Cities | Infrastructure for Growth

Posted | Updated by Insights team:
Dr. Evangelo Damigos; PhD | Head of Digital Futures Research Desk
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Publication | Update: Sep 2020

Is growth the engine of cities?

Cities may generate 80% of global GDP currently, but while they have historically pulled in resources as they grew via industrialization, this phase of urbanization is being driven as much by populations being pushed into cities by rural poverty and depravation. This switch to 'growth being the engine of cities' has profound implications: it is the people that need the city, not the city that needs the people.

Some 4 billion people, representing 54% of the global population currently live in cities; the UN expects this to grow by 1 billion by 2030, and 2 billion by 2050, by which time 66% of us will be living in cities. The challenge though is even greater than this. Of our 2 billion new urbanites, 1.2 billion will come from Asia, and 800 million from Africa. These cities already have chronically limited revenue bases and offer meager services even to those already living there.



How money is invested, on what, and how efficiently makes a massive difference.

According to Citi GPS Report “Sustainable Cities: Beacons of light against the shadows of unplanned urbanization,” cities which are able to invest efficiently in the right infrastructure can benefit from the fiscal multiplier effect, which can lead to greater economic activity, greater employment and potentially lower social costs, as well as greater usage fees and tax receipts, all of which free up more capital for investment. 

“The Infrastructure for Growth” Citi GPS report, Identifies the key factors for effective investment were as follows:

1. Bottlenecks and Output Gaps: Identifying the correct assets to build, and in what order, is critical; the right asset which reduces costs and boosts output (e.g. a bridge which dramatically reduces commuting and transport times and costs, and opens up an area for industrial development and hence job creation) will have a much larger multiplier effect, rather than the famed 'white elephant' projects or bridges to nowhere.

2. Financial Efficiency: Infrastructure investments are notorious for overspend and delays, and clearly if a project costs too much it can more than negate any potential benefits. The correct rigor and project management are critical to achieving a large positive multiplier effect. All too often the announcement of huge infrastructure investment program is associated with a 'bottomless pit of money' mentality on the parts of local governments gold-plating assets, while contractors see the associated gold mine and bid in accordingly.

Successful investment can however have negative social consequences — it can lead to increasing house prices, which can lead to greater levels of inequality and can see less financially mobile individuals pushed out to other cities, which may be cheaper as they are in a negative decline spiral. Hence the overall effect on a national economy needs to be considered — a successful city does not necessarily improve the overall national effects by the same amount as it does locally, and it may reduce overall GDP growth and wealth creation.

Social Infrastructure

Social infrastructure is defined as long-term physical assets in social sectors such as education, health, long-term care, and housing, etc. which enable goods and services to be provided.

 The Citi GPS report, Public Wealth in Cities states that a successful city not only invests in economic assets but also in social and human assets as these have a crucial impact on the finances of cities and well-being of its citizens.

Social assets provide important services for people’s health, environment, and happiness, thus minimizing social afflictions that could have a strain on a city’s budget. Human assets on the other hand (which include the skills and/or knowledge attained by citizens) are important for individuals to achieve economic independence and for government/cities ultimately to increase tax revenue. 

Sustainable Housing  

Housing accounts for more than 70% of land use in most cities and determines urban forms and densities. Housing shortages in many cities represent a major challenge. In South Asia, housing shortfalls are particularly acute amounting to a staggering 38 million dwellings. The UN estimates that one billion new homes are needed worldwide by 2025, costing an estimated 0 billion per year or 9-11 trillion overall. On top of this, there are shortfalls in the quality of housing. Whilst housing for the middle and upper- class citizens in many cities maybe over provided, the poor are generally under-housed.  

Quality of housing is also a huge challenge in many cities. According to the UN one in eight people live in slums today — around 1 billion people — and the largest proportion of this group (over 880 million) live in developing regions. Over the next two decades the urban population in the world’s poorest regions including South Asia and Sub-Saharan Africa are expected to double. Unless investment and adequate measures are put into place, the population living in slums in these areas could increase even further. 

To create efficient, affordable, and inclusive neighbourhoods, housing in cities will have to be rethought.

Housing becomes unaffordable in major cities. Changing acquisition and rental patterns as well as short supply of new homes hit low to moderate income households the hardest.

Population ageing will need adaptations. Especially in spatial infrastructure, cities need to be more accessible and inclusive to all ages.

This should include intergenerational living projects, mobility campaigns and better designs for all age groups.

