Unidirectional Granger Causality Research Articles

The Impact of Macroeconomic Variables on Stock Prices: A Case Study from FTSE Bursa Malaysia KLCI from 1994 until 2022

This study uses monthly historical data to analyse the effects of changes in selected macroeconomic variables on the stock prices of the FTSE Bursa Malaysia KLCI from 1994 to 2022. A multiple regression model employing Ordinary Least Squares (OLS) and the Granger Causality test are employed to study this relationship. Upon evaluating the estimated regression coefficients and corresponding t-statistics, the findings reveal changes in the prices of Brent Crude Oil (BC) futures. Meanwhile, the Currency Exchange Rates (CR) indicate a significantly positive influence on stock prices. In contrast, the rates of Gross Domestic Product (GDP), Interest Rates (IR), and Inflation Rates (CPI) do not significantly influence stock prices. Additionally, unidirectional Granger Causality is observed between stock prices, the rates of GDP, and the CR.

Impact of Exchange Rate Volatility on Economic Growth: An Empirical Evidence from South Sudan

The prime objective of this study is to examine the impact of exchange rate volatility on economic growth in South Sudan, starting from 2008 to 2022, constructed on the basis of monthly time series. The exchange rate is the value of domestic currency convertible in terms of another currency or currency. The degree and trend of fluctuation of exchange rate influences internal and external shocks for both developed and developing economies. The study used the autoregressive (VAR) model to analyze the data due to its effectiveness, flexibility and simplicity in investigating multiple time series datasets. RGDP is the dependent variable, and EXR, EXP, IMP, INF, FDI, and UNEMPR are independent variables, respectively. The study tested the stationarity of time series using the Augmented Dickey-Fuller (ADF) test. Thus, most of the variables indicated stationarity in the first difference with intercept and at a 1% level of significance, except the exchange rate that becomes stationary in the second difference and at a 1% level of significance. In addition, a Pairwise Granger causality test has been applied to explore the relationships between variables in the future; the results portrayed a unidirectional Granger causality between imports (EXP) and exports (IMP) at 0.0567, suggesting that fluctuation in imports influences the pathway of export trends. However, the empirical result of this study concluded that the exchange rate has a negative impact on economic growth, disclosing a coefficient of -0.249154 that implies a 1-unit increase in the exchange rate is linked with a decrease of about 0.249154 units in the real gross domestic product (RGDP) and at a 1% level of significance. The depreciation of a local currency rises the prices of imported goods and services, and leads to imported inflation. The scarcity of the U.S. dollar sets a burden on the exchange rate and weakens the aggregation of the official exchange rate in the country. This worsens economic progress and drives the economy into an absolute verge of collapse, exposing consumers to poverty, that in turn, to a higher unemployment rate, poor living standard, health care, education, as well as derailing apart the foreign direct investment inflows in South Sudan. The study suggests that the government should diversify exports and adopt macroeconomic policies that are geared towards addressing inflationary pressures and stabilizing the domestic currency.

Energy Efficiency, Consumption, and Economic Growth: A Causal Analysis in the South African Economy

Energy efficiency potentially reduces global carbon emissions, whereas the need of emerging countries to maintain economic growth and development entails a sharp increase in energy consumption. However, to meet this, current energy systems need to be transformed. Several studies find different conclusions on the short-run and long-run relationship and the direction of causality, and none of the studies have considered energy efficiency in their model. This study investigates the direction of causality between energy efficiency, energy consumption, and economic growth in South Africa. To determine if a long-run relationship between the variables exists, the Johanson cointegration test is used, and the results indicate that there is a long-run relationship between economic growth, energy depletion, energy efficiency, non-renewable energy consumption, renewable energy consumption, and energy security, with trace statistics suggesting that the null hypothesis of no cointegration should be rejected at a 5% level of significance. The Toda and Yamamoto procedure of the Granger causality approach was then applied. This study finds a unidirectional causality between energy efficiency, non-renewable energy consumption, and economic growth and no causality between renewable energy consumption, energy depletion, energy security, and economic growth. The growth hypothesis is supported, while the neutrality hypothesis is only confirmed regarding renewable energy consumption and economic growth. The results further suggest that a unidirectional Granger causality exists between non-renewable consumption and energy efficiency, and economic growth in South Africa. In South Africa, energy efficiency is a significant tool to enhance sustainable growth and attain climate objectives. Also, energy efficiency helps to lower the costs of mitigating carbon emissions and further advance both social and economic development.

