Download Relationship between oil revenues and government expenditure

Economics and Finance Review Vol. 2(5) pp. 52 – 61, July, 2012
Available online at http://www.businessjournalz.org/efr
ISSN: 2047 - 0401
Relationship between oil revenues and government expenditure using
wavelet analysis method: Evidence from Iran
Mansour Garkaz (Corresponding Author)
Department of Accounting,Ali Abad katoul Branch ,Islamic Azad University ,Ali Abad katoul, Iran
E-mail: [email protected]
Fereydoon Azma
Department of Management,Ali Abad katoul Branch ,Islamic Azad University ,Ali Abad katoul, Iran
E-mail: [email protected]
Reza Jafari
Department of management&Accounting,Ali Abad katoul Branch ,Islamic Azad University ,
Ali Abad katoul, Iran
E-mail: [email protected]
ABSTRACT
Oil export revenues has a highly percentage of the government annual budgets in Iran, therefore has
a strategic role in the structure of the Iranian economy. This article tries to examine the relationship
between oil exports revenues and government expenditure in Iran over the period 1996 - 2007 by
using Wavelet analysis approach. This method help us to detail the main curve of these two variables
to different wavelets in separate categories, so this analyze shows the correlation between them
better and the results are more predictable. We can find a significant impact of oil export revenues
on government expenditure at different period of time. Our results show a strong positive
relationship between these two variables during long term period.
Keywords: Oil revenues, government expenditure, Wavelet analysis approach
INTRODUCTION
Oil is one of the main sources of energy that always had an effective role on the world economy and
the macroeconomic variables, especially in the oil exporting countries to justify their influence.
Detailed look at the world around can be found that any activity is not possible without the use of
energy and the economy of human society is impossible without it. The unique role of oil revenue in
economy of Iran can be seen in structure of government budget and social programs. There are a
large number of papers examining the empirical relationships between oil revenue and oil price
shock. As is evident from these studies, oil price changes and revenues can highly influence the
government programs. Thus it appears that managing of oil revenues can highly influence on state
welfare programs.Despite higher oil price and government revenue in recent years, Iran has a lot of
problem about finance the economic projects that express the problem in financial management. As
we know Iran is the second largest oil producer in the Organization of the Petroleum Exporting
Countries (OPEC). Iran’s economy is largely dependent on oil and is highly susceptible to oil price
shocks. Iran has experienced strong oil revenue and government expenditure in recent years due to
the rise in international oil price. What is certain, whatever the amount of oil revenue dependent
economies are more changes is more marked. However, the economic impact of increased oil
revenues in oil exporting countries is the controversial issues of political economy so that it can be
observed in the way government spending, economic structure and government behavior inside the
country. Iran's oil revenues in the economy as a key variable in determining the form of government
expenditure on current costs and development play a real role. Iran’s government as a main recipient
of oil revenues should distribute oil rents in structure of economy and also pay different kinds of
subsidies. Statistics obtained from the Central Bank of Iran in the period of 1996 - 2007 indicates
even with two different governments as well as different politics, economy dependent on oil revenue
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Economics and Finance Review Vol. 2(5) pp. 52 – 61, July, 2012
Available online at http://www.businessjournalz.org/efr
ISSN: 2047 - 0401
has not only decreased but also in many cases even increased. Therefore global oil price changes on
the overall government policy have had a significant impact.Should be noted that the share of
construction costs and current funding ratio is more important than the government investment rate
shows. The average share of current expenditures in period of 1996-2008 is about 70% whereas the
average share of capital expenditure over the same period is about Iranian budget determined of
about 30% therefore most of government expenditure reflect themselves in current payment.Oil
revenues from the perspective of macroeconomic Petroleum Exporting Countries like Iran is a direct
function of two variables, the global price of crude oil and its export value. Change the value of oil
prices for all crude oil producers and exporters, including Iran, is almost a function of supply and
global demand, but the amount of crude oil production and export capabilities and decisions to shortterm and long-term depends on each of the manufacturers. The ascending process of becoming
global crude oil prices and consequently increase GDP in oil exporting countries like Iran, the two
phenomena can be observed, at first country's foreign exchange earnings are increasing and secondly
increasing hope for people to improve community welfare. It should noted that the abundance of oil
revenues in exporting countries like Iran could be causing the Dutch disease to increase consumer
costs, especially on imported goods and lack of coordination between economic sectors and national
economy.It is clear that government policies determining factor in the economic situation and
people's livelihood and the possible fiscal policy is more dependence on oil revenues, the economy is
more challenging experience. This issue in Iran that government have a fully control on oil exports
revenues and the public sector is a component of income can be seen clearly. In fact, the problems of
single-product economy and excessive reliance on oil revenues in Iran, the country's economy
heavily has influenced by external factors including fluctuations in world oil prices. Surely this
dependence if not realize the anticipated revenues from oil exports, the government not only on
various projects and economic will have problem, but on the economy and future government
programs and projects to improve the welfare of people had negative effects double and thus will be
cause many problems in the country. The significant point is that the steady increase in oil prices in a
country like Iran, although causes increased oil revenues and the government each pay a charge
easily, but for most people has had, rising inflation, increasing commodity prices and harder to live,
so that the IMF has argued, government policies to control inflation and liquidity in no way has
failed to increase oil revenues and operating costs of government failure in these policies to control
liquidity and inflation. In other words, despite the significant increase in government wealth during
2003 to 2009, financial ability Petroleum Exporting governments for not properly planning costs
have fallen. In fact, oil revenue is now spending in the form of government expenditure need an
efficiency management. On the other hand increasing the government spending, the direct and
indirect, aggregate demand will increase greatly the community and with regard to structural
bottlenecks, which has supplied goods and services, the gap between demand and supply in large
community and will increase inflation.
