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The Elasticity of Demand for Gasoline in Brazil with the
Introduction of the Flex-fuel Fleet
Ana Isabel Santos
Marcelo Colomer
Universidade Federal do Rio de Janeiro
(2014)
Abstract
In this article, the primary objective is to describe the correlation between the prices of
gasoline and ethanol in Brazil from 2003, and the variables with the greatest impact on
the pricing of hydrous ethanol fuel.
To do this, we used an econometric model (an OLS with progressive introduction of
instrumental variables) which allowed rigorous analysis of the weight of various
exogenous variables - gasoline C prices, ethanol sales and climatic conditions - in the
price of this biofuel. The state of São Paulo was the target of analysis since it is a
reference in the production and consumption of this type of fuel in Brazil.
This article contributes to an increase in the literature in the fuel industry, in particular,
for the segment of ethanol. The future and environmental concerns require an increased
investment in finding a cleaner global energy matrix. And even though the ethanol
market in the United States and Brazil has the biggest presence, it will certainly become
much more popular in the coming decades, dethroning the most popular petroleum
derivatives: gasoline and diesel.
Keywords: gasoline, ethanol, flex -fuel fleet, Brazil.
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1. Introduction
Brazil is the second largest producer of ethanol after the United States of America
(USA), and already has a long tradition in the production of this biofuel (see Annex
Figure 1).
Brazil was a pioneer in the production of ethanol made from sugar cane. Its introduction
in the energy matrix of the country happened in the early twentieth century and came to
address two major problems: the high dependence on imported oil and the successive
crises that was targeting the sugar sector.
The first experience with ethanol in Brazil happened in 1925. Eight years later, and
during the term of Getúlio Vargas, the Institute of Sugar and Alcohol was created –
IAA, and the obligatory blending of ethanol in gasoline was decreed.
Already in the 70s the National Alcohol Program was launched which promoted more
strongly the reduction of the country's dependence on imported oil. By that time, Brazil
imported about 80 percent of the oil it consumed.
However, despite the successive fluctuations in the price of 'black gold' in International
markets, the ethanol industry was not economically competitive and its sustainability
was ensured for several years by state subsidies.
From the mid-80s, the state tried to reduce its role in the sector, which happened in
1990 with the extinction of IAA and the cutting of subsidies to sugar production. The
country became one of the major exporters of this commodity.
The turning point occurred in 2003 with the start of marketing of flex-fuel vehicle in
Brazil, with Otto cycle engine prepared to process ethanol, gasoline, or a mixture of
both. With the introduction of this new engine in the Brazilian market, the consumer
had the freedom to choose the type of fuel at the time of supply. This new paradigm of
consumption transformed gasoline and ethanol into substitute products.
The introduction of the flex-fuel vehicle in Brazil was widely applauded by consumers.
This is demonstrated by more than 20 million such vehicles circulating on Brazilian
The Elasticity of Demand for Gasoline in Brazil with the Flex-fuel Fleet
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roads. The cars on ethanol accounted for more than 50 percent of the light vehicle fleet
in 2013, only one decade after its introduction (see Annex Figure 2).
The next few lines look in detail at the cross-price elasticity of demand for gasoline and
ethanol. The fact of both becoming two substitute products requires it. Also we will try
to decode the variables that have the most influence on the price of ethanol. The price of
hydrous ethanol fuel for resale will have, in its genesis, influence on the price of
distribution (which already reflects the cost of raw materials, cost of production, freight
and taxes) and the sales margin (LIMA, 2011). Besides these obvious factors, it will
also be interesting to analyze other exogenous variables which are connected to the final
price of ethanol: ethanol sales, weather conditions or even the price of gasoline C.
The aim of this econometric analysis will be the state of São Paulo. It is the Brazilian
region with the highest levels of the production and consumption of ethanol. It currently
represents about 50 % of the national market of biofuel.
1.1 Production and Consumption of Ethanol in the State of Sao Paulo
The Brazilian state of São Paulo, in national terms, has the largest fleet of flex-fuel cars.
It is also the state with the largest area of planted sugar cane (see Annex Figure 3) and
the largest production (see Annex Figure 4) and consumption of ethanol.
