- Email: [email protected]
Housing Indicators
Housing Indicators J Flood, AHURI-RMIT, Melbourne, VIC, Australia ª 2012 Elsevier Ltd. All rights reserved.
Glossary Benchmarking A methodology for improving organisational performance in which performance indicators are developed, similar organisations are found that perform better on these indicators, and the good practices which result in outstanding performance are copied. Holistic approach Taking a comprehensive view of some area of social policy, rather than focusing on one or two key issues that are currently in the public eye. Indicator A single item of data which is tied to a policy goal and points the way to ‘improvement’ according to some norm.
What Are Indicators? Indicators are small ‘models’ simplifying a complex sub ject to a few numbers which can be easily grasped and understood by policy-makers and the general public. They are generally highly aggregated and consist of ratios so that they are normalised in some fashion. They should be policy- and stakeholder-driven so that each indicator has one or more associated objectives and is valuable to some significant group of stakeholders. Some of the characteristics of good indicators are that they should be (1) important, (2) measurable, (3) respon sive, (4) simple and robust, (5) timely, (6) stakeholderdriven, (7) action-oriented, and (8) informative. The characteristics of a good indicator ‘system’ are that it should (1) cover the most important issues, (2) represent the interests of all stakeholders, and (3) be structured in a modular, logical manner. A well-structured system will also show linkages – different indicators may reinforce each other to give a picture of the overall effectiveness of a tightly linked system such as a housing market. The major groups of stakeholders who may benefit from the use of indicators are as follows: Governments: Governments most commonly use indica tors as part of prescriptive reporting structures, or integrated within strategy documents or national sec toral reports. Most housing strategy documents are structured around examples of indicators as measures of conditions or of past successes and failures, and improvements resulting from such strategies are
502
Monitoring Reporting to stakeholders on progress towards meeting organisational objectives; often using indicators. Norm A judgement by one or more groups of stakeholders as to what constitutes better outcomes or a better situation in some area of social policy. Different stakeholders may have opposing norms. Performance indicators Indicators adopted by organisations for reporting. Stakeholder Anyone with a vested interest in the performance of an organisation.
generally anticipated in terms of indicators. Spatial indi cators of need may also be used to distribute funding for infrastructure or social housing. Private sector: The private sector (builders, developers, and real estate agents) needs timely information for investment and sales purposes, concerning economic conditions in cities, government performance, supply/ demand imbalances, and the consumption requirements of residents. Consequently, organisations representing private sector interests are often involved in presenting national housing data series, particularly those relating to prices and market conditions. These are also used in the role of advocacy on behalf of their constituents. In some cases, private organisations have become important suppliers of housing data, particularly relating to prices. For example, Fiserv Pty Ltd owns and maintains the S&P/CaseShiller US National Home Price Index, and Standard and Poor’s disseminates the results. Data analysis firms in most countries provide advice and reports on real estate and investment conditions in national and local markets. ‘Nongovernment and community organisations’ are the major users of indicators in their advocacy and lobbying role, in submitting funding proposals, and, particularly, because through indicators they can monitor the performance of governments. In the sustainability area, not-for-profit organisations have taken on the major role in publishing indicators of community well-being including housing indicators (see Relevant Websites). The ‘public, media, and tenants of housing organisa tions’ may be informed by indicators of the efficient and
APPROACHES
Housing Indicators
equitable performance of markets and satisfactory man agement of housing policy and administration.
History of Housing Indicators From the time of Biderman (1966) and Sheldon and Moore (1968), indicators have been nominated as a means by which progress towards a whole system of social goals could be measured. The importance of indicators to housing policy has also been recognised for a long time, and fairly extensive bibliographies of early contributions in the field have been produced (Horowitz, 1980, 1986). Generally, these contributions were related to particular parts of housing policy, such as housing needs or housing and neighbourhood quality (Goedert and Goodman, 1977; Ingels, 1980; US Bureau of the Census, 1976) rather than to the housing sector as a whole. The United Nations took an interest in shelter and its adequacy from the early 1960s (UNSD, 1993; UNSO, 1962), and in the 1970s, the UN Ad Hoc Group of Experts on Social Indicators for Housing and Urban Development (UN, 1973) sustained this concern. From the late 1970s, there was a massive surge in urba nisation in the developing world, resulting in burgeoning slum or shanty populations surrounding most cities. In the late 1980s, there was a resurgence of interest in monitoring and indicators as it became apparent that sectoral, govern ment-based approaches to solving urban and housing problems had not worked in the developing world and that a multisector, enabling strategy was the preferred approach to achieving improvements (World Bank, 1993). This was underlined by a rapidly emerging interest in sustainability issues, which stressed the interrelatedness of all aspects of human activity with the natural environment. The Housing and Urban Indicators Programme Following the International Year of Shelter for the Homeless, in 1988, the Global Shelter Strategy to the Year 2000 was adopted. This strategy was influenced by market liberal economies, and called for a fundamental shift in government policy away from the direct provision of housing towards an enabling legislative and regulatory environment which ‘facilitates, energises, and supports the activities of the private sector’. In 1989, the United Nations Centre for Human Settlements (now UN HABITAT) was requested to provide cost-effective national monitoring of progress towards realising the goals of the Strategy. In October 1990, the World Bank and UNCHS (now UN-HABITAT) jointly initiated the Housing Indicators Programme (HIP), which was funded and supported by USAID. The methodology and the indicators were lar gely the brainchild of Dr Steven Mayo, a principal
503
economist with the World Bank, and Dr Schlomo Angel, an Israeli expert on slums and urban development. The indicators had a macroeconomic emphasis and some of the indicators were novel and original. The pilot pro gramme resulted in a detailed comparison of the housing sectors in major cities in 52 countries, through the collection of about 40 key indicators on a comparable basis (World Bank/UNCHS, 1991). The final results of the original HIP were not published until after the unti mely death of Mayo (Angel, 2004) (see Relevant Websites and the 1996 and 2001 values are available from the author). Subsequently, 10 of these housing indicators were col lected globally as part of a much more comprehensive urban indicators system in the run up to the Habitat II conference in Istanbul in 1996, and again in 2001, along with tenure data. In this case, data for 237 cities were collected which were sufficient for a global sample and analysis (Flood, 1997; UNCHS, 1997; UN-HABITAT, 2002). The long-term aim of the Programme was ambitious: to engage countries in a lasting process which would place housing issues on the national policy agenda. The major original contribution of the Programme was not just an innovative indicators set but a whole new philosophy about the way data should be used in organisations. Indicators were to be developed and prioritised through participative stakeholder consultations (Flood, 1993), they were to be a holistic collection measuring the health of a whole sector, and every indicator should have an objective and strategy associated with it. They were to be maintained within operational departments or specialpurpose monitoring groups and should not reside or be under the control of central statistical agencies. The sta tistics were also to be collected at the city level – which had not previously been attempted. One of the main purposes of the housing indicators was to establish a set of diagnostics for a ‘well-function ing housing market’ and the indicators were chosen with this in mind. For example, various indicators might show a market in which land was being inade quately supplied, resulting in housing shortages and high prices. Deviations from standard benchmarks might show the presence of market-distorting policies like rent control. It cannot be overstated the effect that the Housing Indicators movement had on thinking about housing pol icy in the developing world, although its ‘soft’ marketoriented philosophy was rarely adopted. Some of the indicators, most notably the median house price-to income ratio (see Relevant Websites), have been accepted globally and by many agencies and are still at the centre of considerable controversy. Separate HIPs were conducted in the early 1990s in a number of countries in the Caribbean, Southern Africa, and Eastern Europe (see Hegedus and Tosics, 1993; Ministry of Public
