ISSN 2776-110X
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Assesing The Relationship Between Oil Rent.
Energy Consumption.
And Government Expenditure In Indonesia Muhammad Rama Ma'rufin1.
Muhammad Ikrom Alfareza2 Islamic Economics study program.
Department of Economics.
University of Jember.
Indonesia Abstract This study was conducted in Indonesia to analyze the relationship between oil rent, energy consumption, and government spending.
This study uses annual data obtained from world bank publications.
The data analysis method used is VECM.
This study finds in Indonesia, there is a three-way casual relationship between energy use and oil rent, but no causal relationship between variables.
This indicates in the greater Indonesian energy consumption, the higher the profit level of Indonesia's oil and gas sector.
Energy consumption has no impact on government expenditure in Indonesia.
So that the policy of limiting the consumption of fossil fuels such as environmental taxes does not significantly suppress the state's development from government expenditure and can actually increase state revenues so that it has the potential to increase development.
Suggestions for future research is to include including environmental tax variables to measure potential environmental tax revenues in Indonesia.
Keyword : Energy Consumption.
Government Expenditure.
Oil Rent.
VECM.
JEL Classification : C01.
H52.
O14.
O44 Received September 30, 2022.
Revised October 11, 2022.
Accepted October 20, 2022 A 2021 PT.
Frost Yunior rights reserved.
DOI : 10.
54204/AEBD/Vol5No1October2022010 Introduction In this globalization era, various kinds of commodities have been traded between countries in international trade in order to meet domestic needs (Viphindrartin.
Wilantari.
Prabowo.
Sasongko, & Priyanto, & Bawono, 2.
Energy is one of commodities which is most traded in the world, including oil.
Oil is a vital commodity for every country because it becomes the source of energy in every country (Sasongko.
Widarni, & Bawono, 2.
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Consumption of oil and fossil energy is at risk of increasing environmental pollution through increasing carbon dioxide (Yanto, 2.
Therefore, the uncertainty of supply and demand of oil is often considered very crucial for several countries in the world because it affects their economy (Umar.
Su.
Rizvi, & Lobon, 2.
Berument.
Ceylan, & Dogan, .
, state that a country's economic structure and its dependence on oil will determine how changes in oil prices affect it.
importing or exporting country.
This means that the impact that occurs due to the erratic nature of global oil prices is strongly influenced by the role taken by the country the global market for oil, besides the significance of the oil commodity for the survival of the country's economy.
Energy plays an important role in human life and economic activities.
Every society and economic activity requires energy, such as transportation, production activities, telecommunication systems, etc (Mofijur.
Fattah.
Alam.
Islam.
Ong.
Rahman.
Najafi.
Ahmed.
Uddin, & Mahlia, 2.
Energy demand in various sectors causes dependence on fossil fuels and continuously reduces the stock and reserve of fossil fuel energy (Martins.
Felgueiras.
Smitkova, & Caetano, 2.
On the other hand, dependence on fossil fuels in various sectors can have negative impacts on the environment such as pollution and climate change (Arroyo & Miguel.
Indonesia is an ASEAN country with the largest energy consumption.
Energy consumption in Indonesia grew about 3.
96% per year in 2019, energy consumption percapita also increased by 24% since 2010, the average of 10 years grew about 2.
8%, and energy production grew about 3.
70% per year (Sewandono & Munandar, 2.
It shows that the high need and demand for fossil energy fuels in Indonesia is unavoidable.
The high demand and consumption of fossil fuel energy requires the government to control its price, or else inflation will occur (Krane, & Idel, 2.
Indonesian government provides subsidy and compensation which are budgeted in the state budget to control the inflation rate and maintain society purchasing power (Erga, & Kasikoen, 2021.
Alim.
Setiyantono, & Zakiah.
As the demand for fossil fuel energy continuously increases, the subsidy and compensation provided by government will also increase (Ichsan.
Lockwood, & Ramadhani.
Indonesia is a country that actively carries out international trade activities or commonly referred to as export-import.