The demand for this biofuel reached nearly six billion litres last year (see Annex Figure
5). If to this figure we add the value of 25% anhydrous alcohol, imposed by regulation
and which is blended with gasoline A, then we have ethanol fuel as the leader in the
state of São Paulo, which means that for every litre of gasoline C, one fifth is anhydrous
ethanol (LIMA, 2011).
Reaching this position as the largest consumer of ethanol – on par with gasoline, São
Paulo plays a major role in the market of both fuels, and its behaviour influences and
reflects the national trend.
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1.2 Ethanol
As already mentioned, sales of hydrous ethanol showed a strong growth from the entry
of flex-fuel vehicles and captured not only the increase in income and consumption as
well as the replacement of gasoline by this biofuel.
The graph below shows the confirmation of the existence of three distinct periods since
the flex-fuel car was introduced into the country. Between 2003 and 2005 we can see a
slow penetration of ethanol-fuelled vehicles in the country. However, the real boom was
between 2006 and 2009, a period when the cars running on ethanol and gasoline
circulating on Brazilian roads reached 10 million units (see Annex Figure 2). The year
2010 marks the start of a less favourable period for this biofuel: the sugar cane crops
and ethanol production were shown to be insufficient to ensure the competitiveness of
the product.
Relationship between sales of ethanol and the GDP in Brazil
(2003-2012)
18
16
14
12
10
8
6
4
2
0
-2
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
GDP (%)
0,5
5,7
2,9
3,8
5,4
5,2
-0,2
7,5
2,7
1
Ethanol Sales (billions m3)
3,2
4,5
4,6
6,1
9,3
13,2
16,4
15
10,8
9,8
Source: IBGE and ANP
1.3 Gasoline
With the introduction of flex-fuel vehicles in Brazil, the gasoline market has undergone
a significant structural change over the last decade. The price of ethanol has become an
The Elasticity of Demand for Gasoline in Brazil with the Flex-fuel Fleet
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important variable to explain the demand for gasoline, which before was explained by
variation in income and its price.
Despite the growth of the economy, the consumption of this derivative varied below the
GDP in almost the entire period between 2003-2009 (ANP, 2013). However, as of 2010,
and with the sharp drop in the competitiveness of ethanol, the demand for gasoline
increased significantly. The justification for this increase was the bad harvest of
2011/2012 which generated a peak in the production of gasoline
The state of São Paulo is the main consumer of hydrated ethanol fuel, with over 50% of
the market share, and its behaviour strongly influences the national scene. The average
prices of ethanol and gasoline C in the state in 2012, indicates the recovery of
competitiveness of the product compared to gasoline (ANP, 2013). However, this
economic advantage is a recent phenomenon, and it is still insufficient to stimulate the
substitution between fuels.
Relationship between sales of gasoline and the GDP in Brazil
(2003-2012)
45
40
35
30
25
20
15
10
5
0
-5
GDP (%)
2003
0,5
2004
5,7
2005
2,9
2006
3,8
2007
5,4
2008
5,2
2009
-0,2
2010
7,5
2011
2,7
2012
1
Gasoline (billions m3)
21,70
23,17
23,55
24,00
24,32
25,17
25,40
29,84
35,49
39,70
Source: ANP e IBGE
The biggest trading partner of Brazil, in terms of ethanol production, is the United
States (see Annex Figure 1). However, Brazilian ethanol is now cheaper than in the
The Elasticity of Demand for Gasoline in Brazil with the Flex-fuel Fleet
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U.S., which enhances its attractiveness to export the product (ANP, 2013). That is, even
with significant increases in the price of gasoline in 2013, the exportation of ethanol
may still remain attractive, especially in case of devaluation of the Real against the U.S.
dollar.
2. Gasolina and Hydrated Ethanol Fuel Behavior of Prices
As already mentioned, one of the main changes resulting from the development of flexfuel technology for Otto cycle engines was the confirmation of hydrated ethanol fuel as
a substitute product for common automotive gasoline, thus increasing the correlation
between the variables - especially the prices - of both markets.
Monthly resale prices of hydrated ethanol and gasoline C
(2002-2013)
3,00
2,50
$R/L
2,00
1,50
Hydrated Ethanol
1,00
Gasoline C
0,50
0,00
Source: ANP
The larger the national fleet of flex-fuel vehicle, the greater the cross-price elasticity of
demand between the markets of the two fuels.
