Asian Journal of Economics, Business and Accounting

Predicting Financial Crises in Iraqi Banks Using the ARIMA Model: An Applied Study on the Non-Performing Loans 2011-2024

Ibrahim Baraka Hamadi — Fri, 31 Jul 2026 00:00:00 +0000

The Iraqi banking sector plays a vital role in maintaining financial stability and supporting economic development. However, rising credit risks require reliable forecasting tools capable of strengthening early warning systems. Despite the widespread application of time-series forecasting models, empirical evidence on predicting non-performing loan (NPL) ratios in Iraqi banks remains limited.

This study evaluates the predictive performance of the Autoregressive Integrated Moving Average (ARIMA) model in forecasting NPL ratios and identifies the most appropriate model specification for each bank. Annual data for four Iraqi commercial banks listed on the Iraq Stock Exchange covering the period 2011–2024 were collected from the Central Bank of Iraq, the Iraq Stock Exchange, and the banks’ annual reports.

Stationarity was examined using the Augmented Dickey–Fuller (ADF) test, while ARIMA specifications were selected based on autocorrelation and partial autocorrelation analyses supported by model selection criteria. Forecast accuracy was evaluated using the coefficient of determination (R²), root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and Theil’s U² coefficient, followed by three-year forecasts for each bank.

The estimated ARIMA models produced statistically acceptable forecasting performance. Gulf Commercial Bank achieved the highest explanatory power (R² = 0.818), whereas Iraqi Investment Bank recorded the lowest forecasting error (MAPE = 33.61%; Theil’s U² = 0.970). Forecasts indicate a gradual increase in NPL ratios during 2025–2027, suggesting a deterioration in loan portfolio quality. These findings demonstrate that NPL ratios can serve as effective quantitative early warning indicators of increasing credit risk rather than direct measures of financial crises. Accordingly, ARIMA models provide a practical and transparent forecasting framework for supporting banking supervision and credit risk monitoring in Iraqi commercial banks.

Influence of Sustainable Housing Finance Mechanisms on Socioeconomic Development of Residents in Machakos County, Kenya

Kioko Stanley Ngumbi, Nzioka Alice, Nzioki Susan — Fri, 31 Jul 2026 00:00:00 +0000

Sustainable housing finance mechanisms are important instruments for improving access to affordable housing and supporting socioeconomic development. This study examined the influence of sustainable housing finance mechanisms on socioeconomic development among residents of Machakos County, Kenya. It focused on financing approaches associated with the Affordable Housing Programme, including rent-to-own schemes, subsidies, government support, land provision and other affordable housing finance arrangements. The study was guided by Programme Theory, which explains how programme inputs and activities generate outputs, outcomes and long-term impacts. A descriptive survey research design was adopted. The target population comprised Affordable Housing Programme beneficiaries and Micro, Small and Medium Enterprises operating within Machakos Central and Mavoko Sub-Counties. From a population of 3,530 respondents, a sample of 359 was selected using stratified and simple random sampling techniques. Primary data were collected using structured questionnaires measured on a five-point Likert scale. A total of 339 completed questionnaires were returned, representing a response rate of 94.4%. Data were analysed using descriptive statistics, Pearson correlation analysis and linear regression analysis. The findings indicate that sustainable housing finance mechanisms are positively associated with socioeconomic development outcomes. Respondents reported improvements in employment creation, poverty reduction, local economic activity, access to utilities, infrastructure, healthcare access, housing quality, affordability, safety and security. The regression results showed that housing finance interventions explained 40.6% of the variation in socioeconomic development outcomes. The ANOVA results indicated that the model was statistically significant. The study concludes that sustainable housing finance mechanisms contribute to socioeconomic development by improving housing affordability, supporting home ownership, enhancing household stability and stimulating local economic activity in Machakos County.

Impact of Environmental, Social, Governance (ESG) and Company Size on Company Value: The Moderating Role of Profitability in Energy Sector Companies (2020-2024)

Diah Iskandar, Sely Megawati Wahyudi, Putri Renalita Sutra Tanjung — Tue, 04 Aug 2026 00:00:00 +0000

Aims: This study examines the effects of Environmental, Social, and Governance (ESG) performance and company size on company value, measured by Price to Book Value (PBV), and tests whether profitability, measured by Return on Assets (ROA), moderates these relationships in Indonesian energy-sector companies.

