Economic analysis of the effect of financial sustainability indicators on economic growth in Iraq for the period (2004–2022)

Falah Thamer Alwan1
1 Kut Technical institute, Middle Technical University

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Экономика, предпринимательство и право (РИНЦ, ВАК)
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Том 13, Номер 11 (Ноябрь 2023)

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Аннотация:
The research aims to economically analyze the impact of financial sustainability indicators on growth in Iraq and give a future vision for financial sustainability indicators to reveal the factors that control the mutual influences between them. The research seeks to verify the hypothesis that there is an inverse correlation between the direction of financial policy tools and financial sustainability indicators. The research reached many conclusions, the most important of which is the existence of an inverse relationship between tax revenue growth rates and the total public debt to gross product index, and economic stability represents the necessary condition for growth. The research concluded with many recommendations. The research has found, through the indicator of the ratio of public debt to GDP, which is one of the most common indicators used by countries and institutions concerned in evaluating the level of debt, that the ratio of public debt to GDP in Iraq, as well as choosing the appropriate general budget style and not adopting budget items in circumstances Current Iraq is based on the fact that the general budget is a financial plan drawn up to achieve economic goals with the greatest possible satisfaction of society.

Ключевые слова: GDP, financial sustainability indicators, economic growth, ARDL model

JEL-классификация: O11, O40, E44



Introduction :

All countries in the world, regardless of their cultures and policies, whether financial or monetary, seek to achieve economic stability and sustainable development. But this will only be achieved by achieving a balance between its revenues and expenditures so as not to fall into the problem of the budget deficit and its inability to pay its debts in the long term. Therefore, it has become necessary for these countries to take preventive measures, by developing financial plans to measure the extent of the state’s ability to pay its obligations in the country. Long term, this is what achieves financial sustainability. Economic growth is one of the most important economic goals for all countries in the world, and Iraq is one of these countries. It always seeks to increase the per capita share of the gross domestic product. It is interested in financing various public spending programs, and that this financing be with its resources and without exposure to financial default and default. In the long term, this is by achieving financial sustainability. But this will only be achieved by efficiently allocating public resources, rationalizing public spending, and developing its revenues outside the field of hydrocarbons because Algeria is classified among the rentier countries that rely heavily on the hydrocarbon sector.

Research problem: All of the above leads us to pose the following problem: To what extent is Iraq able to achieve financial sustainability? What is its impact on economic growth in Iraq?

Research hypothesis: Since Iraq is primarily a rentier country, due to the dominance of oil revenues over its revenues the extent to which these revenues are affected by international oil prices, and the lack of diversification of sources of revenues outside the oil sector as required makes achieving financial sustainability almost impossible.

research importance: The importance of our research is evident in the fact that the concept of financial sustainability has become an absolute necessity, because achieving financial sustainability in the economies of various countries achieves financial stability in the long term, and of course, this financial stability reflects positively on increasing the per capita share of the gross domestic product and economic growth.

Research objectives: The study aims to analyze and measure financial policy in Iraq, by assessing the financial situation. The study also aimed primarily to measure the impact of financial sustainability on economic growth in Iraq.

Research Methodology: The subject of our study required us to adopt a descriptive and quantitative approach by using standard models to highlight the nature of the relationship between financial sustainability and economic growth in Iraq.

The first section: The conceptual framework of financial sustainability

First: The concept of financial sustainability

Recently, we have witnessed increasing interest in the issue of financial sustainability by many researchers, study centers, international financial institutions, and researchers. This term, in the general sense, refers to the ability to service public debt in the medium and long term without the occurrence of financial crises or severe pressures on the public financial situation, such as having to... To reduce public spending by a large percentage or stop public spending on some government activities. In this context, international experiences show that increasing levels of public debt in a way that exceeds the government’s ability to service it leads to public finances becoming unsustainable]1,p.308 [.

Defining financial sustainability: There are several definitions of financial sustainability, but there is no agreement on a specific definition for it, so we can define it as follows: -

Financial sustainability is defined as (the ability to avoid excessive debt by the government)]2,p.1 [.Or it is (how the government increases the primary surplus, not in the short term, but in the long term, which is largely appropriate to cover its current debt)]3,p.26 [.It is also defined as (a reflection of the long-term financing program in any country) or (the ability to achieve net revenues sufficient to cover the accumulated debt and its obligations.

Financial sustainability indicators:

First: The ratio of domestic public debt to GDP:

Despite the simplicity of this indicator, it has great importance in giving an overall picture of the burden of local public debt. It was relied upon as a basis for joining the European Union by the Maastricht Treaty in 1992, as the treaty stipulates that the public debt ratio should not increase. Domestic and external (60%) of the gross domestic product, exceeding the percentage is an indication that the government is entering into a debt crisis) ]4,p.7 [.

