duncan - updated china index of housing...

China Index of Housing Affordability by City (CIHAC)

www.eiu.com

China index of housing affordability by city (CIHAC)

© The Economist Intelligence Unit Limited 20141

Contents

The index 2

Introduction 2

Methodology 7

Questions on the methodology 8



IntroductionThe Economist Intelligence Unit has developed the China Index of Housing Affordability by City (CIHAC) to shed light on housing affordability in the country. The explosion in China’s real estate market over the past decade has resulted in rocketing house prices. Although this has brought about positive wealth effects and stoked a boom in real-estate development, the difficulty that many urban households now experience in getting onto the property ladder has become a major social problem and a potential source of unrest. The Chinese government has since 2010 imposed restrictions on property purchases in an effort to stifle speculative demand and keep a lid on price inflation. It has also launched an ambitious affordable housing construction programme. At the same time, income growth has been rapid and it is not clear whether the high headline rates of house-price growth are justified by market fundamentals.

We have created the CIHAC to evaluate the tightrope effort of bringing house prices to more affordable levels while not risking the financial instability that would stem from a disorderly property market crash. The index measures housing affordability across 40 major cities, of varying size, and spanning all regions of China. This gives a picture of the situation faced by the average Chinese household, rather than by wealthy elites and resident foreigners. Housing affordability is defined as the average cost of a 100-sq m apartment in a given month, divided by our estimates of the average urban household income in that city for the current year. The approach taken in creating the CIHAC is consistent with methodologies used by other major housing affordability indices, but provides new information by utilising our unique city-level household income forecasts for China, to enable a consistent comparison between house prices and income.

It is important to note that, unlike some property price indices, the CIHAC is not based on like-for-like sales. China’s cities are expanding, so in order to understand affordability it is important to consider the expansion of cities and the construction of lower-cost housing further from the centre. The question that we are trying to understand is how, for the average worker in a Chinese city, average house prices compare to average income.

The main sources of data are the National Bureau of Statistics (NBS) and proprietary data from the The Economist Intelligence Unit’s Access China service. The CIHAC stretches back to March 2010, with results presented in terms of a three-month rolling average figure. We plan to regularly update the index in order to assess the impact of ongoing developments in China’s property sector.

The index



MethodologyCalculating average cost of a 100-sq m residential houseThe NBS provides data for 40 cities on year-to-date (YTD) residential housing sales measured by floorspace and value.

We have broken these YTD figures out into monthly figures (m). The technique for working out sales in month n is: m=n- (n-1). For most cities, data is not provided for January-February. In this case, monthly floorspace and monthly value of sales for January-March are assumed to be equal to one-third of the YTD sales for March. For Beijing, Chongqing, Shanghai and Tianjin the government provides data for January-February sales. Monthly data in each of January and February are assumed to be equal to one-half of this. The use of a three-month rolling average reduces the chance that the index will be biased owing to this missing data.

Monthly value of sales is divided by monthly floorspace sales to generate estimated cost per square metre. This is then multiplied by 100 for the cost of a 100-sq m residential house. House prices in China are typically measured in per-square-metre terms rather than by property.

Calculating average urban household incomeThe CIHAC uses a combination of historic average urban household income data derived from the NBS and forecasts developed by The Economist Intelligence Unit’s Access China service. The NBS provides average urban household income per head at the city level for the 40 cities in the index, which have been used as the basis for the forecasts developed by our Access China service. We then multiply this by the NBS figure for the average number of working people per household. (This last figure is a national level average, which is applied to all of the 40 cities.) The data is generated as an annual average.

The average urban household income data for the previous 12 months is generated based on these annual averages, which are allocated proportionately. So, for example, the average urban household income for the previous 12 months in May 2013 would be (5/12*(2013 annual average))+(7/12*(2012 annual average).



Questions on the methodologyHow does this methodology compare with other housing affordability systems?There is no standard system for measuring housing affordability. However, many of the systems adopted internationally measure affordability by contrasting house prices against income or rents. Rental data is not sufficiently robust to be used in China yet, so we adopt the comparison against incomes.

