HOUSING INDICATORS: AN INSTRUMENT IN INTERNATIONAL HOUSING POLICY?

Hugo Priemus

I Introduction

In October 1990, the World Bank launched the Housing Indicators Program, financed in part by the United Nations Center for Human Settlements 'Habitat'. This program sought to create tools for managing the housing sector. More specifically, the program has three aims (see Introduction, p. 1): (a) to provide a comprehensive conceptual and analytical framework for monitoring the performance of the housing sector; (b) to provide important new empirical information on the high stakes of policymaking in the housing sector for societies and economies; (c) to initiate new institutional frameworks that will be more appropriate for formulating and implementing future housing policies in light of new research findings. The World Bank and the UN Center for Human Settlements present the Housing Indicators Program as an essential step in the implementation of the Global Shelter Strategy for the year 2000, which was endorsed by the UN General Assembly in 1988. Incidentally, not only developing countries but also developed economies participate in the Housing Indicators Program. At the end of January 1992, 52 countries were involved in the program (see Appendix I). The Global Shelter Strategy is based on the assumption that government does not provide housing but plays an enabling role. Governments should thus facilitate, energize, and support the activities of the private sector, both formal and informal, in housing development. It is no coincidence that a recent report by Dr. Steve Mayo, the leader of the Housing Indicators Team, bears the title 'Housing: Enabling Markets to Work' (A World Bank Policy Paper, Washington, D.C., November 19, 1991). The World Bank has unswerving confidence in the functioning of markets, also in regard to housing. This article addresses the fundamental questions posed by the Housing Indicators Program (Section 2), the indicators and modules that are used (Section 3), and the Neth. J. of Housing and the Built Environment, Vol. 7 (1992) No. 3

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objectives of the Extensive Survey (Section 4). The conceptual framework is presented in Section 5. The normative view of how the housing sector should work, according to the Housing Indicators Team, is explained in Section 6. This normative view leads to the specification of a number of qualitative regulatory norms (Section 7). Section 8 moves from housing policy goals to housing indicators. Section 9 gives an overview of the planned research outputs of the program. Section 10 presents a brief discussion of the program and some preliminary conclusions.

2 Fundamental Questions Posed by the Housing Indicators Program Governments require instruments to see housing policy from a more global and comparative perspective. Only then can the lessons learned in one country become more relevant to another. The Housing Indicators Program responds to this need. The program seeks to answer three fundamental questions (see Introduction, pp. 2-3): (1) Can informative, robust, reliable, and cost-effective techniques be developed to: (a) measure key aspects of housing-sector performance; (b) establish the linkages between the socio-economic and policy environment and key housing-sector outcomes; and (c) establish the linkages between housing-sector outcomes and broad social and macro-economic performance? (2) How should the use of key indicators of housing-sector performance be integrated into the formulation of national shelter strategies and international development assistance to the housing sector? (3) What institutional developments can be initiated to ensure that housing indicators will be used effectively in informing housing-sector policy?

3 Indicators and Modules

The World Bank developed an extensive series of indicators. The investigators (Steve Mayo, Shlomo Angel, Michael Heller, and Bill Stevens) believe these indicators provide relevant information on housing and housing policy in any given country. They distinguish key, regulatory, and alternate indicators. Key indicators seem likely to be the most powerful indicators of housing-sector performance across countries and through time. Some alternate indicators provide a different way of measuring the same thing as a key indicator, but with more readily available data. The first version of the Housing Indicators Program deals with 25 key housing indicators, 10 regulatory indicators, and 10 socio-economic impact indicators. They were distilled from a comprehensive list of 160 indicators developed at a Habitat Workshop in Nairobi in October 1989. The housing indicators have been grouped into six modules: (1) The Housing Affordability Module, which deals with house prices, rents and 218

