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B2G DATA WORKSHOP. Presenter: Shirley Robinson Cities Support Programme / Economies of Regions Learning Network National Treasury 7 March 2017. The nine largest city economies are overwhelmingly dominant in the SA economy.
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B2G DATA WORKSHOP Presenter: Shirley Robinson Cities Support Programme/ Economies of Regions Learning Network National Treasury 7 March 2017
The nine largest city economies are overwhelmingly dominant in the SA economy City economic and employment growth is absolutely critical for national economic and employment growth
Why Cities Matter? • World Bank World Development Report 2009 – Shaping Economic Geography • Spatial transformation in density, distance and division are essential to economic growth and development • Cities are critical, growth is seldom balanced, and efforts to spread out growth will jeopardize progress • Urban agglomerations or concentrations: • Spur logistical efficiencies in transport and information sharing • Improve access to skills and labour • Enable sharing of knowledge and knowledge spillovers • Boost innovation in response to changing technologies or customer demand • Deepen social and economic mobility – city liveability or quality of life
Why Cities Matter? • But Cities also: • Contribute to higher costs including property rents and labour costs • Higher levels of congestion and undue pressure on infrastructure – housing, water & electricity • Increased poverty and crime • Asuccessful & inclusive city.. • … is one that builds common spaces and flows that enable people to develop pathways out of poverty through access to social and economic opportunities • Collective action is needed to get the public space that allows urban mobility and interconnection • Once development takes place, it is very difficult to reconfigure urban space • How are SA Cities doing?
Accelerating City Transformation for Inclusion, Growth and Sustainability City Spatial Development Planning aims to manage growth and land use changes to ensure that urban growth happens in a sustainable, integrated and equitable manner Cities need to address a fragmented spatial pattern that marginalises high-density, low-skilled, poor people from employment and economic opportunities in the economic nodes …and facilitate economic growth and urbanisation trends – demand for housing – low and middle income Building inclusive, integrated and economically vibrant cities.. .. All while managing growth between urban development demands and environmental protection
Cape Town: Spatial distribution of employment & residential densities Is this picture telling an accurate story ? – is the evidence and data in this picture correct?
Where are we headed? Singapore then.. and now… • Anthropocene… • current geological age where human activity has been the dominant influence on climate and environment • Algorithm… • Altruism…
Digging Deeper: Technical Working Group on Data • We live in a world of large scale and rapid change, increasing technical and social complexity, and significantly more competition … for resources…. For jobs… for opportunities… • Cities keen to undertake accurate evidence-based spatial economic development planning and investments (think transport (My Citi), water, sewerage, electricity…) • Equally, academics & policy think tanks want to undertake firm-level research to understand city economic competitiveness and productivity • BUT – do we have city-level economic data on firms and jobs at the sub-metro (nodal level) – e.g. Cape Town CBD, Belville, PaardenEiland?? • 2014 – conversations start on Digging Deeper – Collaboration between Cities and National Government on enhancing access to city-level administrative & survey economic data
Data on Firms and Jobs, People and Places • Data on Firms and Jobs • .. On People and Places.. WHY? • Jobs are a driver of household decision on where to live (close to jobs) • Where jobs are often affects land values • Knowing where and why firms locate improves insights on types of policies that can support agglomeration economies (transport, amenities, basic services etc) BUT • For SA cities, the spatial distribution of employment data biased towards head office location – all WW jobs in SA recorded in CT CBD • So if we don’t know where the jobs are, how can Cities plan and invest in key infrastructure and basic services??
Using administrative data + survey data • Internationally shift is towards using anonymised administrative data to complement survey data for statistical analysis • Why? • Size & complexity of economy • Cost • Accuracy & credibility • But.. Administrative data not collected for administrative not statistical purposes so assumptions and modelling necessary for statistical analysis. • A shift to the use of administrative data sources takes time.. Requires partnerships.. And the systematic building of capability infrastructure & systems.
Using administrative data + survey data • Interestingly, the first UN World Data Forum, hosted by Stats SA in Cape Town in January 2017 highlighted the shift towards the use of (anonymised) administrative data sources combined with big data (particularly mobile phone, bank accounts, access to internet/broadband) for statistics due to need to: • Improve the integrity & efficiency of statistical production process; • Reduce costs in statistical collection; • Reduce burden placed on respondents to statistical surveys (particularly where respondents are businesses as an element to reducing the costs of doing business) • (See http://undataforum.org/WorldDataForum/sessions/creating-core-registers-for-statistical-production-quality-issues-and-practical-examples/).
Administrative data for City Economic Analysis • Main priority is to access data on where firms and jobs locate • Through … • Accessing anonymous tax (PAYE) data from SARS to replace the data once available through RSC levy collection. • Exploring how the UIF data and other employment information collected by the Department of Labourcan be made available at a disaggregated metropolitan or sub-metropolitan scale. • Working with Cities on anonymized geo-coded Building Plan and Valuation data • Would partnering with private sector on Big Data be possible? • Mobile phone data – anonymized night and day cell location • Access to banking services, internet? • For private sector, win in collaboration is to understand changing City space economies and market potential
Using anonymised tax data for City spatial economic analysis Spatial distribution of jobs (tax certificates Spatial distribution of CIPC registered head offices • Plants are concentrated in cities, but even this sample of plants (from only 300,000 tax certificates who had a work address filled in, restricted to those which matched with the postal codes from CIPC) already show a different picture, less concentrated in Gauteng and Cape Town where most head offices are located
AfriGIS movement data analysis People that are in Pinetown during the evening (OffPeak), but elsewhere during the day.