In the energy sector.
Indonesia also exports a large amount of oil.
becomes one of the sources of revenue that has an important role for the state budget.
The value of oil exports in 1970-2002 was quite large and contributed about 43% to Indonesian government revenue (Dartanto, 2.
Moreover, at that time world oil prices experienced an increase which had a direct impact on state revenue from oil rent.
An increased state revenue can provide an opportunity for the government to increase government expenditure because of the need to enhance economic performance surplus state budget (Liu.
Saleem.
Al-Faryan.
Khan, & Zafar.
Table 1.
Government revenue and expenditure of oil rent in 2000-2010 .
n billion of USD) Revenue Oil rent
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
16,1 14,3 10,8 11
13,5 14,3 19,5 15,3 22,4 12,2 16
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Fuel Subsidy 10,8 3,1 6,2 of 59,01 65,73 39,81 37,27 63,70 69,23 31,79 49,67 48,21 25,4 38,75 fuel subsidy to oil rent Crude oil price (USD/barre.
oil lifting cost .
housand barrel 1405 1273 1320 1092 1072 999 1000 899 931 944 954 per da.
Source : world bank Table 1 shows that the Indonesian government has spent an average of 52.
8% of its oil revenue or rent per year on fuel subsidy.
Following the rise and fall in oil prices will be the volatiliyu of oil rent, then government responds by adjusting the amount of fuel subsidy.
As seen during the 2008 global financial crisis, a sharp increase in oil prices of 25 USD was followed by an increase in oil revenue from 15.
3 USD to 22.
4 USD.
Likewise with subsidy which is adjusted with the increase in oil prices from 7.
6 USD to 10.
8 USD.
Of course, the value of the fuel oil subsidy which has a large proportion will affect the total government expenditure because it absorbs most of the state budget and ultimately results in fiscal pressure.
Oil export activities can increase oil revenues but on the other hand oil import activities amid the large domestic energy demand will increase government expenditure (Solaymani, 2.
With the high value of oil exports, the there will be extra non-tax income from the tax and profitsharing revenues.
from oil rent but government expenditure will also increase to subsidize fossil fuel energy due to the increasing of its needs (Nurfatriani.
Sari.
Saputra, & Komarudin, 2.
This is what makes it an important object to study.
This study aims to analyze short and long term relationship between fossil fuel energy consumption, oil rent, and government expenditure.
Literature Review Some studies had examined the effect of oil rent and price such as Eltony & Al-Awadi .
for the case of Kuwait, and Olomola & Adejumo .
for Nigeria case.
Unfortunatelly, only some studies which include government expenditure in the analysis such as the study of Jbir & ZouariGhorbel .
for the case of Tunisia.
Farzanegan & Markwardt .
for the Iranian Tijerina-Guajardo & Pagyn .
for the case of Mexico, and Esfahani.
Mohaddes, & Pesaran, .
for the case of Iranian economy in the long run.
Another studi of Hesami.
Rustamov.
Rjoub, & Wong, .
analyzed the response of fiscal in Middle Eastern countries to oil revenue or rent fluctuation.
Oil rent plays an important role in the government revenue (Mohammed.
Karimu.
Fiador, & Abor, 2.
by creating a model that links slow growth with the inverse relationship between natural resources and growth rate with government expenditure (Erum & Hussain, 2.
lowering costs is essential to obtaining significant economic success and performance the level 109 | P a g e International Thematic Research on International Trade and Business in Indonesia ASIAN Economic and Business Development Volume 5.
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and volatility of government expenditure (Migkos.
Sakas.
Giannakopoulos.
Konteos, & Metsiou.
Tijerina-Guajardo & Pagan .
explain that if country relies heavily on oil revenue in government expenditure, its economic condition will also depend heavily on the changes of world oil prices which will automatically reduce oil rents.
Uncertain declines in oil revenues will lead to fiscal imbalances.
Gochberg & Menaldo, 2.
explains that government revenue from oil rent is often overestimated and misused.
