A Financial Stability Model for Iraqi Companies

Abstract

The current study aims to develop a financial stability model in Iraq; after reviewing the relevant literature and sources related to financial stability and considering Iraq’s social, economic, political, and cultural conditions, a conceptual model and a research questionnaire have been developed. Based on the developed conceptual model, macro variables at the level of the economy, micro variables at the level of companies, the environmental variables of companies, and corporate governance have been selected as model dimensions. Each dimension has several components, including several indicators; 39 indicators were measured through questions in 2024. The research questionnaire was subjected to the opinion of 21 experts with sufficient experimental and academic records on this subject, and by using the Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods, the results were analyzed, and the final model was extracted. In this model, the scientific method used to analyze the results determines the weight of each dimension, component, and indicator. The results of this research show that the dimensions of corporate governance, the variables of the company environment, micro variables at the company level, and macro variables at the economic level with coefficients of 0.345, 0.251, 0.236, and 0.168, respectively, have the most significant impact on the ranking of the company’s financial stability. So far, research has yet to be conducted to present the financial stability model of Iraqi companies. Therefore, the present research is one of the first studies in this respect, which presents a model both qualitatively (by designing a questionnaire and conceptual model) and quantitatively (through a mathematical model) to measure financial stability that can help the development of science and knowledge in this field.

1. Introduction

Unlike price stability, defining or measuring financial stability is not a simple and easy task due to the interdependence and complex interactions of the various financial system elements of companies with each other and the economy, which is more complicated due to the time and cross-border dimensions of such interactions (Kukushina et al. 2021). Financial stability is when the financial system resists economic shocks and can perform its financial tasks correctly (Taranova et al. 2021). The need for financial stability analysis was first recognized since the establishment of stock markets suggesting organized training in the 17th century; after that, by the industrial revolution in the 19th century, credit rating agencies emerged to evaluate the financial stability of organizations to provide a basis for the investors in decision-making processes (Antonov 2022). More recently, in the 20th century, as a result of the massive development of financial markets, metrics such as earnings per share (EPS) and price-to-earnings (P/E) ratios were formulated to assess the financial stability of corporates (Goswami et al. 2014). In addition to the general need for an assessment of the financial stability of companies, the financial crises positioned in the late 1990s, after financial liberalization, have highlighted the importance of financial stability, and its importance was strengthened by the occurrence of financial and economic crises in 2007–2008 (Yusgiantoro et al. 2019). Before the crisis, corporate indebtedness had reached unprecedented levels, forcing companies to repay their loans and putting further pressure on their financial stability. High leverage levels increased firms’ sensitivities to economic shocks and credit tightening during the crisis (Mayasari and Wulandari 2022). During the crisis, as was evident in the volatility of equity markets worldwide, the systemic nature of risks threatened corporate financial stability. Also, declining commodity prices and the fading of the commodity boom cycle had adverse effects on foreign direct investment in natural resources and changed the fate of businesses operating in the mining and energy sectors. Therefore, the economic slowdown and recession that the crisis triggered reduced the attractiveness of stock markets as an investment destination, reduced foreign investment flows, and reduced companies’ growth prospects (Fingleton et al. 2008). High corporate indebtedness, contagious financial markets, unfavorable economic conditions, and regulatory changes finally caused the financial crisis of 2007–2008, which profoundly impacted companies’ financial stability worldwide. Therefore, financial stability is essential for economic prosperity at the firm and macro levels.

Indebtedness and debt management are critical for improving financial stability in corporate entities, municipalities, and national economies. The following are the major points provided by the existing literature: (1) Efficient public debt management minimizes the vulnerability of an economy to financial shocks and supports a stable financial environment. For example, in Poland, it follows that effective public debt management reduces financial threats and enhances the stability of economics (Misztal 2021). (2) Public debt management is crucial for the broad economic stability of any country. It touches on public finances, monetary turnover, the investment climate, and international cooperation. For example, in Kazakhstan, the improvement in the system of public debt management plays a significant role in increasing financial stability, especially with regard to economic transformation and growing economic risks (Mataibayeva et al. 2019). (3) In the corporate sector, financial stability is conditioned by the balance between companies’ own resources and external debts. Companies with a higher share of their own resources tend to be more stable. Also, excessive reliance on external debt can seriously threaten the firm’s financial health if the economy becomes hostile (Chiladze 2018). Therefore, efficient debt management uses long-term debt financing tools to increase the return on equity and improve overall financial stability.

During the last two decades, researchers of central banks and entities have tried to depict financial stability conditions through various indicators of financial system vulnerabilities (Nadri et al. 2018). Several central banks try to assess financial stability risks by focusing on a few critical indicators through Financial Stability Reports (FSR) (Kalsie et al. 2020). In addition, there are ongoing efforts to develop a unit-wide measure indicating business fragility or financial stress (Akosah et al. 2018). The composite quantitative measures of financial stability are intuitively appealing for their ability to, first, present policymakers and participants with a system of more effective monitoring of the level of stability within the system; second, to foresee the sources and causes of financial stress; and third, to understand their implications better. The methodology for constructing these measures has been changing over the years, shifting the focus from micro-prudential to macro-prudential aspects of financial stability. It shifted focus from looking into the early warning indicators to assessing the condition of the banking system, specifically the default risk of individual institutions, to a comprehensive assessment of risks across financial markets, institutions, and infrastructure of the whole system. Recently, increasing analytical focus has been placed on behavioral dynamics, the eventual emergence of unstable conditions, and the shock transmission mechanisms (Stona et al. 2018). In examining financial stability and providing the necessary model to measure it, we must also analyze the banking and financial systems of the companies listed on the Iraqi Stock Exchange. Therefore, in this research, in addition to the listed companies on the Iraqi Stock Exchange, we also consider banks listed on the Iraqi Stock Exchange. The factors affecting financial instability are diverse and can differ according to the period and the countries included in the analysis.

One of the critical issues underlying these analytical developments is the need to fill data gaps in several fields, such as the financial departments of companies listed on the Iraqi Stock Exchange. The current research can help to review the work carried out in the direction of developing quantitative financial stability criteria, presenting the financial stability model for Iraqi companies in both qualitative and quantitative ways: qualitative through a questionnaire and quantitative through a mathematical model used in the published financial reports of business units. Therefore, in this research, we seek to present a model of financial stability in Iraqi companies. The reason for choosing Iraq is because this country has faced several crises in recent years, including the US military attack, the occupation of this country by the ISIS terrorist group, internal riots in the country, and finally, the global crisis of COVID-19. It is known that each of these crises has dramatically impacted the economy and financial performance of businesses and the financial system of Iraq (Abdullah 2018). Also, by reviewing the subject literature, it has been determined that, so far, most of the studies carried out in the field of financial stability have often identified factors affecting financial stability and ranked various factors affecting it. So far, no research has provided a model for stability. Therefore, the current study, considering the importance of financial stability for the financial systems of banks and business units of countries, seeks to investigate this issue in the developing and crisis-stricken country of Iraq to eliminate the research gap in this field. It will also help the development of science and knowledge in this field.