504
Housing Indicators
Construction and National Housing, Zimbabwe, 1990), generally funded by USAID, as part of an attempt to vitalise or revive the housing sectors of those countries. Aftermath In general, the housing indicators were well received. The main criticisms were in keeping with the origins of the system – that they referred largely to the economic part of the economic–social environmental nexus, and had little distributional or environmental content. Data issues and the costs of data verification remained a major obstacle. Flood (1997) concluded that ‘‘The housing indicators have been less well understood than the other (urban) indicators, partly because they represent data that are not commonly collected, and partly because they represent complex concepts or have difficult collection methods’’. To change institutions is a harder task than collecting indicators, and the funds or political will to do this were never really there. Ultimately, the ‘enabling approach’ appealed neither to the growing sustainability movement nor to the economic right. After 15 years of promotion through the Global Urban Observatory movement, the strategic emphasis on a holistic, sectoral approach and on participative development of indicators through stake holder meetings has not been widely adopted, although particular indicators retain a considerable following. The main follow-up to the Habitat Agenda in 1996 was to construct a network of National and Local Urban Observatories who were tasked with collecting key urban and housing indicators and making sure they were applied to policy. This was to be coordinated by the Global Urban Observatory located in Nairobi. This still exists with limited support, and a few local observatories are active (Vancouver, Barcelona, Jeddah, Medina, and Tehran), though none have a housing focus. Within UN HABITAT after 2003, most effort has gone towards col lecting the Millennium Indicators, http://mdgs.un.org/ unsd/mdg, through national statistical bodies rather than collecting key indicators through operational departments. Several of the original supporters of the HIP, most notably the National Association of Realtors and the Canada Mortgage and Housing Corporation, have con tinued to be independently active in the indicators area. The most lasting legacy of the HIP has probably been Indicator H1, the Median House Price to Income Ratio, which has become the primary indicator of the general health and efficiency of housing and land markets (HJCHS, 2009; Wilcox, 2003, and many other sources). Mainstreaming Housing Indicators The emphasis after 1995 was less about maintaining whole systems of housing indicators to measure the health of the sector – which in practice rarely had a champion
agency within national governments – and was more directed towards including indicators of performance within policy documents and as part of government reporting. By the mid-1990s, most annual reports of gov ernment agencies were required to include indicators of performance. However, the laissez-faire 1990s were anti-planning even within a market liberal framework: the role of gov ernment was to be as a regulator rather than a guiding hand. Even monitoring was discontinued in many housing markets, as specialist departments of housing tended to disappear, retaining only a narrow residual role within much larger social security ministries. Much of the effort in collecting and maintaining housing market indicators devolved to the private sector and to sustainability organisations. The world paid the price for this lack of attention to housing markets and for leaving monitoring largely to partisan delivery agencies or lobbying groups in October 2007, when the subprime mortgage crisis preci pitated the largest economic downturn since the Great Depression. Closer monitoring of the health of over stressed housing markets using indicators might have prompted policy action to take the pressure off prices in the worst-affected areas, and to improve accountability and obtain better compliance with prudential norms.
Housing Indicators Housing and Urban Indicators Programme The 10 housing indicators that were collected for Habitat II in 1996 and Istanbul+5 in 2001, for approximately 235 cities around the world on each occasion, were: H1: House price to income ratio – Median house price/ median household income; a primary indicator of the health of housing markets. H2: House rent to income ratio – Median rent/median income of renters. Less than 20% usually means that rent control is in place. H3: Floor area per person – Consumption indicator, highly correlated with GDP or city product. H4: Permanent structures – Per cent structures of perma nent materials; measures the very poorest communities. H5: Unauthorised housing – Per cent stock ‘not in com pliance’ with current regulations; establishes the strength of the informal sector. H6: Land development multiplier – Ratio of median land price of a developed plot at the urban fringe and the median price of raw, undeveloped land; potentially useful, but hard to measure consistently. H7: Infrastructure expenditure – Total annual expendi tures on infrastructure services per person; a community wealth measure.
Housing Indicators
505
Table 1 Mean value of the 10 key housing indicators, by development quintile, Habitat II collection, 1996
H1. Price to income H2. Rent to income (%) H3. Floor area per person (sq m) H4. Permanent dwellings (%) H5. Dwellings in compliance (%) H6. Land development multiplier H7. Infrastructure expenditure per capita ($) H8. Mortgage to credit ratio (%) H9. Dwelling production per 1000 population H10. Housing investment ratio (%)
Very low
Low
Medium
Higher
Developed
6.6 29.1 7.3 46.9 42.5 5.1 16 5.9 4.7 7.7
8.1 28.2 8.0 77.9 52.5 4.9 15 7.1 6.0 12.2
8.8 15.4 13.2 78.8 72.9 3.9 48 12.0 8.5 6.2
8.3 11.7 17.3 91.7 85.5 4.6 136 20.3 5.6 5.1
4.7 18.0 31.4 95.6 96.2 5.3 421 27.1 4.8 3.2
The development level of cities was defined using the City Development Index, which is described in Flood (1997). Source: Flood J (1997) Urban and housing indicators. Urban Studies 34(10): 1665–1667; Tables 13 and 14.
H8: Mortgage to credit ratio – Ratio of mortgage loans to all loans; can only be measured at the national level. Over 25% in developed countries, almost negligible elsewhere. H9: Housing production – Net number of housing units produced per 1000 population. A major measure of boom/bust or vigour of the sector; usually unknown when informal sector is large. H10: Housing investment – Investment in housing/gross city product; measures importance of housing in the local economy and is difficult to calculate.
HA6. Overcrowding – Households with too few bedrooms. HA8. Inadequate housing – Requiring substantial repairs to bring them to accepted standards. HA11. Homelessness – Number of people per thousand who sleep outside dwelling units or in temporary shelter. Other housing indicators and statistics that are frequently cited include:
Table 1 shows the 1996 averages for these indicators over cities of different levels of development. Indicators H3, H4, H5, H7, and H8 increase with the level of develop ment, as they represent increased consumption, improved dwelling quality, and more developed mortgage systems. House prices are highest with respect to income at middle levels of development – probably because formal sector construction standards are enforced before incomes have risen sufficiently to justify them. Rents H2 fall with devel opment until the final quintile. The construction indicators H9 and H10 are correlated with rates of urban household formation.
