Granger Causality Relationship Research Articles

The Effect of Interest Rates on Portfolio Investments and Foreign Direct Investments in Türkiye

This study aims to analyse the relationship between foreign direct investments (FDI) and portfolio investments (PI) and interest rates. Firstly, ADF and PP unit root tests were applied to determine whether the variables were stationary or not. Since the series became stationary at different levels, the ARDL (Autoregressive Distributed Lag Bound Test) test, one of the cointegration tests, was applied. Afterward, Toda-Yamamoto tests were utilized to determine whether there is causality between the variables and if there is a causality relationship, to determine its directions. According to the ARDL bound test results, it is concluded that there is no short-term asymmetric relationship between PI and other independent variables. In other words, there is no statistically significant relationship between PI and EUR, USD and TL interest rates. On the other hand, it is concluded that the FDI dependent variable and other independent variables are long-run cointegrated in the relevant period. According to the results of the Toda-Yamamoto causality test where FDI and TL, EUR, and USD are independent variables, it is concluded that there is a Granger causality relationship between FDI and TL and EUR interest rates.

Saudi Arabia’s Green Vision: Examining the Kingdom’s Path to Sustainability, Covering Energy, Economy, Tourism, and Carbon Dynamics

This study examines the Green Vision of Saudi Arabia and its efforts towards achieving sustainability in various domains such as energy, economy, tourism, and carbon emissions. The research uses time-series data from 2002 to 2020 to analyze the dynamic impacts of these variables. To achieve this, it employs a co-integration regression test, Granger causality relationships, and one-way and two-way causal effects between carbon emissions, tourism, economic growth, and energy use. The findings of the study provide valuable insights into the challenges and opportunities for sustainability in the kingdom, considering the goals of SDGs 8 and 13. This research contributes to the ongoing discourse on sustainable development in Saudi Arabia and offers significant insights for lawmakers, entrepreneurs, and researchers to influence the country's future direction. The research aims to guide strategic decision-making in line with Saudi Arabia's commitment to achieving a sustainable and resilient future by examining the interconnections between energy, economic growth, tourism, and carbon emissions.

IS THERE A CHICKEN-AND-EGG RELATIONSHIP BETWEEN INTEREST AND INFLATION RATES FOR THE TURKISH CASE?

There is still a hot debate about the causal relationship between interest and inflation rates. On the one hand, through Fisher Effect, it is expected that inflation is the cause while the interest rate is the result. On the other hand, among policymakers in Türkiye, it is expected opposite as inflation is the result and interest rate is the cause since it is argued that inflation is the result mostly stemming from the high-interest rates constituting the high cost of the credits. However, it is strongly argued that low interest rates—which the government has lowered below inflation—rather than high interest rates are the real cause in the Turkish case. In this regard, the key purpose of the paper is to investigate the causal relationship between the interest and inflation rates for the Turkish case for the period of 2004M01-2022M03. The findings reveal that there is a bi-directional Granger causality relationship between the interest rate and the inflation rate for the Turkish case for the relevant period. This result promotes the chicken-and-egg relationship between interest and inflation rates.

HAS THE SUBSTITUTABILITY OF MILK PRODUCTS IN KOREA CHANGED? EVIDENCE FROM THE PRICE ANALYSIS AMONG DOMESTIC FRESH, IMPORTED STERILIZED AND SOYBEAN MILK

This study investigates the price relationship between domestic fresh milk, imported sterilized milk and soybean milk in Korea to analyze the possible substitutable relationship among them. We divided the periods into 2012–2017, 2018–2021 and 2012–2021 (total sample) and utilized the Granger causality test and Geweke’s (1982) method to capture the recent increase in milk import trends in Korea. Our results show that the price causal relationship has changed by comparing 2012–2017 and 2018–2021 periods. While we did not find any Granger causal relationship in 2012–2017, our results show that fresh milk prices are directly and indirectly affected by soybean milk and imported sterilized milk prices, respectively. Our results also present bidirectional Granger causation between imported and soybean milk; however, causal dominance exists in the direction of soybean to imported milk prices based on the Geweke (1982) approach. Our findings imply that the consumption substitutability of fresh milk has changed, and the government of Korea should consider this changed substitutability to reconstruct the volume of the milk production quota to support Korean milk farmers.

