Advance Journal of Econometrics and Finance
The Advance Journal of Econometrics and Finance is a valuable resource for economists, finance professionals, and students alike. This journal provides an up-to-date analysis of the latest economic trends, data, and research from around the world. It also covers topics such as asset pricing, financial engineering, macroeconomics, and microeconomics. With its comprehensive coverage of the field of econometrics and finance, this journal is an invaluable source for anyone looking to stay informed on the latest developments in this field.
SDGs Washing vs Genuine Innovation: The Mediating Role of Sustainability Innovation Authenticity and the Moderating Role of Stakeholder Pressure
This study addresses the rising issue that firms may publicly align with the SDGs while lacking authentic sustainability innovation, thereby creating a gap between corporate sustainability claims and substantive organizational practices. Thus, this study examines the twofold consequences of corporate sustainability practices by distinguishing between genuine innovation and SDG washing. It also examines how sustainability innovation authenticity mediates the relationship and stakeholder pressure moderates it, offering critical insight into the effectiveness of corporate sustainability initiatives. A quantitative research design was adopted, in which primary data were gathered from 450 managers and sustainability professionals in the Pakistani textile industry. A purposive sampling technique was used to target firms engaged in sustainability practices. Partial Least Squares Structural Equation Modeling (PLS-SEM) was applied to test the mediation and moderation relationships. Corporate sustainability practice can have two outcomes: a huge improvement in both authentic innovation and SDG washing. The authenticity of sustainability innovation is the most critical mediating factor, as it enables sustainability innovation and reduces SDG washing. Moreover, the relationship between sustainability practices and authenticity is strengthened through stakeholder pressure, which can motivate companies to take more substantive actions regarding sustainability. This study is relevant to the literature because of its critical analysis of companies' sustainability practices, which goes beyond perceived advantages. The study introduces the concept of sustainability innovation authenticity as a key mechanism for differentiating between substantive and symbolic practices, integrating Institutional Theory and Legitimacy Theory. The results would be beneficial for researchers and practitioners who want to build more effective and credible sustainability initiatives
Copyright (c) 2026 Advance Journal of Econometrics and Finance
How Do Crude Oil Prices, Exchange Rates, Gold Prices, and Interest Rates Impact Inflation in Pakistan?
The purpose of this study is to examine the macroeconomic factors driving inflation in Pakistan from 1990 to 2024, particularly the effects of crude oil prices, exchange rate devaluation, gold prices, and interest rate changes on inflation. The study uses a Structural Equation Model (SEM) to examine the direct and indirect effects of global commodity prices and monetary conditions on domestic prices. To capture large external regime changes, two binary structural dummy variables are included: a COVID-19 shock dummy (2019–2021) and a Russia-Ukraine geopolitical tension dummy (2022–ongoing). Money supply growth and trade openness are among the control variables. Based on annual data from the World Development Indicators (WDI), International Financial Statistics (IFS), and the State Bank of Pakistan (SBP), the SEM path analysis indicates that the two largest direct influences on inflation are the interest rate and the exchange rate. The positive effects of crude oil on the exchange rate and gold prices have a strong indirect impact on inflation. The other significant and negative factor is trade openness, which indicates the import-cost channel. The structural dummies have mixed coefficients, indicating that policy interventions during the crisis period suppress inflationary pressures in both cases. The findings confirm the preeminence of external macroeconomic variables in determining inflation in Pakistan and offer some empirical lessons for policy.
Decentralized Digital Wallets in Pakistan and the UK: Leveraging Blockchain for Secure, Low-Cost Cross-Border Payments and Financial Inclusion
This study explores the role of decentralized digital wallets and blockchain technology in enhancing cross-border payments and financial inclusion, with a focus on Pakistan and the UK. Through semi-structured interviews with 22 participants, including banking professionals, fintech experts, and users of digital wallets, the study examines the benefits, challenges, and potential of blockchain in both developed and developing economies. The findings reveal that while blockchain has the potential to reduce transaction costs and improve the security of cross-border payments, significant differences exist in perceptions and trust between Pakistan and the UK. Participants from the UK demonstrated higher trust in blockchain technology due to a more developed financial ecosystem, while participants from Pakistan expressed concerns about security, regulatory uncertainty, and limited financial literacy. The research highlights the need for improved financial literacy, regulatory clarity, and infrastructure development to foster the adoption of decentralized digital wallets in Pakistan. The study also provides valuable insights into the potential of blockchain to drive financial inclusion in emerging markets. Keywords: Decentralized Digital Wallets, Blockchain Technology, Cross-Border Payments, Financial Inclusion, Emerging Markets
Does Financial Inclusion Outcome is Supporting Formal Borrowing among Individuals
This study examines whether financial inclusion outcomes support formal borrowing in South Asia using Global Findex microdata for 2,591 adults who reported borrowing. Formal borrowing is the dependent variable, while bank account ownership and mobile money account ownership are the main inclusion indicators. Logit models are estimated for the full sample and across gender and urban–rural groups. The results show that bank account ownership is strongly and consistently associated with a higher likelihood of formal borrowing. Mobile money accounts also support formal borrowing, but the effect is weaker and more evident among men and urban residents. Age, income, labour force status and country context further shape borrowing outcomes. Overall, financial inclusion promotes formal borrowing, but access alone is not sufficient. Policies must strengthen enabling conditions so that inclusion translates into meaningful engagement with regulated credit.