Supply: Prices, stock turnover, second homes, building approvals and completions, and supply of unsold homes. Affordability: Proportion able to afford median home. Housing gap: Shortfall in supply of affordable housing. Usually rhetorical rather than numeric. Mortgage finance: Mortgage applications, mortgage approvals, interest rates, foreclosures, and equity withdrawal. Rental: Yields and returns, vacancy rates, and rental distributions. Public housing: Length of waiting lists, subsidies, occu pancy, match with client needs, and special needs. Consumer: Report cards, indexes of satisfaction, and security for the public and for public tenants.
Other Indicators
Other Systems
Several other indicators from the extended housing indi cator system are widely used in OECD countries.
There are a number of standard systems or frameworks for classifying and organising indicators, which can be useful in reducing the amorphousness of metrics estab lished through stakeholder consultations. For environmental indicators, these include the Extended Urban Metabolism system for urban sustainability (Newton et al., 1998), and for organisational performance indicators, outcome-based management (Hatry, 2007). By and large, these classifications do not work very well for housing indicators, since many of these are prices and
HA1. Mortgage affordability – Proportion of households who are eligible for and can afford the maximum loan on a median-priced formal sector house. HA2. Excessive housing expenditure – Proportion of households in the bottom 40% of incomes who are spending more than 30% of their incomes on housing; known as ‘core housing need’ in Canada and ‘housing stress’ in Australia.
506
Housing Indicators
macroeconomic measures which can adopt different roles depending on the context. Statistical Publications A number of statistical investigations of the condition of housing and housing markets in various countries have been undertaken (Canada HRSD, 2009; CSO Ireland, 2008). These frequently use indicators as part of the exposition, and in some cases have led to indicator sys tems being developed (DETR, 1997, 1998). Performance Indicators In Britain, the Netherlands, Scandinavia, and other parts of Europe, the move away from public and council hous ing towards housing associations has strongly encouraged the development of performance indicators. There is now a very substantial literature in the area (Clapham and Satsangi, 1992; Smith and Walker, 1994). The British literature demonstrates the move away from prescriptive central programme indicators to a more communitybased approach with no central monitoring. In 1993, the Australian government laid down a com mon framework for performance indicator reporting across all departments. It took some years before the public housing indicators selected to fit this external framework settled into the system currently used (AIHW 2009; see Burke and Hayward, 2000; Urban Resources and SGS, 1999, for critiques). Benchmarking In benchmarking, workers in organisations examine their internal processes to try to improve effectiveness, estab lish benchmark indicators for performance, find other organisations that perform better or have good practice, and adopt their methods and internal organisation. This seems to have been very rarely done for housing delivery organisations, and it is an area where considerable improvements could be achieved in construction, service delivery, asset management, financial monitoring, and other aspects of organisational processes (Flood, 1999).
Use and Abuse – Indicator Controversies Indicators form one important input to the policy process, but only one input of many that will lead to the usual negotiated process of policy setting. Even if there is a good connection between a specific policy instrument and an indicator, there are normally other policy actions that will influence significantly a particular outcome mea sured by one indicator. The multidimensional nature of most policies is significant, and it is unlikely in most cases
that a single indicator will express every desired outcome of a particular policy. Some people may assume that because an indicator is established and shows a positive result or improvement, then no more needs to be done. Others may disguise bad outcomes by quoting indicators which are not really rele vant, while other important indicators which do not show a positive result are conveniently forgotten. In a few cases, different indicators can be associated with very different policy approaches or can be associated with contradictions in political thinking. Once an indica tor gains a life of its own, it may be subject to attack or denigrated by stakeholders who have a vested interest in ensuring no action is taken. These general principles can be demonstrated through several topical examples.
Affordability Indicators Housing markets are particularly vulnerable to ‘bubble behaviour’ and policy confusion, since correcting a bulge in one part of the market tends to create pressure or undesirable outcomes in others. All governments would like house prices to be both low and rising, which cannot continue. Everyone agrees that affordable housing is a good thing, but governments will frequently take action to support high house prices. Three different groups of stakeholders have conflict ing interests in housing affordability – developers who want controls and levies removed and house prices low ered, real estate agents who want rapid turnover and rising prices, and environmentalists who want cities to stop expanding. Preventing the expansion of cities has environmental and cost advantages in limiting ‘sprawl’, but in a growing market, it will invariably cause a sub stantial upward revision in price and greater congestion costs. These different objectives are generally expressed through different indicators which will suggest different policy responses. For example, H1, the median house price-to-income ratio is regarded as a primary measure of affordability which should be kept below the value of 3. However, following financial deregulation in the early 1980s, the indicator began to run substantially higher than this, and again in the period after 1996, it ran to extremely high levels, over 6 in a number of countries, particularly in Ireland, Spain, and Australia which were exposed to boom conditions (Performance Urban Planning, 2009). However, if alternative measures of affordability such as HA1 or HA2 above are used, the problem appears to go away. HA2 appears to show that interest rates should be kept low, while HA1 encourages the removal of pruden tial constraints on lending. Frequent citation of HA2 has
Housing Indicators
507
prevented governments from increasing interest rates to keep a lid on house prices. Even the very widely used indicator HA2 has been subject to an extensive measurement controversy. The indicator as stated always shows higher levels of housing stress in small households (who naturally devote a higher proportion of their income to housing), and as well it is not comparable between income groups. It is generally agreed that ‘residual income’ after housing is a better and more comparable measure of the stress caused by high housing expenditure. In the end, there is no escaping the reality that high house prices are bad for the economy and for intergenera tional equity, and that in the very long term they are caused by limiting urban expansion (Angel, 2004).
gaining a widespread appreciation of the use of the indi cators for diagnostic purposes. It was not until the Global Financial Crisis that some of the key indicators began to be used for this purpose on a global scale – and mostly in the developed countries. A number of community-based indicators projects have made wide use of other housing indicators covering issues of equity and sustainability. There has been insuffi cient use of indicators for benchmarking the performance of housing organisations and using these in adopting best practice. There is room for an expanded system of National and Local Observatories that can maintain housing and urban indicators and push forward with educating policymakers in their use.
The Slum Indicator
See also: Housing Statistics.
The only housing indicator included in the United Nations Millennium Development Goals was ‘‘7.10. Proportion of people living in slums’’. While this referred to the extremely important concept of delineating areas of social deprivation and poor housing, the term ‘slum’ had not been included in official housing documents since the 1920s, except in India, mostly because it was regarded as impossible to define or measure. However, the notion of slums had substantial political and emotive power for advocacy, and these poli tical advantages ultimately led to the reintroduction of the term (UN-HABITAT, 2003, 2005). It was clear that the concept was multidimensional and very difficult to measure objectively. After several unsuccessful attempts at a definition, UN-HABITAT took a dwelling to be a slum if it had any one of the following: (1) lack of access to improved water supply; (2) lack of access to improved sanitation; (3) overcrowd ing (three or more persons per room); and (4) dwellings made of nondurable materials. In practice, the only information widely available at the household level was water and sanitation, and the slum indicator ended up as a proxy for either of these – which somewhat defeated the original intention.
