words: regression; probability; conditional expectation; econometrics
[7]Collapse of City and Economic Horizon
Jianhua LI
Beijing Institute of Petrochemical Technology School of Economics and Management
Abstract: The urbanization of China is different from that of Europe and American in
two notable features, namely, the pressure of energy and environment makes it
1
Trygve Haavelmo. The Probability Approach in Econometrics, Econometrica, Vol.12(1944)
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The First China-REAL Meeting, 2016
impossible to develop industry continuously in cities, and service industry is an
important force to drive the urbanization. These results in the collapse of city, by which
it means that when labor moves to the city from the surrounding area, the real wage will
increase in the city. This work is aimed to provide evidences that cities collapse, and
investigate the reason of the collapse.
Based on the theoretical models from Masahisa Fujita, Paul Krugman, Anthony J.
Venables(1999), a cobb-douglas style function is employed to reflect the impact of the
consumption of industrial goods and service to family utility, in which the consumption
of service is a composite function determined by a constant elasticity of substitution
function of a certain amount of services. It is concluded by the derived formula that,
when the parameter of preference of service exceeds that of the potential capacity of
labor division in service industry, the city will collapse, labors will always move to the
city, and the economy will collapse to the center of the city. It is indicated by the
empirical test that four from thirty major cities collapsed.
There are two reason of collapse. The first is the geographical range of urban service
industry. The service supply of large cities exceeds the demand of the city itself. Better
services are located in major cities, especially in China. Higher efficiency means higher
real wages and more detailed division of labor means more jobs opportunity. The
second reason of collapse is that difference of real wage caused by the iceberg cost. The
economic horizon of the collapsed cities is determined by iceberg cost. There is a
significant difference of iceberg cost between different services and According to
Baumol(1967), Baumol, Blackman & Wolff(1985), Pugno(2006), Li Jianhua and Sun
Bangzhu(2012), iceberg cost of highly standardized services is lower than low
standardized services. Based on the analysis, some advices are given finally.
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The 2nd International Conference on Forecasting Economic and Financial Systems, 2015
[8] The effects of vertical specialization on regional carbon transfer and allocation
within China
Zengkai ZHANG
Xi’an Jiaotong University
Abstract: Based on multi-regional input-output tables, this paper evaluates the double
counting problem of the regional carbon transfer within China that is caused by vertical
specialization and traces China’s regional carbon emissions along value chain routes
over the 2002–2007 period, which was when China’s gross emissions increased rapidly.
The calculation results show that 1) the double counting problem has become
increasingly serious with the rise in the degree of vertical specialization, particularly for
the coastal regions; the upstream industries with large carbon intensities are the main
contributors to this problem. 2) The net transfer of carbon emissions embodied in the
value-added term of interregional trade is from the inland regions to the coastal regions;
the carbon leakage problem is becoming increasingly serious, with the heavy industry
and electricity generation sectors as the main contributors. 3) Regional
production-based carbon emissions are mainly induced by the local final demand and
exports via the value chain for local products; in addition, the final demand of other
regions and foreign countries are playing an increasingly important role via
interregional trade.
[9] What matters in measuring domestic value added in exports by international
or single country model
Hongxia ZHANG1
Geoffrey J.D. HEWINGS2
1 School of Economics, Renmin University of China. Beijing, China, 100872.
2 Regional Economics Applications Laboratory, University of Illinois. Urbana, IL
61801-3671, USA
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The First China-REAL Meeting, 2016
Abstract: This paper proposes a method to compute the domestic value added in
exports based on international input-output model, and examines it with the method
based on single-country model using world input-output table. It shows that for any
country, in total, the results of domestic value added in exports by international IO
model equal to that by single country IO model. However, in decomposition, the
method on international IO model gives the effects of feedbacks among countries,
originating from the inter country division and the international industrial chains. Yet
the results of single country model cannot provide this kind of decomposition. Then by
using WIOTs, we compute the domestic value added in exports by the method in this
paper, and analyze the results.
Key words international input-output model; the domestic value added in exports;
feedbacks
[10] Administrative Monopoly, Ownership and Wage differentials across Time
and Space in China
Zinan ZHANG
China Economics and Management Academy (CEMA), Central University of Finance
and Economics, Beijing, China 100081
Abstract: This paper explores the effects of the administrative monopoly on the wage
differentials between different ownership enterprises across time and space in China.
