Presented by: THE GLOBAL HAVE & HAVE NOT CHALLENGE Frank Badillo Chief Economist July 2013

Presented by:

THE GLOBAL HAVE & HAVE NOT CHALLENGE

Frank BadilloChief Economist

July 2013

© Copyright 2013 Kantar Retail

Copyright © 2013 Kantar Retail. All Rights Reserved.

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Disclaimers

The analyses and conclusions presented in this seminar represent the opinions of Kantar Retail. The views expressed do not necessarily reflect the views of the management of the retailer(s) under discussion.

This seminar is not endorsed or otherwise supported by the management of any of the companies covered during the course of the workshop or within the following slides.


Have Nots: Losing share of income

Income Inequality Growing Across Countries

The Haves. Are keeping or growing their share of all income earned

The Have Nots. Are losing share of income earned by all households

Producing Haves and Have Nots

Source: Kantar Retail analysis 3

Haves: Gaining share of income

Income level that divides Haves from Have Nots can differ by country

Income level that divides Haves from Have Nots can differ by country


A Broader Definition of Haves and Have Nots

Defined over long term by key attributes beyond income.

The Definers:

–Gen cohort

–Wealth

–Education

–Household type

–Urbanization

–Retirement age

Shifts focus to attributes that cause income to lag or lead


•Part of large younger, working-age cohort•Some wealth•A college degree•Married/couple•An urban resident•Plan to retire late

•Part of large younger, working-age cohort•Some wealth•A college degree•Married/couple•An urban resident•Plan to retire late

•Part of large older cohort nearing retirement•Little wealth•No college degree•Unmarried/divorced•A non-urban resident•Plan to retire early

•Part of large older cohort nearing retirement•Little wealth•No college degree•Unmarried/divorced•A non-urban resident•Plan to retire early

Attributes found at polar ends




Shaped by What Defines and Divides Them

The Definers. Mostly demographic attributes that can differ by country

The Dividers. Mostly external forces:

– Inflation

– Government austerity

External forces further divide Haves and Have Nots

5

Haves…

•Part of large younger, working-age cohort•Some wealth•A college degree•Married/couple•An urban resident•Plan to

retire late

Have Nots…

•Part of large older cohort nearing

retirement•Little wealth

•No college degree•Unmarried/divorced

•A non-urban resident•Plan to

retire early



GovernmentAusterity

Haves…

•Part of large younger, working-age cohort•Some wealth•A college degree•Married/couple•An urban resident•Plan to

retire late

Have Nots…

•Part of large older cohort nearing retirement

•Little wealth•No college degree

•Unmarried/divorced•A non-urban resident

•Plan to retire early

Source: Kantar Retail analysis


Opportunities, Threats Among Haves/Have Nots

Working-age population: Markets skewed toward older cohorts nearing retirement will yield more Have-Not behavior

Early retirement expectations: Adds to pressure on Have Nots, primarily in developed countries

Urbanization: Drives Have household gains in markets such as China, India

College-educated and married: Bull's-eye of Have household formation

Wealth effects: Skew to Haves, but can be negative or positive

Given focus on factors that define and divide them

6

Inflation pressures: Threat looms largest in emerging markets

Government austerity: Threat is greatest in developed markets, but Europe most of all

The Definers

The Definers

TheDividers

TheDividers


© Copyright 2013 Kantar RetailSource: Kantar Retail analysis 7

*Education and retirement data for India is estimated; #Household composition not available for Brazil, China, India, and Russia

These are the countries that rank at polar ends of measures for the given factor

Suggests the factor is most likely to promote Have or Have-Not behavior in that country

Mapping Factors to CountriesWhere most likely to affect Have/Have Not behavior



Brazil, Russia: Where inflation threat to Have Nots is greatest because unlikely to be offset by other factors

France, Germany, Italy, Spain, United Kingdom: Where austerity and older workforce will drive more inequality

India, China, Mexico: Where factors favor gains among Have households

Canada, Japan, United States: Where outlook is mixed for Haves and Have Nots

With focus on net impact among largest markets

8Source: Kantar Retail analysis


Have Gains Broadening Mixed Effects Have Nots Falling Back FurtherChina− Low levels of education and

wealth per capita+ No austerity pressures,

urbanization trend, late

retirement plans

Canada− Workforce skewed older+ Low inflation, high per-capita

wealth

Brazil− Inflation pressures, low levels

of education and wealth per

capita+ Late retirement plans

Russia− Inflation pressures, low per-

capita wealth, little

urbanization

India− Inflation pressures, low levels

of education and wealth+ No austerity pressures,

workforce skewed younger,

urbanization trend, late

retirement plans

Japan− Workforce skewed older,

high percentage of single-

person households, no

urbanization+ Low inflation, high levels of

education and per-capita

wealth, late retirement plans

France− Austerity, workforce skewed

older, early retirement

expectations, little

urbanization+ Low inflation, high per-capita

wealth

Spain− Austerity, workforce skewed

older, low education levels+ Low inflation, high per-capita

wealth, high percentage of

family households

Mexico− Low levels of education + No austerity pressures,

workforce skewed younger,

late retirement plans

United States− High percentage of single-

person households+ High levels of education and

per-capita wealth

Germany− Austerity, workforce skewed

older, little urbanization+ Low inflation, high per capita

wealth

United Kingdom−Austerity, workforce skewed

older, little urbanization+High levels of education and

per-capita wealth

Italy− Austerity, workforce skewed older, low education levels, little

urbanization, early retirement expectations+ Low inflation, high per-capita wealth, high percentage of

family households


Countries by Impact of Defining/Dividing FactorsLikely net impact on Haves and Have Nots



Developed vs. Emerging: Expect a Have/Have Not challenge in developed and emerging markets alike

Value proposition: Adapt a dual Have/Have Not value proposition to each country based on its mix of key attributes

Food/fuel inflation: Use as local indicator of stress on Have Nots

Discretionary spending: Expect Have household effects to be most evident in discretionary categories and channels

Consumables spending: Expect Have Not effects to be focused in consumable/nondiscretionary categories, channels

A value focus: Expect value-focused brands and retailers—in-store and online—to continue to thrive/expand

General conclusions and implications

10Source: Kantar Retail analysis

© Copyright 2013 Kantar Retail 11


Income Inequality: Greatest in Key Markets

Split into Haves and Have Nots relevant in all markets

Notable that:

– United States looks as much like China and emerging markets as developed markets

– European markets have the least income inequality—but austerity will likely change that

And affects developed and emerging markets alike

Source: OECD, International Monetary Fund, and Kantar Retail analysis 12

Income Inequality Measured by Gini Index*100 = inequality; 0 = equality

* Based on after-tax income; Highlighted in red bold are the largest markets# Brazil and China are estimated based on IMF data, all other countries are OECD data

Most income inequalityMarket IndexBrazil# 58.4Chile 50.1Mexico 46.6China# 44.9Russia 42.8Turkey 41.1United States 38.0Israel 37.6Portugal 34.4United Kingdom 34.1Spain 33.8Greece 33.7

Least income inequality Market IndexIceland 24.4Slovenia 24.6Norway 24.9Denmark 25.2Czech Republic 25.6Finland 26.0Slovakia 26.1Belgium 26.2Austria 26.7Sweden 26.9Luxembourg 27.0Hungary 27.2


Generational Mix: Key in Developed Markets

Tilt toward aging workforce likely to yield more Have-Not behavior

Japan, Germany, and Italy are most vulnerable

Relevance in emerging markets likely depends on other factors as well

Source: United Nations Population Division, and Kantar Retail Analysis 13

Working-Age Population by Country*Share of Population Age 15 to 34 Relative to Age 55-plus

* Highlighted in red bold are the largest markets

Countries Skewed OldCountry 15-34 55+ IndexJapan 24% 33% 72Germany 24% 29% 84Italy 24% 28% 85Finland 26% 29% 92Denmark 25% 27% 95Greece 26% 27% 96Netherlands 25% 26% 98Sweden 27% 27% 100Portugal 27% 27% 100Belgium 26% 26% 101France 26% 25% 102Austria 26% 25% 104Switzerland 26% 25% 104Hungary 29% 27% 107United Kingdom 27% 25% 109Czech Republic 29% 27% 109Spain 28% 24% 114Norway 27% 24% 115Canada 28% 24% 120Ukraine 31% 25% 123

Countries Skewed YoungCountry 15-34 55+ IndexUAE 65% 1% 4347Qatar 47% 4% 1172Kuwait 41% 6% 705Saudi Arabia 37% 7% 563Iraq 35% 7% 512Nigeria 33% 7% 506Pakistan 37% 8% 440Bangladesh 38% 9% 430Iran 43% 10% 420Algeria 40% 10% 405Philippines 35% 9% 404Malaysia 37% 11% 342South Africa 38% 11% 341Vietnam 38% 11% 338Indonesia 34% 10% 327India 36% 11% 324Egypt 36% 11% 322Peru 36% 11% 318Mexico 35% 11% 309Venezuela 35% 12% 303


Retirement Expectations: An Added Dimension

Most susceptible are countries such as Italy and France that have early retirement expectations and workforce skewed older

An older workforce is less of a Have-Not driver where workers delay retirement

Early retirement plans will magnify Have-Not threat

Source: OECD and Kantar Retail analysis 14

Average Retirement Age of Men by Country *In 2011

* Highlighted in red bold are the largest markets; Does not include India among largest markets considered

By earliest ageCountry AgeLuxembourg 58.0France 59.1Belgium 59.6Hungary 60.4Austria 60.4Slovak Republic 60.4Italy 60.8Malta 61.0Poland 61.5Slovenia 61.7Finland 61.8Greece 61.8Bulgaria 61.8

By oldest ageCountry AgeMexico 71.5Korea 71.4Brazil 70.7Japan 69.3Iceland 68.2Chile 68.1Israel 67.7China 66.8Sweden 66.3Portugal 66.2New Zealand 65.9Switzerland 65.5Cyprus 65.3


Urbanization: A Creator of Have Households

As countries grow, movement into urban areas drives gain in Have households

China and India are likeliest candidates

Developed markets hurt by slow-growing urban areas

Source: GeoHive and Kantar Retail analysis 15

Population of Cities of 2 million or more *Among 60 largest countries by GDP

* Highlighted in red bold are the largest markets: CAGR is 2010-2020

Little Urban Growth(pop. in

No. of millions)Country cities 2020F CAGRKorea 4 18.5 0.1%Germany 1 3.6 0.4%Ukraine 1 2.9 0.5%Italy 3 9.0 0.5%Japan 7 65.2 0.5%Russia 2 17.5 0.7%Belgium 1 2.1 0.8%United Kingdom 3 14.6 0.9%Portugal 1 3.1 0.9%Singapore 1 5.6 1.0%Greece 1 3.7 1.0%France 1 11.7 1.1%Argentina 1 14.9 1.1%

Strong Urban Growth(pop. in

No. of millions)Country cities 2020F CAGRUAE 1 3.1 5.5%Nigeria 6 33.0 4.0%Vietnam 2 12.7 3.5%Saudi Arabia 3 14.0 3.2%Bangladesh 3 29.4 3.1%China 54 315.9 3.1%Iraq 2 9.8 3.0%Thailand 2 12.4 2.9%Pakistan 8 43.3 2.9%India 22 160.3 2.7%Kuwait 1 3.0 2.6%Turkey 4 24.9 2.4%Algeria 1 3.6 2.4%


Education: Single Biggest Driver of Haves

No surprise that developed markets are most educated

Offsetting factors may be at work in places like Spain and Italy—markets that are developed even though skewed toward less education

But may be offset by other factors in some countries

Source: OECD and Kantar Retail analysis 16

Educational Attainment by Country1

Share of population 25-64 years old

1 Data is for 2010 except where noted. Highlighted in red bold are the largest markets; Does not include India among largest markets considered

2 Basic Education is roughly equivalent to less than a U.S. high school education3 College Educated is roughly equivalent to a four-year college degree or higher4 Data is from 2000 for China, 2003 for Argentina, 2004 for Saudi Arabia, 2007 for Indonesia and South

Africa, and 2009 for Brazil

Skewed toward basic education

Basic CollegeCountry Education2 Degree3

China4 82% 1%Indonesia4 76% 5%South Africa4 72% 5%Saudi Arabia4 69% 16%Turkey 69% 13%Portugal 68% 15%Mexico 64% 16%Brazil4 59% 11%Argentina4 58% 14%Spain 47% 22%Italy 45% 14%Greece 35% 17%

Skewed toward higher education

Basic CollegeCountry Education2 Degree3

Norway 19% 35%United States 11% 31%Israel 18% 31%Netherlands 27% 30%Iceland 28% 29%United Kingdom 11% 28%Denmark 23% 28%Korea 20% 27%Australia 27% 27%Canada 11% 26%Japan 1% 25%Sweden 13% 25%


Household Composition: Key Ingredient

A high percentage of married/couple households helps offset less education in places like Spain, Italy

Fewer married/ couple households in developed countries likely pushing more toward Have-Not behavior

Married/couple + college educated = Have bull's-eye

17

Household Type by Country*Latest Year Available#

* Highlighted in red bold are the largest markets; Does not include Brazil, China, India, and Russia among largest markets considered; NA=Not Available

# Data are from 2000 for Estonia, Finland, Korea, Latvia, and the United States; 2001 for Bulgaria, Denmark, Greece, Italy, Lithuania, the Netherlands, Norway, Portugal, Slovakia, and Spain; 2002 for Romania, and Sweden; 2005 for Iceland, and Japan; 2006 for New Zealand.


Skewed toward couple families

Single-Couple Person

Country Families HouseholdsKorea 72.6 NAPortugal 69.1 17.3Greece 64.9 19.7Sweden 63.9 NASpain 62.9 20.3Romania 62.8 18.9Italy 62.3 24.9Iceland 60.8 30.7New Zealand 60.1 22.6Netherlands 59.9 33.6

Skewed away fromcouple families

Single-Couple Person

Country Families HouseholdsLithuania 40.9 28.7Latvia 45.6 25.0Estonia 46.8 33.5Japan 49.5 29.5Finland 49.8 37.3Slovakia 50.6 19.4Denmark 50.9 36.8United States 51.7 27.3Bulgaria 52.1 22.7Norway 52.2 37.7


Wealth Effects: Most Affect Have Households

Negative post-recession wealth effects persist in markets where workforce is skewed older

Is especially the case among Baby Boomers in the United States

Emerging markets such as Brazil, Russia, China, and India will see positive wealth effects—if gains can be sustained

But impact can be negative as well as positive

Source: National Bureau of Economic Research, and Kantar Retail analysis 18

Relative Wealth Per Adult by Market*In 2000, among 60 largest markets by GDP

By most wealthHong KongUnited StatesIrelandSwitzerlandUnited KingdomNetherlandsSingaporeBelgiumJapanItalyTaiwanAustraliaFranceNorwayCanadaSpainGermanyIsraelGreece

* Highlighted in red bold are the largest markets

By least wealthNigeriaBangladeshIndiaPakistanAlgeriaIndonesiaVietnamRomaniaPeruUkraineChinaEgyptRussiaKazakhstanIranBrazilTurkeySaudi ArabiaPhilippines