Second: Tax Gap Index]5,p.418-419 [.

This indicator is based on the idea of maintaining the required ratio of public debt to GDP. It follows that tax policy must aim to reduce the difference between taxes achieved for financial sustainability and actual taxes. Accordingly, the target tax-to-GDP ratio is:

(Target tax ratio to GDP = ratio of government spending to output (without interest payments) + (real interest rate - real output growth rate) x ratio of public debt to GDP).

It is often noted that the percentage of actual taxes collected annually, i.e. the proceeds of tax revenues available annually, is not sufficient to finance the burden of spending in a way that prompts the search for other funding sources. This indicator helps to monitor and analyze the development of tax revenues as it is one of the main variables in implementing policies. Public finances and financing the burdens of government activities, however, do not represent a sufficient condition for judging the sustainability of the government’s financial policies.

Third: Primary disability index:

This indicator depends on estimating the value of the primary deficit or surplus of the general budget by calculating the difference between public expenditures without interest payments and public revenues without interest collections, as this ratio indicates the strength of the restrictions imposed on decision-making regarding the annual general budget due to the increase in the burden of public debt. It results in crowding out other aspects of public spending in the general budget, which results in converting most public expenditures into inevitable expenditures]6,p.6 [. This indicator of the general budget is a necessary condition to ensure the stability of the ratio of public debt to output and financial sustainability, but it is not a sufficient condition to achieve this. In theory, to achieve financial sustainability, it is required that the budget continue to achieve a cumulative primary surplus over a long period, through which it guarantees the payment of the public debt burdens due annually. Two types of public debt indicators can be clarified as follows.

1- Internal public debt indicators: -

Internal or (local) public debt is the main source of financing the state’s general budget deficit and one of the financial policy tools for managing the national economy, and as such it is considered an economic phenomenon that exists in all countries. Therefore, it is clear that managing internal debt is one of the priorities of financial policy tasks, and it has become one of the It is necessary to control public debt, especially local government debt, which represents the largest portion of it, through a plan that balances the financing needed from real savings to finance investments, development needs, and the requirements of the state budget on the one hand, and the requirements of reducing this debt and then reducing its burdens.

2- Indicators of external public debt: -

Most economists have agreed that external debt can lead to an increase in the rate of economic growth in a country by increasing the resources available to that country, provided that the debt is used to finance successful investments. This is from a theoretical perspective. As for the scientific aspect, many studies have concluded that an increase in The level of debt will negatively affect economic growth. It is necessary to refer to indicators of external public debt and its development by finding the relationship between the cost of debt and some macroeconomic variables during a specific time.

Types of financial rules]7,p. 18-19 [.

1- Balanced - budget rule: (It aims to reduce the general budget deficit to a certain level, by rationalizing public spending and raising its efficiency. The “Maastricht” agreement of the European Union, which sets the maximum limit for the general budget deficit allowed to member states of the European Union. So that it does not exceed (3%) of the gross domestic product, and this goal represents the basis for regulating the general budget deficit to ensure the achievement of financial sustainability]8,p.18-19 [. The motive behind this is that increasing the deficit cancels the effect of public spending or tax reduction on Aggregate demand, especially as it requires abundant funds to cover it and thus crowd out the private sector, which limits the effectiveness of fiscal policy to achieve stability. On the other hand, reducing the deficit relative to GDP leads to an increase in the growth of the average per capita share of output by a range of (0.25-0.5%)]9,p.230 [

2- Debt rule. It aims to set a safe limit for the total public debt that society can bear without having negative effects on stability and economic growth, International Monetary Fund experts believe that the resulting percentage of public debt should not exceed (60%), but this percentage cannot be relied upon. In determining an ideal ratio for public debt, especially since this ratio varies from one country to another depending on the differences in many factors and variables, and therefore the size of the debt is determined by two factors: the size of national income at a level close to the full employment of resources, and the nature of the tax system and its impact on the marginal efficiency of capital and the propensity to consume]10,p. 409 [.

3- Expenditure rule. It sets a limit on total spending or current spending in terms of absolute value, growth rates, or as a percentage of GDP, with a time that often ranges between (3-5) years]11,p.70 [, which can be used appropriately as an operational tool required to influence the reduction of The debt widening gap, especially when concurrent with the debt rule or budget balance rule, provides an operational tool for achieving fiscal discipline that is consistent with debt sustainability.

second topic: The concept and importance of economic growth and its relationship to financial sustainability.