2. Theoretical Principles

Financial stability is a feature of a financial system that eliminates financial imbalances that arise endogenously in financial markets or result from significant adverse and unpredictable events (Icaza 2017). When the system is stable, it absorbs economic shocks, mainly through self-correcting mechanisms, and prevents adverse events from disrupting the real economy or contaminating other financial systems (Elsayed et al. 2023). Financial stability is crucial for economic growth, as most transactions in the real economy are conducted through the financial system (Hadian and Dargahi 2018).

Without financial stability, businesses and banks will be reluctant to finance profitable projects, the price of assets may deviate significantly from their intrinsic values, and the payments settlement program may be derailed (Habib et al. 2020). Therefore, financial stability is essential to maintain the confidence of businesses and financial institutions (Dai and Zhou 2022). The potential consequences of excessive volatility can include financial crises, bankruptcies of business units and banks, severe inflation, and stock market crashes (Akins et al. 2016). In other words, financial stability is the goal of central bank policy for price stability and the healthy development of countries’ economies and business units (Mamipour and Godarzi 2020). Because financial instability imposes high costs on the economy and businesses, as the volatility of price variables in financial markets increases, financial institutions or companies may go bankrupt (Enaiati et al. 2022).

Moreover, economic development can be limited at such a time, as economic agents need help making rational decisions and the efficiency of resource allocation decreases. Since the 1980s, several countries have achieved the positive effects of the rapid growth of the financial industry due to the progress of financial liberalization (Dai and Zhou 2022). At the same time, they have also experienced a dramatic slowdown in economic growth due to heavy economic costs caused by financial instability or financial crises (Martinez-Miera and Repullo 2020). In the face of this, countries have greatly emphasized this issue when implementing their policies. Attention to financial stability among all countries is currently increasing, as new factors with the potential to create financial instability, including strengthening financial sector linkages between companies and the uncontrolled development of complex financial instruments, have emerged that make it difficult for businesses to help financial institutions have financial stability against crises (Xie et al. 2022). Therefore, given the importance of financial stability for the economy and the financial system of businesses and banks, it is necessary to provide a model that can correctly depict the various factors affecting financial stability. Especially in Iraq, due to the crises it has gone through in recent years, such a model can be used to assess the financial stability of the financial system of its banks while measuring the financial stability of the listed companies on the Iraqi Stock Exchange.

2.1. Financial Stability

Over the past decade, financial stability has become one of the important goals of economic policy. Many central banks and financial authorities, such as the International Monetary Fund, the World Bank, and the Bank for International Settlements, publish periodic financial stability reports to embed analysis and the pursuit of financial stability into their mainstream activities. Financial stability goes way beyond the absence of crises. A stable financial system is one that, through the conduct of other processes and financial and economic functions such as savings and investments, lending and borrowing, and liquidity creation and distribution, among others, effectively conducts the geographical and temporal allocation of economic resources, evaluating, pricing, and allocating financial risks. It must also manage the risks and have the ability to maintain the performance of those key functions despite adverse external shocks or imbalances.

The system is composed of infrastructures such as legal, payment, settlement, and accounting systems; institutions such as banks, security firms, and institutional investors; and markets for stock, bonds, money, and derivatives. In case of trouble with one component, there is a potential to affect the whole stability of the system itself (Barra and Zotti 2019). However, given that the system is strong enough to hold on to its core functionalities, problems in one component of the system might not necessarily threaten overall stability (Dai and Zhou 2022). The need for financial stability does not pre-assume that all areas within the financial system need to work optimally all the time. It allows for the self-correction of mechanisms to reduce and eliminate these imbalances before they grow to become full-blown crises, such that the national currency performs its roles as a medium of exchange, unit of account, and store of value functions. This, therefore, means that financial and monetary stability are interconnected. According to Barra and Ruggiero (2021), overall, a financial system would be termed stable if disturbances and crises are improbable to hurt economic activity. Increased competition or the assimilation of new information may lead to the closure of a financial institution, growing volatility, or significant market corrections, which indicate good health in the financial system (Bazzazan 2020).

Because the financial system is continuously changing, the concept of financial stability does not pertain to any one stable state or trajectory that the system would revert to post-shock; rather, it alludes to a spectrum or continuum. This multidimensional continuum reveals itself in different observable and measurable variables that are of help in providing for the quantification of the effectuality of a financial system in fulfilling its facilitative roles (Xie et al. 2022). Financial stability is a broad concept and difficult to reduce to be measured by a single metric. The contagion effects and non-linear interactions among the different segments of the financial system cause problems in predicting financial crises. Therefore, a systemic and comprehensive perspective on the stability of the financial system is needed (Ayam 2021).

At the same time, crisis prevention has to be based on a realistic understanding of the degree to which developments in financial stability can be controlled. Many of the policy instruments available for ensuring financial stability pursue other primary objectives, like the protection of depositors in their dealings with banks (prudential policies), price stability (monetary policy), or the efficient settlement of payment transactions (payment policies). The impact of such policy tools on financial stability is most often indirect and occurs after some lag, which may be in contravention of the original purpose of using those tools (Zargarkoche and SoroushRad 2019). Although financial stability is advisable to be identified and quantitatively assessed, in this paper, an approach toward the identification of the most important dimensions and indicators that are relevant for the effect on financial stability is pursued so that this variable can be calculated and forecasted accurately.

2.2. Financial Stability Dimensions and Indicators

Financial stability is multidimensional, so it takes work to measure. Financial stability is measured and evaluated based on the performance of financial markets, institutions, and infrastructures and the interaction between the financial sector and the macroeconomic environment. Therefore, financial stability cannot be analyzed as a single variable or a financial indicator per business, such as macro-level liquidity ratios, with an indicator such as the inflation rate (Dai and Zhou 2022).

Financial market stability refers to the ability of financial markets to absorb a shock and not destabilize their fundamental functions with regard to price discovery and liquidity. Financial market stability is a situation in which companies listed in the financial markets can meet obligations without foreign interference or aid, prices do not change in the short term, and there is a change in fundamental indicators (Ghassan and Krichene 2017). This stability should alleviate the systemic risks to preclude broad contagion or market failure, especially during serious market constraints (Baur and Schulze 2009). Markets in developed countries show more stable characteristics compared to their counterparts in emerging markets, where the impact of systematic shocks can be very high during periods of crisis (Chirilă and Chirilă 2015). Shi et al. (2011) believe that to achieve financial market stability, a sound regulatory framework must be implemented, which compels finance institutions to carry out their business transparently and accountably with the proper practice of risk management. Moreover, monitoring crises can enforce capital adequacy so that the listed institutions might be more resilient under economic shocks. Using advanced analytics, market practitioners can continuously monitor market activities, which is necessary for the early detection of potential risks to prevent systemic risks (Chen et al. 2013). Interventionist monetary and fiscal policies by governments and central banks during times of crisis—for example, the adoption of quantitative easing or the provision of liquidity support—can help stabilize the financial markets. Policymakers may also help stabilize financial markets by proposing clear crisis management protocols so that markets can respond well during sudden shocks. This includes designing contingency plans and emergency liquidity provisions. Therefore, financial market stability is a prerequisite for successful economic development. Financial markets can be stabilized by comprehensive regulatory measures, improved market surveillance, and investor education to ensure sustained economic growth.