Ageing affecting the Americas?: exploring the growth direction: the relationship between the elderly population and economic growth in the American context

The main aim of this study is to explore the relationship between the elderly population and economic growth in 25 North and South American countries use annual secondary data from 1961 to 2021. Instead of focusing on the conditional mean, this study tests for Granger causality in the entire conditional distribution of the elderly population and economic growth through wavelet coherence analysis. The study findings indicated a unidirectional Granger causality running from per capita gross domestic product (GDP) to the elderly population for Bolivia, Colombia, Guyana, Peru and Puerto Rico and also from elderly population to per capita GDP for Costa Rica, Ecuador and Honduras. However, there is no causal relationship between the elderly population and economic growth for the rest of the countries. Wavelet coherence analysis depicted that economic growth positively led the elderly population in North America during the early 21st century. Furthermore, economic growth had been negatively leading the elderly population in South America throughout the period under consideration. This empirical study shows that policymakers of these economies need to analyse the transformation in the elderly population-economic growth causality robustness throughout the year when devising policies.

Analysis of Relevant Factors Influencing the Development of Pharmacist Human Resources in China: Based on the Time Series Vector Auto-Regression Model.

To analyze and predict the dynamic influence trends and degrees caused by various factors that may affect the expansion of the hospital pharmacist team in China. Time series data including the number of hospital visits in all hospitals in China, the total number of pharmacists, per capita health expenditure, and per capita GDP from 2002 to 2022 were collected at the national level. A vector autoregressive (VAR) model was constructed, and methods such as the Granger causality test, impulse response analysis, and variance decomposition were employed to explore the influence process and direction of various influencing factors on the number of pharmacists in China. The Augmented Dickey-Fuller (ADF) test indicates the first-order difference series of the time series is stationary (P<0.05). The model stability test shows the modulus of all specific root reciprocals falls within the unit circle, indicating model stability and credible results. The cointegration test reveals a cointegration relationship among the number of hospital visits, per capita health expenditure, per capita GDP, and the number of pharmacists (P<0.05). The Granger causality test indicates a unidirectional Granger causality relationship between the number of hospital visits, per capita health expenditure, and the number of pharmacists. The impulse response function indicates that the number of pharmacists shows an upward trend after being impacted by one unit of the number of hospital visits and per capita GDP, while the positive impact of per capita health expenditure on the number of pharmacists turns into a negative impact in the third stage. Variance decomposition shows that the contribution rate of the number of hospital visits to the number of pharmacists is 12%, the contribution rate of per capita health expenditure to the number of pharmacists is 57%, and the contribution rate of per capita GDP to the number of pharmacists is 80%. The number of hospital visits, per capita health expenditures, and per capita GDP all positively contribute to the development of the pharmacist workforce. Per capita health expenditures lead to an increase in the number of pharmacists in the short term. Among the selected indicators, the primary drivers of pharmacist workforce development are per capita health expenditures and per capita GDP. Hospital visits have a relatively minor contribution to the growth in the number of pharmacists.

A study on the impact of high-quality openness on China’s economic growth based on mathematical statistics

Abstract The level of high-quality openness is determined by the degree of economic openness, so this paper explores the impact of high-quality openness on China’s economic growth according to the degree of economic openness and analyzes the long-term equilibrium relationship and short-term dynamic adjustment process between high-quality openness and economic growth by using mathematical and statistical methods such as co-integration analysis and error correction model. An indicator system containing multiple dimensions such as trade openness, foreign cooperation, and real tariff rate is constructed, and China’s relevant data for the past 15 years are collected for empirical analysis. The research results show that there exists a long-term stable equilibrium relationship between economic growth and the indicators of economic openness, and every 1% increase in overall economic openness leads to a 0.48532% increase in GDP. In the short term, the openness of the Chinese economy has a minor impact on economic growth over the same period. Additionally, there is a unidirectional Granger causality between economic openness and China’s economic growth, i.e., economic openness can enhance economic growth, but economic growth is not the cause of economic openness. It indicates that high-quality openness can promote China’s economic growth.