Considering the above we can say that the biggest negative impact on the economy of oil income is
coverage of economic weaknesses and inefficiencies in Iran. On the other hand, although Iran
foundations of production and technology and business environment component is advanced, but
massive oil wealth without the trouble has been provided to the community, the country's row with
developing countries and per capita income has relatively high.
Generally, in economics such as Iran's economic structure that is very dependent on oil, when oil
projects are difficult, other industries are also affected especially when government funding is
reduced, investment in oil industry and consequently reduced investment in other industries, and this
creates many problems for the economy.
Figure 1 shows the annual values from oil revenue; government consumer expenditure (G.C.E) and
investment expenditure (I.E) that state in Iran over 1996 to 2008. Figure 1 illustrates the curves of
these values that requests in the years clearly expressing a desire to increase consumption in the
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Economics and Finance Review Vol. 2(5) pp. 52 – 61, July, 2012
Available online at http://www.businessjournalz.org/efr
ISSN: 2047 - 0401
economy in the form of current and development spending (investment) since 1996. As is evident
from this figure, there is a relationship between oil revenues variations and G.C.E and I.E changes.
Table 1 summarizes the status of Iran's economic development over the period of this research.
As can be seen economic boom during the third development plan (2000-2004) despite the high
growth government spending, has reduced government size in the central and public levels of
government. However, the size of public sector due to the dramatic increase in current expenses
owned enterprises, banks and state-profit agencies is larger during the program. In 2005, current and
development expenditures at all levels of government to a significant growth in 2004 had become
much larger, leading to the three levels of government are mentioned.
In the years 1997 to 1999 that Iran's oil revenue due to price fluctuations reduced, government
spending and budget policies based monetary contraction figure facing that affected by spending,
government funding and bank credits is in the range of 5 to 7 thousand million dollars and the cash
rate between 11 to 19 thousand million dollars. As a result of economic growth between 2 and 4
percent are limited. But the years since 2002 that oil revenues will grow and affect the government
expenditure, public funds and easing monetary base figures from the banking system 12 thousand
million dollars over the border and especially in the years after 2005 that figure was a sharp increase
of oil revenues monetary base from 22 to 54 thousand million dollars has increased.
MATERIALS AND METHODS
Regarding the effects of oil revenues on government consumption expenditure in few studies
conducted so far and this paper is trying to pay closer examination of this issue. There are several
models to explain behavior of some macroeconomic variables and relationship between them. Many
of researchers suggested some models to explain these relationships. To develop the experience in
these contexts we can point the fallowing models:
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Economics and Finance Review Vol. 2(5) pp. 52 – 61, July, 2012
Available online at http://www.businessjournalz.org/efr
ISSN: 2047 - 0401
Abeysinghe (2000) model
Abeysinghe formulated a structural VARX model to link up the GDP series through a trade matrix.
Oil prices affect consumption expenditure, investment expenditure and the trade balance directly,
and play a legitimate role in the model.
Wagner’s ‘law’ of expanding state activity
Wagner’s ‘law’ of expanding state activity, is the proposition that there is a long run propensity for
government expenditure to grow relative to national income. In fact this law explains there is a long
run propensity for the scope of government to increase with higher levels of economic development.
Wagner’s ‘law’ is not really a theory of public expenditure growth but, rather, a generalization
concerning the secular trend of public spending.
