Causality Test Research Articles

Can artificial intelligence and green finance affect economic cycles?

The COVID-19 recession and the Ukraine-Russia War (URW) crisis have added a new layer of complexity to global economic cycles, necessitating the evolution of economic systems and proactive responses to emerging economic challenges. In this context, the recent article introduces artificial intelligence (AI) as a new driver of economic cycles and analyzes its dynamic role alongside the Belt and Road Initiative (BRI), the Paris Agreement (PA), green finance (GB), and economic shocks (ES) in determining global economic cycles. The article employs novel econometric tools, namely the CAViaR-TVP-VAR model, the Quantile Coherence method, panel Quantile on Quantile Kernel-Based Regularized Least Squares (PQQKRLS), and the Quantile-Quantile Granger causality (QQGC) test for robust findings. The outcomes reveal that AI influences economic cycles in the short run while significantly mitigating these cycles in the medium and long run. Furthermore, the BRI exhibits a positive link with economic cycles during the short and medium run; however, it can contribute to economic stability in the long run by impeding economic fluctuations. Similarly, green finance and the PA show mixed influences across various time horizons, except for the long run, which confirms their negative association with economic cycles. Additionally, ES has a direct link with economic cycles across most periods. The robustness check based on the QQGC test and PQQKRLS method supports the main results. Our results identify AI, BRI, and the PA as new drivers of economic cycles with the potential to counter global economic cycles. Therefore, based on these findings, the study proposes several policy implications tailored to different time horizons.

Challenges for low-carbon economies in Latin America. Testing pollution haven hypothesis in developing countries

Our research investigates the determinants of CO₂ emissions in Latin American countries (LAC), focusing on the roles of renewable energy consumption (RENC), economic growth (GDP), foreign direct investment (FDI), urbanization (URB), and access to electricity (ACEL). Employing a panel ARDL model, we account for both short-run and long-run dynamics between CO₂ emissions and their determinants. In the long run, RENC demonstrates a significant negative impact on CO₂ emissions (-0.15). Higher-order terms of RENC reveal non-linear effects, with RENC² showing a positive coefficient (0.05) and RENC³ a negative coefficient (-0.006), indicating diminishing returns as renewable energy consumption increases. Economic growth is positively associated with CO₂ emissions (0.1), reflecting the trade-off between economic expansion and environmental sustainability. FDI has a small but significant negative impact on emissions (-0.0003), while ACEL also reduces emissions (-0.03). In the short run, CO₂ emissions adjust to long-run equilibrium at a rate of -0.04, with GDP exerting the strongest short-run influence. The Energy Kuznets Hypothesis for CO₂ emissions is found to be a monotonically decreasing function of RENC, implying that as RENC increases, CO₂ emissions consistently decrease, albeit at a slower rate. The error correction term (ECT) is negative and significant (-0.04), indicating that CO₂ emissions adjust towards the long-run equilibrium by about 4% each period. The Dumitrescu-Hurlin panel causality test confirms bidirectional causality between RENC and CO₂ emissions. Unidirectional causality is also observed from URB to CO₂ emissions and from CO₂ to ACEL. Variations in energy consumption profiles and stages of economic development across the region explain differing impacts of RENC and FDI on emissions, where some countries experience the pollution haven effect, while others benefit from the pollution halo.

Asymmetric Nexus Between Shadow Economy and Financial Instability: Does Institutional Quality Matter?

Policymakers worldwide, especially central banks, are concerned about the causes and remedies of financial instability. This study examines the asymmetric influence of the shadow economy on financial instability. Moreover, the study analyzes the moderating role of institutional quality in the shadow economy and financial instability nexus. This study used novel econometric techniques, including RALS-ADF and RALS-LM unit root tests, RALS-Fourier ARDL, NARDL, and single Fourier-Toda and Yamamoto causality tests, using yearly data from 1984-2020 for Turkey. Specifically, a positive shock to IQ declines financial instability, while a negative shock to IQ promotes it. Further, the negative shock to SE lessens the financial instability. Moreover, the negative shock to the interaction term implies that the shadow economy outweighs the IQ (depending on the level of IQ) in its effect in the case of Turkey, i.e., even if IQ increases (which usually decreases financial instability), the increasing SE has a dominant effect, and eventually upsurges financial instability. Additionally, in line with the institutional failure hypothesis, the negative shock to interaction term leads to a substantial increase in financial instability. Finally, the findings showed a one-way causality that runs from economic growth to financial instability and bidirectional causality between SE and GDP. The government should reduce shadow economic activities in the economy by enhancing IQ, which can increase government revenue and reduce financial instability.

