Granger Causality Relationship Research Articles

Water pollution, industrial agglomeration and economic growth: Evidence from China

This paper investigates the causal relationship between water pollution, industrial agglomeration, and economic growth in 11 Chinese provinces in China. Using a bootstrap autoregressive distributed lag (ARDL) analysis, we examine the estimated models’ stability and investigate the Granger causality relationships between system variables. The results indicate that our estimation provides evidence of a long-run relationship between water pollution, industrial agglomeration, and economic growth in China. The bidirectional running from other water pollution variables is confirmed from the casualty tests in Shanghai and Yunnan. Specifically, the unidirectional causality relationship running from industrial agglomeration and economic growth to water pollution provide statistical evidence of the important role that industrial agglomeration and economic growth play in increasing water pollution.

Do mixed-data sampling models help forecast liquidity and volatility?

This paper aims to contribute to the existing studies on the Granger-causal relationship between volatility and liquidity in the stock market. We examine whether liquidity improves volatility forecasts and whether volatility allows the improvement of liquidity forecasts. The forecasts based on the mixed-data sampling models, MIDAS, are compared to those obtained from models based on daily data. Our results show that volatility and liquidity forecasts from MIDAS models outperform naive forecasts. On the other hand, the application of mixed-data sampling models does not significantly improve the performance of the forecasts of either liquidity or volatility based on a univariate autoregressive model or a vectorautoregressive one. We found that in terms of the forecasting ability, the VAR models and the AR models seem to perform equally well, as the differences in forecasting errors generated by these two types of models are not statistically significant.

Explaining Government Expenditure and Growth Rate Dynamics in Ghana: A Vector Error Correction Model

This paper examined the Granger-causality relationship between public expenditure and real capita GDP in Ghana, using aggregate data for a sample of 59 years, over the period of 1961–2020. Econometric analyses employed included: The simple Linear Regression Model (SLRM), Augmented Dickey-Fuller (ADF), Granger-causality, and Cointegration Tests (CT). The OLS output reveals that the series has a limited ability in predicting each other as indicated by the very low R-square which comes close to zero, the ADF test showed that the series is stationary at the first difference, and The Granger-causality test revealed that there is no causality between the series. That is there is no Granger causal linkage between economic growth and government expenditure. In other words, economic growth and government expenditure are independent of the causal mechanism. The null hypothesis of number co-integration is not rejected since there is no co-integration at the 5% level of significance. This means that there is no long-run relationship between the series. There is a need for policy in public investment to impact growth rates in the future. Government expenditures need to be institutionalized in order to plan public spending over a period so that government expenditure is projected as a stable share of all anticipated flow of future levels of real income.

The relationship between the development level of American public libraries and the output of science and engineering publications

This paper explores the exact relationship between the development level of American public libraries and the output of science and engineering publications. We use the sample data from 1996 to 2019 to build a time series model, and analyze the long-term equilibrium, short-term correlation and Granger causality relationships between them with stationarity test, cointegration test, Granger causality test, and impulse response function. The results suggest that there are a long-term equilibrium relationship and a bidirectional Granger causality between them. The two interact and promote each other. The impact of the development level of American public libraries on the output of science and engineering publications can be seen in fewer time periods, while the impact of the output of science and engineering publications on the development level of American public libraries take more time periods to show.

Analysing the dynamic co-movement between tourism and expected economic growth considering extreme events

In the post epidemic period, it is important to clarify the relationship between economic growth and tourism growth. The aim of this study is to characterize the co-movement between expected macroeconomic conditions and inbound tourism, focussing on the nonlinear relationship between these variables. Dynamic copula-based GJR-GARCH models are employed to measure nonlinear dependence. Total inbound tourism to Thailand and its disaggregation for its 10 main origin countries, are considered in the empirical study. The results show that there exists significant co-movement between expected economic growth and inbound tourism, and prove the importance of considering nonlinearities and extreme events. Also, copula nonlinear Granger causality is used to conclude that inbound tourism and expected economic growth have nonlinear bi-directional and unidirectional Granger causality relationship. Finally, this paper puts forward some policy suggestions to restore tourism and boost economic growth in the post epidemic period.