Does Digitalisation Have an Impact on Profitability Evidence from the Turkish Banking Sector

Purpose –Developments and innovations in information technologies have seriously affected the banking sector as they have affected all sectors. Thus, significant gains have been achieved in terms of transaction speed and costs have been significantly reduced. This study aims to investigate the impact of the digitalisation process in the banking sector on the profitability of the sector.Design/methodology/approach –In the study, quarterly data set for the period 2010/Q4-2024/Q1 is used. Time series analyses are used to examine the relationship between variables. Time series analysis was utilized in the study. Phillip Perron (PP) unit root test was used to determine the stationarity levels of the variables used in the study. ARDL (Autoregressive Distributed Lag Bound Test) bounds test approach was utilized to reveal the long-run relationship between the series. Toda-Yamamoto test was used to test the causality relationship between the variables.Findings –According to the findings obtained as a result of the analyses, it is determined that there is a cointegration relationship between the return on assets of the Turkish banking system and the volume and number of digital banking transactions. According to the results of Toda-Yamamoto causality tests, it was concluded that there is a unidirectional Granger causality relationship between return on assets and digital banking transaction volume, while no causality relationship was found between returnon assets and the number of digital banking transactions. It is concluded that digital banking applications have a positive effect on the return on assets of the Turkish Banking sector.Discussion –It is important for banks to increase their service quality by focusing more on digitalisation efforts, to equip their personnel with digital technologies and to aim to increase the use of digital banking applications by making detailed introductions to their customers.

Energy Price Impact on BRIC Stock Markets: A Granger Causality Analysis

Energy prices and the stock market are two of the crucial factors in the evolving landscape of global finance, particularly in major emerging economies. However, research on how energy price changes impact stock markets in BRIC countries remains limited, despite their diverse roles in global energy markets and economies. This study investigates the causal dynamics between energy prices and stock market performance in BRIC countries, aiming to uncover short-term fluctuations and long-run relationships in these major emerging economies. Utilizing daily data from 2013 to 2023, stationarity tests, cointegration analysis, and Granger causality tests are employed to examine these relationships. Key findings reveal weak evidence of a long-run equilibrium between energy prices and stock market indices, challenging previous assumptions about their cointegration. More significantly, the findings uncovered a strong unidirectional Granger causality from oil prices to all BRIC stock market indices, while gas prices show a more selective influence. Notably, no evidence of reverse causality from stock markets to energy prices was found, highlighting the exogenous nature of global energy prices in relation to BRIC stock markets. This study uniquely analyzes oil and gas price effects on BRIC stock markets, offering insights for investors and policymakers amid increasing commodity-financial market integration. Doi: 10.28991/ESJ-2024-08-06-015 Full Text: PDF

THE RELATIONSHIP BETWEEN FDI AND ECONOMIC GROWTH IN INDIA. A TIME SERIES APPROACH

Foreign Direct Investment (FDI) has gained importance after the second world war. In broader sense Foreign Direct Investment incorporates the establishment of up to date and advanced facilities, mergers and acquisitions, investing the profits earned from other overseas business activities, providing loans to other companies etc. In narrow sense the Foreign Direct Investment means investment in the country other than the investors own country. FDI can be better understood by studying the real reason that why the companies have shown interest in investing abroad rather than exporting and outsourcing their products to domestic firms. In due course of time many theories and approaches were developed to explain FDI. Although several researchers have tried to explain the phenomenon of FDI, we cannot say there is a generally accepted theory, every new evidence added some new elements and criticism to the previous ones. FDI in India is playing a noticeable role in the growth and development of the country. India is one of the important countries of the world which is able to receive substantial amount of FDI. The present study has made an effort to see the relationship between the FDI and Economic growth in India. GDP has proxies for economic growth. First the Johansen cointegration test result shows the long run relationship between variables and the Granger causality test result exhibits that there is unidirectional Granger causality between FDI and GDP. Next the Multiple Regression model result presents that the estimated coefficients on FDI &amp; exports have a positive relationship with GDP. Therefore, it is statistically revealed that FDI and Exports are instrumental in influencing the level of economic growth in India. India is having certain drawbacks like Weak infrastructure, Complicated tax structure, Restrictive labor laws, Bureaucracy and Corruption. Unless and until these challenges are met with, India will never compete with China regarding FDI inflows. KEYWORDS: Foreign Direct Investment, Gross Domestic Product, Economic Growth.

CAUSAL RELATIONSHIP BETWEEN GREED AND FEAR INDEX AND NON-PERFORMING LOANS: AN EMPIRICAL STUDY ON THE TURKISH BANKING SECTOR

This study aims to investigate the causality relationship between the greed and fear index and non-performing loans in the Turkish banking sector. Time series analyses are used in this study. For this purpose, Zivot and Andrews unit root test was used to determine the stationarity of the series. Then, Granger causality test was applied to determine whether there is a causality relationship between the series and if there is a causality relationship, the direction of the causality relationship. According to the results of the study, there is a unidirectional Granger causality relationship between the non-performing loan ratios of the Turkish banking sector and the greed and fear index. In other words, it is concluded that an increase in the Greed and Fear Index increases the non-performing loan(NPL) ratios of the banking sector.

