determinants of total consumption in sudan

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Determinants of Total Consumption Expenditure in

Sudan: An Empirical Study, 1970-1994

Badreldin Mohamed Ahmed Abdulrahman

Department of Economics, Faculty of Economics and Social Studies, University of

Zalingei, West Darfur, Sudan.

[email protected] or [email protected]

Abstract:

The objective of this paper is to examine empirically the determinants of

total consumption expenditure in Sudan over the period 1970-1994.

Annual time series data has been used in the analysis to estimate a linear

form of the model for the period. Total consumption of expenditure and

national income are the dependent variable and explanatory variable

respectively. The analysis coverage the period 1970-1994, where the data

were obtained from central bureau of statistic. Using these data OLS

technique is applied to a linear form of the standard model. The result

indicates that the major determinant of total consumption expenditure is

national income during the period under consideration.

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1. Introduction:

Consumption is a common concept in economics, and gives rise to

derived concepts such as consumer debt. Generally consumption is

defined by opposition to production. But the precise definition can vary

because different schools of economists define production quite

differently. According to some economists, only the final purchase

of goods and services constitutes consumption, and every other

commercial activity is some form of production. Other economists define

consumption much more broadly, as the aggregate of all economic

activity that does not entail the design, production and marketing of

goods and services (e.g. "the selection, adoption, use, disposal and

recycling of goods and services").

Likewise, consumption can be measured by a variety of

different metrics such as energy in energy economics . The

total consumer spending in an economy is generally calculated using

the consumption function, a metric devised by John Maynard Keynes,

which simply takes the aggregate disposable income and multiplies it by

a "marginal propensity to consume". This metric essentially defines

consumption as the part of disposable income that does not go

into savings. But disposable income in turn can be defined in a number of

ways - e.g. to include borrowed funds or expenditures from savings.


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Studies of consumption investigate how and why society and individuals

consume goods and services, and how this affects society and human

relationships. Contemporary studies focus on meanings of goods, role of

consumption in identity making, and the 'consumer' society (e.g. Douglas

et al.). Traditionally, consumption was seen as rather unimportant

compared to production, and the political and economic issues

surrounding it. With the development of a consumer society, increasing

consumer power in the market place, the growth in marketing,

advertising, sophisticated consumers, ethical consumption etc, it is

recognized as central to modern life. Sociology of consumption has

moved well beyond Thorstein Veblen's early work inconspicuous.

Current theories investigate the role of economic and cultural factors in

constraining consumption (Bourdieu), as development of an approach

that sees consumers as 'victims' of producers and their social situation. A

counter theory highlights the subversive aspects of consumption, with

consumers buying and using goods, places etc in ways unintended by the

producers. Examples include city squares turned to skateboard parks, and

music sharing on the internet.

Studies of consumption come from a variety of backgrounds. Consumer

studies attempt to help marketing. User research aims to improve product

design. Feminist studies highlight the importance of women as

consumers, and particularly the role of the domestic arena in

consumption. Media studies try to understand the consumption of media

products such as television and video games. Cultural Studies is


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interested in the role of material goods in culture (e.g. Mackay) Critical

Theory is an important influence on contemporary studies, as

consumption is central to contemporary culture. Domestication

theory focuses on mass market technologies.

Studying consumption can be done through traditional survey methods, or

various ethnographic techniques. Consumption studies are difficult

because they involve investigating everyday life situations, bringing

research into the private domain, rather than formalized settings such as

the workplace (wikapedia the free Encyclopedia, 2010).

Consumption creates the demand for something. Meanwhile once

demand is create supply is created. Supply is the manufacturer of the item

which is being consumed, or is in demand. That is basically how an

economy works Supply and demand.

Incomes and prices are seen as consumption's two major determinants.

The determinants are as follows:

1. Current disposable income

2. Relative income.

3. Life cycle income.

4. Wealth.

5. Price Level.

6. Rate of Interest.

7. Expected future income.

8. Others: advertisement, social safety-net, availability or scarcity of

loan, geographical location, weather etc.


