Causality Test Research Articles

Environmental fiscal policy and carbon emissions in Turkey: evidence from cointegration and causality analysis with structural breaks

Environmental degradation, a critical issue in academic literature, arises from multiple factors including increased carbon emissions, urbanization, industrialization, mass production, and extensive use of non-renewable energy sources. These factors notably impact sustainable economic growth and environmental quality. Globally, efforts are directed towards optimizing carbon emissions to minimize their adverse effects. This necessitates effective environmental policies. This study examines the effectiveness of Turkey's environmental policy using cointegration and causality tests that account for structural breaks. The analysis utilizes data from 1990 to 2020, the most comprehensive dataset for Turkey to date. Findings indicate that Turkey's environmental policy is effective in reducing carbon emissions, highlighting a need for policy reassessment.

The heterogeneity impacts of digital transformation, human capital, and trade openness on income and labour productivity in Vietnam

Improving labor productivity and per capita income are top priorities in Vietnam’s economic policy for the next decade. This study aims to explore the heterogeneous impacts of digital transformation, human capital, and trade openness on income and labor productivity in the Vietnamese economy from 1990 to 2018. The empirical results, obtained through the quantile regression method and Bayesian inference, unequivocally demonstrate that digital transformation and trade openness significantly promote labor productivity and income improvement. Moreover, the increase in human capital unequivocally enhances income and supports the rise in labor productivity. The Granger causality test reveals a uni-directional causality running from digital transformation to income and no causal relationship between digital transformation and labor productivity. Based on these findings, we recommend that the government and businesses should invest in and develop the Internet of Things (IoT), telecommunications, and network security infrastructure. These fundamental elements affect how well and successfully the digital transformation goes. Additionally, raising the caliber of the workforce ought to be taken into account.

The Financial Feasibility of Investing in a Sustainability Index in India

ESG is at the center of dialogue for investments, corporate governance and management. It used as an acronym for ‘Environmental, Social and Governance’ factors. The rapid rise of ESG has led to the prominence of socially responsible investing and has created a dual objective for investor’s capital. Researchers have previously studied the volatility of sustainable investments and whether SRI affects portfolio performance. Analyzing the financial feasibility of investing in a sustainability index was done by utilizing the historical data of returns on BSE ESG Index, NIFTY 500 Index and the BSE ESG 100 Index from October 2017 to April 2024. S&P BSE 100 ESG Index was used as a proxy for a sustainability index and the S&P BSE 100 Index was the index used to proxy traditional investments. This study has utilized financial ratios along with EGARCH and Granger causality test to understand the risk-reward characteristics of sustainable investments and compare them with traditional investments to understand whether it is financially viable to be a sustainably responsible investor. T test was conducted to identify whether is a significant difference between the returns of the sustainability index and its parent index. Results suggest that the sustainability index has a lower risk-adjusted return than traditional investments however, there is not a significant difference between the returns of the sustainability index and its parent index. There is a presence of strong persistent volatility in the sustainability index and negative shocks have a greater impact on the volatility of the index. Data also suggests a bi-directional relationship between the S&P 500 ESG Index and India’s sustainability index. The study recommends investors to consider the cost associated with investing in sustainability themed instruments while also taking into considerations the factors which are responsible for volatility of sustainable investments as well as the asymmetrical impact of negative shocks on returns.

The Business Cycle and the Financial Cycle: Granger Causality for the Peruvian Economy, 2000 – 2019

It is relevant to know the relationship between the financial and business cycles to prevent the appearance of financial crises and their negative effects on the macroeconomy. In this sense, a better understanding of the links between financial cycles and the business cycle of Peru can provide valuable information for economic and macroprudential policy decisions. This study examines the causal relationship between Peru's financial and business cycles. The dynamic factors methodology is used to measure the financial cycle, taking four representative indicators of the financial sector: Volume of loans to the private sector (credit market), the Lima Stock Exchange General Index (stock market), Embig Peru (bond market), and the Exchange Rate (currency market) (Ramos, 2019). On the one hand, using the Granger causality test in the frequency domain, it was found that the financial cycle causes the business cycle at frequencies greater than 10 quarters (2.5 years). In contrast, the business cycle does not cause the financial cycle.