The impacts of different types of globalization on energy security risk: Can globalization be a remedy for the energy security risk of OECD countries?

This study analyzes the impact of globalization and its sub-dimensions on energy security risk for OECD countries. In our study, annual data of 26 OECD countries for the period 1980-2018 were used. Second generation panel data techniques were used as the methodology. The results of the analysis show that economic, political and aggregate globalization increases energy security risk, while social globalization is statistically insignificant. The Dumitrescu-Hurlin panel causality test results demonstrate that there is a unidirectional causality relationship between inflation and energy security risk, and a bidirectional causality relationship between economic globalization, social globalization, political globalization, aggregate globalization, GDP and Gross Fixed Capital Formation and energy security risk. The study also analyzed how the impact of globalization on energy security risk varies across countries. The results of the analysis reveals that there are significant differences in the direction, significance and coefficient size of the relationship across countries. These findings suggest that the effects of globalization on energy security risks vary across countries. Therefore, countries should develop policies to minimize energy security risks by taking into account their own dynamics.

Financial Development in Nigeria: A Causal Imperative for Economic Growth

This research investigated the causal relationship between financial development and economic growth in Nigeria from 1994 to 2023. Secondary data were obtained from the Central Bank of Nigeria's Statistical Bulletin and the World Bank's Financial Development Indicators Database. The unit root test was used to establish data stationarity, revealing conflicting results that necessitated the application of Auto Regressive Distributed Lag and the Granger Causality Test. The findings indicated that the private sector credit ratio to gross domestic product, the number of bank accounts per 100,000 persons, and the lending-deposit spread were significant predictors of Nigeria's gross domestic product. Furthermore, the applied indicators of financial development neither facilitate nor enhance economic growth, nor does economic growth assist or promote the utilized measures of financial development throughout the research period, as shown by the lack of causation in our findings. Consequently, the research indicated that of the variables used, just one – the asset quality ratio – did not substantially affect economic growth, and moreover, none of the four measures of financial development used fostered economic expansion. The study advocated for Nigerian banks to strengthen their credit policies and rigorously comply with them, as this would mitigate non- performing loans and subsequently improve asset quality ratios. Additionally, it emphasized the necessity for banks to enhance their financial inclusion initiatives, which would attract more deposits, thereby augmenting their credit capacity. An increase in credit provision would elevate operational efficiency and, consequently, bolster their contribution to the growth of the Nigerian economy.

Assessing the impact of tourism on sustainable economic development in Indonesia: A comprehensive analysis using the Fourier bootstrap autoregressive distributed lag approach

This research analyzes the relationship between political stability, renewable energy utilization, economic progress, and tourism in Indonesia from 1990 to 2020. We employ advanced econometric techniques, including the Fourier Bootstrap Autoregressive Distributed Lag (ARDL) approach and Fourier Toda-Yamamoto causality testing, to ensure the robustness of our results while accounting for smooth structural changes in the data. The analysis uncovers a long-term equilibrium relationship between tourism and its fundamental determinants. Our research reveals significant positive impacts of political stability and renewable energy consumption on tourism in Indonesia. A stable political environment creates a favorable climate for tourism development, instilling confidence in both domestic and international tourists. Promoting renewable energy usage aligns with sustainable tourism practices, attracting environmentally conscious travelers. Furthermore, our findings demonstrate a bi-directional causal relationship between these variables over time. Changes in political stability, renewable energy consumption, and economic growth profoundly influence the tourism sector, while the growth of tourism itself can also stimulate economic development and foster political stability. Our findings underscore the need for environmentally sustainable and politically stable tourism policies. Indonesia’s tourism sector can grow sustainably with renewable energy and stability. Policymakers can develop strategies with tourism, political stability, renewable energy, and economic prosperity in mind.

