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ON MEASURING THE
   COMPLEXITY OF
    URBAN LIVING

Lubna Hasan
Pakistan Institute of Development
Economics
31 Oct 2007
Measuring Complexity
 Cities are the prime agents of
  development
 Cities face many challenges owing to
  urbanization and globalization
 Need to measure and monitor cities

 City rankings are a useful tool to
  monitor progress.
The ‘Stylized Facts’ of Urban
Economics

Cities are centers of economic,
 social and cultural activities.
From being “isolated seats of
 power from where to govern
 rural holdings,” cities have
 become the ultimate abode of
 humanity”.
The ‘Stylized Facts’ of Urban
Economics


“As countries develop, urban
 settlements account for a
 larger share of national
 income”.
The Economics of Cities
 New  York, Los Angeles, Chicago, Boston,
  and Philadelphia together constitute the
  fourth largest economy in the world.
 Sao Paulo and Bangkok hold about 10%
  of the total population but account for
  about 40% of the GDP.
 Per capita income in African cities is
  65% higher than the national average.
The Economics of Cities

 1. Frankfurt . . . . . . . . . . . 68,947
 2. Karlsruhe . . . . . . . . . . . 64,903
 3. Paris . . . . . . . . . . . . . 62,220
 4. Munich . . . . . . . . . . . . 56,813
 5. Dusseldorf . . . . . . . . . . 50,048
   (In million dollars)
The Economics of Cities
Cities are the “super markets for
  employment, incubator of technology,
  suppliers of social services and
  shelter, portals to the rest of the
  world, processors of agriculture
  produce, adders of manufactured
  value, places to make money through
  trade, industry, finance, real state”
Urban Loads
 Congestion

 pollution

 Crime
The ‘Stylized Facts’ of Urban
Economics


Globalization of economic
 activity has put cites in a new
 set of relation vis-à-vis
 capital.
City Competition - the New
Reality
 City branding has become a ‘must do’
 for cities. In today’s globalised,
 networked world, every place has to
 compete with every other place for
 its share of the world’s consumers,
 tourists, businesses, investment,
 capital, respect and attention. Cities
 are increasingly the focus of this
 international competition.
City Marketing
 Zurich is the world’s best city to live in
  (Mercer Consulting 2006).
 London, New York, Oslo, Tokyo and
  Zurich are the most expensive cities,
  while Swiss cities house the highest
  earners in the world (UBS 2006).
 London and Paris are the best cities to
  locate businesses (European Cities
  Monitor 2005).
"Basel beats differently."
1. Basel is a city of research and
   development, of science and
   education.

2. Basel is one of Europe's leading
   centres of the fine arts.

3. The people of Basel cultivate the
   art of savoir vivre and love to share
   the high quality of life with their
   guests.

4. Basel is a place where innovative,
   high-quality ideas, products, and
   services are exchanged and traded.
Quality of life

   With a thriving economy, a stable political system, Austria's beauty
    and cultural diversity all contribute to a high-quality of lifestyle for
    locals and tourists alike.
   Austria's capital Vienna ranks as one of the most attractive cities
    world wide. The feeling of well-being enjoyed by locals and tourists
    has been repeatedly confirmed by leading international studies and
    city rankings.

   Vienna - 4th place in a world wide quality of life survey
Visit Vancouver
Recognition & Awards

  2004: Vancouver voted Top
  City in Americas by Conde
  Nast Traveler.

  2003: Mercer Human Resource
  Consulting rates Vancouver as
  top city in North America for
  quality of life.

  2002: Vancouver ties with
  Melbourne as the Top City to
  live within the Economist
  Intelligence Unit survey.
   Our 12th annual Hot
    Cities report will give
    you the lowdown on the
    nation’s most dynamic
    cities for
    entrepreneurs.

   Whether you’re looking
    to expand, relocate or
    simply stay put, our
    quick guide to the top
    10
Developing World Cities in
Global Competition
 Shanghai  most favorite destination for
  European investors.
 Beijing, Mumbai and Mexico City
  follow Suite.
City Development Index


CDI = (Infrastructure index + Waste index +
 Education index + Health index + City
 product index) /5
 Infrastructure  = 25 x Water connections +
  25 x Sewerage + 25 x Electricity + 25 x
  Telephone
 Waste = Wastewater treated x 50 +
  Formal solid waste disposal x 50
 Health = (Life expectancy – 25) x 50/60 +
  (32 – Child mortality) x 50/31.92
 Education = Literacy x 25 + Combined
  enrolment x 25
 Product = (log City product -4.61) x
  100/5.99
CDI Value
                     St
                        oc
                          kh




                                                                      100
                                                                            120




                                           20
                                                40
                                                        60
                                                                 80