The existing literature provided the evidence that wages in state-owned firms (SOEs)
were higher than that in non-SOEs form 2000s and the differences is ever higher in
eastern area. However, the wage differential did not attract labors in non-SOEs and the
SOE’s labor share was still decreasing during 2003-2011. Our interpretation of the
puzzle is that the wage differential partly came from the administrative monopoly,
rather than the improvement of total factor productivity. Based on the Annual Survey of
Industrial Firms in China during 2003-2011, our calibration version shows over the
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The 2nd International Conference on Forecasting Economic and Financial Systems, 2015
entire period nearly 20% wage differences came from the monopoly rent, and the effect
was even more significant in eastern China. Moreover, we argue that the recent
decrease in wage differences is related to government policies which allow non-state
firms flow into the administrate monopoly industry.
JEL classification: L16 O21
Keywords: Administrative Monopoly, Resource Misallocation, Wage differentials
[11] Using a Grey-Markov model optimized by Cuckoo Search algorithm to
forecast the annual foreign tourist arrivals to China
Xu Suna JianzhouWanga YixinZhangb YiningGaoa
a
School of Statistics, Dongbei University of Finance and Economics, Dalian 116025,
China
b
School of Mathematics and Statistics, Lanzhou University, Lanzhou 73000, China
Abstract: With the rapid developing of the international tourism industry, it is a
challenge to forecast the variability of international tourism market since the 2008
global financial crisis. In this paper, a novel CMCSGM (1, 1) forecasting model is
proposed to tackle the effects caused by the volatility of tourism market on the
forecasting precision. The Markov-chain grey model is adopted for its highlight in the
small-sample observations and exponential distribution samples. And the optimal input
subset method and Cuckoo search optimization algorithm are applied to improve the
performance of Markov-chain grey model. The experimental study of the annual
foreign tourist arrivals to China forecasting shows that the proposed CMCSGM (1, 1)
model is much more efficient and accurate than the conventional MCGM (1, 1) models.
Keywords: Forecast, China, Tourism demand, Optimal input subset, Cuckoo search
algorithm
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The First China-REAL Meeting, 2016
[12] Impact of recycled water price adjustment on price level in China
Xiuli LIU (Corresponding Author) Qingrong ZOU
Key Laboratory of Management, Decision and Information System, Academy of
Mathematics and Systems Science, Chinese Academy of
Sciences,Beijing,100190,China
Abstract: The final price of recycled water is generally lower than the cost, which
hinders its development. It is conductive to raising the price of recycled water for its
development. However, there are close relationships among product price of
production department, so it is necessary to analyze the impact of raise recycled water
price on other sectors’ price and the overall price level. In this paper, based on
input-output price model and the relationship between recycled water price and water
price, we calculated the impact with 2007 and 2012 the national 26 sectors
non-competitive input-output tables, under the case scenarios that the price of recycled
water were increased by 60% and 23% in 2007 and 2012 which were raised to
1.6RMB/ton. When the recycled water price was raised by 60% in 2007, the CPI
increased by 5.51×10-4% and PPI increased by 6.25×10-4. When the price was
increased by 23% in 2012, the CPI increased by 1.95×10-4% and PPI increased by
2.30×10-4. The results indicated the influence of price fluctuation of recycled water on
production field was greater than on the consumption filed. There was weak influence
on other sectors’ price and overall price level while raise the price of recycled water, so
raise the price of recycled water would not produce large fluctuations in the economy
and society.
Keywords recycled water price; Input-output price model; CPI; PPI
[13] Using Average Propagation Lengths to Identify the Structural Change in the
Chinese Economy
Zhuozhuo TU Xiuli LIU (Corresponding Author)
Academy of Mathematics and Systems Science, Chinese Academy of Sciences,
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The 2nd International Conference on Forecasting Economic and Financial Systems, 2015
Zhongguancun East Road No.55, Beijing, China, 100190
Abstract: The Average Propagation Lengths has been proposed as a measure of the
structural change and complexity of an economy. In this paper, we adopt this method to
uncover the transformation in Chinese economic structure over the past twenty years.
First, we define the distance between two sectors as the average number of steps it takes
an exogenous change in one sector to affect the value of production in another sector.
The distance does not depend on whether the linkages are forward or backward in
nature. Then, we introduce the strength of the linkage between two sectors as the
average of the backward and forward linkage, as measured by the Leontief and the
Ghosh inverse while excluding the direct effects. Combining the strength of the
linkages and the distance between sectors allows us to visualize the economic structure
more vividly. Finally, we employ the results from APL to find out the evolution of the
complexity of Chinese economy. In this paper, the production structure and complexity
of Chinese economy are studied from a set of input-output tables estimated for the
period 1995-2011 from WIOD.