households incomes; (2) The Housing Finance Module, which deals with mortgages, credits and interest rates; (3) The Housing Quality Module, which deals with key attributes of housing quality; (4) The Housing Production Module, which deals with housing production and investment; (5) The Housing Subsidies Module, which deals with subsidies and targeted subsidies; and (6) The Regulatory Audit Module, which deals with regulations affecting the exchange of land and housing, land registration and ownership, housing finance regulation, rent control, administrative delays, land use and land development controls and property taxation. All the key indicators and the alternate indicators are numbers, percentages or ratios. Several of the Regulatory Indicators are composite indicators, which are formulated from responses to a large number of simple yes/no questions concerning the regulatory and institutional environment of the housing sector. In each of the 52 participating countries, a Housing Indicators Consultant was recruited. The consultant's task was to quantify the categories of indicators for a particular city (usually the capital) in that country. A Lotus 1-2-3 spreadsheet was provided to construct indicators out of the raw data. Both the printed Modules and the Lotus worksheets were used as the medium for data collection and reporting in order to standardize reporting and reduce errors. The raw data refers to the year 1990. It is preferably hard data (published statistics and the results of empirical research). But if that is unavailable, soft data is used, such as indirect evidence and the informed opinion of experts. The program is the first step in what is intended to be an iterative learning experience. In 1991/1992, three regional meetings were organized (Bangkok, Nairobi, Quito) where the country-based consultants compared notes and discussed the methodology of the indicators. The consultants conducted an extensive survey of the housing sector, aimed at obtaining values for 25 key indicators of housing sector performance, 10 alternate indicators, 10 regulatory indicators designed to quantify the regulatory and institutional framework within which the housing sector operates, and 10 alternate regulatory indicators. In two countries (Hungary and the Philippines) an intensive survey was conducted, including a household survey. Household survey and associated socio-economic data already existed at the World Bank for 10-12 countries. The data had been used to formulate hypotheses on bivariate and multivariate relationships among housing indicators. These hypotheses will be tested in the cross-country comparison based on the results of the Extensive Survey. In the Spring of 1992, the World Bank published an update and revision of the indicator modules and worksheets.

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4 Objectives of the Extensive Survey

The Housing Indicators Team mentions three objectives of the Extensive Survey: (1) to create a basic set of indicators of the housing sector; (2) to obtain current estimates for these indicators in 40-50 countries; (3) to establish key relationships among these indicators, and between them and key indicators of social and economic development, using cross-sectional data from the extensive surveys in these countries. The more practical aims of the Extensive Survey are: (1) to provide an analytical tool for governments for measuring the performance of the housing sector in a comparative, consistent, and policy-oriented perspective; (2) to establish baseline data in participating countries for new national shelter strategies and new housing sector loans; (3) to create a framework for comparing housing sector performance between cities and countries, as well as between different time periods; (4) to help establish a new institutional framework within countries for formulating and implementing sector-wide housing policies; and (5) to work toward the creation of an international network of experts and institutions capable of overseeing the development of the housing sector. After the Regional Meetings a number of In-Country Seminars are planned, to be conducted by the country-based consultant. The objectives of these In-Country seminars are: (a) to present the comparative findings of the Extensive Survey; (b) to examine the policy implications of the findings; and (c) to assess the practical implications of the survey for further, more intensive data collection and analysis in support of new housing-policy initiatives.

5 Conceptual Framework: A Model of the Housing Sector

In the introduction to the Housing Indicators Program, the Housing Indicators Team presents the conceptual framework of the program, which appears to be a clear market-oriented approach. The Team concludes that "... it is useful to look at the housing sector as a single market. In such a market, the housing units in individual sub-markets are viewed as particular combinations of qualities which are obtainable for a given price (Introduction, p. 7). Prices are determinded in the market by demand and supply factors. Housing demand is determined by: - demographic conditions (rate of urbanization, new household formation); - macro-economic conditions affecting household incomes. Demand is also influenced by the availability of housing finance and by government policies: taxation, subsidies and particularly subsidies targeted to the poor. Housing 220

supply is affected by the availability of resource inputs, such as residential land, infrastructure, and construction materials. It is also affected by: - the organization of the construction industry; - the availability of skilled and productive construction labor; - the dependence on imports. Both demand and supply of housing are affected by the regulatory, institutional, and policy environment. Finally, the Housing Indicators Team supposes that housing policies and housing outcomes may in turn affect broader socio-economic conditions, such as: the underfive mortality rate, the rate of inflation, the household savings rate, manufacturing wage and productivity levels, capital formation, and the balance of payments of the government budget deficits. The Team gives the model of the housing sector in figure 1. We think that the Housing Indicators Team overestimates the power of housing demand and housing supply. Neither housing demand nor housing supply are autonomous variables. As the Housing Indicators Team is well aware, these variables are influenced by socio-economic (including demographic) developments. These developments may be influenced by housing outcomes. Yet the most important relation is from socio-economic developments to the housing sector, and not in the first place from the housing sector to broader socio-economic developments. Finally, the role of housing policy has to be included. Figure 2 presents an amended model of the housing sector. Figure 1