In other words, a change in price of a fuel is reflected, almost immediately, on the
demand of the other.
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In recent years the prices of gasoline A in the production units of Brazil have remained
relatively stable. Especially, because its price fluctuations were always offset by an
increase in the rate of CIDE (Contribution for Intervention in the Economic Domain).
The source of the volatility, even though it is small, of this derivative until 2012
connects to the commodity prices on the international oil and derivatives markets.
However, from that year, and after a rise of 7.83% on producer prices, the CIDE was
reduced to zero.1
As we have seen already, and as we will confirm later, there are two mechanisms by
which the change in the price of ethanol influences the common gasoline sold in Brazil.
The first, is due to the mandatory blend of anhydrous ethanol in gasoline A2 and the
second is a consequence of the introduction of flex-fuel fleet in the country in 2003,
which enabled the migration of demand for both fuels.
2.1 Cross Price Elasticity of Demand of Gasoline and Ethanol
Prices are formed from two markets: the first of goods and services and the second
related to factors of production. The price and quantity demanded of goods are
negatively correlated. That is, if the price of a particular product the tendency leads to a
decrease in consumption of that product or service. Price changes are influenced by
changes in its supply and demand (STIGLITZ and WALSH, 2003).
The concept of elasticity measures the impact of changes in each of these elements on
the amount that consumers wish to purchase goods or products. From the price elasticity
of demand it is possible to achieve cross-price elasticity, which measures the percentage
change in the price of the goods or product X on the quantity demanded of other goods
or product Y.
1
Decree nº 7.764/2012.
The mandatory percentage of anhydrous ethanol content in gasoline is twenty-five percent (25%), according to
CIMA Resolution (Interministerial Council for Sugar and Alcohol) No. 1 of 28 February 2013.
2
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When these goods are substitutes, the increase in the price of X will be reflected in an
increase in demand for Y, and vice versa. This is the case of hydrated ethanol fuel and
gasoline.
The flex-fuel vehicle was designed taking as a starting point the platforms of gasoline
powered cars, therefore it was originally optimized for use with gasoline C. Based on
this assumption, the flex-fuel vehicles when fuelled solely on alcohol or gasoline
achieve very similar consumption. According to information published by Volkswagen
or General Motors, the use of ethanol as fuel in flex-fuel models allows a 70% running
distance with the same amount of gasoline C. In other words, by volume the latter has a
yield 30% above hydrated ethanol fuel. 3
This ratio of 70% reflects the ratio of the calorific values of gasoline C (25% anhydrous
ethanol) and hydrated alcohol. (CORREIA, 2007) In other words, 70 percent of the
price of gasoline C represents the cross-price elasticity of demand for gasoline and
ethanol. The main determinant of the final consumer reaches a level of 70%, the relative
price between hydrated ethanol and gasoline C (see Annex Figure 6).
If ethanol has its final pump price 70% above the price of gasoline, then the consumer
will choose the latter. (GOLDEMBERG et al, 2008). Based on the data of average
annual prices provided by ANP, from 2003 to 2012, the relationship between the prices
of the two fuels was examined using the following approach and table below:
Relationship of Prices = Ethanol Price / Gasoline C Price
3
Tests conducted by the Research Centre of Petrobras and by independent bodies showed results below this level, although some
tests with newer vehicles from other automakers have reached results higher than 70%.
The Elasticity of Demand for Gasoline in Brazil with the Flex-fuel Fleet
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Relationship of Prices between Gasoline and Ethanol in Brazil (2003-2012)
Average Price
of Ethanol
Average Price
of Gasoline
Relationship of
Prices
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
1,35
1,21
1,39
1,63
1,45
1,45
1,49
1,67
2,00
2,94
2,07
2,08
2,34
2,55
2,51
2,50
2,51
2,57
2,73
2,74
0,65
0,58
0,59
0,63
0,57
0,58
0,59
0,64
0,73
1,07
Regarding the market prices, FEIJÓ and ALVIM (2008) highlight the extreme
sensitivity of consumers to the price differential between gasoline and hydrated ethanol
fuel which causes them to migrate from one to the other quickly, which will have an
impact on the domestic demand.
However, despite the widely distributed and used literature on ethanol and gasoline C,
this value has been contested. There are other studies that have analyzed the problem of
cross-price elasticity of demand of ethanol and gasoline.