Keywords: Input-Output Analysis; Economic Structure Change; Average Propagation
Lengths; Chinese Economy
[14] Prediction and Analysis of Beijing’s Population Structure Based on the PDE
Model
Xiuli LIU (Corresponding Author)
Qing LIU
Academy of Mathematics and Systems Science, Chinese Academy of Sciences,
Zhongguancun East Road No.55, Beijing, China, 100190
Abstract: Accurate prediction of population age structure provides an important
reference for administration of the population and the relevant policy designing. The
Population-Development-Environment Model (PDE) was applied in which population
migration was taken into consideration. Based on the data from Beijing’s sixth census,
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The First China-REAL Meeting, 2016
the paper estimated mortality parameters by time series and predicted the population
age structure of Beijing in 2015 and 2020 in the low, central and high scenarios. The
results showed that, Beijing would have a total population about 21,567,000 by 2015
and faced the problem of low fertility and population aging. In the central scenario
where the New Two-child Policy of Single-child Parent is implemented, Beijing’s total
population would be about 23,389,000 in 2020. Its population aging would have been
significantly decreased. In the low scenario where family planning program had never
changed, Beijing’s total population would be about 23,167,000 in 2020, and the
problem of population aging would be more serious than that in the central scenario. In
the high scenario where all the couples who enjoy the Universal Two-child Policy have
a second child, Beijing would have total population about 23,619,000 in 2020.
Although its population structure would be younger compared to the central scenario, it
would bring rapid population growth. The population would increase by 1 million in
the following 10 years.
Key words: PDE Model, population structure, prediction, New Two-child Policy of
Single-child Parent
[15] Uncovering the Structural Transformation of the Chicago Economy Using
Feedback Loop Analysis and APL
Xiuli LIUa Geoffrey J. D. Hewingsb Zhuozhuo TUa
a Academy of Mathematics and Systems Science, Chinese Academy of Sciences,
Zhongguancun East Road No.55, Beijing, China, 100190
b Regional Economics Applications Laboratory, University of Illinois, 607 S.
Mathews, #318, Urbana, IL, USA, 61801
Abstract: Hierarchical feedback loop analysis is employed in this paper to identify
changes in the economic interactions among sectors during the process of structural
transformation of the Chicago economy. Hierarchical feedback loops of Chicago for
years 1995, 2000, 2005 and 2010 were obtained. It is found that the first two feedback
loops captured the main character of the economic structure transformation. The input
of three sectors, Hotels, Repair Services and Trade, Construction, were the three main
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The 2nd International Conference on Forecasting Economic and Financial Systems, 2015
and stable forces of the first two feedback loops. The input of five other sectors, Food
and Kindred products, Health & Nonprofit, Finance, Insurance, Transportation and
Eating & Drinking Places, presented the greatest change over the period from 1995 to
2010. The input from Hotels, Repair services to Construction, from Finance,
Insurance to Trade, from Trade to Hotels, Repair Services and the new transaction
from Construction to Stone, clay and glass accounted for 83.5% of the intensity
change in the first feedback loop from 1995 to 2010. The structure change of linkages
played little role in the complexity change of the second feedback loop. The change of
linkages strength from Trade to Construction, from Rubber and Plastics to Chemicals
and Allied products accounted for about 83.0% of this latter loop.
Keywords:
Hierarchical
Feedback
Loop
Analysis;
Economic
Structure
Transformation; Input-Output Analysis; Chicago Economy
[16] A neoclassic model on regional economic growth: Spatial evidence from
China
Fei CHEN Xiangwei SUN
Nanchang University
University of Illinois
Abstract: In this article, to explore the economy growth performance at
prefecture-level in China, we following Erutr and Kock (2007) and Elhost et. al.
(2010), adopt a spatial-expanded neoclassic Solow growth model, and SDM panel
data model. First, we identified that the spatial fixed effect best fit for spatial- time
panel data in China. Second, we set Spatial Durbin Model to reflect economy growth
convergence in China, to explore the spatial spillover effect and linear relationship
between initial economy level and growth in China. Result shows that the spatial
spillover exists not only in economy growth of neighbors, but also in initial economy
level of neighbors. Furthermore, to control the underling heterogeneity cross China,
we exclude 5 provinces in west of China. Then regression analysis and comparison
analysis shows that, after controlling spatial heterogeneity, the spatial spillover effect
change differently for different variable. After excluding west region in China, the
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The First China-REAL Meeting, 2016
convergence presents a little faster speed than the one calculated from whole China
sample.
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