Study Design: The study employed a quantitative explanatory design using firm-year panel observations.

Place and Duration of Study: The sample was selected through purposive sampling among energy-sector companies listed on the Indonesia Stock Exchange (IDX) during 2020–2024. The final dataset comprised 495 firm-year observations.

Methodology: SmartPLS was used to estimate the structural relationships among ESG score, company size, profitability, company value, and the two interaction terms. The evaluation used descriptive statistics, R-square, path coefficients, t-statistics, and p-values.

Results: The structural model explained 1.2% of the variance in company value (R-square = 0.012; adjusted R-square = 0.002). ESG score had a positive but statistically non-significant association with company value (beta = 0.029; t = 1.198; p = 0.231), while company size had a negative and statistically non-significant association (beta = -0.187; t = 0.753; p = 0.451). Profitability was also not significant as a direct predictor (beta = 15.328; t = 0.802; p = 0.422). The interaction between profitability and ESG was statistically non-significant (beta = -0.004; t = 0.113; p = 0.910), as was the interaction between profitability and company size (beta = -0.593; t = 0.880; p = 0.379).

Conclusion: The findings indicated that ESG score, company size, and profitability did not provide statistically detectable explanations of PBV in the observed energy-sector sample, and profitability did not strengthen either focal relationship. The very low explanatory power of the model suggested that company value during 2020–2024 was predominantly associated with factors outside the variables included in this study.

Financial Literacy, Behavioural Biases and Formal Financial Service Usage among Tribal Communities: Evidence from Gumla District, Jharkhand, India

Sharmeen Ejaz — Wed, 05 Aug 2026 00:00:00 +0000

This study examines the relationship between financial literacy, behavioural biases, and the use of formal financial services among tribal households in Gumla district, Jharkhand. A descriptive and exploratory design was employed. Primary data were collected from 60 households across Chainpur, Bishunpur, and Gumla Sadar through a structured questionnaire, field observations, and semi-structured interviews, supplemented by official secondary sources. Financial literacy was assessed using a 10-item instrument and classified as low, medium, or high. The results show that 36.7% of households had low financial literacy, 46.7% had medium literacy, and 16.6% had high literacy. One-quarter reported irregular account use, while 40% expressed fear of making financial mistakes and 60% preferred cash for routine transactions. More than half relied on Self-Help Groups or community leaders for financial advice. Only 35% used mobile banking or digital payments. A marked gender difference was observed: 90% of women reported low digital confidence, compared with 40% of men. The findings indicate that account ownership alone does not ensure effective financial participation. Formal financial service usage is associated with the interaction of literacy, confidence, behavioural tendencies, gender, and income regularity. Meaningful inclusion therefore requires community-based and gender-sensitive interventions that combine practical financial education, digital confidence-building, simplified procedures, and trusted local support.

Relationship between Agriculture Expenditure and Agriculture Growth in Rajasthan

Kirandeep Kaur — Wed, 05 Aug 2026 00:00:00 +0000

This study examines the dynamic relationship between government expenditure on agriculture and agricultural growth in Rajasthan using annual time-series data for 1980–2018. Four functional specifications were estimated to assess the relationships among agricultural expenditure, agricultural net state domestic product (NSDP), total government expenditure, and total NSDP. The analysis employed the autoregressive distributed lag (ARDL) model, vector autoregression (VAR), and vector error correction model (VECM), following unit-root and cointegration testing. Model selection and diagnostic tests were used to assess the adequacy of the estimated specifications. The Johansen–Juselius results identified one cointegrating relationship between total government expenditure and total NSDP, while no Johansen cointegration was detected for the other model specifications. However, the ARDL bounds test indicated a long-run relationship between agricultural expenditure and agricultural NSDP. The VECM results revealed unidirectional short- and long-run causality from total NSDP to total government expenditure. The VAR estimates further showed unidirectional causality from total NSDP to agricultural expenditure and from agricultural expenditure to total government expenditure. Overall, the findings indicate that the direction and persistence of the expenditure–growth relationship vary across the variables and econometric specifications considered. The results imply that agricultural expenditure should be allocated and monitored carefully, with greater attention to productive capital expenditure, so that public spending can support sustained agricultural development in Rajasthan.