Effects of Social and Economic Development on CO2 Emissions in the Countries of the Visegrad Group

The aim of this study is to assess the impact of socio-economic development, consumption of renewable energy, educational spending, and foreign direct investment on carbon dioxide emissions in the Visegrad countries (Czech Republic, Hungary, Poland, and Slovakia) between 1991 and 2021. The study employed the Autoregressive-Distributed Lag Bound Testing model and Toda–Yamamoto causality tests to establish short- and long-term relationships for each of the dependent variables and countries, aiming to verify the hypotheses. For the Czech Republic and Slovakia, a bidirectional relationship was identified between carbon emissions and the Human Development Index (HDI). In Poland, bidirectional causality was indicated between renewable energy consumption and carbon dioxide emissions. Unidirectional causality was evident for the Czech Republic, Hungary, and Slovakia between the specified variables. Short-term findings indicate that an increase in renewable energy production may lead to higher carbon dioxide emissions in the Visegrad countries. In the long term, only Slovakia demonstrates a significant relationship between educational spending and reduced carbon emissions. Toda–Yamamoto tests reveal unidirectional causality between foreign direct investment and carbon dioxide emissions for the Czech Republic and Slovakia. Empirical findings suggest that policymakers should invest in socio-economic development and renewable energy to reduce CO2 emissions and achieve long-term sustainability in the Visegrad countries. Poland needs to shift its energy policy away from coal, and all countries should enhance education to effectively transmit environmental knowledge and values.

GOVERNANCE AND FOREIGN DIRECT INVESTMENT : EVIDENCE IN ASEAN

This research analyzes the connection of Regulatory Quality (RQ) and Rule of Law (ROL) on Foreign Direct Investment (FDI) in ASEAN countries between 2002 to 2022. Utilizing the pooled mean group (PMG) technique with data sourced from the World Bank, the study found that Regulatory Quality significantly impacts FDI in the long term. Short-term results indicate significant corrections to the divergence of the long-term equilibrium production levels. Causality tests reveal a two-way relationship between FDI and Regulatory Quality in ASEAN countries, but no reciprocal relationship with Rule of Law was identified.

Forecasting and Impact Analysis of the Development Trends of China's New Energy Electric Vehicles Based on Time Series Causal Analysis

New energy electric vehicles with numerous properties have experienced explosive growth in recent years. This research constructs an ISM model to analyze the key factors influencing the new energy vehicle market and develops both a Winters' additive model and an ARIMA model to forecast the development of the NEV industry from 2023 to 2033. The results show that, the development of the new energy vehicles in the following ten years as a growth trend. Moreover, Granger causality tests, conducted within the VAR framework, revealed that NEV sales growth and market share significantly impact policy effectiveness and market dynamics. Simultaneously, the environmental impact was assessed using a LCA model, which indicates that the development of new energy vehicles is beneficial to the ecological environment. The results contribute to the theoretical and empirical understanding of the NEV market, providing valuable insights for policy makers and industry stakeholders.

Regenerating Sustainable energy and environmental solutions: Challenges and Opportunity in Belt and Road Initiative Countries

This study examines financial development, economic growth, energy consumption, trade openness, urbanization, and environmental degradation in 47 Belt and Road Initiative (BRI) countries from 1980 to 2022. Panel unit root tests (IPS, LLC, PP, and ADF) ensured data correctness and stationarity. Three co-integration tests examined the variables' connections. Difference of means (DOLS) and functional moment (FMOLS) tests examined BRI economies' co-integration. A paired Granger causality test found bidirectional correlations between CO2 emissions, urbanization, financial development, economic growth, and the creation of gross fixed capital. Trade openness only correlated with ecological well-being. International study suggests regional, state, and federal policy implications. The empirical investigation used a panel causal heterogeneous test, dynamic ordinary least squares(DOLS), and fully modified ordinary least squares (MOLS) with fixed and random effects. Trade openness negatively affected CO2 emissions, but all other regressors positively affected environmental quality. Good governance and country-specific policies are needed to maximize BRI advantages. Despite conflicting energy statistics, the study found that economic development hurt the environment in all 47 countries. Industrialized nations generally use renewable energy, which minimizes ecological issues, hence their omission from the BRI full panel may explain the negative coefficient. Since most BRI economies are in emergent and growing countries, environmental preservation and renewable energy technologies need more time and money. Instead of coal, the Chinese government and other BRI nations are urged to invest in wind, hydro, solar, and biomass. Sharing green energy technology might help BRI economies. Cross-national urbanization strategy should incorporate eco-friendly solutions. The panel and governments may utilize the paper's substantial policy recommendations.