Model

of the

housing

sector

(used by the Housing Indicators Team)

Q outcomesH~/

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Figure 2 Amended model of the housing sector (proposal of the author)

Socio-economie developments

'"'"demand Housing

~4~

~-~ Housing supply

Housing policy [

outcomes 6

Normative View

The Housing Indicators Team presents a normative view of how the housing sector should work. Policy-making in the housing sector must be based on such a normative view. Therefore it is necessary to look at the performance of the housing sector from a number of different perspectives: those of housing consumers, housing producers, housing finance institutions, local governments, and central governments. Each of these five perspectives focuses on different aspects of the sector and on different qualitative norms. A number of these qualitative norms are listed below: (1) Housing Consumers a. Everyone is housed. b. There is a separate dwelling unit for every household. c. Housing expenditures do not take up an undue portion of household income. d. House prices are not subject to undue variability. e. Living space is adequate. f. Structures are safe, providing adequate protection from the elements, from fire, and from natural disasters. g. Infrastructure services and amenities are available and reliable. 222

h. Location provides good access to employment opportunities. i. Tenure is secure and protected by due process of law. j. Households may freely choose between different housing options and different housing tenure (owning vs. renting). k. Housing finance is available to smooth housing consumption over time and allow households to pursue desired patterns of saving and investment. 1. Adequate information on housing options is available and affordable, to ensure efficient choice. (2) Housing Producers a. Adequate supply of residential land is available at reasonable prices. b. Infrastructure networks are adequate and do not hold back residential development. c. Building materials and equipment are available at reasonable prices. d. Entry of new firms, large and small, into the residential construction sector is not impeded. e. There is sufficient skilled manpower in the housing sector. f. The residential construction sector is not discriminated against by special tariffs or controls on imported building materials and equipment. g. Adequate financing is available to enable efficient land development and construction. h. Housing production and investment can respond to changes in demand without undue delay. i. Contracts are enforceable. j. Regulations concerning land development, land use, building, land tenure, taxation, or special programs are well-defined and predictable, and government application of these is efficient, timely, and uniform. k. There is a wide latitude in the choice of input combinations, which can generate a broad spectrum of housing choices. 1. Adequate information exists to enable procedures to forecast housing demand with reasonable certainty. m. Rates of return on all types of housing investment, including rental housing, are sufficient to maintain incentives for investment.

(3) Housing Finance Institutions a. Housing finance institutions are permitted to compete for deposits on even terms. b. They are not forced to compete unfairly with subsidized housing finance institutions. c. Lending should be at positive, real interest rates with a sufficient margin to maintain the health of the institution. d. Sufficient deposits exist of an appropriate term structure for long-term mortgage lending. e. Mortgage lending instruments are permitted which are in demand by households, and which provide adequate protection for the institution. 223

f. Systems of property rights, tenure security and foreclosure are such that the financial interests of lenders can be protected. g. Appropriate institutions exist, in either the public or the private sector, which protect financial institutions against undue risk associated with mortgage lending. (4) Local Governments a. Housing and associated infrastructure are of adequate quality to ensure that public health and safety standards are maintained. b. Infastructure networks and services are extended in a timely fashion to all communities. c. The location of new housing communities is in close proximity to existing main infrastructure networks. d. The spatial organization of the urban area, in terms of land use, is productive and efficient. e. Sufficient land can be obtained for laying infrastructure networks and providing local amenities and public services. f. Housing provides a main source of municipal revenues for building and maintaining infrastructure services and neighborhood amenities.

(5)

Central Governments

a. Adequate, affordable housing is available to all. b. Targeted subsidies are available to assist households who cannot afford minimum housing. c. Housing sector policy and strategy is integrated into national social planning. d. The performance of the housing sector is monitored regularly. e. The housing sector contributes toward meeting broad social and economic objectives: 1. Alleviation of poverty; 2. Controlling inflation; 3. Generating household savings and mobilizing household productive resources; 4. Generating employment and income growth; 5. Enabling social and spatial mobility; 6. Increasing productivity; 7. Generating investment growth; 8. Accumulating national wealth; 9. Reducing the balance of payments deficit; 10. Reducing the government budget deficit; 11. Developing the financial system. Of course, the above list is incomplete. Nonetheless, the Housing Indicators Team feels that it does provide a normative overview of a well-functioning housing sector

