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Value relevance can be defined as the ability of accounting variables to explain or predict financial outcomes. This study intends to examine the value relevance of accounting information, specifically the impact of accounting information on the stock prices of non-financial public companies listed on the Bulgarian Stock Exchange. The examined period is 01.01.2016 -- 31.12.2021. We apply the panel unit root test, descriptive statistics, the panel regression models, the correlation matrix, and the Granger causality test. The results collected demonstrate that the earnings per share, the dividend per share, and the book value of equity per share calculated for the analyzed companies have an impact on the stock price of these enterprises. A moderate positive correlation between stock price and other accounting variables is revealed. [ABSTRACT FROM AUTHOR]

Currently, the rapid development of China's social economy has put forward higher requirements for the power supply chain, and the research on the power material price prediction model helps to ensure the adaptability and flexibility of the supply chain and provides assistance to the management of power materials. However, the time discontinuity of power material procurement data, the existing research methods to meet the demand for forecasting data in discontinuous time, this paper starts from the raw materials of electric power equipment, using Granger causality test to screen the factors affecting the price of raw materials and the lead time, and predicts the price of raw materials through the two models of linear regression and Random Forest, and calculates the numerical relationship between the raw material price and the purchase price of electric power materials, so as to utilize the predicted price of raw materials to forecast the price of electric power materials and to predict the price of electric power materials. Finally, it is found that the linear regression model is more favorable for the prediction of power equipment procurement price, and it predicts the future procurement price of 110kV power cables, and provides procurement strategies based on the prediction results. [ABSTRACT FROM AUTHOR]

Industrialization is a key element for economic growth in both developed and undeveloped countries. Due to globalization, the cause-effect between industrialization, economic growth and urbanization are changing. This study investigates the relationship between economic expansion, urbanization, and industrialization in Kenya using a quantitative methodology. Using World Bank economic indicator parameters, it focuses on understanding the complex interrelationships between these factors. Vector Autoregression (VAR) modeling is used to analyze the relationships between GDP, urbanization, and industrialization between 1990 and 2018. The Granger causality test is used to determine the causal linkages between GDP, urbanization, and industrialization. Results show that urbanization is increasing steadily across Kenya, with a high population in central, western, Rift valley, and coastal regions. The availability of agricultural land influences urbanization, with a significant positive relationship between the three parameters. The Granger causality test shows a unidirectional relationship between GDP, urbanization, and industrialization. A minimum of 20% is considered as the benchmark for urbanization to reduce both GDP and industrialization. Unplanned and rapid urbanization, accompanied by ecologically unfavorable industrialization schemes, threatens Kenya's biodiversity. The study provides insight into the interconnection between the three pillars of the economy and the statistical models developed are useful in forecasting future trends. [ABSTRACT FROM AUTHOR]

The study explores both the long- and short-run liaisons between three conceptual dimensions: economic growth, energy consumption, and trade openness in 29 net energy importing middle-income economies using annual data from 1990 to 2019. We hereby assess ARDL models which examine the long-run links by integrations in between these three conceptual variables, and additionally Dumitrescu-Hurlin and Granger causality tests for panel and individual country models, respectively. For panel country samples, we reveal bidirectional causality connection between trade openness and economic growth along with unidirectional causalities from economic growth to energy consumption and from energy consumption to trade openness in the short-run. Bidirectional positive feedback relationships stand between economic growth - energy consumption and trade openness - energy consumption in the full sample and the upper middle-middle economies subsample in the long-run. Findings for individual country estimations reveal significant long-run relationships between energy consumption and economic growth in 12, energy consumption and trade openness in 6, and economic growth and trade openness in 9 of the middle-income economies examined. [ABSTRACT FROM AUTHOR]

The goal of this study is to examine the impact of remittance inflow on inflation using the System Generalized Method of Moments (SGMM) and Dumitrescu- Hurlin Granger causality approach in countries from Central and Eastern Europe over the period 1994 to 2019. As the levels of economic and financial development vary considerably across these countries and some of them are member states of the European Union (EU), we split them into two more homogenous groups - EU member states and non-EU countries. The application of the SGMM approach reveals that remittances have a negative and significant impact on inflation in the non-EU countries, whereas they exert positive impact in the EU member states and in the whole region overall. The Granger causality test shows a unidirectional causal relationship between remittances and inflation in all country groups, whereas the existence of a positive causal relationship from remittances to inflation has been established in twelve countries. [ABSTRACT FROM AUTHOR]