Vector autoregressive model (VAR)
The vector auto regression (VAR) model is one of the most successful, flexible, and easy to use
models for the analysis of multivariate time series. It is a natural extension of the univariate
autoregressive model to dynamic multivariate time series. The VAR model has proven to be
especially useful for describing the dynamic behavior of economic and financial time series and for
forecasting. It often provides superior forecasts to those from univariate time series models and
elaborate theory-based simultaneous equations models. Forecasts from VAR models are quite
flexible because they can be made conditional on the potential future paths of specified variables in
the model. The VAR model provides a multivariate framework where changes in a particular
variable (oil price) are related to changes in its own lags and to changes in other variables and the
lags of those variables.
Structural Vector Autoregressions (SVARs)
This model is a multivariate, linear representation of a vector of observables on its own lags. SVARs
are used by economists to recover economic shocks from observables by imposing a minimum of
assumptions compatible with a large class of models. This article reviews, first, the relation of
SVARs with dynamic stochastic general equilibrium models. Second, it discusses the normalization,
identification, and estimation of SVARs. The article finishes with an assessment of the advantages
and drawbacks of SVARs.
LITERATURE REVIEW
Economic research studies has been regarding the impact of crude oil on the country's economy
largely focused on the effects of oil price shocks on economic growth of countries and supply and
demand in international market. Studies in this regard can be cited as follows:
Zonnoor, S. H (1995) examined the growth of government expenditures and revenues in Iran over
the period of 1970 - 1990 in light of conventional theories as to the nature of public sector economic
activity. In his study simple forms of government expenditure and tax functions are estimated. They
also examined the speed of the adjustment process by estimating a simple disequilibrium model of
government expenditures and receipts. Using a constant shares model as well as a constant marginal
shares model, they compared the pattern of expenditures and the revenues structure before and after
the Iran’s revolution.
Richard G Zind (1999) in his study assessed the impact on the sectoral outputs of these pressures and
of the offsetting government budget deficits. The findings indicated that, in the resulting equilibrium,
sectoral output growth was maintained but at a considerably lower rate. Other findings related to the
sectoral re-allocations of national output and to major differences among the member States in the
sectoral allocations of their national outputs.
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Economics and Finance Review Vol. 2(5) pp. 52 – 61, July, 2012
Available online at http://www.businessjournalz.org/efr
ISSN: 2047 - 0401
Raguidin and Rayes (2005) using an unrestricted vector autoregressive model (VAR) examined the
effect of oil price shocks on the Philippine economy from 1981 to 2003.
El-anashasy (2006) examined the relationship between oil price and government consumption
spending on Venezuela’s economic performance over the period of 1950-2001 by employing
modeling VAR and VECM.
Mehrara, M; Niki Oskoui, K (2006) studied the sources of macroeconomic fluctuations in oilexporting countries using a structural VAR approach. They defined four structural shocks, which are
identified as nominal demand, real demand, supply, and oil price shocks. They found that oil price
shocks are shown to be the main source of output fluctuations in Iran.
Mohammad Reza Farzanegan and Gunther Markwardt (2007) studied the dynamic relationship
between oil price shocks and major macroeconomic variables in Iran by applying a VAR approach.
The study points out the asymmetric effects of oil price shocks; for instance, positive as well as
negative oil price shocks significantly increase inflation. They found a strong positive relationship
between positive oil price changes and industrial output growth. They identified a marginal impact of
oil price fluctuations on real government expenditures.
Arman, A; Aghajari, SJ (2009) investigated the impact of oil revenue on the inflation and growth
rates of Iran in the period of pre-exchange rate reform of 1993. They found out that oil revenue only
influences growth by a slow direct effect. Also inflation is influenced by oil revenue through a direct
effect, foreign prices, and the real exchange rate. The net effect is that greater oil revenue has tended
to reduce inflation, though the effect has been greatest since the revolution.
Salehi Esfahani, H; Mohaddes, K(2009) developed a long run growth model for a major oil
exporting economy and derives conditions under which oil revenues are likely to have a lasting
impact. They showed that (log) oil exports over the period 1979-2006 enter the long run output
equation with a coefficient equal to the share of capital and found clear evidence for two long run
relations: an output equation as predicted by the theory and a standard real money demand equation
with inflation acting as a proxy for the (missing) market interest rate. They also defined that the
Iranian economy adjusts quite quickly to the shocks in foreign output and oil exports, which could be
partly due to the relatively underdeveloped nature of Iran’s financial markets.
Mehrara, M., Maki, M. and Tavakolian, H. (2010) studied the non-linear relationship between oil
revenues and real output growth of the Iranian economy during 1959–2007 using a threshold error
correction model. They showed that the response of economic growth to oil revenue growth in low
regimes of oil revenues is greater than in high regimes of oil revenues.