Secure Smart Contract Engineering and Software Development Practices for Resilient FinTech Blockchain Systems
FinTechs have been moving to blockchain to automate financial processes, enhance auditability, and decrease the use of manual intermediaries. Smart contracts make this automation possible, by encoding business rules into executable code, but their design flaws, lax secure coding discipline and limited organizational readiness can turn automation into systemic risk. The paper will explore the role of smart contract security engineering, software development maturity in ensuring secure and scalable blockchain implementation in FinTech. The study combines the principles of Secure Software Development Life Cycle (SSDLC) with the principles of Technology-Organization-Environment (TOE) perspective and empirically tests the offered model with the help of quantitative, cross-sectional design. Data are gathered among professionals involved in FinTech and software development practices in Pakistan and evaluated with the help of Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings indicate that maturity of software development has the highest level of association with blockchain adoption and implementation success ( 0.75), followed by technology department capability ( 0.40) and security engineering and scalability readiness reinforce overall architectural maturity and mitigate exposure to cyber risk. Model analysis shows that it was adequately fitting (SRMR = 0.09) with moderate explanatory power on the outcome construct (R 2 = 0.66). The results have shown that resilient FinTech blockchain systems rely not only on the underlying blockchain platform, but also on disciplined engineering processes and institutional capability. Future research can build on the framework by including behavioral and governance variables and testing the model in various regions to enhance generalizability.
Smart Contract Engineering, Fintech Software Engineering, Blockchain Security, Secure SDLC, Technology–Organization–Environment, Scalability Engineering, Cyber Risk, Secure Software Development Practices
Digital Transformation in KSA: Assessing the Adoption of Blockchain and Smart Contracts under Vision 2030
Background: Within the framework of Saudi Arabia’s Vision 2030, the Kingdom is prioritizing digitalized citizen services, including secure e-government payment systems. However, adoption rates remain suboptimal due to factors related to user trust and technological familiarity. Hypothesis: This research tests the implications of blockchain-enforced identity management, smart contracts, and cybersecurity protocols on e-government payment adoption through the mediating role of perceived security of digital transactions. Methods: A quantitative study using structural equation modeling (SEM) in SmartPLS 4 was conducted with a sample of 500 Saudi Arabian citizens. Constructs were tested in terms of reliability, validity, and the mediation effect. Findings: Smart contract implementation had the most significant direct impact on adoption, followed by blockchain identity and cybersecurity protocols. Perceived security acted as a partial mediator in the adoption of smart contracts. The model demonstrated significant predictive power. Conclusion: Technological innovation alone is insufficient for mass adoption; it must be coupled with user trust. The study highlights that perceived security is the critical mechanism translating FinTech infrastructure into citizen adoption. These insights offer actionable guidance for policymakers and developers tasked with realizing the digital governance goals of Vision 2030.
From Control to Credibility: How Digital Marketing and Strategic Project Management Expose or Mask Organizational Hierarchies
Organizational failure is mainly a human phenomenon as opposed to technological. This paper explores the structural processes by which dysfunctional internal hierarchies trigger organizational decay, especially how digital marketing behaviors mask, but do not fix, dysfunction, and how Strategic Project Management (SPM) is a tool of organizational visibility. Using a mixed-methods design, involving 35 organizations during 18 months (January 2025 March 2026), survey data of 102 professionals, and in-depth interviews of 45 organizational heads, this study proves that 68 per cent of project failures can be explained by internal political factors, namely, favoritism, resources hoarding, and talent suppression, with only 32 per cent Companies that had a high Hierarchy Transparency Index (HTI) score (more than 70) had a 78 percent project success rate, retained 89 percent of high performing talent in a three-year horizon, and had 12.4x digital marketing returns on investment. Low-HTI organizations (less than 50) on the other hand had a 41 percent project success rate, retained talent at only 34 percent and a paltry 3.2 times marketing ROI. To describe the four steps between improper leadership appointment and organizational degeneration, a theoretical model is proposed, which is called the Insecurity Cycle. The paper also suggests two practical tools as the Hierarchy Transparency Index (HTI) and Equity-Led Governance Model to assist in diagnostic and corrective action of the organization. The results of the exemplar organizations (Microsoft, Google, Nestle, and Unilever) validate that the transparent, fair hierarchical systems are the keystone to the credibility of the brand, the success of the project, and the long-term performance.
organizational hierarchy; strategic project management; digital marketing credibility; talent suppression; brand authenticity; insecurity cycle; hierarchy transparency index
From Industry 4.0 To Industry 5.0: The Role of Green HRM, Hybrid Work Systems, And Ethical Ai Governance in Achieving Sustainable Organizational Performance in Saudi Arabia’s Pilgrim Facilitation Sector
This study looks at how companies in Saudi Arabia that help pilgrims and tourists can perform better by going green and using smart technology. We focused on private firms in the Kingdom and asked 280 employees how they manage their teams and tech. The results are quite clear. When these companies use "Green HRM", which basically means training staff to care about the environment, they see a big jump in their overall sustainability. We also found that hybrid work models aren't just a trend; they actually help these firms stay resilient and eco-friendly by being more flexible. On top of that, using AI in an ethical way makes a huge difference. If the software used for logistics or crowd control is fair and transparent, the whole organization runs better. Essentially, if a firm wants to succeed today, it can't just focus on money. It needs to balance its people, its remote work setups, and its digital ethics all at once. By doing this, these Saudi firms are moving toward a more human-centered and sustainable future, perfectly hitting the goals of the transition from Industry 4.0 to 5.0.