                                       0
                                ol
                                   m
                            M
                             ad
                                ri
                                  d
                            Pr
                               ag
                                 ue
Sa
   nt            Bu         D
      o              en       oh
          A            os        a
              nd
                 re        A
                    /        ir
                      S         es
                        ao
                            Pa
                                ul
                       Bu         o
                         la
                 Po         wa
                    rt          yo
                        of
                            Sp
                                ai
                                   n
                         H
                           ar
                              ar
                        Ja e
                           ka
                              rt
                                 a
                            Ce
                      D         bu
                          am
                           as
                              cu
                                 s
                         La
                            ho
                                re
                        Co
                           lo
                    Ca       m
                                bo
                       sa
                          bl
                            an
                                ca
                       A
                         su
                                                                                  City Developemnt Index




                            nc
                               io
                       Ba        n
                          gh
                              da
                                 d
                           Ga
                     Ch        za
                        i
                        tt
                           ag
                              on
                       Ki        g
                          ns
                             ha
                               sa
                                                         CDI
Ranking of World Cities by GUO City Development Index
            120




            100




            80
CDI Value




            60




            40




            20




             0
                  0       20      40     60       80      100   120     140   160

                                               CDI Rank



                                                   CDI
H
                    on
                       g




                                                                  100
                                                                        120




                                          0
                                              20
                                                   40
                                                        60
                                                             80
                            K
                                 on
                                   g

                           S
                            eo
                              ul
                   M
                    el
                      bo
                                 un
                                    e
                 B
                  an
                    ga
                               lo
                                  r   e

                          H
                      an
                K        oi
                 at
                   hm
                      an
                         du


                           C
                               eb
                                  u

                   D
                      ha
               M         ka
                an
                  da
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                        yo
                           ng

                          M
                           ed
                             an
                    C
                        ol
                           o   m




Connectivity
                                   bo

                        La
                          ho
                                   re
                                                                              Connectivity Index




                            S
                             uv
                                    a
                     B
                      is
                            hk
               P               e      k
                hn
                  om
                            P
                             en
               U                      h
                   la
                      a   nb
                             a   at
                                   ar

                           N
                               ag
                                  a
                      H
                           oh
                              h    ot
0
                                                                                                    100




                                                       10
                                                            20
                                                                 30
                                                                      40
                                                                           50
                                                                                60
                                                                                     70
                                                                                          80
                                                                                               90
                          D
                              ha
                                    ka

                          S
                           e
                                   ou
              B                            l
               a
                      ng
                              a
                                   lo
                                        re

                      La
                        h
             M                     o
                                       re
              a
                  nd
                          a
                              lu
                                   yo
                                        n
              H                                g
                  on
                     g
                               K
                                o
                                       ng

                      H
                          oh
                                   h
                                       ot
                  C
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                               m
                                    bo

                          M
                           e
                                   da
                                        n

                          H
                               an
             P                    o
              h                            i
                  no
                     m




Congestion
                               P
                                e
                                        n
             K                              h
              a
                   th
                          m
                               an
                                       d
             U                             u
                 la
                      a
                                                                                                          Congestion Index




                          nb
                               a
                                   a
                                       ta
                                               r

                          C
                               eb
                                        u
                      B
                       is
                               hk
                                  e
                                        k

                          N
                               ag
                                  a

                              S
                               u
                                    va
                  M
                   e
                          lb
                               o
                                   un
                                           e
 Jamal, Khan, Toor and Amir (2003) rank
 districts of Pakistan on the basis of
 deprivation indices. These indices are
 based on education, housing quality and
 congestion, residential housing services
 and employment sectors and are
 constructed from Population and Housing
 Census data of 1998.
 Pasha et al (1998) develop a district
 ranking system for Pakistan based on
 economic and social development. The
 social development indicator includes
 education, health and water supply.
 Whereas, the economic development
 indicators includes income and wealth,
 agriculture, housing conditions, transport
 and labor.
 Hussain (2003) has also calculated
 Human Development Index at the
 district level for Pakistan, following the
 same methodology as used in the
 construction of cross country HDI.
Measuring Pakistani Cities
 At  present, there is no country-wide
  system for measuring cities and city
  life in Pakistan.
 The only efforts at measuring cities –
  UN-Habitat’s Global Urban Indicators
  Program and ADB Cities Data Book -
  have limited scope.
Measuring Pakistani Cities
 They  are restricted to a maximum of
  two cities
 These exercises are not carried out
  on yearly basis
 They have their own agenda.