Corruption in Namibia: Examining the Nexus Between Survey-Identified Causes and Empirical Validation

This study investigates the causal relationship between the factors identified in the 2016 National Corruption Perception Survey Report and corruption levels in Namibia. By analysing data from 2000 to 2022, the Toda-Yamamoto VAR Granger causality test was employed to investigate the impact of greed, poor leadership and law enforcement, poverty (working poverty), and poor pay (compensation to employees) on corruption levels. The results revealed statistically significant causal linkages between greed, poor leadership and law enforcement, and poverty. Poor pay, however, showed no significant causal influence on corruption. These findings highlight the necessity of tackling issues such as equal income distribution, poverty, and governance inadequacies in anti-corruption initiatives. Targeted measures based on empirical evidence can effectively reduce corruption and increase transparency in governance. Additionally, conducting more recent corruption surveys in Namibia could yield up-to-date perceptions that could be adopted in similar country-specific studies elsewhere.

Harberger-Laursen-Metzler Hypothesis: An Analysis with ARDL Bounds Test Approach

The Harberger, Laursen, and Metzler (HLM) hypothesis posits that a positive (negative) change in terms of trade, ceteris paribus, will lead to positive (negative) movements in the trade balance. When tested on developing countries, the hypothesis yields varying results. Some studies validate the hypothesis, while others suggest it is not applicable. Additionally, causality tests examining long-term relationships also produce different outcomes. Türkiye ranks among the countries with significant trade deficit issues. Therefore, testing the validity of the HLM hypothesis in the context of Türkiye is of great importance. The motivation of this study is to examine the impact of changes in terms of trade on the long-term trade balance in Türkiye from 2013 to 2023. In this context, both the volume and unit value of the terms of trade are considered. According to the findings, there is a positive relationship from terms of trade to the trade balance. Short-term deviations are found to be corrected within approximately three months. The causality test indicates that terms of trade are a Granger cause of the trade balance, and this causality is unidirectional. In this study, Türkiye's terms of trade and trade balance data for the specified periods were meticulously analyzed, and the validity of the HLM hypothesis was carefully tested. The analysis results provide strong evidence supporting the HLM hypothesis. These findings offer significant insights for Türkiye's economy and trade policies.

Unveiling the synergy: How natural resources, energy prices and financial development drive the energy transition in N‐11 countries

AbstractThe energy transition (ET) is one of the major components of achieving the Sustainable Development Goal (SDG) 7. Based on the growing recognition of the need for sustainable energy, this study aims to investigate the influence of natural resource rent, energy prices (EPs), financial development (FD), trade and economic growth on the ET from 1990 to 2021 in N‐11 countries. The study employed the Fully Modified Ordinary Least Squares and Dynamic Ordinary Least Squares techniques for the panel data analysis. These test findings revealed that natural resources rent, EPs, trade and economic growth are positively and significantly associated with ET. It indicates that these factors' are essential in promoting the shift towards renewable and sustainable energy sources. Whereas FD has a negative relationship with the ET, which underscores the need for targeted interventions and policy measures to address the challenges faced by financial systems. Moreover, the Pairwise Dumitrescu Hurlin panel causality test results declared the bidirectional association between natural resources and FD, economic growth and EPs and trade with all other variables. The study's outcomes suggest policy implications to promote and accelerate the ET process towards a greener and more sustainable future.

Exploring the Relationship between Clean Energy Indices and Oil Prices: a Ten-Day Window approach

This paper aims to assess the comovements between clean energy indices, namely the Clean Energy Fuels (CLNE), Nasdaq Clean Edge Green Energy (CELS), S&P Global Clean Energy (SPGTCLEN), TISDALE Clean Energy (TCEC.CN), Wilderhill (ECO), West Texas Intermediate (WTI) stock indices, over the period from 1 January 2018 to 23 November 2023. We used 10-day windows to analyse the duration and nature of the shocks. Granger causality tests revealed that 20 of the 30 possible pairs showed significant movements, with the WTI influencing all the clean energy indices, highlighting its global importance. CELS also showed a robust influence on all pairs, while SPGTCLEN had a significant but less far-reaching influence. The CLNE and ECO indices showed limited influences, suggesting the potential for diversification, the TCEC.CN proved to be independent and a determining factor for portfolio diversification. The Impulse Response Functions (IRF) confirmed significant movements between CELS, SPGTCLEN and WTI, reflecting the market's response to policies and adjustments in expectations. Fluctuations in oil prices substantially affect clean energy indices, highlighting the interconnectedness and volatility of these markets. In conclusion, these results indicate that despite the growth of clean energy, the sector is still influenced by fluctuations in the fossil fuel market.