FERREIRA, PRADO and Silveira (2009) propose a model of competition between
producers of gasoline and ethanol based on the assumption that with the introduction of
flex-fuel fleet in Brazil, the ratio of prices of both fuels should converge to a rate of
replacement of 70%. However, the method of time series does not find evidence of this
happening.
Another theoretical model SALVO and HUSE (2010b) puts precisely the same
hypothesis: hydrous ethanol fuel and gasoline C will tend to converge, in technical
terms, for a replacement rate of 70%. The model also indicates that the prices of the two
fuels follow a trend of increase with the gradual USE of flex-fuel cars in Brazil.
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BOFF (2011) also uses the time series to investigate the long-term trends in prices of
gasoline C, ethanol and sugar. He concluded that the average fuel price increases before
the rate of efficiency.
In the absence of consensus, PESSOA, REZENDE and ASSUNÇÃO (2011) developed
a model that confirms that the distribution companies, even with a rate of 100% flexfuel vehicles on the market, always find an optimum price for both fuels. Since the price
is set by the actual distribution companies.
This result puts into question the normal operation of the pricing mechanism based on
fluctuations in supply and demand, and belies the rate of 70% between prices of
gasoline and ethanol. Although in practice this value does not always dictate the
substitution of one fuel for another, in mathematical terms it continues to be widely
used and will still reflects the price - elasticity of demand cross between gasoline and
ethanol.
3. Methodology
Although there is not much, the literature that there is on the use of the flex-fuel fleet in
Brazil, debates the issue of prices. Especially the impact of gasoline C, the favourite
fuel used in the country and the principal substitute for ethanol.
As has already been mentioned several times, the aim of this study brings us to the
pricing of ethanol based on different variables such as the price Gasoline C, vehicle
fleet (whose increase may dictate the increase in demand for biofuel) or climatic
conditions, which as we already understand, dictate a significant increase in the price of
ethanol. This was the case of a poor harvest in 2011/2012.
There are definitely many other variables that affect the price of ethanol. However,
these are the ones that seem to me the most relevant in the socioeconomic perspective,
mainly because they are quite comprehensive.
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Gasoline and ethanol prices, as well as the ethanol sales reflect production costs,
margins of distribution, freight or taxes.
And finally the climatic conditions, how do these correlate with the price of ethanol?
Empirically, we realize that there is a strong relationship between price and yield.
The value of all variables used correspond to annual averages in the state of São Paulo.
We propose the creation of a multiple linear regression model in which the price of
hydrated ethanol fuel (p_etanol) is a function of the price of gasoline (p_gas), of the
ethanol sales in the state of São Paulo (v_etanol) and the climatic conditions (climate).
Ethanol Prices =f (Gasoline prices + ethanol sales + climate)
Adjusted in their logarithmic form, the variables p_ethanol, p_gasoline and v_etanol
allow the possibility to evaluate the correlation between two variables, described in
separate units without any linear change which may impact the correlation between
variables. Thus, R2 for example, will not be affected by the scale of the data and the
standard error of the estimated coefficients, which if the data were scaled, would suffer
changes. (WOOLDRIDGE, 2012)
The calculation of the multiple linear regression model is performed using the
econometric software Eviews.
Therefore, we have:
log Price Etanol = α + log X1β1 + log X2β2 + γ +
ε
Dependent Variable
log Price Etanol: Ethanol price in São Paulo, from 2003 to 2012.
Independent Variables
X1β1: Gasoline price in São Paulo, from 2003 to 2012.
The Elasticity of Demand for Gasoline in Brazil with the Flex-fuel Fleet
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X2β2: Ethanol sales in São Paulo, from 2003 to 2012.
γ: Climate dummy, that takes the value of 1 if the weather is favourable and that
takes the value of 0 if the weather is unfavourable.
Instrumental Variables
X3β3: WTI oil spot price per barrel, from 2003 to 2012.
X4β4: Ethanol production in São Paulo, from 2003 to 2012.
For the regression hypothesis there is at least one factor which influences the
distribution price of ethanol (H1). The null hypothesis (H 0) reflects the lack of
correlation between any of the variables and the price of hydrated ethanol fuel.