In addition, future expectations of income that are too high and then do not match the realization of income will increase the fiscal deficit.
Classical economic theory explains that abundant Natural resources can be advantageous impact on the economy (Kronenberg, 2.
Also, classical economists argue that natural resource is one of the top ten influential factors influencing economic growth in several empirical studies (Doppelhofer.
Miller, & Sala-i-Martin, 2.
On the other hand, many According to studies, natural resources abundance has a negative correlation on the economy, for example the study of Sachs & Warner .
, and Sala-i-Martin .
This situation is also known as Authe paradox of plentyAy.
The study of Kronenberg .
found that natural resource abundance in developing countries of Eastern Europe is associated with slower economic growth.
Likewise, the study of Sachs & Warner .
found that almost all countries economic growth occurs when natural resources are abundant.
that tends to stagnate since the early 1970s.
Gylfason .
also found that Long-term economic expansion is typically slower in some rich natural resources countries.
Alfaki & El Anshasy, .
argue that the biggest issue with dependence is connected to the erratic nature of oil prices and the dwindling supply of Oil rent is very volatile due to changes in world oil prices.
On the other hand, oil as non-renewable energy will continue to decrease and even its reserves will be depleted over time.
Therefore, the sale or exploitation of oil will not always be profitable (Gelb, 1.
Oil industry analysts distinguish oil reserves into two, namely proven reserve and probable reserve.
Proved reserves are reserves that have been and are expected to be mined now, within the last five years, and probable reserves are those that have been discovered but have been found but have not yet been used for either technical or economic reasons (Pollo.
Alexandrino.
Augusto, & Hantao, 2.
In the fulfillment of the energy needs of each country, of course, it is not only supplied from within the country but also from other countries, so it is necessary to carry out the international The price difference between world and domestic oil prices is often very unequal, so in this case the government must provide subsidies or compensation through government expenditure (Schaffitzel.
Jakob.
Soria.
Vogt-Schilb, & Ward, 2.
This causes energy consumption growth to be faster quicker than economic expansion.
Alternatively put In other words, the large energy subsidies result in very excellent energy efficiencies in these nations (Bildirici.
Castanho.
Kayky, & Geny, 2.
High levels of fossil fuel energy consumption as a result of Some researchers predict that Iran will eventually experience price distortions that will convert it from a net exporter to an importer (Couharde & Mouhoud, 2.
Energy subsidy patterns must be reformed to generate broad support and generate broad benefits.
Reasonable The cost of living of individuals will be significantly impacted by an increase in energy and the elimination of subsidies.
will have a significant impact on people's cost of living 110 | P a g e International Thematic Research on International Trade and Business in Indonesia ASIAN Economic and Business Development Volume 5.
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unless another fiscal or social action is taken (Husaini.
Puah, & Lean, 2.
The social impact of rising energy prices on various low- and middle-income societies can be mitigated by redistributing some of the increased government revenues through discrete transfers to lowincome societies (Taghizadeh-Hesary.
Rasoulinezhad.
Shahbaz, & Vo, 2.
Research Method This study was conducted in Indonesia to analyze the relationship between oil rent, energy consumption, and government expenditure.
This study used annual data obtained from the publication of the world bank.
The data analysis method used is VECM.
Modeling using VECM is based on time series data which is not stationary but cointegrated.
If it the projection is made It will make mistake regression results when using non-stationary data.
(Gujarati, 2.
If the If spurious regression is interpreted incorrectly, the analysis's findings will be incorrect, that would lead to poor conclusions.
being taken so that the policies made will be wrong.
A unit root Test is utilized to test the constancy the information.
It used Augmented Dickey-Fuller (ADF).
If ADF test statistic value is less than the critical value for the MacKinnon table with db = n - k, where k = number of parameters and n = number of observations.
H 0 is accepted or the data are Conversely, if the ADF test higher worth than all of the MacKinnon table important value, so H0 can be rejected or the data can be concluded to be stationary.
