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October 2019

Research

Institute

Global wealth databook 2019

Thought leadership from Credit Suisse and the world's foremost experts 2

Preface

For the past ten years, the Credit Suisse

Research Institute"s Global wealth report has

been the leading reference on global household wealth. It contains the most comprehensive and entire wealth spectrum - from the very base of the “wealth pyramid," covering 2.9 billion adults with wealth below USD 10,000, to those at the apex of the wealth pyramid, who comprise less than 1% of the adult population, but own 44% of household wealth. During the 12 months to mid-2019, aggregate global wealth rose by USD

9.1 trillion (2.6%) to a combined total of USD

361 trillion. Wealth per adult grew by a modest

1.2%, although global average wealth achieved

yet another record high of USD 70,850 per adult.

While the Global wealth report highlights the

main features of global wealth holdings in recent years, the Credit Suisse Research Institute"s

Global wealth databook provides a great deal

more detail. It presents a considerable quantity of additional data on the level and distribution of household wealth across countries, as well as describing the data sources used in the project and the methodology used to obtain the pub- lished results. This level of detail sets it apart

ɇResearch for the Global wealth report and

Global wealth databook has been undertaken on

b ehalf of the Credit Suisse Research Institute b y Professors Anthony Shorrocks and Jim

Davies, recognized authorities on this topic,

a ssisted by D r . Rodrigo Lluberas. The Credit S uisse Research Institute is Credit Suisse"s i n-house think tank. The Institute was estab crisis with the objective of studying long-term e conomic developments, which have - or promise to have - a glob al impact within and beyond the

The Global wealth databook provides estimates

for the level and distribution of wealth for over

200 countries for the period 2000 to mid-2019.

It covers the pattern and trend of household

wealth at both the regional and country levels. T o mark its tenth anniversary, this year"s report examines in more detail the underlying factors which help explain the evolution of wealth levels and wealth distribution. Particular attention is paid to the growing importance of China and other emerging economies, especially in the they became the dominant contributor to global wealth creation.

Nannette Hechler-Fayd"herbe

Wealth Management

Global Head of Economics & Research

Global wealth databook 2019 3

2 Preface

4 Section 1 Estimating the pattern of global household wealth

9 Table 1-1 Coverage of wealth levels data

10 Table 1-2 Household balance sheet and financial balance sheet sources

12 Table 1-3 Survey sources

14 Table 1-4 Changes in asset prices and exchange rates 2018DZ19, selected countries

15 Table 1-5 Wealth shares for countries with wealth distribution data

17 Section 2 Household wealth levels, 2000DZ19

19 Table 2-1 Country details

23 Table 2-2 Population by country (thousands)

27 Table 2-3 Number of adults by country (thousands)

31 Table 2-4 (by year) Wealth estimates by country 2000DZ19

111 Table 2-5 Components of wealth per adult in USD, by region and year

112 Table 2-6 Components of wealth as percentage of gross wealth, by region and year

113 Table 2-7 Changes in household wealth 2018DZ19, selected countries

114 Section 3 Estimating the distribution of global wealth

117 Table 3-1 Wealth pattern within countries, 2019

121 Table 3-2 Wealth pattern by region, 2019

122 Table 3-3 Membership of top wealth groups for selected countries, 2019

123 Table 3-4 Percentage membership of global wealth deciles and top percentiles by country of residence, 2019

127 Table 3-5 Main gains and losses in global wealth distribution, 2018DZ19

128 Table 3-6 High net worth individuals by country and region, 2019

130 Section 4 The evolution of wealth levels

134 Table 4-1 Global trends in assets and debts per adult (in USD), 2000DZ19

134 Table 4-2 Annual growth (%) of wealth per adult using alternative currency units, selected countries, 2000DZ19

135 Table 4-3 Annual growth (%) of real wealth per adult (in real USD) and contribution by country type, 2000DZ19

135 Table 4-4 Savings rate versus growth of wealth per adult, 2000DZ19, selected countries

136 Table 4-5 Growth of wealth versus growth of GDP (in real USD), 2000DZ19, selected countries

136 Table 4-6 Ratio of wealth to GDP for selected countries and country type, various years

137 Section 5 The evolution of wealth distribution

143 Table 5-1 World wealth inequality, 2000DZ19

143 Table 5-2 Mean wealth per adult (2019 USD) by country type: 2000DZ19

144 Table 5-3 Wealth share of top 1% by country type, 2000DZ19

144 Table 5-4 Wealth share of top 10% by country type, 2000DZ19

145 Table 5-5 Financial assets as % of total assets by wealth group, selected countries

145 Table 5-6 Change in the wealth share of the top 1% and top 10% versus change in the ratio of market capitalization to

