Pairwise Granger Causality Research Articles

The link between gender inequality, financial development, and economic growth in Nigeria: A spectral Granger causality approach

AbstractThe male and female genders have crucial roles to play in economic advancement. Thus, the main reason for this research is to pinpoint the causal link between gender inequality (GPIN), financial development (FIDX), inflation (INFL), and economic growth (GDPC) in Nigeria from the year 1980–2020 utilizing the Spectral Granger and Pairwise Granger causality methods and “Residual Augmented Least Square (RALS) cointegration. The RALS result show confirms the stationarity properties of the variables. The Spectral Granger causality outcomes show that GPIN granger causes GDPC in the long, medium, and short–term. In addition, the FIDX granger causes GDPC in the long and short–term, while the medium–term impact is insignificant. For INFL, causality only occurs in the long–term. On the other hand, the Pairwise Granger causality results show that GPIN and FIDX granger cause GDPC, while INFL is insignificant. Therefore, if GPIN and FIDX can predict economic expansion, policymakers need to create policies that can reduce diverse forms of inequalities, promote financial development, and reduce inflation to the barest minimum.

Asymmetric connectedness among BSE SENSEX, INR–USD exchange rate, gold price and crude oil price: fresh evidence from nonlinear ARDL

PurposeThis paper investigates the asymmetric connectedness among the Indian stock market, crude oil price, gold price and the USD–INR exchange rate.Design/methodology/approachWe construct a nonlinear autoregressive distributed lag model that contains the four aforementioned variables. We further used the pairwise Granger causality test to identify the direction of causality.FindingsThe results verify an asymmetrical long-run co-movement between the Indian stock market index, exchange rate, international crude oil prices and gold prices. In the long run, the performance of the Indian stock market is mainly affected by both positive as well as negative shocks in the INR–USD exchange rate, positive shocks in gold prices and positive shocks in crude oil prices. Further, a feedback mechanism is observed between positive shocks in the INR–USD exchange rate and Indian stock market performance.Originality/valueThe research paper revisited the linkage among the variables using a novel methodology proposed by Shin et al. (2014).

Financial Development's Role in the 2030 Sustainable Development Agenda: Asian Countries

The purpose of achieving sustainable development goals (SDGs) requires the mobilisation of finance and its alignment with sustainability principles. This study intends to examine the influence of financial development on the attainment of Sustainable Development Goals (SDGs) in an economy. Approach - The authors conduct an analysis of a sample comprising 35 Asian countries, focusing on their SDG (Sustainable Development Goals). Patterns and indicative indicators of the Sustainable Development Goals (SDGs). A probit model is used to analyse the effect of Financial development impacting the trajectory of the Sustainable Development Goals. Then, a pairwise Granger causality test is used for Examining the relationship between the Sustainable Development Goals and financial development The results suggest that there is a favourable relationship between financial development and the advancement towards the Sustainable Development Goals. The test for causation There is a reciprocal relationship between financial development and industry, infrastructure, and innovation. Enhancing financial growth and promoting sustainable cities and communities, as well as fostering financial development and taking action on climate change, There is a one-way relationship where gender equality influences financial progress. Research limitations/ramifications - The findings also have implications for the government of a nation as the privately-owned enterprises.

Determinants of environmental sustainability in the United States: analyzing the role of financial development and stock market capitalization using LCC framework

This research investigates how the USA's load capacity factor (LCF) has been impacted by trade openness, financial development, stock market capitalization, and industrialization over the period 1990–2022. This study also tests the “Load Capacity Curve (LCC)” hypothesis. Various unit root tests were conducted to determine the stationarity of the dataset, revealing that the variables are free from unit root problems and exhibit mixed orders of integration. The “Autoregressive Distributed Lag (ARDL)” bounds test confirmed co-integration among the variables. The results from the ARDL model validated the existence of the LCC hypothesis in the USA. The findings also demonstrated that industrialization is positively correlated with LCF, whereas financial development, stock market capitalization, and trade openness are negatively correlated with LCF. To ensure the robustness of the ARDL estimations, the study also employed several regressions, all of which confirmed the validity of the ARDL results. Additionally, pairwise Granger causality tests revealed unidirectional causal relationships between GDP and LCF, stock market capitalization and LCF, and industrialization and LCF, while no causal relationships were found between financial development and LCF and trade openness and LCF. The findings advocate that the USA should advance eco-friendly industrial practices to ensure environmental sustainability, alongside regulated financial markets and institutions that mandate the utilization of green investments.

