Urban References

• There is much urbanisation occurring in the Global South, neoliberalism can be blamed for the creation of inequalities

• Slums are not all uniform and have varying characteristics

• The IMF and World Bank have ulterior motives and hidden disadvantages leading to urban poverty and slum growth, SAPs entrench this poverty in their restructuring of economies

• There are many risks associated with living in slums as well as working in the informal sector, these are especially challenging for women and children

Davis, 2006

• IMF structural adjustments as ‘the equivalent of a natural disaster’

• Definitive blame on neoliberal ideology championed by the Bretton Woods organisations

Balogun, 1995

• Problems with simplifications of African urban data viewed as ‘the more urban, the better’ to problems policy relevance

• Policy makers often misrepresent trends as they chose to ignore important bits of data

Potts, 2018

• There has been insufficient attention paid to adaptions occurring over the past 30 years in urban migration patterns, within the Sub-Saharan region Nigeria is particularly important to understand as it holds over 50% of West Africa’s total population

• Since 1952 all census results have been contested, Africapolis data in 2008 showed that nearly half of the smaller urban settlements had a lower urban population than the 1963 census, there are lower levels of urbanisation and slower increase for West Africa as a whole

• This is due to weak urban economies after 1980/90s SAPs, foreign competition and unreliable electricity

Potts, 2012

• There is much scope for improved research and information on urbanisation in Africa, this is important to improve the wellbeing of urban communities

• Many settlements grow without economies moving away from agricultural activities towards higher productivity sectors meaning incomes remain low and quality of life suffers, this reveals a problem in tying economic criteria to urbanisation

• Natural growth and rural-urban migration sees Nigeria’s urban population continue to grow when understanding wider social and environmental implications within demographic data

Turok, 2018

• Using more diverse sources of evidence shows urbanisation is not stalling in Nigeria, rural transformation and natural increases have been overlooked in the past and will contribute to Nigeria’s growing population in the future

• Declining mortality and high fertility see urban populations grow as well as rural ones that then become classed as urban

• Migration also occurs as people move to find employment, education, marriage, escape conflicts or environmental pressures etc.

• Demographic forces should be better considered in understanding Nigeria’s urban transition

Fox et al., 2018

• Definitions of the urban and city boundaries are not set to universal criteria meaning exaggeration is easy and comparisons are inaccurate

• There is a lack of census data particularly in SSA as they are expensive and international donors do not support them, this means UNDP relies on estimates and projections

• Claims of economic and population growth in SSA being unprecedented are not true, urban primary measures also lack real data

• Data limitations also understate the extent of depth of poverty in Asia and Africa as the application of a universal poverty line in inappropriate, there is also little data on housing and living conditions in informal settlements as well as GHG emissions of these urban areas

Satterthwaite, 2010

• Urbanisation is no longer rapid in Africa due to informal urban economies, SAPs and circular migration

• African economies are often trapped in viscous cycles due to the impact of SAPs and liberalised international trade being harmful due to a lack of competitive advantage

• Rates of urbanisation are important indicators of large economic structures and smaller economic livelihoods that provide essential context for policy making; we must move away from generalisations in the region

Potts, 2012

• Processes of urbanisation in SSA are occurring far more slowly than reported, false figures often come to be regarded as fact due to being constantly restates

• Data relies on erratic censuses, the more reliable Africapolis data set showed urbanisation was slowing in the region

• This can be attributed to SAPs, SSA being unable to compete in an era of economic liberalisation and circular migration as migrants enter and then leave towns due to economic insecurity and hardship

• The future for much of SSA is predominantly rural

Potts, 2012

• To make international comparison easier, the UN Statistical Commission endorsed the Degree of Urbanisation approach

• This provides an objective and data-driven approach to classifying urbanisation that can be applied globally

• It is simple, transparent, helps monitor the SDGs, captures agglomeration and is cost-effective

• It will remain comparable over space and time

Dijkstra et al., 2020