In terms of company financial stability, several studies have been conducted, and some indicators of financial stability have been provided. For companies, financial stability refers to the ability to maintain the overall balance in a company’s financial structure and to fulfill all financial obligations uninterruptedly over time, whether affected by economic difficulties or market fluctuations. It indicates a company’s ability to generate sufficient cash, keep adequate liquidity, manage debt effectively, and ensure profitability and growth. In particular, an optimally balanced capital structure, including internal resources with outside debt, may allow a firm to conduct business efficiently without having too great of a financial burden. Therefore, debt management and efficient capital structure are among the paramount factors determining the financial stability of corporates (Chiladze 2018). Liquidity and profitability, referring to a company’s ability to meet short-term obligations and have consistent profitability, are other factors increasing the financial stability of corporates through generating continuous positive cash flows. Other financial stability perspectives address financial risks and market uncertainties by implementing risk management approaches and enhancing adaptability to modify the changing economic conditions (Oleynik and Borisova 2019).

Existing literature also explores some aspects of the financial stability of companies. For example, Allen and Wood (2006) have taken asset price volatility as a measure of financial stability. Financial stability avoids disruptions in the financial system that are likely to cause significant production costs, financial problems in institutions, or disruptions in capital markets. They also defined financial stability as the stability of the value of money, the stability of prices, the favorable level of employment, trust in monetary and financial institutions, and the absence of fluctuations in the liquidity and profitability of companies. Virolainen (2004) introduced macro-level indicators such as interest rates, GDP growth, and credit expansion as companies’ financial stability indicators.

However, at the micro level, financial stability criteria are mainly based on liquidity risk, financial solvency, systematic and non-systematic risk, and the Altman Z criterion for predicting financial crises. The review of research (e.g., Beck et al. 2014; Virolainen 2004; Ghassan and Krichene 2017) shows that in the research of Beck et al. (2014), the return on equity basis is used as an indicator of financial stability.

Also, for the purpose of conducting an objective analysis of the value and structure of the company’s assets and liabilities and determining the degree of financial stability and independence, comparing the objectives of financial and economic activities with the regulations of the company, the debt and interest coverage ratios are used as criteria. The financial security and trust of the company are leveraged in external financing (Dai and Zhou 2022).

On the other hand, the literature review also suggests that fundamental accounting variables, financial ratios, or a combination of them are generally considered factors affecting financial stability (Pinčák and Bartoš 2015).

Blank (2013) used indicators such as liquidity ratios and debt repayment, such as the current ratio and debt repayment period, to assess financial stability. Thus, if liquidity indicators are greater than normative values, it can be a sign of the improper use of available financial resources. Therefore, indicators of business activity such as asset turnover, inventory, claims receipt period, and working capital can be used to assess financial stability. Because these ratios indicate the management of assets in production and sales and the employment of working and total capital, it is essential in strengthening companies’ liquidity.

Table 1. Indicators employed for financial instability.

Authors	The Index Used for Financial Instability
Altman (1968)	Altman’s Z-score index is a measure to predict the probability of financial instability or helplessness based on financial ratios, including working capital to assets, residual profit to assets, profit before interest and tax to assets, the market value of stocks, and sales to assets.
Ohlson (1980)	Score index 9-factor linear combination of coefficients to evaluate the business probability of failure or financial instability. In this regard, the exponential power of this score is divided by 1 plus this exponential power. In this index, the forecasting factors are the sum of assets, the price index in national income, the sum of liabilities, working capital, current liabilities, and current assets; if the sum of liabilities is greater than the sum of assets, it takes 1; otherwise, 0. Net profit, operating cash flows; if the company has made losses in the last 2 years, it takes 1; otherwise, 0.
Zmijewski (1984)	It uses a model based on net profit to assets, total liabilities to assets, and current assets to current liabilities to predict financial instability.
Hillegeist et al. (2004)	They have used famous indicators based on accounting and market variables called BSM-Prob, which indicates the probability of financial helplessness and instability. The variables used include the current market value of assets, the objective value of debt, the expected return on assets, and the expected interest rate of stocks.
Campbell et al. (2008)	To measure financial stability and instability, the following model is developed by the authors: CHS = −20.26NIMTAAVG + 1.42TLMAT − 2.13EXRETAVG + 1.41SIGMA − 0.045RSIZE − 2.13CASHMTA + 0.075MB − 0.58PRICE − 9.1 In this model, NIMTAAVG is the measure of profitability, TLMTA is the measure of financial leverage, EXRETAVG is the average past excess return, SIGMA is the volatility of stock returns, RSIZE is the relative size of the company based on market value, CASHMTA is liquidity and short-term investment. In addition, MB is the market’s ratio to the stock’s book value and PRICE is the stock price based on decimals. CHS uses quarterly accounting data, lack of success, or instability for reasons related to performance and receiving points from rating agencies. The probability of failure and financial instability for a few years is based on logistic regression estimation.
Sudarsanam and Lai (2001)	The Toffler Z Index consists of components such as profit before tax, current liabilities to current assets, total liabilities to current liabilities, and total assets to the non-credit interval.
Zhang et al. (2018)	Crisis and non-crisis model. This index classifies companies into two categories, crisis and non-crisis, in terms of financial stability.

Note: The term financial instability represents bankruptcy, financial distress, and financial crisis to increase the understandability of Table 1.

summarizes the research on financial stability and the indicators used to measure financial instability as follows.

According to

Table 2. Studies based on company-level characteristics (micro variables).

Authors	Research Question	Sample Studied	Method Used	Findings	Economic Significance
Al-Hadi et al. (2017)	The relationship between CSR and the probability of occurrence of financial instability in the economic cycle	651 Australian companies, years 2007–2013, randomly selected	Altman’s Z-index: Lower values indicate less financial instability.	CSR reduces the possibility of financial instability at the maturity stage.	One deviation of the CSR benchmark reduces the probability of financial instability by 46%.
Zhang et al. (2018)	The impact of R&D spending on financial volatility	55652 American companies, years 1980–2011	Linear regression	R&D positively impacts financial volatility, especially in a recession, and intangible assets negatively impact future financial volatility.	One standard deviation of R&D reduces financial volatility by 1.3 percentage points.
Beck et al. (2014)	The relationship between CSR and the likelihood of financial instability	58 Taiwanese companies in 2007–2010	The structural equation model can predict financial volatility.	CSR reduces the possibility of financial instability in the global recession crisis.	-
Tinoco and Wilson (2013)	Accounting variables, capital market, and financial volatility	23218 English companies, years 1980–2011	Binary logistic regression	The full model has the same power to explain volatility changes as Altman.	No
Magee (2013)	Foreign exchange backing and financial instability	401 American companies, 1996–2000	Merton’s instability probability (1974)	Foreign exchange backing has a negative impact on financial instability.	One deviation of the foreign exchange backing benchmark reduces the probability of financial instability by 0.785%.
Kane et al. (2005)	Employee relations and the possibility of financial instability	2228 American companies, 1991–2001	Altman’s Z-index	Good relationships with employees have a negative impact on financial instability.	No
Tennyson et al. (2008)	Usefulness of financial information and financial instability	Two examples of 23 successful and unsuccessful English companies		The level of relevance of financial information has a negative impact on financial instability.	No

, by reviewing the literature, the factors affecting companies’ financial helplessness or financial instability are categorized into three categories: company-level characteristics or performance micro variables, macroeconomic-level variables, and corporate governance determining factors. The research conducted on the factors of financial instability (Beaver et al. 2011) in companies is shown as follows:

Also, according to

Table 3. Studies based on the components of corporate governance.