BANKING SECTOR DEVELOPMENT AND ECONOMIC GROWTH DEVELOPING COUNTRIES: A BOOTSTRAP PANEL GRANGER CAUSALITY ANALYSIS

The purpose of this paper is to revisit the Granger causal relationship between banking sector development and economic growth for forty developing countries in the period 1970-2012. We devised two indices to comprehensively assess the development of the banking sector and employed a panel bootstrapped approach for Granger causality testing. This method adequately addresses concerns related to cross-sectional dependence and heterogeneity. Our empirical findings offer modest backing for the supply-leading, demand-following, and complementarity hypotheses. Moreover, our analysis suggests a causal relationship between banking sector development and economic growth across twenty-five countries. This paper investigates the relationship between banking sector development and economic growth in developing countries using a Bootstrap Panel Granger Causality Analysis. The banking sector plays a crucial role in fostering economic development by mobilizing savings, allocating capital efficiently, and channeling investments into productive sectors. However, the precise nature of the causal linkages between banking sector development and economic growth remains subject to empirical scrutiny, particularly in the context of developing economies characterized by diverse institutional settings and economic structures. Employing a panel data approach, this study examines the causal dynamics between banking sector development and economic growth across a sample of developing countries. By leveraging the richness of cross-country variation and time-series dynamics, we aim to provide a nuanced understanding of the symbiotic relationship between banking sector development and economic growth. Our discoveries illuminate the causal connection between banking sector advancement and economic growth in developing nations, presenting significant insights for policymakers, economists, and scholars. Through informing policy discussions and promoting data-driven decision-making, this research contributes to the crucial goals of sustainable development and inclusive growth in developing economies.

Heterogeneous dependence of the FinTech Index with Global Systemically Important Banks (G-SIBs)

This paper aims to investigate the Granger causality relationship in quantile between the FinTech Index and globally systemically important banks (G-SIBs). The result was observed that at the median and under conditions of extreme quantiles in the FinTech Index, there was no Granger causality relationship between the FinTech Index and the vast majority of systemically important banks. Our research offered vital insights to regulatory agencies, highlighting the importance of monitoring market conditions at higher or lower quantiles to prevent the impact of financial technology on G-SIBs and to maintain global financial stability.

Energy-growth nexus in Australia and New Zealand for the past 150years-evidence from time-varying and quantile Granger causality analysis.

Using historical data on energy from (Malanima 2020) and GDP from the Maddison Project Database, this paper investigates the energy-growth nexus in a less-studied region, mainly Australia and New Zealand, since 1870. The long annual series allow meaningful application of recently developed time-varying and quantile Granger causality analysis. Results indicate that there is a bi-directional Granger causal relationship between economic growth and energy, coal, and oil consumption at both ends of the distribution, and during various time periods over the past 150years. Little evidence is found on the Granger causal relationship from gas consumption to economic growth, but some evidence on the direction from economic growth to gas consumption. The Granger causal relationships between electricity consumption and GDP change over time, but results suggest much closer links between the two in most recent decades, and big (positive and negative) changes in electricity consumption significantly Granger causes economic growth.

The Unseen Ripples: Examining the Links Between COVID-19-induced Disruptions and Trade Dynamics in Asia-Pacific Countries

The global COVID-19 epidemic and the strategies that were adopted to restrict its spread, such as lockdowns, had a significant impact on international trade. While the health crisis and the lockdown restrictions were linked, their repercussions on world trade patterns were distinct. This study examines trade data from 30 Asian-Pacific countries to examine how the COVID-19 pandemic affected their trading patterns. In addition, it looks at the effects of COVID-19-related policies on trade flows and explores the causality between changes in trade flows and policies induced by COVID-19. The cross-sectionally augmented autoregressive distributed lag (CS-ARDL) model, Juodis, Karavias, and Sarafidis (JKS) causality test and Dumitrescu–Hurlin causality test were employed to examine trade patterns of the Asia-Pacific amidst the COVID-19 pandemic. The results of CS-ARDL model showed that COVID-19 cases, deaths and policy-related indices induced a noteworthy and negative influence on export and import flows of Asia and Pacific both in the short- and long run. However, with few exceptions, on average, the impact of COVID-19-related measures is far bigger than that of COVID-19 deaths as well as cases in the long run. Further, the study found that the COVID-19 cases, deaths and COVID-19 policy-related measures have a Granger-causal relationship with exports and imports. Therefore, fostering regional cooperation, strengthening trade agreements and prudent management of COVID-19-induced policies will be essential in a crisis like COVID-19 to streamline trade processes and to achieve the optimum level of exports and imports.