Almost half of all buildings in Europe are over 70 years old. To increase sustainability and high quality of life, it is necessary to upgrade or retrofit buildings. Abandoned spaces have to be converted to useful purposes.


Sustainable housing is not only about economic facets of housing but includes other indicators such as social, cultural, and environmental. According to the UN, sustainable housing are those that are built and managed as healthy, durable, safe and secure; affordable; using low energy and affordable building materials; resilient to potential natural disasters; connected to safe and affordable water, energy, and sanitation; use resources efficiently; well connected to jobs and; properly integrated into social, cultural, and economic fabric of society. It is rather difficult to find cities that have managed to capture the whole definition of sustainable housing.

Sustainable green living usually comes at a price and is rarely offered as affordable; on the other hand, some cities have developed affordable housing, but these are in areas which are cut off from employment, and from the social, cultural, and economic fabric of the city.

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Objectives and Study Scope

This study has assimilated knowledge and insight from business and subject-matter experts, and from a broad spectrum of market initiatives. Building on this research, the objectives of this market research report is to provide actionable intelligence on opportunities alongside the market size of various segments, as well as fact-based information on key factors influencing the market- growth drivers, industry-specific challenges and other critical issues in terms of detailed analysis and impact.

The report in its entirety provides a comprehensive overview of the current global condition, as well as notable opportunities and challenges. The analysis reflects market size, latest trends, growth drivers, threats, opportunities, as well as key market segments. The study addresses market dynamics in several geographic segments along with market analysis for the current market environment and future scenario over the forecast period. The report also segments the market into various categories based on the product, end user, application, type, and region.
The report also studies various growth drivers and restraints impacting the  market, plus a comprehensive market and vendor landscape in addition to a SWOT analysis of the key players.  This analysis also examines the competitive landscape within each market. Market factors are assessed by examining barriers to entry and market opportunities. Strategies adopted by key players including recent developments, new product launches, merger and acquisitions, and other insightful updates are provided.

Research Process & Methodology


We leverage extensive primary research, our contact database, knowledge of companies and industry relationships, patent and academic journal searches, and Institutes and University associate links to frame a strong visibility in the markets and technologies we cover.

We draw on available data sources and methods to profile developments. We use computerised data mining methods and analytical techniques, including cluster and regression modelling, to identify patterns from publicly available online information on enterprise web sites.
Historical, qualitative and quantitative information is obtained principally from confidential and proprietary sources, professional network, annual reports, investor relationship presentations, and expert interviews, about key factors, such as recent trends in industry performance and identify factors underlying those trends - drivers, restraints, opportunities, and challenges influencing the growth of the market, for both, the supply and demand sides.
In addition to our own desk research, various secondary sources, such as Hoovers, Dun & Bradstreet, Bloomberg BusinessWeek, Statista, are referred to identify key players in the industry, supply chain and market size, percentage shares, splits, and breakdowns into segments and subsegments with respect to individual growth trends, prospects, and contribution to the total market.

Research Portfolio Sources:

  • BBC Monitoring

  • BMI Research: Company Reports, Industry Reports, Special Reports, Industry Forecast Scenario

  • CIMB: Company Reports, Daily Market News, Economic Reports, Industry Reports, Strategy Reports, and Yearbooks

  • Dun & Bradstreet: Country Reports, Country Riskline Reports, Economic Indicators 5yr Forecast, and Industry Reports

  • EMIS: EMIS Insight and EMIS Dealwatch

  • Enerdata: Energy Data Set, Energy Market Report, Energy Prices, LNG Trade Data and World Refineries Data

  • Euromoney: China Law and Practice, Emerging Markets, International Tax Review, Latin Finance, Managing Intellectual Property, Petroleum Economist, Project Finance, and Euromoney Magazine

  • Euromonitor International: Industry Capsules, Local Company Profiles, Sector Capsules

  • Fitch Ratings: Criteria Reports, Outlook Report, Presale Report, Press Releases, Special Reports, Transition Default Study Report

  • FocusEconomics: Consensus Forecast Country Reports

  • Ken Research: Industry Reports, Regional Industry Reports and Global Industry Reports

  • MarketLine: Company Profiles and Industry Profiles

  • OECD: Economic Outlook, Economic Surveys, Energy Prices and Taxes, Main Economic Indicators, Main Science and Technology Indicators, National Accounts, Quarterly International Trade Statistics

