Causality Test Research Articles

The Relationship between Renewable Energy Consumption and Economic Growth: Insights from Iceland and Azerbaijan

Iceland leads globally in per capita green energy production, while oil-dependent Azerbaijan endeavors to transition its energy policy towards sustainable alternatives. Investigating the impacts of renewable energy consumption on the economy represents a significant contemporary scientific inquiry. The objective of this research is to empirically examine the causal relationship between GDP per capita, a key metric of economic growth, and renewable energy consumption, a fundamental aspect of the green economy. In this research, the Toda-Yamamoto causality test framework of the vector autoregressive (VAR) model was utilized to examine the causal relationship between the variables. The outcomes of this investigation reveal a significant causality between renewable energy consumption and economic growth in Iceland and Azerbaijan.

Fuel Subsidy and Education Sector Financing in Nigeria: A Short-run Adjustment to Equilibrium Approach

This study examined the impact of fuel subsidy on education sector financing in Nigeria from 1990 through 2023. Annual data were obtained from the Nigeria Petroleum Corporation and World Development Indicators, (WDI) on variables such as fuel subsidy, government expenditure on education sector, Oil Revenue, pump price of Premium Motor Spirit and secondary school enrolment in Nigeria. A bound cointegration test and ECM were employed. Granger test for causality was also used to ascertain the direction of causation in the series. The estimated error correction term, ECT (-1) is significant. There is no causal relationship from fuel subsidy to education sector financing. However, education sector financing granger causes fuel subsidy. Premium Motor Spirit and education sector financing were found to granger-cause each other. The study recommends that government should ensure that fuel subsidy is not allowed to deprive education of its fair share of government spending, given that current spending on the sector has been established to have implication for the sectors growth in the future years.

Green cryptocurrencies versus sustainable investments dynamics: Exploration of multifractal multiscale analysis, multifractal detrended cross-correlations and nonlinear Granger causality

Within this study, we analyse green cryptocurrencies versus sustainable investments dynamics by calculating a multifractal multiscale analysis (MMA) with Hurst surfaces paired with powerlaw distributional coherence tests for each series. Next, we determine multifractal cross-correlations by applying a maximal overlap discrete wavelet transform (MODWT) based trend-filtered variation of a multifractal detrended cross-correlation analysis (MF-DCCA). Finally, to determine the strength and directionality of potential causations, we determine the results of a nonlinear Granger causality test. The results for the MMA state q-dependent unstable multifractality for each series. The coherence tests indicate that the series follow powerlaws or exponentially nested powerlaws and yield fat-tails in some cases. Moreover, we find strong scaling and multifractal cross-correlations between the cryptocurrencies and the sustainability series. Finally, the nonlinear Granger causality tests across four lags indicate a complex interplay between some of the selected cryptocurrencies and various indices. These results suggest the existence of potential predictive powers of these cryptocurrencies on the market indices.

Renewable Energy Consumption and Economic Growth in Nigeria Nexus

With rising rates of globalization, increasing climate change and economic growth, energy usage and energy security, governments are paying more attention to the impact of renewable energy consumption on the economies. The paper examines the relationship between renewable energy consumption and economic growth in Nigeria using a time series data from 1996 to 2021. The results of the unit root show mixed stationarity from our variables which result in the usage of ARDL technique of analysis. The long run results show that renewable energy was negative and significant thus, validates the conservative hypothesis. C02 was also negatively significant to RGDP while labor force was positively significant. The ECM shows 77% adjustment level backs to equilibrium. Granger causality test validated the feedback hypothesis of no causality among the renewable energy and the Nigeria economy.

Development - Economic Freedoms Interaction: A Comparative Analysis of D8 and G8 Country Groups

One viewpoint, which has been gaining traction recently, posits that augmenting economic freedom within liberal markets while minimizing public intervention spurs development. Conversely, another standpoint suggests that as development progresses, there emerges a heightened demand for greater economic freedom, resulting in the implementation of liberal policies. In this context the primary objective of this study is to scrutinize the presence of causality between economic freedom and development. Additionally, the study delves into whether this causal relationship, if extant, is consistent across countries at varying stages of development. Consequently, an examination is conducted on two distinct country groups, namely D8 and G8, employing the Dumitrescu-Hurlin panel causality test. This method dissects the directional link between economic freedom and development for these country clusters spanning the period 2000-2019. The analysis reveals that within D8 nations, a reciprocal causality exists between economic freedom and development. In contrast, among G8 countries, no causal link emerges from economic freedom to development, while a unilateral causal relationship emerges from development to economic freedom.