Another important aspect of VAR estimation model testing is determining the lag of System VAR.
ideal lag is required to record the impact of person changes in the VAR system.
There are several criteria using methods like Akaike's to calculate the ideal latency AIC, also recognized as Schwartz's Information Criterion (SCI).
Hannan Quinn.
Final Prediction Error (FPE), and (HQ).
A cointegration test is used to assess whether variables have a long-term relationship, whether they are independent or dependent.
Cointegrated variable is a variable that does not contain a unit root and does not have an intercept (Wardhono, 2.
This study uses the Johannes test to find cointegration on variables.
Granger causality is a test used to see causality or reciprocity between two variables so that it can be seen whether the two variables statistically influence each other .
wo-way or reciprocal relationshi.
, have a unidirectional relationship or have no relationship at all (Gujarati, 2.
The the VECM concept an formula with each variable acting as the dependent variable.
A feature of VECM is that the model includes an ECT component, or error correction term.
The VECM's standard form model such as the dimensions of lag 1 .
OIycyc = yuyceycOe1 yn1 OIycycOe 1 yn2 OIycycOe2 U ynycyOIycycOeycy 1 syc Where yceycOe1 OIycyc = ycUycOe 1 Oe .
uc yuiXycOe.
: 1st derivative vector of dependent variable OIycycOe 1 : 1st the dependent variable's derivative vector with first lag yceycOe1 : inaccuracy resulting from the Y-X regression equation at lag-1 syc : remaining triangle yu : matrix of cointegration constants yui : coefficient matrix of required element -i, where i = 1, 2, .
, p 111 | P a g e International Thematic Research on International Trade and Business in Indonesia ASIAN Economic and Business Development Volume 5.
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After estimating the VECM model, we need to explain the structures produced by the model.
could shape the role of the impulse response (IRF)to describe consequently its model dynamic structure and determine the shocks effects among variables.
In other words.
IRF represents the shock behavior of one variable over another at certain period of time, so the length in terms of the dependent variable effect on the shock in the mistake phrase using the values of the standard deviation of the VECM method (Gujarati, 2.
Forecast error variable decomposition (FEVD), also referred as variance decomposition, is a complex mechanism of the Vector error correction model that divides different possibilities variation.
VD was performed then IRF test, however unlike VD, was associated with shifting of shock effects to other variables in current and future period of time.
Result and Discussion In this study, doing a unit rest on the data from three variables is the first step in the data analysis Based on data processing.
Results are displayed in a table 2.
Table 2.
Unit root check
Variable Alpha
Oil Rent
Energy Consumption Government expenditure Stat ADF
-0,591
p-value 1st different Stat.
ADF
p-value Based on Table 2 it can be seen that the oil rent, energy consumption and government expenditure data are data containing unit roots at the level or not staying put at level .
It can be seen that what the unit root test revealed, the value of of the ADF statistic for the energy consumption and government expenditure variables are greater than A = 5%, this means that H0 is accepted, which means that the data is station or there is unit root in the data Although the unit root test on oil rent has a statistical p-value of ADF smaller than A = 5% which means that the data is stationary, but if one of the variables data is not stationary then the other variable data must also be tested by unit root at the same level so that Oil rent data will also be tested by unit root at the 1st different level with other variables that are not stationary.
The first unit root test's outcome showed different level indicate that all variable data have an ADF statistical p-value smaller than A = 5% so that H0 is rejected, which imply that there is no unit root in the data or is stationary.
Thus, the oil rent, energy consumption, and government expenditure variables are initially non-stationary at first different.
Before the cointegration test, the optimal amount of lag must be determined.
The results of the optimal lag test demonstrate that Final Prediction Error (FPE).
Akaike Information Criterion (AIC).
Schwarz Information Criterion (SCI), and Hannan Quinn (HQ) indicators indicate that the optimal lag is 1.
Then, before conducting further analysis, it is necessary to determine whether the model is stable has been given at first difference and lag-1.