Conclusions The original aim of the World Bank/UN-HABITAT hous ing indicators – to provide an overall diagnostic tool for looking at the effectiveness of the whole housing system – has rarely been emulated except perhaps in medical diag nosis, which was frequently used as an analogy. The Indicators Programme succeeded in its aims of espousing an enabling market-oriented approach to hous ing through much of the developing world. Like many indicators activities, it was not so successful in maintain ing a sustained collection within policy departments, or in
References Angel S (2004) Housing Policy Matter: A Global Analysis. Oxford, UK: Oxford University Press. Australian Institute of Health Welfare (AIHW) (2009) Public Rental Housing 2007–08. Canberra: AIHW. Biderman AD (1966) Social indicators and goals. In: Bauer RA (ed.) Social Indicators, pp. 68–153. Cambridge, MA: MIT Press. Burke T and Hayward D (2000) Performance Indicators and Social Housing in Australia. http://researchbank.swinburne.edu.au (accessed 18 June 2011) Canada Human Resources and Skills Development (Canada HRSD) (2009) Indicators of Well Being in Canada: Housing. http:// www4.hrsdc.gc.ca/[email protected]?did=7 Central Statistical Office Ireland (2008. Construction and Housing in Ireland 2008 Edition. Dublin: Stationery Office. Clapham D and Satsangi M (1992) Performance measurement and accountability in British housing management. Policy and Politics 20(10): 63–74. Department of the Environment, Transport the Regions (DETR) (1997) Housing in England 1995/6. London: DETR. Department of the Environment, Transport the Regions (DETR) (1998) Developing a System of Housing Quality Indicators. DEGW Consulting. London: DETR. Flood J (1993) Housing indicators in Australia: A consultative method. Netherlands Journal of Housing and the Built Environment 8(1): 95–124. Flood J (1997) Urban and housing indicators. Urban Studies 34(10): 1665–1667. Flood J and Spiller Gibbins Swan (SGS) (1999) Methodology for developing benchmarking for housing outcomes. AHRF 208, Final Report. Nairobi: UNCHS-HABITAT. Goedert JE and Goodman JL, Jr. (1977) Indicators of the Quality of US Housing. Washington, DC: Urban Institute. Harvard Joint Centre for Housing Studies (HJCHS) (2009) The State of the Nation’s Housing 2009. Cambridge, MA: Harvard University. Hatry H (2007) Performance Measurement, Getting Results, 2nd edn. Washington, DC: Urban Institute. Hegedus J and Tosics I (1993) Housing indicators in transitional economies: A new tool for policy making: The Hungarian housing indicators program intensive survey. Netherlands Journal of Housing and the Built Environment 8(1): 85–94. Horowitz CF (1980) Housing Indicators and Housing Policy. Monticello, IL: Vance Bibliographies. Horowitz CF (1986) Housing Indicators and Public Policy, 2nd ed. Monticello, IL: Vance Bibliographies.
508
Housing Indicators
Ingels M (1980) Housing Data Resources: Indicators and Sources of Data for Analyzing Housing and Neighborhood Conditions. Washington, DC: Bureau of the Census. Ministry of Public Construction and National Housing, Zimbabwe (1990) Monitoring of the Shelter Sector Performance Using the Shelter Indicator Methodology. Zimbabwe: MPCNH. Newton P, Flood J, Berry M, et al. (1998) Environmental Indicators for National State of the Environment Reporting. Human Settlements. Canberra, ACT: Department of the Environment. Performance Urban Planning (2009) 5th Annual Demographia International Housing Affordability Survey. http:// www.demographia.com/dhi.pdf(accessed 18 June 2011) Sheldon EB and Moore WE (1968) Indicators of Social Change: Concepts and Measurement. New York: Russell Sage Foundation. Smith R and Walker R (1994) The role of performance indicators in housing management: a critique. Environment and Planning A 26(4): 609–621. United Nations. Ad Hoc Group of Experts on Social Indicators for Housing and Urban Development (1973) Social Indicators for Housing and Urban Development. Dublin: UN. United Nations Centre for Human Settlements (UNCHS) (1997) Indicators Programme 1994–96. Programme activities. Analysis of the data collection. Report to Commission for Human Settlements. Canberra: AHRF. UN-HABITAT (2002) State of the World’s Cities Report 2002. Nairobi: UN-HABITAT. UN-HABITAT (2003) The Challenge of Slums: Global Report on Human Settlements 2003. London: Earthscan. UN-HABITAT (2005) State of the World’s Cities Report 2004/5. London: Earthscan. United States, Bureau of the Census (1976) Financial characteristics by indicators of housing and neighborhood quality. Washington, DC: US Bureau of the Census. United Nations. Statistical Division (1993) Housing in the World: Graphical Presentation of Statistical Data. New York: UN. United Nations Statistical Office (1962) Statistical Indicators of Housing Conditions. New York: United Nations. Urban Resources and Spiller Gibbins Swan (1999) Methodology for Developing Benchmarking for Housing Outcomes. AHRF 208, Final Report, April 1999. Wilcox S (2003) Can Work Can’t Buy. York, UK: Joseph Rowntree Foundation. World Bank (1993) Housing: Enabling Markets to Work. Washington, DC: World Bank.
World Bank/UNCHS (1991–1993) The Housing Indicators Program, Vol. 1: Report of the Executive Director, Vol. II: Indicator Tables, Vol. III: Preliminary Findings, Vol. IV: The Extensive Survey Instrument. Washington, DC: World Bank/UNCHS.
Further Reading Demographia (2010) 6th Annual Demographia Internationl Housing Affordability Survey. http://www.demographia.com United Nations Centre for Human Settlements (UNCHS-HABITAT) (1995) Monitoring Human Settlements: Abridged Survey. Indicators Programme. Nairobi: UNCHS.
Relevant Websites www2.standardandpoors.com – Benchmarks, research, data, and analytics. www.manhattan-institute.org – Manhattan Institute. www.mortgageguideuk.co.uk – Mortgage guide UK. www.realtor.org/research/research/ecoindicator – National Association of Realtors. http://soer.justice.tas.gov.au/2003/indicator – State of the Environment Tasmania. www.sustainablemeasures.com/Database/Housing.html – Sustainable Measures. Links to a number of communitybased housing indicators. www.un.org/esa/dsd/index.shtml – UN Commission on Sustainable Development. ww2.unhabitat.org/programmes/guo/ – United Nations Human Settlements. http://mdgs.un.org/unsd/mdg – United Nations Statistical Division. Millennium Development Goals Indicators. www.bus.wisc.edu/realestate/documents/inthsg2.xls – Wisconsin Real Estate Programme. The values of the original housing indicators collected for the 1993 pilot.
