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Income Elasticity for Consumer Goods in OECD Countries

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Abstract

The paper covers analysis of influence of GDP for household final consumption expenditure in 15 European countries UE plus 4 candidates as UE members of OECD: Czech Republic, Hungary, Poland and Slovak Republic. Our researches have shown considerable differentiation in macroeconomic features between candidates and newcomer countries and those that created UE. Econometric models proved that income elasticity of demand for the first group estimated for years 1994-2000 is similar to elasticity for the second group for years 1970 -1980
BOLESLAW BORKOWSKY, HANNA DUDEK, WIESLAW SZCZESNY
100
Testata
BOLESLAW BORKOWSKI
Warsaw Agricultural University
Income Elasticity for Consumer
Goods in OECD Countries
Agribusiness Paesaggio & Ambiente
--
Vol. VII (2003) n. 2, Marzo 2004
BOLESLAW BORKOWSKI - HANNA DUDEK - WIESLAW SZCZESNY
Income Elasticity for Consumer Goods in OECD Countries.
The paper covers analysis of influence of GDP for
household final consumption expenditure in 15 European countries UE plus 4 candidates as UE members of OECD:
Czech Republic, Hungary, Poland and Slovak Republic. Our researches have shown considerable differentiation in
macroeconomic features between candidates and newcomer countries and those that created UE. Econometric models
proved that income elasticity of demand for the first group estimated for years 1994-2000 is similar to elasticity for the
second group for years 1970 -1980.
The demand for
consumer goods is
strongly connected
to income (W
1998). Lately the
methods of demand
analysis have
developed rapidly.
Many various
econometrical
methods have been
applied to the
analysis of the
consumption level both in macro and micro
scale. In many empirical studies, the objects of
estimation are elasticities.
Elasticity of demand is widely used for
researching influence of a given factor on
demand. It is expressed by the following ratio:
where:
- estimated demand,
- i-th factor, i=1,2,..,k
Income elasticity of demand informs of the
percentage change in the demand for consumer
good resulting from one-percentage change
in income, when all other variables are
constant.
Usually income elasticities of demand for
consumer goods are positive. Sometimes there
are exceptions to the rule in case of such
products like: bread, potatoes, flour where
income elasticity of demand can be negative.
(Adamowicz 2000).
In order to make research for consumer
demand some econometric models are applied
as :
•Linear
•Double-log model
•Working’s model
•Törnquist’s models (por. Borkowski, Dudek,
Szczesny 2003).
i
i
x
yx
y
y
x
E
i
= ˆ
ˆ
ˆ
kikii xbxbby
+
+
+
=
...
ˆ110
k
b
ki
b
ii xxby = ...
ˆ1
10
+++=
ki
k
i
ix
b
x
bby 1
...
1
exp
ˆ
1
10
101
Income elasticity of demand for consumer goods in OECD countries
Most researches on income elasticity of demand
are focused on analysis of different social-
economical situated households budgets. There
are a few of them interested in the macro scale
problem considering different countries
including time in the issue.
The work concerns analysis of income
influence on the global consumer demand in
15 European countries UE plus 4 candidates
to UE being members of OECD: Czech
Republic, Hungary, Poland and Slovak
Republic. The years considered in the research
go from 1970 to 2000. Due to the great
difficulty in assessing income values because
of different currencies and inflation, the gross
domestic product per capita in USD at prices
of 1995 as a explanatory variable and
household final consumption expenditure as
explained variable, had to be used.
1. Methods of analysis1. Methods of analysis
1. Methods of analysis1. Methods of analysis
1. Methods of analysis
At the first stage of the researches we divided
the countries examined into homogeneous
groups. The groups have been chosen taking
into account the following macroeconomic
features collected from Eurostat in years 1994-
1999:
X1- direct foreign investments in percentage of
GDP;
X2- percentage of unemployment;
X3- exports of goods and services in percentage
of GDP;
X4- imports of goods and services in percentage
of GDP;
X5- average year inflation in percentage;
X6- rural population in percentage to the whole
population;
X7- GDP per capita in constant prices of 1995
in USD;
X8- added value in agriculture in percentage of
GDP;
X9- added value in industry in percentage of
GDP;
X10- added value in services in percentage of
GDP;
X11- employment in agriculture in percentage
of the whole employment;
2. Empirical results2. Empirical results
2. Empirical results2. Empirical results
2. Empirical results
We preferred the division of objects into 2
groups according to the chosen criterion. There
have been differences mostly between the
groups and lesser inside them.
The first group consists of 8 countries:
Greece, Ireland, Czech Republic, Hungary,
Spain, Portugal, Slovak Republic and Poland.
Finland, Germany, Sweden, Netherlands,
Denmark, France, United Kingdom, Belgium,
Austria and Italy belong to second group. The
X12- employment in industry in percentage of
the whole employment,
X13- employment in services in percentage of
the whole employment.