Volatility Repercussion on Shariah and non-Shariah Stock Market Indices for India and Pakistan through ARCH & GARCH Techniques
The object of this paper is to examine the volatility repercussion of Shariah and non-Shariah stock market indices of India and Pakistan stock exchanges with the help of non-parametric approaches. The motivation is to examine the risk return trade off between Islamic and conventional stock market indices considering the perspective of investors portfolios. This study measures the performance of Shariah and non-Shariah stock market indices in the context of India and Pakistan stock exchanges. Collection of the secondary source data is from the period of January 03, 2011 to December 29, 2023 respectively with daily frequency. Examining the volatility of both indices for each market is checked through different techniques including risk and return analysis, ARCH and GARCH models. The results intimate that Nifty50 (Non-Shariah) index performs better than its counterparts, i.e. Nifty 50 Shariah index in the Indian stock market, whereas KMI-30 (Shariah) index outperforms to KSE-30 (non-Shariah) index in Pakistan stock exchange. Additionally, volatility repercussion for Indian market especially for Nifty50 Shariah index is high in terms of risk return trade off but Pakistan stock exchange for KMI-30 index applies the strategy of high risk and high return than its KSE-30 (conventional) index. The study could be expanded to macroeconomic variables, other capital markets particularly for Asian markets and panel studies on the selected countries. This study has practical implications particularly to investors, regulatory bodies, financial analysts and potential researchers to make comparison for the performance of Shariah and non-Shariah stock market indices in terms of risk and return trade off. This paper is the first ever study to assess volatility repercussion of Shariah and non-Shariah stock market indices in the context of India and Pakistan stock exchanges.
Socioeconomic Determinants of Female Educational Attainment in Pakistan: Stage-Specific Evidence from a Multinomial Logit Analysis
Gender disparities in educational attainment remain a defining structural impediment to human capital formation in South Asia. Despite constitutional commitments to universal schooling, Pakistan exhibits severe and cumulative female attrition across every educational transition, with tertiary participation among women among the lowest in the region. This study investigates the socioeconomic and demographic determinants of female educational attainment using nationally representative household data from the Pakistan Social and Living Standards Measurement (PSLM) Survey 2018–19 (N = 22,314 female respondents). A multinomial logistic regression framework models female educational outcomes across five hierarchical categories—primary, middle, secondary, higher secondary, and higher education—with higher education as the reference category. Six predictors are examined: age, residential region, marital status, annual household income, distance from institution, and educational expenditure. Results reveal that educational expenditure is the most pervasive barrier, exercising significant negative effects across three of four educational comparisons. Rural residence exerts an intensifying constraint that peaks at the higher secondary to tertiary transition. Household income becomes a binding and significant determinant specifically from the secondary level onward, while marital status constrains progression at the middle level only and distance matters exclusively at the tertiary threshold. These stage-specific findings carry direct implications for targeted scholarship design, rural institutional investment, and early marriage legislation in Pakistan. The 2018–19 data constitutes the most recent nationally representative provincial-level PSLM/HIES release with complete income, expenditure, and distance modules; the forthcoming HIES 2024–25 microdata will enable post-COVID comparison in future work.
Does the Marshall-Learner Condition Hold for Pakistan? Exchange Rate Elasticity, and the Long-Run Determinants of Export Earnings
Pakistan's external sector is characterised by persistent current account deficits, chronic exchange rate pressure, and a structurally narrow export base that has failed to keep pace with regional competitors over four decades. This study examines the short-run and long-run macroeconomic determinants of Pakistan's export earnings over the period 1976–2019, focusing on four theoretically motivated drivers: the nominal exchange rate (ER), foreign direct investment (FDI), domestic inflation (INF), and real GDP per capita growth (GDP). Annual time-series data from the World Development Indicators are analysed using the Autoregressive Distributed Lag (ARDL) bounds testing approach to cointegration (Pesaran et al., 2001), supplemented by an error correction model (ECM), pairwise Granger causality tests, and a full suite of residual diagnostics including serial correlation, heteroskedasticity, and CUSUM parameter-stability tests. The bounds test yields an F-statistic of 11.330, far exceeding the 1% upper critical bound, establishing a robust long-run cointegrating relationship. Long-run estimates show that exchange rate depreciation is the dominant driver of export earnings, with an elasticity of 1.521 — a finding consistent with the Marshall-Lerner condition holding for Pakistan over the full sample. Inflation enters positively but modestly, reflecting the nominal exchange rate transmission channel. FDI and GDP are individually insignificant in the long run, a result attributed to the sectoral concentration of FDI in Pakistan's non-tradable infrastructure and energy sectors. A novel finding is the oscillating short-run FDI dynamic — positive contemporaneously, negative at lags one and two, and positive again at lag three — consistent with an investment gestation period in which newly committed FDI initially draws in capital-goods imports before activating export capacity. The ECT coefficient of −0.388 implies adjustment toward equilibrium at approximately 39% per annum. Granger causality is bidirectional among exports, the exchange rate, FDI, and GDP, confirming the interconnected and self-reinforcing character of Pakistan's external sector. Inflation is causally exogenous to all trade variables. The findings carry direct implications for exchange rate management, FDI targeting policy, and export diversification strategy in Pakistan.