Glossary Benchmarking A methodology for improving organisational performance in which performance indicators are developed, similar organisations are found that perform better on these indicators, and the good practices which result in outstanding performance are copied. Holistic approach Taking a comprehensive view of some area of social policy, rather than focusing on one or two key issues that are currently in the public eye. Indicator A single item of data which is tied to a policy goal and points the way to ‘improvement’ according to some norm.
What Are Indicators? Indicators are small ‘models’ simplifying a complex sub ject to a few numbers which can be easily grasped and understood by policy-makers and the general public. They are generally highly aggregated and consist of ratios so that they are normalised in some fashion. They should be policy- and stakeholder-driven so that each indicator has one or more associated objectives and is valuable to some significant group of stakeholders. Some of the characteristics of good indicators are that they should be (1) important, (2) measurable, (3) respon sive, (4) simple and robust, (5) timely, (6) stakeholderdriven, (7) action-oriented, and (8) informative. The characteristics of a good indicator ‘system’ are that it should (1) cover the most important issues, (2) represent the interests of all stakeholders, and (3) be structured in a modular, logical manner. A well-structured system will also show linkages – different indicators may reinforce each other to give a picture of the overall effectiveness of a tightly linked system such as a housing market. The major groups of stakeholders who may benefit from the use of indicators are as follows: Governments: Governments most commonly use indica tors as part of prescriptive reporting structures, or integrated within strategy documents or national sec toral reports. Most housing strategy documents are structured around examples of indicators as measures of conditions or of past successes and failures, and improvements resulting from such strategies are
502
Monitoring Reporting to stakeholders on progress towards meeting organisational objectives; often using indicators. Norm A judgement by one or more groups of stakeholders as to what constitutes better outcomes or a better situation in some area of social policy. Different stakeholders may have opposing norms. Performance indicators Indicators adopted by organisations for reporting. Stakeholder Anyone with a vested interest in the performance of an organisation.
generally anticipated in terms of indicators. Spatial indi cators of need may also be used to distribute funding for infrastructure or social housing. Private sector: The private sector (builders, developers, and real estate agents) needs timely information for investment and sales purposes, concerning economic conditions in cities, government performance, supply/ demand imbalances, and the consumption requirements of residents. Consequently, organisations representing private sector interests are often involved in presenting national housing data series, particularly those relating to prices and market conditions. These are also used in the role of advocacy on behalf of their constituents. In some cases, private organisations have become important suppliers of housing data, particularly relating to prices. For example, Fiserv Pty Ltd owns and maintains the S&P/CaseShiller US National Home Price Index, and Standard and Poor’s disseminates the results. Data analysis firms in most countries provide advice and reports on real estate and investment conditions in national and local markets. ‘Nongovernment and community organisations’ are the major users of indicators in their advocacy and lobbying role, in submitting funding proposals, and, particularly, because through indicators they can monitor the performance of governments. In the sustainability area, not-for-profit organisations have taken on the major role in publishing indicators of community well-being including housing indicators (see Relevant Websites). The ‘public, media, and tenants of housing organisa tions’ may be informed by indicators of the efficient and
APPROACHES
Housing Indicators
equitable performance of markets and satisfactory man agement of housing policy and administration.
History of Housing Indicators From the time of Biderman (1966) and Sheldon and Moore (1968), indicators have been nominated as a means by which progress towards a whole system of social goals could be measured. The importance of indicators to housing policy has also been recognised for a long time, and fairly extensive bibliographies of early contributions in the field have been produced (Horowitz, 1980, 1986). Generally, these contributions were related to particular parts of housing policy, such as housing needs or housing and neighbourhood quality (Goedert and Goodman, 1977; Ingels, 1980; US Bureau of the Census, 1976) rather than to the housing sector as a whole. The United Nations took an interest in shelter and its adequacy from the early 1960s (UNSD, 1993; UNSO, 1962), and in the 1970s, the UN Ad Hoc Group of Experts on Social Indicators for Housing and Urban Development (UN, 1973) sustained this concern. From the late 1970s, there was a massive surge in urba nisation in the developing world, resulting in burgeoning slum or shanty populations surrounding most cities. In the late 1980s, there was a resurgence of interest in monitoring and indicators as it became apparent that sectoral, govern ment-based approaches to solving urban and housing problems had not worked in the developing world and that a multisector, enabling strategy was the preferred approach to achieving improvements (World Bank, 1993). This was underlined by a rapidly emerging interest in sustainability issues, which stressed the interrelatedness of all aspects of human activity with the natural environment. The Housing and Urban Indicators Programme Following the International Year of Shelter for the Homeless, in 1988, the Global Shelter Strategy to the Year 2000 was adopted. This strategy was influenced by market liberal economies, and called for a fundamental shift in government policy away from the direct provision of housing towards an enabling legislative and regulatory environment which ‘facilitates, energises, and supports the activities of the private sector’. In 1989, the United Nations Centre for Human Settlements (now UN HABITAT) was requested to provide cost-effective national monitoring of progress towards realising the goals of the Strategy. In October 1990, the World Bank and UNCHS (now UN-HABITAT) jointly initiated the Housing Indicators Programme (HIP), which was funded and supported by USAID. The methodology and the indicators were lar gely the brainchild of Dr Steven Mayo, a principal
503
economist with the World Bank, and Dr Schlomo Angel, an Israeli expert on slums and urban development. The indicators had a macroeconomic emphasis and some of the indicators were novel and original. The pilot pro gramme resulted in a detailed comparison of the housing sectors in major cities in 52 countries, through the collection of about 40 key indicators on a comparable basis (World Bank/UNCHS, 1991). The final results of the original HIP were not published until after the unti mely death of Mayo (Angel, 2004) (see Relevant Websites and the 1996 and 2001 values are available from the author). Subsequently, 10 of these housing indicators were col lected globally as part of a much more comprehensive urban indicators system in the run up to the Habitat II conference in Istanbul in 1996, and again in 2001, along with tenure data. In this case, data for 237 cities were collected which were sufficient for a global sample and analysis (Flood, 1997; UNCHS, 1997; UN-HABITAT, 2002). The long-term aim of the Programme was ambitious: to engage countries in a lasting process which would place housing issues on the national policy agenda. The major original contribution of the Programme was not just an innovative indicators set but a whole new philosophy about the way data should be used in organisations. Indicators were to be developed and prioritised through participative stakeholder consultations (Flood, 1993), they were to be a holistic collection measuring the health of a whole sector, and every indicator should have an objective and strategy associated with it. They were to be maintained within operational departments or specialpurpose monitoring groups and should not reside or be under the control of central statistical agencies. The sta tistics were also to be collected at the city level – which had not previously been attempted. One of the main purposes of the housing indicators was to establish a set of diagnostics for a ‘well-function ing housing market’ and the indicators were chosen with this in mind. For example, various indicators might show a market in which land was being inade quately supplied, resulting in housing shortages and high prices. Deviations from standard benchmarks might show the presence of market-distorting policies like rent control. It cannot be overstated the effect that the Housing Indicators movement had on thinking about housing pol icy in the developing world, although its ‘soft’ marketoriented philosophy was rarely adopted. Some of the indicators, most notably the median house price-to income ratio (see Relevant Websites), have been accepted globally and by many agencies and are still at the centre of considerable controversy. Separate HIPs were conducted in the early 1990s in a number of countries in the Caribbean, Southern Africa, and Eastern Europe (see Hegedus and Tosics, 1993; Ministry of Public