The chosen period of time is so short because
of lack of data for Czech and Slovakia before
1994.
The above mentioned features have been
adopted by using unitarization methods as
follows:
.
},...,1:min{},...,1:max{
},...,1:min{
nixnix
nixx
x
ii
ii
i==
=
=
To set up homogeneous groups of countries
the GCCA by using Gini and grade
correspondence indicators algorithm have been
adopted. What makes this method very
interesting and useful is the fact of showing
objects and features on an over-representation
map (Ciok and others 1995). It helps to point
out features which account for the main
differences of objects into groups.
Two econometric models are applied :
• Linear
• Double-log model
where:
yit - household final consumption expenditure
in i-th country in t-th year (per capita in USD
at prices of 1995),
xit - gross domestic product in i-th country in t-
th year (per capita in USD at prices of 1995),
t - year.
21
0
ˆbb
itit txby =
BOLESLAW BORKOWSKY, HANNA DUDEK, WIESLAW SZCZESNY
102
Testata
features such as average year inflation, GDP
per capita, employment in agriculture and
services in percentage of the whole employment
differ the groups the most.
Fig. 1
The draft of the analysis of differences inform
of the over-representation map
Source: Own draft. Description of the countries up to the
ISO standards.
The first group consists of 8 countries: Greece,
Ireland, Czech Republic, Hungary, Spain,
Portugal, Slovak Republic and Poland.
Finland, Germany, Sweden, Netherlands,
Denmark, France, United Kingdom, Belgium,
Austria and Italy belong to second group. The
features such as average year inflation, GDP
per capita, employment in agriculture and
services in percentage of the whole employment
differ the groups the most.
Correlation of expenditures for consumption
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
 
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
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$
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Source: Own computing
Tab. 1
Dispersion of data
and GDP in the first group (0,9680) has been
much higher than that in the second (0,9005).
The level of consumption in the countries with
lower incomes has proved stronger relation
with incomes.
Parameters of both econometrical models
have been estimated separately in the groups.
It has shown the following results:
Group I
Group II
values in parenthesis are standard errors of
regression coefficients.
In the double-logs model we have omitted
the variable t due to lack of statistical
significance.
The countries of lower GDP have shown a
considerable increase of expenditures for
consumption when GDP increased in
comparison with the countries with the higher
GDP. The growth of one unit in GDP has
brought about extra expenditures for
consumption by 0,54 in average in the first
group, while the same phenomena has caused
the growth of only 0,36 units in the second
group.
The first group includes the countries which
have had their market transformation especially
in the second half of 90. This transformation
txy itit 37,3 25359,072,65046ˆ += 9350,0
2=R
[12 338] [0,0192] [16,80]
8702,0
97,1
ˆitit xy = 9462,0
2=R
[0,6 6] [ 0,03 16]
txy itit ++= 42,1003588,055,195819
ˆ 8152,0
2=R
[10608,3] [0,0222] [53,21]
6950,0
02,12
ˆitit xy = 8011,0
2=R
[5,14] [0,0404]
103
Income elasticity of demand for consumer goods in OECD countries
G
has made considerable changes in consumption
such as diversification of incomes, increase of
prices and diminishing of food demand . The
above mentioned phenomena have appeared
in the first group. It therefore explains high
income elasticity of demand for consumer
goods.
The question is whether such phenomena
took place also in the second group in an earlier
period, let say about 10 years ago.
Surveys for years 1984-1990 have shown
the following:
Estimated models for years 1980-1986 are:
For years 1970-1980 we got the following
results:
The results have showed similarity of income
elasticities of demand for the first group rela-
tive to the years 1994-2000 and the second
one relative to the years 1970-1980. The first
group, consisting mostly of candidates to the
UE and newcomer countries to the UE, has
the similar income elasticity to those which
created the UE.
3. Conclusions3. Conclusions
3. Conclusions3. Conclusions
3. Conclusions
Our researches have shown considerable
differentiation in macroeconomic features
between candidates and newcomer countries
and those ones which created the UE.
Econometric models proved that income
elasticity of demand for the first group
estimated for years 1994-2000 is similar to the
elasticity for the second group for years 1970-
1980.
ReferencesReferences
ReferencesReferences
References
Adamowicz M. (2000),
Demand and supply elasticity
,
Warszawa.
Borowska A., Dudek H., Szczesny W. (2002),
Choosing
functional forms and method of estimation in food demand
models
, Statistical Messages, 7.
Borkowski B., Dudek H., Szczesny W. (2003):
Econometrics
, Choice issues, PWN, Warszawa.
Ciok A., Kowalczyk T., Pleszczyñska E., Szczesny W.
(1995),
Algorithms of grade correspondence cluster analysis
,
The Collected Papers on Theoretical and Applied Computer,
Science, 7.
Kukua K. (2000),
Zero Unitarization Method
, PWN,
Warszawa.