The Impact of International Oil Price Shocks on Pakistan Stock Market

The aim of the study is to investigate the dynamic relationship between oil price and four highly capitalized sector of Pakistan stock market. Namely Oil and Gas Marketing Companies, Oil and Gas Exploration Companies, Commercial Banks, and Textile Companies, including Pakistan Stock Index. We retrieve daily data on stock prices from Pakistan stock Market and the oil price from Energy Information Administration covering the period 1st, January 2005 to 31st, December 2014. To end this, we apply the Vector Auto Regressive (VAR) Model to find out the relationship between oil price and stock price. In order to provide more effective and credible conclusions the Granger Causality and Impulse Response Functions are implemented. Within the VAR Model the results indicates that there are both Short run and long run relationship between the oil price and Pakistan Stock Market sectors. The Granger Causality test determines a unidirectional, Granger Causality relationship running from oil price to stock prices. In contrast, the Impulse Response Function suggests that oil price have both positive and negative responses to the stock prices. Thus, our main finding from overall results we conclude there is strong impact of oil price shocks on Pakistan Stock Market. This study provide the evidence for a complete understanding on the relationship between oil price and Pakistan Stock Market. This study likely to offer some valuable insights for policymakers and financial regulators for developing financial and economic policies.

ISLAMIC FINANCIAL DEVELOPMENT AND INCOME INEQUALITY IN INDONESIA

The objective of this paper is to analyze the short and long run relationship between Islamic financial development and income inequality in Indonesia over the period of 2000-2020. The study has employed the Auto Regressive Distributed Lag (ARDL) bound testing approach and the Error Correction Mechanism (ECM) to examine the existence of long-run and short-run relationship, while variance decomposition (VDC) technique is used to provide Granger causal relationship between the variables. The cointegration tests show that there is a long run relationship between Islamic financial development, economic growth, inflation and income inequality in Indonesia. However, Islamic financial development itself is found to be not statistically significant in influencing income inequality during the sample period for long-run. This study found a positive and statistically significant (10%) effect of Islamic financial development in explaining the changes in income inequality in the short run. In terms of policy, enhancing financial access is needed to ensure that financial development fully supports the reduction of income inequality in Indonesia.

The Interaction and Its Evolution of the Urban Agricultural Multifunctionality and Carbon Effects in Guangzhou, China

The dual identity of carbon sources and carbon sinks makes agriculture the focus of carbon neutralization-related research. Compared with traditional rural agriculture and urban industrial production, urban agriculture has its own particularities. It is of positive practical significance to explore the interaction and its evolution process between urban agricultural multifunctionality and carbon effects in seeking solutions to alleviate carbon pressure. Based on the changes in agricultural carbon emissions and carbon sequestration in Guangzhou from 2002 to 2020, we used the Granger causality analysis method to investigate the interaction between urban agricultural multifunctionality and carbon effects and then used the grey association model to analyse the evolution process of associative degrees between the two and divide the agricultural development stages. Finally, according to the practicalities of Guangzhou, we analyzed carbon effects generated in the multifunctional transformation of urban agriculture and put forward corresponding policy suggestions on how to solve the problem of excessive carbon dioxide emissions through agriculture in metropolitan areas. The results show that from 2002 to 2020 in Guangzhou, urban agricultural production decreased, the economic and social function increased, and the ecological function climbed and then declined. The carbon sequestration of urban agriculture in Guangzhou was approximately four times more than the carbon emissions. Carbon emissions experienced a process of first decreasing, then increasing, then remaining constant, and finally decreasing, while carbon sequestration first decreased and then increased. Second, the carbon emissions of urban agriculture in Guangzhou have a causal relationship with the production, social, and ecological functions. Carbon emissions are the Granger cause of the economic function but not the opposite. The carbon sequestration of urban agriculture in Guangzhou has a causal relationship with production and economic functions. Carbon sequestration is the Granger cause of the ecological function but not the opposite. There is no Granger causal relationship between carbon sequestration and the social function. Third, from 2002 to 2020, the interactive development process of urban agricultural multifunctionality and carbon effects in Guangzhou can be divided into three stages: production function oriented (2002–2006), economic and social function enhanced and production function weakened (2007–2015) and the economic and social function exceeded the production function (2016–2020). Fourth, the multifunctional transformation of urban agriculture has brought about carbon effects of reducing emissions and increasing sequestration. There is a long time lag between multifunctional transformation and carbon effects of urban agriculture.