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Objectives of the paper:

The objective of this paper is to examine empirically the determinants

of total consumption expenditure in Sudan. For this purpose a model is

specify with real consumption as the dependent variable, and national

income as explanatory variable. Ordinary least squares (OLS) is applied

to the model using annual time series data covering the period (1970-

1994).

The rest of this paper is organized as follows. Section two briefly

reviews the literature, while section three specifies the model. Section

four reports the empirical results. The summary and concluding remarks

are given in section five.

2. Literature Review:

The behavioral economic concept of unit price predicts that

consumption and response output (labor supply) are determined by the

unit price at which a good is available regardless of the value of the cost

and benefit components of the unit price ratio. Experiment 1 assessed 4

pigeons' consumption and response output at a range of unit prices. In one

condition, food was available according to a range of fixed-ratio

schedules, whereas in the other condition, food was available according

to a range of random-ratio schedules. Consistent with unit price

predictions, consumption and response output were approximately

equivalent across schedule types within the lower range of unit prices.


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However, at Unit Prices 64 (ratio value = 192) and greater, considerably

more consumption and response output were observed in the random-

ratio condition. Experiment 2 replicated these findings with 4 pigeons

using the rapid demand curve assay procedure that is commonly used in

the behavioral economics literature. Findings are integrated with two

mathematical models of behavior under variable reinforce delays

(Madden et al, 2005).

Consumption is normally the largest GDP component. Many

persons judge the economic performance of their country mainly in terms

of consumption level and dynamics.

According to Piano (2001), Consumption is the value of goods and

services bought by people. Individual buying acts are aggregated over

time and space. He argued that, first, consumption may be divided

according to the durability of the purchased objects. In this vein, a broad

classification separates durable goods (as cars and television sets)

from non-durable goods (as food) and from services (as restaurant

expenditure). These three categories often show different paths of growth.

Second, consumption is divided according to the needs it satisfies. People

in different position in respect to income have systematically different

structures of consumption. The rich spend more for each chapter in

absolute terms, but they spend a lower percentage in income for food and

other basic needs. The percentage values of an aggregation over all the

households in a country can thus be used for judging income

distribution and the development level of the society. The rich have both


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higher levels of consumption and savings. In differentiated product

markets, the rich can usually buy better goods than the poor. This

happens also because they tend to use different decision making rules. In

other words, consumption depends on social groups and their behaviors,

as well as their proneness to advertising. Third, for exactness' sake, one

should distinguish "consumption" as use of goods and services from

"consumption expenditure" as buying acts. For durable goods this

difference may be relevant, since they are used for long time periods.

Fourth, only newly produced goods enter into the definition of

consumption, whereas the purchase of, say, an old house is not

considered consumption, since it was already counted in the GDP of the

year in which it was built.

Consumption of animal source food has always been low and declining

as a result of the low production and continuously growing population.

Ethiopia per-capita consumption in 2004 declined by more than 10%

from an average of 20 kg in 1961, in contrary, the average world meat

consumption for example doubled (quoted in FAO, 2005).

Current income is the most relevant determinant of consumption. Income

comes from labor (employment and wages), capital (e.g. profit leading to

dividends, rent, etc) and remittances from abroad. Cumulated savings in

the past can be squeezed in case of necessity and give rise to a jump in

consumption, similarly with what happens with wealth increase, due for

instance to stock exchange boom or house prices boom. Expectations on


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future income, especially if concerning short-term credible events, may

also play an important role (Piano, 2001).

According to age of the decision-maker, individual and household

consumption varies, both in values and composition. Thus, aggregate

consumption may be influenced by demographic factors, such as an older

and older population, even though one should not rely too much on these

relationships since demographic variables are extremely slow in changes,

whereas consumption clearly reacts to economic climate. Other things

equal, a higher price level (inflation) reduces the real current income, thus

real consumption. A GDP component as it is, consumption has an

immediate impact on it. An increase of consumption raises GDP by the

same amount, other things equal. Moreover, since current income (GDP)

is an important determinant of consumption, the increase of income will

be followed by a further rise in consumption: a loop has been triggered

between consumption and income. An autonomous increase of

consumption, if at the same level of income, would reduce savings, but

the positive loop just described (known as the "Keynesian multiplier")

will imply an increase of income level with a positive impact on future

savings.