504
Housing Indicators
Construction and National Housing, Zimbabwe, 1990), generally funded by USAID, as part of an attempt to vitalise or revive the housing sectors of those countries. Aftermath In general, the housing indicators were well received. The main criticisms were in keeping with the origins of the system – that they referred largely to the economic part of the economic–social environmental nexus, and had little distributional or environmental content. Data issues and the costs of data verification remained a major obstacle. Flood (1997) concluded that ‘‘The housing indicators have been less well understood than the other (urban) indicators, partly because they represent data that are not commonly collected, and partly because they represent complex concepts or have difficult collection methods’’. To change institutions is a harder task than collecting indicators, and the funds or political will to do this were never really there. Ultimately, the ‘enabling approach’ appealed neither to the growing sustainability movement nor to the economic right. After 15 years of promotion through the Global Urban Observatory movement, the strategic emphasis on a holistic, sectoral approach and on participative development of indicators through stake holder meetings has not been widely adopted, although particular indicators retain a considerable following. The main follow-up to the Habitat Agenda in 1996 was to construct a network of National and Local Urban Observatories who were tasked with collecting key urban and housing indicators and making sure they were applied to policy. This was to be coordinated by the Global Urban Observatory located in Nairobi. This still exists with limited support, and a few local observatories are active (Vancouver, Barcelona, Jeddah, Medina, and Tehran), though none have a housing focus. Within UN HABITAT after 2003, most effort has gone towards col lecting the Millennium Indicators, http://mdgs.un.org/ unsd/mdg, through national statistical bodies rather than collecting key indicators through operational departments. Several of the original supporters of the HIP, most notably the National Association of Realtors and the Canada Mortgage and Housing Corporation, have con tinued to be independently active in the indicators area. The most lasting legacy of the HIP has probably been Indicator H1, the Median House Price to Income Ratio, which has become the primary indicator of the general health and efficiency of housing and land markets (HJCHS, 2009; Wilcox, 2003, and many other sources). Mainstreaming Housing Indicators The emphasis after 1995 was less about maintaining whole systems of housing indicators to measure the health of the sector – which in practice rarely had a champion
agency within national governments – and was more directed towards including indicators of performance within policy documents and as part of government reporting. By the mid-1990s, most annual reports of gov ernment agencies were required to include indicators of performance. However, the laissez-faire 1990s were anti-planning even within a market liberal framework: the role of gov ernment was to be as a regulator rather than a guiding hand. Even monitoring was discontinued in many housing markets, as specialist departments of housing tended to disappear, retaining only a narrow residual role within much larger social security ministries. Much of the effort in collecting and maintaining housing market indicators devolved to the private sector and to sustainability organisations. The world paid the price for this lack of attention to housing markets and for leaving monitoring largely to partisan delivery agencies or lobbying groups in October 2007, when the subprime mortgage crisis preci pitated the largest economic downturn since the Great Depression. Closer monitoring of the health of over stressed housing markets using indicators might have prompted policy action to take the pressure off prices in the worst-affected areas, and to improve accountability and obtain better compliance with prudential norms.
Housing Indicators Housing and Urban Indicators Programme The 10 housing indicators that were collected for Habitat II in 1996 and Istanbul+5 in 2001, for approximately 235 cities around the world on each occasion, were: H1: House price to income ratio – Median house price/ median household income; a primary indicator of the health of housing markets. H2: House rent to income ratio – Median rent/median income of renters. Less than 20% usually means that rent control is in place. H3: Floor area per person – Consumption indicator, highly correlated with GDP or city product. H4: Permanent structures – Per cent structures of perma nent materials; measures the very poorest communities. H5: Unauthorised housing – Per cent stock ‘not in com pliance’ with current regulations; establishes the strength of the informal sector. H6: Land development multiplier – Ratio of median land price of a developed plot at the urban fringe and the median price of raw, undeveloped land; potentially useful, but hard to measure consistently. H7: Infrastructure expenditure – Total annual expendi tures on infrastructure services per person; a community wealth measure.
Housing Indicators
505
Table 1 Mean value of the 10 key housing indicators, by development quintile, Habitat II collection, 1996
H1. Price to income H2. Rent to income (%) H3. Floor area per person (sq m) H4. Permanent dwellings (%) H5. Dwellings in compliance (%) H6. Land development multiplier H7. Infrastructure expenditure per capita ($) H8. Mortgage to credit ratio (%) H9. Dwelling production per 1000 population H10. Housing investment ratio (%)
Very low
Low
Medium
Higher
Developed
6.6 29.1 7.3 46.9 42.5 5.1 16 5.9 4.7 7.7
8.1 28.2 8.0 77.9 52.5 4.9 15 7.1 6.0 12.2
8.8 15.4 13.2 78.8 72.9 3.9 48 12.0 8.5 6.2
8.3 11.7 17.3 91.7 85.5 4.6 136 20.3 5.6 5.1
4.7 18.0 31.4 95.6 96.2 5.3 421 27.1 4.8 3.2
The development level of cities was defined using the City Development Index, which is described in Flood (1997). Source: Flood J (1997) Urban and housing indicators. Urban Studies 34(10): 1665–1667; Tables 13 and 14.
H8: Mortgage to credit ratio – Ratio of mortgage loans to all loans; can only be measured at the national level. Over 25% in developed countries, almost negligible elsewhere. H9: Housing production – Net number of housing units produced per 1000 population. A major measure of boom/bust or vigour of the sector; usually unknown when informal sector is large. H10: Housing investment – Investment in housing/gross city product; measures importance of housing in the local economy and is difficult to calculate.
HA6. Overcrowding – Households with too few bedrooms. HA8. Inadequate housing – Requiring substantial repairs to bring them to accepted standards. HA11. Homelessness – Number of people per thousand who sleep outside dwelling units or in temporary shelter. Other housing indicators and statistics that are frequently cited include:
Table 1 shows the 1996 averages for these indicators over cities of different levels of development. Indicators H3, H4, H5, H7, and H8 increase with the level of develop ment, as they represent increased consumption, improved dwelling quality, and more developed mortgage systems. House prices are highest with respect to income at middle levels of development – probably because formal sector construction standards are enforced before incomes have risen sufficiently to justify them. Rents H2 fall with devel opment until the final quintile. The construction indicators H9 and H10 are correlated with rates of urban household formation.