The complicated interplay between the Romanian BET index, monetary policy rate, inflation rate, and RON/USD currency rate is studied using a Vector Autoregression (VAR) approach in this article. The methodology is based on the VAR model's ability to explain the dynamic relationship between multiple time series, with Granger causality tests used to identify the directionality of influence, impulse response functions used to trace the effects of economic shocks and forecast error variance decomposition used to measure the extent of variable interdependence. The findings show results about the links of monetary policy rate, inflation rate, BET index and exchange rate, with the purpose to find if capital markets are sensitive to macroeconomic policy decisions. The study emphasizes the central bank's policy rate's significance in influencing market expectations, as well as the complex impact of inflationary trends on currency valuation. [ABSTRACT FROM AUTHOR]

This study aims to provide an empirical explanation of the Causality of Domestic Investment, Foreign Investment and Employment in Central Kalimantan Province. The method in this study used VAR (Vector Auto Regression) or VECM (Vector Error Corection Model) analysis. This type of research is descriptive and associative research. The type of data in this research is secondary data obtained from the Central Statistics Agency of Central Kalimantan Province from 1992-2021. VAR/VECM Analysis steps. such as: Data Stationaryity Test (Unit Root Test), Cointegration Test (Panel Cointegration Test), Optimum Lag, Granger Causality Test, VAR/VECM Model Estimation. The results of this study show that (1) Domestic investment and one-way domestic investment and foreign investment in Central Kalimantan Province, (2) Foreign investment and absorption of non-caliphate workers in Central Kalimantan Province, (3) Domestic investment and absorption of one-way caliphate labor in Central Kalimantan Province, (4) There is a long-term relationship between domestic investment, Foreign Investment and Employment in Central Kalimantan is carried out with the Eviews 10 software. [ABSTRACT FROM AUTHOR]

The study seeks to explore and present the macroeconomic factors that drive Foreign Direct Investments (FDI) in Nigera. It employed least square methods with model diagnostic tests and Granger causality processes on 1986--2020 Nigerian yearly data. The results show that interest rate, currency rate, and level of economic activity (represented by growth in real GDP) influence the flow of FDI into Nigeria. FDI is neither driven by inflation nor by market openness. The policy implications are that when considering policies aimed at attracting foreign direct investors to Nigeria, government and monetary authorities should give priority to such factors as interest rates, exchange rates, and the growth rate of the economy. It is suggested that reduced loan rates and slight Naira depreciation should be encouraged and promoted. [ABSTRACT FROM AUTHOR]

Copyright of Journal of the Cukurova University Institute of Social Sciences is the property of Cukurova University Institute of Social Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study, for the first time in Taiwan, uses the mixed frequency vector autoregressive (MF-VAR) model in the high-frequency dataset to investigate the causal association between economic progress and carbon dioxide emissions over time periods spanning from 1970Q1-2019Q4. This study also includes primary energy consumption as a control variable for analysis since the bias of missing variables could lead to misleading results. In accordance with the forecast error variance decomposition and the Granger causality test, our empirical findings imply that the MF-VAR model has more explanatory power than the traditional VAR model. The empirical LF-VAR model results demonstrate a reciprocal and causal association between economic progress and carbon dioxide (CO2) emissions is supported by evidence; primary energy consumption significantly influences economic progress. Additionally, MF-VAR model results also indicate, in Taiwan, a reciprocal and causal association between economic progress and carbon dioxide emissions as well as between primary energy consumption and economic progress. Based on the finding of the results, this study suggests policy implications to the government that an effective energy strategy should be addressed along with the plan for economic development in Taiwan. [ABSTRACT FROM AUTHOR]

The cross-strait relations between Taiwan and China are critical in the Asia Pacific and the world. This study focuses on economic relations and their implications. The main conclusions include: First, the economic gap in output is increasingly larger, thus favouring China. Based on a time series robust least squares model, this study finds that this economic strength will significantly reduce the number of Taiwan's foreign allies. At the same time, this economic strength also brings military imbalance. Second, by employing the Granger causality tests to examine the causality relations between the stock markets of Taiwan and China, which reflect the economic integrations in areas such as the trade of goods and services and capital flow, this study finds that China is in a dominant position. At the same time, Taiwan is in a dominated position. However, except for tourism, the effects of China's dominant position as leverage seem limited. [ABSTRACT FROM AUTHOR]