Corporate Governance Quality in Emerging-market Banks: An Empirical Analysis Using a Composite Governance Index

Fateha Hossain, Nazmin Sultana Rafa, Oli Ahad Thakur, Afroja Akter — Thu, 06 Aug 2026 00:00:00 +0000

This study evaluates the corporate governance quality of five conventional commercial banks in Bangladesh using a disclosure-based composite governance index. The study adopts a quantitative, cross-sectional, disclosure-based design using secondary data collected from the audited annual reports of the top five conventional commercial banks (CCBs) in Bangladesh. Comparability across institutions was achieved by applying purposive sampling in selecting the sample. The study population comprised 33 conventional commercial banks operating in Bangladesh, from which the top five banks were selected through purposive sampling to ensure comparability across institutions. The analysis focuses on BRAC Bank PLC, City Bank PLC, Dutch-Bangla Bank PLC, Eastern Bank PLC, and Prime Bank PLC for the financial year 2024. Secondary data were collected from publicly available audited annual reports and assessed across six governance dimensions: board of directors, risk management committee, internal audit committee, nomination and remuneration committee, compliance and ethics committee, and disclosure and transparency. A total of 57 indicators were used after excluding experience-based indicators that were not consistently disclosed across the sampled banks. Each criterion was scored using a structured scale, and dimension-wise mean scores were combined to estimate the overall Corporate Governance Index. The results show that BRAC Bank PLC achieved the highest overall score of 4.34 and was classified as having very strong governance. Eastern Bank PLC, Prime Bank PLC, City Bank PLC, and Dutch-Bangla Bank PLC were classified as having strong governance, with overall scores of 3.65, 3.50, 3.48, and 3.41, respectively. Disclosure and transparency scores were generally high across the sample, while risk management and compliance-related dimensions showed comparatively weaker performance in some banks. The findings suggest that governance quality among the selected banks is relatively strong but uneven across dimensions, indicating the need for improved risk governance, compliance monitoring, and more consistent disclosure practices.

Selected Macroeconomic Determinants of Foreign Direct Investment in Kenya

Stella Kagendo Ndwiga Ndung’u — Thu, 06 Aug 2026 00:00:00 +0000

This study empirically investigates the effects of selected macroeconomic determinants on foreign direct investment (FDI) inflows in Kenya. Using annual time-series data covering 1986–2021, the study applies an autoregressive distributed lag (ARDL) model to capture short-run dynamics and lagged adjustment effects in FDI. Secondary data were obtained from official national sources: exchange-rate and interest-rate series were drawn from the Central Bank of Kenya, while inflation and FDI series were obtained from the Kenya National Bureau of Statistics. The ARDL bounds test suggests no cointegration at the 5% level; therefore, the results should be interpreted mainly as short-run relationships. Structural-break testing indicates a regime shift around 2013. The regression results show that the contemporaneous exchange-rate measure has a positive and statistically significant association with FDI. Inflation is positive and significant in the current period and at selected lags, while interest rates are positive and significant in the current period and show a delayed effect. The findings underscore the importance of macroeconomic conditions in shaping Kenya’s FDI dynamics and suggest that policies promoting exchange-rate predictability, inflation stability, and interest-rate credibility may strengthen investor confidence.

The Impact of Cognitive Biases on Investment and Financial Decision-making in Nigeria

Sofayo, Abiola A., Anisulowo, Temitope A., Anthony, Boluwatife O. — Fri, 07 Aug 2026 00:00:00 +0000