Per capita consumption rates in China are still about 11 times below

ours, but let’s suppose they rise to our level. Let’s also make things easy

by imagining that nothing else happens to increase world consumption —

that is, no other country increases its consumption, all national

populations (including China’s) remain unchanged and immigration


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ceases. China’s catching up alone would roughly double world

consumption rates. Oil consumption would increase by 106 percent, for

instance, and world metal consumption by 94 percent.( New York Times,

Jan, 2008).

Absolute income, lifecycle, permanent income and relative have been

the most variables that compound the consumption model in Sudan

during the period 1960-2000.(quoted in Elzibair,2007).

3. The Model and Research Methodology:

In this section we specify an empirical model and outline the research

methodology that will be adopted in the analysis. The model takes the

following form:

C = f(Y), f1> 0, (1)

Where:

C: total consumption Expenditure.

Y: national income

According to economic theory, national income (y) and prices of goods

are the main determinants of consumption expenditure. But in this paper

we used the national income as the only determinant of total consumption

expenditure of good and services in Sudan. Thus we supposed that


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national income has been played a key role in explanting of consumption

expenditure and determining of it.

We adopt ordinary least squares technique to the data covering the period

1970-1994. The data are collected from the central bureau of statistics in

republic of Sudan.

So it is important to note that the final consumption expenditure

(formerly total consumption) is the sum of household final consumption

expenditure (private consumption) and general government final

consumption expenditure (general government consumption).

The empirical result of the study is shown in next section.

4. The Empirical Results:

Applying ordinary least squares method to the data covering the

period (1980-2005) on the variables mentioned above, we estimated a

linear form of equation (1). The regression results are given in equation

(2) below, where the figures inside the brackets are t-ratios of the

estimated parameters.

C = 2.263 Y (2)

(102.016)

R2 = 0.998 F = 10407.304 DW = 2.597


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Equation (2) is statistically significant at the level 1% as indicated by the

(F) ratio. The value of R2 suggests that 99% of the variation in

consumption expenditure (C) is explained by variation in national income

(Y), while the Durbin-Watson statistics indicates the absence of serial

correlation in the model at the 1% level.

5. Conclusion:

This paper attempted to shows the determinants of total consumption

expenditure in Sudan over the period 1970-1994. Annual time series data

has been used in the analysis to estimate a linear form of the model for

the period. Total consumption expenditure is chosen as dependent

variable, while national income represents the explanatory variables. Data

for the study were obtained from central bureau of statistics in republic of

Sudan. Using these data OLS method is applied to the model. The

empirical result provides evidence that national income is the major

determinant of consumption expenditure during the study period.


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Reference:

1. Bertu, S and H. Kawashima: "Pattern and Determinants of Meat

Consumption in Urban and Rural Ethiopia".

2. Elzibair, M. M. (2007): "Consumption Function Estimation for Sudan

(1960-2000): unpublished M.Sc, Department of Economic, University

of Khartoum, Khartoum, Sudan.

3. Madden, G.J (etal) (2005). "Labor Supply and Consumption of food

in closed Economy under a range of fix- and random ratio schedules:

test of unit price", Journal of Experimental Analysis of Behavior

(JEAP).

4. New York daily news paper, Jan, 2008.

5. Piano, V. (2001), '' Consumption". Economic Web Institute

6. Wekipedia, the free encyclopedia.


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Appendices:

Table (A.1):

National Income (Y) in Sudan, 1970-1994.