The Limits of Plato’s Test

Abstract Aristotle is often taken to define priority in being in Metaphysics Δ.11, where he says that those things are prior in being which “admit of being without other things, while these others cannot be without them: a division which Plato used” (1019a3-4). But Aristotle’s pattern of arguments about priority – some of which use Plato’s Test and others of which use distinct, causal tests – looks puzzling if Plato’s Test is his definition. This paper offers a new interpretation of Δ.11 on which it offers a guide to the Aristotelian use of Plato’s Test, given that being is said in many ways, rather than endorsing it as Aristotle’s own definition of priority. This reading illuminates Aristotle’s pattern of arguments in the corpus – explaining why Aristotle uses Plato’s Test in some cases and departs from it in others – and suggests a plausible story about how these arguments were shaped by engaging with Plato.

The Relationship between Activities of the Insurance Industry and Economic Growth: The Case of G-20 Economies

The aim of this study is to examine the impact of developments in the insurance sector on economic growth. This study examines an annual dataset spanning 1992 to 2022 from ten countries within the G-20 economies, for which data is reliably accessible. The analysis employs panel cointegration and panel causality tests to explore the underlying relationships. The results show that the activities of the overall insurance sector have a positive effect on economic development, while non-life insurance activities, as a sub-component of the insurance sector, also demonstrate a similar impact. Furthermore, findings indicate the existence of a bidirectional causality relationship between economic development and non-life insurance premiums. This study provides various recommendations to policymakers in the process of developing policies on the growth of national economies.

Will peer-to-peer online lending affect the effectiveness of monetary policy?

Online lending is a product of digital transformation, which has had a profound impact on the traditional money market. This paper discusses the impact of peer-to-peer (P2P) online lending on the effectiveness of monetary policy. Through the bootstrap sub-sample rolling-window Granger causality tests show that P2P has both positive and negative impacts on the money supply (M2). The positive impact of P2P on M2 indicates that online loans increase the amount of money supply. The negative impact of P2P on M2 shows that it may cut the money supply, thus weakening the monetary policy effectiveness. The general equilibrium model is inconsistent with these results, which underlines a positive effect from P2P to M2. In turn, the negative impact points out that the adjustment of monetary policy will hinder the development of P2P. The negative impact of M2 on P2P indicates that through the regulation of money supply, the online lending market can be correctly guided to prevent financial market from getting out of control. Through the supervision of online lending industry, we can accurately grasp the development of the internet financial industry and reduce its impact on monetary policy.

Inflation, exchange rate, and economic growth in Ethiopia: A time series analysis

This study aims to investigate the dynamic relationship between inflation, exchange rate, and economic growth in Ethiopia for the period 1991–2020. This is because of rampant inflation, continuously devalued domestic currency, and the declining growth rate of the country due to violent conflicts. The study uses the ARDL model for short-run and long-run dynamics, the Bound test of co-integration to confirm if the target variables go together or not, and Granger causality tests are performed to detect dynamic effects. The ARDL model estimates suggested that inflation and exchange rate are negatively related to economic growth. This implies that an increase in the price level reduces the production of goods and services, while devaluation has a negative impact by reducing imports of intermediate goods. Thus, increasing domestic resource mobilization, improving regulatory quality, and deepening the financial sector can be viewed as solutions to decrease chronic foreign exchange shortages, lower inflation, and boost economic growth rates.

Exploring the LCC Hypothesis in the Nordic Region: The Role of AI Innovation, Environmental Taxes, and Financial Accessibility via Panel ARDL

