Exploratory Spatial Data Analysis of Regional Economic Disparities in Beijing during the Preparation Period of the 2008 Olympic Games

Transcription

1 Exploratory Spatial Data Analysis of Regional Economic Disparities in Beijing during the Preparation Period of the 2008 Olympic Games Xiaoyi Ma, Tao Pei Thursday, May 27, 2010 The State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences

2 1 Motivation Outline 2 Methodology and Data 3 Results 4 Discussion 5 Conclusions 2

3 1 Motivation Outline 2 Methodology and Data 3 Results 4 Discussion 5 Conclusions 3

4 Motivation The total investment for the 2008 Olympic Games from 2002 to 2007 is about 35.1 billion dollars efficiently promoted the growth in per capita GDP of Beijing. (The research report of Beijing Municipal Statistic Bureau) The chart of per capita GDP of Beijing from

5 Motivation University Area (Haidian) Northern Scenic Tourist Area (Shunyi) Western Community (Shijingshan) Central Area (Chaoyang) 5

6 Motivation Newly constructed venues and infrastructure, Region revival, Increased tourism, Improved public welfare, Additional employment, Local business opportunities The influence of the Olympic Games Some changes in spatial patterns of regional economic development? Benefits Hypothesis To Validate The per capita GDP growth: Venue regions the most Near-venue regions more than those regions not close to Olympic events the Spillover Effect 6

7 1 Motivation Outline 2 Methodology and Data 3 Results 4 Discussion 5 Conclusions 7

8 Methodology Traditional Statistics Analysis Overlook the spatial interactions and geographical locations The expected effects of the Olympic Games could be overestimated or underestimated Exploratory Spatial Data Analysis (ESDA) Emphasize the significance of spatial interactions and geographical locations By identifying spatial autocorrelation and spatial heterogeneity, the economic performance can be characterized according to time. Powerful tool for revealing the space-time dynamics of regional economic development. 8

9 Methodology Exploratory Spatial Data Analysis (ESDA) Aims:Describe and visualize spatial distributions Discover patterns of spatial association Identify atypical observations Suggest different spatial regimes or other forms of spatial heterogeneity (Anselin, 1999) Output:The measure of global and local spatial autocorrelation. Anselin L (1999) Interactive Techniques and Exploratory Spatial Data Analysis. In: Longley P, Goodchild M, Maguire D, Rhind D (eds) Geographical information systems: principles, techniques, management and applications. Wiley, New York, pp

10 x Methodology Global spatial autocorrelation x Global Moran s I statistic: The number of regions in the study area I n w ( x x)( x x) ij i j n i= 1 j= 1 n n n 2 ( xi x) wij i= 1 i= 1 j= 1 = n The attribute value for region i The spatial weight matrix based on the distance between the centroids of regions w The mean of the attribute values for the n regions ij 1 = 0 i, j within the threshold distance Otherwise 10

11 Methodology Local Spatial Autocorrelation Moran Scatter Plot : Four Quadrants: Positive Spatial Autocorrelation High-High, Low-Low Negative Spatial Autocorrelation High-Low, Low-High 11

12 x Methodology Local spatial autocorrelation x Local indicators of spatial autocorrelation (LISA) Local Moran s I statistic: The attribute value for region i ( x x) I = w ( x x) i i ij i m0 j with m The mean of the attribute values for the n regions 0 ( xi x) = n i 2 The spatial weight matrix based on the distance between the centroids of regions The number of regions in the study area 12

13 Data 1. Regional per capita GDP and vital statistics data over the period extracted from the Beijing area statistical yearbooks. 2. The administrative map of Beijing got from the administrative map of China with the scale of 1:1,000,

14 1 Motivation Outline 2 Methodology and Data 3 Results 4 Discussion 5 Conclusions 14

15 Results Global Spatial Autocorrelation 0.2 I Global Moran's I Year Moran s I statistics for per capita GDP of Beijing s eighteen districts or county,

16 Results Local Spatial Autocorrelation Moran Scatter Plot Changping Shijingshan Xicheng W_per capita GDP per capita GDP 16

17 Results Local spatial autocorrelation LISA Changping Shijingshan 17

18 1 Motivation Outline 2 Methodology and Data 3 Results 4 Discussion 5 Conclusions 18

19 Discussion Haidian Chaoyang Results Contradictory Shijingshan (Venue Region) Changping (Near-Venue Region) Hypothesis 19

20 Discussion Changping (Near-venue region): From the quadrant HH to LH The bid winning of 2008 Olympics accelerated the proceedings of Suburbanization of Residence in Beijing. Large communities: Tiantongyuan and Huilongguan were built. The sharp increase of population The lower per capita GDP growth The resident population statistics of Changping,

21 Discussion Shijingshan (venue region): From the quadrant HH to LH Due to the 2008 Olympic Games, Beijing accelerated the improvement of environment pollution. The policy-based limiting production of the Capital Iron and Steel Company The sharp decrease of production (Wan, 2006) The lower per capita GDP growth Wan X., Report on the implement of national economic and social development plan in 2006 and draft in 2007 of Shijingshan district. 21

22 1 Motivation Outline 2 Methodology and Data 3 Results 4 Discussion 5 Conclusions 22

23 Conclusions Investigate the influence of the 2008 Olympic Games for the development of regional economic ESDA & GIS analyze the spatial patterns of regional per capita GDP The growth of per capita GDP for each region in Beijing not as the same as Hypothesis A new centre-surrounding polarization scheme replacing the North-South polarization scheme 23

24 Thank You Xiaoyi Ma, Tao Pei Thursday, May 06, 2010 The State Key Laboratory of Resources and Environmental Information System 24 Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences