The Future of World Car Fleet: The Road Ahead (A BBVA Research model for long-term automobile projections) November, 212 Cross-Country Emerging Markets Unit
Key Messages Motivation: Analysis of long run determinants of car industry Developing Models for tracking long term changes ( pionering model ) Analisys of long term trends which are shaping the new economic order. Wealth not population is driving the economic transformation Population+Wealth ( Middle Classes ) will be key for business opportunities Results: Car industry will experience an important transformation Population, Wealth, Middle Classes and Urbanization will bias the future of Car Fleet to Emerging Markets East Asia will experience the highest increase followed by Latam Development Economies will experience moderate increases except in the US economy BBVA Markets will improve depending on where we focus Annex The BBVA Research Car Model Motivation and alternative models The BBVA CAR Model: Especification, estimation and comparative results Comparative analysis 2
Contents Analysis of long run determinants of Car Industry Global results Annex: The BBVA Research CAR Model 3
Car Fleet Determinants BBVA Model: Car Fleet Determinants Population World Car Fleet Determinants Car Ownership Long Run Saturation levels Cyclical Determinants Real GDP per Capita Population Density GDP Growth Acceleration Economic Recessions (dummy) Urbanization Rates Infrastructure (Roads Quality) Financial Depth (Private Credit/ GDP) 4
Different Population Dynamics Population pyramids for selected economies (21) and UN G7 Countries Eagles Ageing Advanced Eagles Populating Premiun 1+ 9-94 Female Male Female Male 1+ 9-94 Female Male 8-84 8-84 7-74 7-74 6-64 6-64 5-54 5-54 4-44 4-44 3-34 3-34 2-24 2-24 1-14 1-14 -4 4 3 2 1 1 2 3 4 5 4 3 2 1 1 2 3 4 5-4 5 4 3 2 1 1 2 3 4 5 5
Labor force will gradually decline in EM but still maintains an important premium with Developed Labor Force Population Population Growth (% yoy) and UN Labor Force Population Population Growth (% yoy) and UN 4 3 Mid term Long term 4 3 Mid term Long term 2 2 1 1-1 -2 China Korea India Indonesia G7 195 1955 196 1965 197 1975 198 1985 199 1995 2 25 21 215 22 225 23 235 24 245 25-1 -2 195 1955 196 Russia Brazil G7 1965 197 1975 198 1985 Turkey Mexico 199 1995 2 25 21 215 22 225 23 235 24 245 25 6
..But Household size will also decline limiting the population decline impact in some goods World Household Size (members per housold unit) and UN Household Size and GDP Per cápita (in members ans log of gdp per capita) and UN 8 7. 6.5 7 6. 6 5.5 5. 5 4.5 4. 4 3.5 3 3. 2.5 2 2. Yemen Jordan Sudan India Central African Republic Tunisia Chad Tanzania Iran Bangladesh Vietnam Paraguay Belize Mexico Malawi Botswana Panama Costa Rica FYR Macedonia Sri Lanka Brazil Bosnia and Herzegovina Israel Uruguay Slovenia Poland Ireland Spain Russia Bulgaria Lithuania Hungary Canada France Belgium United Kingdom Netherlands Germany Finland 1 1 2 3 4 ln of real PPP-adjusted GDP 7 Household size
The Wealth Effects: GDP per capita growth differences will remain important GDP per capita Growth Rate (198-22) (% yoy, in nominal PPP-adjusted USD) Advanced Economies Advanced economies Major advanced economies (G7) European Union Other advanced economies Central and eastern Europe 199-2-1 21-2 1 2 3 4 5 6 7 8 9 1 Emerging Economies Commonwealth of Independent States Newly industrialized Asian economies Developing Asia Latin America and the Caribbean Middle East and North Africa 1 2 3 4 5 6 7 8 9 1 8
With a Fast track in Middle Classes creation Estimation of income distribution by GDP per capita in emerging economies (198-22) (millions of people and % of total population; original data in real PPP-adjusted USD) 6 5 4 3 2 1% Slow Motion Distribution changes Fast Track Slow Motion Distribution changes Fast Track 9% 8% 7% 6% 5% 4% 3% 1 198 1982 1984 1986 1988 199 1992 1994 1996 1998 2 22 24 26 28 21 212 214 216 218 22 Affluent High Middle Class Medium Middle Class Low Middle Class Low Income Poor 2% 1% % 198 1982 1984 1986 1988 199 1992 1994 1996 1998 2 22 24 26 28 21 212 214 216 218 22 Affluent High Middle Class Medium Middle Class Low Middle Class Low Income Poor Affluent (>4 USD) High Middle Income (25 to 4 USD) Medium Middle Income (15 to 25 USD) Low Middle Income (5 USD to 15 USD) Low Income (1 USD to 5 USD) Poor( <1 USD 9 9
Specially in some areas Estimation of income distribution by GDP per capita in emerging economies regions (198-22) (millions of people and % of total population; original data in real PPP-adjusted USD) 2 East Asia South Asia 16 25 2 12 15 8 1 4 5 22 218 216 214 212 21 28 26 24 22 2 1998 1996 1994 1992 199 1988 1986 1984 1982 198 22 218 216 214 212 21 28 26 24 22 2 1998 1996 1994 1992 199 1988 1986 1984 1982 198 Emerging Europe Latam 6 5 35 3 4 3 2 25 2 15 1 1 5 22 218 216 214 212 21 28 26 24 22 2 1998 1996 1994 1992 199 1988 1986 1984 1982 198 22 218 216 214 212 21 28 26 24 22 2 1998 1996 1994 1992 199 1988 1986 1984 1982 198 1 1 Affluent (>4 USD) High Middle Income (25 to 4 USD) Medium Middle Income (15 to 25 USD) Low Middle Income (5 USD to 15 USD) Low Income (1 USD to 5 USD) Poor( <1 USD
and in some segments related to different consumption patterns 2 18 16 14 Low Medium Income (5 to 15 USD) Africa Em.Europe LatAm East Asia South Asia 8 6 Medium Middle Income (15 to 25 USD) Africa Em.Europe LatAm East Asia South Asia 25 2 High Middle Income (25 to 4 USD) Africa Em.Europe LatAm East Asia South Asia 3 25 2 Affluent (>4 USD) Africa Em.Europe LatAm East Asia South Asia Million People 12 1 8 6 4 2 4 2 15 1 5 15 1 5 198 199 2 21 22 198 199 2 21 22 198 199 2 21 22 198 199 2 21 22 Consumers Cycle Basic Goods Food Housing Motorcycles White Goods Tourism cars White Goods Luxury Cars Tourism Services 11
Middle classes will trigger demand for semi necessities and discretionary spending Consumption Patterns in China (2-22) (% of total urban household spending) Source: Mckinsey 12
Urbanization will increase very fast in some of the regions 9 8 7 6 5 4 3 World Urbanization Rates(198-22) (Urban population as a % of total) Source: United Nations.7.6.5.4.3.2.1 World Urbanization Rates(198-22) (Annual Change in Urbanization Rates) Source: United Nations.8 2 1 West Europe East Europe Latam N.América Asia Africa -.1 197 1975 198 1985 199 1995 2 25 21 215 22 225 West Europe N.América East Europe Asia Latam Africa 13
Regional Aggregates mask some rapid changes in some countries (Andeans & South East Asia) World Urbanization Rates(211) (Urban population as a % of total) Source: United Nations World Urbanization Rates(23) (Urban population as a % of total) Source: United Nations 14
and we will observe an intensive Urban agglomeration process specially in Asia Percentage of urban population and agglomerations by size class Source: UN Urbanization Prospects, 211 revision 211 225 15
But Emerging Markets still lags in transport infrastructure Road Density World Map (Sinthetic indicator, from -1=lighter to 1= Darker) Source:World Bankand BBVA Research Paved Road World Map (% of total roads, from =lighter to 1= Darker) Source:World Bank Development Indicators 16
.. and this leads to important opportunities of investment in this segment Public Private Initiatives Infrastructure Transport Projects (US Billions) Source:World Bank 35 3 25 Middle East & Africa Asia Latam Emerging Europe 2 15 1 5 211 21 29 28 27 26 25 24 23 22 21 2 1999 1998 1997 1996 1995 1994 1993 1992 1991 199 17
Contents Analysis of long run determinants of Car Industry Global results Annex: The BBVA Research CAR Model 18
A brief reminder on the composition of aggregates EAGLEs Nest G7 Other Europe Russia Turkey Poland Ukraine France Germany Italy UK Spain America Brazil Mexico Argentina Chile Colombia Peru Canada USA Asia Pacific China India Indonesia Korea Taiwan Bangladesh Malaysia Pakistan Philippines Thailand Vietnam Japan Australia Middle E. & Africa Egypt Nigeria S.Africa Iran S.Arabia 19
Increase and distribution of world car fleet by decades: Eagles (China) will lead the next decade Distribution of world car fleet (198-22) (% of total world car fleet) 1% 9% 8% 7% 6% 5% 4% 3% 2% 1% Increase of world car fleet by decades (mn) (Million cars) 35 3 25 2 15 1 5 China EAGLEs exchina Nest US G6 Others % 198 199 2 21 22 China EAGLEs exchina Nest US G6 Others 198-199 199-2 2-21 21-22 2
Expected increase in 21-22 and levels of car fleet by 22 Increase of world car fleet ex China (22 vs 21) (Million cars) 3 25 2 15 1 5 EAGLEs exchina Nest US G6 Others 24 22 2 18 16 14 12 1 8 6 4 2 Car fleet of largest markets in 22 (mn) (Million cars) China EAGLEs exchina Nest US G6 Others India US Brazil Russia Indones Mexico Turkey Thailand Malaysia Colombia Argenti S.Africa UK S.Arabia Poland France Canada Peru Ukraine Australia Nigeria Vietnam Iran Egypt Korea China US Japan Brazil India Russia Germany Italy France UK Mexico Spain Canada Poland Indonesia S.Arabia Korea Turkey Australia Malaysia Iran Argentina S.Africa Thailand Ukraine 21
Determinants of the expected increase in the car fleet. Wealth not population as the main driver Determinants of Car Fleet Expansion (198-22) (million Cars) 18 16 14 12 1 8 6 4 2 China EAGLEs exchina Nest US Population Car Ownership G6 Others Determinants of Car Fleet Expansion (198-22) (million Cars) 3 25 2 15 1 5 Population Car Ownership India US Brazil Russia Indonesia Mexico Turkey Thailand Malaysia Colombia Argentina S.Africa UK S.Arabia Poland France Canada Peru Ukraine Australia Nigeria Vietnam Iran 22
Change and levels of car ownership Car ownership Evolution(198-22) (Cars Units per 1 people) 8 7 6 5 4 3 2 1 China EAGLEs exchina Nest US G6 Others 198 199 2 21 22 Car ownership Groups Evolution(198-22) (Cars Units per 1 people. Bubble size proportional to car fleet Car ownership (units per 1, people) 6 5 4 3 2 1-1 EAGLEs (198) Nest (22) Nest (198) G7 (198) G7 (22) EAGLEs (22) 7 8 9 1 11 log of GDP per capita (real PPP-adjusted USD) 23
Expected annual increase in car fleet for the next decade concentrated in Asia and Latam Expected annual increase in World Car Fleet (21-22) (% yearly growth) % 2% 4% 6% 8% 24
Different Growth Areas across the world Car ownership (units/1 people) Car Ownership Gomperzt Curve (Car Ownership and Sensitivity to GDP per Capita Growth as a function of GDP per capita levels) 5 45 4 35 3 25 2 15 1 5 Accelerating Explosive Strong growth Growth Moderate growth Car Ownership Sensitivity Saturation area 3.5 3. 2.5 2. 1.5 1..5 COW sensitivity to real GDP pc growth Car Fleet Growth Areas (Car Ownership and Sensitivity to GDP per Capita Growth as a function of GDP per capita levels) Growth Area Long-term income per capita (in real PPPadjusted USD) Sensitivity of car ownership to income per capita* From to From to Accelerating Growth 1,1 4,6 1 2.5 Explosive Growth 4,6 12,5 2.5 3.1 (max) Strong Growth 12,5 15.8 1.75 2.5 Growth 15.8 19,9 1 1.75 Moderate Growth 19,9 24,4.5 1 Saturation 24,4 + min».5 *Change of car ownership (units per 1, people) to a change of 1 USD in income per capita 5, 1, 15, 2, 25, 3, 35, 4, 45,. Real GDP per capita inppp-adj. USD 25
Explosive and strong growth will be concentrated in Asia, Latam and Turkey Car Fleet Growth Areas (Car Ownership and Sensitivity to GDP per Capita Growth as a function of GDP per capita levels) Growth Area Long-term income per capita (in real PPP-adjusted USD) Sensitivity of car ownership to income per capita* From to From to Countries and Groups Accelerating Growth 1,1 4,6 1 2.5 Bangladesh, Pakistan, Nigeria, Vietnam, Philippines, India, Cameroon, Kenya Explosive Growth 4,6 12,5 2.5 3.1 (max) Indonesia, Egypt, Ukraine, Thailand, Colombia, China, S.Africa, Peru, Brazil, Paraguay, Bolivia, Ecuador Strong Growth 12,5 15.8 1.75 2.5 Turkey, Mexico, Panama, Uruguay, Bulgaria, Romania Growth 15.8 19,9 1 1.75 Malaysia, Chile, Russia, Argentina, Hungary, Croatia, Lithuania, Latvia Moderate Growth 19,9 24,4.5 1 Poland, Portugal, Slovakia, Saudi Arabia, Greece, Estonia, Oman Saturation 24,4 + min».5 Korea, G7, Australia, Spain, Switzerland, Netherlands, Czech Republic, Slovenia, New Zealand *Change of car ownership (units per 1, people) to a change of 1 USD in income per capita 26