Mohammad Hassani and Amirali Nojoomi (2010) employed the error correction version of ARDL
procedure to examine the factors determining Iran's oil revenues using the time series data for 19702008. The model found that factors such as oil production, oil price, and oil proved reserves have
long run effects on Iran oil export revenues. In the long–term, the effects of variables such as
domestic oil consumption and world oil production are negative.
Mohammad Reza Farzanegan (2011), in his study analyzed the dynamic effects of shocks like
international sanctions on different categories of the Iranian government expenditures from 19592007 using impulse response functions (IRF) and variance decomposition analysis (VDC) techniques
and expressed that only the military expenditures of Iran respond significantly to a shock in oil
revenues (or oil prices), while non-military expenditure categories do not show significant reactions
to such innovations.
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Economics and Finance Review Vol. 2(5) pp. 52 – 61, July, 2012
Available online at http://www.businessjournalz.org/efr
ISSN: 2047 - 0401
DATA AND METHODOLOGY
Statistical data
Data used in the analysis are seasonal time series on oil revenues as the independent variable and
government consumption expenditure as the dependent variable during the period 1996–2008. This
information is accessible from site of Central Bank of Iran.
Methodology
In this paper, we examine changes in variables of different pay intervals by using wavelet analysis.
Wavelet Transform is a new mathematical technique that a lot of interest in its use in solving
engineering problems in recent years is observed. This method is suitable for analyzing non-stable
waves. Using Wavelet transform reviews can analyze the main wave in various areas of time and
frequency. Root of Wavelet analysis method was taken in Fourier function except that Fourier sine
and cosine waves are with clear frequencies and the period while on the wavelet domain are limit
defined. Unlike the Fourier transform the wavelets are in terms of scale and position appropriate and
provide efficient method for analyzing complex signals and therefore give out more accurate results
that are also more credibility. Idea of a complete set of functions was used to display a special
function defined by Fourier in 1806. In 1909 Haar was the first person who pointed to the wavelet.
Fourier functions only be used for reliably and efficiently functions and because of we often need
information on time – frequency, Gabor in 1946 solved the problem by using window functions. But
the story of wavelet really began from 1980. In 1982 Murelt, used the wavelet concept as a tool for
analyzing the signal of earthquake. At the same time Grassman obtained inversion formulas for
wavelet. The first step in wavelet analysis is drawing the time-series diagrams. Using SPSS and
MATLAB software, drawing and values of each variable statistical information obtained. In the
second stage of normal data and fitted regression line equation is obtained for it. The line equation is
shown by:
y = a + bx+ε
In the third stage using the software MATLAB, the initial graph to a number of different frequencies
wavelet analyses obtains for each of the corresponding regression equation. If deviations wavelet
descriptive statistics is negligible compared to the initial data choice models are approved.
Considering the above model can be selected the following display:
S=
This formula represents “S” as main wave and
low-frequency waves or other words indicating a
low frequency sine wave (large period) that give the overall changes in two variables to one another.
Respectively
represent the low-frequency waves to high for each category and can be
related to:
=
+
For “S” the regression line equation is obtained by:
For
the regression line equation is obtained by:
For
the regression line shown by:
S= 0.996x + 10046
= 2.333x – 18661
= 0.369x - 236.92
= 0.903x + 23.3
= 0.412x – 2.821
= - 0.94x + 21.27
= - 0.726x - 239
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Economics and Finance Review Vol. 2(5) pp. 52 – 61, July, 2012
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ISSN: 2047 - 0401
In this research we can use the software subject to the initial wave of seasonal values of the
corresponding amounts in the five levels of decomposition that can be established as the following
equation:
∑(
)
“i” represent the row relating to the above numbered corresponding season and changes from 1 to 48.
“j” shows the number of category.
shows numeric value of wave at point i and
also
represents the wave component at point (i, j).
According to Figure 2 that shows the Scatter plot of two variables, we can say that the true
relationship between them exists.
Descriptive statistics for two variables "revenues from oil exports “and"government consumption
expenditures“, also are presented in Table 3.
Descriptive Statistics
Table 2. Descriptive statistics
Government consumption expenditure
Oil income
Mean
44016.7750
49962.0563
Std.deviatinon
1.281E9
1.490E9
Variance
35790.51801
38598.76882
Skewness
.0979
1.044
Kurtosis
-.0249
. 002
Pearson Correlation
R Square
0.964
0.93
Criteria skewness of two variables shows that both the community has different symmetry of normal
distribution and the right are crooked, but the coefficient indicates that the strain distribution of oil
revenues in terms of population distribution is almost normal. The government consumption
expenditure strain is slightly different with normal distribution. Pearson correlation between two
variables is 0/964 which indicates a strong correlation between them. The coefficient of
determination equal to 0.93 is obtained and represent, 93 percent of government consumption
expenditure changes being explained by oil revenues.