  • Oxford Economics: Global Industry Forecasts, Country Economic Forecasts, Industry Forecast Data, and Monthly Industry Briefings

  • Progressive Digital Media: Industry Snapshots, News, Company Profiles, Energy Business Review

  • Project Syndicate: News Commentary

  • Technavio: Global Market Assessment Reports, Regional Market Assessment Reports, and Market Assessment Country Reports

  • The Economist Intelligence Unit: Country Summaries, Industry Briefings, Industry Reports and Industry Statistics

Global Business Reviews, Research Papers, Commentary & Strategy Reports

  • World Bank

  • World Trade Organization

  • The Financial Times

  • The Wall Street Journal

  • The Wall Street Transcript

  • Bloomberg

  • Standard & Poor’s Industry Surveys

  • Thomson Research

  • Thomson Street Events

  • Reuter 3000 Xtra

  • OneSource Business

  • Hoover’s

  • MGI

  • LSE

  • MIT

  • ERA

  • BBVA

  • IDC

  • IdExec

  • Moody’s

  • Factiva

  • Forrester Research

  • Computer Economics

  • Voice and Data

  • SIA / SSIR

  • Kiplinger Forecasts

  • Dialog PRO

  • LexisNexis

  • ISI Emerging Markets

  • McKinsey

  • Deloitte

  • Oliver Wyman

  • Faulkner Information Services

  • Accenture

  • Ipsos

  • Mintel

  • Statista

  • Bureau van Dijk’s Amadeus

  • EY

  • PwC

  • Berg Insight

  • ABI research

  • Pyramid Research

  • Gartner Group

  • Juniper Research

  • MarketsandMarkets

  • GSA

  • Frost and Sullivan Analysis

  • McKinsey Global Institute

  • European Mobile and Mobility Alliance

  • Open Europe

M&A and Risk Management | Regulation

  • Thomson Mergers & Acquisitions

  • MergerStat

  • Profound

  • DDAR

  • ISS Corporate Governance

  • BoardEx

  • Board Analyst

  • Securities Mosaic

  • Varonis

  • International Tax and Business Guides

  • CoreCompensation

  • CCH Research Network

Forecast methodology

The future outlook “forecast” is based on a set of statistical methods such as regression analysis, industry specific drivers as well as analyst evaluations, as well as analysis of the trends that influence economic outcomes and business decision making.
The Global Economic Model is covering the political environment, the macroeconomic environment, market opportunities, policy towards free enterprise and competition, policy towards foreign investment, foreign trade and exchange controls, taxes, financing, the labour market and infrastructure. We aim update our market forecast to include the latest market developments and trends.

Forecasts, Data modelling and indicator normalisation

Review of independent forecasts for the main macroeconomic variables by the following organizations provide a holistic overview of the range of alternative opinions:

  • Cambridge Econometrics (CE)

  • The Centre for Economic and Business Research (CEBR)

  • Experian Economics (EE)

  • Oxford Economics (OE)

As a result, the reported forecasts derive from different forecasters and may not represent the view of any one forecaster over the whole of the forecast period. These projections provide an indication of what is, in our view most likely to happen, not what it will definitely happen.

Short- and medium-term forecasts are based on a “demand-side” forecasting framework, under the assumption that supply adjusts to meet demand either directly through changes in output or through the depletion of inventories.
Long-term projections rely on a supply-side framework, in which output is determined by the availability of labour and capital equipment and the growth in productivity.
Long-term growth prospects, are impacted by factors including the workforce capabilities, the openness of the economy to trade, the legal framework, fiscal policy, the degree of government regulation.

Direct contribution to GDP
The method for calculating the direct contribution of an industry to GDP, is to measure its ‘gross value added’ (GVA); that is, to calculate the difference between the industry’s total pre­tax revenue and its total bought­in costs (costs excluding wages and salaries).

Forecasts of GDP growth: GDP = CN+IN+GS+NEX

GDP growth estimates take into account:

  • Consumption, expressed as a function of income, wealth, prices and interest rates;

  • Investment as a function of the return on capital and changes in capacity utilization; Government spending as a function of intervention initiatives and state of the economy;

  • Net exports as a function of global economic conditions.


Market Quantification
All relevant markets are quantified utilizing revenue figures for the forecast period. The Compound Annual Growth Rate (CAGR) within each segment is used to measure growth and to extrapolate data when figures are not publicly available.