Authors	Research Question	Sample Studied	Method Used	Findings
Gottardo and Moisello (2017)	Family ownership and financial instability	1137 views of Italy in 2004–2013	Binary logistic regression	Family ownership, the number of family members in management, and female CEOs negatively affect financial instability.
Schulze (2022)	Characteristics of the board of directors and financial instability	962 Australian companies, years 2000–2007	Probability of financial instability, Merton (1974)	Management ownership reduces financial instability, and the percentage of non-executive directors increases financial instability.
Darrat et al. (2016)	Characteristics of corporate governance and financial instability	217 successful and 9100 unsuccessful American companies, 1996–2006	Logistic regression	Obligator, personal knowledge and experience, percentage of female managers, length of CEO tenure, CEO succession, reduced financial volatility, and CEO power increases financial volatility.
Hsu and Wu (2023)	Board composition and financial instability	Two samples of 234 English companies in 1997–2000	Binary variable for financial instability and financial stability of the company	A company with more non-obligatory grey managers has more financial stability.
Kallunki and Pyykkö (2013)	Managing Director, Executive Director, and financial instability	48716 Finnish companies, years 2001–2008	Z-adjusted salary or benchmark CEO pay	A CEO or executive with a history of self-interest increases financial instability.
Tinoco and Wilson (2013)	Private ownership and financial instability	1852 acquired companies from 15 European countries in 2008–2000	Altman’s Z index and Olson’s index	Experienced private acquisition syndication managements have a negative effect on financial instability.

, the factors affecting the occurrence of financial instability based on corporate governance are described as follows:

2.3. Research Background

Al-Rjoub (2021) examined financial stability indicators for Jordan. He divides financial health indicators into four categories: 1. have announced capital adequacy; 2. earnings and solvency; 3. liquidity; 4. based on these variables, asset quality constructed by the composite financial stability index with equal weighting using the principal component method from 2003 to 2015. He showed that financial stability in the banking sector in Jordan is consciously resilient to shocks and adverse economic conditions.

Ilesanmi and Tewari (2020) investigated the issue of financial stress indicators and economic activities in South Africa. The financial stress index is a single aggregate index constructed to reflect finance’s volatile systemic nature and measure the financial system’s vulnerability to internal and external shocks. They have identified the financial stress index for South Africa between 2006 and 2017 using principal component analysis. The results show that the financial stress index is handy for measuring the effectiveness of government measures to reduce the impact of financial stress.

Kalsie et al. (2020) also examined the measurement of financial stability and its impact on foreign direct investment with evidence from BRIC countries. Economic stability has become a key fiscal, economic, and monetary policy objective. They pursued two objectives, one to create four indicators of financial stability and the second to use four indicators of financial stability constructed in a two-stage least squares regression framework to determine the impact of financial stability indicators on foreign direct investment for the period 2000 to 2017 in four countries, Brazil, Russia, India, and China. The results showed that all four indicators of financial stability in Brazil are significant. In the case of Russia, the government’s financial management needs to be carried out correctly. In the case of China, the large flow of foreign direct investment could be more effective in attracting foreign capital. The openness of the economy in all countries except India is conducive to foreign direct investment; of the four, Brazil is on the right track.

Ozili (2018) examined the impact of financial instability on sustainable development. The findings of the sustainable development index analysis show that financial stability significantly impacts sustainable development, and its impact is negative in Asian countries. European and Asian countries have a higher sustainable development index than African countries.

Orazalin et al. (2024) investigated whether CSR contributes to the financial sector’s financial stability. Their research suggests that CSR initiatives contribute to the financial stability of the financial sector and three subsectors.

2.4. Conceptual Model

After conducting exploratory studies and reviewing the research conducted, the analytical model of the present research, which is the basis for formulating the research question, is as follows, illustrated in Figure 1. Moreover, the conceptual model of the study is displayed in Figure 2.

3. Research Method

The philosophy of the current research is that the upcoming research is one of quantitative–qualitative study in the form of interpretations and positivism, and it is a mixture of different approaches such as exploratory, descriptive, quantitative, and qualitative. Therefore, it is also part of the philosophy of pragmatism. In the current research, the study conducts a survey and collects secondary data numerically by using interviews and then preparing a questionnaire. Therefore, the current research is quantitative–qualitative. Also, this research collects data for the variables and prepares essential indicators of financial stability in the world and Iraq by using experts’ opinions (including board members, financial managers, university professors, auditors, and other stakeholders) and studying previous research. Therefore, it is descriptive, and in the end, since there has yet to be research on financial stability modeling in Iraq, future research will gain new insight into the calculation of financial stability in Iraq and explain a model in this regard through an exploratory strategy.

3.1. Statistical Sample and Research Period

The statistical population of this research is divided into two parts:

The first part comprises research experts’ opinions about the leading stability indicators. The experts must have related occupational experience and knowledge about the current study’s topic. For example, they must be board members, financial managers, university professors, auditors, and other stakeholders.

The second part will include all the managers (including the CEO, financial manager, and managers of other departments) of the companies listed on the Iraqi Stock Exchange, which is used to measure the validity and reliability of the questionnaire extracted from the expert interviews at the beginning of 2024.

3.2. Sampling

The philosophical stance of the current study is a mixed-methods approach that includes quantitative and qualitative methodologies. This study applies exploratory and descriptive strategies to understand the financial stability indicators of Iraq. The research might be in the form of surveys and secondary data by interviewing experts, and it could be followed up by developing a structured questionnaire. It aims to obtain the essential indicators of financial stability by collecting insights from board members, financial managers, university professors, auditors, and other related experts from a wide circle of respondents. Since no previous study has been conducted with respect to modeling the financial stability of Iraq, this research may provide new insights for developing a model to assess financial stability in such a context.

Our purposive sampling technique may ensure the selection of at least 100 experts based on a pre-compiled list of academic and professional individuals in the field of finance. The selection criterion is guaranteed to be one that allows only participating respondents who have some form of educational background in the area under study and related practical experience. It is justified on the basis that in statistical advice, a sample size of 100 is sufficient for qualitative studies, given that this number can ensure data saturation to give out a robust analysis of expert opinions.

3.3. Necessary Features for Experts

To ensure the reliability of this study’s findings, selected experts have to be experienced and knowledgeable and may provide high-quality and reliable information. Therefore, some criteria shall be developed to identify the participants that best fit this role. Such factors will be in direct relation to the studied topic and the model for financial stability being examined. In the selection of experts to be included in this study, the following factors shall be taken into account. (1) Experts require a relevant educational background in finance, economics, accounting, or management areas. A minimum requirement will be a bachelor’s degree in one of the disciplines mentioned above. (2) Experts should have good professional experience with the research subject. This may include a minimum of 5 years of work experience holding a senior financial or managerial position, such as Chief Financial Officer, Financial Controller, Treasurer, etc.; a minimum of 5 years of work experience as a financial analyst/investment banker/portfolio manager working in the financial services industry; at least 5 years of work experience as a financial regulator, policymaker, or central bank official; or at least 5 years of working experience as an academic researcher or professor in finance, economics, or some other related area. (3) Experts must be able to show publications of research articles, books, or reports relating to financial stability, risk management, or corporate finance in reputable journals or other publications. This would serve to demonstrate the individual’s expertise and contribution to the field. (4) Professional certification as a Chartered Financial Analyst, Certified Public Accountant, or Certified Treasury Professional will be considered an added qualification to the aforementioned. (5) Experts shall have an absolute reputation and recognition in the Iraqi financial sector. Evidence may be in the form of awards, honors, or leadership positions held within professional associations or industry organizations. Considering these criteria, we may ensure that the collected data in the study are of high quality and represent insights and experiences from people with an in-depth understanding of financial stability within the Iraqi context.