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Economics and Finance Review Vol. 2(5) pp. 52 – 61, July, 2012
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Linear relationship between two variables by the regression equation is shown below:
Y = - 633.248 + 0.894x
Y: Government consumption expenditure
X: Oil income
The elongation and skewness criteria show, these two variables are not normally distributed and are crooked to
the right.
Figure 4 shows the seasonal values of two variables “revenues from oil exports” and “government consumption
expenditures”. Now if any of these graphs using the Wavelet transform daubcies 4 detail in different scales and
analysis any of them by using regression, results can be obtained according to
Table 3. The results show
significant
relationship
between
two
variables
at
different
time
intervals.
DETAILED DISCUSSION AND CONCLUSIONS
So what is noted in countries with structure of economy like Iran has greatly increasing in
government revenues can directly and indirectly cause increasing in government spending and the
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Economics and Finance Review Vol. 2(5) pp. 52 – 61, July, 2012
Available online at http://www.businessjournalz.org/efr
ISSN: 2047 - 0401
demand for the entire community Petroleum exporting countries oil revenues is a directly function of
two variables, the global price of crude oil and its export value. Theoretically negative impact of oil
revenue boom can contract the manufacturing sector of trade and industrial goods and expands the
business services sector. It can be seen how to spend oil revenues in the form of current and
development spending by the government. Statistics show that 80-70 percent of export earnings and
50-40 percent of Iran's budget comes from oil. On the other hand, increasing revenues and overall
government spending can cause of domestic consumption growth and will require more imports.
Although in most developed industrial countries with great oil revenues such as Norway, politicians
believe that oil consumption and injection revenues to Norway’s economy is harmful, but this pattern
cannot be seen in a country like Iran and therefore will affect the different parts of the economy.
With the values of decomposed curves "oil revenue” and "government consumption expenditures",
compare the corresponding values of each level and calculating descriptive statistics can also be
observed that in the short term, medium as well as long term the most cost changes by government
consumption variable be explained by oil exports income. Linear correlation between two variables
in the three-month intervals and six-month is in the average and in the nine-month intervals and
annually is relatively high. Also, linear correlation between variables in the long run is high that
show much desire to use this income.
Considering the results we can say there is a significant relationship between two variables at
different time periods as shown with . In
that is the three-month period equivalent to twovariable, linear correlation is moderate voters, but by changes in government consumption spending
oil revenue is explained considerably light, by increasing to six-month time scale, the linear
correlation of two variables in comparison with the before condition will be to poor but in ninemonth time scale as well as annually and also more than yearly scale, the linear correlation are
relatively high and therefore can be concluded there have
always been government policy in
spending oil revenues and only its intensity in different time intervals is changed .
So we can see that, with increasing wavelet scale a stronger positive relationship between two
variables exists. On the other hand, absolute values of “coefficient of regression line” indicate the
degree of correlation between two variables with the wavelet scale increases, this relationship
become stronger.
The next step is to review the analysis of variance and standard deviation of two variables.
According to the calculations done, can be seen that the variance of two variables initially dropped at
first and then increased again expressing uncertainty of two quantity variables. Of course this
uncertainty about "revenues from oil exports" is more. According to the previous comment about the
symmetry of the two variables are different with normal distribution, can be known the amount of
volatility in oil revenues intervals in oil prices and changes in export value. Also high correlation
between government consumption spending and oil revenues explains its deviation from the mean.
One of the biggest negative impacts on the economy of oil income is coverage of economic
weaknesses and inefficiencies of it. In these circumstances the government expenditures are not
financed by taxpayers, and since the result of oil revenue performance was not up economic sectors,
increasing their boom shows no real economy, thus increasing revenues and injected them into the
community quickly leads to increased prices. In this case there is no government funding restrictions
and can immediately invest in the process of economic development and define new projects that
many of them might not be justified economically and therefore only increase government spending.
Iran's economic development issue is not resources, but is resource management. Even oil resources
accumulate the physical capital but if other crunchers determine economic growth does not fall into
consideration, achieving continuous growth and the upside is not possible.
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Economics and Finance Review Vol. 2(5) pp. 52 – 61, July, 2012
Available online at http://www.businessjournalz.org/efr
ISSN: 2047 - 0401
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