First: The nature of economic growth:

Economic growth is considered one of the basic goals that governments pursue, and people aspire to, because it represents the material outcome of the economic and non-economic efforts exerted in society, as it is one of the necessary conditions for improving the standard of living of societies, and it is also considered an indicator of their prosperity, and economic growth is linked to A group of fundamental factors in society that constitute a suitable climate for its development, such as the provision of highly efficient institutions, good governance, community participation, and scientific research.

The concept of economic growth and its types:

1- The concept of economic growth

Due to the great importance that characterizes the subject of economic growth in economic analysis in the past and present, its concepts have become numerous and varied according to the diversity and difference of opinions of analysts and thinkers, and their different places and environments. On this basis, economic growth has several definitions that can be mentioned as follows: Economic growth is defined as An increase in the gross domestic product, or gross national income, to achieve an increase in the average per capita share of real income]12,p.7 [. Economic growth is also defined as an increase in the nation’s ability to produce goods and services. The greater the growth rate of the national economy than the growth rate. The population, the better, because it will lead to raising the standard of living of individuals]13,p.52 [.

Types of economic growth

Many criteria can be used to determine the types of economic growth, and they are constantly evolving due to the amount of support and intellectual interest from academics. We will limit ourselves to dividing the types of growth according to the criterion of the degree of intensity of growth and the criterion of the degree of planning.

A- Classification according to the degree of severity of growth: The types of growth can be classified according to this criterion into:

· Expanded economic growth: This growth is represented by the fact that income growth occurs at the same rate as population growth, meaning that per capita income is static.

· Zero growth: The emergence of zero growth is due to a study conducted by the Club of Rome under the supervision of Dennis Meadows, “which indicates that the rate of population growth is increasing exponentially in the supply of food, which is decreasing over time, and that industrial production will also decline as a result of the depletion of mineral resources in Under the ground and oil, famine will spread by the end of the next hundred years. In general, the zero growth rate expresses that rate that maintains environmental balance through developing the activities of sectors that preserve the environment. It is also required that the growth rate be subject to a constant and continuous increase]14,p.70 [.

B- Classification according to the degree of planning. According to this criterion, the types of economic growth can be divided into the following types]15,p.67 [:

· Natural growth is the growth that occurred historically with the transition from a feudal society to a capitalist society, in social historical paths that led through objective processes to the social division of labor and the first accumulation of capital with an increase in commodity production for exchange and the formation of the internal market so that every product has a market in which there is supply and in which to request;

· Transient or unstable growth is growth that does not have the characteristic of continuity. Rather, it is characterized by its emergence as a result of emergency conditions that are usually external, and the growth that it caused soon declines and disappears. This growth represents the case of developing countries.

· Planned growth: This is the growth that occurred as a result of comprehensive planning processes for society’s resources and requirements, but its strength and effectiveness are closely linked to the ability and interaction of citizens with those plans. It is self-propelled growth if it continues over a long period of more than a few decades and thus turns into economic development.

Second: The relationship between economic growth and financial sustainability

Financial sustainability and economic growth:

Financial sustainability affects economic performance in different ways and forms, as the sustainability of the government’s financial position has a real impact on capital costs on the one hand, and on the government’s ability to issue debt on the other hand, because the assumption restrictions are more severe with financial unsustainability, which can That leads to the emergence of the phenomenon of crowding out in the economy, and this leads to higher costs of capital (interest rates) in the country as a result of higher risk premiums by adding new costs around lending borne by both the government and the private sector, and thus is a serious deterioration in private investments and growth. Economics: Sergeant and Wallace explained in 1985 that weak financial sustainability means the government is unable to issue new bonds to finance spending, which will lead to expectations that government debt will be financed by new monetary issuance, which in turn leads to pessimistic expectations about a rise in... Current and future inflation rates, which require deflationary measures that also lead to weak growth in output and employment. On the one hand, on the other hand, individuals and establishments having a state of certainty or certainty about the government’s agreed programs help them in making investment decisions. For example, if individuals and establishments are certain of the type and direction of spending on the country’s central structures, this prompts them to design their future investment plans in a way that is compatible with this trend. This certainty can only be achieved through the continuation of the government’s spending programs without interruption. This matter can only happen with the possibility of sustainable government funding, which gives the government high flexibility in the face of financial shocks that may occur during the implementation of budget plans.

Third: Analysis of financial sustainability indicators for the structure of public debt and net budget for the period (2004-2022).