Volatility Asymmetry and Spillover Effects in Crude Oil Futures Market: Evidence from China

In order to study the international influence and function of domestic crude oil futures prices in depth, based on the daily data of 2018-2022, this paper uses Granger causality test, cointegration test, ECM model and several forms of GARCH model to make empirical research on the price correlation, volatility, asymmetry and risk spillover effects of domestic crude oil, Brent crude oil, WTI crude oil and Oman crude oil futures in the three major foreign crude oil markets. The study found that there is a Granger causal relationship and a cointegration relationship between domestic and foreign crude oil futures prices. There are interactions in the crude oil futures markets at home and abroad, and there are different fluctuation patterns in the short-term fluctuation process. There are asymmetries, leverage effects and spillover effects in the volatility of the four crude oil futures markets at home and abroad with different intensities. The bearish news of the three foreign markets is greater than the impact of the bullish news than that of the domestic one. There are risk spillover effects and volatility effects between domestic and the three foreign crude oil futures markets, and the domestic spillover effect on foreign crude oil is greater than the spillover effect on domestic crude oil from abroad. The conclusion is that the international influence of domestic crude oil futures prices is stronger than that of Omani crude oil, and weaker than Brent and WTI crude oil. The leverage effect of the three foreign markets is greater than that of China, and the leverage effect of the Oman crude oil futures market is the strongest. The asymmetry and spillover effect of fluctuations in the domestic and foreign crude oil futures markets lead to the risk and speculation of the three foreign markets being greater than that of the domestic one, and the speculative arbitrage through the domestic and foreign crude oil markets may cause huge market risks, and it is suggested that the internationalization of the domestic futures market needs more systems and mechanisms to support the construction.

Nonparametric identification of Kronecker networks

We address the problem to estimate a dynamic network whose edges describe Granger causality relations and whose topology has a Kronecker structure. Such a structure arises in many real networks and allows to understand the organization of complex networks. We propose a kernel-based PEM method to learn such networks. Numerical examples show the effectiveness of the proposed method.

The Effect of Real Effective USD/TRY Exchange Rate on Tourism Income: An Empirical Analysis of Turkey

The exchange rate is one of the most important factors affecting the travel costs of tourists. Therefore, the depreciation of the national currency makes tourist travel cheaper. Similarly, the appreciation of the national currency makes travel more expensive for tourists. From this point of view, this study aims to seek the effects of real effective USD/TRY exchange rate on tourism income and average tourism expenditure per capita for the period 2003Q1-2019Q4. In the empirical analysis, the Granger causality test was used to examine the relationship between the variables. According to the results of the study, a bilateral Granger causality relationship was determined between the real effective USD/TRY exchange rate and the average tourism expenditure per capita. However, Granger causality could not be determined between the real effective USD/TRY exchange rate and tourism income. Afterwards, variance decomposition and impulse-response functions analyses were performed to support the results obtained from the Granger causality test. According to the results of the variance decomposition analysis, the ratio of the average tourism expenditure per capita in Turkey to be explained by tourism income and real effective exchange rate is quite high.

The Triangular Causal Relationship between Economic Growth, Tourism, and Foreign Direct Investment: A Case Study in Central Vietnam

The article proposes a method to broach the complication and mixture of the triangular causal nexus among gross domestic product (GDP), foreign direct investment (FDI), and foreign tourist arrivals (FTA) in Thua Thien Hue (TTH) province that has not yet been studied. FDI into TTH province fluctuates unpredictably, so the study investigates the causal relationship between the triangular variables over the whole period (1995–2019) and the shortened period (2003–2019). The ARDL model is the most optimal choice due to the heterogeneity of stationary characteristics and short time series data. The shortened period has established more statistically significant short- and long-term Granger causal relationships, excluding the economic crisis effect. The Granger causality test only underlined a unidirectional short-term relationship running from FTA to FDI in the shortened period. Policies for economic development in TTH province need to strengthen the coordination between foreign investment and tourism so that all economic sectors can jointly create spillover effects on economic growth.

Statistical analysis of atmospheric parameters, noise temperature and digital terrestrial television signal strength over Jos metropolis, Plateau state, Nigeria