The corruption-economic growth nexus and the relationship between innovation and corruption have long been extensively studied. While individual issues have been empirically analysed, two effects have not yet been sufficiently researched: (1) the overall effect of innovation on the corruption-growth relationship and (2) the direction of causality between these variables. The present article used data from 109 countries over the 2010–2018 period and focused on the macro level. We employed Granger causality tests for panel data (Dumitrescu–Hurlin) to determine the direction of causation among variables. We also employed nonstationary panel techniques with Fully Modified Ordinary Least Square (FM-OLS) to assess stationarity and long-run relationships. After investigating the direct impact of corruption on economic growth, we then examined the indirect effect through different transmission channels, including innovation. The results were tested and found robust in subcategories based on the developmental and regional levels. Finally, this study analysed the impact of innovation on the relationship between corruption and economic growth. The results indicated a robust negative relationship between corruption and economic growth and corruption and innovation. The findings also revealed a positive relationship between innovation and economic growth and a bi-directional causality between the variables. Furthermore, innovation was found to reduce the harmful effects of corruption on economic growth, mainly in developed countries. [ABSTRACT FROM AUTHOR]

The 12th Sustainable Development Goals (SDGs) highlighted the importance of ensuring sustainable consumption and production patterns. Researchers have found that energy subsidies may encourage overconsumption, misuse, and moral hazard problems. Hence, there is a need to rationalize inefficient energy subsidies. Consequently, the Malaysian government has been implementing a subsidy reformation program to improve energy efficiency and reduce fiscal burdens. This study aims to identify and compare the impacts of energy subsidies and oil prices on energy consumption across the agricultural, industrial and service sectors in Malaysia. It is critical for policymakers to better understand the role of energy subsidies in influencing energy consumption, especially the magnitude to which energy subsidies influence energy consumption, in order to structure a subsidy reform strategy which effectively addresses the energy overconsumption issue. In this study, a time series dataset covering the years of 1978 through 2018 is analyzed. The ARDL approach and Granger causality test were employed to determine meaningful statistical evidence and revealed four important findings. Firstly, energy subsidies have a positive relationship with energy consumption. Secondly, oil prices have a negative relationship with energy consumption and energy subsidies significantly interact with oil prices to affect energy consumption. This significant positive moderating effect suggests that energy subsidies may counteract the negative impact of oil prices on energy consumption. Thirdly, output has the greatest (positive) impact on energy consumption. And finally, energy subsidies drive higher outputs in the agricultural sector. [ABSTRACT FROM AUTHOR]

Uncertainty about monetary policy associated with uncertainty in interest rate is an important determinant of economic decisions. Due to the dominant position of the US economy on global financial markets, in addition to countries' own uncertainties, uncertainty related to the monetary policy of the USA may have an impact on other economies. In this study, we investigated the impact of interest rate uncertainties for different maturities on industrial production, inflation, unemployment and exchange rate. We used the impulse response functions based on the vector error correction model (VECM). We also conducted the Granger causality test to analyse the causality. We examined the impact of US monetary policy uncertainty on the mentioned variables of Turkey. Our findings suggest that uncertainty in long-term interest rates increases unemployment and inflation rates. Although we find that uncertainty in interest rate reduces growth of industrial production, we do not find a causal relationship between these variables. Finally, we show that a shock related to US monetary policy uncertainty tends to increase unemployment significantly, while reducing the growth of production. [ABSTRACT FROM AUTHOR]

The main aim of this research paper is to investigate long-term causal linkages and volatility patterns based on a comparative empirical study between the developed stock markets from USA and Netherland. The selected sample period covers a very long time interval, from February, 2000 to February 2023. The econometric framework includes a series of statistical tests such as Augmented Dickey Fuller (ADF) test, but also Granger causality test and VAR models. The empirical results are relevant and contribute to the existing literature regarding the behaviour of developed stock markets. [ABSTRACT FROM AUTHOR]

The Baltic Sea highly susceptible to the proliferation of Phytoplankton blooms. Present work examines the long-term trend and spatio-temporal variability of satellite derived chlorophyll concentration (Chl a) in the Baltic Sea during the period 2004–2021. Furthermore, the influence of water quality and meteorological parameters on Baltic Sea primary productivity has been analyzed using robust Generalized Additive Models (GAM) and Granger Causality statistical test. Statistically significant increasing trend in chlorophyll a concentration is observed in the Baltic Sea at the 95 % confidence interval. GAM model reveals that the most significant controlling factor is sea surface temperature (p < 0.0001), followed by nitrate and phosphate. Both GAM and Granger Causality tests confirm that water quality parameters are the major drivers in limiting the growth of Phytoplankton blooms in the Baltic Sea. Summer bloom shows in-phase relationship with Sea surface temperature and out of phase relationship with the phosphate nutrient. • Increasing trend of Chlorophyll a concentration in the Baltic Sea results from increased nutrients loads and warmer temperature. • Sea surface temperature acts as most significant predictor that limits the growth of phytoplankton blooms. • Water quality parameters are the potential causal drivers that promotes the growth of phytoplankton blooms in the Baltic Sea. • Summer bloom shows in-phase relationship with Sea surface temperature and out of phase relationship with the phosphate nutrient. [ABSTRACT FROM AUTHOR]