This study investigates the impact of artificial intelligence (AI) innovation on environmental sustainability in the Nordic region. Additionally, it tests the Load Capacity Curve (LCC) hypothesis by incorporating factors such as financial accessibility, environmental tax, and urbanization, using data spanning from 1990 to 2020. The methodology includes the Cross-Sectional Dependence test and the slope homogeneity test, revealing issues of heterogeneity and cross-sectional dependence. Furthermore, first and second-generation panel unit root assessments indicate that the variables are free from unit root problems. Panel Cointegration tests confirm that the variables are cointegrated in the long run. To analyze both short-run and long-run relationships, the study employs the Panel Autoregressive Distributed Lag (ARDL) model. The results from the Panel ARDL model support the LCC hypothesis in the Nordic region, showing a U-shaped relationship between income and load capacity factor. Moreover, AI innovation and environmental tax significantly and positively contribute to environmental sustainability in both the short and long run. In contrast, higher financial accessibility and urbanization degrade environmental sustainability over these timeframes. To validate the robustness of the Panel ARDL estimations, the study also uses Fully Modified OLS, Dynamic OLS, and Fixed Effects OLS approaches, all of which corroborate the ARDL findings. The study employs the D-H causality test to explore causal relationships among the variables. The test results reveal a unidirectional causal relationship between income and AI innovation to the load capacity factor and a bidirectional causal relationship between financial accessibility and the load capacity factor, as well as between urbanization and the load capacity factor. However, no causal relationship is found between environmental tax and the load capacity factor.

The Relationship between Tourism, Financial Development and Economic Growth in MP

Tourism and economic growth in India from 1960 to 2014 are examined in this research, takinginto account the relative importance of financial development in that time period. It has been shown thatboth the long-term and short-term development of India's economy is enhanced by inbound tourism. Alsofound is a long-term one-way Granger causality between tourism and economic development.Furthermore, the outcomes of the Granger causality test indicated a one-way association between twovariables ranging from GDP growth to tourist development. The findings support the rise of economicdriventourism in MP.

The role of environmental innovation on ecological footprint in nations with high technology exports concentrations in international trade

This study focuses on four major high-technology exporting countries––the USA, Germany, France, and China––to explore the long and short-run associations among ecological footprint, environmental technology patents, high-technology exports, and economic growth. The sample covering 1988–2019 is subject to a set of structural breaks, including 2009 Global Recession in addition to uncertainty in the order of integration captured by unit root tests, which provide basis for novel Fourier ARDL and Fourier Toda-Yamamoto causality methods. The Fourier ARDL findings reveal the importance of environmental technology innovations in dampening the level of ecological footprints and promoting a more sustainable environment in the USA, Germany, and France, whereas more high-technology exports in international trade worsen the ecological footprints in these countries in addition to the negative effects of economic growth in all countries including China. In contrast, high-technology exports appear to mitigate ecological footprint in China, however, eco-friendly technologies fail to reduce ecological footprints as in other analysed nations. The causality tests indicate bidirectional and unidirectional causal relationships among variables with the exception of China where the neutrality hypothesis holds between economic growth and ecological patents and also high-technology exports and ecological patents. These findings provide important insights in achieving sustainable development.

Influence of mesenchymal and biophysical components on distal lung organoid differentiation

BackgroundChronic lung disease of prematurity, called bronchopulmonary dysplasia (BPD), lacks effective therapies, stressing the need for preclinical testing systems that reflect human pathology for identifying causal pathways and testing novel compounds. Alveolar organoids derived from human pluripotent stem cells (hPSC) are promising test platforms for studying distal airway diseases like BPD, but current protocols do not accurately replicate the distal niche environment of the native lung. Herein, we investigated the contributions of cellular constituents of the alveolus and fetal respiratory movements on hPSC-derived alveolar organoid formation.MethodsHuman PSCs were differentiated in 2D culture into lung progenitor cells (LPC) which were then further differentiated into alveolar organoids before and after removal of co-developing mesodermal cells. LPCs were also differentiated in Transwell® co-cultures with and without human fetal lung fibroblast. Forming organoids were subjected to phasic mechanical strain using a Flexcell® system. Differentiation within organoids and Transwell® cultures was assessed by flow cytometry, immunofluorescence, and qPCR for lung epithelial and alveolar markers of differentiation including GATA binding protein 6 (GATA 6), E-cadherin (CDH1), NK2 Homeobox 1 (NKX2-1), HT2-280, surfactant proteins B (SFTPB) and C (SFTPC).ResultsWe observed that co-developing mesenchymal progenitors promote alveolar epithelial type 2 cell (AEC2) differentiation within hPSC-derived lung organoids. This mesenchymal effect on AEC2 differentiation was corroborated by co-culturing hPSC-NKX2-1+ lung progenitors with human embryonic lung fibroblasts. The stimulatory effect did not require direct contact between fibroblasts and NKX2-1+ lung progenitors. Additionally, we demonstrate that episodic mechanical deformation of hPSC-derived lung organoids, mimicking in situ fetal respiratory movements, increased AEC2 differentiation without affecting proximal epithelial differentiation.ConclusionOur data suggest that biophysical and mesenchymal components promote AEC2 differentiation within hPSC-derived distal organoids in vitro.

