Invisiblising cities: the obsession with national statistics and international comparisons
In the latest in our series of blogs and interviews about the transition to a predominantly urban world, David Satterthwaite discusses the vast gaps in city data, and explains why planning, governing and servicing cities calls for data that is broken down into city and sub-city level.
How do you plan, manage and govern a city with no data about most enterprises, most workers, most housing and, often, most land transactions and land use changes?
How do you run an effective healthcare system with no local data on the most serious illnesses, injuries and causes of premature deaths in homes, streets and workplaces?
This blog looks at the massive gaps in basic data for most cities (and city districts) in low- and middle-income countries, and examines why this is the case.
Data on what we see, hear and can measure
The informal population: so much of what goes on in cities in the global South is invisible or only partially visible – and unrecorded.
In most cities, there is little or no data on populations living in informal settlements even though these settlements house 30-80% of these cities’ populations. No maps, no street names, no registered addresses. And no data on provision of basic services.
Informal enterprises: there is equally little data in most cities about informal enterprises – what they are, what they do. And more broadly, there is lack of data on the informal economy, despite its importance for the city economy and even greater importance as the source of livelihoods for most of the low-income population.
The economy of Dharavi, a long-established large informal settlement in Mumbai, is worth an estimated US$500 million a year. And many of its businesses supply or service formal enterprises.
In high income nations, employers are legally obliged to report on employee deaths, serious injuries or illnesses and extended absence from work. But such reporting systems are less common or complete in the global South, not least because these do not include informal enterprises.
A city’s visible aspects: what about the very visible aspects in cities that can be seen, heard and also recorded – counted or measured? You can count people, buildings, businesses, motor vehicles… and set up systems to record them. But so many people, buildings and enterprises still go uncounted.
Home and workplace risks: For some home and workplace risks, data can be collected using specialist equipment – for instance air pollution and temperature monitors. But no monitors exist to automatically record the incidence of diarrheal diseases or traffic accidents.
They can be recorded (and monitored) through hospital or health care records, but this requires reporting systems and these are rarely in place – or if they are, coverage is very partial.
Factors influencing growth: we know very little about many (less visible or invisible) factors that cause or influence the growth of cities. These include capital investment and income flows to and from a city, including remittances.
For each city, these include informal and formal labour markets, land prices and availabilities (especially in informal land markets) and the quality and reach of public services.
“Censuses are a public good”
It is part of a government’s function to collect data needed for planning, managing, servicing and governing city populations and enterprises and tracking progress.
Censuses provide valuable data on a range of indicators relevant to health, wellbeing, and housing and living conditions. They are also unique in that they cover (or should cover) every individual and household. This means they can provide data disaggregated down to each city – and far beyond this to each street and to the smallest political/administrative divisions.
This makes censuses valuable for all levels of government and for citizens and civil society groups, enabling them to see, for instance, the quality of housing or of provision for water and sanitation in each street or ward/district.
Censuses are particularly valuable as they identify with precision where the worst quality housing or the worst provision for water and sanitation are located. At a meeting I attended in Sao Paulo in 2016 entitled 'Meeting towards the Habitat III conference', a Brazilian statistician (whose name I sadly do not remember) commented that “censuses are a public good". In Brazil, census data is available to local governments and the public, and for each locality.
But unlike in Brazil, many census authorities do not make the disaggregated data available to the public or even to local government. They see themselves as serving national, not local, governments.
Censuses are also complex and expensive – which is why they are generally done every ten years. There are also many nations where censuses are not carried out regularly; some have not had a census for 20 or more years.
For some nations there are worries about accuracy, such as state governments inflating their population figures to get a larger share of funding from national government. There are worries of completeness – for instance the failure to cover most informal settlements because the interviewers are frightened to go there and/or because there are no maps to guide them.
Household surveys are much cheaper than censuses as they draw data from far fewer households. Demographic and Health Surveys (DHS) provide great detail on health, population and nutrition – Nigeria’s 2018 survey, for example, runs to over 700 pages.
Over 90 countries have implemented Demographic and Health Surveys, and many of them carry them out every few years so key trends can be assessed. But their data are not available for cities. Nigeria’s 2018 DHS has no mention of key Nigerian cities.
The samples of the surveys that comprise a DHS are too small to provide statistically valid data on individual cities. They provide findings for urban and rural populations and sometimes by state – but this is no use to city governments.
In many cities, vital registration systems are not functioning properly or have limited coverage – depriving city governments of valuable data on premature deaths and their causes and locations.
These systems have long been a key source of information needed for public health. Where they do function, they help highlight the very high infant, child and maternal mortality rates in many cities, especially in informal settlements.
A further question: how many hospitals and healthcare centres are keeping and using records that should form a key part of city and national data on health?
City governments need city data
Much of the data that governments and international agencies generate and use come from surveys conducted at national level. The same national approach applies for water and sanitation data used to monitor progress on the Sustainable Development Goals (SDGs).
Monitoring progress on the SDGs has become increasingly detailed: there are 230 individual indicators to monitor the 17 goals. But the data is massed together – coverage is reported for national, rural and urban populations. Data to measure progress on the Paris Agreement on climate change also operates at this national level.
Implementing international UN frameworks in cities largely falls to city governments – but to put these frameworks into practice, cities need disaggregated data. And to fully utilise such data they need more power, capacity, funding and accountability. Getting this recognised remains a challenge; we still see instances where local governments are classified as ‘other stakeholders’.
Time and again, city governments have shown their potential to innovate, and their agility to adapt to rapid change. But to make robust planning and policy decisions that will deliver the ambition of progressive international agendas, they need data with the sophistication to match.
In response to the limitations and deficiencies in official data, city governments and community organisations are turning to other sources including community-led mapping of informal settlements.
The next blog in this series will look at how city governments and slum/shack dweller federations are drawing on alternative data sources and filling gaps in official data.