Price Dynamics and Integration of Onion Markets in India

The current study uses the Correlation matrix, Vector Auto Regressive model, Granger causality test and Instability index to investigate the level of market integration, price transmission and price instability in the key onion markets in India, namely, Azadpur, Bangalore, Belgaum, Hassan, Haveri, Hubli, Mysore, and Nashik. The findings provided substantial evidence for the co-integration and interdependence of these markets. Bangalore market has a positive relationship with the Nashik and Azadpur markets, with coefficients of 1.15 and 0.54, respectively. Bangalore and Belgaum displayed a solid, significant positive correlation with a coefficient of 0.770. Conversely, some markets show relatively weaker correlations, such as Azadpur and Hassan, with a coefficient of 0.389. Instability across major onion markets revealed that all the markets are volatile, as the instability index was more than 30 per cent. Since there is unidirectional causality from Hubli-Bangalore and Azadpur-Bangalore market pairs, it makes it necessary for future research to examine the influence of internal and external factors like market infrastructure, improving information technology to allow regular flow of market information to assist farmers in increasing their income. Keywords: Granger causality, instability, price transmission, price volatility. JEL Codes: B23, C01, C22, E31.

Natural resources and economic growth: Examining the role of globalization, financial development, and digitalization in India

Natural resources are considered vital for economic growth, laying the foundations for various industries. Therefore, the present study aims to examine the importance of natural resources, globalization, financial development, and digitalization in India's economic performance from 1970 to 2020. The study utilizes the Auto-regressive distributed lag (ARDL) techniques with structural breaks and the Granger causality test to detect the direction of causality. Further, Fully Modified Ordinary Least Square (FMOLS) and Dynamic Ordinary Least Square (DOLS) were used to check the robustness of the long-run coefficients. The finding supports the “Resource curse hypothesis” in India. Globalization and financial development drive the long-run growth performance. In the short run, digitalization and globalization enhance growth performance. The Granger causality result unfolds a bidirectional causal relationship between economic growth and digitalization and unidirectional causation from financial development and globalization to economic growth. The study's outcomes have notable policy implications that emphasize the need to induce financial development, integrate digital technology into core sectors of the economy, and encourage market openness and efficient utilization and management of natural resources for sustainable economic growth.

Crude oil futures and the short-term price predictability of petroleum products

This study investigates the lead-lag effect between crude oil futures and petroleum products from the view of price predictability. The findings of the Granger causality test provide evidence for the leading role of crude oil futures. Further empirical results show that crude oil futures demonstrate strong predictive power for petroleum products both in- and out-of-sample, and this predictability is a short-term phenomenon. During economic recessions, petroleum product prices exhibit stronger predictability, with out-of-sample R2 reaching a maximum of 39.161 %. Additionally, the outstanding forecasting performance remains robust across a range of settings. Finally, two potential economic sources underlying the lead-lag relationship between crude oil and petroleum product markets are provided: the differential response speed to common energy market information and the perspective of raw material supply.

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.

Modeling of Brazilian Wind Power Generation Capacity: A Multivariate Analysis with Neural Networks

Over the last twenty years, Brazil has experienced significant changes in its electric energy matrix, notably with the expansion of wind and solar energy sources. In the early 2000s, hydroelectric plants with a capacity of 70 gigawatts (GW) were responsible for generating 90% of the country's electricity, while solar and wind sources contributed merely 1%. Today, the scenario has evolved, with wind and solar energy comprising approximately 25% of the national generation, indicating a departure from the previous hydro-dominated matrix. This research aims to apply specific types of neural networks to multivariate data to forecast Brazil's wind power generation capacity, providing insight into the potential for future energy strategies. This research contributes as a as a decision support tool contemplating relevant information for analysts, researchers, and participants in the renewable energy market. The monetary volume destined to import key components of the wind, considering specific time lags, was utilized to forecast the Installed capacity of the wind farms in Brazil. The Toda-Yamamoto Causality Tests revealed unidirectional Granger causality in the sense of the Import variable for the Brazilian Installed Capacity variable for wind energy production. Another result obtained was the finding that the variable that matters most in the multivariate configuration of the Neural Network is the variation in Installed Capacity in megawatts, followed by the import volume of wind energy components, which exhibited critical lags at 3 and 6 months.