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.

Impact of banking subsystem liquidity creation on real economic output

PurposeThis study aims to examine the impact of liquidity creation per capita of tri-banking system and dual banking system on real economic output.Design/methodology/approachThis study applies the feasible generalized least square framework on the data set of 12 countries, 8 with tri-banking system and 4 with dual banking system over the 2013–2022 period.FindingsThe findings show that for countries with tri-banking system, only liquidity creation by full-fledged Islamic Banks (FIBs) and hybrid conventional banks (HCBs) spurs real output, with the impact of HCBs being greater than that of FIBs. Nonetheless, for countries with dual banking system, both FIBs’ and pure CBs’ (PCBs) liquidity creation fosters real output. However, the impact of PCBs is slightly greater. Finally, Granger causality results confirm only the positive impact of the tri-banking system’s liquidity creation on real output.Practical implicationsFor countries with tri-banking system, only HCBs’ and FIBs’ liquidity creation spurs real output. However, for countries with dual banking system, liquidity created by both FIBs and PCBs fosters real output. However, only liquidity created by tri-banking system has a unidirectional Granger causality with real output.Originality/valueTo the best of the authors’ knowledge, this is the first study that examines the impact of the banking subsystem liquidity creation on real economic output. Examining the impact of the liquidity created by this banking subsystem on the real economy is important for both regulators and policymakers.

Possible factors influencing the development of the number of pharmacists in China: A time series VAR model analysis from the perspective of supply and demand theory

Objective: The supply and demand theory is used as a perspective to analyze the impact and prediction of factors such as the number of consultations in medical institutions on the number of hospital pharmacists in China. Methods: A total of 21 years of time-series data on the number of pharmacists, doctors and nurses in China’s hospitals, the number of consultations, the per capita health cost and the per capita GDP were collected from 2002 to 2022, and a vector auto-regressive model influencing the number of pharmacists in China was established to analyze the dynamic process of the influence of the number of consultations, the per capita health cost and the per capita GDP on the number of pharmacists and the direction of the influence in China. Results: There is a unidirectional Granger causality and long-term cointegration relationship between the number of consultations and the number of pharmacists, and the number of consultations will have a greater impact on the number of pharmacists in the long run and will be more stable in the later period; there is also a unidirectional Granger causality and long-term cointegration relationship between the per capita health cost and the number of pharmacists, and the per capita health cost will have a greater impact on the number of pharmacists in the short run. Conclusion: The rise in the number of pharmacists will occur along with increases in the number of visits, health costs per capita, and GDP per capita, with health costs per capita having a greater impact on the number of pharmacists in the short term, and visits and GDP per capita having a greater impact on the number of pharmacists in the long term and being more stable in the later years. Key words: number of pharmacists, vector auto-regressive model, number of consultations, per capita health costs, GDP per capita

The relationship between air pollution and cardiovascular diseases in Türkiye

The aim of this study was to determine the effect of air pollutant particles on the cardiovascular disease burden (CVDALY) in Turkey. Particulate Matter 2.5 (PM 2.5) and Non-methane volatile organic compounds (NMVOC) were taken as the independent variable and CVDALY as the dependent variable. The variables were analyzed within the Panel Data Analysis and Machine Learning Approaches frame. Unidirectional Granger causality was determined from PM 2.5-NMVOC to CVDALY and revealed that they acted together in the long term. The regression analysis that was made using econometric and multivariate regression models revealed that generally 1 unit increase in PM 2.5 increased CVDALY by between 0.0021-0.0029 units; 1 unit increase in NMVOC increased CVDALY by between 0.00024-0.0004 units. In Machine Learning approach, it had been determined that if the PM 2.5 and NMVOC were reduced to 0.84- and 9.48 respectively; CVDALY would be decreased to 0.022. In other words, Machine Learning approaches results showed that reducing PM 2.5 by about 4.5 times and NMVOC by about 30% would be reduced CVDALY by about 39.6% from the current status of Turkey. The empirical results showed that PM 2.5 - NMVOC increased CVDALY in Turkey. From this perspective establishing and implementing policies to improve air quality in Turkey could be an important approach in reducing cardiovascular diseases.