Technological Innovation in FinTech and Its Role in Advancing Financial Inclusion: A Comprehensive Literature Review
Financial technology (FinTech) has significantly transformed the structure and delivery of modern financial services by introducing innovative digital solutions that improve accessibility, affordability, transparency, and operational efficiency within financial systems. Over the last decade, technological advancement has accelerated the digitalization of banking, lending, payments, investment management, and insurance services across developed and developing economies. Innovations such as mobile banking, digital wallets, blockchain systems, artificial intelligence, cloud computing, and big data analytics have changed the way individuals and businesses interact with financial institutions and financial markets (Arora, 2024; Chang et al., 2024). that enhance access to financial services, especially for underserved and financially excluded populations. This literature review critically examines the relationship between technological innovation in FinTech and financial inclusion by synthesizing contemporary academic and policy-oriented literature. The review explores major FinTech technologies including digital payments, blockchain, artificial intelligence, big data analytics, mobile banking, cloud computing, and open banking systems. It further evaluates theoretical foundations such as the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), Innovation Diffusion Theory, and the Technology–Organization–Environment (TOE) framework. The review identifies how FinTech innovations improve accessibility, affordability, efficiency, and convenience of financial services while simultaneously creating new challenges related to regulation, cyber security, digital literacy, consumer protection, and digital inequality. The findings reveal that FinTech significantly contributes to financial inclusion through digital payment systems, mobile money, digital lending, peer-to-peer financing, crowd funding, and AI-driven credit scoring models. However, the benefits remain uneven due to socioeconomic, geographic, gender, and technological disparities. The study adopts a systematic literature review methodology by analyzing peer-reviewed journal articles, policy reports, conference papers, and institutional publications related to FinTech and financial inclusion. Findings suggest that supportive regulatory frameworks, improved digital infrastructure, financial literacy programs, and collaborative ecosystems among governments, financial institutions, and technology firms are essential to maximize inclusive financial outcomes.
An Analysis of the Macroeconomic, Structural, and Institutional Factors Affecting Tax Revenue in Pakistan: Evidence from an ARDL Model
This paper investigates the key macroeconomic, structural, demographic and institutional determinants of Pakistan's tax-to-GDP ratio. The country continues to be financially constrained despite being relatively under-taxed, thus warrants a closer inspection of the tax determinants for the country. This research is followed time series data over the years from 1990 to 2024 was used in the study. The study employed the popular Autoregressive Distributed Lag (ARDL) bounds testing methodology to test for the presence of a long-run relationship and short-run dynamics among the series. The unit root tests indicate mixed levels of integration among the variables thus validating the use of the cointegration bounds test approach in the context. The study made three models to avoid the multicollinearity issues among variable. This allows the study to understand macroeconomic, structural and institutional factors. From the bounds test, the research found that there is a long-run relationship in all models. In the long run, levels of per capita income, level of democracy, inflation, control of corruption, labor force, male labor force and urbanization and have impacting positively on tax-to-GDP ratio. While the agriculture share in GDP, age dependency ratio and income inequality have negative effects. In the short run, the variables display persistent effects with adjustment to the long run. The diagnostic and stability tests indicate efficiency and stability of the models. The findings imply that strengthening the institutional framework, pursuing structural macroeconomic policy initiatives, and expanding the urban formal sector can help improve the country's tax potential in the long run. JEL Classification: H20; H26; E62; O23; C22.
Effect of the Role of Institutions and Exchange Rate Volatility on Tax Revenue in Pakistan
Pakistan has been one of the fragile economies facing the danger of default after events like COVID-19, post COVID-19 developments, Russia and Ukraine war. Ever-rising debt and soaring public expenditure (mainly interest payments) have almost made it impossible for the country to run day-to-day business. The root of this agony lies in the low level of tax revenue by the government. Tax collection performance has been dismal in case of Pakistan and exchange rate volatility has added to the misery of Government. By employing ARDL and measuring exchange rate volatility through standard deviation the current study found the role of exchange rate volatility to be significantly damaging the tax collection efforts. This damaging effect can be marginalized by better institutional performance. The study suggests steps should be taken to address volatility and improve the institutional performance so that the Government will be able to collect more revenue and avoid danger of default and have enough resources to spend on education and health.
Copyright (c) 2024 Advance Journal of Econometrics and Finance
An Examination of Artificial Intelligence and Risk Management in Financial Institutions
Artificial Intelligence (AI) has transformed the operations of financial institutions by improving efficiency, accuracy, and decision-making processes in risk management. Financial institutions such as banks, insurance companies, and investment firms increasingly use AI technologies to identify, assess, monitor, and control financial risks. This study examines the relationship between artificial intelligence and risk management in financial institutions. The article explores how AI technologies including machine learning, predictive analytics, natural language processing, and automation contribute to fraud detection, credit scoring, cybersecurity, regulatory compliance, and operational risk management. The study also investigates the challenges associated with AI adoption such as ethical concerns, algorithmic bias, data privacy, transparency, and regulatory issues. A qualitative research methodology based on secondary data analysis has been adopted to examine recent literature, case studies, and reports related to AI applications in finance. The findings indicate that AI significantly enhances the speed and accuracy of risk assessment while reducing operational costs and human errors. However, the absence of clear regulatory frameworks and ethical governance creates challenges for financial institutions. The study concludes that AI has become an essential tool for modern risk management practices, but organizations must develop balanced strategies that combine technological advancement with ethical and regulatory considerations. The research contributes to understanding the growing role of AI in financial risk management and provides recommendations for future implementation and policy development.
