Stanley Wing-fai NG, CEO, Registered Professional Planner (Hong Kong),

MRTPI(UK), MHKIP,MGISA(HK), MSc(HKU). BSc.(NTU)

April, 2006

Cities Competitiveness & Risk Ranking(A Preliminary Study on Correlation between Expert Ranking and Demographic Indicators)

Cities/ Counties Based Investment Decisions

Statistics and Census • Demographic

• Economic Indicators• Personnel Indicators

• 2300+ Cities/ Counties

Input 2 DatabaseInput 1Expert Ranking System• Competitiveness• Investment Index• Empirical• 50-108 cities/ ind. zones

Correlation AnalysisGeneral Rules

Branch/ Factory/ OutletBranch/ Factory/ OutletDecisionDecision

Market,Resources Local Gov Sch.

Relations Other Factors

Input 1: Expert Ranking SystemCities’ Competitiveness & Risks

• Several Taiwan scholars’ Studies for Trade Associations “Analysis on Competitiveness and Risks for China Cities”

• 2001-2004 published• Survey and Expert Ranking System

– Questionnaire Survey– Focus Group– Case Studies, Factory Visits

• Publication Ref: – “ 兩力兩度見商機 – 2004 中國大陸地區投資環境與風險調查”

• Author: Taiwan Electrical and Electronic Manufacturers’ Association 台灣區電機電子工業同業公會 ,• ISBN:986-7877-12-8, 2004. 主任委員：焦佑君，主持：呂鴻德，協同主持：黃銘章，顧問：高孔廉

– 生產力中心 China Productivity Center (Taiwan),– “ 進軍中國大陸市場機遇與挑戰”，外貿協會 Taiwan External Trade Development Council

Index Derived

• Ranking in Competitiveness – 108 cities – Major Cities and Counties include 108 major cities, industrial zones, Special Economic Region– Competitive power is calculated by: infrastructure, finance status, investment environment, economic status and employment.

• Ranking in Overall Investment Index – 41 cities– Investment Risks

• Local Governance Risks, Environmental Risks, Social Risks etc

– Investment Index is calculated by the • Competitive Power, • Investment environment, • Investment risk of a city.

Expert Ranking:-

• Empirical data from case studies– Case studies, interview, survey – In-depth case studies of Taiwanese factories/ investors – 108 cities/ counties/ industrial zones ranked depends on cases and data readiness

• Not applicable to cities/ counties not ranked– about 100 cities out of 2300+ cities/ counties

• General limitation of expert ranking system– personal factors– different scale/ parameters

Input 2: Census & Statistics DataDemographics and Economy

• Census & Statistics Data in China – 2300+ Cities• Data Availabilities

– USA/ UK /HK system vs. China system– national data vs. local data– Data reliabilities, personnel vs. government corporate

• Data Release Time Frame– 2005, national and provincial data– 2004, cities/ counties and districts inside cities– 2003, cities/ counties and districts rectified in 2005

Demographics and Statistics for 2300+ CitiesDemographics and Statistics for 2300+ Cities

Jointly developed by ACMR and MapAsiaJointly developed by ACMR and MapAsia

CHINA infoMapCHINA infoMap

ExclusiveExclusive LicenseLicense

Sample of Bar Chart

Thematic Map – Pie Chart

Compare Expert Ranking with Statistics

• Regression Analysis• ANOVA Analysis (Analysis of

Variance)• Map Overlay Analysis• Parameters

– Competitiveness and Investment Index– Variables in wages, population, GDP,

Education Attainment, Industrial Output

Basic Information

• China Census data 2003 was used.

(2003 data rectified in 2005)

• Factors for the calculation: Wages, GDP, Population, Industry and Education

• “Factors” against Competitive Power

• “Factors” against Investment Index

Competitive Power

• Calculated by: infrastructure, financial status, investment environment, economic status and employment of a City.