The first indicator: is the ratio of net budget to gross domestic product

It is noted from Table (1) that the surplus/GDP ratio index took an oscillating path between rise and fall in relative importance during the period (2005-2013). It recorded its highest percentage (27) in (2010), and its lowest percentage reached (2%). ) The year 2004 AD, which is the result of the lifting of economic sanctions on Iraq and the increase in production and export of oil, in addition to the increase in its prices during that period. As for the ratio of the deficit to (GDP), it is noted that it took an upward path during the period 2013 - 2022, as it moved from its lowest ratio in (2015) to the highest ratio (13) for the year (2020), which is a result of the reflection of the political conditions to which the country was exposed. Which led to an increase in expenditures over revenues, and in fact, the continued growth of consumption items in the budget at the expense of investment items that are relied upon to generate future revenues. It is noted that all budgets were planned with a deficit, but the reality indicates that most budgets were implemented with a surplus, which is clear evidence that budget planning is done far from practical reality, in addition to poor implementation, especially the low rates of implementation of investment spending due to lag in implementation and the inability of the implementing companies to implement properly. Sound technicians, their lack of experience, and the impact of administrative and financial corruption in referring works to reputable companies capable of actual completion. Also, the delay in referring works due to not approving the budget on time was an important reason for the projects not being implemented according to what was planned. Also, political differences, especially in the provincial councils, were Among the most important reasons for the delay in completion and failure to provide services are the services scheduled within the annual plans and budgets, which made the budget appear in a surplus and not a deficit. As for the deficit, its main reasons were the decline in global oil prices, the sharp rise in the operational agreement, cases of waste and financial corruption, the presence of a very high slackness in positions and institutions, the number of advisors, and high salaries and privileges. Large amounts of officials, high military and security spending, state institutions’ spending, and other cases of unjustified spending. In addition, there is a lack of diversification of revenues and a low percentage of economic sectors’ contribution to the GDP, especially in commodity sectors such as manufacturing and agriculture, which negatively affected the growth of the GDP and the ability of these sectors to generate income in a way that reduces the budget deficit. We conclude that for most of the years, especially from 2004 until 2012, the ratios were positive, meaning that the budgets were in surplus. As for the period from 2013 until the end of the study period, the ratios of deficit to GDP were increasing until they reached 2018 (10%). This deficit is considered large because it will generate The country's public debts, both internal and external.

Table No. (1) Net Budget to GDP Index for the Period (200-2022)
Years
GDP(billion dinars
1
growth rate
Net budget (billion dinars)2
net budget/GDP
3
2004
53235
0.38
865
0.01
2005
73533
0.29
14127
0.19
2006
95587
0.16
10248
0.1
2007
111455
0.4
15568
0.13
2008
157026
0.01
20848
0.13
2009
158643
0.02
2642
0.01
2010
162064
0.34
44022
0.27
2011
217327
0.16
30049
0.13
2012
254225
0.07
14677
0.05
2013
273027
0.01
5360
0.01
2014
276332
0
6805
0.02
2015
276332
0.01
3947
0.01
2016
280924
0.006
12658
0.04
2017
282722
0.11
1845
0.006
2018
284100
0.09
25696
0.09
2019
286157
0.02
25875
0.09
2020
187169
0.61
24568
0.13
2021
301439
0.27
26753
0.08
2022
383064
-1
20668
0.05
Source: Column (1,2) based on Central Bank data for the years (2004-2022) Column (3) is the work of the researcher.

second indicator: is the ratio of internal public debt to gross domestic product

According to the point of view of two international institutions, the International Monetary Fund, and the International Debt Relief Association, the International Monetary Fund confirms that the ratio of debt to GDP ranges between 25% to 30, while the International Debt Relief Association confirms that the ratio ranges between 20 and 25%. We note from Table (2) that the percentage was high in 2004, that is, 11, although the percentage was acceptable according to the indicators of the International Monetary Fund and the International Debt Relief Association, this percentage decreased through the government’s work to re-export oil after years of economic sanctions. Which was imposed by the United Nations, as well as the arrival of oil prices to high prices that oil markets had not witnessed before. All of these factors made the debt-to-GDP ratio low from 2005 until 2015, where the percentages ranged from 9% to 12% during that period, The ratios are consistent with the standards of the International Monetary Fund and the International Debt Relief Association. After this period, the Iraqi economy was exposed to double problems (the entry of terrorist gangs into some governorates and the decline in oil prices. These problems made the country borrow from inside and outside to finance military operations in addition to providing employee salaries that require large sums through administrative laxity in most of the Ministry of State, so the relationship became... There was an inverse relationship between the public debt and the gross domestic product during that period, as the public debt increased with the decrease in the gross domestic product, which made the percentage increase. After it was 12 in 2015, it became 24 in 2016, and after the situation stabilized and the governorates were liberated from the crimes of terrorist gangs, the percentage began to gradually decrease, reaching % 21 in 2017, and at the end of the study period it amounted to 17%. Despite the lack of consensus among the various international organizations regarding setting the minimum levels for these indicators, the minimum levels proposed by developing countries are shown and they are issued by two different international organizations, the International Mitigation Organization and the Monetary Fund. The International Organization, where the latter suggested that the ratio of debt to GDP is 25% to 30%, while the International Organization for Mitigation has specified between 20 to 25%. From this, we conclude that the ratio of debt to GDP was acceptable ratios during the first years of the study period, that is, from 2004 to 2015, That is, achieving financial sustainability during those years and achieving the debt-to-GDP ratio index. However, in recent years it reached dangerous stages during the years 2020 and 2022, where it reached 34 and 23%, respectively, due to political circumstances and as a result of COVID-19, which led to a decline in oil prices, that, no Achieving the financial sustainability index during the last period of the study Failure to meet the standards of the International Monetary Fund and the International Debt Relief Association.

