Urbanization in Tanzania Phase 1: Data assembly and preliminary analysis

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Urbanization in TanzaniaPhase 1 Data assembly
and preliminary analysis

• Dr Hugh Wenban-Smith

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Workshop objectives

• Present IGC work on urbanisation in Tanzania
• Invite your views on directions for future work
• Seek collaboration with Tanzanian researchers
• Foster development of a community of urban
  researchers here
• Ultimately, help to inform policies for growth
  linked to urbanisation

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Why research urbanisation?

• Popn of Dar up from 1/4m in 1965 to 4.4m in 2012
  nearly 20 times as big
• Other towns in Tanzania
• Arusha xx times
• Mbeya xx times
• Mwanza xx times
• Engine of growth? (World Bank, 2009)
• Big challenge to manage urban growth on this
  scale need to understand whats driving
  urbanisation

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Census data A great resource

• Tanzania censuses 1967, 1978, 1988, 2002 and
  2012
• Provide primary data of good quality (not Poor
  Numbers)
• Congratulations to NBS on a difficult job well
  done

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Urbanisation Our approach

• Not enough to look just at growth of towns and
  cities
• Urban areas are embedded in the wider economy and
  form an urban system
• Need to look at dynamics e.g. effect of
  population growth, conditions in rural areas,
  rural-urban migration and relations between large
  and small towns
• Regional differences help to identify causes

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Headline findings

• Total mainland popn up from 12m to 43.6m (3.6
  times)
• Mainland urban popn up from 0.7m to 12.7m (18
  times)
• Mainland rural popn up from 11.2m to 31m (3
  times) - i.e. Big increase in pressure on land
  and other natural resources despite rapid
  urbanisation

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Regional analysis

• Going down to regional level reveals interesting
  differences
• Analytical tools
• Propensity for regional in-migration
• Propensity for rural out-migration
• Propensity for urban in-migration

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Propensity for regional in-migration

• P(rim)
• Method
• 1. Take base year regional population
• 2. Add expected growth using national rate
• 3. Subtract actual growth
• 4. Divide by expected population
• 5. Reverse sign (e.g. instead of - ), convert
  to percentage (x100)

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P(rim) Two examples

• Dar region 1978-2012
• 1. 843,090
• 2. 1,681,124
• 3. 3,521,451
• 4. /2,524,214 - 0.729
• P(rim) 72.9

• Lindi region 1978-2012
• 1. 527,624
• 2. 721,312
• 3. - 337028
• 4. /1,248,936 0.308
• P(rim) -30.8

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Region P(rim) 1978-2012
Dar es Salaam (DAR) 72.9
Rukwa/Katavi (RUK/KAT) 22.2
Arusha/Manyara (ARU/MAY) 20.6
Kigoma (KIG) 19.5
Kagera/Geita (KAG/GEI) 9.0
Tabora (TAB) 8.8
Mwanza/Geita/Simiyu (MWA/GEI/SIM) 6.0
Mbeya (MBE) -2.3
Shinyanga/Geita/Simiyu (SHI/GEI/SIM) -3.6
Mara (MAR) -4.9
Ruvuma (RUV) -5.7
Morogoro (MOR) -7.4
Singida (SIN) -10.3
Pwani (PWA) -12.9
Dodoma (DOD) -13.2
Tanga (TAN) -17.9
Kilimanjaro (KIL) -23.6
Iringa/Njombe (IRI/NJO) -27.1
Mtwara (MTW) -29.2
Lindi (LIN) -30.8
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P(rom) and P(uim)

• Method similar to P(rim)
• P(rom) Percentage of expected rural popn that
  migrates to own urban or other region
• P(uim) Urban in-migrants as a percentage of
  expected urban popn

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P(rom) and P(uim)
In P(rim) order (Dar on left Lindi on right)
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More findings

• Regions with high out-migration also show high
  rural out-migration
• Regions with high urban in-migration do not
  follow this pattern
• Issues for future research
• How do regions with high rural out-migration
  differ from those with low?
• How do regions with high urban in-migration
  differ from those with low?
• Does this change over time? Why?

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Migration vs In-city growth

• As urban popns grow, so does natural popn growth
• Is natural growth now more important than
  rural-urban migration? (Cf. Zambia)
• See Table 6 in working paper in-migration still
  explains more than half urban growth but not for
  some regions (TAB, MAR, SIN, MTW and Lin)

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Some data problems

• Definition of urban appears to vary between
  censuses
• When urban boundary expands, some of population
  increase not due to migration
• How to address these problems?
• Investigate feasibility of a density based
  measure
• Check boundary changes of regional capitals

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Future Research (1)

• Phase 1 work has assembled data and done some
  preliminary analysis
• Much more work needed if we are to understand the
  urbanisation process so as to identify policies
  needed to promote future growth, for rural as
  well as urban areas

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Future Research (2)

• Phase 2 of the IGC project will investigate
• How high rural out-migration regions differ from
  others
• How high urban in-migration regions differ from
  others
• How urbanisation in Tanzania relates to episodes
  in post-Independence economic history (e.g.
  villagisation SAP policies Mining boom)

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Future Research (3)

• We realise that our project is only a start, at
  least providing usable data for other projects
• Plenty of room for other researchers, e.g. What
  are implications for urban governance, urban
  finance and urban infrastructure?
• Also what are implications for rural development
  and rural-urban interaction?
• Hope we have lighted a spark of interest
• Look forward to a bushfire of comments, questions
  and suggestions