3.4. Data Collection Methods and Instruments

The purpose is to present a model of financial stability in Iraqi companies, identify and explain its constituent factors and elements, and determine the value and importance of each of them in the model of financial stability. To carry out this research, the methods of study and exploratory search in relevant texts are used, and on the other hand, the opinions of academic publishers and the capital market are used.

A questionnaire approach is used to measure the determinants of financial stability in Iraq, as this approach can easily be adaptable to the situation and population of this country to which one applies, thus making it easy to cover most of the drivers of variables relevant to the research topic and demographic group. Moreover, it is administrable in various formats, such as online, face-to-face, or by telephone, making it the most effective instrument for collecting experts’ viewpoints. Also, the respondents may provide detailed and qualitative answers, as the questionnaires contain open-ended questions, reaching beyond simple answers to provide further distinctions of ideas, emotions, and experiences. Finally, the employed survey can yield data for a vast number of concepts, from social attitudes/behavior to individual-level health outcomes and environmental factors (Wang et al. 2022).

In particular, several reasons motivated the authors to use a non-parametric approach, while there are several parametric measurements for financial stability proposed by the existing literature. The study entails developing a conceptual model that considers the different dimensions affecting financial stability, such as macroeconomic and microeconomic variables at both the company and environmental levels and corporate governance. Therefore, such an approach gives insight into the realistic scenario of the elements influencing financial stability within the particular case of Iraq. In addition, a panel of 21 experts in related fields of study, validating the questionnaire to meet the objective of the study, may significantly increase the credibility of the data collected through the questionnaire. Thus, the employed methodology provides a robust analysis of financial stability by combining qualitative insights proposed through a questionnaire analysis and quantitative analysis using methods such as AHP and TOPSIS. In essence, this mixed-method approach provides a deeper understanding of the data with accommodation for statistical rigor, anchored in context-appropriate insights. By the employed approach, the weights for the various dimensions and components are determined clearly to bring out which factor most impacts financial stability, which seems impossible to obtain by employing parametric measurements of financial stability. This quantitative aspect is very important in assisting policymakers and practitioners in prioritizing interventions. More importantly, non-parametric methods require a few assumptions to be made about the distribution of the data. This is highly useful when the data may not be normally distributed, usually in the case of finance data exposed to sources of variability. Financial data always contain at least a certain number of outliers—extreme values that make a biased result. Meanwhile, the employed approach in this study is free from outliers and data abnormality, suggesting more robust and accurate insight into the central tendency and relationships within the data. The mixed method used in this study may serve as a necessary complement to any parametric analysis, adding insight or confirming the purpose of the findings. It leads to enhanced robustness of the research outcomes, which helps in producing an exhaustive understanding of the dynamics of financial stability. Finally, this approach is employed because of the special social, economic, and political context that Iraq possesses. The employed method may permit a much more tailored analysis, which catches hold of the generalities of this local environment.

Relevant to the theoretical framework of this investigation, there are several merits of AHP and TOPSIS approaches in the measurement of financial stability as follows. (1) Flexibility and adaptability: AHP and TOPSIS are flexible techniques that can be used in any environment of decision-making. They can deal with qualitative and quantitative criteria; therefore, they will be appropriate for the problem of financial stability, which is complex and involves objective data and subjective expert judgments. (2) Hierarchical structure: AHP decomposes the decision problem into a hierarchy, whereby the relationships among the goal, criteria, and alternatives can be better understood. This structured approach brings clarity to the relative importance of factors impacting financial stability. (3) Consistency check: AHP has a consistency check built into the process for measuring the logical consistency of the pairwise comparisons. This enables the detection of inconsistencies in expert judgments and hence gives an idea about where to correct them for reliable results. (4) Sensitivity analysis: AHP and TOPSIS allow for sensitivity analysis, which means that the former can check variations in the weights of the criteria for the final ranking of the alternative. This will also add weight to the results on the robustness and point out critical factors. (5) Dealing with uncertainty: AHP and TOPSIS are non-parametric methods, hence applicable in situations with uncertainty and ambiguity of choice in decision-making. No assumption about the underlying probability distribution is required; hence, the methods are quite appropriate for analysis with financial data that may not be normally distributed. (6) Ranking interventions: AHP and TOPSIS could, thus, be of great help in giving policymakers at different levels clear weights of the various dimensions impacting financial stability, thereby allowing them to prioritize their interventions. Quantification is thus hugely important in optimizing resource allocation and targeting only key factors with the most effect. These advantages are further enhanced by the combination of the two methods: that of eliciting qualitative insight and that of quantitative analysis, making AHP and TOPSIS very strong tools for the attainment of a holistic understanding of financial stability in the context of Iraq. Collectively, there are several advantages proposed by the mixed method employed in this study.

The employed questionnaire is disclosed in Appendix A. There are several reasons to employ this questionnaire, including (1) comprehensive coverage: the survey covers a wide range of drivers in promoting financial stability. The drivers are at the firm level, corporate governance level, macroeconomic, and environmental levels. In general, the presented questions may cover most of the potentially critical views of the topic. (2) Clear and concise questioning: the majority of the questions are solidly clear and concise; thus, they are easily understood by the respondents, which improves the credibility of the findings. (3) Using the Likert scale: the data responses are on a 5-point Likert scale, hence allowing the data to be analyzed numerically for computation and comparison; it also allows for statistical analysis and credible comparison. (4) Structured format: the contained questions are structured and separate the different categories of factors, making them easier to read and suiting the experience of the respondents. (5) Focusing on key areas: this questionnaire is guided by key thematic areas such as corporate governance, macroeconomic conditions, and firm-specific and environmental factors that play critical roles in ascertaining the overall financial health of a firm. The controlled thematic areas provide a thorough foundation on which valuable cues can be picked regarding what drives financial stability. This questionnaire may enhance the credibility and applicability of our results significantly.

4. Data Analysis

The study aims to examine the financial stability ratings in the capital market, identify and describe its constituent factors and elements, and determine their value and importance in the company’s financial stability rating model. To conduct this research, in the first stage, an exploratory study and search are conducted in the relevant literature, and on the other hand, the opinions of academic and capital market experts are used. The theoretical framework of the topic and relevant sources will also be determined, and by studying English and Arabic articles, research questions are designed to formulate the model.

In the next stage, after designing the initial framework of the research to validate it, we identify the model’s dimensions and determine whether the predicted financial stability model and its elements and constituent factors are compatible with the situation and reality of the Iraqi capital market. For this purpose, based on

Table 4. Descriptive statistics of respondents to the research questionnaire.