Does External Debt Cause Growth? A Comparative Study Of Nigerian And South African Economies

Research Aims: The purpose of this study is to ascertain the effect of external debt on economic growth and the causal relationship that exists between external debt and growth in South Africa and Nigeria between 1981 and 2022. Design/methodology/approach: To this end, VECM, VAR and pairwise Granger causality were used to analyze the data. on GDP, external debt, debt servicing, government expenditure, and exchange rate. . Research Findings: The results show that the effect of external debt on economic growth is insignificant in the near term, having positive influence in South Africa and negative impact in Nigeria. However, the long-term effects are detrimental and noteworthy in South Africa. Also, the results on causality indicate that, in Nigeria, there is no causal relationship between external debt and economic growth, but in South Africa, there is a unidirectional relationship between GDP and external debt Theoretical Contribution/Originality: This study concludes that, whereas exchange rates are the primary predictor of economic growth in Nigeria, external debt neither causes nor determines economic growth in South Africa or Nigeria. Rather, causation flows from economic growth to external debt exclusively in South Africa. Therefore, this study recommends that the government of both countries should channel their available resources towards developmental projects that will spur growth. Keywords: External debt, Causality, Growth, Emerging Market, GDP

A Novel Directed Seed-Based Connectivity Analysis Toolbox Applied to Human and Marmoset Resting-State fMRI

Estimating the direction of functional connectivity (FC) can help to further elucidate complex brain function. However, the estimation of directed FC at the voxel level in fMRI data, and evaluating its performance, has yet to be done. We therefore developed a novel directed seed-based connectivity analysis (SCA) method based on normalized pairwise Granger causality that provides greater detail and accuracy over ROI-based methods. We evaluated its performance against 145 cortical retrograde tracer injections in male and female marmosets that were used as ground truth cellular connectivity on a voxel-by-voxel basis. The ROC curve was calculated for each injection, and we achieved AUC (Area Under the ROC Curve) of 0.95 for undirected and 0.942 for directed SCA in the case of high cell count threshold. This indicates that SCA can reliably estimate the strong cellular connections between voxels in fMRI data. We then used our directed SCA method to analyze the human default mode network (DMN) and found that dlPFC (dorsolateral prefrontal cortex) and temporal lobe were separated from other DMN regions, forming part of the language-network that works together with the core DMN regions. We also found that the cerebellum (Crus I & II) was strongly targeted by the posterior parietal cortices and dlPFC, but reciprocal connections were not observed. Thus, the cerebellum may not be a part of, but instead a target of, the DMN and language-network. Summarily, our novel directed SCA method, visualized with a new functional flat mapping technique, opens a new paradigm for whole-brain functional analysis.Significant StatementWe developed a novel directed seed-based connectivity analysis (SCA) method. To evaluate its performance, we used 145 retrograde tracer injections into the common marmoset left cortex as ground truth cellular connectivity. These were compared with directed and undirected SCA on a voxel-by-voxel basis. We achieved AUC=0.95 for undirected and AUC=0.942 for directed SCA, thus SCA can estimate strong cellular connections with high accuracy. Then, we analysed the human default mode network (DMN) with directed SCA and found that the dorsolateral prefrontal cortex and temporal lobe were not part of the DMN, but part of the language network. Secondly, our analysis showed that the cerebellum may not be part of, but instead a target of, the DMN and language network.

Econometric Analysis of South Africa’s Fiscal and Monetary Policy Effects on Economic Growth from 1980 to 2022