The role of socioeconomic and behavioral factors in HIV-related deaths

In today’s increasingly interconnected globe, there continues to be a pressing need for thorough research that can shed light on the causes of HIV-related mortality and the primary factors at play in this epidemic. By using an annual dataset, this study analyzed the impact of behavioral risk factors, income, and human capital on HIV-related deaths (HIVD) across all countries and regions. The empirical findings of the panel regression demonstrate that drug use and unsafe sex have a statistically significant and positive effect on HIVD. On the other hand, mean years spent in school and gross national income per capita both have a statistically significant and negative influence on HIVD. The findings of the variance decomposition suggest that drug use should be confronted in wealthy nations to lower HIVD, but both human capital and economic development have a greater influence on the battle against HIVD in underdeveloped and developing countries. In addition, the findings of the panel Granger causality test demonstrate that factors other than unsafe sex can be used as leading indicators in the process of forecasting HIVD. According to these findings, economic variables, as well as behavioral risk factors in emerging nations, and in industrialized countries, should be taken into account when formulating strategies for preventing HIV/AIDS.

Bank Financial Distress and Stock Price Crashes: A Quasi‐Experimental Approach

ABSTRACTUsing 118,292 US bank‐month observations, we examine the effects of short‐term changes in bank's financial distress on stock price crash risk. There is a significant positive association between short‐term changes in distress on stock price crash risk. The results remain consistent across alternative measures of distress and crash risk. We confirm robustness by employing additional tests for reverse causality and propensity score matching. We find opacity, proxied by discretionary loan‐loss provisions to be a potential channel through which increase in distress affects future crash risk. Our study underscores the critical association between increasing financial distress, loan‐loss reporting, and crash risk.

Urban Resilience Amid Supply Chain Disruptions: A Causal and Cointegration-Based Risk Model for G-7 Cities Post-COVID-19

The COVID-19-induced strain on global supply chains led to significant market imbalances and unprecedented inflation, particularly affecting urban economies. Containment policies and stimulus packages resulted in unpredictable demand shifts, challenging urban supply chain planning and resource distribution. These disruptions underscored the need for robust risk management models, especially in cities where economic activity and population density exacerbate supply chain vulnerabilities. This study develops a comprehensive risk model tailored for G-7 urban economies, analyzing the causal and cointegration relationships between key economic indicators. Using Granger causality tests and a factor-augmented vector autoregression (FAVAR) approach, the study examines complex time series and high-dimensional variables, focusing on urban-specific indicators such as the composite leading indicator (CLI) and business confidence indicator (BCI). Our results indicate strong causal relationships among these indicators, validating CLI as a reliable early predictor of urban economic trends. The findings confirm the viability of this urban supply chain risk management model, offering potential pathways for strengthening urban resilience and economic sustainability in the face of future disruptions. This approach positions the study within the context of urban science, emphasizing the impacts on cities and how urban economies can benefit from the developed risk model.

An Analysis of The Distortive Effect of Environmental Policy Stringency on Physical Trade Balance for Fossil Fuels in China

ABSTRACT Utilizing advanced econometric techniques such as quantile ARDL regression and time-varying Granger causality tests, we offer empirical evidence that China’s stricter environmental policies distort its physical trade balance for fossil fuels. Our findings indicate a clear trend: stricter environmental policies cause significant increases in the amount by which fossil fuel resources contained in Chinese imports exceed those contained in its exports. This suggests a form of carbon leakage, where firms involved in domestic production and exportation of fossil fuels to evade the heightened costs associated with stringent regulations reduce domestic production, which is then replaced by foreign production. Our findings underscore an imbalance in the regulatory approach between domestic production/exports of fossil fuels and its imports. While regulations on domestic production and exports are becoming tighter, those governing imports remain relatively lax.