Artificial Intelligence, Risk Management, Financial Institutions, Machine Learning, Fraud Detection, Financial Technology, Cybersecurity, Predictive Analytics, Banking Sector, Automation
Corporate Responsibility and Organizational Culture as Strategic Drivers of Employee Commitment: Evidence from Riyadh’s Destination Management Companies
Riyadh’s tourism sector undergoes rapid transformation. This study investigates the critical drivers of workforce loyalty within Destination Management Companies (DMCs) in Saudi Arabia. Specifically, the research examines the impact of Corporate Social Responsibility (CSR) and Organizational Culture on Organizational Commitment. Global competition for talent necessitates a deeper understanding of these variables. The study employed quantitative, cross-sectional survey design. Exactly 160 professionals operating in Riyadh’s DMC sector provided primary data. The methodology utilized established, validated academic scales and processed the results through multiple regression analysis in SPSS. The empirical results reveal a profound shift in management dynamics. The research identifies Corporate Social Responsibility as the dominant predictor of employee loyalty. The regression model explains exactly 78.6% of the variance in commitment levels. Statistical testing confirms a massive, positive relationship between social signaling and workforce dedication (B = 0.879, p < 0.001). Conversely, the analysis officially rejects the independent significance of Organizational Culture (p = 0.100). These findings suggest that for Saudi tourism workers, external ethical corporate behavior carries significantly more weight than internal workplace norms. The study concludes that DMCs must prioritize high-visibility social initiatives to secure long-term talent retention. The research delivers urgent strategic recommendations for executives navigating the Vision 2030 economic expansion.
Ownership Structure, Audit Quality, And The Governance–Performance Nexus: Dynamic Panel Evidence
The study explores how corporate governance systems and quality of audit affect firm performance in an emerging market using a non-financial listed company in the Pakistan Stock Exchange (PSX). The article, based on the agency theory and complementary governance frameworks, investigates the impact of board properties, ownership structure, audit committee properties, and composite governance indices on firm performance in terms of Return on Assets (ROA), Return on Equity (ROE), and Tobin, Q (TQ). It uses an unbalanced panel sample over a series of years and uses a Fixed Effects (FE) regression and dynamic two-step System Generalized Method of Moments (System GMM) estimator to overcome the advantages of unobserved heterogeneity, endogeneity, and dynamic persistence of firm performance. Pre-estimation diagnostics verify the stationarity, absence of extreme multicollinearity and endogeneity thus justifying the use of System GMM. Empirical evidence has shown that the independent board, board diversity, ownership concentration, audit committee independence and expertise, audit quality, and the overall corporate governance quality has a positive and statistically significant effect on the performance of the firm. On the other hand, CEO duality is significantly and persistently negatively linked to all performance measures, indicating the negative impact of managerial concentration. The findings of dynamic GMM also support performance persistence and support the soundness of the findings with standard post-estimation tests, such as Arellano-Bond and Hansen tests. Moreover, interaction studies indicate that strong corporate governance enhances the performance advantages of ownership structure and audit quality. The findings provide comprehensible evidence that good governance and good quality auditing are critical determinants of firm performance in Pakistan. The research, therefore, provides germane implications to regulators, policymakers, and corporate executives seeking to strengthen governance systems and increase the value of firms in emerging economies.
FinTech Adoption under Perceived Risk: The Mediating and Moderating Role of Trust, Usefulness, and Digital Literacy
The rapid expansion of financial technologies (FinTech) has transformed financial service delivery; however, user adoption remains uneven in emerging economies where concerns related to security, trust, and digital capability persist. Addressing this gap, this study investigates how risk perception influences behavioral intention to adopt FinTech services by integrating the Technology Acceptance Model (TAM) and Protection Motivation Theory (PMT). Specifically, the study examines the mediating roles of trust and perceived usefulness, alongside the moderating role of digital literacy, to explain users’ adoption intentions under conditions of perceived risk. The proposed model is tested using survey data collected from 410 banking customers in Pakistan through structural equation modeling (PLS-SEM). The findings reveal that risk perception exerts a significant negative effect on behavioral intention. However, this relationship is partially mediated by trust and perceived usefulness, indicating that users cognitively and relationally process perceived risk before forming adoption intentions. Furthermore, digital literacy significantly moderates the risk intention relationship, weakening the deterrent effect of perceived risk among more digitally competent users. This study advances FinTech adoption by integrating threat appraisal and benefit evaluation mechanisms into a unified framework, extending both TAM and PMT. The findings offer actionable insights for policymakers and FinTech providers seeking to enhance trust, promote digital capability, and foster inclusive digital financial adoption in emerging economies. FinTech adoption, Risk perception, Behavioral intention, Trust, usefulness, Digital literacy.