Growth markets will lie in the Emerging Markets area Expected increase in Car Fleet (2-1) (% yearly growth) China UAE India Venezuela Peru Mexico Brazil Turkey Bolivia Panama Russia Korea Chile Colombia Argentina Australia Spain Portugal United Kingdom Switzerland Belgium France Japan Italy United States Germany Uruguay Paraguay -1-5 5 1 15 2 25 Expected increase in Car Fleet (21-2) (% yearly growth) China India Peru Colombia Panama Turkey Bolivia Paraguay Chile Uruguay Brazil Argentina Venezuela Mexico Russia UAE Australia United States Korea United Kingdom France Belgium Spain Switzerland Italy Japan Portugal Germany 2 4 6 8 1 12 14 27
Contents Analysis of long run determinants of Car Industry Global results Annex: The BBVA Research CAR Model 28
Literature on car ownership Dargay, Gately and Sommer (27): They use a similar saturation model. Panel of 45 countries. They assume a different sensitivity of every country to GDP per capita. Chamon, Mauro, and Okawa (28): They assume there is no saturation rate. They concentrate on estimating a take off income threshold at which car demand starts to grow exponentially. Medlock, K. B., and Soligo, R. (22): Panel of 28 countries. The model includes the user cost of capital and assume and find different saturation levels for each country. 29
Enhancements of BBVA Car Model We include the level of financial development and an infrastructure quality indicator as determinants of each country saturation level. We associate the saturation level to a long-term or «structural» level of income instead of the observed GDP per capita. We allow short term deviations of income per capita from its «structural» level to account for short-term variations in car ownership, instead of relying on the lagged value of the dependent variable to model short-term dynamics. 3
Model specification The model is estimated by maximum likelihood using a non-linear estimator with robust standard errors. The equation that we finally estimate is the following: exp exp CAROW = Car Ownership, GDPPC = Real GDP per capita in PPP-adj. USD, DENS = Population Density, URB = Urbanization Ratio, ROADSQ = Quality of Road Infrastructure, PCRED = Private Credit Ratio 31
Estimated regression Saturation Level determinants Long-term per capita income Other structural determinants Short-Term determinants Variable Coefficient α (max. constant Saturation Level) 499.9*** γ (Gompertz curve shape) -3.95*** β (real GDPpc PPP-adj. 15y MA) -.17*** Real GDPpc PPP-adj. deviation 5yMA-15yMA. 7*** Population density (above US) -.18*** Population density (below US) -.19 Urbanization rate (above US) 2.259*** Urbanization rate (below US) -1. 6* Roads quality Indicator 9.86*** Credit to private sector 1.152*** Real GDPpc PPP-adj. dev. Obs.-5yMA. 9*** Real GDPpc PPP-adj. dev. obs.-5yma (in recessions) -. 1*** Adjusted R 2,991 Number of Observations 2.1 Number of Countries 92 *** indicates significance at a 1% confidence level, ** at a 5% level and * at a 1% level 32
BBVA Research forecasts (212) compared with previous IMF work (28) Growth of Car fleet (21-22) (average % yoy) 14 13 12 11 1 9 8 7 6 5 4 3 2 1 BBVA Research (212) IMF (28) WORLD Advanced Emerging USA* India China *BBVA Research uses only passenger cars and not light trucks 12 11 1 9 8 7 6 5 4 3 2 Car fleet of largest markets in 22 (Million cars) 1 BBVA Research (212) IMF (28) WORLD Advanced Emerging USA* India China 33
Variables definition and source Variable Definition Source Car ownership Passenger cars per 1, people World Bank and UN GDP per capita Real GDP per capita in PPP-adjusted USD 25 constant terms) IMF and BBVA Research Population density Population per km 2 of area United Nations Urbanization Percentage of urban population United Nations Road density 1 Road kilometers per km 2 of area World Bank Road density 2 Road kilometers per capita World Bank Private credit Private credit to non-financial institutions to GDP ratio World Bank, Haver and BBVA Research 34
Cross-country emerging markets analysis unit Chief Economist Álvaro Ortiz Vidal-Abarca alvaro.ortiz@bbva.com +34 63144485 Ext 51933 Senior Economist David Martínez Turégano dmartinezt@bbva.com +34 69 845 429 SeniorEconomist Alfonso Ugarte Ruiz alfonso.ugarte@bbva.com +34 91 374353 35