This study examined South Africa’s economic growth rate from 1980 to 2022 through an econometric analysis of fiscal and monetary policies. The study sought to investigate the relationships between the economy’s growth rate and various fiscal and monetary policy variables, taking into account different economic approaches such as Keynesian, monetarist, and Wagner’s perspectives. The methodology used consisted of data preparation, multiple unit root tests, Autoregressive Distributed Lag (ARDL) cointegration analysis, diagnostic tests, and pairwise Granger causality analysis. The empirical analysis found a long-term cointegration among the economic growth rate, government debt, expenditure, and revenue in fiscal policy, though government debt and expenditure were not statistically significant. Contrary to economic theory, increased government revenue had a negative correlation with economic growth. There was no long-term relationship found between the economic growth rate and monetary policy variables such as the official exchange rate, inflation rate, real interest rates, and M3 money supply. Pairwise Granger causality tests revealed a one-way relationship between government spending and economic growth, providing support to the Keynesian approach to fiscal policy. This study also discovered evidence that economic growth Granger-causes inflation, implying that economic growth may have predictive power for inflation, consistent with the demand-pull inflation hypothesis. However, no direct predictive relationships were found between the selected monetary policy variables and economic growth, supporting the long-run theory of monetary neutrality. This study suggests evaluating spending, managing inflation, implementing reforms, closing infrastructure gaps, encouraging investment, and ensuring fiscal sustainability.

Coffee in Indian Economy: Performance and Prospects

Coffee is a universal hot beverage, and its international trade volumes point to significant approval in favour of coffee consumption. For many nations in the tropics, coffee is a major source of foreign exchange. This study provides a comprehensive analysis of the global and domestic coffee industry, with a particular focus on India's role based on the secondary data taken from different sources like ITC trade map, Coffee Board of India and international coffee organization statistics, etc. In 2022, global coffee production reached 10.89 million tons, with Brazil, Vietnam, and Indonesia leading the output. Despite being the eighth-largest coffee producer, India's export ranking is relatively low due to significant domestic consumption. This study employs standard econometric tools, such as compound annual growth rate, Cuddy Della Index, Markov chain analysis, etc. The Johansen co-integration test revealed a long-run equilibrium relationship among selected Arabica and Robusta coffee markets. Furthermore, the pair-wise Granger causality test identified unidirectional causality in price transmission among certain Arabica markets, while bidirectional causality was observed among Robusta markets. The paper also highlights the declining coffee yield in India due to biotic and abiotic stressors, despite an increase in production and cultivation area. The study concludes with a discussion on the dynamics of Indian coffee exports, where high domestic demand and fluctuating international prices contribute to the sector's variability. This research provides valuable insights into the performance and prospects of the coffee industry within the Indian economy, offering a basis for future policy and market interventions.

Does foreign aid crowd out domestic saving in Ethiopia: ARDL model approach

This paper attempted to examine the relationship between domestic savings and aid in the context of Ethiopia during the period 1996 to 2018 by using ARDL framework. What is more, by disaggregating aid according to its source, the impact of aid from bilateral and multilateral donors on domestic savings is also analyzed. The other distinct feature of this study is that using a Pair-Wise Granger Causality it attempts to investigate the causality between the two variables. The result indicates that increases in aggregate aid are associated with a decline in domestic savings in the long run, also though its impact in the short run is insignificant. Turning to different kinds of aid, bilateral aid is found to have a significant negative association with savings in the long run. However, multilateral aid appears to increase domestic savings and helps the level of domestic savings from becoming worse than the current situation the causality test performed points that there exists two-way causality between the two variables, it indicates that there is bidirectional causality between aid and savings.

Impact of Urbanization, Development Level, and Openness on Institutions in Bangladesh: An ARDL Investigation Using Two Measures of Institutional Quality

Future development policies require a better understanding of the various factors that affect the quality of institutions in Bangladesh. In this paper, we estimate empirical ARDL models to investigate the roles of urbanization, openness, and the level of development as determinants of institutional quality. We use two measures of institutional quality, both derived from the World Bank’s Worldwide Governance Indicators (WGIs). The first proxy, INQ, is a composite index developed from the six WGIs using Principal Component Analysis (PCA). The second indicator, AvgINQ, is the average of the six WGIs. For each indicator of institutional quality, three models were estimated, resulting in six models in total. The impact of urbanization on institutional quality is consistent in terms of sign and significance across all six models, a claim that cannot be made for the other variables in the model. The error correction term reflects dampening convergence to equilibrium for the first proxy for institutional quality but regular convergence when the second proxy is used. In terms of ARDL diagnostics, models with AvgINQ as the dependent variable perform better. The Johansen cointegration test confirms the existence of a long-term relationship among the variables in all the models. Pairwise Granger causality tests are also conducted. The findings emphasize the importance of managing urbanization pressure for better institutional quality.