This paper analyzes the dynamic impact of economic, social, and governance factors on PM2.5 concentrations in 89 countries from 2006 to 2019. Using the GMM-PVAR approach and Impulse-Response Functions, we examine how shocks to specific variables affect PM2.5 concentrations over a 10-year period. Our findings reveal that the influence of these factors on PM2.5 levels varies over time. For example, a shock in urbanization has no effect on PM2.5 concentrations in the first year, but in the second year, pollution increases significantly. In the third period, PM2.5 levels decrease, but they rise again in the fourth period, albeit not significantly. By the fifth period, pollution decreases until a new equilibrium is reached in the sixth period. Additionally, a shock in financial development, government effectiveness, industrialization, trade openness, or GDP has no effect on PM2.5 concentrations in the initial period. However, during the second period, air pollution decreases, followed by an increase in the third period and a decrease again in the fourth period. These dynamic patterns highlight the need for environmental policies that consider the evaluation time horizon. Our analysis is supplemented by the Granger causality test, guiding specific policy recommendations based on our findings. [Display omitted] • The highest concentrations of PM2.5 are observed in Tajikistan, Cameroon, Niger, and Egypt. • The lowest PM2.5 concentrations are found in Norway, Sweden, and Finland. • Reducing air pollution has a significant impact on urbanization levels in countries. • Changes in government effectiveness significantly affect PM2.5 concentrations. • GDP influences PM2.5 concentrations with feedback effects. [ABSTRACT FROM AUTHOR]

Since the Japanese government announced the launch of the Fukushima nuclear contaminated water discharge plan, it has aroused widespread concern and controversy in the international community. As a maritime neighbor of Japan, China has been affected by this incident, and Chinese public sentiment and aquatic product prices have fluctuated to a certain extent.In order to explore the internal relationship between the two, this study based on the microblog (Chinese Twitter) text data obtained by web crawler, and used LDA model to mine the public discussion topics at different stages of the event, perceived the public emotional changes, formed the public emotional time series, and constructed Granger causality test model to explore its relationship with aquatic product price volatility. Through empirical analysis, this paper has the following important findings: First, the impact of the change of negative public sentiment on the price fluctuation of aquatic products is more obvious than that of the overall public sentiment; second, the negative public sentiment is not only the Granger cause of the price fluctuation of seawater products, but also the Granger cause of the price fluctuation of freshwater products.To a certain extent, this study enriches the research on the influencing factors of aquatic product price volatility, especially exploring the relationship between public sentiment on social platforms and aquatic product price volatility under the influence of uncertain events. The research results provide theoretical reference for guiding network public opinion, eliminating public negative emotions, ensuring the stable operation of market prices and guaranteeing people's normal life; At the same time, the study of social media data also provides us with a unique perspective, which enables us to grasp the emotions of the social public more accurately, and thus provides important value for our academic research. [ABSTRACT FROM AUTHOR]

Climate policy is essential for fostering sustainable development and addressing climate-related issues, while climate policy uncertainty (CPU) introduces complex challenges in providing a consistent framework for action. In this study, we delve into the spillover dynamics among China's domestic CPU, foreign CPU, physical assets, and financial assets across various market scenarios, through a quantile-based connectedness method and evidence from China. The findings reveal: (1) The spillover dynamics are asymmetric across quantiles and time, and the COVID-19 pandemic influences the total connectedness. (2) The complexity of spillover patterns in physical assets is likely contingent upon market conditions, policy sources, asset types, and industrial-chain positions, while the spillovers of financial assets are quantile-dependent and time-varying, with the agricultural equity market showing relative resilience to the pandemic. (3) There is no significant Granger causality in quantiles between domestic CPU and foreign CPU under the entire sample period, and the rankings regarding the spillovers from CPUs to assets vary across market conditions. Implications for policymakers, investors, and firms are provided. • The spillovers of climate policy uncertainties (CPUs) and assets are asymmetric. • The pandemic influences the quantile-dependent total connectedness. • The spillover dynamics rely on market conditions and asset types. • Granger causality between China's domestic and foreign CPU is absent. • The agricultural sector shows relative resilience to the pandemic shock. [ABSTRACT FROM AUTHOR]

The main goal of the paper is to assess the relationship between inflation, inflation instability and nominal uncertainty in the Bulgarian economy in January 2000 - May 2022. Employing the ARCH model, GARCH-M model, EGARCH model and Granger Causality Test we find a two-way causal relationship between inflation and inflation instability. Initially, inflation provokes inflation instability, and inflation instability provokes inflation consequently. Nominal uncertainty is measured by wavelet analysis, which establishes the presence of nominal uncertainty in the Bulgarian economy. Therefore, at certain lags, the inflation instability is transformed into nominal uncertainty. The empirical evidence raises the question of the effectiveness of the Currency Board Arrangements in Bulgaria. [ABSTRACT FROM AUTHOR]