Variable	Respondent Opinion	Frequency	Percentage
Gender	Male	19	90%
	Female	2	10%
Age	Less than 40	11	53%
	40–45	4	19%
	45–50	2	09%
	50–55	4	19%
Position	University professor	2	10%
	Accountants	5	24%
	Auditor	4	19%
	Financial manager	6	28%
	Other	4	19%
Work experience	Less than 10	11	52%
	10–15	3	14%
	15–20	1	06%
	20–25	3	14%
	25 and up	3	14%
Education	Bachelor’s degree	12	57%
	Master’s degree	4	19%
	PhD	5	24%
Field of study	Economics	6	28%
	Accounting	11	53%
	Management	4	19%

, financial stability indicators were prepared and compiled as a questionnaire with 39 questions. In other words, an initial questionnaire was provided by preparing an initial list of 100 academic and professional experts and examining scientific and experimental records regarding the research topic. To ensure the research selection and final questionnaire met rigorous standards, the work was reviewed by a panel of 21 highly qualified researchers with expertise in the field. Table 4 shows the descriptive statistics of the respondents by education, service history, gender, position in the department, level of education, and field of study.

According to the final goal of the research, which is to provide a financial stability model for Iraqi companies, experts’ opinions should be analyzed to determine the statistical significance of the coefficient of each model’s dimensions, components, and indicators. The hierarchical analysis process method will be used to analyze dimensions and components, and the TOPSIS method will be used to analyze indicators. The reason for using the TOPSIS method in the analysis of indicators is that the number of indicators exceeds the limit of other applicable methods, such as AHP. The AHP is a structured technique to organize and analyze a complex decision based on qualitative and quantitative factors. It involves breaking down a decision into a hierarchy of objectives, criteria, and alternatives. The TOPSIS approach, as a statistical technique, is used to provide the order of preference by similarity to the ideal solution in our multi-criteria decision analyses, which considers evaluation and ranking against multiple criteria. We employed the TOPSIS due to its simplicity and rationality. TOPSIS gives an apparent and rational view of how to make decisions; it is easy to understand and implement, increasing our findings’ credibility. It suggests a quantifiable process featured with flexibility for various kinds of data as necessary for our settings. It can accommodate a high number of criteria and alternatives, so it is suitable for the analysis of the complicated situation of this study. TOPSIS also provides a simple computational process that can easily be automated by the authors, thus enabling efficient analysis of the data sets used for this study. Therefore, the authors have used TOPSIS to ensure the credibility of the findings. In addition, employed method for determining model’s coefficient is displayed in Figure 3.

4.1. The Results

The AHP provides a framework for thinking about complex issues. This process helps us to make appropriate and correct decisions for complex issues by simplifying the decision-making process. AHP is a method in which a complex situation is decomposed into smaller parts, and these parts are in a hierarchical structure. In this method, according to the importance of each variable and the numerical values assigned to it, the most critical variables are identified through mental judgments. In other words, the priority order of the variables is determined.

AHP creates an effective structure for group decision-making by streamlining the group thinking process. Assigning numerical values to the variables helps the decision-makers have the appropriate thinking pattern to reach the result. Also, the nature of consensus in group decision-making (its consultative nature) improves the consistency of judgments and increases the reliability of AHP as a decision-making instrument. In this way, with the help of AHP, very complex problems that include many factors can be understood and simplified.

Table 5. Dimension coefficients and model components.

Dimensions
Macro Variable at Economy Level (C1) 0.168			Micro Variable at Company Level (C2) 0.236			Company Level Variables (C3) 0.251			Corporate Governance Variables (C4) 0.345
Code	Title	Coefficient	Code	Title	Coefficient	Code	Title	Coefficient	Code	Title	Coefficient
C11	Characteristics of the economy	0.304	C21	Performance	0.201	C31	Company’s characteristics	0.401	C41	Shareholders’ rights	0.225
C12	Instability	0.265	C22	Financial structure	0.331	C32	Variables related to profitability	0.590	C42	Transparency	0.312
C13	Political factors	0.431	C23	Resource management	0.163				C43	Effectiveness of the board of directors	0.129
			C24	Liquidity	0.305				C44	Effects of ownership	0.334

shows the coefficients of each dimension and component obtained using AHP.

As is known, the dimension of corporate governance with a coefficient of 0.345 significantly impacts corporate governance. According to prior investigations, improved corporate governance may lead to financial stability for several reasons. In this regard, Susanto and Walyoto (2023) indicate that enhanced corporate governance may assist companies in improving their stability through risk management. Effective corporate governance structures, through the board of commissioners and audit committees, enhance a company’s ability to identify, assess, and mitigate financial risks. This ensures companies’ resilience in facing emerging financial shocks. Moreover, independent decision-making can be guaranteed through effective corporate governance mechanisms, which include frequent board meetings and a balanced board structure. Consequently, a strong corporate governance structure can support the organization’s adaptation to changing markets, including insurance innovations to maintain financial stability and business dynamism (Nwogugu 2015). It helps a company avoid suboptimal financial decisions that may endanger its financial stability. Effective corporate governance can also lead to more transparency in financial reporting and operations (Mabvira 2018). This is important in discovering or averting financial misreporting, critical to maintaining financial stability and investor trust in the market.

The dimensions of company environment variables, micro variables at the company level, and macro variables at the economic level are also critical, with coefficients of 0.251, 0.236, and 0.168, respectively. According to the results, the financial stability score (FSS) can be obtained at the dimension level through model (1):

Model (1):

$$\mathrm{F}\mathrm{S}\mathrm{S}=0.168 \mathrm{C}1+0.236 \mathrm{C}2+0.251 \mathrm{C}3+0.345 \mathrm{C}4$$

Also, according to the obtained coefficients for the components, the related equations at the level of the components are described as follows:

Model (2):

$$\mathrm{C}1=0.304 \mathrm{C}11+0.265 \mathrm{C}12+0.431 \mathrm{C}13$$

Model (3):

$$\mathrm{C}2=0.201 \mathrm{C}21+0.331 \mathrm{C}22+0.163 \mathrm{C}23+0.305 \mathrm{C}24$$

Model (4):

$$\mathrm{C}3=0.410 \mathrm{C}31+0.590 \mathrm{C}32$$

Model (5):

$$\mathrm{C}4=0.225 \mathrm{C}41+0.312 \mathrm{C}42+0.129 \mathrm{C}43+0.334 \mathrm{C}44$$

By combining model (1) with models (2), (3), (4), and (5), the financial stability score equation can be obtained based on the components as follows:

Model (6):

$$\begin{array}{ll}\mathrm{F}\mathrm{C}=0.051 \mathrm{C}11& +0.044 \mathrm{C}12+0.072 \mathrm{C}13+0.047 \mathrm{C}21+0.078 \mathrm{C}22+0.038 \mathrm{C}23\\ & +0.072 \mathrm{C}24+0.102 \mathrm{C}31+0.148 \mathrm{C}32+0.069 \mathrm{C}41+0.107 \mathrm{C}42\\ & +0.044 \mathrm{C}43+0.115 \mathrm{C}44\end{array}$$

4.2. Prioritization of Indicators by TOPSIS Method

TOPSIS is one of the multi-criteria decision-making methods based on the distance size based on the Euclidean model for the negative and positive ideal solutions. The research conceptual model shows that each component includes one or more indicators. Due to the high number of indicators, the TOPSIS has prioritized the indicators. After performing the various steps of this method, the priority of the indicators regarding each of the components is in

Table 6. Coefficients of each index in the model.