Sectoral carbon dioxide emissions and environmental sustainability in Pakistan

Global greenhouse gases and carbon dioxide emissions have escalated to concerning levels. Given the growing urbanization, industrialization, and energy consumption, it is crucial to understand how carbon dioxide emissions from various sectors influence environmental sustainability in Pakistan. The prime objective of this study is to examine the nexus between sectoral carbon dioxide emissions and environmental sustainability in Pakistan, analyzing data from 1971 to 2014. The study employs the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) method and the Autoregressive Distributive Lag (ARDL) model to analyze patterns and relationships, providing insights into how each sector's emissions contribute to the overall environmental impact. The results highlight that the independent variables – economic growth, population growth, and energy consumption - are the most significant contributors to overall carbon dioxide emissions, driven by the high consumption of fossil fuels. At an aggregate/disaggregate level, various models show mixed associations between dependent variables such as overall carbon dioxide emissions, carbon dioxide emissions from gaseous fuel consumption, carbon dioxide emissions from liquid fuel consumption, carbon dioxide emissions from solid fuel consumption, carbon dioxide emissions from residential buildings, commercial and public services, and carbon dioxide emissions from the transportation sector with the independent variables. Pairwise Granger causality confirms a unidirectional causality among various pairs of relationships. The study suggests that policymakers in Pakistan adopt a multi-sectoral approach to achieve environmental sustainability. It also recommends accelerating the transition to renewable energy sources such as solar, wind, and hydropower to reduce dependence on fossil fuels.

Business Confidence in Indonesia: Which Macroeconomic Factors Have Long-Term Impact?

Business confidence refers to the level of optimism or pessimism that business owners have about the prospects of their companies and the overall economy. Thus, the focus of this study is to examine the long-term impact of various macroeconomic factors—economic growth, government expenditure, interest rates, inflation, exchange rates, and the composite stock price index—on the business confidence index in Indonesia by utilizing monthly data from January 2009 to December 2022. We employ Dynamic Ordinary Least Squares (DOLS) and Fully-Modified Ordinary Least Squares (FMOLS) as the main methods, with Canonical Cointegrating Regressions (CCR) as a robustness check method. The study also utilizes pairwise Granger causality tests for a comprehensive analysis. The findings indicate that all macroeconomic factors significantly impact the business confidence index in the long term across all methodologies. Specifically, economic growth, inflation, and the composite stock price index exert a positive impact, while government expenditure, interest rates, and exchange rates indicate a negative impact on the business confidence index. This evidence emphasizes the importance for businesses to diligently monitor macroeconomic trends and understand the patterns in these indicators so that companies can better anticipate changes in business sentiment. Taking a long-term perspective when making strategic decisions and investments is also advisable, recognizing that the influence of macroeconomic factors on business confidence may be more pronounced over time.

Efficiency in Operations of NASDAQ Listed Technology Companies from 2011 to 2023

The performance of technology companies listed on NASDAQ significantly impacts larger economic trends. Investors need specific information to navigate market volatility and make informed decisions in an increasingly complex marketplace. Furthermore, amidst the ongoing digital revolution, legislators and regulatory agencies must comprehend the operational dynamics of technology companies to develop frameworks that support innovation while maintaining market stability. Our study assesses the impact on the overall operational efficiency of NASDAQ-listed firms from 2011 to 2023, resulting from the interdependence of critical variables such as selling, general, and administrative expenses (SGA), cost of goods and services sold (COGS), and investments in research and development (R&D). Johansen’s cointegration methodology and pairwise Granger causality tests were employed to unveil long-term relationships, equilibrium adjustments, and causal relationships among the considered variables. The results provide critical insights into the strategic management of operational variables by the listed companies. The economic significance of the results obtained underscores the paramount importance of efficiently managing the cost of goods and services sold to achieve superior operating performance among these leading technology firms.