The role of outward foreign direct investment as a filter for high energy intensity economies in the European Union

This study examines the effects of outward foreign direct investment (FDI) on energy intensity among the member countries of the European Union between 2000 and 2021. This relationship is deemed important in elucidating whether there is a process of filtering out energy-intensive companies where the use of FDI is employed to lead out production and improve energy intensity in the source country of the investment. To estimate this relationship, we employ feasible generalized least squares (FGLS) and panel corrected standard error (PCSE) for robustness purposes. Additionally, we complement our results with an estimation of the Granger causality relationships between our variables. Our findings reveal a highly significant trend wherein outward FDI from European Union countries tends to reduce energy intensity, thereby enhancing the productivity of the source countries of the investment. Conversely, only the technological productivity ratio exhibits a unidirectional causal relationship with energy intensity, while GDP per capita and natural resource rents serve as causes of energy intensity and vice versa. From this study, some policy recommendations can be derived whereby the European Union can continue to incentivize this filtering process to ensure better technological advancement in its production system, thereby improving the efficiency of the European industrial fabric.

Causality relationship between bank indices: an application on selected countries

Purpose- If price volatility in one stock exchange has an impact on other stock exchanges, this is called volatility spillover effect. Along with volatility, the change in returns in one stock exchange can also affect other stock exchanges in the short term. This situation is called interconnectedness, co-movement and furthermore, interdependence of stock markets. Therefore, this study aims to investigate the causality relationship between the bank indices of the 5 countries with the highest income (USA, China, Japan, Germany and India) in 2022 according to IMF data. Methodology- In the study, the daily frequency data set between 04/01/2018 -16/11/2023 was used. In the analysis phase, firstly, ADF and PP unit root tests were applied to determine whether the variables are stationary or not. Causality relationships between variables were tried to be determined by Granger Causality test. Findings- When the relationship between the bank indices of the 5 major economies subject to the research is analysed, a granger causality relationship was found between DAX variable and FTSE, TR INDIA and NIKKEI, between FTSE index and NASDAQ and NIKKEI, between TR INDIA and NIKKEI. Conclusion- Ülke borsası arasında bağımlılık ilişkilerinin kendini göstermesi ve konjonktür dalgalarının bu sürece etki etmesi, finans piyasasında alınan kararlar ile ortaya çıkan etkilerin diğer finans piyasasına etki edebileceğini ve bu doğrultuda da yatırımcı hareketlerini yönlendirebileceğini göstermesi bakımından oldukça önemlidir. Keywords: International stock exchanges, bank indices, Granger Causality Test JEL Codes: C22, G15, G20