Table No. (2) Public debt to GDP ratio index for the period (2004-2022)
Years
Total public debt
(billion dinars)
1
GDP
(billion dinars)
2
Public debt/GDP
3
2004
6061
53235
0.11
2005
6593
73533
0.08
2006
5645
95587
0.05
2007
5193
111455
0.04
2008
4455
157026
0.02
2009
8434
158643
0.05
2010
9180
162064
0.05
2011
7446
217327
0.03
2012
6547
254225
0.02
2013
4255
273027
0.015
2014
9520
276332
0.03
2015
32142
276332
0.11
2016
47362
280924
0.16
2017
47678
282722
0.16
2018
41822
284100
0.14
2019
38331
286157
0.13
2020
64246
187169
0.34
2021
69912
301439
0.23
2022
69060
383064
0.18
Source:
• Column (1,2) based on Central Bank data for the years (2004-2022)
• Column (3) is the work of the researcher

third section: measuring and analyzing the impact of financial sustainability indicators on economic growth in Iraq for the period (2004-2022).

To expand the sample of research observations, the time series was divided into quarterly after it was annual, and for the econometric analysis to come out in conformity with reality and economic logic and by economic assumptions for analyzing methodologies and relationships between variables, the autoregressive lag gap (ARDL) model was used and to identify the terms of long and short-term relationships between The independent variables and their impact on the dependent variable, where Y represents the growth rate and x1 represents the net budget over GDP x2 represents public debt over GDP. The observations have been included in the following table:

Table (3) Growth rate, net budget, and public debt for the period (2004-2022)

X2
X1
Y
years
0.11
0.01
0.38
2004
0.08
0.19
0.29
2005
0.05
0.1
0.16
2006
0.04
0.13
0.4
2007
0.02
0.13
0.01
2008
0.05
0.01
0.02
2009
0.05
0.27
0.34
2010
0.03
0.13
0.16
2011
0.02
0.05
0.07
2012
0.015
0.01
0.01
2013
0.03
0.02
0
2014
0.11
0.01
0.01
2015
0.16
0.04
0.006
2016
0.16
0.006
0.11
2017
0.14
0.09
0.09
2018
0.13
0.09
0.02
2019
0.34
0.13
0.61
2020
0.23
0.08
0.27
2021
0.18
0.05
-1
2022
Source: Based on Central Bank data for the years (2004-2022)

Data dormancy:

The extended Dickey-Feller and Phillips-Perron tests were used, which showed that there is a mixture of stability for the estimated model if The same is true of direction, constant, and bodies. As for the expanded Dickey-Feller test, it indicated that all variables did not stabilize at the level, but rather stabilized at the first difference, meaning that there is a state of uncertainty about the stability of the variables, but rather it is a mixture of stability, some of which stabilized at the appropriate level and some of which stabilized at the first hypothesis, and this qualifies us to use the methodology. Autoregressive lag gaps (ARDL), through which we can estimate the slowdowns appropriate to the nature of our data and model. The stability results are listed according to the following table:

Table (4) stability results.