• Parameters against Competitive Power– Wages- total wages of the city, Million RMB– GDP – Million RMB– Population – Million– Education – High school student, Middle school

student in million– Industry Output Million

• 108 Cities included in the Expert Ranking System

Competitive Power of Major Cities(Expert Ranking)

Wages of China Major Cities

Population of China Major Cities

GDP of China Major Cities

Industrial Output of China Major Cities

Education Attainment

Regression of Wages

0.00

20.00

40.00

60.00

80.00

100.00

120.00

140.00

160.00

0.00 1000000

0000.00

2000000

0000.00

3000000

0000.00

4000000

0000.00

5000000

0000.00

6000000

0000.00

7000000

0000.00

8000000

0000.00Wages

Com

petit

ive Po

wer

Competitive Power

Calculated Competitive Power

Wages against Competitive Power

Population against Competitive Power

Regression of Population

0.00

20.00

40.00

60.00

80.00

100.00

120.00

140.00

0.00 50000000

0.00

10000000

00.00

15000000

00.00

20000000

00.00

25000000

00.00

30000000

00.00

35000000

00.00Population

Com

petit

ive Po

wer

Competitive Power

Calculated Competitive Power

GDP against Competitive Power

Regression of GDP

0.00

50.00

100.00

150.00

200.00

0.00 10000000.

00

20000000.

00

30000000.

00

40000000.

00

50000000.

00

60000000.

00

70000000.

00GDP

Com

petit

ive

Power

Competitive Power

Calculated Competitive Power

Education Attainment against Competitive Power

Regression of High School

0.00

20.00

40.00

60.00

80.00

100.00

120.00

0.00 100000.00 200000.00 300000.00 400000.00 500000.00 600000.00High School

Com

petit

ive

Pow

er

Competitive Power

Calculated Competitive Power

Industrial Output against Competitive Power

Regression of Secondary Industrial Production

0.00

20.00

40.00

60.00

80.00

100.00

120.00

0.00 5000000.

00

1000000

0.00

1500000

0.00

2000000

0.00

2500000

0.00

3000000

0.00

3500000

0.00

4000000

0.00

4500000

0.00

Industrial Production

Com

petit

ive

Power

Competitive Power

Calculated Competitive Power

Investment Index

• Calculated by the competitive power, investment environment and investment risk

• Parameters in Wages, population, GDP, Education and Industrial Output against Investment Index

• 41 Cities included in the Expert Ranking System

Investment Index of China Major Cities(Expert Ranking)

Wages against Investment Index

Regression of WAGES

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

80.00

90.00

100.00

0.00 10000.00 20000.00 30000.00 40000.00 50000.00 60000.00 70000.00 80000.00WAGES

Inde

x

Index

Calculated Investment Index

GDP against Investment Index

Regression of GPD

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

80.00

90.00

100.00

0.00 10000000.00 20000000.00 30000000.00 40000000.00 50000000.00 60000000.00 70000000.00GPD

Inde

x

Index

Calculated Investment Index

Population against Investment Index

Regression of POPULATION

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

80.00

90.00

100.00

0.00 500.00 1000.00 1500.00 2000.00 2500.00 3000.00 3500.00

POPULATION

Inde

x

Index

Calculated Investment Index

Education against Investment Index

Regression of Education

0.0010.00

20.0030.0040.0050.00

60.0070.0080.00

90.00100.00

0.00 100000.00 200000.00 300000.00 400000.00 500000.00 600000.00Education

Inde

x

Index

Calculated Investment Index

Industrial Output against Investment Index

Regression of Industry

0.00

10.00

20.00

30.00

40.00

50.0060.00

70.00

80.00

90.00

100.00

0.00 500000

0.00

100000

00.00

150000

00.00

200000

00.00

250000

00.00

300000

00.00

350000

00.00

400000

00.00

450000

00.00

Industry

Inde

x

Index

Calculated Investment Index

1. 1. Expert Ranking of Competitiveness Expert Ranking of Competitiveness positive correlate with some major positive correlate with some major demographic indicators, i.e. GDP, per capital demographic indicators, i.e. GDP, per capital GDP, output of secondary industries, wages GDP, output of secondary industries, wages

2.2. Correlation of Experts’ Investment Correlation of Experts’ Investment Index (include Risks Index) not so Index (include Risks Index) not so significant. significant.

Preliminary Findings:-Preliminary Findings:-

• GDP, per capita GDP, Industrial Output and Wages having higher correlation with Competitive Power among other factors

• Population and Education Attainment having lower correlation with Competitive Power among the factors.

• For the Investment Index, none of the factors obtain a significant correlation with investment index.

• For further analysis, time series analysis may improve the predictive model of the competitive power and Investment Index.

Thank You

Stanley Ng (CEO), stanley@mapasia.com

• Team member: Stanley NG, CEO Winsome Wong, GIS Specialist Ng Wing Yiu, Data Manager

• MapAsia.com City Country Consultancy LtdHong Kong . China . Kuala Lumpur . Singapore mapsale@mapasia.com, 852-27409680,