Index Code	Definition	Index Coefficient in Component	Index Coefficient in the Final Model
The priority of component indicators of macro variables at the economic level
The priority of component indicators of economic characteristics
C111	Oil price	0.428	0.021
C112	Inflation	0.572	0.029
The priority of volatility component indicators
C121	Isis	0.331	0.014
C121	Changes in exchange rates	0.273	0.012
C123	Economic and political instability	0.369	0.016
C131	Sanctions	1	0.07241
According to the definition of only one index for this component, its coefficient is one.
The priority of micro variable component indicators at the level of companies
The priority of liquidity component indicators
C211	Debt repayment period	0.278	0.013
C212	Quick ratio	0.457	0.021
C213	Current ratio	0.265	0.012
The priority of resource management component indicators
C221	Periodicals Collection	0.196	0.015
C222	Working capital	0.350	0.027
C223	Turnover of assets	0.258	0.020
C224	Turnover of goods	0.196	0.015
The priority of financial structure component indicators
C231		0.225	0.008
C232		0.312	0.012
C233		0.463	0.017
The priority of performance component indicators
C241	Return on investment	0.116	0.008
C242	Earnings per share	0.237	0.016
C243	Return on capital	0.145	0.010
C244	Net profit margin	0.119	0.008
C245	Fluctuation of profitability	0.215	0.015
C246	Stock beta	0.168	0.012
The priority of the component indicators of the variables of the company’s environment
The priority of the component indicators of the company’s characteristics
C11	Industry dummy variable	1	0.10291
According to the definition of only one index for this component, its coefficient is one
The priority of profitability component indicators
C321	Growth opportunities	0.362	0.053
C322	Return on equity	0.638	0.094
Prioritization of component indicators of corporate governance variables
Priority of shareholder rights component indicators
C411	Announcement of dividend policy	0.183	0.014
C412	Providing financial reports	0.298	0.023
C413	Future management and performance forecasting	0.193	0.014
C414	Presenting the report of the board in meeting	0.326	0.025
The priority of transparency component indicators
C421	Disclosure of remuneration of board members	0.421	0.045
C422	Disclosure of contract details	0.351	0.037
C423	Disclosure of shares of board members	0.228	0.024
The priority of indicators of the effectiveness of corporate governance
C431	Independence of the board of directors	0.250	0.011
C432	Financial expertise of the board of directors	0.319	0.014
C433	Expertise in the board industry	0.103	0.004
C434	The duality of management	0.119	0.005
C435	The existence of an audit committee	0.209	0.009
The priority of ownership affects component indicators
C441	Institutional ownership	0.467	0.053
C442	Property management	0.533	0.061

.

As seen in the above table, the value of two of the indices’ coefficients for each column is equal to one, indicating that these two components consist of only one variable, respectively, sanctions and the industry dummy variable, instead of a composite of multiple indicators. The coefficient of each index in the final model can be calculated through the following relationship:

$${\mathrm{W}}_{\mathrm{m}}={\mathrm{W}}_{\mathrm{d}}+{\mathrm{W}}_{\mathrm{c}}+{\mathrm{W}}_{\mathrm{i}}$$

${\mathrm{W}}_{\mathrm{m}} \mathrm{i}\mathrm{s}$ the result of the index coefficient, ${\mathrm{W}}_{\mathrm{i}}$ is the index coefficient in the component, ${\mathrm{W}}_{\mathrm{c}}$ is the component coefficient, and ${\mathrm{W}}_{\mathrm{d}}$ is the dimension coefficient. The values of ${\mathrm{W}}_{\mathrm{c}}$ and ${\mathrm{W}}_{\mathrm{d}}$ are reported in Table 6. For example, the index coefficient of C441 in the final model is calculated as follows:

$${\mathrm{W}}_{\mathrm{m}}=0.345\ast 0.334\ast 0.467=0.0538$$

The sum of index coefficients in the final model for all indices (39) will equal one. By comparing the coefficients of the indicators in the final model, their importance in assessing each company’s financial stability is determined. For example, the index has the highest coefficient among the 39 indicators of the model. As mentioned in the last part of the introduction, none of the countries, the rating institutes, or the research conducted have mentioned the coefficients of dimensions, components, and indicators, and only the titles of dimensions, components, and indicators have been mentioned. Therefore, comparing the results with those of previous studies is impossible. However, the cultural, political, economic, and social differences between the countries make it impossible to use them in other countries

5. Discussion

The current study, considering the importance of the financial stability of the financial systems of the banks and business units of emerging countries such as Iraq, seeks to highlight critical aspects affecting the financial stability of companies and banks.

Generally, the statistical significance of the coefficient of the dimensions in the final model is, respectively, 0.342 for the corporate governance dimension, 0.312 for the corporate variables dimension at the micro level, 0.251 for the corporate environment variables, and 0.166 for the macro variable at the economic level, which indicates the increasing impact of corporate governance in developing the financial stability of Iraqi companies.

Primarily, the findings suggest that enhanced corporate governance may assist companies in improving their stability through risk management (Susanto and Walyoto 2023). Effective corporate governance structures, through the board of commissioners and audit committees, enhance a company’s ability to identify, assess, and mitigate financial risks. This ensures companies’ resilience in facing emerging financial shocks. Moreover, independent decision-making can be guaranteed through effective corporate governance mechanisms, which include frequent board meetings and a balanced board structure. Consequently, a strong corporate governance structure can support the organization’s adaptation to changing markets, including innovations in the insurance market. For example, insurance maintains financial stability and business dynamism (Nwogugu 2015). It helps a company to preclude from suboptimal financial decisions that may endanger its financial stability. Effective corporate governance can also lead to more transparency in financial reporting and operations (Mabvira 2018). Additively, related to corporate governance, ownership structure effects have the highest coefficient of importance, with a coefficient of 0.334. It refers to the structure of a firm’s distribution of ownership rights among all stakeholders, including individual shareholders, institutional investors, governmental owners, and management. The ownership structure can exert a great influence on the financial stability of a firm. Moudud-Ul-Huq et al. (2022) indicate that ownership structures can affect the financial stability of a company through efficient risk management. They document that Islamic banks are less risky than other forms of ownership, adding to their financial stability. They also suggest that ownership structure can affect a firm’s market power and competitive position. Firms with solid ownership structures may be better positioned to cope with competitive pressures, thus enhancing their financial stability. Rubio-Misas (2020) indicates that companies with a more concentrated ownership structure tend to show lower levels of financial stability, consistent with the view that in closely held firms, the owner and manager incentives are more aligned. Therefore, different ownership structures may increase or decrease companies’ risk-taking ability and risk-management strategies, eventually determining their stability.

Similarly, among the components related to macro variables at the economic level, political factors have the highest coefficient of importance, with a coefficient of 0.431. In essence, a predictable business environment requires political stability. Political instability, which includes violence and unrest, is likely to affect business operations, chase away investment, and increase operational risks (Zaiane and Moussa 2021). For instance, the political instability resulting from the Arab Spring impacted the performance of banks in the MENA region, an aspect that depicts the deteriorating impact of political turmoil on financial stability.