Y
X1
X2
With Constant
t-Statistic
-0.1419
-3.7042
-1.5248
Prob.
0.9402
0.0059
0.5157
n0
***
n0
With Constant & Trend
t-Statistic
-0.1322
-3.9932
-2.5726
Prob.
0.9934
0.013
0.2938
n0
**
n0
Without Constant & Trend
t-Statistic
0.4305
-2.1598
-0.824
Prob.
0.8043
0.0305
0.3557
n0
**
n0
At First Difference
d(Y)
d(X1)
d(X2)
With Constant
t-Statistic
-3.8659
-5.4462
-4.9123
Prob.
0.0036
0
0.0001
***
***
***
With Constant & Trend
t-Statistic
-4.2333
-5.3957
-4.8978
Prob.
0.0065
0.0001
0.0008
***
***
***
Without Constant & Trend
t-Statistic
-3.823
-5.495
-4.9431
Prob.
0.0002
0
0
***
***
***
UNIT ROOT TEST TABLE (ADF)
At Level
Y
X1
X2
With Constant
t-Statistic
1.2045
-2.1296
-0.1493
Prob.
0.9979
0.234
0.9389
n0
n0
n0
With Constant & Trend
t-Statistic
2.4393
-2.2092
-1.8941
Prob.
1
0.4765
0.6464
n0
n0
n0
Without Constant & Trend
t-Statistic
1.6248
-1.3841
0.7361
Prob.
0.9736
0.1531
0.8712
n0
n0
n0
At First Difference
d(Y)
d(X1)
d(X2)
With Constant
t-Statistic
-0.0873
-3.2774
-2.9559
Prob.
0.946
0.02
0.0445
n0
**
**
With Constant & Trend
t-Statistic
-1.1736
-3.2547
-6.5927
Prob.
0.9075
0.083
0
n0
*
***
Without Constant & Trend
t-Statistic
0.0717
-3.2924
-2.7639
Prob.
0.7021
0.0013
0.0064
n0
***
***
Notes: (*)Significant at the 10%; (**)Significant at the 5%; (***) Significant at the 1%. and (no) Not Significant *MacKinnon (1996) one-sided p-values
Source: Outputs of the statistical program Eviews 12.0

Standard analysis methodology

The autoregressive distributed lag model (ARDL) was followed based on the results of the stability of the data that were explained above. To know the trends of the relationship, whether it is a long-term or short-term relationship, the aforementioned methodology was used, and the methodology resulted in slowdowns appropriate to the nature of the research, which are as follows, which are two slowdowns for the variable Y and two slowdowns for the variable X1 and Four decelerations of the variable X2. It is known that this methodology is based on selecting appropriate slowdowns according to the Akaike infronastio criterion (AIC) criterion, which represents the lowest value and is done by comparing 20 proposed models of the results that we will explain later. The results were satisfactory from a statistical and measurement standpoint, as R2 reached more than 96%. The corrected coefficient of the determination reached 96%, as was the case with the calculated F, as it was significant at the 1% level, as well as the Darbin-Watson value, which indicates that it falls within the region of non-correlation between the random residuals, as follows:

Table 5: Autonomous slowdown methodology for distributed gaps (ARDL).

Dependent Variable: Y


Method: ARDL



Date: 09/16/23 Time: 00:01


Sample (adjusted): 2005Q1 2022Q4

Included observations: 72 after adjustments

Maximum dependent lags: 4 (Automatic selection)
Model selection method: Akaike info criterion (AIC)
Dynamic regressors (4 lags, automatic): X1 X2
Fixed regressors: C


Number of models evaluated: 100

Selected Model: ARDL(2, 2, 4)












Variable
Coefficient
Std. Error
t-Statistic
Prob.*










Y(-1)
1.787887
0.096903
18.45032
0.0000
Y(-2)
-0.729035
0.131168
-5.558028
0.0000
X1
0.731183
0.217384
3.363551
0.0013
X1(-1)
-1.515769
0.344194
-4.403822
0.0000
X1(-2)
0.653194
0.240873
2.711784
0.0087
X2
3.567397
0.342080
10.42855
0.0000
X2(-1)
-6.269638
0.670371
-9.352496
0.0000
X2(-2)
2.540852
0.744032
3.414979
0.0011
X2(-3)
-0.152306
0.569146
-0.267605
0.7899
X2(-4)
0.481647
0.349375
1.378598
0.1731
C
-0.007453
0.013776
-0.540983
0.5905










R-squared
0.968224
Mean dependent var
0.198667
Adjusted R-squared
0.963015
S.D. dependent var
0.272718
S.E. of regression
0.052448
Akaike info criterion
-2.918225
Sum squared resid
0.167798
Schwarz criterion
-2.570401
Log-likelihood
116.0561
Hannan-Quinn criteria.
-2.779756
F-statistic
185.8679
Durbin-Watson stat
2.252969
Prob(F-statistic)
0.000000













*Note: p-values and any subsequent tests do not account for the model
selection.


Source: Outputs of the statistical program Eviews 12.0

F-Bounds Test

Its values reached 2.20. It is clear from the table below, which shows the F-Bounds Test, that the calculated F value was 2.20, which is of course less than all statistical levels (1%, 2.5%, 5%, 10%), and this indicates that there is no long-term equilibrium relationship. Between the studied variables, there may be a short-term balanced relationship according to the studied sample: N=75 and N=70 observations.