Examining the relationship between bitcoin and altcoins

Purpose- The purpose of this study is to examine the long and short-term relationship between Bitcoin and altcoins selected based on their market capitalization through an empirical analysis. For this purpose, the daily data of Bitcoin and nine altcoins consisting of Ether, Ripple, Tether, Litecoin, Monero, Stellar, Dash, Nem, Dogecoin for the period 07/08/2015-08/01/2020 were used. Methodology- The long-run relationship between Bitcoin and altcoins is first analyzed by Vector Autoregression (VAR) analysis. Granger causality test was utilized to determine the short-run causality relationship between the variables. The tests were conducted with the Eviews program. Findings- According to the results of the VAR analysis conducted to investigate the long-run relationship, there is a long-run relationship between Dogecoin, Dash, Litecoin, Nem, Stellar and Ripple and Bitcoin. After determining the long-run relationship between the variables, the relationships between the variables were analyzed with the help of impulse response functions. Impulse response function shows the effect of a one-unit shock to one variable on the other variable. Accordingly, when the results of impulse response functions are analyzed; it is seen that a one-unit random shock in Bitcoin has a negative effect on Ripple, Nem, Litecoin, Dash, Litecoin, Dogecoin in the first two periods, the effect decreases in the second period, and this effect disappears in the third period. A random shock to Bitcoin causes a positive effect on Stellar that lasts for two periods. This positive effect ends in the third period. After analyzing the relationship between Bitcoin and altcoins with impulse response functions, the source of the changes in the variance of the variables is analyzed through variance decomposition. According to the variance decomposition results, the effect of Bitcoin on Dogecoin is 25% in the first period and 22% in the other periods. The variance decomposition of Dash shows that approximately 18% of the change in standard deviation was caused by Bitcoin in the first period and this percentage increased to 25.5% in the following periods. Litecoin's variance decomposition results show that 33% of the change in standard deviation from the first period to the last period was caused by Bitcoin. It is observed that approximately 8% of the change in Nem's standard deviation in the first period was caused by Bitcoin, while this rate increased to 21.5% in the last period. From the first period to the last period, 13.5% of the change in Stellar's standard deviation was caused by Bitcoin. When the variance decomposition of Ripple is analyzed, it is observed that 10% of the difference in the standard deviation is due to Bitcoin. This situation continued similarly from the first period to the last period. Following the VAR analysis, Granger causality test was conducted to explain the short-term relationship between the variables. According to the test results, there is a bidirectional Granger causality between Bitcoin and all altcoins. Accordingly, when Bitcoin is taken as the dependent variable, it is the Granger cause of Ether, Ripple, Tether, Litecoin, Monero, Stellar, Dash, Nem, Dogecoin. When the Granger causality relationship between altcoins is analyzed, a causality relationship was observed from Tether to Stellar, while no causality was found from Stellar to Tether. Similarly, while Granger causality is observed from Tether to Ripple, there is no causality from Ripple to Tether. The variance decomposition of Stellar and Ripple shows that Tether does not contribute to the change in standard deviation. The variance decomposition test supports the Granger test results. All altcoin variables except these are Granger causes of each other. Conclusion- At the end of the study, according to the results of the VAR analysis to determine the long-run relationship, there is a long-run relationship between Dogecoin, Dash, Litecoin, Nem, Stellar and Ripple and Bitcoin. There is no long-run relationship between Tether, Monero, Ether and Bitcoin. According to the Granger causality analysis test results conducted to observe the short-term relationship, there is a bidirectional Granger causality between Bitcoin and all altcoins. Accordingly, when Bitcoin is taken as the dependent variable, it is the Granger cause of Ether, Ripple, Tether, Litecoin, Monero, Stellar, Dash, Nem, Dogecoin. As a result, it is observed that Bitcoin has a short-term relationship with all 9 altcoins subject to the study, and a long-term relationship with Dogecoin, Dash, Litecoin, Nem, Stellar and Ripple. These results show that the price movements in Bitcoin have an impact on altcoins. Keywords: Bitcoin, altcoin, cryptocurrency, causality analysis, VAR analysis. JEL Codes: G17, G10, C58

Revisit the impact of exchange rate on stock market returns during the pandemic period

This study revisits the Grange causality between the Taiwan stock exchange weighted index and new Taiwan dollars by exploiting a novel approach, cross-quantilogram from January 30, 2020 – December 30, 2022 (a total of 722 days). Our findings show that the negative granger causality relationship from the new Taiwan dollars to the Taiwan stock market is obtained, and the persistence of this phenomena only for one day. This evidence not only supports the flow-oriented hypothesis, but also provides investors, practitioners, and government with important implications.

COVID-19 Pandemic and Stock Market Contagion Between the Chinese Mainland and Hong Kong

This study utilizes stock market data from March 2020 to December 2022, employing VAR models and Granger causality models to investigate the daily returns and contagion effect of the CSI 300 and the HSI in Hong Kong. Based on this, the analysis explores the impact of the pandemic on the contagion effect between the mainland Chinese and Hong Kong stock markets. The research findings indicate that during the pandemic period, there exists a unidirectional Granger causality relationship from the Hong Kong stock market to the mainland Chinese stock market. The pandemic has intensified the connection between mainland China and Hong Kong, significantly increasing their mutual influence. The overall trends of the two stock markets are consistent, with the mainland Chinese market exhibiting smoother fluctuations during this period.

