Transcript Hugh Wenban-Smith - International Growth Centre

Urbanization in Tanzania
Phase 1: Data assembly
and preliminary analysis
Dr Hugh Wenban-Smith
Workshop objectives
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•
•
•
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
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 what’s driving urbanisation
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
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
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
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
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)
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
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–
–
–
–
1. 527,624
2. + 721,312
3. - 337028
4. /1,248,936 = 0.308
P(rim) = -30.8
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
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
P(rom) and P(uim)
In P(rim) order (Dar on left; Lindi on right):
160.0
140.0
120.0
100.0
80.0
PROM
PUIM
60.0
40.0
20.0
0.0
1
2
3
4
5
6
7
8
9
10
11
-20.0
Rank
12
13
14
15
16
17
18
19
20
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?
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)
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
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
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)
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