Additionally, among the components of micro variables at the company level, the financial structure with a coefficient of 0.331 has the highest coefficient of importance. The financial structure is vital to ensuring the financial stability of a company. The financial structure of a given company determines its flexibility toward change in the market. High debt levels limit a firm’s flexibility during economic downturns, making them very vulnerable to financial distress (Abbas et al. 2021). For instance, the case of the Asia Cell Communications Company has highlighted that overdependency on debt adversely affects financial flexibility, which restrains a firm’s ability to pay off short-term liabilities and, consequently, its financial stability. Moreover, the financial structure directly affects the liquidity position of a firm. A firm with a much more balanced financial structure including sufficient cash and manageable debt can better cope with unexpected expenses or economic downturns (Aslam et al. 2016). Low liquidity can trigger inadequate cash flow, threatening a firm’s financial stability. Finally, the financial structure indicates how a company efficiently runs its assets. A company with a reasonable balance between debt and equity typically has better asset and investment management skills (Eisdorfer et al. 2013). Therefore, effective asset and investment management can contribute to financial stability by ensuring that a company generates sufficient returns on assets to compensate for its liabilities.

Finally, among the components of the variables of the company’s environment, variables related to profitability with a coefficient of 0.590 have the highest statistical significance. One major aspect that can have a telling effect on the financial stability of any firm is profitability. It directly determines the ability of a firm to generate cash flows and manage its liquidity. Higher profitability secures more funds for meeting short-term obligations, ensuring financial stability. Studies show that reduced liquidity due to low profitability can lead to a cash flow crisis, thus threatening the firm’s financial stability (Abbas et al. 2021). Furthermore, profitability determines a firm’s ability to service its interest and other debt-related obligations. High profitability ensures that firms can service interest and principal payments on time and are less likely to default on loans, thus ensuring financial stability (Aslam et al. 2016). In other words, reduced profitability will limit the ability of a company to service its debt, which is likely to increase financial risks. Finally, profitability may assist companies in improving their financial stability by providing a competitive advantage. The more profits a company obtains, the more it can invest in innovation, technology, and marketing, hence maintaining a market and financial position (Halim et al. 2023).

Model (6) shows the financial stability score equation based on research components. In this equation, C32 (profitability variables) has a coefficient of 0.148, C44 (ownership effects) has a coefficient of 0.115, C42 (Transparency) has a coefficient of 0.107, and C31 (company characteristics) has a coefficient of 0.102, with the most significant impact in the final model.

Table 7. Index coefficients in the final model.

No.	Code	Title	Coefficient in the Final Model	No.	Code	Title	Coefficient in the Final Model
1	C32	Variables related to profitability	0.148	8	C41	Shareholders’ rights	0.069
2	C44	Effects of ownership	0.115	9	C11	Characteristics of the economy	0.051
3	C42	Transparency	0.107	10	C21	Function	0.047
4	C31	Features of the company	0.102	11	C12	Instability	0.044
5	C22	Financial structure	0.078	12	C43	Effectiveness of the board of directors	0.044
6	C24	Liquidity	0.072	13	C23	Resource management	0.038
7	C13	Political factors	0.072

presents the research components in the order of statistical significance of their coefficients in the final model.

At the index level, in the final model, the index coefficients are presented in Table 7. Dummy variable indicators of industry, return on equity, sanctions, managerial ownership, institutional ownership, growth opportunities, disclosure of board members’ remuneration, contract details, inflation, and working capital have the highest coefficients in the final model.

Table 8. Top ten research indicators in terms of importance factor in the final model.

Code	Index Title	Coefficient in the Final Model
C311	Industry dummy variable	0.102
C322	Return on equity	0.094
C131	Sanctions	0.072
C442	Managerial ownership	0.061
C441	Institutional ownership	0.053
C321	Growth opportunities	0.053
C421	Disclosure of remuneration of board members	0.045
C422	Disclosure of contract details	0.037
C112	Inflation	0.029
C222	Working capital	0.027

shows the indicators with higher importance coefficients (top 10 indicators).

6. Implications

The results suggest that Iraqi companies should pay enough attention to the company environment, corporate governance, and macroeconomic-level variables because these factors can affect their financial stability. Correspondingly, the following implications are proposed to companies, management, policymakers, and stockholders.

Based on the results of corporate governance enhancements, companies are required to enhance corporate governance structures to support improved risk management that is resilient against financial shocks and instability. Companies are supposed to implement proper mechanisms of governance, where effective board meetings are needed, with balanced board structures that guarantee independent decision-making. Increasing transparency in financial reporting and operations will reduce financial misreporting and sustain investor trust, which is necessary for risk management. Moreover, the ownership structure of firms should be considered and shaped very carefully since it influences their positioning with respect to financial stability via efficient risk management and competitive positioning.

To achieve political stability, which is necessary for a predictable business environment, governments must reduce political instability since its related shocks are among the biggest threats to organizational success. Companies must be prepared to handle the risks associated with political instability, positively impacting business operations and investments. According to the findings on the capital structure, firms should manage their level of indebtedness to be in a better position to deal with an economic downturn by reducing their vulnerability to financial distress. Those companies possessing a balanced financial structure are more resilient to financial shocks. For example, sufficient cash to keep the business running and bearable levels of debt that ensure sustainability during irregular periods or economic downturns are among the effective factors ensuring superior performance. The efficient management of assets and investments may also help companies keep the apt returns that will cover all liabilities.

Finally, the companies notice that high profitability is vital for generating cash flows and liquidity management, and securing sufficient funds is critical to meet short-term obligations. Therefore, a firm’s profitability determines its ability to service interest and debt obligations, reducing the risk of default. Accordingly, it is recommended that profits should be reinvested in innovation, technology, and marketing to maintain a competitive and financial position in the market.

7. Conclusions

To conclude, the research provides a general model supporting the relationship between corporate governance, financial structure, political stability, and profitability in achieving company financial stability in Iraq. These findings have positive insightful implications for company management, policymakers, and investors, who have to worry about these dimensions to create a more stable and resilient financial environment in Iraq. By understanding these critical variables, the companies in Iraq may also achieve their financial stability, which contributes to the economic development of the nation.

Although this research depicted the financial stability model for the companies in Iraq, there are a few limitations, and further investigations can be performed based on our results about the complex nature of financial stability.

While the results might well apply to other similar emerging economies, they cannot be generalized to other cultural or economic settings. Indeed, the study is based on a relatively modest number of companies and experts, and while more widespread, diversified, and larger, the sample is the stronger foundation for establishing more decisive general conclusions. The research method used was cross-sectional, collecting data at one point in time. This methodology imposes limitations to find out changes in the status of financial stability over the long run or to establish a causal relationship between the variables.

Future research can adopt a longitudinal research design to trace the changes in the level of financial stability. This may help in understanding the dynamics of financial stability and the impact of various factors in different economic cycles during a long period. Comparative studies across different emerging markets might help to explain the way contexts impact financial stability. This can help identify best practices that can be transferable across different settings. Researchers can step ahead and investigate further dimensions or variables that are likely to affect financial stability; this includes technological changes, market competition, or regulatory changes.