Impact of Net Export on Gross Domestic Product (GDP) of Pakistan
This study analyses the effects of net exports upon Pakistan's GDP with an analysis of annual time-series data covering 1978 to 2017. The dependent variable will be GDP in this research with exports, imports, gross fixed investment, Government expenditure, interest paid on external debt and Private consumption representing the independent variables. The ADF unit root test results indicated that the variables are stationary primarily at first differencing which allows the ARDL approach to be employed. The ARDL bounds test provided evidence of long run cointegration between the variables through a F-statistic of 5.080 which was above the 5% upper bound (3.61). Long run results indicated that exports have a positive influence on GDP; (β=0.1735; p<0.001) alongside a positive effect from gross fixed investment (β=0.1862; p<0.001), government expenditure (β=0.1740; p<0.001) and private consumption (β=0.9041; p<0.001). Imports were found to have a negative impact upon GDP (β=-0.2735; p<0.001) whilst interest paid on external debt also has a negative affect (β=-0.0272; p=0.020). The short run results were also found to be significant with an ECM coefficient of negative significance (β=-0.9989; p<0.001) confirming that adjustments to long-run equilibrium occur rapidly. This study recommends the promotion of export activity through improved productivity; increased levels of productive investment; and an emphasis on the importation of capital goods as means of achieving such growth in exports and GDP. Keywords:Gross domestic product, time series, trade balance, cointegration
Do Remittances Promote or Constrain Growth? Evidence from South Asian Economies
This study examines the remittance–growth nexus in Pakistan, India, Bangladesh, and Sri Lanka over 1980–2015 using a panel ARDL model with Pooled Mean Group (PMG) estimation. The approach captures both short-run dynamics and long-run relationships while allowing for cross-country heterogeneity. Results indicate that a 1% increase in remittances is associated with a 1.38% decline in long-run GDP growth. Dumitrescu–Hurlin tests show no bidirectional Granger causality, suggesting remittances operate largely outside the productive economy. In contrast, foreign direct investment and exports have positive and significant long-run effects. Short-run impacts are heterogeneous—positive in Pakistan, negative in Bangladesh, and insignificant in India and Sri Lanka. Overall, the findings support dependency and Dutch disease perspectives, highlighting the need to channel remittances toward productive investment through financial and institutional reforms. Keywords: Remittances; Economic Growth; South Asia; Panel ARDL; Pooled Mean Group; Dutch Disease
Credit Risk and Bank Performance in Emerging Markets. A Dual Protocol Systematic Review with Evidence from Pakistan
This paper sets forth the methodological framework of a systematic literature review investigating the link between credit risk management and bank performance, with a special emphasis on emerging markets and the Islamic banking system within Pakistan. Based on the PRISMA 2020 reporting protocol (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), the literature review process extracted evidence from the initial 1350 identified literature databases, identifying 247 relevant studies after a detailed process of screening and deduplication. An update performed in 2025 and based on an integrative narrative strand, led to a final evidence base of 281 studies, with a chronological scope from the earliest model of credit risk measurement, the Altman Z-score model of 1968, to the use of machine learning techniques in the area in the latest period. This methodology merges systematicity and contextual sensitivity, utilizing Zotero reference management software to support deduplication, thematic labeling, and structured data extraction organized around 6 key themes: credit risk measurement techniques; the relationship between bank performance and risk; macroeconomic influences on the same topic; Islamic banking perspective; institutional specific studies focused on Pakistan; and technical/methodological developments in this topic. Quality assessment was applied along three aspects: technical/methodological robustness, context relevance, and influence in the academic field, adopted from existing management-related systematic review frameworks. This document specifies methods to account for publication bias, geographical bias, conceptual bias, researcher bias, and integrative bias. With documentation of the systematic literature search, selection criteria, screening process, quality assessment methodology, and theme extraction strategy, this paper contributes to the debate over the adaptability of medical systematic review methodologies to a context of information retrieval specific to banking and finance research.
Forecasting Pakistan Stock Returns Using Economic Policy Uncertainty: Deep Learning Evidence from an Emerging Market
Accurate forecasting of stock returns remains a persistent challenge in financial economics, particularly in emerging markets characterized by policy uncertainty, macroeconomic volatility, and evolving institutional structures. Pakistan offers a relevant setting due to recurring political transitions, inflationary pressures, exchange rate instability, external financing constraints, and periodic policy shifts that frequently influence investor sentiment and market behavior. This study examines whether Economic Policy Uncertainty (EPU) improves the forecasting of Pakistan stock returns and whether advanced deep learning models outperform conventional econometric approaches. Using monthly data from 2010 to 2024, traditional benchmark models, including ARIMA, GARCH, and ARDL, are compared with modern deep learning architectures comprising Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), CNN-LSTM, and Transformer models. Forecasting performance is evaluated using root mean squared error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). The empirical findings show that incorporating EPU significantly enhances predictive accuracy across competing models, confirming the informational relevance of policy uncertainty for financial markets. Deep learning models consistently outperform benchmark econometric models, indicating the presence of nonlinear, dynamic, and time-varying relationships in Pakistan’s stock market. Among all competing approaches, Transformer and CNN-LSTM models deliver the strongest forecasting performance, with gains becoming more pronounced during crisis periods, including COVID-19-related disruptions and episodes of macroeconomic stress. The study contributes new evidence from an underexplored emerging market and demonstrates the value of integrating uncertainty indicators with modern artificial intelligence techniques for financial forecasting. The findings provide practical implications for investors, regulators, and policymakers seeking to strengthen decision-making, risk management, and market monitoring under uncertain economic conditions.