An Empirical Investigation of GDP, Industrialization, Population, Renewable Energy and CO2 Emission in Bangladesh: Bridging EKC-STIRPAT Models

This research paper explores the presence of the Environmental Kuznets Curve (EKC) in Bangladesh, delving into the intricate relationships among GDP, industrialization, renewable energy utilization, and CO2 emissions. Utilizing the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, our investigation spans the 1992 to 2021 timeframe, offering a comprehensive analysis of the interplay between these crucial factors in the context of Bangladesh's environmental sustainability. In this study, the F-bound test is utilized to establish the cointegration relationship among variables. And the short-run and long-run elasticity of explanatory variables is investigated by employing the Autoregressive Distributed Lag (ARDL) approach. This research also employed a pairwise granger causality test to explore the direction of causality between them. Empirical results prove the existence of a cointegration relationship among CO2 emission, GDP per capita, a quadratic form of GDP per capita, renewable energy, industrialization, and population. The findings provide strong support for the presence of the EKC in the case of Bangladesh. Besides that, significant inverse relationship was also obtained between CO2 emission and renewable energy consumption. Additionally, the study found the detrimental long-term effects of industrialization on the environment. The EKC hypothesis argues that Bangladesh can accomplish sustainable economic development. To attain the goal country should adopt appropriate government policies and ensure their implication. This study strongly advocates using sustainable energy sources and implementing regulations on pollutant industries.

Return and Volatility Spillover in Equity and Commodity Market: Some Indian Evidence

This study empirically investigates the return and volatility spillover among equity markets, Agro and non-Agro commodity markets. The study has used daily return data of BSE SENSEX as equity index, MCX iCOMEDEX, including Gold, Silver, and Crude oil, as non-agro indices, and NCDEX (AGRIDEX) as agro commodity indices to analyze volatility transmission between assets and markets using Generalized Autoregressive Conditional Heteroscedasticity (GARCH) and Exponential Generalized Autoregressive Conditional Heteroscedastic (EGARCH) model. The study has used dummy variables in the variance equation to identify the structural breaks during the COVID 19 pandemic. Further, Vector Auto Regression (VAR) pair-wise Granger causality test has been used to understand returns’ causality. The study has found a bidirectional and unidirectional causal relationship between variables. The study indicates that NCDEX could influence all the variables except MCX Gold. In structural breaks with deterministic dummy variables during COVID-19, we have found mixed evidence of asymmetric impact on conditional volatility. The study also indicates a positive and significant asymmetric volatility effect in the case of MCX Gold and MCX Silver during the COVID-19 period. The study has specified that SENSEX dominates the inflow of information to all commodity markets. Also, the findings signpost that information flows from NCDEX to MCX Gold, MCX Silver, and MCX Crude Oil. JEL Codes: C32, E30, E44, F41, G15, Q43

Revisiting the Nexus between Renewable Energy Consumption and Economic Growth in Nigeria: The VECM Approach

The research investigates the effect of renewable energy consumption on economic growth as well as analyzing the dynamic relationship between both variables from 1990 to 2022. Annual secondary data covering the period between 1990 and 2022 were used in the study. Data on real gross domestic product, renewable energy consumption (% of total final energy consumption), gross capital formation (% of GDP), labor force, total and trade (% of GDP) were sourced from World Development Indicator. The study applies Johansen co-integration test and Vector Error Correction Model (VECM) to examine the effect of renewable energy consumption on economic growth and other explanatory variables as well as using pairwise granger causality test to examine the causal relationship between both variables. The empirical evidence revealed long-term relationship between renewable energy consumption and economic growth. Evidence shows that there is no causality either unidirectional or bi-directional between both variables. In short run, renewable energy consumption revealed a significant positive impact on economic growth. This shows that renewable energy may stimulate economic growth, particularly as it has a greater short-term impact on economic growth than capital formation. The key policy implication drawn from the results indicate the need for investment in renewable energy technologies and infrastructure, which can help to increase the availability and affordability of renewable energy, improve workforce development in Nigeria renewable energy sector.

Effect of Employee Health and Safety Cost on Profitability of Listed Oil and Gas Companies in Nigeria

The present study employed an ex-post facto research design to investigate the impact of employee health and safety costs on the profitability of oil and gas companies listed on the Nigerian Exchange Group (NXG) in 2023. Utilizing data analysis techniques such as descriptive statistics, Pairwise Granger Causality Tests, Panel unit root tests, and Ordinary Least Squares (OLS) regression analysis through E-view-9 software, the study fills gaps in previous research by focusing specifically on this underexplored aspect of corporate expenditure. Through purposive sampling, the study ensures a comprehensive analysis of companies with up-to-date financial reports, enhancing the reliability and validity of the findings. The study found that there is insufficient evidence to conclude that employee health and safety costs have a significant direct effect on profitability for the listed oil and gas companies in Nigeria within the examined timeframe. By adopting a rigorous research methodology and statistical approach, the study provides valuable insights into the relationship between employee health and safety costs and profitability in the Nigerian oil and gas sector, contributing significantly to the existing literature and advancing understanding in this field. The study further suggested that oil and gas companies should implement proactive safety measures, such as regular training and equipment upgrades, to prevent workplace accidents and reduce associated costs. Also, they should enhance transparency by integrating employee health and safety metrics into sustainability reporting frameworks to build stakeholder trust and accountability.