The efficient market hypothesis dominates in the studies on the effectiveness of stock market performance, one illustration of which is the presence of calendar anomalies of different nature. The advent of the Adaptive Market Hypothesis calls into question both the presence of such anomalies and the effectiveness of the stock market. To confirm the effective market hypothesis, the time series behaviour of the rates of return of the most significant global stock indices and a local Ukrainian PFTS Stock Index has been investigated in the work. According to the study results, the efficient market hypothesis has not been confirmed; the results partially confirm the adaptive market hypothesis. To confirm the hypothesis that global stock markets have an impact on local stock exchanges, a pre-selected sample of time series of stock index rates of return was used. The Granger causality test was used for this purpose. To determine whether the time series of the dynamics of the stock index rates of return are stationary, the advanced Dickie-Fuller test was used since it takes into account the possible autocorrelation in residuals. The Phillips-Perron test was used as well. [ABSTRACT FROM AUTHOR]

Sustainable development has become a new engine to promote economic growth, in which scientific and technological progress, green finance and the efficient development of a green economy have become the main driving forces of economic and societal development. Hence, the continuous improvement of innovation ability through scientific research innovation, as well as the rapid development of the technology market, is an important force for the sustainable development of China. Therefore, by first analysing the related data from 2001 to 2020 of China's technology market, the time series value of the comprehensive evaluation is obtained. Then, based on the unit root test, cointegration test and Granger causality, this study explores the relationship between the technology market turnover and scientific research innovation. The results show a second-order cointegration between the technology market turnover and scientific research innovation. Scientific research innovation can promote the development of the technology market from the perspective of long-term equilibrium and reverse correction in the short term. Mutual Granger causality and a first-order significant lag are observed between technology market development and scientific research innovation. It is necessary to further improve the management mechanism of the technology market. The government should promote the continuous innovative development of the technology market to improve the efficiency of resource allocation and enhance the connection between the technology market and innovation subjects. [ABSTRACT FROM AUTHOR]

Impairments in speech production can have devastating effects on the overall quality of life in left-hemisphere stroke survivors with aphasia; however, there is a paucity of research focusing on neural deficits in speech motor planning networks that are activated prior to the onset of speech production in this clinical population. In the present study, we examined directional brain connectivity correlates of speech preparation and planning in low-β (13-20 Hz) and high-β (21-30 Hz) band neural oscillations in participants aphasia compared with controls prior to the onset of speech. Electroencephalographic (EEG) data were concurrently recorded from 33 participants with post-stroke aphasia and 22 neurologically intact controls while they engaged in speech production tasks. Using Granger causality, brain connectivity was calculated between electrode pairs that fell within fronto-frontal, fronto-central, and fronto-parietal networks implicated in sensorimotor integration and speech planning. Clinical assessment was further conducted in post-stroke participants to measure the severity of language impairment associated with aphasia. Increased intra-hemispheric connectivity was found within low- and high-β bands in the left parieto-central and parieto-frontal as well as the right fronto-frontal and fronto-central electrodes in post-stroke participants compared with controls prior to the onset of speech production. In addition, we found that decreased inter-hemispheric centro-central connectivity within high-β band was negatively correlated with aphasia severity whereas increased parieto-frontal connectivity within high-β band was positively correlated with aphasia severity. These findings suggest that participants with left-hemisphere stroke express aberrant brain connectivity within low- and high-β bands in both left and right hemispheres during the planning phase of speech production, and that these deficits are associated with specific aspects of their language impairment, as indicated by their clinical symptoms due to aphasia. [ABSTRACT FROM AUTHOR]

This study examines the causal relationship between road transportation and economic growth in 31 provinces and municipalities in China by using province-level panel data covering the period from 1980 to 2015. This study adopts the Granger causality analysis based on meta-analysis in heterogeneous mixed panels. The empirical model also considers the heterogeneity of the coefficients and the cross-sectional correlations of the panel data. The empirical results confirm that the bi-directional causal relation between road transportation and economic development is the dominant type in various provinces and municipalities in China. Moreover, the results reveal a unidirectional causality running from road transportation to economic growth in Beijing, Shanghai, Heilongjiang; a unidirectional causality running from economic growth to road transportation in Tianjin, Fujian and Hunan; and no causal relation in Tibet. The results imply that road transportation and economic growth in most parts of China are mutually coordinated. [ABSTRACT FROM AUTHOR]