The study of the relationship between the Received Signal Strengths (RSS) from Unity TV (786 MHz) located at Rayfield (9.84 o North 8.89 o East), Jos, Plateau State and some atmospheric parameters with noise temperature has been done using two years half-hourly data. The measurement was carried from 5 am and 9 pm daily. The analysis was carried out using the regression, co-integration and Granger causality models. The results show that the RSS is higher in the morning hours (5.00 am–9.00 am) late in the evening (6.30 pm–9.00 pm) but lower between 9.00 am and 6.30 pm. This might be due to the “dusty” atmosphere and low reflection of ionosphere in the day time which causes signal attenuation within the day time. The correlation coefficients from the coefficient of determination (R squared) of 0.88, 0.004, 0.838. 0.25, 0.867, and 0.112, are −0.94, −0.07, 0.92, −0.50, −0.93, −0.334 for atmospheric temperature, pressure, relative humidity, wind speed, noise temperature and rainfall respectively. It means all the independent variables except relative humidity are inversely proportional with the RSS. Also, the higher R2 values for atmospheric temperature, relative humidity and noise temperature respectively, indicates higher correlation between RSS and these parameters. It can be inferred that the models are suitable for predicting Unity TV (UTV) signal strength and that of other TV stations in Jos and environs, using T, RH and NT as inputs. The results also showed that there is a co-integration and Granger Causal relationship between the parameters and RSS.The result will find applications to the Nigeria Broadcasting Commission in the assigning of frequencies taking atmospheric parameters into considerations, Radio Engineers and Scientists, Satellite link designers, and mobile communication experts for the link budget design and appropriate equipment deployment based on the atmospheric condition on the geographical areas.

Micro input factors affecting industrial energy efficiency in Hebei Province based on granger causal relation test model

Reasonably allocating the micro factor investment in the industry and trying to improve the energy efficiency are very important for the green development of industrial economy in Hebei Province, so as to the achievement of its double carbon target. This paper takes industrial energy consumption, assets and labor in Hebei Province as micro-input elements. Based on the panel data of 34 industrial industries in Hebei Province from 2005 to 2016, we identify the correlation of micro-input factors in different industries and conduct Granger causality test. The study shows that: (1) About half of the industry’s combined energy consumption is correlated with the number of employees and assets; About two-thirds of the industry’s asset workers are relevant; (2) There is a two-way causal relationship between the total energy consumption and assets of most industries and the annual average number of employees. (3) The rational allocation of capital, labor and energy consumption depends on the deepening reform of the factor market. The high energy consumption industry should actively improve and innovate the energy technology in this process to realize the coordinated promotion of energy saving and carbon reduction, and thus to promote the healthy and sustainable development of the industry steadily.

High-Dimensional Granger Causality Tests with an Application to VIX and News

Abstract We study Granger causality testing for high-dimensional time series using regularized regressions. To perform proper inference, we rely on heteroskedasticity and autocorrelation consistent (HAC) estimation of the asymptotic variance and develop the inferential theory in the high-dimensional setting. To recognize the time-series data structures, we focus on the sparse-group LASSO (sg-LASSO) estimator, which includes the LASSO and the group LASSO as special cases. We establish the debiased central limit theorem for low-dimensional groups of regression coefficients and study the HAC estimator of the long-run variance based on the sg-LASSO residuals. This leads to valid time-series inference for individual regression coefficients as well as groups, including Granger causality tests. The treatment relies on a new Fuk–Nagaev inequality for a class of τ-mixing processes with heavier than Gaussian tails, which is of independent interest. In an empirical application, we study the Granger causal relationship between the VIX and financial news.

Bitcoin Elektrik Tüketimi ile Küresel Ekonomik Politik Belirsizlik Endeksi (GEPU) Arasındaki İlişkinin Analizi

It is possible to define uncertainty as the variability of conditions, the ambiguity and obscurity of statements and events. Uncertainty, for whatever reason, affects the economy in different ways. Uncertainty causes people to be more concerned about their future income. Various estimation and methods have been developed in recent years to calculate the uncertainty, which is equivalent to the concept of uncertainty. These indices, in which economic and political uncertainties are calculated, appear as a form of calculation that also includes political discourses along with financial risk. The aim of this study is to examine the causality relationship between the Global economic political uncertainty index and Bitcoin electricity consumption. For this purpose, the Toda-Yamamoto causality test was applied using data from the period 2011:M7-2022:M1. According to the obtained Toda-Yamamoto causality test findings, Granger causality relationship has been determined both from the global economic-political uncertainty index to Bitcoin electricity consumption and from Bitcoin electricity consumption to the global economic-political uncertainty index.