Does Higher Institutional Quality Result in Environmental Sustainability? A Comparative Study of India and China

There is a lack of comprehensive research comparing India and China in terms of institutional quality and environmental degradation. This special issue aims to make threefold distinct contributions. By comparing India and China, we can learn from each other's experiences and gain insight into the shared difficulties both nations face when trying to achieve environmental sustainability in the face of high-quality institutional frameworks. The impact of corruption, economic development, ecological risk, and renewable energy sources on carbon dioxide emissions in China and India is investigated in this study. For this reason, we also employ the ARDL model and pairwise Granger causality to prove that something caused another. Applying the ARDL long-run bound test, the empirical results reveal a long-run connection between variables in both China and India. In the case of China and India, the estimated results also reveal a negative correlation between carbon emissions and the usage of renewable energy sources, but a positive correlation between carbon emissions and economic growth, corruption, and environmental risk. Improving institutional quality is the goal, and the present theoretical and applied discourse on comparative environmental sustainability is a good place to start. As a result, policymakers in China and India should oppose unfair practices that undermine competition laws and policies by instituting stringent anti-corruption measures and environmental rules. Energy efficiency measures that reduce carbon emissions without slowing economic growth should also be the government's primary focus.

High Public Debt in Japan: The Institutional Quality Perspective

This study aims to look at the long-term and short-term links between institutions' quality and public debt. The analysis seeks to shed light on two key aspects: firstly, the influence of country-level institutional quality on public debt, and secondly, the duration of the effects or shocks caused by this relationship. This research employs time-series data spanning from 1996 to 2017 to examine the relationship between institutional quality at the country level and public debt in Japan. Various econometric techniques were employed to analyse the determinants of public debt in Japan, including ’The Unit Root Test, Johansen's Co-integration Analysis, Vector Error Correction (VEC) Model, Variance Decomposition, Impulse Response Analysis, Pairwise Granger Causality Test, and The Toda-Yamamoto Model’. The results of the estimation demonstrate a statistically significant correlation between country-level institutional quality and public debt, both in the long and short term. The evidence indicates that factors such as Voice and Accountability (VA), Political Stability (PS), Government Effectiveness (GE), and Regulatory Quality (RQ) have a negative and statistically significant impact on public debt. Conversely, the Rule of Law (RL) and Control of Corruption (CC) exhibit a positive and statistically significant influence on public debt. The occurrence of public debt can frequently be attributed to the insufficient focus of policymakers, which can be attributed to governance deficiencies. Hence, the implementation of public debt management is necessary to mitigate the possibility of default. The findings indicate that it would be advisable for Japan to enact comprehensive policies aimed at mitigating public debt.

Integration of Pakistan's stock market with the stock markets of top ten developed economies

This study examines the integration of Pakistan's Stock Market with the stock markets of the top ten largest economies in the world—USA, China, Japan, Germany, the UK, India, France, Italy, Brazil, and Canada—from January 2015 to October 2020. To examine long- and short run integration, this study employed Johansen and Juselius co-integration and pair-wise Granger causality tests. In the long run, the results indicated that Pakistan's Stock Market is not integrated with these markets. This implies that the market is more attractive in portfolio diversification for international investors, and vice versa. In the short run, the results revealed that, except for China, Pakistan's stock market integrates with the remaining nine markets. However, Pakistan's stock market exhibits a bidirectional relationship with the USA, Japan, Germany, the UK, and France in the lead-lag relationship. However, its relationship with India, Italy, Brazil, and Canada is unidirectional, with Pakistan's stock market leading, while these markets are following. For Pakistani investors, China is the optimal market, and vice versa. Importantly, our findings help policymakers to comprehend Pakistan's dynamic relationship with its trading partners. To the best of our knowledge, no prior study has employed advanced techniques to address the time-varying correlation among the selected markets. By determining Pakistan's stock market integration with its trading partners, this study aimed to fill this empirical literature gap.