Behavioural finance explains how cognitive biases can lead investors to make systematic errors when making investment decisions, potentially resulting in poor or harmful outcomes. Biases such as overconfidence and regret or loss aversion distort investors’ perceptions and judgement, influencing investment and financial decision-making and contributing to suboptimal financial planning and risk-taking behaviour. This study therefore determines the impact of cognitive biases on investment and financial decision-making among investors in Nigeria. A survey strategy was adopted. The study population comprised 400 individual investors selected in Nigeria to ensure diversity in economic development and cultural context. The Taro Yamane formula was used to calculate a sample size of 200. A structured questionnaire containing three sections, A, B, and C, was used for data collection. Two hundred copies of the questionnaire were administered online to participants via Google Forms using a purposive sampling technique; 161 were completed correctly and submitted for analysis. Descriptive statistics (frequency counts, percentages, means, and standard deviations) and inferential statistics, including linear regression analysis, were applied at the 0.05 level of significance. The results revealed that the two selected cognitive biases had a weak and statistically insignificant positive impact on investment and financial decision-making among selected active individual investors in Nigeria (F = 2.641, p = 0.106 > 0.05). In addition, R = 0.128, R2 = 0.016, and adjusted R2 = 0.010 indicate that overconfidence bias and loss/regret aversion bias explained only 1.6% of the variation in investment and financial decision-making. The study was limited by its online survey design, its reliance on self-reported responses, and its focus on two cognitive biases. These constraints should be considered when interpreting the findings on investment and financial decision-making in Nigeria. The study examines the impact of overconfidence bias and loss/regret aversion bias on investment and financial decision-making among Nigerian investors in 2026. study concluded that cognitive biases exerted a weak and statistically insignificant positive impact on investment and financial decision-making among Nigerian investors. It recommended that financial advisers be trained to identify signs of cognitive bias in clients’ decision-making. Regulators, universities, and financial institutions should expand investor education initiatives to raise awareness of overconfidence bias and loss/regret aversion bias. Finally, policymakers should continue to monitor how emerging financial products, including cryptocurrencies and AI-driven investments, interact with cognitive biases.

Macroeconomic Factors and the Performance of the Manufacturing Sector in Kenya

James Murunga — Sat, 08 Aug 2026 00:00:00 +0000

The share of the manufacturing sector in Kenya's GDP has been declining for over a decade starting from a high of 12% in 2011 to a low of 7% in 2024. This decline raises concerns about Kenya's ability to attain its Vision 2030 goal of becoming a middle-income country by the year 2030. This study therefore investigates the effects of the macroeconomic factors on the performance of the manufacturing sector in Kenya. The macroeconomic factors considered include inflation, exchange rate and interest rate. The study also controlsfor the effects of foreign direct investment and gross fixed capital formation on the country's manufacturing output-to-GDP ratio. Annual time-series data from 1970 to 2024 is used. Some variables are integrated of order zero, whereas others were are integrated of order one. In addition, the autoregressive distributed lag bounds test reveals the absence of a long-run relationship among the variables. These characteristics informsd the choice of a short-run autoregressive distributed lag model. The results show that the coefficient on the first lag of the natural logarithm of the manufacturing output-to-GDP ratio is positive andstatistically significant. The coefficient is alsoless than one, illustrating a stable dynamic adjustment process. The coefficients on inflation and the exchange rate is negative and statistically significant. Specifically, the estimates show that a 1% increase in inflation leads to a 0.042% decrease in the manufacturing output-to-GDP ratio, ceteris paribus. Similarly, inflation in the previous period reduces the current manufacturing output-to-GDP ratio by approximately 0.044%. In addition, a 1% increase in the exchange rate leads to a 0.3% decrease in the manufacturing output-to-GDP ratio in both the current and subsequent periods. These results imply that inflation and the exchange rate are the macroeconomic factors the determine the manufacturing performance in Kenya. Based on these findings, the study recommends that policymakers should prioritise maintaining low inflation and a stable exchange rate. This can be achieved by strengthening macroeconomic policy coordination between the Central Bank of Kenya and the National Treasury to ensure that monetary, fiscal and exchange-rate policies are mutually supportive.