Does Structural Transformation Foster Economic Growth? Empirical Evidence from Indian States with Reference to Assam

This study examines the association between structural transformation and economic growth for a panel of 19 states and UTs focusing on Assam. Employing dynamic panel econometric models from 1977–1978 to 2017–2018, the study indicated that the association between economic growth and structural transformation among the 19 states/UTs panel seems to be random. However, parametric techniques such as DOLS suggest a significant long-term relationship between structural change in output and economic growth across Indian states. Assam, being a key player in north-east India’s economy, holds particular importance in India–South Asia trade dynamics. However, the state has been experiencing a simultaneous structural economic shift and adverse economic situation, evident from the existing literature. Thus, it is pertinent to examine the structural change-economic growth linkage for Assam, which will be helpful for policy-making to ensure sustained economic growth. For Assam, the vector auto regression and Granger causality test reveal significant results, showing a bi-directional causality between structural change and economic growth, supporting the Kaldor–Verdoorn’s law.

Does Political Instability cause and affect Macroeconomic instability in Pakistan?

This study is intended to examine the cause and effect of political instability on macroeconomic instability in Pakistan over the period of 1993-2023. As the nature of the data is time series therefore stationarity testing is necessary and ADF and PP tests are used for the said purpose. ARDL is employed to tests the required impact and granger causality to get the required objective. Result of the ARDL model reported that Inflation rate and Unemployment rate negatively and significantly influenced Political stability in long-run. Besides this, ECM is applied for short run effect. ECM’s result shows that Unemployment rate, Exchange rate, and Current account balance negatively and significantly influence Political stability in short-run. In the second model, the impact of Political stability variables employed Political stability & absence of terrorism, Voice & accountability, Regulation Quality, and Government Effectiveness on Macroeconomic instability. ARDL model result indicated that Political stability & absence of terrorism, Voice & accountability, and Government effectiveness have negative and significant impact on macroeconomic crisis index. Bound test result shows long-run relationship existence among variables. Besides this, ECM model shows that Political stability & absence of terrorism, Voice & accountability, Regulation Quality, and Government Effectiveness negatively and significantly influence macroeconomic instability. Beside this granger causality test was applied to test causal relationships among variables. The test found that Macroeconomic instability unidirectional granger cause Political stability significantly. Furthermore, Political variables index and Inflation rate show bidirectional causality. Unemployment rate unidirectional causes Political variables index. Similarly, current account balance is unidirectional granger causal political index. On the other hand, only Voice & accountability shows unidirectional causal relationship with Economic variables index.

Research on Interaction Effect Between Rural Roads and Peasants' Income Based on Granger Causality Test

This study aims to address the lack of methods for adjusting the scale of online ride hailing capacity. Taking G city as an example, a dynamic monitoring index system for the scale of online ride hailing capacity is constructed by comprehensively considering factors such as order volume, driver labor hours and income levels, and the operation status of the taxi market. Pearson correlation analysis and stepwise linear regression methods are applied to screen the indicators, and key indicators and threshold standards for the dynamic adjustment mechanism of online ride hailing capacity are proposed, providing theoretical basis and decision support for the adjustment of urban online ride hailing capacity scale

Derivative Markets and Economic Growth: A South African Perspective

It is well established that financial development and innovation promote economic growth through improving the allocation of capital, enhancing risk management, contributing to price discovery, and increasing market efficiencies. While a vast empirical literature is devoted to the nexus between financial development and economic growth, however, substantially less research has been done on the relationship between derivatives and growth, especially in the emerging-market context. Derivatives can be viewed as a specific category of financial innovation, which may advance economic growth through its specialised functions of risk management and price discovery. This paper contributes to bridging this gap in the literature by exploring the impact of exchange-traded futures derivatives on South African economic growth, output, and economic growth volatility. It employs ARDL bounds tests, Granger causality tests and GARCH volatility modeling to analyse the effects of exchange-traded futures derivatives on various measures of South African economic activity. The main result is that exchange-traded futures derivatives contribute positively to South African economic growth and economic activity. This may suggest that opportunities might exist in other emerging economies, with financial structures comparable to that of South Africa, to encourage the development of organised and well-regulated derivatives markets to unlock economic growth in these economies.