Supply: Prices, stock turnover, second homes, building approvals and completions, and supply of unsold homes. Affordability: Proportion able to afford median home. Housing gap: Shortfall in supply of affordable housing. Usually rhetorical rather than numeric. Mortgage finance: Mortgage applications, mortgage approvals, interest rates, foreclosures, and equity withdrawal. Rental: Yields and returns, vacancy rates, and rental distributions. Public housing: Length of waiting lists, subsidies, occu pancy, match with client needs, and special needs. Consumer: Report cards, indexes of satisfaction, and security for the public and for public tenants.
Other Indicators
Other Systems
Several other indicators from the extended housing indi cator system are widely used in OECD countries.
There are a number of standard systems or frameworks for classifying and organising indicators, which can be useful in reducing the amorphousness of metrics estab lished through stakeholder consultations. For environmental indicators, these include the Extended Urban Metabolism system for urban sustainability (Newton et al., 1998), and for organisational performance indicators, outcome-based management (Hatry, 2007). By and large, these classifications do not work very well for housing indicators, since many of these are prices and
HA1. Mortgage affordability – Proportion of households who are eligible for and can afford the maximum loan on a median-priced formal sector house. HA2. Excessive housing expenditure – Proportion of households in the bottom 40% of incomes who are spending more than 30% of their incomes on housing; known as ‘core housing need’ in Canada and ‘housing stress’ in Australia.
506
Housing Indicators
macroeconomic measures which can adopt different roles depending on the context. Statistical Publications A number of statistical investigations of the condition of housing and housing markets in various countries have been undertaken (Canada HRSD, 2009; CSO Ireland, 2008). These frequently use indicators as part of the exposition, and in some cases have led to indicator sys tems being developed (DETR, 1997, 1998). Performance Indicators In Britain, the Netherlands, Scandinavia, and other parts of Europe, the move away from public and council hous ing towards housing associations has strongly encouraged the development of performance indicators. There is now a very substantial literature in the area (Clapham and Satsangi, 1992; Smith and Walker, 1994). The British literature demonstrates the move away from prescriptive central programme indicators to a more communitybased approach with no central monitoring. In 1993, the Australian government laid down a com mon framework for performance indicator reporting across all departments. It took some years before the public housing indicators selected to fit this external framework settled into the system currently used (AIHW 2009; see Burke and Hayward, 2000; Urban Resources and SGS, 1999, for critiques). Benchmarking In benchmarking, workers in organisations examine their internal processes to try to improve effectiveness, estab lish benchmark indicators for performance, find other organisations that perform better or have good practice, and adopt their methods and internal organisation. This seems to have been very rarely done for housing delivery organisations, and it is an area where considerable improvements could be achieved in construction, service delivery, asset management, financial monitoring, and other aspects of organisational processes (Flood, 1999).
Use and Abuse – Indicator Controversies Indicators form one important input to the policy process, but only one input of many that will lead to the usual negotiated process of policy setting. Even if there is a good connection between a specific policy instrument and an indicator, there are normally other policy actions that will influence significantly a particular outcome mea sured by one indicator. The multidimensional nature of most policies is significant, and it is unlikely in most cases
that a single indicator will express every desired outcome of a particular policy. Some people may assume that because an indicator is established and shows a positive result or improvement, then no more needs to be done. Others may disguise bad outcomes by quoting indicators which are not really rele vant, while other important indicators which do not show a positive result are conveniently forgotten. In a few cases, different indicators can be associated with very different policy approaches or can be associated with contradictions in political thinking. Once an indica tor gains a life of its own, it may be subject to attack or denigrated by stakeholders who have a vested interest in ensuring no action is taken. These general principles can be demonstrated through several topical examples.
Affordability Indicators Housing markets are particularly vulnerable to ‘bubble behaviour’ and policy confusion, since correcting a bulge in one part of the market tends to create pressure or undesirable outcomes in others. All governments would like house prices to be both low and rising, which cannot continue. Everyone agrees that affordable housing is a good thing, but governments will frequently take action to support high house prices. Three different groups of stakeholders have conflict ing interests in housing affordability – developers who want controls and levies removed and house prices low ered, real estate agents who want rapid turnover and rising prices, and environmentalists who want cities to stop expanding. Preventing the expansion of cities has environmental and cost advantages in limiting ‘sprawl’, but in a growing market, it will invariably cause a sub stantial upward revision in price and greater congestion costs. These different objectives are generally expressed through different indicators which will suggest different policy responses. For example, H1, the median house price-to-income ratio is regarded as a primary measure of affordability which should be kept below the value of 3. However, following financial deregulation in the early 1980s, the indicator began to run substantially higher than this, and again in the period after 1996, it ran to extremely high levels, over 6 in a number of countries, particularly in Ireland, Spain, and Australia which were exposed to boom conditions (Performance Urban Planning, 2009). However, if alternative measures of affordability such as HA1 or HA2 above are used, the problem appears to go away. HA2 appears to show that interest rates should be kept low, while HA1 encourages the removal of pruden tial constraints on lending. Frequent citation of HA2 has
Housing Indicators
507
prevented governments from increasing interest rates to keep a lid on house prices. Even the very widely used indicator HA2 has been subject to an extensive measurement controversy. The indicator as stated always shows higher levels of housing stress in small households (who naturally devote a higher proportion of their income to housing), and as well it is not comparable between income groups. It is generally agreed that ‘residual income’ after housing is a better and more comparable measure of the stress caused by high housing expenditure. In the end, there is no escaping the reality that high house prices are bad for the economy and for intergenera tional equity, and that in the very long term they are caused by limiting urban expansion (Angel, 2004).
gaining a widespread appreciation of the use of the indi cators for diagnostic purposes. It was not until the Global Financial Crisis that some of the key indicators began to be used for this purpose on a global scale – and mostly in the developed countries. A number of community-based indicators projects have made wide use of other housing indicators covering issues of equity and sustainability. There has been insuffi cient use of indicators for benchmarking the performance of housing organisations and using these in adopting best practice. There is room for an expanded system of National and Local Observatories that can maintain housing and urban indicators and push forward with educating policymakers in their use.
The Slum Indicator
See also: Housing Statistics.
The only housing indicator included in the United Nations Millennium Development Goals was ‘‘7.10. Proportion of people living in slums’’. While this referred to the extremely important concept of delineating areas of social deprivation and poor housing, the term ‘slum’ had not been included in official housing documents since the 1920s, except in India, mostly because it was regarded as impossible to define or measure. However, the notion of slums had substantial political and emotive power for advocacy, and these poli tical advantages ultimately led to the reintroduction of the term (UN-HABITAT, 2003, 2005). It was clear that the concept was multidimensional and very difficult to measure objectively. After several unsuccessful attempts at a definition, UN-HABITAT took a dwelling to be a slum if it had any one of the following: (1) lack of access to improved water supply; (2) lack of access to improved sanitation; (3) overcrowd ing (three or more persons per room); and (4) dwellings made of nondurable materials. In practice, the only information widely available at the household level was water and sanitation, and the slum indicator ended up as a proxy for either of these – which somewhat defeated the original intention.