Table (6) Bounds Tes

F-Bounds Test
Null Hypothesis: No levels of relationship










Test Statistic
Value
Signif.
I(0)
I(1)













Asymptotic: n=1000

F-statistic
2.207713
10%
2.63
3.35
K
2
5%
3.1
3.87


2.5%
3.55
4.38


1%
4.13
5





Actual Sample Size
72

Finite Sample: n=75



10%
2.725
3.455


5%
3.253
4.065


1%
4.458
5.41








Finite Sample: n=70



10%
2.73
3.445


5%
3.243
4.043


1%
4.398
5.463










Source: Outputs of the statistical program Eviews 12.0

The following table shows the significance of the error correction equation parameter, and its significance reached 0.0034. The Durbin-Watson stat value was 2.252969, the R-squared value was 0.81, the Adjusted R-squared value was 79%, and the Akaike info criterion was 79%.

-3.001559) (And this is the lowest possible value

table(7 ) error correction

ARDL Error Correction Regression

Dependent Variable: D(Y)


Selected Model: ARDL(2, 2, 4)


Case 2: Restricted Constant and No Trend

Date: 09/16/23 Time: 00:06


Sample: 2004Q1 2022Q4


Included observations: 72












ECM Regression
Case 2: Restricted Constant and No Trend










Variable
Coefficient
Std. Error
t-Statistic
Prob.










D(Y(-1))
0.729035
0.100941
7.222406
0.0000
D(X1)
0.731183
0.194953
3.750568
0.0004
D(X1(-1))
-0.653194
0.206402
-3.164673
0.0024
D(X2)
3.567397
0.322677
11.05561
0.0000
D(X2(-1))
-2.870193
0.457940
-6.267618
0.0000
D(X2(-2))
-0.329341
0.352397
-0.934575
0.3537
D(X2(-3))
-0.481647
0.338876
-1.421307
0.1603
CointEq(-1)*
0.058851
0.019334
3.043872
0.0034










R-squared
0.817244
Mean dependent var
0.016046
Adjusted R-squared
0.797255
S.D. dependent var
0.113718
S.E. of regression
0.051204
Akaike info criterion
-3.001559
Sum squared resid
0.167798
Schwarz criterion
-2.748596
Log likelihood
116.0561
Hannan-Quinn criteria.
-2.900853
Durbin-Watson stat
2.252969













* p-value incompatible with t-bounds distribution.










F-Bounds Test
Null Hypothesis: No levels of relationship










Test Statistic
Value
Signif.
I(0)
I(1)










F-statistic
2.207713
10%
2.63
3.35
K
2
5%
3.1
3.87


2.5%
3.55
4.38


1%
4.13
5















Source: Outputs of the statistical program Eviews 12.0

Lakrang test

According to the test results, which showed that the model does not suffer from an autocorrelation problem between the random variables, according to this test, the result of Prob for F (2,59) was 0.2432, which was not significant, and we must accept the null hypothesis, which states that there is no serial correlation between the random residuals, and this also supports our statement. The Chi-Square probability, which is greater than the 5% level, is an indication that there is no serial correlation between the random variables, as in the following table.

Table( 8) LM test

ARDL Error Correction Regression

Dependent Variable: D(Y)


Selected Model: ARDL(2, 2, 4)


Case 2: Restricted Constant and No Trend

Date: 09/16/23 Time: 00:06


Sample: 2004Q1 2022Q4


Included observations: 72












ECM Regression
Case 2: Restricted Constant and No Trend










Variable
Coefficient
Std. Error
t-Statistic
Prob.










D(Y(-1))
0.729035
0.100941
7.222406
0.0000
D(X1)
0.731183
0.194953
3.750568
0.0004
D(X1(-1))
-0.653194
0.206402
-3.164673
0.0024
D(X2)
3.567397
0.322677
11.05561
0.0000
D(X2(-1))
-2.870193
0.457940
-6.267618
0.0000
D(X2(-2))
-0.329341
0.352397
-0.934575
0.3537
D(X2(-3))
-0.481647
0.338876
-1.421307
0.1603
CointEq(-1)*
0.058851
0.019334
3.043872
0.0034










R-squared
0.817244
Mean dependent var
0.016046
Adjusted R-squared
0.797255
S.D. dependent var
0.113718
S.E. of regression
0.051204
Akaike info criterion
-3.001559
Sum squared resid
0.167798
Schwarz criterion
-2.748596
Log-likelihood
116.0561
Hannan-Quinn criteria.
-2.900853
Durbin-Watson stat
2.252969













* p-value incompatible with t-bounds distribution.