The Nexus between Monetary Policy Transmission Mechanisms and Economic Development in Sierra Leone for the Period (1993 – 2023)

This research investigated the transmission mechanisms of monetary policy and their impact on economic development in Sierra Leone from 1993 to 2023, aiming to evaluate their effectiveness in achieving key macroeconomic goals such as employment generation, balance of payments stability, and maintaining a relatively stable general price level. The study sought to understand how these transmission mechanisms influence economic development in Sierra Leone, particularly at a time when the country is grappling with significant macroeconomic challenges, including high unemployment, price volatility, and elevated inflation rates. Data spanning from 1993 to 2023 were collected from the World Bank Economic Indicators and Bank of Sierra Leone Statistical Bulletin through a purposive sampling approach. The research employed a blend of ex- post facto, longitudinal, descriptive, causal-effect, and correlation research designs. The statistical analyses conducted included the Augmented Dickey Fuller (ADF) unit root test, Granger causality test, ordinary least squares multivariate regression, generalized method of moments, Johansen co-integration, and vector error correction mechanisms. The findings revealed that capital stock (coefficient of 0.13), money supply (0.17), migrant remittances (6.5), and exchange rate (0.08) exhibited significant and positive long-term relationships with Sierra Leone economic development during the observed period. Conversely, the monetary policy rate (0.10) and credit to the private sector (0.30) demonstrated positive yet insignificant effects on economic development. Interest rates (-0.71) were found to have a significant negative relationship, while the inflation rate (-0.03) was negatively related but not significant. The study concludes that monetary policy transmission mechanisms have both short-term and long-term relationships with economic development in Sierra Leone, underscoring the importance of their effective implementation. Monetary policy transmission mechanisms have proven to be effective instruments for fostering economic development in Sierra Leone. It is advisable for both the Ministry of Finance and Bank of Sierra Leone, as the regulatory authorities, to consistently ensure an optimal combination of monetary policy tools. This approach is essential for significantly impacting economic activities, encouraging investments, and ultimately enhancing macroeconomic stability in the country. Furthermore, these regulatory bodies should regularly evaluate the monetary policy rate and the credit available to investors to create a favorable investment and business environment in Sierra Leone. Additionally, effective policies should be implemented to increase remittance inflows into Sierra Leone, directing investments towards productive uses rather than consumption, which may lead to inflationary pressures. The insights gained from this study contribute to the existing literature on economic development and the mechanisms of monetary policy transmission. The dynamic estimation technique, akin to the Generalized Method of Moments, effectively assessed the endogeneity between monetary policy variables and economic development in Sierra Leone.

Towards Carbon Neutrality: The Impact of Private AI Investment and Financial Development in the United States – An Empirical Study Using the STIRPAT Model

This investigation analyses the influence of private AI investment and financial development (FD) on CO2 emissions in the United States, using the STIRPAT framework to account for the functions of GDP, population, and foreign direct investment (FDI). The data's robustness was verified through the application of a variety of unit root tests, which confirmed that the variables are free of unit root issues and exhibit a varied order of integration. The ARDL bound test was used to investigate the cointegration among the variables and it found a long-run equilibrium relationship. The ARDL model results show that income, FDI, FD, and population significantly increase CO2 emissions in both the short and long term. In contrast, we found that private investment in AI led to a significant reduction in CO2 emissions over these time frames. Additional estimations were conducted using FMOLS, DOLS, and CCR methods to verify the ARDL results, all of which attested to the initial findings' robustness. In addition, the study implemented a pairwise Granger causality test to illustrate the directional relationships between the variables. There is a unidirectional causal link between GDP, private AI investment, FDI, population, and CO2 emissions, according to the findings. Most notably, we observed bidirectional causality between CO2 emissions and FD. Diagnostic tests further corroborated the validity of the study's conclusions, confirming that the model is free from specification errors, serial correlation, and heteroscedasticity.