Multi-scale bioimpedance flexible sensing with causal hierarchical machine learning for fish vitality evaluation under adversity stress

Multi-scale bioimpedance flexible sensing with causal hierarchical machine learning for fish vitality evaluation under adversity stress

The dependence structure and causality detection in crude oil markets

ABSTRACT It is essential to capture the dependence structure among the world’s dominant crude oil markets for understanding the world’s crude oil pricing mechanism. The dependence structure and interaction between Shanghai International Energy Exchange (INE) market and other major crude oil markets in the world are investigated to determine whether the world crude oil market is efficient. Using the vine copula model based on GARCH, we analyze the dependence structure and interactions among these markets. The highest dependence is found between West Texas Intermediate (WTI) and BRENT crude oil markets, displaying strong symmetric tail dependence. DUBAI market exhibits unidirectional Granger causality to WTI and INE markets. Empirical results suggest that the world crude oil markets are not efficient and are far from One Great Pool. DUBAI and Brent markets emerge as leaders in the current international crude oil pricing system, while INE markets do not significantly influence DUBAI and BRENT markets.

DOES CURRENCY VOLATILITY AFFECT NON-PERFORMING LOANS? EVIDENCE FROM THE TURKISH BANKING SECTOR

This study aims to econometrically investigate the relationship between non-performing loans and Euro and USD indices in Turkey. The data set of the study consists of the Turkish banking sector non-performing loan ratio and Euro and American Dollar (USD) indices variables for the period 01/2003-09/2023. Time series analyses were used to test the relationship between the variables. Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root tests were applied to the data. Since the series became stationary at different levels, the ARDL (Autoregressive Distributed Lag Bound Test) test, one of the cointegration tests, was applied. Afterward, whether there is causality between the variables and if there is a causality relationship, the determination of the direction of causality is mutually tested with the “Granger Causality” method. According to the results of the research, a cointegration relationship was found between the non-performing loan ratios of the Turkish banking system and the Euro and USD indices. In the long run, it is concluded that a 1% increase in the Euro index is associated with a 2.93% decrease in non-performing loan ratios. On the other hand, in the short run, Euro and USD index values have no effect on non-performing loan ratios. According to the results of the Granger causality test, a unidirectional Granger causality relationship was detected between non-performing loan ratios and the Euro index. A similar unidirectional causality relationship was also found between the Euro index and the USD index.

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.

Financial development, energy consumption, and economic growth in the ASEAN countries: evidence from the PVAR approach.

The Association of Southeast Asian Nations (ASEAN), a new global economic force, has struggled to achieve a dual objective of enhanced economic growth and improved environmental quality. Financial development is generally considered an important tool in achieving these simultaneous objectives. This paper examines the response mechanism and the inter-relationship between the ASEAN region's financial development, energy consumption, and economic growth. Unlike previous studies, the paper uses a generalized method of moments panel vector autoregression (GMM-panel VAR) framework for the 1981-2021 period. The second-generation Granger causality test is used to identify their causality relationship. Economic growth supports financial development and reduces energy consumption from fossil fuel sources in the ASEAN countries. Financial development also reduces fossil fuel energy consumption. The bi-directional relationship between economic growth and fossil fuel energy consumption exists. Energy consumption and financial development are also bi-directionally linked. However, only the unidirectional Granger causality from economic growth to financial development is found. The variance decomposition analysis results confirm that economic growth accounts for the most significant variance in fossil fuel energy consumption and financial development in the ASEAN countries. Policy implications have emerged based on these findings.

The impact of agriculture production and renewable energy consumption on CO2 emissions in developing countries: the role of governance.

Environmental pollution has aggravated the climate change issues posing unusual challenges to the survival and growth of humanity, including extreme weather, loss of species, and sustainability of the ecosystem in developing countries. Unlike previous studies, this paper adds new dimension to the literature by incorporating corruption into agriculture production-environment nexus. This study adds new dimension to the literature by examining corruption, agriculture, and renewable energy on CO2 emissions. The study therefore examines the effects of governance (corruption) and agriculture production on CO2 emissions in 20 countries in Africa from 1990 to 2019. The study employed recent panel econometric approach which accounts for cross-sectional dependence in the variables. The findings of the fixed effect model and panel dynamic ordinary least squares (PDOLS) show that forest and renewable energy consumption decrease CO2 emissions. However, corruption, agriculture production, export, and urbanization escalate CO2 emissions in African countries covered in the paper. Moreover, the Dumitrescu-Hurlin Granger causality indicates a bidirectional causality between agriculture production and CO2 emissions, renewable energy use, agricultural output, and forest. Also, unidirectional Granger causality runs from corruption to forest and agriculture production. On these premises, consented efforts by governments should be made to support good institutions in order to promote good governance to avert pervasive consequences of corruption on the environment.