Internal Control Effectiveness as a Moderator in the Relationship Between Corporate Social Responsibility and Firms' Financial Performance: Evidence from Pakistan
Corporate Social Responsibility (CSR) has become a decisive strategic issue in companies in developing economies but its nexus with financial performance is still the matter of continuous empirical discussion and especially in the institutional sphere of weak governance structures, unclear regulations and heterogeneous stakeholders. This paper explores the moderating position of internal control effectiveness in the connection among multi-dimensional CSR and financial performance of firms in the Pakistani corporate environment. Based on a synthesized theoretical context, rooted in the Stakeholder Theory, Legitimacy Theory, Agency Theory, Social Contract Theory, and Environmental Theory and supported by Resource-Based View (RBV) and Institutional Theory, the research hypothesis is that the strong offices of internal control enhance the CSR-performance connection through quality of governance, transparency, and optimization of resources. The proposed study will have a mixed-method quantitative design which involves the use of both primary and secondary data. The structured questionnaire surveys conducted on a five-point scale (likert scale) were used to measure firm level practices of CSR across seven theoretically based dimensions: Economic, legal, ethical, philanthropic, environmental, stakeholder and governance as a primary source of data. Two globally accepted compliance framework networks were used to operationalise the internal control effectiveness: the Committee of Sponsoring Organizations of the Treadway Commission (COSO) framework and the Sarbanes-Oxley Act (SOX) compliance indicators. To create three performance proxies of financial performance Return on Assets (ROA), Return on Equity (ROE) and the Q ratio of Tobin, which reflects accounting-based and market-based aspects of performance, secondary data were obtained through audited financial statements and Bloomberg databases. Four control variables at firm level are included: the size of firms, the age of firms, financial leverage, and high levels of research and development (R&D). The sample includes non-financial Pakistani companies that belong to the Pakistan Stock Exchange (PSX) during [202025]. The hypothesized relationships are tested using moderate regression analysis (hierarchical with moderated) with the help of panel data methods, such as fixed-effects and random-effects. Two-Stage Least Squares can resolve the endogeneity issues. (2SLS) estimation. The empirical evidence indicates that: (i) the CSR dimensions are positively and differentially related to the financial performance; (ii) internal control effectiveness positively mediates the CSR-financial performance relationship, which supports the governance-sustainability nexus. (iii) The size of the firm, leverage, age and R&D all play a significant role in determining the strength of this relationship in the Pakistani institutional environment. This research has taken part in the emerging yet developing literature on CSR in the South Asian emerging markets by offering the first work of exhaustive empirical analysis of internal controls as a boundary to the CSR performance relationship. The results have important policy and regulatory implications to corporate boards, regulators, and investors in Pakistan, guiding the design of CSR mandates, governance codes enforced, by the Securities and Exchange Commission of Pakistan (SECP), and the internal audit standards that comply with international best practice. Keywords: Corporate Social Responsibility (CSR); the Internal Control Effectiveness; Financial Performance; COSO Framework; SOX Compliance; Return on Assets; Return on Equity; Tobins Q; Stakeholder Theory; Legitimacy Theory; the Agency Theory; the Social Contract Theory; the Environmental Theory; the Institutional Theory; the Resource-Based View; the Pakistan Stock Exchange; the Emerging markets, the Corporate Governance
Corporate Social Responsibility (CSR), Consumer Trust, and Financial Performance: A Triangular Model of Management–Marketing–Finance Integration
This study examines the relationship between Corporate Social Responsibility (CSR), consumer trust, and financial performance within an integrated management, marketing, and finance framework. As organizations increasingly invest in CSR initiatives, understanding their impact on consumer behavior and financial outcomes is essential. A quantitative, cross-sectional design was employed, with data collected from 300 consumers familiar with CSR activities using a structured questionnaire. The proposed mediation model was analyzed using Structural Equation Modeling (SEM) and bootstrapping techniques. Results indicate that CSR significantly enhances consumer trust (β = 0.514, p < 0.001), which in turn positively influences financial performance (β = 0.478, p < 0.001). Furthermore, consumer trust partially mediates the CSR–financial performance relationship, with an indirect effect (β = 0.246) accounting for 52.8% of the total effect (β = 0.466). These findings validate a triangular model linking behavioral and financial outcomes and offer practical insights for leveraging CSR to achieve sustainable performance. Keywords: CSR, trust, financial performance, consumer behavior, sustainability, SDGs, marketing.
Exploring the Impact of Digitalization on Economic Growth: Evidence from Emerging Markets
Digitalization has emerged as a critical driver of economic growth in emerging markets yet its causal mechanisms remain underexplored amid infrastructure gaps and digital divides. This study employs Panel ARDL-ECM analysis on 25 emerging economies (2010-2026) including Pakistan, India and Brazil to examine digitalization's impact on GDP growth. Findings reveal a robust long run elasticity of 1.45a one standard deviation increase in the Digitalization Index (DI) yields 1.45% higher GDP growth, with human capital index (HCI) moderating effects (0.89). Error correction term (-0.38) indicates 1.8-year adjustment half life while digital divides elevate unemployment by 0.67%. Pakistan exhibits transitional dynamics (1.22 elasticity, 2.8 year half life) due to infrastructure constraints. Robustness via GMM-SYS, quantile regression and regional heterogeneity confirms leapfrogging potential for laggards. Results validate digitalization as an economic "preservation coating" against stagnation, urging infrastructure investments and literacy campaigns.Simulations using policy models predict a cumulative 2.5% increase in real GDP due to greater than 10% DI improvements. Digital transformation is necessary to realise the trillions of dollars of potential in many emerging markets (EM’s).
The Practical Application Of Hedge Accounting Under Ifrs 9 And Its Impact On Financial Reporting
Background: The study aims to review the practical applications of hedge accounting IFRS 9 to understand its impact financial reporting. Hedge accounting gives a clear idea that how the true economic risk management is possible based on the currency interest rates and commodity price rates. The role of the profit and loss is a prominent parameter in this context. It also demands for the risk management to reveal the handling based on currency market dealing for highly effectiveness on financial tools. Method: The study employs a mixed method where primary data is taken from the respondents’ sample of 150 samples. 4 hypotheses are justified and proved in the end. Smart PLS is employed in this regard to help the data analysis. Secondary data is taken from the literature and supports the thematic analysis for research questions to be answered. Findings: The hedge accounting affects the income statements and equity where the balance sheets are also influenced because accurate representation of financial performance is based on the perspective of handling hedge accounting as an accountable and important system. Recommendations: Training the accounting professionals about IFRS 9 and using effectiveness testing is playing an essential role in handling the challenges of financial risks are recommended.