Unraveling The Dynamics Of Foreign Direct Investment And Economic Activity In Brazil: A Copula-Based Analysis

This study analyzes the relationship between FDI and the IBC-Br from 2003 to 2022. Our objective is to examine the effect of FDI on Brazil´s economic activities. Thus, we look also for a connection between the Brazilian Central Bank’s leadership in each period and the FDI effect on IBC-Br. To explore this, we employ an approach based on the Granger Causality Test and copula models that encompass Gaussian, t-Student, Gumbel, Frank, and Clayton functions. Our findings indicate that in the short term, FDI exerts some influence on IBC-Br, while the reverse relationship is not observed. Furthermore, using the Clayton Copula function, we identify the dependency of causal relationships between the variables, particularly in extreme economic scenarios. These discoveries contribute to a more comprehensive understanding of the dynamics between FDI and economic activity in the different periods of the Brazilian Central Bank’s leadership.

A Comprehensive Analysis of Remittances and Basic Level Government School Enrollment in Nepal

This study aims to examine the factors that impact student enrollment in government schools at the basic level in Nepal. The data were collected from secondary sources publication over the periods of 2000-2022. The Autoregressive Distributed Lag (ARDL) model was applied to analyze the correlations between enrollment and economic factors, such as per capita GDP, population growth, and remittances, in both the short-term and long-term. The results suggest that remittances have a significant negative impact on enrollment, raising concerns about the absence of parents due to working abroad. On the other hand, the level of per capita GDP had a positive effect on the accessibility of education, highlighting the importance of economic development. The population growth did not have a significant impact in this model. The co-integration test suggests a strong and lasting connection between the variables, while the Granger causality tests reveal that remittances and per capita GDP had a significant impact on enrollment. These findings offer valuable insights for policymakers aiming to improve access to high-quality education for every child in Nepal. The paper also discussed potential areas for future research, such as investigating the underlying causes of the negative impacts of remittances and addressing the issue of serial correlation in the model.

Economic cointegration of the North American agricultural sector

Objective: To determine if the Mexican, Canadian, and American agricultural industries are cointegrated. Methodology: Six cointegration tests were carried out between the Mexican, Canadian, and American agricultural, forestry, fishing, and hunting industries, as well as the Mexican animal husbandry and exploitation sector. The USA was the independent variable in all cases. Results: The Mexican sector, with an α of 5% (with and without trend) is not cointegrated with the USA and Canada, while Canada and the USA, with an α of 5% (with and without trend) are cointegrated. Study Limitations/Implications: The agricultural sector of the three countries were not analyzed separately and the Engle-Granger causality test was not used. Although some products from Mexico's agricultural sector have managed to make inroads in the USA and Canada, further advances are still possible. Therefore, there are areas of improvement for Mexican products. Likewise, NAFTA and the USMCA/CUSMA have failed to achieve their objective of cointegrating the agricultural sectors of the three nations. Conclusions: The Mexican sector was not cointegrated with the American and Canadian sectors during the analysis period —i.e., the Mexican sector is not influenced by and does not have the same long-term behavior (with delays) than the USA and Canadian sectors. However, the Canadian sector is cointegrated with the USA sector —i.e., the Canadian sector is influenced and has the same long-term behavior than the USA sector.

Extreme Risk Spillovers From US Soybean Futures Market to China's Soybean‐Linked Futures Markets

ABSTRACTThis study investigates the cross‐border risk spillovers between the US soybean futures market and Chinese soybean‐related futures markets. We first confirm the existence of strong tail dependence between US soybean futures and four Chinese soybean‐related futures by conducting a novel quantile‐Granger causality test. Second, tests under MVMQ‐CAViaR further provide evidence of risk spillovers from CBOT soybean futures to the DCE No.1 soybean, No.2 soybean, soybean meal, and soybean oil futures in value‐at‐risk at different quantiles. Lastly, results from the quantile impulse‐response function reveal the time‐varying and asymmetric property of risk spillover effects. In addition, we compare the results from two subsample periods and identify different risk spillover effects across markets at different quantiles that may contribute to the investors' decision‐making under extreme market conditions.

