International Wealth Index

(IWI)

Jeroen Smits

Global Data Lab / Nijmegen Center for Economics

Radboud University, The Netherlands

j.smits@fm.ru.nl

This presentation

• Welfare measurement in poor countries

• Asset based wealth indices

• International Wealth Index (IWI)

• Reliability tests of IWI

• Comparison with other measures

• Poverty measurement

Measuring the economic situation of households

in poor countries

• Income

- Often unstable

- Not always in cash

- Reporting errors

• Consumption/expenditure

- Expensive surveys

- Comparability issues

- Reporting errors

• Alternative: Asset based wealth index

Asset based wealth indices

• Widely used since 2000 for analyzing variation in health, education, poverty etc.

• Households are ranked by asset ownership:

- Consumer durables (TV, fridge, car)

- Housing characteristics (quality of building material, toilet facility, number of rooms)

- Access to basic services (water, electricity)

• Assets are entered into a Principal Component Analysis and first factor chosen as wealth index

• Indicate longer-term socio-economic position, living standard, or welfare of households

Advantages of wealth indices

• Reliability of measurement: Assets included are

easily observable by interviewer

• Intuitive appeal: These are assets that the large

majority of us wants to own (or at least buys when

having the possibility)

• Ease of computation: Asset coefficients are added

up to get the index

• Widely available in household surveys for developing

countries (DHS, MICS)

• Very much used!

Disadvantages of existing indices

• For each survey a new index is constructed on the basis of the

available assets (which differ between surveys).

• Indices are completely tailored towards the situation in the

country/year for which they are made

• Wealth index is standardized variable, values of households

have no absolute meaning.

• Meaning is usually given by dividing values into quintiles, with

the lowest quintile including the 20 percent poorest households

and the highest quintile the 20 percent richest households.

• However, lowest quintile in Ethiopia much poorer than lowest

quintile in Malaysia.

Conclusion: Available indices are not comparable across

countries and years

International Wealth Index (IWI)

• First strictly comparable index that can be used for all low and

middle income countries

• Construction similar to traditional wealth indices, but using data

from many surveys instead of one

• Data on 2.1 million households derived from 165 surveys held

between 1996 and 2011 in 97 developing countries

• A household’s ranking on IWI indicates to what extent the

household possesses a basic set of assets, valued highly by

people across the globe

• Any household for which the required asset information is

available can be ranked on IWI and any household with the

same combination of assets is ranked the same.

Assets included

• Whether a household or one of its members owns a

TV, Refrigerator, Phone, Car, Bicycle, Cheap utensil,

Expensive utensil (yes/no)

• Access to electricity (yes/no)

• Quality of Floor material, Toilet facility, Water supply

(low, middle, high quality)

• Number of rooms for sleeping (0 or 1, 2, 3 or more)

• 12 assets measured by 20 indicators

Consumer durables Weights

Television 8.612657

Refrigerator 8.429076

Phone 7.127699

Car 4.651382

Bike 1.84686

Cheap utensils 4.118394

Expensive utensils 6.507283

Housing characteristics

Floor material:

Low quality -7.558471

Medium quality 1.227531

High quality 6.107428

Toilet facil ity:

Low quality -7.439841

Medium quality -1.090393

High quality 8.140637

Number of rooms:

Zero or one -3.699681

Two 0.38405

Three or more 3.445009

Public utilities

Access to electricity 8.056664

Water source:

Low quality -6.306477

Medium quality -2.302023

High quality 7.952443

Constant 25.00447

Table 1. Asset weights for IWI formula

• To compute IWI for a specific household, the

household’s values on the indicators are

multiplied with the asset weights in Table 1 and

summed up

• IWI runs from zero to 100 with 0 for households

having none of the durables and lowest quality

housing, and 100 for households having all

durables and highest quality housing

• To add IWI to a new household survey, no new

PCA analysis is needed, but the IWI formula is

used to rank every household on the IWI scale.

• Separate formulas are available for households

for which one or two items are missing

Using IWI

Table 2. Pearson correlations between IWI based on

all 12 assets and reduced IWIs based on 11 assets

IWI without: Correlation

- water 0.986

- toilet 0.987

- rooms 0.996

- floor 0.991

- electricity 0.996

- TV 0.996

- refrigerator 0.996

- phone 0.996

- car 0.999

- bicycle 0.999

- cheap utensil 0.999

- expensive utensil 0.997

IWI doe not depend on a specific asset

IWI doe not depend on data for a specific region

or time period

Pearson correlations between IWI and wealth indices

with data for time period specific wealth indices

Years correlation

1996-2000 0.999

2001-2005 0.999

2006-2011 0.997

Pearson correlations between IWI and wealth indices with data for a global

region removed and between IWI and region-specific wealth indices

Global region Region removed Region-specific

index

Asia 0.999 0,998

Sub-Saharan Africa 0.999 0,996

Latin America 0.999 0,998

Middle East and North Africa (MENA) 0.999 0,999

Correlations with HDI and components

Table 4. Pearson correlations of IWI with HDI and its components

IWI

Life expectancy

a .841 Life exp

GNIc

a .788 .672 GNIc

Exp. years of education

a .720 .651 .682 Exp. edu

Mean years of education

b .658 .559 .538 .728 Mean edu

HDIb .899 .870 .835 .833 .808

a N=87

b N=85

IWI-based poverty measures

• Percentiles of the IWI distribution can be used as poverty lines

• Comparison with 1.25$ and 2$ headcount ratios and MPI

• High correlations, especially of IWI-30 with MPI and IWI-50 with

2$ headcount ratio

Pearson correlations of IWI-based poverty lines with headcount ratios (N=76) and the Multidimensional Poverty Index (N=69)

Headcount 1.25$ Headcount 2.00$ MPI

IWI Pov20 0.845 0.839 0.894

IWI Pov30 0.875 0.886 0.911

IWI Pov40 0.874 0.906 0.907

IWI Pov50 0.860 0.914 0.887

IWI Pov60 0.835 0.906 0.855

Conclusions

• IWI is a simple, understandable and stable indicator of the

economic situation of households, regions and countries across

the developing world

• Test analyses show that IWI hardly depends on the inclusion of a

specific asset, nor on data for a specific region or time period

• The stability might mean that there is some kind of universal

human asset preference that does not differ much across place

and time

• IWI is highly correlated with the HDI and its components

• IWI can be used to create poverty measures that are highly

correlated with headcount ratios and MDI

• IWI can be used for studying sub-national differences and trends

Database Developing World

www.globaldatalab.org

DHS MICS (2000/2005/6) PAPFAM, SIMPOC, IPUMS & Other