global urban competitiveness report (2007-2008) ni pengfei global urban competitiveness project...

Global Urban Competitiveness Report

(2007-2008)

Ni PengfeiNi Pengfei

Global Urban Competitiveness Project (GUCP)Global Urban Competitiveness Project (GUCP)

Institute of Finance and Trade Economics (CASS)Institute of Finance and Trade Economics (CASS)

Beijing, China, 20 octo 2008Beijing, China, 20 octo 2008

Beijing Urban competitiveness in World’s Cities

Method of Analysis

Global Urban Competitiveness: Conceptual Framework

The urban sustainable competitiveness implies a city’s ability in relation to other cities in the world to attract and translate resources, control and occupy markets, accumulate wealth as fast as possible and offer urban residents material benefits, which is determined by the combination of its enterprise operating factors and industrial systems.

UC1= F （ the size of GDP, number of international patent applications, the distribution of multinational corporations, price advantages, economic growth rate, GDP per capita, GDP per square kilometer, employment rate, and labor productivity ）

UC2= F （ E 、 T 、 I 、 L 、 H 、 S 、 G ） . UC2 means the input or structure of the city’s competitiveness, E means the quality of enterprise, T means human resource, I means industry structure, L means the living environment, H means the business soft environment, S means the business hard environment, G means the global connectivity.

UC1= UC2

Global Urban Competitiveness: Index System

Urban Indicative Competiti

veness

GDP per Capita

Economic Growth

Rates

GDP per Square

Kilometer

TNCsNumber

International

Patent Applicati

ons

Price Advantag

esGDP Size

Labor Productiv

ity Employment Rates

Explanatory components of urban competitiveness

Company Essence

Industry Structure

Human Resources

Living Environment

Software Environment

Hardware Environment

Global Connectivity

Global Urban Competitiveness: City Samples

500 Cities for General Urban Competitiveness MeasurementUniversality: cities from 5 continents, 130 countries and regions, representing

different areas and levels of developmentSelection criterion: the numbers is determined according to national populati

on and income per capita; and then filtered by the scale, status and the accessibility, accuracy and standardization of the statistical data.

150 Cities for Detailed AnalysesRepresentativeness: from 5 continents, 47 countries and regions. Focus on ke

y cities of North America, Europe, Asia and Oceania ， and some pivotal cities located in South America and Africa.

Selection criterion: global influence, the social and economic position in its area, the typicalness of its kind, special research value and accessibility of the data, also some consideration of previous research.

10 Cities for competitiveness case studySelection criterion: Successful, creative, sustainable and usable urban experie

nce.

Data for statistical index Global Urban Competitiveness Index system has 114 indexes.

The acquirement of the data is complicated.Every sample city has the original statistics related to the indexe

s, such as urban population and area, but the statistic scopes are different nationally

Majority of the sample cities has related original statistics, and some are living indexes published by consultancy services.

There is no related international or national statistical agency yet, even no subjective survey data, such as industrial index, city function index or enterprise quality

Global Urban Competitiveness: Data sources and statistical methods

Data collection channel

International organizations and official statistical publications, then processed for consistency (mainly use statistics in 2005, time series data only from 2001 to 2005).

Internet provide index-related statistics, quantified according to certain criteria (mainly use statistics in 2007, time series data from 2004 to 2007).

Global Urban Competitiveness: Data Sources and Statistical Methods

Processing of collected index-related data Data integration: In order to solve the difference between statistic

scopes and criterions, a study has been done about statistical items and criterions of international organizations, such as statistical distribution from United Nation Statistics Division, World Development Indicators from World Bank, database of Organization for Economic Co-operation and Development etc. Then data transformation relations are established among statistical items from different countries. Therefore, using this most reasonable, comparable and complete statistical standard set to process the collected data, we generated a unified data base covering 500 cities around the globe.

Missing Data: if a city has the deficiency of certain indexes, estimation is made according to the given national statistics, its domestic position and corresponding performance.


Solution for index-related data which can not be collectedGrading method to replace Index. In the light of unified standard, such

index will be replaced by another related index which is most identical and typical, grading by indirect factors. For example, use distribution of transnational financial company to indicate the urban financing development status.

Typical sample comparative method. According to the standard, typical samples will be selected and compared within a sample city, to represent, indicate, and standardize certain aspect of this city. For example, enterprises are represented by an example of a typical industry.

Grading method using related information. According to the aspect of the index, find the key point and class standard, then collect related data which can be used to indicate such index.


Global Urban Competitiveness : Method of Quantit

ative Analysis Global urban competitiveness index (GUCI) of 500 cities in world.

Choosing non-linear weighted integration method to deal with data .

Choosing clustering analysis method for comparative research.

Global Urban component competitiveness index (GUCSI) of 500 cities in world.

The explanatory component competitiveness sub-indices are divided into three lev

els, where the tertiary level indices can be integrated into secondary level indice

s and then integrate the secondary-level indices into primary level indices using

equal weighting.

Cause and effect analysis of competitiveness in 150 cities from world

Employ the non-linear fuzzy curve analysis and the linear regression analysis met

hods

The case study of top 10 cities in world

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Research Results

Beijing Urban competitiveness in World’s 500 Cities

City Competitiveness Score

Rank

New York 1 1

London 0.944185 2

Tokyo 0.790169 3

Paris 0.759375 4

Washington 0.696406 5

Los Angeles 0.668836 6

Stockholm 0.647921 7

Singapore 0.645897 8

San Francisco 0.642095 9

Chicago 0.629848 10

Beijing 0.457567 66

GUCI distribution and comparison of 500 cities (Unit: index)

Global Cities: Which city is the most competitive?