The AR roots able output in Table 2 indicates that the model is stable, which is characterized by a modulus value that is less than 1 .
so that a cointegration test can be performed to determine the analytical method to be used.
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Table 3.
Stability test output Root Modulus 891604 - 0.
Cointegration test result for lag 1 of oil rent, energy consumption, and government expenditure variables using trace statistics is shown in Table 3.
Table 4.
Cointegration test output Unrestricted Cointegration Rank Test (Trac.
Hypothesized Trace No.
of CE.
Eigenvalue Statistic Critical Value Prob.
None * At most 1 At most 2 In Table 4 .
The outcome of a hypothesis test employing trace statistics is evident.
show that ycy ycycaycoycyce is 0.
0001 which is less than = 5%.
The value of the trace statistics is 49.
257 which is greater than 29.
In light of this, it can be said that there is just one cointegration equation.
It was decided to use the Granger Casualty Test to assess the causal relationship between the in this study.
Table 4 shows the results, which show that ranger causality test results, oil rent has no causal relationship to government expenditure and conversely, with the probability of 0.
888 and 604 which are greater than the alpha value of 0.
Energy consumption also does not have causal relationship with government expenditure and conversely, with probability values of 0.
276 which are greater than the alpha value of 0.
The same result also occurs in the casual connection between energy usage and oil rent, where the output of the granger accident test shows that energy consumption does not have a causal relationship with oil rent and conversely, with probability values of 0.
178 and 0.
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Table 5.
Granger causality test output Null Hypothesis:
Obs F-Statistic Prob.
OIL_RENT does not Granger Cause GOV_EXPEN GOV_EXPEN does not Granger Cause OIL_RENT ENERGY_CON does not Granger Cause GOV_EXPEN GOV_EXPEN does not Granger Cause ENERGY_CON ENERGY_CON does not Granger Cause OIL_RENT OIL_RENT does not Granger Cause ENERGY_CON VECM Estimation :
D(Oil_Ren.
= - 0.
749619287312 ( Oil_Rent(-.
352825548916 gov_Expen(-.
63892846873 energy_Con(-.
* - 46.
3159558962 ) - 0.
0318392096759d(Oil_Rent(-.
) 439639805563d(Gov_Expen(-.
) 0.
138429349148d(Energy_Con(-.
) - 1.
D(Gov_Expe.
= 0.
0614314662751(Oil_Rent(-.
352825548916gov_Expen(-.
63892846873energy_Con(-.
- 46.
3159558962 ) 0.
0627494150301d(Oil_Rent(-.
) 0699865417173d(Gov_Expen(-.
) - 0.
232332299556d(Energy_Con(-.
) 0.
D(Energy_Co.
= - 0.
00925598824052( Oil_Rent(-.
352825548916gov_Expen(-.
63892846873energy_Con(-.
- 46.
3159558962 ) - 0.
00168097477478d(Oil_Rent(-.
) 121020809728d(Gov_Expen(-.
) - 0.
419232171587d(Energy_Con(-.
) 1.
Based on the above model.
Energy Consumption has a significant positive causality relationship with oil rent with a coefficient of 0.
638 so an increase in energy consumption of one unit will increase oil rent by 0.
638 units in the long run.
However, other variables do not have a significant causal relationship.
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Response to Cholesky One S.
Innovations Response of OIL_RENT to OIL_RENT Response of OIL_RENT to GOV_EXPEN Response of OIL_RENT to ENERGY_CON Response of GOV_EXPEN to OIL_RENT Response of GOV_EXPEN to GOV_EXPEN Response of ENERGY_CON to OIL_RENT Response of ENERGY_CON to GOV_EXPEN Response of ENERGY_CON to ENERGY_CON Response of GOV_EXPEN to ENERGY_CON Figure 1.
Impulse Respons Output When conducting an impulse response analysis, impulse response function (IRF).
The results of the IRF plot can be seen in Figure 1.
It can be seen that there are 9 IRF plots for the next 30 periods, which visually explain a response of varible to other variables that arise due to a shock of 1 standard deviation either from its variable or other variables.