Some systems generate average house prices across all units sold, others (such as the IMF’s price-income ratio) take a standard size house and work out affordability on that base. We adopt the latter approach, given that pricing per square metre is commonly discussed in China and that relevant data is available. House price data can be derived from either official or appropriate non-governmental sources.

Some systems adopt a per-head income measure (as in the UK), some use household income as the relevant metric. We adopt the latter, as we feel that it is more suitable and more widely used. However, housing tends to be owned individually rather than collectively (by all earning members of the household) in China, which means that the debate has strong points on both sides. Household surveys are usually the method for gathering income data.

Why do you choose 100-sq m?China’s housing market is usually discussed in terms of cost per square metre, not overall house prices. We did research on data derived from the China Index Academy’s China Real Estate Index System/Soufun, which suggests that the average house size in China is close to 100 sq m.

There is some variation in average house size between different cities— average house sizes in Xiamen, Suzhou, Guangzhou and Wenzhou, for example, seem to be significantly higher than this, while those in Chongqing and Kunming tend to be significantly smaller. This means that the CIHAC may make housing in places like Xiamen look more affordable than it is. However, data dealing with average house sizes are patchier than those for sales by floorspace and value, covering a much smaller city sample. There are also issues relating to cross-comparability with the NBS data. Therefore, we feel that there are significant advantages to using a standard “average house size” for all cities.

Why do you use NBS figures?While there are flaws with the NBS numbers, their data set is broad (covering a wide range of cities) and allows a degree of consistency that would be lost if other sources were used. The Economist Intelligence Unit’s Access China service works closely with the NBS so has a strong understanding of the methods that it uses and the relative strengths and weaknesses of different NBS data. Its own figures are designed to fit well with those of the NBS.

How valid is the system for breaking out sales into monthly data?It is not ideal to break the YTD data into monthly figures by the methods given above. The YTD figures often include revisions for previous months, a problem that often seems to produce abnormally large



distortions in the December month when breaking out the figures monthly. However, the NBS does not provide relevant monthly figures, so this is seen as the best option available.

Why do you use a three-month rolling average?The problems of breaking out monthly figures are smoothed by the application of a three-month rolling average. In addition, some of the 40 cities covered in the index have lower levels of transactions or weaker statistical collection systems, which can lead to high levels of volatility in the monthly data. This is also reduced through the use of three-month rolling averages.



Access China Access China is a unique service that will help your business to succeed in China. It is the only single source of data, analysis and forecasts for all 31 provinces and 287 of China’s largest cities, providing you with a comprehensive understanding of the country today. More importantly, it will give you confidence that you will still understand China in 10 and 20 years’ time.What will Access China allow you to do?

l Benchmark in detail the provinces and prefectures of China, using consistent and comparable data.

l Understand the market potential for your products and services in any location within China.

l Investigate operating costs, infrastructure development and labour markets to help you to make investment decisions.

l Monitor what other businesses are doing in various regions.

l Gain a forward-looking perspective on how quickly China’s cities and its regions are growing.

l Feed reliable data into your own China business strategy models.

www.eiu.com/china

While every effort has been taken to verify the accuracy of this information, The Economist Intelligence Unit Ltd. cannot accept any responsibility or liability for reliance by any person on this report or any of the information, opinions or conclusions set out in this report.

Cover image - © zhangyang13576997233/Shutterstock

LONDON20 Cabot SquareLondonE14 4QWUnited KingdomTel: (44.20) 7576 8000Fax: (44.20) 7576 8500E-mail: [email protected]

NEW YORK750 Third Avenue5th FloorNew York, NY 10017United StatesTel: (1.212) 554 0600Fax: (1.212) 586 1181/2E-mail: [email protected]

HONG KONG6001, Central Plaza18 Harbour RoadWanchai Hong KongTel: (852) 2585 3888Fax: (852) 2802 7638E-mail: [email protected]

GENEVARue de l’Athénée 321206 GenevaSwitzerlandTel: (41) 22 566 2470Fax: (41) 22 346 93 47E-mail: [email protected]

duncan - updated china index of housing...

Documents