Mergos G., Mizzi L. (1999),
Analysis food demand during
transitions to a marked economy
, IAMO, Vissenschaftsverlag
Vauk, Kiel.
Ostasiewicz W. (1999),
Statistical methods of data analysis
,
Wroc³aw.
Szczesny W. (2002),
Grade correspondence analysis applied
to contingency tables and questionnaire data
, Intelligent Data
Analysis, vol. 6.
WA. (1998)
, Food demand elasticity and supply elasticity
of farming and food products
, Agro-business encyclopaedia,
Warszawa .
Zeliaœ A. (2002),
Taxonomic analysis of spatial
differentiation of life standard in Poland in dynamic formulation
,
Kraków.
Elasticità della domanda rispetto alElasticità della domanda rispetto al
Elasticità della domanda rispetto alElasticità della domanda rispetto al
Elasticità della domanda rispetto al
reddito per i beni di consumo neireddito per i beni di consumo nei
reddito per i beni di consumo neireddito per i beni di consumo nei
reddito per i beni di consumo nei
paesi dell'OECDpaesi dell'OECD
paesi dell'OECDpaesi dell'OECD
paesi dell'OECD
Sommario
: Introduzione; 1. Metodi di analisi; 2. Risul-
tati empirici; 3. Conclusioni
Il lavoro riguarda l’analisi dell’influenza del PIL sulla spesa per i
consumi finali interni di 15 paesi Europei più 4 candidati membri
dell’OECD: la Repubblica Ceca, Ungheria, Polonia e la Repub-
blica Slovacca. Le nostre ricerche dimostrano notevoli differenze
nelle caratteristiche macreconomiche tra i candidati - i nuovi
membri e i Paesi che formarono inizialmente l’UE. Modelli
econometrici hanno dimostrato che l’elasticità del reddito per la
domanda del primo gruppo, stimata per gli anni 1994-2000 è
simile all’elasticità per il secondo gruppo per gli anni 1970-1980.
txy itit 37,3 25359,072,65046ˆ += 9350,0
2=R
[12 338] [0,0192] [16,80]
8702,0
97,1
ˆitit xy = 9462,0
2=R
[0,6 6] [ 0,03 16]
txy itit ++= 42,1003588,055,195819
ˆ 8152,0
2=R
[10608,3] [0,0222] [53,21]
6950,0
02,12
ˆitit xy = 8011,0
2=R
[5,14] [0,0404]
txy itit ++= 29,1133807,00,221484
ˆ 9319,0
2=R
[56905,2] [0,0135] [28,68]
7318,0
97,7
ˆitit xy = 9159,0
2=R
[2,19] [0,0264]
txy iti ++= 91,114250,087,21252
ˆ 9304,0
2=R
[56082,6] [0,0143] [28,31]
7730,0
17,5
ˆitit xy = 9298,0
2=R
[1,38] [0,0259]
txy iti ++= 96,235038,099,46624
ˆ 9544,0
2=R
[42120,8] [0,0201] [21,39]
8542,0
30,2
ˆitit xy = 9457,0
2=R
[0,86] [0,0359]
... Polish and Italian consumption profiles are much different ( Borkowski et al., 2004). In the Italian diet the following products are dominant: fruits (twice as high consumption as in Poland), vegetable oils and fish (almost 40% more in comparison to Poland), vegetables, milk and stimulants (almost 15% more in comparison to Poland). ...
Choosing functional forms and method of estimation in food demand models, Statistical Messages
  • M Adamowicz
  • Warszawa
  • A Borowska
  • H Dudek
  • W Szczesny
Adamowicz M. (2000), Demand and supply elasticity, Warszawa. Borowska A., Dudek H., Szczesny W. (2002), Choosing functional forms and method of estimation in food demand models, Statistical Messages, 7. Borkowski B., Dudek H., Szczesny W. (2003):
Analysis food demand during transitions to a marked economy, IAMO, Vissenschaftsverlag Vauk
  • Warszawa Pwn
  • G Mergos
  • L Mizzi
, Algorithms of grade correspondence cluster analysis, The Collected Papers on Theoretical and Applied Computer, Science, 7. Kukua K. (2000), Zero Unitarization Method, PWN, Warszawa. Mergos G., Mizzi L. (1999), Analysis food demand during transitions to a marked economy, IAMO, Vissenschaftsverlag Vauk, Kiel. Ostasiewicz W. (1999), Statistical methods of data analysis, Wroc³aw. Szczesny W. (2002), Grade correspondence analysis applied to contingency tables and questionnaire data, Intelligent Data Analysis, vol. 6.
Food demand elasticity and supply elasticity of farming and food products, Agro-business encyclopaedia
  • A Wooe
Wooe A. (1998), Food demand elasticity and supply elasticity of farming and food products, Agro-business encyclopaedia, Warszawa. Zeliaoe A. (2002), Taxonomic analysis of spatial differentiation of life standard in Poland in dynamic formulation, Kraków.