The purpose of this study is to examine the causal linkage between military expenditures and economic growth in 27 North Atlantic Treaty Organization (NATO) member countries. Different periods are studied due to the unavailability of data for the common period for all countries. Both the symmetric and the asymmetric causality between military expenditures and economic growth are investigated under cross-sectional dependence and panel heterogeneity by using the bootstrap panel Granger causality testing approach. The results indicate that there is both symmetric and asymmetric Granger-causality between military expenditures and economic growth, which vary from one country to another. The robust empirical findings support the military expenditures and economic growth nexus in 12 of the 27 NATO member countries. Moreover, the findings show that more empirical evidence between military expenditures and economic growth can be obtained when the asymmetric causality is considered, in addition to the symmetric causality. [ABSTRACT FROM AUTHOR]

Copyright of Industria Textila is the property of Institutul National de Cercetare-Dezvoltare pentru Textile si Pielarie and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

India is an agrarian economy and stands 2nd in the world population. India is in sixth place in the list of the most significant economies globally and 3rdin the purchasing power after the United States and China. However, India still has many growing concerns like a declining share of agriculture in the GDP, rapid increment in the population, unemployment, and others. The present study investigated the linkage between agricultural land, population density, and economic growth in India. The data from 1970 to 2019 was analysed using a vector error correction model (VECM) and Granger causality test. Further, the variance decomposition (VDC) and impulse response function (IRF) was employed for a detailed explanation of the variables' relationship and innovation responses of explanatory variables. The Granger causality test results suggested that agricultural land and the gross domestic product have a neutral relationship. The population density and gross domestic product support the feedback hypothesis. Additionally, population density affects agricultural land, whereas agricultural land does not affect population density. From a policy perspective, policymakers should frame strategies to decide the nation's comprehensive significance of population density. Too high populace density diminishes the natural endowment per capita. However, it facilitates infrastructure development, prompting an ideal populace density for economic development. [ABSTRACT FROM AUTHOR]

The agricultural, Industrial and Services sectors have crucial role in the economic development of Pakistan economy. The goal of this study was to investigate the interrelationships among the key sectors and between the key sectors and GDP. To accomplish the study time series data ranging 1950 to 2014 were obtained from different sources. Stationarity analysis of time series was made by applying Augmented Dickey- Fuller and Philips - Perron unit root tests, stationarity analysis indicated that all the variables were not level I (0) stationary but differenced I (1) stationary which satisfied the condition of same order of integration and study variables to be cointegrated. Correlation analysis depicted positive and negative correlations among study variables. To attain the objective of the study Engel Granger two step method was applied. The co-efficient indicated long run relationship among the variables. The Error Correction Model’ short run coefficient was found significant and depicted convergence to long run equilibrium. The Granger causality analysis explored the existence of bidirectional causality between agriculture and GDP, bidirectional causality between industry and GDP, bidirectional causality between GDP and services sector, unidirectional causality between industry and agriculture and industry was found granger cause agriculture, bidirectional causality between agriculture and services sector and indicated unidirectional causality between industry and services sector and industry was found granger cause services. [ABSTRACT FROM AUTHOR]

Below paper is an attempt to study impact of World Stock Market of Countries like United Kingdom, United States of America and China on stock market of India NSE over a period of five years covering from 1 april 2016 to 31 march 2021 using Correlation, Regression and Granger's causality test. Result of the study shows that movement in stock market of united states of America, United Kingdom, China impact the stock market of India NSE (directly or indirectly). in this way this paper is an attempt to examine indispensable factor that affect Indian stock market directly or indirectly. this paper also analyze various prior study done in the same field. [ABSTRACT FROM AUTHOR]

This study examines the impact of cryptocurrency uncertainty indices on green bonds, currency, and commodity markets by using weekly data from January 1, 2014, to December 30, 2022. The study analyzes such relationships employing the time-varying robust Granger-Causality test coupled with the TVP-VAR-DY approach. The empirical findings unfold the heterogeneous effects of uncertainty indices toward diverse financial instruments pronounced during financial or economic turbulence. The DY approach indicates that total connectedness among financial assets varies significantly over time. The green bond market is the net receiver, while ishares Global Clean Energy ETF (ICLN) and VanEck Low Carbon Energy ETF (SMOG) indices transmit the shocks for the whole period. The findings suggest that holdings in the green bond market after the health crisis offer greater hedging opportunities to investors. The results have significant ramifications for financing, hedging, and policymaking. • We examine the impact of cryptocurrency uncertainty indices on green bonds, currency, and commodity markets. • Time-varying robust Granger-Causality test and TVP-VAR-DY techniques are employed. • The effect is more pronounced during financial or economic turbulence. • The Green Bond market is the net receiver, while ETF (ICLN) and ETF (SMOG) indices transmit the shocks for the whole period. [ABSTRACT FROM AUTHOR]