Based on Figure 1, the IRF analysis of oil rent response for the next 30 periods shows that oil rent response from the shock of itself tends to be high in the first period but has negative trend until the 6th period.
This means that oil rent shock to itself tends to weaken until 30th period and begin to stabilize and stagnate in the 7th to 30th period.
Meanwhile, the response of oil rent to government expenditure shock is increased until the 2nd period but after the 2nd to 5th period it decreased, which means its response weakens.
The response to oil rent to government expenditure shock begin to stabilize and stagnate in the 6th until 30th period.
On the response of oil to the instruction by hand rent to energy consumption shocks has a negative trend until the 7th period, meaning that its response However, after the 7th period, its response begin to stabilize and stagnate until the 30th The IRF analysis of government expenditure response for the next 30 periods shows that the government expenditure response to the shock of itself is very high and has a positive trend until the 5th period, meaning that the response is strengthening.
After the 5th period, the response begin to stabilize and stagnate until the 30th period.
However, the government expenditure response to the oil rent shock has a positive trend until the 5th period and begin to stabilize and stagnate until the 30th period.
On the other hand, the government expenditure response to energy 115 | P a g e International Thematic Research on International Trade and Business in Indonesia ASIAN Economic and Business Development Volume 5.
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consumption shock has a negative trend until the 4th period, meaning that its response tends to Its response also begin to stabilize and stagnate in the 5th period to the 30th period.
The IRF analysis of the energy consumption response for the next 30 periods shows that the energy consumption response to the shock of itself is quite high but has a negative trend until the 4th period, meaning that its response tend to weaken.
However, it also begin to stabilize and stagnate in the 8th untill 30th period.
Energy consumption response to oil rent shock has positive trend until the 5th period, meaning that it is strengthening before finally it is stable and stagnant until the 30th period.
On the other hand, the response of energy consumption to government expenditure shock tends to fluctuate until the 7th period before finally becoming stable and stagnant until the 30th period.
Variance Decomposition using Cholesky .
Factors Variance Decomposition of OIL_RENT OIL_RENT GOV_EXPEN ENERGY_CON Variance Decomposition of GOV _EXPEN OIL_RENT GOV_EXPEN ENERGY_CON Variance Decomposition of ENERGY _CON OIL_RENT GOV_EXPEN ENERGY_CON Figure 2.
forecast error decomposition variance (FEDV) output 116 | P a g e International Thematic Research on International Trade and Business in Indonesia ASIAN Economic and Business Development Volume 5.
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Figure 2 shows the summary of FEDV analysis result for each variable.
the outcome of the FEDV analysis for oil rent something in the sentence , shocks to itself cause 95% fluctuations and become the largest contributor to the changes in oil rent, but in the long run, they decline until the 30th period, and in the end, the changes in oil rent is contributed by government expenditure by 49% and energy consumption by 31 percent which are greater than the oil rent contribution which is only 20% in the 30th period.
The results of the FEDV analysis for government expenditure show that the change in government expenditure is more influenced by its variable than oil rent and energy consumption, and tends to be stable and stagnant since the 2nd period, with respectively contributions of 85%, 14%, and 1%.
The same evidence happened to the results of the FEDV analysis for energy consumption which show that the change in energy consumption is more influenced by its variable than other variables, namely oil rent and government expenditure, and tend to be stable and stagnant since the 3rd period, with respectively contributions of 77%, 20%, and 3%.
Conclution There is a tangential connection between energy use and oil rent in Indonesia, but There is no passing connection between variables and this indicates that the higher the energy consumption in Indonesia, the higher the profit level in the oil and gas sector in Indonesia.
Energy consumption has no impact on government expenditure in Indonesia.
So that the policy of limiting the consumption of fossil fuels such as environmental taxes does not significantly suppress the state's development from government expenditure and can actually increase state revenues so that it has the potential to increase development.
Suggestions for future research is to include including environmental tax variables to measure potential environmental tax revenues in Indonesia.
References