Inflation Threats: Weigh on Emerging Markets

Toll may prove greatest on Russia and Brazil, where may be fewer offsetting effects

In developed markets, inflation may prove a bigger threat than expected if shift to pro-growth policies not managed well

Source: International Monetary Fund and Kantar Retail analysis 19

Consumer Price Inflation by MarketCAGRs among 60 largest markets by GDP

Low Inflation2000- 2010-

Market 2010 2020Switzerland 0.9% 0.5%Greece 3.4% 0.9%Japan -0.3% 1.5%Belgium 2.1% 1.6%Ireland 2.2% 1.6%UAE 5.4% 1.7%Portugal 2.4% 1.7%France 1.7% 1.7%Spain 2.8% 1.8%Italy 2.2% 1.8%Netherlands 2.1% 1.8%Norway 2.0% 1.9%Germany 1.6% 1.9%Taiwan 0.9% 1.9%Sweden 1.5% 2.0%Canada 2.0% 2.0%New Zealand 2.6% 2.1%Israel 2.1% 2.1%Denmark 2.0% 2.1%Czech Republic 2.5% 2.1%

High Inflation2000- 2010-

Market 2010 2020Venezuela 22.0% 23.3%Iran 14.6% 22.4%Pakistan 7.7% 11.1%Argentina 9.5% 10.0%Vietnam 7.7% 8.8%Egypt 7.9% 8.6%India 6.3% 8.5%Nigeria 12.9% 8.4%Bangladesh 6.2% 6.5%Kazakhstan 8.6% 6.3%Russia 12.5% 6.3%Turkey 17.5% 5.7%Iraq 27.9% 5.4%South Africa 6.0% 5.2%Indonesia 8.6% 5.1%Brazil 6.6% 5.0%Algeria 3.6% 4.7%Ukraine 11.1% 4.3%Qatar 5.1% 4.0%


Government Austerity: Threat to Mature Markets

Threat is greatest mostly in Europe, where challenged to sustain big role in the economy

China and other emerging markets in much better position to restimulate and sustain growth

Source: International Monetary Fund and Kantar Retail analysis 20

Government Spending by Market*In 2012 as share of GDP among 60 largest markets

* General Government Total Expenditure includes net acquisition of nonfinancial assets, which includes land, buildings, roads, and other infrastructure; Highlighted in red bold are the largest markets

By highest spendersMarket ShareDenmark 58.4France 56.6Finland 55.0Belgium 54.8Austria 51.1Italy 50.7Greece 50.3Netherlands 50.1Sweden 50.1Ukraine 49.3Hungary 48.9Spain 46.7Portugal 45.6Venezuela 45.4Czech Republic 45.1Germany 45.0Argentina 44.6Iraq 44.2Israel 43.6United Kingdom 43.5

By lowest spendersMarket ShareBangladesh 16.4Iran 17.6Singapore 17.6Philippines 18.8Indonesia 19.1Peru 19.6Hong Kong 20.8Pakistan 20.9Korea 21.4UAE 22.0Taiwan 22.5Kazakhstan 23.2Chile 23.3Thailand 24.1China 24.8Nigeria 27.1Mexico 27.3India 27.5Colombia 28.2Malaysia 29.7


Related Content on Haves and Have Nots

June 2012 Mid-Year Forum presentation, Strategic Outlook Workshop, The Macro-Retail Outlook to 2020: A Landscape Shaped by Have and Have Nots

April 2012 article, The Macroeconomic Outlook for Retail: The Have Not Swing Votes

April 2012 Shopper Forum presentation, The Haves and Have Nots

February 2012 article, The Macroeconomic Outlook for U.S. Retail: The Have Not Challenge

December 2011 Year-End Forum presentation, The Way Forward: Illuminating The Uncertain Economic Landscape

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Presented by: THE GLOBAL HAVE & HAVE NOT CHALLENGE Frank Badillo Chief Economist July 2013