When making decisions, investors who want to buy specific companies often pay attention to the situation on the entire market or in a given industry. Therefore, the starting points are the historical and current quotations of companies and indexes published by Warsaw Stock Exchange. The capital market is a system in which there are various types of connections, in particular between companies or companies and indexes. The main goal of the paper is the examining of the dependence between quotations of the companies from the food sector and the main market indicators. The indexes taken into account are WIG, WIG20, mWIG40, sWIG80 and WIG-food. In order to answer the question whether there are dependencies between the food industry (represented by the WIG-food index) and other market segments, i.e. the segment of small, medium and large companies and the entire market, research was conducted using the Granger causality test. Various lags were considered. Previously, the autocorrelation of return rates and their stationarity were examined. The data concerned the period 2008-2019, for which the monthly rates of return were determined. The rates are calculated in standard not-logarithmic way. The period of time taken into account is after crisis time but the market situation was unstable. There were periods of downward and uprise market. The paper shows that the WSE broad market indices have an impact on the WIG-food index, but the opposite is not true. The use of Granger's causality model confirmed earlier conclusions from the analysis of the coefficients of effectiveness and linear regression models, which were the subject of earlier works by the authors and others. It occurred that one period lags had the most influence on the correlations (also two, three and six lags were examined). That is why Granger causality test were performed for these cases. The final results show that the dependences between main indexes of Warsaw Stock Exchange and WIG-food are rather weak. [ABSTRACT FROM AUTHOR]

This study examined the impact of exchange rate volatility on manufacturing output in the ECOWAS, using time series data spanning from 1970 to 2019. The study employed panel data analysis to examine the relationship between exchange rate volatility and manufacturing output among all the ECOWAS countries. GARCH was used to establish the existence of volatility; Dumitrescu & Hurlin Granger non-causality test for causality direction between manufacturing and exchange rate, while Panel fixed, and random effect model was used to assess the magnitude of the effects of exchange rate volatility on manufacturing output in ECOWAS. The result of the volatility test from GARCH confirmed the presence of volatility in Exchange rates across all the countries in ECOWAS. Furthermore, the random effect model results showed that exchange rate volatility has a positive and significant impact on manufacturing output in ECOWAS. Based on the findings of this study, it is therefore recommended that exchange rate policies such as floating exchange rates and exchange rate sterilized intervention that will pave the way for competitiveness should be formulated by monetary authorities in ECOWAS. [ABSTRACT FROM AUTHOR]

To investigate the contribution of green credit (GC) to improving air quality in China, the bootstrap sub-sample rolling-window Granger causality test is employed. This test considers the structural changes of parameters that affect the accuracy of the conclusion and analyzes the dynamic relationship between GC and air quality. The sub-sample empirical results show that GC's infancy and mature stages have diverse impacts on the environment. In the early stage of GC, due to a low proportion of GC in overall credit and lack of the incentive to provide GC for banking institutions, the environmental effect of GC has not been demonstrated. With the continuous improvement of the GC system, the positive effects of GC on air quality begin to emerge later, which is supported by GC and air quality interaction theory. This discovery is beneficial for policymakers to find flaws in the current GC system and grasp the direction of a well-designed GC policy to construct a modern economic system with sustainable development Moreover, this paper provides another perspective that air quality has a feedback effect on GC policy. This evidence that air quality is a leading indicator helps enterprises predict banking institutions' credit preference changes and adjust financing strategies in advance. It is significant to build a virtuous cycle between GC and the environment and promote sustainable economic development. [ABSTRACT FROM AUTHOR]

The purpose of this study is to see whether Okun's coefficient exists in South Africa. The study analysed yearly data from 1995 to 2020. The study used an error correction model (ECM) to assess the short-run relationship between the variables under investigation. The granger causality test is also used to examine the variables' short-run causality. According to the study's results, there is a negative and significant relationship between unemployment and GDP in the short run. As a result, Okun's Law applies in South Africa. The Granger causality test findings reveal that GDP Granger causes unemployment in South Africa. As a result, the study recommends that policymakers prioritize balancing labour-intensive and capital-intensive jobs, as well as encouraging entrepreneurship and sufficient education and training. [ABSTRACT FROM AUTHOR]