 Other efforts at measuring
  performance are district based
Measuring Pakistani Cities
 Make  city as the relevant unit of
  analysis
 Develop a city ranking system for
  Pakistan
 Extend GUIP to major cities of
  Pakistan
Dimensions
Demographic          City Population

Health and           Person per Hospital
                     Bed/Doctor/Nurse
Education
                     School Enrollment Rates
                     Tertiary Graduates
                     School Children per Classroom
Urban Productivity   City Product
                     Employment by Industry
                     Unemployment
                     Household Expenditure
Housing              House Price to Income Ratio
                     House Cost to Income Ratio
Dimensions
Infrastructure   Water Connections
                 Investment/ expenditure per capita
                 Electricity Connections
                 Investment/ expenditure per capita
                 Solid Waste Collection Household
                 Number
                 Investment/ Generation per capita
                 Solid Waste expenditure
Urban
Environment      Sewage Disposal
                 Waste Water treated
                 Energy Usage
                 Noise Complaint
                 Pollution
Dimensions
Urban Transport   Travel Time
                  Expenditure on Roads
                  Road Congestion
                  Automobile Ownership
Culture           News apers/Media
                  Cultural Events/Attendance
                  Museums/Attendance
Public Safety     Crimes

New Technology    Telephone Connections
                  Internet Connections
Dimensions
Urban Land         Vacant Government Land
                   Vacant Land with Planning Permission
                   Public Open Space
                   Prime Commercial Land Price
                   Prime Rental Cost