Y Year

593.8 1970

702.0 1971

830.7 1972

1130.4 1973

1370.5 1974

1672.1 1975

2119.7 1976

2617.4 1977

3083.8 1978

3892.9 1979

4807.9 1980

6221.0 1981

8408.5 1982

10214.9 1983

13561.9 1984


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17803.3 1985

33167.5 1986

42463.7 1987

76615.1 1988

101720.7 1989

178336.5 1990

396304.0 1991

886656.0 1992

1736976.0 1993

3828565.4 1994

Source: Central Bureau of Statistics

Table (A.2):

Total Consumption Expenditure (C) in Sudan 1970-1994.

C Year

496.5 1970

559.5 1971

684.3 1972

776.5 1973

1026.5 1974

1378.5 1975

1576.7 1976


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2105.3 1977

2710.1 1978

3012.8 1979

3981.9 1980

5152.8 1981

6458.0 1982

9445.9 1983

11073.5 1984

15947.0 1985

19362.5 1986

32552.4 1987

41489.6 1988

74217.3 1989

101233.1 1990

174169.4 1991

362764.4 1992

836743.0 1993

1660369.0 1994

Source: Central Bureau of Statistics


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Regression:

Variables Entered/Removed (b,c)

Model

Variables

Entered

Variables

Removed Method

1 y(a) . Enter

a All requested variables entered.

b Dependent Variable: c

c Linear Regression through the Origin

Model Summary(c,d)

Model R

R

Square(a)

Adjusted

R Square

Std. Error of

the Estimate

Durbin-

Watson

1 .999(b) .998 .998 42305.99527 2.597

a For regression through the origin (the no-intercept model), R

Square measures the proportion of the variability in the dependent

variable about the origin explained by regression. This CANNOT

be compared to R Square for models which include an intercept.

b Predictors: y

c Dependent Variable: c

d Linear Regression through the Origin

Variables Entered/Removed (b,c)


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Model

Variables

Entered

Variables

Removed Method

1 y(a) . Enter



c Linear Regression through the Origin

ANOVA(c,d)

Model

Sum of

Squares df Mean Square F Sig.

1 Regression 186269646084

83.460 1

1862696460848

3.460 10407.304 .000(a)

Residual 42955133666.0

07 24 1789797236.084

Total 186699197421

49.460(b) 25

a Predictors: y

b This total sum of squares is not corrected for the constant

because the constant is zero for regression through the origin.

c Dependent Variable: c

d Linear Regression through the Origin


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Coefficients(a,b)

Model

Unstandardized

Coefficients

Standardized

Coefficients t Sig.

B

Std.

Error Beta

1 y 2.263 .022 .999 102.016 .000

a Dependent Variable: c

b Linear Regression through the Origin

Residuals Statistics(a,b)

Minimum Maximum Mean Std. Deviation N

Predicted Value 1123.4036

3756827.0

000 304940.0728 824172.65101 25

Residual -

156277.00

000

71738.515

63 -10546.64482 40913.70020 25

Std. Predicted

Value -.369 4.188 .000 1.000 25

Std. Residual -3.694 1.696 -.249 .967 25


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b Linear Regression through the Origin

Regression

Variables Entered/Removed(b)

Model

Variables

Entered

Variables

Removed Method

1 y(a) . Enter




20

Model Summary

Model R

R

Square

Adjuste

d R

Square

Std. Error

of the

Estimate Change Statistics

R

Square

Change

F

Change df1 df2

Sig. F

1 .999(a) .998 .997

41586.89

070 .998

9519.3

67 1 23

a Predictors: (Constant),

ANOVA(b)

Model

Sum of

Squares df

Mean

Square F Sig.

1 Regressi

on

164634

546829

19.200

1

16463454

682919.2

00

9519.3

67 .000(a)

Residual 397777

97990.23

17294694

77.848


21

492

Total 165032

324809

09.690

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a Predictors: (Constant), y

b Dependent Variable:

Coefficients(a)

Model

Unstandardized

Coefficients

Standardiz

ed t Sig.


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Coefficient

s

B

Std.

Error Beta

1 (Consta

nt)

-

12050.

603

8890.6

53 -1.355 .188

y 2.274 .023 .999 97.567 .000


determinants of total consumption in sudan

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