from key perspectives. 224

Reviewing these norms, a few discrepancies come to light. a. Understandably, there are major contradictions between the norms. When norms la, lb, and lc are combined (every household has an independent and affordable dwelling), it is often hard to reconcile them with norm 5e, point 10 (reduction of the government budget deficit). It is not clear which priorities have to be set. b. The norms are generally stated in an 'open' form, without quantified standards. What is a reasonable ratio of housing expenditure to income (norm lc)? And what standards are used to determine whether the living space is adequate (norm le)? c. Some norms are impossible to achieve, such as a really free choice between owing and renting (norm)j). In most countries, such a free choice does not exist for low-income people. d. The influence of the housing sector on broad social and economic variables (norm 5e) is probably overestimated. Nevertheless, the list of norms developed by the Housing Indicators Team appears to provide a useful basis for the development of housing indicators.

7 Qualitative Regulatory Norms The government must provide an enabling legal framework for the entire cycle of housing development, transaction, use, maintenance and replacement. The Housing Indicators Team concludes that "Despite the diversity of regulatory systems, ideal regulatory systems aim towards a common set of norms. These qualitative norms may in turn be embodied in a limited number of concrete policy goals and measured by quantitative indicators (Introduction, p. 14). The Housing Indicators Team produced the following list of qualitative regulatory norms (Introduction, pp. 14-16).

(1) Housing Market Development a. Private individuals have extensive rights to own and use land and housing; there is a mechanism to transfer those rights through enforceable agreements, and there is an efficient system for dispute resolution. b. Regulation encourages emergence of the wide range of housing types, institutions and actors, including developers, contractors, building materials suppliers, and estate managers. (2) Land Market Development a. The regulatory system makes sufficient land available for development and redevelopment. b. Tenure systems encourage transfer and development of land. c. Conversion of agricultural land to urban uses is not too cumbersome. d. The land registration system has broad coverage.

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(3) Housing Finance Development a. Financial institutions are allowed flexibility to respond to changing market conditions with new financial instruments and organizations. b. Regulations ensure the solvency of financial institutions directly through appropriate supervision and indirectly through insurance markets. c. Effective foreclosure and eviction processes allow land and housing to be used as collateral for loans. d. The regulatory system responds to the informal financial sector by providing it with an accessible dispute resolution mechanism. (4) Public Sector Involvement a. Public sector involvement in the direct development, production, and management of housing is limited. b. The public sector uses indirect controls to organize and manage housing production and delivery by the private formal and informal sector. c. The regulatory system ensures adequate production of public goods such as environmental amenities and infrastructure through structured private incentives and direct provision. d. Targeted regulations and public assistance protect especially vulnerable groups.

(5) Low Price

Distortions a. The regulatory system has transparent and low price distortions in land markets, housing production, sales, rental markets, and in financial markets.

(6) Bureaucratic Bottlenecks a. The regulatory system functions with low bureaucratic costs and delays both under the formal procedures and in practice.

(7)

Affordable Standards a. Land use and building regulations:

minimum lot sizes and density restrictions, along with other regulations, explicitly take into account their economic effect on housing affordability. b. The regulatory system is appropriate to the level of economic development, and low-priced housing can be built in compliance with the codes. c. Urban planning requirements allow a broad range of development options and flexibly respond to changing market conditions.

(8)

Compliance

a. Well-functioning urban legal systems increase compliance by requiring affordable standards and imposing low bureaucratic costs and little delay. (9) Squatter Tolerance a. The regulatory system responds effectively to the presence of a large number of squatters by providing them with regularized tenure and 226

affordable infrastructure, by limiting evictions, and by ensuring that adequate land is available for new low-priced housing. (10) Housing as a Local Tax Base

a. The tax system - including property taxes and assessments - can recapture a portion of the private gains on the appreciation of property values from public effort expended in housing and land development. The first version of housing indicators determined by the Housing Indicators Team is specified in Appendix II. Appendix III shows the links between housing policy goals, as formulated in Sections 6 and 7, and housing indicators, as defined in Appendix II.