Urban Governance   Functions of Local government
                   Annual Plans

                   Voters Participation

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Measuring complexity

  • 1. ON MEASURING THE COMPLEXITY OF URBAN LIVING Lubna Hasan Pakistan Institute of Development Economics 31 Oct 2007
  • 2. Measuring Complexity  Cities are the prime agents of development  Cities face many challenges owing to urbanization and globalization  Need to measure and monitor cities  City rankings are a useful tool to monitor progress.
  • 3. The ‘Stylized Facts’ of Urban Economics Cities are centers of economic, social and cultural activities. From being “isolated seats of power from where to govern rural holdings,” cities have become the ultimate abode of humanity”.
  • 4.
  • 5.
  • 6.
  • 7.
  • 8. The ‘Stylized Facts’ of Urban Economics “As countries develop, urban settlements account for a larger share of national income”.
  • 9. The Economics of Cities  New York, Los Angeles, Chicago, Boston, and Philadelphia together constitute the fourth largest economy in the world.  Sao Paulo and Bangkok hold about 10% of the total population but account for about 40% of the GDP.  Per capita income in African cities is 65% higher than the national average.
  • 10. The Economics of Cities 1. Frankfurt . . . . . . . . . . . 68,947 2. Karlsruhe . . . . . . . . . . . 64,903 3. Paris . . . . . . . . . . . . . 62,220 4. Munich . . . . . . . . . . . . 56,813 5. Dusseldorf . . . . . . . . . . 50,048 (In million dollars)
  • 11. The Economics of Cities Cities are the “super markets for employment, incubator of technology, suppliers of social services and shelter, portals to the rest of the world, processors of agriculture produce, adders of manufactured value, places to make money through trade, industry, finance, real state”
  • 12. Urban Loads  Congestion  pollution  Crime
  • 13. The ‘Stylized Facts’ of Urban Economics Globalization of economic activity has put cites in a new set of relation vis-à-vis capital.
  • 14. City Competition - the New Reality City branding has become a ‘must do’ for cities. In today’s globalised, networked world, every place has to compete with every other place for its share of the world’s consumers, tourists, businesses, investment, capital, respect and attention. Cities are increasingly the focus of this international competition.
  • 15. City Marketing  Zurich is the world’s best city to live in (Mercer Consulting 2006).  London, New York, Oslo, Tokyo and Zurich are the most expensive cities, while Swiss cities house the highest earners in the world (UBS 2006).  London and Paris are the best cities to locate businesses (European Cities Monitor 2005).
  • 16. "Basel beats differently." 1. Basel is a city of research and development, of science and education. 2. Basel is one of Europe's leading centres of the fine arts. 3. The people of Basel cultivate the art of savoir vivre and love to share the high quality of life with their guests. 4. Basel is a place where innovative, high-quality ideas, products, and services are exchanged and traded.
  • 17. Quality of life  With a thriving economy, a stable political system, Austria's beauty and cultural diversity all contribute to a high-quality of lifestyle for locals and tourists alike.  Austria's capital Vienna ranks as one of the most attractive cities world wide. The feeling of well-being enjoyed by locals and tourists has been repeatedly confirmed by leading international studies and city rankings.  Vienna - 4th place in a world wide quality of life survey
  • 18. Visit Vancouver Recognition & Awards 2004: Vancouver voted Top City in Americas by Conde Nast Traveler. 2003: Mercer Human Resource Consulting rates Vancouver as top city in North America for quality of life. 2002: Vancouver ties with Melbourne as the Top City to live within the Economist Intelligence Unit survey.
  • 19.
  • 20. Our 12th annual Hot Cities report will give you the lowdown on the nation’s most dynamic cities for entrepreneurs.  Whether you’re looking to expand, relocate or simply stay put, our quick guide to the top 10
  • 21. Developing World Cities in Global Competition  Shanghai most favorite destination for European investors.  Beijing, Mumbai and Mexico City follow Suite.
  • 22.
  • 23. City Development Index CDI = (Infrastructure index + Waste index + Education index + Health index + City product index) /5
  • 24.  Infrastructure = 25 x Water connections + 25 x Sewerage + 25 x Electricity + 25 x Telephone  Waste = Wastewater treated x 50 + Formal solid waste disposal x 50  Health = (Life expectancy – 25) x 50/60 + (32 – Child mortality) x 50/31.92  Education = Literacy x 25 + Combined enrolment x 25  Product = (log City product -4.61) x 100/5.99
  • 25. CDI Value St oc kh 100 120 20 40 60 80 0 ol m M ad ri d Pr ag ue Sa nt Bu D o en oh A os a nd re A / ir S es ao Pa ul Bu o la Po wa rt yo of Sp ai n H ar ar Ja e ka rt a Ce D bu am as cu s La ho re Co lo Ca m bo sa bl an ca A su City Developemnt Index nc io Ba n gh da d Ga Ch za i tt ag on Ki g ns ha sa CDI
  • 26. Ranking of World Cities by GUO City Development Index 120 100 80 CDI Value 60 40 20 0 0 20 40 60 80 100 120 140 160 CDI Rank CDI
  • 27. H on g 100 120 0 20 40 60 80 K on g S eo ul M el bo un e B an ga lo r e H an K oi at hm an du C eb u D ha M ka an da lu yo ng M ed an C ol o m Connectivity bo La ho re Connectivity Index S uv a B is hk P e k hn om P en U h la a nb a at ar N ag a H oh h ot
  • 28. 0 100 10 20 30 40 50 60 70 80 90 D ha ka S e ou B l a ng a lo re La h M o re a nd a lu yo n H g on g K o ng H oh h ot C ol o m bo M e da n H an P o h i no m Congestion P e n K h a th m an d U u la a Congestion Index nb a a ta r C eb u B is hk e k N ag a S u va M e lb o un e
  • 29.  Jamal, Khan, Toor and Amir (2003) rank districts of Pakistan on the basis of deprivation indices. These indices are based on education, housing quality and congestion, residential housing services and employment sectors and are constructed from Population and Housing Census data of 1998.
  • 30.  Pasha et al (1998) develop a district ranking system for Pakistan based on economic and social development. The social development indicator includes education, health and water supply. Whereas, the economic development indicators includes income and wealth, agriculture, housing conditions, transport and labor.
  • 31.  Hussain (2003) has also calculated Human Development Index at the district level for Pakistan, following the same methodology as used in the construction of cross country HDI.
  • 32. Measuring Pakistani Cities  At present, there is no country-wide system for measuring cities and city life in Pakistan.  The only efforts at measuring cities – UN-Habitat’s Global Urban Indicators Program and ADB Cities Data Book - have limited scope.
  • 33. Measuring Pakistani Cities  They are restricted to a maximum of two cities  These exercises are not carried out on yearly basis  They have their own agenda.  Other efforts at measuring performance are district based
  • 34. Measuring Pakistani Cities  Make city as the relevant unit of analysis  Develop a city ranking system for Pakistan  Extend GUIP to major cities of Pakistan
  • 35. Dimensions Demographic City Population Health and Person per Hospital Bed/Doctor/Nurse Education School Enrollment Rates Tertiary Graduates School Children per Classroom Urban Productivity City Product Employment by Industry Unemployment Household Expenditure Housing House Price to Income Ratio House Cost to Income Ratio
  • 36. Dimensions Infrastructure Water Connections Investment/ expenditure per capita Electricity Connections Investment/ expenditure per capita Solid Waste Collection Household Number Investment/ Generation per capita Solid Waste expenditure Urban Environment Sewage Disposal Waste Water treated Energy Usage Noise Complaint Pollution
  • 37. Dimensions Urban Transport Travel Time Expenditure on Roads Road Congestion Automobile Ownership Culture News apers/Media Cultural Events/Attendance Museums/Attendance Public Safety Crimes New Technology Telephone Connections Internet Connections
  • 38. Dimensions Urban Land Vacant Government Land Vacant Land with Planning Permission Public Open Space Prime Commercial Land Price Prime Rental Cost Urban Governance Functions of Local government Annual Plans Voters Participation

Editor's Notes

  1. Mean=64.3, median=68.1, min=21.7, max=98