Our market segments reflect major categories and subcategories of the global market, followed by an analysis of statistical data covering national spending and international trade relations and patterns. Market values reflect revenues paid by the final customer / end user to vendors and service providers either directly or through distribution channels, excluding VAT. Local currencies are converted to USD using the yearly average exchange rates of local currencies to the USD for the respective year as provided by the IMF World Economic Outlook Database.

Industry Life Cycle Market Phase

Market phase is determined using factors in the Industry Life Cycle model. The adapted market phase definitions are as follows:

  • Nascent: New market need not yet determined; growth begins increasing toward end of cycle

  • Growth: Growth trajectory picks up; high growth rates

  • Mature: Typically fewer firms than growth phase, as dominant solutions continue to capture the majority of market share and market consolidation occurs, displaying lower growth rates that are typically on par with the general economy

  • Decline: Further market consolidation, rapidly declining growth rates


The Global Economic Model
The Global Economic Model brings together macroeconomic and sectoral forecasts for quantifying the key relationships.

The model is a hybrid statistical model that uses macroeconomic variables and inter-industry linkages to forecast sectoral output. The model is used to forecast not just output, but prices, wages, employment and investment. The principal variables driving the industry model are the components of final demand, which directly or indirectly determine the demand facing each industry. However, other macroeconomic assumptions — in particular exchange rates, as well as world commodity prices — also enter into the equation, as well as other industry specific factors that have been or are expected to impact.

  • Vector Auto Regression (VAR) statistical models capturing the linear interdependencies among multiple time series, are best used for short-term forecasting, whereby shocks to demand will generate economic cycles that can be influenced by fiscal and monetary policy.

  • Dynamic-Stochastic Equilibrium (DSE) models replicate the behaviour of the economy by analyzing the interaction of economic variables, whereby output is determined by supply side factors, such as investment, demographics, labour participation and productivity.

  • Dynamic Econometric Error Correction (DEEC) modelling combines VAR and DSE models by estimating the speed at which a dependent variable returns to its equilibrium after a shock, as well as assessing the impact of a company, industry, new technology, regulation, or market change. DEEC modelling is best suited for forecasting.

Forecasts of GDP growth per capita based on these factors can then be combined with demographic projections to give forecasts for overall GDP growth.
Wherever possible, publicly available data from official sources are used for the latest available year. Qualitative indicators are normalised (on the basis of: Normalised x = (x - Min(x)) / (Max(x) - Min(x)) where Min(x) and Max(x) are, the lowest and highest values for any given indicator respectively) and then aggregated across categories to enable an overall comparison. The normalised value is then transformed into a positive number on a scale of 0 to 100. The weighting assigned to each indicator can be changed to reflect different assumptions about their relative importance.


The principal explanatory variable in each industry’s output equation is the Total Demand variable, encompassing exogenous macroeconomic assumptions, consumer spending and investment, and intermediate demand for goods and services by sectors of the economy for use as inputs in the production of their own goods and services.

Elasticity measures the response of one economic variable to a change in another economic variable, whether the good or service is demanded as an input into a final product or whether it is the final product, and provides insight into the proportional impact of different economic actions and policy decisions.
Demand elasticities measure the change in the quantity demanded of a particular good or service as a result of changes to other economic variables, such as its own price, the price of competing or complementary goods and services, income levels, taxes.
Demand elasticities can be influenced by several factors. Each of these factors, along with the specific characteristics of the product, will interact to determine its overall responsiveness of demand to changes in prices and incomes.
The individual characteristics of a good or service will have an impact, but there are also a number of general factors that will typically affect the sensitivity of demand, such as the availability of substitutes, whereby the elasticity is typically higher the greater the number of available substitutes, as consumers can easily switch between different products.
The degree of necessity. Luxury products and habit forming ones, typically have a higher elasticity.
Proportion of the budget consumed by the item. Products that consume a large portion of the consumer’s budget tend to have greater elasticity.
Elasticities tend to be greater over the long run because consumers have more time to adjust their behaviour.
Finally, if the product or service is an input into a final product then the price elasticity will depend on the price elasticity of the final product, its cost share in the production costs, and the availability of substitutes for that good or service.

Prices are also forecast using an input-output framework. Input costs have two components; labour costs are driven by wages, while intermediate costs are computed as an input-output weighted aggregate of input sectors’ prices. Employment is a function of output and real sectoral wages, that are forecast as a function of whole economy growth in wages. Investment is forecast as a function of output and aggregate level business investment.