8 Research Outputs

Accordingto the Housing Indicators Team, the entire Housing Indicators Program will result in four major kinds of research outputs: (1) tables showing indicator values for a set of 25 key indicators, the 10 alternate indicators, the 10 regulatory indicators and the 10 alternate regulatory indicators, for 40-50 cities in selected countries; (2) a set of tested hypotheses, described both graphically and verbally using crosscountry comparisons, concerning the significant relationships among these indicators; (3) a World Bank monograph, provisionally entitled Housing Indicators for PolicyMaking. This monograph will have two main parts. The first part will introduce the conceptual framework for using housing sector indicators to measure sector performance and to guide policy, and will discuss the indicators and the relationships among them. The second part will discuss methods for data collection, data processing and analysis, institutional arrangements for creating and using indicators, and comparative costs of alternative approaches; (4) research papers by country-based consultants and their associates using comparative international data on the indicators to discuss national housing policy and future monitoring of the housing sector.

9 Discussion

A number of publications on the housing indicators will appear; the first ones will be by the World Bank researchers, to be followed by the reports by the countrybased consultants. Initial experiences reveal the difficulty of finding reliable housing statistics. In many countries, the consultants have to estimate a substantial number of variables. Furthermore, many misunderstandings arise regarding precise definition of some of the variables (e.g., homelessness, segregation) and the dimensions in which these variables are expressed. Finally, quite a few simple 227

mistakes were made in the beginning. Still, after a number of corrections and adaptations, the Extensive Survey does yield reliable data. Moreover, when the countries are ranked by increasing per capita GNP, relatively strong correlations emerge. These tend to support previously formulated hypotheses and regularities, and even comply with common sense. The normative implications of the indicators should be viewed with caution. A high percentage of homeownership is in itself neither good nor bad. It is surprising that the share of social rental dwellings is not reported, nor is the percentage of households receiving housing allowances mentioned. Low rents may be welcome to renters, but the taxpayers will have to foot the bill for the subsidies, and the low return on investments may block initiatives to build rental housing. Yet high rents can lead to reduced demand and thus to cut-backs in housing construction. Many indicators express the point at which the balance is right. In addition, they reflect the context, which determines whether an indicator is beneficial or not. If a building permit can be arranged in one day, this is a favorable sign; the housing supply is thus able to respond to increasing demand. But if a building permit application takes six months to process, this might point to an adequate quality control and a strong role of physical planning and environmental policy. That would enhance not only the quality of the dwelling but also the quality of the residential area and the environment, which is conspicuous by its absence among the present housing indicators.

10 Conclusions Researchers as well as policy-makers could level many points of criticism at the methodology and the applicability of the housing indicators in regard to the formulation and monitoring of housing policies. There may be various reasons to amend the indicators. Some of them should be dropped, others added, and yet others redefined. And this is just what the Housing Indicators Team did on the basis of their initial experiences. The Housing Indicators presented in Appendix II have already been updated and amended. Nonetheless, further amendments are foreseen. If the indicators are maintained for a few years, the raw data may be used not only for cross-section analysis but also for time series analysis. This could make a substantial contribution to the utility of the housing indicators. It is advisable to retain the network of country-based consultants for a longer period of time, as they can keep the information for each country up to date. The European Community may wish to conduct a similar exercise in Europe. Of course, it remains to be seen whether the housing indicators are really useful in formulating national housing policy. In our opinion, we should not have high expectations of their utility. The value of the housing indicators seems to emerge primarily when they are used to compare national housing policies and to define the procedures for harmonizing housing policies. At present, the Housing Indicators Team is comparing all 52 participating countries. This is an interesting exercise. They could also consider conducting a 228

more narrowly focused study in the future. For instance, they might apply the indicators to developing countries. The results could serve as a basis for comparison of West European countries, which will probably undergo a gradual harmonization of housing policy. Or they could provide a basis for comparison of countries in Central and Eastern Europe, each of which is undergoing a reorientation of their housing market and housing policy at a dizzying pace. In the coming years, countless start-up problems will surely emerge in the Housing Indicators Program. But in the longer term, the program is bound to prove itself to be a unique and promising instrument for comparative housing research and comparative housing policies.

References

Mayo, Steve, 1991, Housing: Enabling Markets to Work, A World Bank Policy Paper, Washington DC, November 19. World Bank, 1991a, The Housing Indicators Program Part h Introduction, Washington DC. World Bank, 1991b, The Housing Indicators Program Extensive Survey Part Ih Indicator modules and worksheets, Washington DC. World Bank, 1992a, The Housing Indicators Program Extensive Survey Part Ih Indicator modules and worksheets update and revisions (march 1992), Washington DC. World Bank, 1992b, The Housing Indicators Program Extensive Survey. Preliminary Results (June 1992), Washington DC.