Infant Mortality, Education and Financial Development: Evidence from World Level Data Using Heterogeneous Panel Granger Causality Analysis

Education and financial development are crucial factors in achieving better health, including the reduction of infant mortality. This article investigates the causal relationship between education, financial development and infant mortality rate using annual data for 81 countries for the period 1980–2015 and employing the Emirmahmutoglu and Rose (2011) Granger causality test procedure for heterogeneous mixed panels. The results show that, individually and jointly, education and financial development Granger cause infant mortality in some countries across the major regions of the world. This suggests that improved education and a developed financial system are likely to reduce the infant mortality rate. JEL Codes: C33; E25; I

Green investment and its transformative impact on energy use in agriculture: A holistic approach towards carbon dioxide emissions

The extensive use of non-renewable energy sources in agriculture and associated unsustainable practices have contributed greatly to climate change issues. Africa's lack of green initiatives has exacerbated environmental pollution in the last decade. In that regard, this study investigates the transformative impact of green investment on carbon emissions in agriculture fueled by dependency on non-renewable energy use in the sector. It utilizes advanced econometric techniques, including dynamic ordinary least squares, fully modified ordinary least squares, and the causality tests to conduct a rigorous analysis. The findings reveal a concerning rise in agricultural pollution via crop and livestock production. However, green investment is found to have a positive impact on carbon dioxide emissions, hence a potent tool for significantly reducing carbon emissions. The causality analysis unveils a bidirectional causal relationship between green investment and agricultural pollution and a unidirectional causality between green investment and carbon emissions, shedding light on the complex interplay between these variables. Also, non-renewable energy is found to increase carbon emissions in the region. The outcomes of this research contribute valuable insights and lay a foundation for future research and policymakers to enhance the future of agricultural research and sustainability. It also offers a roadmap for developing effective policies that balance the immediate needs of the agricultural sector with the imperative of long-term environmental sustainability. Finally, it has a global significance on the relevance of green initiatives to boost sustainable agriculture and reduce pollution.

Geo-political risks, uncertainty, financial development, renewable energy, and carbon intensity: Empirical evidence from countries at high geo-political risks

Geopolitical risks and uncertainty negatively affect the economy and environmental quality. High geopolitical risks and high uncertainty increase carbon emission intensity by increasing dependence on fossil fuels. However, research in this area is still in its infancy and more empirical evidence is needed to justify the causal link. This research examines the causal mechanism linking geopolitical risk, uncertainty, financial development, renewable energy, and carbon intensity in a sample of eighteen countries with high geopolitical risk between 1985 and 2021. The selected countries have a high intensity of geopolitical risks due to internal and external conflicts that have worsened in recent years. We employ cointegration techniques from Hatemi-J [1] and Maki [2] in the presence of structural breaks, fully modified ordinary least squares (FMOLS), canonical cointegration regression (CCR) models, and static time-variant Granger causality (1969) test. We find robust empirical evidence that geopolitical risk, financial development, renewable energy, uncertainty, and carbon intensity have a cointegrating relationship in the presence of structural breaks. Results from FMOLS and CCR models indicate that carbon intensity responds differently to changes in geopolitical risk, renewable energy, uncertainty, and financial development. Environmental and energy policymakers should mitigate carbon intensity through long-run rather than short-run mechanisms to achieve SDG12 and SDG13.

Does energy policy uncertainty matter for renewable energy and energy efficiency technologies? An affordable and clean energy perspective

Uncertainty can affect both macroeconomic indicators and the environment. Countries are implementing various energy policies to combat global warming, but these policies contain some uncertainties and contradictions. The environmental impact of uncertainties in energy policies is a research topic that has just begun to be investigated by researchers. This study examines the effects of energy policy uncertainty (ENERPU) on renewable energy R&D (RR&D), energy efficiency R&D (EER&D) and renewable energy consumption in the four countries with the highest RR&D expenditures (USA, Germany, Japan, and Spain). The study uses the novel multivariate quantile-on-quantile (M-QQR) approach from 2003 m1 to 2022 m9. The results of the study show: (i) The impact of ENERPU varies by quantile and country. (ii) ENERPU causes a decrease in renewable energy consumption and hinders RR&D expenditures. (iii) ENERPU increases EER&D. The Fourier quantile causality test confirms the robustness of the empirical results. Based on these findings, policymakers are recommended to minimize ENERPU and implement stable energy policies to develop the renewable energy sector and technologies.