Twenty years with the Euro: Eurozone banking market integration revisited

Banking market integration is essential for a stable European Monetary Union but was severely disrupted during the Eurozone crisis. With heterogeneous national banking markets, interpreting the recent post-crisis convergence of national interest rates as restored integration has been challenged in the literature. We therefore scrutinize integration under the condition of market heterogeneity for 12 Eurozone countries before, during and after the Eurozone crisis from 2003 to 2019, employing a novel combination of state-of-the-art network analyses and estimates of bilateral interest rate linkages. We measure integration as bi-directional (Granger) causality relations between lending rates or margins in order to identify crisis-resilient arbitrage mechanisms. Their extent, disruption and restoration inform our subsequent network analysis, which unveils that the Eurozone crisis has fundamentally and persistently disrupted this network beyond the crisis period even when interest rates and margins are converging. Our approach complements and extends existing integration analyses by revealing policy-relevant but otherwise undetected disintegration.

Exploring Information Flow from Posteromedial Cortex during Visuospatial Working Memory: A Magnetoencephalography Study.

The posteromedial cortex (PMC) is a major hub of the brain's default mode network, and is implicated in a broad range of internally driven cognitions, including visuospatial working memory. However, its precise contribution to these cognitive processes remains unclear. Using MEG, we measured PMC activity in healthy human participants (young adults of both sexes) while they performed a visuospatial working memory task. Multivariate pattern classification analyses revealed stimulus-related information during encoding and retrieval in a set of a priori defined cortical ROIs, including prefrontal, occipital, and ventrotemporal cortices, in addition to PMC. We measured the extent to which this stimulus information was exchanged between areas in an information flow analysis, measuring Granger-causal relationships between areas over time. Consistent with the visual nature of the task, information from occipital cortex shaped other regions across most epochs. However, the PMC shaped object representations in occipital and prefrontal cortices during visuospatial working memory, influencing occipital cortex during retrieval and PFC across all task epochs. Our findings are consistent with a proposed role for the PMC in the representation of internal content, including remembered information, and in the comparison of external stimuli with remembered material.SIGNIFICANCE STATEMENT The human brain operates as a collection of highly interconnected regions. Mapping the function of this interconnectivity, as well as the specializations within different regions, is central to understanding the neural processes underlying cognition. The posteromedial cortex (PMC) is a highly connected cortical region, implicated in visuospatial working memory, although its precise contribution remains unclear. We measured the activity of PMC during a visuospatial working memory task, testing how different regions represented the stimuli, and whether these representations were driven by other cortical regions. We found that PMC influenced stimulus information in other regions across all task phases, suggesting that PMC plays a key role in shaping stimulus representations during visuospatial working memory.

Can people hear others’ crying?: A computational analysis of help-seeking on Weibo during COVID-19 outbreak in China

Social media like Weibo has become an important platform for people to ask for help during COVID-19 pandemic. Using a complete dataset of help-seeking posts on Weibo during the COVID-19 outbreak in China (N = 3,705,188), this study mapped their characteristics and analyzed their relationship with the epidemic development at the aggregate level, and examined the influential factors to determine whether and the extent the help-seeking crying could be heard at the individual level using computational methods for the first time. It finds that the number of help-seeking posts on Weibo has a Granger causality relationship with the number of confirmed COVID-19 cases with a time lag of eight days. This study then proposes a 3C framework to examine the direct influence of content, context, and connection on the responses (measured by retweets and comments) and assistance that help-seekers might receive as well as their indirect effects on assistance through the mediation of both retweets and comments. The differential influences of content (theme and negative sentiment), context (Super topic community, spatial location of posting, and the period of sending time), and connection (the number of followers, whether mentioning others, and verified status of authors and sharers) have been reported and discussed.

Does green finance inspire sustainable development? Evidence from a global perspective

This study assesses the causal link between green finance (GF) and sustainable development (SD) at a global scale with the bootstrap rolling-window Granger causal relationship test. The empirical results demonstrate that GF produces positive impacts on SD in multiple subperiods, which supports interaction theory. However, this article does not reach a consistent conclusion on the issue of the direction from sustainable development to green finance. GFs are a vital financing tool for sustainable development agendas. However, the influence of GF on SD has not been proven. There is currently no empirical evidence on how it can be conducive to the achievement of the 2030 Agenda. In this study, an empirical analysis of the influence of multiple stakeholders on SD through participation in green finance projects is conducted. Additionally, this analysis first identified different causalities in multiple subperiods. In a specific context, causality in a certain direction is crucial. Furthermore, we deemed that government and international organizations should guide high-quality green investment and risk prevention under the system framework. Finally, improving the classification standards, evaluation system, and information disclosure of GF can also promote the contribution of countries to sustainable development actions.