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APPENDIX I Overview of countries and cities included in the Extensive Survey of the Housing Indicators Program 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52

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Country

City

Czechoslovakia Hungary Poland Tanzania Bangladesh Malawi Madagascar Nigeria China India Pakistan Kenya Ghana Indonesia Philippines Senegal Zimbabwe Egypt Cote d'Ivoire Morocco Thailand Jamaica Ecuador Colombia Tunisia Turkey Jordan Chile Mexico Malaysia Brazil South Africa Algeria Venezuela Korea Greece Spain Israel Singapore Hong Kong Australia UK Netherlands Austria France Canada Germany Finland Sweden US Norway Japan

Bratislava Budapest Warsaw Dares Salaam Dhaka Lilongwe Antananarivo Ibadan Bejing New Delhi Karachi Nairobi Kumasi Jakarta Manila Dakar Harare Cairo Abidjan Rabat Bangkok Kingston Ouito Bogota Tunis Istanbul Amman Santiago Monterrey Kuala Lumpur Rio de Janeiro Johannesburg Algiers Caracas Seoul Athens Madrid Tel Aviv Singapore Hong Kong Sydney London Amsterdam Vienna Paris Toronto Munich Helsinki Stockholm Washington, D.C. Oslo Tokyo

GNP/Capita NA NA NA 160 170 180 190 290 330 340 350 370 400 440 630 650 650 660 770 830 1000 1070 1120 1180 1230 1280 1500 1510 1760 1940 2160 2290 2360 3250 3600 4800 7740 8650 9070 9220 12340 12810 14520 15470 16090 16960 18480 18590 19300 19840 19990 21020

APPENDIX II Provisional list of 25 Key Housing Indicators, 10 Alternate Indicators, 10 Regulatory Indicators, and 10 Alternate Regulatory Indicators

Provisional list of 25 Key Housing Indicators (used by the Housing Indicators Team in the first months of 1992) Quantity and Price Goals

Quantity indicators: Indicator 1: New Household Formation defined as the annual percentage increase in the number of new households. Indicator 2: Homelessness defined as the number of people per thousand of the urban area population who sleep outside dwelling units (e.g. on streets, in parks, railroad stations, and under bridges) or in temporary shelter in charitable institutions. Indicator 3: Housing Production defined as the total number of units (in both the formal and informal sectors) produced last year per 1000 population. Indicator 4: Housing Investment defined as the total investment in housing (in both formal and informal sectors in the urban area), as a percentage of gross city product.

Price Indicators: Indicator 5: The House-Price-to-Income Ratio defined as the ratio of the median free-market price of a dwelling unit and the median household income. Indicator 6: The Rent-to-Income Ratio defined as the ratio of the median annual rent of a dwelling unit and the median annual household income of renters. Indicator 7: House Price Appreciation defined as the annual rate of change of house prices, measured as a weighted average of all sales during the most recent year.

Housing Quality Indicators

Structure and Density: Indicator 8: Floor Area Per Person defined as the median usable living space per person last year. Indicator 9: Permanent Structures defined as the percentage of structures of permanent materials.

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Infrastructure Services: Indicator 10: Water Connection defined as the percentage of dwelling units with a water connection in the plot they occupy. Indicator 11: Journey to Work defined as the median length in minutes of a one-way commute in the urban area excluding home-based workers.

Tenure: Indicator 12: Unauthorized Housing defined as the percentage of the total housing stock in the urban area which is not in compliance with current regulations.

Choice: Indicator 13: Residential Mobility defined as the percentage of all households who moved their unit last year (including newly formed households). Indicator 14: The Vacancy Rate defined as the percentage of the total number of completed dwelling units which are presently unoccupied. Indicator 15: Owner-Occupancy defined as the percentage of all dwelling units which are owned by their occupants. Indicator 16: Residential Segregation defined as the percentage of the urban population living in the largest contiguous low-income settlement in the urban area.

Housing Demand-Side Indicators Financial Indicators: Indicator 17: The Housing Credit Portfolio defined as the ratio of total mortgage loans to all outstanding loans in both commercial and government financial institutions. Indicator 18: The Credit-to-Value Ratio det'med as the ratio of mortgage loans for housing last year to total investment in housing (in both the formal and informal sectors) last year.

Fiscal Indicators: Indicator 19: Housing Subsidies defined as housing subsidies as a percentage of the government budget last year. Indicator 20: Targeted Subsidies defined as the percentage of housing subsidies reaching below-median-income households.