Is trade relevant to the macro drivers of carbon dioxide emissions? A study of high‐ and low‐trade openness economies

AbstractThe objective of this research is to systematically compare the impact of macro determinants on CO2 emissions, using the theoretical frameworks of trade, the Environmental Kuznets Curve, and the Pollution Haven Hypothesis. The study specifically focuses on high‐ and low‐trade‐openness economies from 1995 to 2020. Methodologies employed include stepwise regression, fully modified least squares, pooled ordinary least squares, and fixed effects models. Long‐run dynamics were assessed using Granger causality tests and Pedroni and Johansen cointegration tests. The results indicate both long‐term and short‐term relationships between CO2 emissions and the following variables: (i) gross capital formation (GCF), (ii) per capita income (PCI), (iii) population (POP), and (iv) trade openness. Trade openness has a positive and significant effect on CO2 emissions in highly trade openness economies, whereas it has a negative effect in low trade‐open economies. Highly open economies are more significantly impacted by GCF and POP on CO2 emissions compared with low‐ trade openness economies. Additionally, PCI positively and significantly influences CO2 emissions in low‐ trade openness countries, and this effect is greater than in high‐ trade openness economies. The study also identifies a bidirectional causal relationship between PCI, GCF, and CO2 emissions in both groups of economies, as well as a unidirectional relationship between trade openness, POP, and CO2 emissions in both high‐ and low‐ trade openness countries.

How do global commodities react to increasing geopolitical risks? New insights into the Russia-Ukraine and Palestine-Israel conflicts

The present study examines the impact of geopolitical risk on global commodities returns by including both major conflicts spanning from January 3, 2023 to December 18, 2023 to cover both the Russia-Ukraine and Palestine-Israel wars. Our study utilizes the QVAR model, the Quantile-on-Quantile regression (QQR) and the frequency causality test. Surprisingly, during the pre-conflict period, our findings reveal a weak positive influence of GPR on commodities, indicating their resilience to extreme negative shocks. Variance decompositions further highlight the limited role of GPR in explaining the commodity price variance. The spillover analysis highlights a low interconnectedness between GPR and commodities, demonstrating a high hedging effectiveness against expected negative GPR shocks. The heterogeneous reaction of commodities to extremely positive GPR shocks suggests diverse responses, emphasizing the need for nuanced investment strategies. Conversely, during the crisis periods, commodities exhibit a resilience to both negative and positive shocks from geopolitical tensions, therefore, presenting diversification opportunities for investors. The causality frequency analysis emphasizes the complex dynamics between GPR and commodities in both the time and frequency domains. Our study also offers significant implications for investors, portfolio managers, and policymakers, advocating for recognition of the weak pre-conflict link between GPR and commodities.

Sustainable Energy Usage for Africa: The Role of Foreign Direct Investment in Green Growth Practices to Mitigate CO2 Emissions

In line with Africa’s commitment to keeping up with the United Nations Framework Convention on Climate Change, achieving a sustainable future requires balancing economic growth with environmental sustainability. This study investigates the long-term impacts of foreign direct investment, economic growth, agricultural production, and energy consumption on CO2 emissions across 43 African nations from 1990 to 2021. Despite significant research on the individual effects of these factors, the combined influence on CO2 emissions remains underexplored. Addressing this gap, this study employs cross-sectional augmented distributed lag estimators (CS-DL and AMG) and updated estimation packages to effectively examine the relationships between variables. Our findings are as follows: firstly, economic growth and energy use was shown to have a significant positive influence on CO2 in the long term. Also, foreign direct investment significantly promotes CO2 emissions. Secondly, the causality test shows a unidirectional causal relationship between CO2 emissions and foreign direct investment. The test also revealed a bidirectional relationship between GDP and CO2 emissions, as well as between energy consumption and CO2 emissions. Again, a bidirectional causation was observed between agricultural production and CO2 emissions. Thirdly, the impulse response analysis shows that GDP will contribute more to emissions over the 10-year forecast period. This study also proposes policy implications to lessen CO2 across the continent and advocates for the judicious adoption of existing policy frameworks like the 2030 Agenda for environmental Sustainability.