Conclusions The original aim of the World Bank/UN-HABITAT hous ing indicators – to provide an overall diagnostic tool for looking at the effectiveness of the whole housing system – has rarely been emulated except perhaps in medical diag nosis, which was frequently used as an analogy. The Indicators Programme succeeded in its aims of espousing an enabling market-oriented approach to hous ing through much of the developing world. Like many indicators activities, it was not so successful in maintain ing a sustained collection within policy departments, or in
References Angel S (2004) Housing Policy Matter: A Global Analysis. Oxford, UK: Oxford University Press. Australian Institute of Health Welfare (AIHW) (2009) Public Rental Housing 2007–08. Canberra: AIHW. Biderman AD (1966) Social indicators and goals. In: Bauer RA (ed.) Social Indicators, pp. 68–153. Cambridge, MA: MIT Press. Burke T and Hayward D (2000) Performance Indicators and Social Housing in Australia. http://researchbank.swinburne.edu.au (accessed 18 June 2011) Canada Human Resources and Skills Development (Canada HRSD) (2009) Indicators of Well Being in Canada: Housing. http:// www4.hrsdc.gc.ca/[email protected]?did=7 Central Statistical Office Ireland (2008. Construction and Housing in Ireland 2008 Edition. Dublin: Stationery Office. Clapham D and Satsangi M (1992) Performance measurement and accountability in British housing management. Policy and Politics 20(10): 63–74. Department of the Environment, Transport the Regions (DETR) (1997) Housing in England 1995/6. London: DETR. Department of the Environment, Transport the Regions (DETR) (1998) Developing a System of Housing Quality Indicators. DEGW Consulting. London: DETR. Flood J (1993) Housing indicators in Australia: A consultative method. Netherlands Journal of Housing and the Built Environment 8(1): 95–124. Flood J (1997) Urban and housing indicators. Urban Studies 34(10): 1665–1667. Flood J and Spiller Gibbins Swan (SGS) (1999) Methodology for developing benchmarking for housing outcomes. AHRF 208, Final Report. Nairobi: UNCHS-HABITAT. Goedert JE and Goodman JL, Jr. (1977) Indicators of the Quality of US Housing. Washington, DC: Urban Institute. Harvard Joint Centre for Housing Studies (HJCHS) (2009) The State of the Nation’s Housing 2009. Cambridge, MA: Harvard University. Hatry H (2007) Performance Measurement, Getting Results, 2nd edn. Washington, DC: Urban Institute. Hegedus J and Tosics I (1993) Housing indicators in transitional economies: A new tool for policy making: The Hungarian housing indicators program intensive survey. Netherlands Journal of Housing and the Built Environment 8(1): 85–94. Horowitz CF (1980) Housing Indicators and Housing Policy. Monticello, IL: Vance Bibliographies. Horowitz CF (1986) Housing Indicators and Public Policy, 2nd ed. Monticello, IL: Vance Bibliographies.
508
Housing Indicators
Ingels M (1980) Housing Data Resources: Indicators and Sources of Data for Analyzing Housing and Neighborhood Conditions. Washington, DC: Bureau of the Census. Ministry of Public Construction and National Housing, Zimbabwe (1990) Monitoring of the Shelter Sector Performance Using the Shelter Indicator Methodology. Zimbabwe: MPCNH. Newton P, Flood J, Berry M, et al. (1998) Environmental Indicators for National State of the Environment Reporting. Human Settlements. Canberra, ACT: Department of the Environment. Performance Urban Planning (2009) 5th Annual Demographia International Housing Affordability Survey. http:// www.demographia.com/dhi.pdf(accessed 18 June 2011) Sheldon EB and Moore WE (1968) Indicators of Social Change: Concepts and Measurement. New York: Russell Sage Foundation. Smith R and Walker R (1994) The role of performance indicators in housing management: a critique. Environment and Planning A 26(4): 609–621. United Nations. Ad Hoc Group of Experts on Social Indicators for Housing and Urban Development (1973) Social Indicators for Housing and Urban Development. Dublin: UN. United Nations Centre for Human Settlements (UNCHS) (1997) Indicators Programme 1994–96. Programme activities. Analysis of the data collection. Report to Commission for Human Settlements. Canberra: AHRF. UN-HABITAT (2002) State of the World’s Cities Report 2002. Nairobi: UN-HABITAT. UN-HABITAT (2003) The Challenge of Slums: Global Report on Human Settlements 2003. London: Earthscan. UN-HABITAT (2005) State of the World’s Cities Report 2004/5. London: Earthscan. United States, Bureau of the Census (1976) Financial characteristics by indicators of housing and neighborhood quality. Washington, DC: US Bureau of the Census. United Nations. Statistical Division (1993) Housing in the World: Graphical Presentation of Statistical Data. New York: UN. United Nations Statistical Office (1962) Statistical Indicators of Housing Conditions. New York: United Nations. Urban Resources and Spiller Gibbins Swan (1999) Methodology for Developing Benchmarking for Housing Outcomes. AHRF 208, Final Report, April 1999. Wilcox S (2003) Can Work Can’t Buy. York, UK: Joseph Rowntree Foundation. World Bank (1993) Housing: Enabling Markets to Work. Washington, DC: World Bank.
World Bank/UNCHS (1991–1993) The Housing Indicators Program, Vol. 1: Report of the Executive Director, Vol. II: Indicator Tables, Vol. III: Preliminary Findings, Vol. IV: The Extensive Survey Instrument. Washington, DC: World Bank/UNCHS.
Further Reading Demographia (2010) 6th Annual Demographia Internationl Housing Affordability Survey. http://www.demographia.com United Nations Centre for Human Settlements (UNCHS-HABITAT) (1995) Monitoring Human Settlements: Abridged Survey. Indicators Programme. Nairobi: UNCHS.
Relevant Websites www2.standardandpoors.com – Benchmarks, research, data, and analytics. www.manhattan-institute.org – Manhattan Institute. www.mortgageguideuk.co.uk – Mortgage guide UK. www.realtor.org/research/research/ecoindicator – National Association of Realtors. http://soer.justice.tas.gov.au/2003/indicator – State of the Environment Tasmania. www.sustainablemeasures.com/Database/Housing.html – Sustainable Measures. Links to a number of communitybased housing indicators. www.un.org/esa/dsd/index.shtml – UN Commission on Sustainable Development. ww2.unhabitat.org/programmes/guo/ – United Nations Human Settlements. http://mdgs.un.org/unsd/mdg – United Nations Statistical Division. Millennium Development Goals Indicators. www.bus.wisc.edu/realestate/documents/inthsg2.xls – Wisconsin Real Estate Programme. The values of the original housing indicators collected for the 1993 pilot.