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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 Includes1. Access to all technical sessions2. Lunch and dinner during the conference3. Coffee breaks during the sessions4. One hard copy of the conference guide5. One souvenir for the First China-REAL meetingLate registration and any other questions about registration please contact: Qingrong Zou: 15600601956

Presentation InstructionThe 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 ConnectionWIFI: AMSSPassword: 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: 18813189838Scientific Programme: Qingrong Zou: 15600601956

Map of the venue and nearby area

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Contents

PROGRAM..............................................................................................................................................1Sponsors.....................................................................................................................................................1Conference Committee..............................................................................................................................2Time Table.................................................................................................................................................4Abstracts....................................................................................................................................................7[1] Evolution of Production Space and Regional Industrial Structures in China......................................7[2] China’s Position, Trade Revenue and Competitiveness on the Global Value Chains: An Analysis Based on Trade in Value Added Accounting Framework..........................................................................7[3] Is County-to-city Upgrade in China a Failed Urbanization Policy?....................................................8

[4] Identification and Dynamic Characteristics of Beijing-Tianjin-Hebei Mega-city Region：Based on 5th and 6th Census in China......................................................................................................................9Yuyuan WEN.............................................................................................................................................9School of Economics, Renmin University of China, Beijing 100872.......................................................9[5] PM2.5 and the Path Choices of Urbanization....................................................................................10[6] Regression—the probability foundation and approach to estimate...................................................11[7]Collapse of City and Economic Horizon............................................................................................12[8] The effects of vertical specialization on regional carbon transfer and allocation within China........13

[9] What matters in measuring domestic value added in exports by international or single country model.......................................................................................................................................................14[10] Administrative Monopoly, Ownership and Wage differentials across Time and Space in China....14[11] Using a Grey-Markov model optimized by Cuckoo Search algorithm to forecast the annual foreign tourist arrivals to China............................................................................................................................15[12] Impact of recycled water price adjustment on price level in China.................................................16[13] Using Average Propagation Lengths to Identify the Structural Change in the Chinese Economy. .17[14] Prediction and Analysis of Beijing’s Population Structure Based on the PDE Model....................18

[15] Uncovering the Structural Transformation of the Chicago Economy Using Feedback Loop Analysis and APL....................................................................................................................................19

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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, ChinaXikang Chen, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, ChinaProgram Chair:Geoffrey J. D. Hewings, Regional Economics Applications Laboratory, University of Illinois, 607 S. Mathews, #318, Urbana, IL, USA, 61801Organizing committee Chair:Xiuli Liu, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, ChinaProgram committee members:Canfei He, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, ChinaPing Lei, School of Humanities & Economic Management, China University of GeoscienceTang Wei, School of Economics, Fudan University

Wen Chen, Department of International Trade and Business, School of Economics,

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http://www.cefs.ac.cn/


Xiamen University, Xiamen

Wang Zhenquan, Beijing Institute of Petrochemical TechnologyHongxia Zhang, School of Economics, Renmin University of China. Beijing, China, 100872

Yuyuan Wen, Renmin UniversityZinan Zhang, China Economics and Management Academy (CEMA), Central University of Finance and Economics, Beijing, China 100081Xu 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 UniversityContacts:[email protected]. 55, Zhongguancun East Road, Haidian District, Beijing,100190, China

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Time Table

8:00-17:00 Registration Lobby

9:00-9:05Open Session (Chair : Xikang Chen)

N205Opening Address: Shouyang Wang, General Chair

9:05-10:05

Keynote Speech (Chair: Xikang Chen)

N205Speaker: Prof. Geoffrey Hewings

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

10:15-10:45Speaker: Qi Guo

Qi Guo, Canfei He, Evolution of Production Space and Regional Industrial Structures in China

10:45-11:15Speaker: Tang Wei

Tang Wei, Is County-to-city Upgrade in China a Failed Urbanization Policy?

11:15-11:45Speaker: Zinan Zhang

Zinan Zhang, Administrative Monopoly, Ownership and Wage differentials across Time and Space in China

11:45-12:15

Speaker: Xiuli LiuXiuli Liu, Geoffrey J. D. Hewing, Uncovering the

Structural Transformation of the Chicago Economy Using Feedback Loop Analysis and APL

12:15-13:30 Lunch/Rest Wuke Restaurant

14：00-

15:30Session 2 （Chair: Xiuli Liu） N205

14:00-14:30 Speaker: Yuyuan WenYuyuan Wen, Identification and Dynamic Characteristics

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of Beijing-Tianjin-Hebei Mega-city Region：Based on

5th and 6th Census in China

14:30-15:00Speaker: Jianhua Li

Jianhua Li, Collapse of City and Economic Horizon

15:00-15:30Speaker: Zengkai Zhang

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

15:40-16:10Speaker: Zhenquan Wang

Zhenquan Wang, Regression—the probability foundation and approach to estimate

16:10-16:40 Speaker: Qingrong ZouXiuli Liu, Qingrong Zou, Impact of recycled water price

adjustment on price level in China

16:40-17:10

Speaker: Hongxia ZhangHongxia Zhang, Geoffrey J.D. Hewing, What matters in

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

9:00-9:30Speaker: Ping Lei

Ping Lei, PM2.5 and the Path Choices of Urbanization

9:30-10:00Speaker: Qing Liu

Xiuli Liu, Qing Liu, Prediction and Analysis of Beijing’s Population Structure Based on the PDE Model

10:00-10:30

Speaker: Xu SunXu Sun, JianzhouWang, YixinZhang, YiningGao, Using

a Grey-Markov model optimized by Cuckoo Search algorithm to forecast the annual foreign tourist arrivals

to China

10:30-10:50 Coffee Break Lobby

10:50-12:20 Session 5 (Chair: When Chen) N205

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10:50-11:20

Speaker: Zhuozhuo Tu

Zhuozhuo Tu, Xiuli Liu, Using Average Propagation Lengths to Identify the Structural Change in the Chinese

Economy

11:20-11:50

Speaker: Wen Chen

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

11:50-12:20

Speaker: Fei ChenFei Chen, Xiangwei Sun, A Neoclassic Model on

Regional Economic Growth: Spatial Evidence from China

12:20-13:20 Lunch/Rest and conference close Wuke Restaurant

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Abstracts

[1] Evolution of Production Space and Regional Industrial Structures in ChinaQi 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 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

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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 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)

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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. (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 UrbanizationPing 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 estimateZhenquan 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. 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

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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 HorizonJianhua 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 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

1 Trygve Haavelmo. The Probability Approach in Econometrics, Econometrica, Vol.12(1944)

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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.

[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

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

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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 ZHANGChina Economics and Management Academy (CEMA), Central University of Finance

and Economics, Beijing, China 100081Abstract: 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 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

aSchool of Statistics, Dongbei University of Finance and Economics, Dalian 116025, China

bSchool 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

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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

[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, Zhongguancun East Road No.55, Beijing, China, 100190

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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, 100190Abstract: 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, 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

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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

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 SUNNanchang UniversityUniversity of Illinois

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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

convergence presents a little faster speed than the one calculated from whole China

sample.

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