China's Belt and Road Initiative: Opportunities and Challenges for Renewable Energy Cooperation
China's Belt and Road Initiative (BRI) transformed global renewable energy cooperation delivering 73 GW operational capacity across 68 countries by 2026Q142.1% of $141.8B energy portfolio versus coal's 18.2% post 2021 Xi coal halt. Staggered difference in differences analysis (N=2,847 projects) confirms +23.1 GW BRI treatment effect (p<0.01) with green public procurement (GPP) mediating 47.2% of impact. PV prevents (42.3 GW, 3.8¢/kWh LCOE, 14.2% IRR) $18.4B of annual imports, creates 329K jobs, and reduces CO₂ emissions by 187 MT. There are regional disparities with MENA leading & achieving 87% (UAE at record 1.35¢/kWh) while Pakistan struggles from grid constraints (8.2% curtailment, $140M in losses). 45.3% of local content is achieved through technology transfer by training 42,000 technicians at 12 technical training academies. Integrating VRE at 42% penetration (780 MW/min ramp rate) results in BESS (Battery Energy Storage Systems) mandates of four hours. Phase III scenarios project 302-532 GW by 2040 ($184-324B savings) through GPP scaling green RMB bonds hybrid storage. BRI redefines South to South cooperation, positioning China as Global South decarbonization anchor despite debt distress grid fragility challenges.
Impact of Financial Development and Trade Liberalization on Total Factor Productivity: Evidence from Export and Non-Export Firms of Pakistan
This paper examines the impact of financial development, trade liberalization and corporate tax on Total Factor Productivity (TFP) of the export and non-export industrial firms listed over the Pakistan Stock Exchange. The analysis used data for the post liberalization period from 1997 to 2017 using System Generalized Method of Moments (Sys-GMM). We used three proxies for financial development to analyze their impact on TFP. The Financial Development Index and Financial Institution Depth Index that capture multidimension effect had significant positive impact on TFP of both the export and non-export firms, however, the impact is stronger in case of exporting firms. Besides, trade liberalization proxied by average tariff rate, customs duty and sales tax, the results are statistically significant. The reduction in average tariff rate exerted positive impact on TFP for exporting firms while negative for non-export firms. The impact of customs duty is insignificant. Reduction in sales tax exerted positive impact on TFP of export-firms while negative for non-export firms. Reduction in corporate tax asserted significant positive influence on TFP growth of exporting and non-exporting firms, however, the impact is greater for export-firms. Keywords: Financial Development, Trade Liberalization, Total Factor Productivity, Corporate Tax, Export and Non-Export Firms
Growth, Foreign Direct Investment And Environmental Outcomes In South Asian Economies
This study investigates the relationship between economic growth, foreign direct investment, energy consumption and environmental degradation in South Asian countries over the period 1997–2022. Using balanced panel data for eight countries and employing a fixed effects estimation approach, carbon dioxide emissions are used as a proxy for environmental degradation. The results provide robust evidence in support of the Environmental Kuznets Curve hypothesis, revealing an inverted U-shaped relationship between economic growth and carbon emissions. Economic growth, foreign direct investment, non-renewable energy consumption and trade openness are found to exacerbate environmental degradation, whereas renewable energy consumption significantly reduces carbon emissions. These findings suggest that economic expansion and investment-led growth in South Asia have occurred largely at the expense of environmental quality. The study highlights the importance of strengthening environmental regulations, promoting renewable energy adoption and guiding foreign investment toward environmentally sustainable activities to achieve long-term sustainable development in the region.
Economic Growth, Foreign Direct Investment, Carbon Emissions, Environmental Kuznets Curve, Fixed Effect Model.
Harnessing Solar Potential in Pakistan: A Review of Renewable Energy Policies and Future Prospects
Pakistan's chronic energy crisis, marked by 20-hour load shedding and $22B annual fossil import bills, confronts unparalleled solar potential (5.3 kWh/m²/day average irradiation). This study evaluates renewable energy policies' efficacy in harnessing 50 GW economic capacity. Findings reveal explosive growth from 885 MW (2019) to 35 GW (2026)69% of generation capacity exceeding AREP 2019 targets by 142-1,420%. Distributed solar dominated (95% capacity): 6.2 GW net metered (1.42M prosumers) and 27.1 GW off grid driven by 2.4-year payback periods amid PKR 65/kWh tariffs. AREP catalyzed transformation: net metering enabled 4.2M households GPI auctions secured 1 GW utility scale at PKR 5.5/kWh (47% furnace oil discount). Economic impacts crystallized: $22.5B import savings 1.75M jobs 50.1 MtCO₂ avoided annually. Technical excellence confirmed 79.8% performance ratios 1,780 kWh/kWp yields. Grid challenges emerged at 69% VRE penetration (780 MW/min ramps) demanding 4 GW storage by 2028. Phase II requires net billing transition, agrivoltaics mandates and HVDC corridors to scale 100 GW by 2035, positioning Pakistan as South Asia's solar superpower.