The dynamic causality between Chinese and ASEAN stock markets

COVID-19 has caused severe shocks to the Chinese and ASEAN stock markets. This paper investigates the relationship between the Chinese and ASEAN stock markets using the bootstrap rolling-window causality test. The results show that there is a bidirectional Granger causality relationship between the Chinese and ASEAN stock markets with time-varying characteristics. Before the COVID-19 outbreak, the interaction between the Chinese and ASEAN stock markets was mainly positive. After the COVID-19 outbreak, during the off-peak period, the interaction between the Chinese and ASEAN stock markets was positive or negative at different periods; during the peak period of the epidemic, the ASEAN stock markets had negative impacts on the Chinese stock market. In addition, the relationship between the Chinese and ASEAN stock markets was enhanced during COVID-19. According to the interaction mechanism, economic and political factors would affect the relationship between the Chinese and ASEAN stock markets, but major events such as COVID-19 have a greater impact. Therefore, macroeconomic policy should play a positive role in the stock market.

Does social communication make investors stay in the market?

Abstract The role of online discussions in rallying investors has been highlighted by the GameStop frenzy of 2021. We know little, however, about the effect of online discussions on investor survivorship. Previous studies have emphasized the role of communication with respect to market entry, but not with respect to market survival. Survivorship studies, in turn, have largely focused on the role of financial factors in the investors’ decision to quit trading, but have not investigated so far how social interactions and communication impact the decision to quit or stay. Using a dataset covering 1.1 million observations for 4,731 traders over 18 months, we examine the role of online discussions in traders’ decisions to stay in the market. We find that traders who actively engage in them tend to be 16 per cent to 30 per cent less likely to quit trading. We identify a positive Granger-causal relationship between online discussions and the probability of survival. Our results are robust to alternative measures of communication and different sets of control variables. Based on this evidence, we draw attention to the necessity of studying the nexus between finance and social media as an important component of platform capitalism.

Contagion Effect Between Bombay Stock Exchange (BSE), National Stock Exchange (NSE) and Nasdaq

This comprehensive study investigates the contagion effect and relationships among three major stock exchanges—specifically, the two largest stock exchanges in India, BSE (Bombay Stock Exchange) and NSE (National Stock Exchange), and the globally renowned NASDAQ—spanning an extensive eight-year period on a daily basis. Employing a robust analytical framework in E-views, the study conducts a suite of tests, including Unit Root tests, Granger causality analysis, Johansen's Cointegration test, Vector Error Correction Models (VECM), and Dynamic Ordinary Least Squares (DOLS). The results of our investigation reveal a significant cointegration among BSE, NSE, and NASDAQ, indicating a long-term relationship between these stock exchanges. Notably, the study establishes that BSE Granger causes NSE, given their shared national context. Moreover, in an international context, NASDAQ emerges as a Granger cause for both BSE and NSE, while NSE Granger causes NASDAQ. This nuanced understanding of Granger causality relationships has profound implications for investors seeking to optimize their portfolios. Importantly, our findings suggest a viable strategy for portfolio diversification, emphasizing the potential benefits of allocating investments across stock exchanges with limited correlation. Specifically, investors can strategically diversify their portfolios by considering exchanges that do not exhibit Granger causality relationships with each other. This insight provides a practical guide for investors looking to capitalize on opportunities in markets with distinct and uncorrelated movements, thereby enhancing the effectiveness of international portfolio diversification. In essence, this study underscores the feasibility of diversification between exchanges with no observed Granger causality relationships, shedding light on the nuanced dynamics of inter-market dependencies. Investors can leverage these findings to make informed decisions, mitigating risks, and capitalizing on diverse opportunities across global financial markets.