Beyond the Layover: The 7Ps Marketing Mix, Service Quality Gaps, and Guest Experience in Small-Town Hotels

Rustum D Gevero, Jofran P Doromal — Sat, 08 Aug 2026 00:00:00 +0000

This study investigates how small-town hotels implement marketing strategies and manage service quality in secondary, transit-oriented destinations. Although previous research has extensively covered hospitality in major tourist hubs, limited attention has been given to the unique operational challenges of rural transit municipalities. To address this gap, the study evaluates the implementation of the 7Ps marketing mix and identifies the service gap between guest expectations and actual hotel performance in Maramag, Bukidnon. Employing a descriptive research design, this research analyzes survey data from hotel guests and interviews with managers across five registered hotels. The study measures performance and importance using a validated four-point Likert scale. The findings show that hotels excel in "People" and "Price" but struggle significantly with "Physical Evidence" and "Promotion." Guests highly value reliable Wi-Fi and digital engagement, yet the hotels suffer from aging facilities and outdated marketing methods. The staff's exceptional service currently masks these underlying infrastructural and technological deficits. These findings contribute to rural tourism management by demonstrating that small hotels need context-specific marketing strategies rather than copying big-city models. The study underscores the importance of targeted facility upgrades, digital transformation, and staff retention. By providing a practical blueprint, this research offers a framework for secondary municipalities to improve competitiveness while preserving their local hospitality strengths.

Financial Literacy and Access to Finance among Small Business Owners in Ghana

Othniel Ekow Kwainoe — Sat, 08 Aug 2026 00:00:00 +0000

This study examines the relationship between financial literacy and access to finance among small business owners in Ghana. Financial literacy was measured through items on budgeting, cash-flow management, interest, financial statements, borrowing costs, insurance and investment risk. A simulated dataset of 242 small businesses was analysed using descriptive statistics, correlation, multiple regression and binary logistic regression. The results indicate moderate financial literacy, with stronger knowledge of budgeting and cash-flow management than insurance and borrowing-cost calculations. Financial literacy significantly predicted access to finance after controlling for business age, size, registration, owner education and financial record-keeping (β = .431, p < .001). Among loan applicants, a one-unit increase in financial literacy more than doubled the odds of approval (OR = 2.203, p < .001). Financial records and collateral also improved approval prospects, while high interest rates and complex documentation remained barriers. The study shows that financial education should be combined with record-keeping support and more accessible lending procedures. Given the cross-sectional design, limited national representativeness and reliance on self-reported financing outcomes, the findings should be interpreted cautiously, and future research should use longitudinal data and lender records while examining regional and sectoral differences.

Artificial Intelligence and Banking Transformation: A Global Critical Narrative Review of Value Creation, Risk and Governance

Mesud Mohammed, Gurudutta Japee — Fri, 07 Aug 2026 00:00:00 +0000

Artificial intelligence has moved from specialised analytical support to a strategic infrastructure for banking, yet evidence of transformation remains more uneven than the prevailing innovation narrative suggests. This critical narrative review examines how artificial intelligence is changing bank operations, customer interfaces, credit allocation, fraud control, organisational capabilities, competitive structure and prudential governance across advanced and emerging economies. Live literature searches covered publications from 1 January 2000 to 31 May 2026, supplemented by necessary foundational material and authoritative regulatory sources. The synthesis distinguishes improvements in prediction from changes in decision rights, processes and business models. Evidence is strongest for narrowly specified applications, including credit-risk estimation, transaction monitoring, fraud detection and selected service tasks. Even in these domains, gains depend on data quality, class imbalance, concept drift, implementation architecture and the cost of false decisions. Evidence that artificial intelligence reliably raises bank-level productivity or profitability is newer and contradictory: recent studies report positive effects in some Chinese samples, whereas United States patent evidence indicates improved asset quality alongside higher short-run operating costs and weaker profitability. Customer-facing and generative systems extend transformation beyond prediction, but their benefits are constrained by hallucination, privacy, cyber-security, explainability and accountability requirements. Alternative data may widen access to formal finance, yet can also reproduce exclusion through proxy discrimination and opaque segmentation. At system level, common vendors, correlated models and automated responses may create concentration and procyclical feedback. The review argues that artificial intelligence should be treated as a socio-technical and institutional transformation rather than a stand-alone technology investment. Durable value requires complementary changes in data governance, workforce design, model-risk management, procurement, consumer redress and supervisory capacity. Future research should prioritise causal, longitudinal and cross-country designs, distributional outcomes, production-scale model monitoring and measurable links between governance controls and financial performance.