Assessing Fiscal Sustainability with Panel Unit Root, Cointegration, and Granger Causality Tests: Evidence from the Broader Groups of Countries

Abstract The question of fiscal sustainability of countries has become one of the central topics in economic policy, especially in times of increasing public debts. One way to assess fiscal sustainability is to examine compliance with the intertemporal budget constraint, which involves testing the stationarity of government revenues and expenditures, the primary budget balance, and the first differences of public debt. Part of this approach includes testing cointegration and causality among different pairs of variables. Under this approach, the paper is focused on both first- and second-generation panel unit root tests, cointegration, and Granger causality test. This paper focuses on assessing the fiscal sustainability of four panels of countries divided by continents: Europe, Asia and Oceania, Africa, and Latin America, the Caribbean, and North America. It has been found that fiscal sustainability is present in all the broader groups of countries considered but in a weak form. Fiscal sustainability was confirmed when considering a constant in calculations, while deviations were observed among groups of countries when both a constant and trend were considered. The study serves as a starting point for a more extensive analysis of fiscal sustainability. For more accurate findings, it would be necessary to categorize countries into smaller and economically more homogeneous groups and analyze them using other fiscal sustainability methods as well.

Exchange Rate Volatility and Foreign Remittances in SAARC Countries

This study explores the relationship between exchange rate volatility and foreign remittances on the economies of SAARC countries over the period 2000 to 2023. With the ongoing debate among policymakers and researchers on this subject, the study employs the Cross-Sectional Autoregressive Distributed Lag (CS-ARDL) model to analyze data from eight SAARC nations. The variables considered include remittances, foreign reserves, trade, foreign direct investment (FDI), political stability, and GDP growth, sourced from the World Development Indicators (WDI), while exchange rate volatility is calculated using the GARCH method. The analysis involves two models. In the first model, remittances serve as the dependent variable, with exchange rate volatility, GDP growth, trade, inflation, and political stability as independent variables. In the second model, exchange rate volatility is the dependent variable, with remittances, GDP growth, trade, inflation, foreign reserves, and FDI as the independent variables. The results indicate both long-run and short-run relationships between exchange rate volatility and foreign remittances in SAARC countries. The findings show that remittances are positively associated with GDP growth and inflation, while exchange rate volatility, trade, and political stability have negative relationships with remittances. Additionally, exchange rate volatility has a positive association with inflation, while GDP growth, remittances, trade, FDI, and foreign reserves exhibit negative associations with exchange rate volatility. Granger causality tests reveal complex bidirectional and unidirectional causal relationships among the variables. These insights offer valuable implications for policymakers aiming to manage exchange rate volatility and enhance remittance inflows in the SAARC region.

Analyzing the Nexus between AI Innovation and Ecological Footprint in Nordic Region: Impact of Banking Development and Stock Market Capitalization using Panel ARDL method

This study investigates the impact of Artificial Intelligence (AI) innovation on the ecological footprint in the Nordic region from 1990 to 2020, alongside the effects of banking development, stock market capitalization, economic growth, and urbanization. Utilizing the STIRPAT model, the study incorporates cross-sectional dependence and slope homogeneity tests, revealing issues of heterogeneity and cross-sectional dependence. The analysis employs both first and second-generation panel unit root tests, confirming that the variables are free from unit root problems. Panel cointegration tests demonstrate that the variables are cointegrated in the long run. To explore the short- and long-term relationships, the study utilizes the Panel Autoregressive Distributed Lag (ARDL) model. The Panel ARDL results indicate that economic growth, stock market capitalization, and urbanization positively correlate with the ecological footprint in both the short and long run. Conversely, AI innovation and banking development negatively correlate with the ecological footprint. To validate the Panel ARDL estimations, robustness checks are performed using Fully Modified OLS, Dynamic OLS, and Fixed Effects with OLS, all of which support the initial findings. Furthermore, the study employs the D-H causality test to identify causal relationships. The results show a unidirectional causal relationship between AI innovation, stock market capitalization, urbanization, and the ecological footprint. In contrast, a bidirectional causal relationship exists between economic growth and the ecological footprint, as well as between banking development and the ecological footprint.