The results of multiple linear regression will then be analyzed observing the variable
that will represent a p-value significant for hypothesis testing. Values of p > 0.05
indicate no correlation. But p values < 0.05 indicate statistical differences and these
results will be discussed.
According to HAIR et al. (2005), the p-value represents the level of less impact required
to reject a null hypothesis (H0).
4. Data
Empirical results were obtained using as primary data the The Survey of Prices and Fuel
Margins of ANP (Levantamento de Preços e de Margens de Combustívies) that
provides data on the average annual price of distribution of gasoline C and ethanol in
R$/litre, according to Major Regions and Federation Units. The study covered the
period 2003-2012.
Some concepts and information used in the introduction and explanation of the ethanol
and gasoline (1.2 and 1.3) variables were collected from UNICA, the Union of
Sugarcane Industries. Unica was also the source of some figures, such like ethanol sales
or sugar production.
The Elasticity of Demand for Gasoline in Brazil with the Flex-fuel Fleet
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Finally, the macroeconomic data on the Brazilian economy, including GDP data for the
period 2003-2012 was taken from IBGE - Brazilian Institute of Geography and
Statistics and IMF – International Monetary Fund.
5. Results
After the design of the multiple regression model with instrument variables – it yielded
the following result:
For this model the coefficient of determination R2 obtained was 95%. This signifies that
95% of data variability is explainable by the covariates of the regression model. The
result also shows that two explanatory variables were significant in the regression
model - they show a p-value below 0.05 – i.e. the price of gasoline and climate.
According to p-value, we are able to reject the null hypothesis (H0) that reflects the lack
of correlation between any of the variables and the price of hydrated ethanol fuel.
The Elasticity of Demand for Gasoline in Brazil with the Flex-fuel Fleet
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6. Conclusions
Ethanol will not easily recover its competitiveness towards gasoline. From 2010 and
until nowadays, ethanol became no more attractive to consumers, according to the 70%
ratio theory (see Annex Figure 6). It happened because of the sugar cane crops and
ethanol production, which were insufficient to ensure its competitiveness.
The variables that strongly influence ethanol prices, as noticed by the OLS model, are
climatic conditions and gasoline prices. Since 2008, and because of the reduction of
CIDE to zero, the source of volatility of gasoline became smaller, and the price
fluctuations are now only offset by an oil price increase or decrease. Nowadays, the
impact of gasoline price on ethanol price might be only residual, since gasoline’s price
is now stabilized.
So, the only change of ethanol, to readjust its price, is an outstanding sugar cane crop –
strongly dependent on weather conditions – and production.
The present research showed some of the weaknesses that exist in the pricing of ethanol
in the state of São Paulo. Nevertheless, considering the size of the ethanol market in this
state, the largest in the country, it is possible to generalize this complexity at a national
level. We can conclude that in the period 2003-2012, a part of the independent variables
of the linear multiple regression model influence the price of ethanol. They are: gasoline
prices and climatic conditions, as already mentioned above.
However, explaining the origin of ethanol prices in the Brazilian market is an issue that
goes far beyond the econometric models (PESSOA, REZENDE and ASSUNÇÃO,
2011), as the market price can be determined by companies, based on cost and profit
margins.