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Housing Supply Indicators Inputs: Indicator 21: The Land Development Multiplier defined as the average ratio between the median land price of a developed plot at the urban fringe in a typical subdivision and the median price of raw, undeveloped land in an area currently being developed. Indicator 22: Infrastructure Expenditure Per Capita defined as the ratio of the total expenditures (operations, maintenance, and capital) by all levels of government on infrastructure services (roads, sewerage, drainage, water supply, electricity and garbage collection) during the current year to the size of the urban population. Indicator 23: Construction Cost defined as the present replacement cost (Iabor, materials, on-site infrastructure, management and contractor profits) per square meter of a median-priced dwelling unit. Labor and Management: Indicator 24: Industrial Concentration defined as the percentage of new formal-sector housing units constructed by the five largest developers (either private or public) in the urban area last year. Indicator 25: The Skill Ratio defined as the ratio between the median wage of a construction worker with at least five years of experience in a skilled trade, e.g. carpentry or masonry, and the median wage of an unskilled construction worker.

Provisional list of 10 Alternate Indicators Indicator AI: Households Per Dwelling Unit defined as the ratio between the total number of households and the total number of dwelling units of all types in the urban area during the current year. Indicator A2: Persons Per Room defined as the ratio between the median number of persons in a dwelling unit and the median number of rooms in a dwelling unit. Indicator A.3: Squatter Housing defined as the percentage of the total housing stock in the urban area which is currently occupying land illegally. Indicator A4: New Housing Credit defined as the ratio of new mortgage loans to all new loans in both commercial and government financial institutions made last year.

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Indicator A5: Mortgage-to-Prime Difference defined as the average difference in percentage points between interest rates on mortgages in both commercial and government financial institutions and the prime interest rate in the commercial banking system. Indicator A6: Mortgage-to-Deposit Difference defined as the average difference in percentage points between interest rates on mortgages in both commercial and government financial institutions and the interest rate on one-year deposits in the commercial banking system. Indicator A7: Mortgage Default Rate defined as the percentage of mortgage loans which are three or more months in arrears in both commercial and government financial institutions. Indicator A8: Land Concentration defined as the share of vacant land in the urban area owned by the five largest public, customary, or private land holders. Indicator A9: Import Share of Construction defined as the percentage share of residential construction materials which are imported (in value terms). Indicator A10: Construction Time defined as the median time (in months) from the start of construction to completion of a medianpriced dwelling unit.

I n a d d i t i o n to t h e s e 25 key and 10 a l t e r n a t e indicators, d a t a s h o u l d also b e c o l l e c t e d in t h e e x t e n s i v e surveys c o n c e r n i n g the 10 r e g u l a t o r y indicators, a n d t h e 10 a l t e r n a t e r e g u l a t o r y . T h e s e a r e d e f i n e d below: P r o v i s i o n a l list o f 10 R e g u l a t o r y I n d i c a t o r s Indicator RI: Restrictions on Exchange defined as a composite of questions on the extent of ownership and transfer restrictions in land, housing, and building materials. Indicator R2: Land Registration Coverage defined as the percentage of the metropolitan area covered by a land registration system which allows for buying, selling, long-term leasing, or mortgaging urban land, Indicator R3: Housing Finance Development defined as a composite of questions on the presence and flexibility of housing finance institutions and instruments, Indicator R4: Public Sector Involvement defined as the percentage of annual housing production under the direct control and ownership of public housing corporations. Indicator RS: Rental Price Distortion defined as the ratio of the median controlled rent of the typical private-sector rent-controlled unit to the free-market rent of a comparable unit in the uncontrolled part of the market.

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Indicator R6: Permits Delay defined as the median length in months to get approvals, permits, and titles for a new mediumsized (50-200 unit) residential subdivision in an area at the urban fringe where residential development is permitted. Indicator R7: Minimum Lot Size defined as the minimum lot size for a single-family housing unit in a new 50-200 unit residential subdivision. Indicator R8: Compliance defmed as the ratio of building permits issued to new housing starts in both the formal and informal sectors during the past year. Indicator R9: Squatter Tolerance defined as the difference between the number of squatter dwelling units for which tenure has been regularized last year and the number of squatter dwelling units demolished last year without resettlement. Indicator R10: Effective Property Tax Rate defined as the percentage of the real market value of residential property which is collected as property tax.