F-Bounds Test
Null Hypothesis: No levels of relationship










Test Statistic
Value
Signif.
I(0)
I(1)










F-statistic
2.207713
10%
2.63
3.35
K
2
5%
3.1
3.87


2.5%
3.55
4.38


1%
4.13
5















Source: Outputs of the statistical program Eviews 12.0

Test for homoscedasticity of variance

It is clear from the results of the standard analysis listed below that the estimated model has passed the problem of non-stationarity of heteroscedasticity, as well as according to the probability of the calculated F and Chi-Square, which exceeded the 5% level of significance. This is a clear indication that the model does not suffer from the problem of non-stationarity of heteroscedasticity, but rather It is in a state of constant homoskedasticity, as in the following states:

Table (9) Homoscedasticity test

Heteroskedasticity Test: Breusch-Pagan-Godfrey
Null hypothesis: Homoskedasticity











F-statistic
0.659144
Prob. F(10,61)
0.7571
Obs*R-squared
7.021356
Prob. Chi-Square(10)
0.7234
Scaled explained SS
14.05493
Prob. Chi-Square(10)
0.1705















Test Equation:



Dependent Variable: RESID^2


Method: Least Squares


Date: 09/16/23 Time: 00:10


Sample: 2005Q1 2022Q4


Included observations: 72












Variable
Coefficient
Std. Error
t-Statistic
Prob.










C
0.001933
0.001492
1.295348
0.2001
Y(-1)
-0.010215
0.010496
-0.973228
0.3343
Y(-2)
0.022372
0.014207
1.574732
0.1205
X1
0.020816
0.023545
0.884104
0.3801
X1(-1)
-0.021103
0.037280
-0.566071
0.5734
X1(-2)
-0.009569
0.026089
-0.366787
0.7150
X2
-0.014056
0.037051
-0.379382
0.7057
X2(-1)
0.075394
0.072608
1.038377
0.3032
X2(-2)
-0.083400
0.080586
-1.034923
0.3048
X2(-3)
0.002809
0.061644
0.045574
0.9638
X2(-4)
0.011918
0.037841
0.314943
0.7539










R-squared
0.097519
Mean dependent var
0.002331
Adjusted R-squared
-0.050429
S.D. dependent var
0.005543
S.E. of regression
0.005681
Akaike info criterion
-7.363742
Sum squared resid
0.001968
Schwarz criterion
-7.015918
Log-likelihood
276.0947
Hannan-Quinn criteria.
-7.225273
F-statistic
0.659144
Durbin-Watson stat
1.578609
Prob(F-statistic)
0.757137













Source: Outputs of the statistical program Eviews 12.0

Testing the cumulative sum and its squares at a 5% significance level.

The chart below shows that the path of the phenomenon did not go beyond the critical limits over the time studied. This is a good indicator on the one hand that supports what the standard tests have reached, and on the other hand, it gives us a simplified idea of the possibility that no structural changes are affecting the Iraqi economy, given that the path of the phenomenon fluctuates around The average is as shown in the following chart:

Conclusions

1- The levels of stability or stationarity varied between the level and the first difference. Two unit root tests were used, which are both the expanded Dickey-Feller test and the Phillips-Ferm test for non-parametric tests. Naturally, some variables stabilized at the constant, some at the constant and the trend, and others with the constant and the trend, and sometimes without the constant and the trend.

2- Through the model estimated using the autocorrected deceleration methodology for distributed regression (ARDL), the appropriate slowdowns for the model variables were estimated according to the reality of the Iraqi economy, which is (2,2,4). The coefficient of determination and the corrected coefficient of determination reached the significance of the model as a whole according to the test, and the calculated F reached

3- Post-tests proved that the model does not suffer from the problem of serial correlation between random residuals and the problem of non-stationary homoscedasticity. Rather, the results proved the opposite, that the model does not suffer from the problem of serial correlation. According to the Lackering test, as well as according to the Heteroscedasticity test, it was proven that the model does not suffer from the problem of non-stationary homoscedasticity. Variation. On the contrary, homogeneity and variance stability is the most general phenomenon of the model. It can be said that the model is Homoskedasticity. Its results have been included in the standard analysis tables and post-tests listed above.

4- There is an inverse relationship between tax revenue growth rates and the total public debt to gross product index.

5- Economic stability represents the necessary condition for growth.

Recommendations:

1- The necessity of working to raise the efficiency of the tax system and working to reduce the rate of tax evasion through accurate data and statistics to increase public revenues.

2- Choosing the appropriate general budget type and not adopting budget items in Iraq’s current circumstances on the basis that the general budget is a financial plan drawn up to achieve economic goals with the greatest possible satisfaction of society.

3- Improving the efficiency of public spending to achieve optimal exploitation of available resources.

4- Proposing the existence of a financial allocation fund, such as a fund to support the financial balance of the general budget, and to maintain financial stability permanently.

5- Relying on new financing tools, such as sukuk, to attract new segments of investors who are looking for financial instruments that are compatible with the country’s policy.


Источники:

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