The Elasticity of Demand for Gasoline in Brazil with the Flex-fuel Fleet
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7. Annexes
Figure 1: Global Production of Ethanol (2013)
World
23448
Brazil
6267
Ethanol
USA
13300
0
5000
10000
15000
Millions of Gallons
20000
25000
Source: US Energy Information Administration (AIE)
Figure 2: Brazilian fleet of Otto light vehicles
(2006-2012)
35
30
Millions
25
20
Total Fleet
Flex-fuel
15
Gasoline
10
5
0
2006
2007
2008
2009
2010
2011
2012
Source: UNICA
The Elasticity of Demand for Gasoline in Brazil with the Flex-fuel Fleet
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Figure 3: Cultivated area with sugar cane (2003-2012)
12,0
Millions of Hectares
10,0
8,0
South-Central Region
6,0
North-Northeast Region
Brazil
4,0
2,0
0,0
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Source: UNICA
Figure 4: Production of Ethanol in Brazil and by Regions
(2003-2013)
25000
Thousand m3
20000
15000
Brazil
North - Northeast Region
10000
Center - South East Region
São Paulo
5000
0
Source: UNICA
The Elasticity of Demand for Gasoline in Brazil with the Flex-fuel Fleet
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Figure 5: Consumption of Fuels in the state of São Paulo
(2010-2013)
18,00
16,00
Billions of Gallons
14,00
12,00
10,00
Gasoline
8,00
Ethanol
6,00
4,00
2,00
0,00
2010
2011
2012
2013
Source: UNICA
Figure 6: Price elasticity of ethanol in Brazil
(2003-2012)
3,5
3
Price $R/L
2,5
2
Ethanol Price
1,5
Gasoline Price
1
Price Elasticity of Ethanol
0,5
0
2003
2004
2005
2006
2007
2008
2009 2010
2011
2012
Ethanol Price
1,35
1,21
1,39
1,63
1,45
1,45
1,49
1,67
2
2,94
Gasoline Price
2,07
2,08
2,34
2,55
2,51
2,5
2,51
2,57
2,73
2,74
Price Elasticity of Ethanol
1,44
1,45
1,63
1,78
1,75
1,75
1,75
1,79
1,91
1,91
Source: ANP and IBGE
The Elasticity of Demand for Gasoline in Brazil with the Flex-fuel Fleet
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8. References
ANDERSON Soren T. (2011). The Demand for Ethanol as a Gasoline Substitute.
ANP – Agência Nacional de Petróleo, Gás Natural e Biocombustíveis.
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BOFF H. P. (2011). Modelling the Brazilian Ethanol Market: How Flex-fuel Vehicles
are Shaping the Long Run Equilibrium. China-USA Business Reviews, 10 (4), 245-264.
CORREIA Eduardo Luis (2007). A Retoma do Uso de Álcool Biocombustível no Brasil.
Empresa de Pesquisa Energética (EPE). Balanço Energético Nacional 2013.
https://ben.epe.gov.br/BENRelatorioFinal2013.aspx
FEIJÓ F., ALVIM A. M. (2008). Impactos Econômicos para o Brasil de um Choque
tecnológico para a produção de Etanol. ANPEC – Associação dos Centros de Pósgraduação em Economia.
FERREIRA, A., F. PRADO, and J. Silveira (2009). Flex cars and the alcohol price.
Energy Economics, 31(3), 382-394.
FONTANA, José Domingues (2011). Biodiesel para leitores de 9 aos 90 anos. Editora
UFPR.
GOLDEMBERG José, et al. (2008). Bioenergia no Estado de São Paulo: situação
actual perspetivas, barreiras e propostas. São Paulo: Imprensa Oficial do Estado de
São Paulo.
GORTER Harry de, et al (2013). An Economic Model of Brazil’s Ethanol-Sugar
Markets and Impacts of Fuel Policies.
GUJARATI, Damodar N., PORTER, Dawn C. (2009). Basic Econometrics. 5 ed.
McGraw Hill.
HAIR Jr. J. H., ANDERSON R. E., et al (2005b). Análise Multivariada de Dados. 5 ed.
Porto Alegre: Bookman.
International Monetary Fund (IMF). World Economic Outlook (January 2014).
http://www.imf.org/external/pubs/ft/weo/2014/update/01/index.htm
LIMA Nilton Cesar (2011). A Formação dos Preços do Etanol Hidratado no Mercado
Brasileiro de Biocombustíveis.
The Elasticity of Demand for Gasoline in Brazil with the Flex-fuel Fleet
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PESSOA, João Paulo, et al (2011). Flex Cars and Competition in Ethanol and Gasoline
Retail Markets.
SAIZ Albert, WACHTER Susan. Immigration and the Neighborhood. American
Economic Journal: Economic Policy 3 (May 2011): 169–188.
SALVO A., HUSE C. (2010a). Consumer Choice between Gasoline and Sugarcane
Ethanol. Northwestern University and Stockholm School of Economics.
US Energy Information Administration (EIA).
http://www.eia.gov/cfapps/ipdbproject/IEDIndex3.cfm?tid=5&pid=53&aid=1
WOOLDRIDGE, Jeffrey M. (2009). Introductory Econometrics: A Modern Approach,
4 e. South-Western Cengage Learning.
The Elasticity of Demand for Gasoline in Brazil with the Flex-fuel Fleet