house prices and change in adult population, selected countries

146 Table 5-7 Change in number of USD millionaires by country type, 2000DZ19 (thousands)

147 Table 5-8 Decomposition of the change in number and wealth of USD millionaires since 2000, selected countries

147 Table 5-9 Number of women in the United States Forbes 400 list, 1990DZ2018

147 Table 5-10 Incidence of inheritance by age, selected OECD countries

148 Section 6 Composition of wealth portfolios

151 Table 6-1 Assets and debts as percentage of gross household wealth for selected countries by year

153 Table 6-2 Percentage composition of gross household financial wealth, by country and year

156 Section 7 Region and country focus

162 Table 7-1 Summary details for regions and selected countries, 2019

163 Table 7-2 Wealth per adult (USD) at current and smoothed exchange rates, for regions and selected countries, 2000DZ19

165 Table 7-3 Total wealth (USD trn) at current and constant exchange rates, for regions and selected countries, 2000DZ19

167 Table 7-4 Composition of wealth per adult for regions and selected countries, 2019

168 Table 7-5 Wealth shares and minimum wealth of deciles and top percentiles for regions and selected countries, 2019

169 Table 7-6 Distribution of wealth for regions and selected countries, 2019

172 Bibliography and data references

175 About the authors

176 General disclaimer / Important information

4

1.1 Introduction

We provide estimates of the wealth holdings of

households around the world for each year since

2000. More specifically, we are interested in the

distribution within and across nations of individual net worth, defined as the marketable value of financial assets plus non-financial assets (princi- pally housing and land) less debts. No country in the world has a single comprehensive source of information on personal wealth, and many low- and middle-income countries have little direct evidence of any kind. However, a growing number of countries DZ including China and India as well many high-income countries DZ have rele- vant data from a variety of different sources which we are able to exploit in order to achieve our objective. The procedure involves three main steps, the first two of which follow the structure set out in Davies et al. (2008, 2011). (See also Davies et al.,

2017.) The first step establishes the average level

of wealth for each country. The best source of data for this purpose is household balance sheet (HBS) data, which are now provided by 50 coun- tries, although 25 of these countries cover only financial assets and debts. For an additional three countries wealth levels can be calculated from household survey data. Together these countries cover 65% of the global population and 95% of total global wealth. The results are supplemented by econometric techniques, which generate esti- mates of the level of wealth in countries that lack direct information for one or more years.

The second step involves constructing the pat-

tern of wealth holdings within nations. We use direct data on the distribution of wealth for 36 countries. Inspection of data for these countries suggests a relationship between wealth distribu- tion and income distribution, which can be exploited in order to provide a rough estimate of wealth distribution for 136 other countries, which have data on income distribution but not on wealth ownership.

It is well known that the traditional sources of

wealth distribution data are unlikely to provide an accurate picture of wealth ownership in the top tail of the distribution for most countries. To over- come this deficiency, the third step makes use of the information in the Forbes world list of billion- aires to adjust the wealth distribution pattern in the highest wealth ranges.

Implementing these procedures leaves 37 coun-

tries for which it is difficult to estimate either the level of household wealth or the distribution of wealth, or both. Usually the countries concerned are small (e.g. Andorra, Bermuda, Guatemala,

Monaco) or semi-detached from the global

economy (e.g. Cuba, Somalia, North Korea). For our estimates of the pattern of global wealth, we assign these countries the average level and distribution of the region and income class to which they belong. This is done in preference to omitting the countries altogether, which would implicitly assume that their pattern of wealth holdings matches the world average. However, checks indicate that excluding these nations from the global picture would make little difference to the results.

Table 2-1 lists the 211 countries in the world

along with some summary details. Note that

China and India are treated as separate regions

due to the size of their populations. The following sections describe the estimation procedures in more detail. Two other general points should be mentioned at the outset. First, we use official exchange rates throughout to convert currencies to our standard measure of value, which is US dollars at the time in question. In international comparisons of consumption or income it is common to convert currencies using purchasing power parity (PPP) exchange rates, which take account of local prices, especially for non-traded services. However, in all countries a large share of personal wealth is owned by households in the top few percentiles of the distribution, who tend to be internationally mobile and to move their as- sets across borders with significant frequency.