Compliance relationship analysis between environmental governance attention and environmental quality in the Beijing–Tianjin–Hebei region

This study analyzes the changes and allocation characteristics of environmental governance attention in the Beijing–Tianjin–Hebei region based on the government work report from 2002 to 2020 and explores the compliance relationship between environmental governance attention and environmental quality. The results show that the allocation of local government environmental governance attention shows high consistency with that of the central government, and the overall environmental governance attention shows a fluctuating upward trend. There is a long-term stable co-integrated relationship between environmental governance attention and environmental quality in the Beijing–Tianjin–Hebei region, as well as a two-way Granger causality relationship in the short term. The non-linear influence of environmental governance attention on the environmental quality in the Beijing–Hebei–Tianjin region can be described using the LSTR2 model. During 2004–2016, environmental governance attention often had non-linear effects on the environmental quality. Since 2016, there has been a stable linear relationship between environmental governance attention and environmental quality. Finally, some policy suggestions on improving the local performance evaluation system and establishing a collaborative environment system for the Beijing–Tianjin–Hebei region have been put forward for the government.

Examining Relationships between Regional Ecological Risk and Land Use Using the Granger Causality Test Applied to a Mining City, Daye, China

Land use changes are an important factor contributing to the increasingly severe deterioration of the ecological environment. Therefore, regional analyses of land use and ecological risk should be developed for the restoration of ecological functions. In this study, a comprehensive ecological risk assessment was constructed on a regional scale and applied to Daye, a traditional mining city in China. Cointegration analyses and Granger causality tests were used to explore the complex relationship between land use and ecological risks in the study area from 2007 to 2021. The results show a long-term and stable relationship between land use changes in different sub-regions and ecological risks, albeit with distinct Granger causality relationships. This research presents the development trend of the relationship between land use change and ecological risks in a mining city, from rapid economic growth to economic restructuring and full-region ecological governance.

Flight delay propagation inference in air transport networks using the multilayer perceptron

Recent studies have explored the delay propagation network among airports by inferring Granger causality among time series using linear methods. Granger causality indicates whether delays at one airport can help predict delays at itself or other airports and thus help to understand the interconnection among airports. This paper makes inferences about the Granger causality relation among airports by applying a nonlinear multilayer perceptron method to the arrival delay time series in Europe and China. We find that the propagation results can be overestimated with data input containing early arrival flights, besides delayed flights. Europe presents a smaller magnitude of delay propagation than China, considering only delayed flights, indicated by the link densities of the networks with the same penalty parameter. Unlike some recent research findings, our results suggest that large airports have more out-degree and more impact in the delay propagation network. These results can help predict and understand delay propagation in daily operations or simulation environments.

COVID-19 pandemic and trade flows: empirical evidence from selected Asian Pacific countries

PurposeThis paper aims to investigate the effects of the COVID-19 crisis on trade flows in Asia Pacific countries and explores the causality between COVID-19-related shocks and trade.Design/methodology/approachThe authors used two novel techniques, namely, two-stage instrumental-variables (2SIV) approach and Juodis, Karavias and Sarafids (JKS) causality test, to examine trade dynamics in the Asia Pacific region during the pandemic.FindingsUsing the monthly trade data of 17 Asia Pacific countries between January 2020 and December 2021, the results were threefold. Firstly, the empirical analysis showed that during the COVID-19 crisis, the flow of exports tended to persist idiosyncratically in comparison to the flow of imports. In particular, a specific finding was that the persistence level in exports was about 20%–25% higher than that in imports. Secondly, the authors found that the past values of COVID-19 cases and COVID-19 deaths contain information that helps to predict exports/imports over and above the information contained in the past values of exports/imports alone. Finally, the study established that the government response and stringency indexes have a Granger-causal relationship with exports and imports.Research limitations/implicationsFor the foreseeable future, these findings have significant policy ramifications. Firstly, if a COVID-19 crisis-like situation emerges in the future, it will be critical for countries to maintain their competitiveness throughout the crisis, like the COVID-19 pandemic, while also rebuilding trade relationships wherever possible. Secondly, because information about government responses and measures can also be used to predict future trade flows, prudent management of government responses and stringent measures will be necessary in a crisis like COVID-19 to achieve the optimum level of exports and imports. At the same time, the trading partners should give up the idea of trade protection and focus on finding a way to balance the conflicting needs of imports and exports.Originality/valueTo the best of the authors’ knowledge, the authors, for the first time, used a 2SIV approach and JKS causality test to examine trade dynamics in the Asia Pacific region during the pandemic. In addition, the authors present the first comprehensive analysis of the evolving relationships between export and import flows and governmental policy responses under COVID-19. As a result, it contributes uniquely to both public and international economics.