P r o v i s i o n a l list o f 10 A l t e r n a t e R e g u l a t o r y I n d i c a t o r s Indicator RAI: Public Land Ownership defined as the estimated percentage of total urban land, including developable raw land at the urban fringe that is publicly owned, including parastatals, land banks, and expropriations. Indicator RA2: Customary Land Ownership defined as the estimated percentage of total urban land, including developable raw land at the urban fringe that is owned by religious, customary, tribal, clan, or trust owners. Indicator RA3: Cement Price Distortion defined as the ratio of the free-market to the official price for cement. Indicator RA4: Extent of Rent Control defined as the percentage of the rental stock, including informal rentals, under the coverage of a rent control system. Indicator RA5: Rent Control defined as a composite of questions on the stringency of rent control. Indicator RA6: Foreclosure Delay defined as the typical time in months from the beginning to the conclusion of foreclosure proceedings on a seriously delinquent mortgage. Indicator RA7: Rental Eviction Delay def'med as the typical time in months to evict a private-sector rental tenant for non-payment of rent.

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Indicator RA8: Salable Land Ratio defined as the ratio of the maximum net salable residential land to the total undeveloped land area in a new middle-sized (50-200 unit) residential subdivision. Indicator RA9: Land Development Controls defined as a composite of questions on the affordability of land use and building code regulations. Indicator RA10: Property Tax Receipts defined as the percentage of property tax receipts in the local government budget.

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APPENDIX III From housing policy goals to housing indicators

The relation between housing policy goals and housing indicators (see Appendix II) as determined by the Housing Indicators Team is shown in the following overview (see Introduction, pp. 17-19). Housing Policy Goals (1)

Quantity and Price Goals: Adequate Housing for All

Affordability

(2)

Quality Goals: Reduction of Overcrowding

Durability Provision of Basic Services Accessibility Security of Tenure Choice

(3)

Demand-Side Goals: Development of Housing Finance

Development of Fiscal Policy Subsidies for Low-Income Groups

(4)

Supply-Side Goals: Residential Land Development

Infrastructure Provision Low-Cost Construction Reorganizing the Building Industry Construction Labor Force Development

(5)

No.

Housing Indicators

1 A1 2 3 4 5 6 7

New Household Formation (Households Per Dwelling Unit) Homelessness Housing Production Housing Investment House-Price-to-Income Ratio Rent-to-Income Ratio House Price Appreciation

8 A2 9 10 11 12 A3 13 14 15 16

Floor Area Per Person (Persons Per Room) Permanent Structures Water Connection Journey to Work Unauthorized Housing (SquatterHousing) Residential Mobility The Vacancy Rate Owner Occupancy Residential Segregation

17 18 A4 A5 A6 A7 19 20

The Housing Credit Portfolio The Credit-to-Value Ratio (New Housing Credit) (Mortgage-to-Prime Difference) (Mortgage-to-Deposit Difference) (Mortgage Default Rate) Housing Subsidies Targeted Subsidies

21 A8 22 23 A9 A10 24 25

The Land Development Multiplier (Land Concentration) Infrastructure Expenditure Per Capita Construction Cost (Import Share of Construction) (Construction time) Industrial Concentration The Skill Ratio

Regulatory and Institutional Reform Goals: Housing Market Development R1

Restrictions on Exchange

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Land Market Development Housing Finance Development Public Sector Involvement Low Price Distortions

Removing Bureaucratic Bottlenecks Affordable Standards Compliance with Regulations Squatter Tolerance Housing as a Local Tax Base

(6)

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Broad Soeio-Economic-lmpact Goals: Alleviation of Poverty Controlling Inflation Generating Household Savings Generating Income Growth Increasing Productivity Generating Investment Growth Reducing the Balance of Payments Deficit Reducing the Government Deficit

R2 RA1 RA2 R3 R4 R5 RA3 RA4 RA5 R6 RA6 RA7 R7 RA8 RA9 R8 R9 R10 RA10

Land Registration Coverage (Public Land Ownership) (Customary Land Ownership) Housing Finance Development) Public Sector Involvement Rental Price Distortion (Cement Price Distortion) (Extent of Rent Control) (Rent Control) Permits Delay (Foreclosure Delay) (Rental Eviction Delay) Minimum Lot Size (Salable Land Ratio) (Land Development Controls) Compliance Squatter Tolerance Effective Property Tax Rate (Property Tax Receipts) Under-Five Mortality Rate The Rate of Inflation The Household Savings Rate Manufacturing Wage Growth Manufacturing Productivity Capital Formation Balance of Payments Deficit The Government Deficit