For such people, the prevailing foreign currency

rate is most relevant for international compari- sons. So, there is a stronger case for using official exchange rates in studies of global wealth.

Global wealth databook 2019 5

The second issue concerns the appropriate unit

of analysis. A case can be made for basing the analysis on households or families. However, personal assets and debts are typically owned (or owed) by named individuals, and may be retained by those individuals if they leave the family.

Furthermore, even though some household

assets, such as housing, provide communal benefits in households that include members other than a single individual or married couple, it is unusual for members to have an equal say in the management of assets, or to share equally in the proceeds if the asset is sold. Membership of households can be quite fluid (for example, with respect to older children living away from home) and the pattern of household structure varies markedly across countries. For all these reasons DZ plus the practical consideration that the number of households is unknown in most countries DZ we prefer to base our analysis on individuals rather than household or family units. More specifically, since children have little formal or actual wealth ownership, we focus on wealth ownership by adults, defined to be individuals aged 20 or above.

1.2Household balance sheet data

The most reliable source of information on

household wealth is household balance sheet (HBS) data. As shown in Table 1-ǷǸ financial and non-financial balance sheet data are available for 25 countries for at least one year.

These are predominantly high-income countries,

the exceptions being China, Mexico and South Africa, which fall within the upper middle- income category according to the World Bank. The data are described as complete if financial assets, liabilities and non-financial assets are all ade- quately covered. Another 25 countries have financial balance sheets, but no details of real assets. This group contains nine upper middle income countries and six lower middle income countries, and hence is less biased towards the rich world than the group with complete house- hold balance sheets. The sources of these data are recorded in Table 1-2.

Europe and North America, and OECD countries

in particular, are well represented among coun- tries with HBS data. China joined this group last year. There has been considerable recent discus- sion of the household balance sheet in China. Li (2017) surveys the series that have been devel- oped by different researchers. Piketty et al. (2017, 2018) provide the most comprehensive data and also the longest times series, so we use their estimates here. Li (2017) shows that his own independent estimates, which are for 2004DZ

14 only, are similar to those of Piketty et al.,

(2017) if farmland is omitted from the latter. This provides support for the accuracy of the Piketty et al. estimates, but also a reason to prefer them in addition to the greater length of their time series, since farmland is a key household asset in rural China. Piketty et al. estimate the value of this land carefully, taking into account its increas- ingly private character over time.

HBS coverage is sparse in Africa, Asia and Latin

America. Fortunately, survey evidence on wealth

is available for the two largest developing coun- tries without HBS data DZ India and Indonesia DZ which compensates to some extent for this defi- ciency. Although only financial HBS data are available for Russia and nine other transition countries aside from China, complete HBS data are available for the Czech Republic and

Hungary.

1.3 Household survey data

Information on assets and debts is collected in

nationally representative surveys undertaken in an increasing number of countries (see Table

1-3 for our current list and sources.) For three

countries this is the only data we have, and we use it to help estimate wealth levels, as explained in the next section, as well as distributions. Data on wealth obtained from household surveys vary in quality, due to the sampling and non-sampling problems faced by all sample surveys. The high skewness of wealth distributions makes sampling error important. Non-sampling error is also a problem due to differential response rates DZ above some level wealthier households are less likely to participate DZ and under-reporting, espe- cially of financial assets. Both of these problems make it difficult to obtain an accurate picture of the upper tail of the wealth distribution using survey evidence alone. To compensate, wealthier households are over-sampled in an increasing number of surveys. This is best done using indi- vidual information, as in the US Survey of

Consumer Finances, the Household Finance and

Consumption (HFCS) surveys in Finland, France

and Spain, and the Wealth and Assets Survey (WAS) in the U.K. (Vermeulen, 2018). Over- sampling at the upper end is not routinely adopted by the developing countries which include asset information in their household surveys, but the reported response rates are much higher than in developed countries and the sample sizes are large in some cases, for example in India.

The US Survey of Consumer Finance is suffi-

ciently well designed to capture most household wealth, but this is atypical. In particular, surveysquotesdbs_dbs17.pdfusesText_23

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