This report measures competitiveness of 500 cities in the world with 9 indexes, namely GDP, GDP per capita, GDP per square kilometer, labor productivity number of multinational corporation headquarters, number of international patent applications, price advantage, economic growth rate, and employment rate.

The top 20 competitive cities are New York, London, Tokyo, Paris, Washington, Los Angeles, Stockholm, Singapore, San Francisco, Chicago, Toronto, Seoul, Boston, San Diego, Oakland, Helsinki, Madrid, Vienna, Philadelphia, and Houston.

The top 20 cities are the strongest ones in terms of economy size, development level, technical innovation, and economic control. Among the top 20 cities, 10 located in North America, 7 in Europe, and 3 in Asia. In conclusion, the regions with the strongest urban competitiveness are North America, Europe and Asia.

CityGross Domestic Product

Rank

$ billions

Tokyo 584.9532 1

Paris 525.0543 2

New York 502.51 3

London 446.2 4

Mexico City 220.08 5

Los Angeles 180.08 6

Hongkong 179.78 7

Seoul 176.6 8

Sydney 171.69 9

Melbourne 134.76 10

Beijing 82.71 23


CityRatio of Nominal Exchange Rate

to Real Exchange Rate Rank

Score

Yangon 11.11111 1

Harare 8.333333 2

Addis Ababa 6.25 3

Phnom Penh 5.555556 4

Pyongyang 5.263158 5

Accra 5.263158 6

Kinshasa 5.263158 7

Ho Chi Minh City 5 8

Hanoi 5 9

Kampala 5 10

Beijing 4.347826 60


City GDP Per Capita Rank

$

Geneva 62676.92 1

New York 61178.19 2

Oakland(US) 60638.41 3

Edinburgh 59540.23 4

Washington 58548.98 5

London 57948.69 6

Oslo 57931.4 7

Belfast 56105.86 8

Basel 55247.85 9

Zurich 54056 10

Beijing 6309.51 277


Incomes per capita of cities worldwide (Unit: US $)

CityGDP Per Square

KilometreRank

$ thousands

New York 643498.2 1

Geneva 633715.1 2

Victoria(CA) 565083.3 3

Macao 482636.2 4

Lyon 337620.8 5

San Francisco 326156.5 6

Manchester 309761.2 7

San Juan 302016.4 8

Nottingham 300355.8 9

Kawasaki 296998.8 10

Beijing 6785.89 358


GDP per square kilometre of cities worldwide (Unit: US $ thousands)

City Employment Rate Rank

%

Moscow 99.2 1

Tijuana 99.1 2

Baku 99.02 3

Acapulco 99 4

Quanzhou 98.83 5

Oakland(US) 98.67 6

Al Kuwayt 98.51 7

Minsk 98.5 8

Shenzhen 98.4 9

Huizhou 98.2 10

Beijing 97.92 14


CityReal Economic Growt

h Rate（ for 5 years）

Rank

%

Huhehaote 0.2 1

Baotou 0.2 2

Yantai 0.195727 3

Dongguan 0.192492 4

Baku 0.19 5

Zhongshan 0.184408 6

Huizhou 0.181123 7

Weifang 0.179826 8

Wuhu 0.179669 9

Manaus 0.179569 10

Beijing 0.116805 79


Economic growth rates of cities worldwide (Unit: %)

City Labor Productivity Rank

$

London 161120.7 1

New York 141880.7 2

Detroit 141259.2 3

New Orleans 126097.1 4

Philadelphia 124986.8 5

Boston 121893.5 6

Cleveland 119658.1 7

Oslo 118069.9 8

San Jose 116237.8 9

Baltimore 113666.5 10

Beijing 11698.64 291


Labor productivities of cities worldwide (Unit: US $ )

CityNumber of International Pate

nt Applications Rank

number

Tokyo 89445 1

Osaka 39718 2

Paris 20364 3

London 17968 4

New York 16915 5

Seoul 16651 6

Stuttgart 15277 7

San Diego 14338 8

San Jose 12309 9

Stockholm 11785 10

Beijing 3012 56


Internatioanl patent applications by cities worldwide (Unit: number)

CityMultinational Corp

oration Distribution

Rank

Score

New York 522 1

London 501 2

Hongkong 378 3

Paris 342 4

Tokyo 332 5

Singapore 317 6

Beijing 311 7

Shanghai 295 8

Moscow 289 9

Sydney 289 10


The distribution of multinational companies worldwide (Unit: index )

Global Urban Economic Control Center: Evolution in Progress

Relationship between global space and economic decision-making: the US,UK and Australia are the forerunners in the ranking, and some Asian cities like Shanghai, Beijing and Seoul are also in high rankings, which indicate that the global economic decision-making center is changing.

Relationship between Urban Scale and Economic Decision: New York , London and Tokyo, are the world top cities and are still the economic-decision making centers, however, the headquarters of many multinationals are located in small cities, like Geneva and Brussels, these cities are high-level international cities and have good economic decision-making abilities.

Global Urban Cities: The Future of Cities is Uncertain

According to the clustering analysis method with 9 index data of 500 cities, we find that:

Some top cities located in the world economic core areas are getting stronger and stronger. The gap between them and other cities in the world becomes wider and wider.

Some developed cities located in economic core-areas of the world slowed-down and even declined.

Some cities located in the edge zones of the economic core-areas are rising rapidly and even exceeding their competitors.

Some less developed cities in periphery areas are declining further.

Some less developed cities in the periphery areas rising rapidly. Some less developed cities in the periphery rose rapidly and

then declined again.

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