In this paper, we examine a potential causal link between vehicle emission standards and local automotive industry performance, using a 42-country panel data set covering a 19-year period between 2000 and 2018. Our panel logit analysis shows that having a sizeable local automotive industry decreases the chance of adopting stringent vehicle emission standards, while the stock of automotive FDI increases the chance. This finding suggests that the primary motivations for vehicle emission standards may not be purely environmental. Our follow-up Granger causality test demonstrates that such non-environmental motivations have in fact translated into an actual industry-promotion outcome. Stricter emission standards in OECD member countries tend to promote local automotive output and international vehicle export with a 3-year time lag, while this causal link is limited to up-market exports for non-OECD panels. Automotive FDI hosts with large domestic markets and/or local-brand automakers also present a similar causal link, but in this case significant long-term industry-promotion effects appear only after a short-term negative shock. These results suggest that a regulation-induced short-term efficiency loss may be partly offset by a long-term productivity gain through advance/timely local adoption of cleaner technologies. • Vehicle emission standards involve non-environmental motivations, as well. • Local production volume and FDI stock affect the stringency of the standards. • Regulation-induced efficiency loss can be partly offset by long-term productivity gain. • Stricter standards tend to have pro-export effects with a 3-year lag. • The causal link depends on domestic market size and local-brand automakers. [ABSTRACT FROM AUTHOR]

This study examines the correlation and integration between various stock exchanges of India, China, Singapore, the United States of America and, the United Kingdom. This paper also investigates the causality between the selected stock exchanges during the pandemic period of H1N1 and COVID-19. The analysis was made by using the daily stock exchange values. The prior and after four months of data chosen for the study based on the first case of H1N1 and COVID-19 registered in the USA. The correlation, Johansen Co-integration, and Granger Causality test are applied in this study. Through the various techniques, the strong association between all the selected stock exchanges are been identified during the pandemic situation of H1N1 and COVID-19. The finding can be used for investment and proactive decisions during pandemic situation. [ABSTRACT FROM AUTHOR]

This paper focused on studying the determinants of foreign investment in the Kingdom of Saudi Arabia between 1979 and 2019. The context of the study is unique in that it targeted KSA, a developing nation, and its 41-year market starting in 1979 through 2019. This study uses some technique such as, cointegration by unit roots test (ADF, PP and KPSS), Johansen's cointegration test (trace and maximum-eigenvalue) and Granger causality tests for short-run and long-run in order to confirm causal relationship between variables. moreover, this study uses ARDL regression to test the short-run and long-run relationship between determinants of FDI. The study revealed that FDI has cointegrating with some variables as tested by Johansen's cointegration test. Moreover, Granger causality tests. The results of Granger causality tests show that FDI does not Granger cause with all variables during the short-run but GDP Granger cause with FDI. Moreover, GDP, inflation and external balance have causality with FDI during long-run. in addition, the results of ARDL (short-run) found that external balance has effect positively significant with FDI. the outcomes are expected to boost the flow of foreign investment, which is the paper's goal that has been central from the start. The report confirms all recent and existing studies and is considered to be a comprehensive contribution to the Saudi economy, since the report selected a 41-year period - one not previously studied by previous researchers. [ABSTRACT FROM AUTHOR]

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The research article examined the causal nexus in between two listed (NCDEX) benchmark agricultural futures indices in India, say, NKRISHI (Weighted Index) and AGRIDEX (Return based Index). Daily closing futures prices has been retrieved from official platform of NCDEX dated from April 1, 2018 to January 29, 2020 as first period (Pre-COVID19) and from January 30, 2020 to October 11, 2021 as second period (During COVID19). The causal nexus has been examined by using of Unit Root test (ADF), pairwise Granger Causality and Johansen Co-integration tests. The empirical investigation help to comprehend that there is no significant relationship (long-run as well as short-run) in between AGRIDEX and NKRISHI indices in both Pre-COVID19 and During-COVID19 periods. The results concluded that there is not a big impact on both the indices after the COVID19 outbreak. The Results highlight the efficiency of both the markets, say, NKRISHI and AGRIDEX futures indices, and also establish relevant information for investors, policymakers, researchers and hedgers for future investments and further analysis. It contributes to the market efficiency literature for agricultural futures market. [ABSTRACT FROM AUTHOR]

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The study used the VECM-BEKK-MGARCH method to model the volatility transmission between the markets of gasoline, exchange rates, and the hazelnut market for the period of 21.07.2005-20.3.2018. The suitability of the VECM-BEKK-MGARCH method was confirmed by statistical testing. The changes in hazelnut prices were not affected by the changes in the prices or final values in the other two sectors (Granger causality). Moreover, the Granger causality tests revealed that, while the change in the gasoline market was not affected by the other two markets, the change in the exchange rates market was affected by the other two markets. Furthermore, especially the volatilities (longterm uncertainties) of the markets were affected by both their own short- and long-term volatilities and other sectors' short- and long-term volatilities. It was shown that the long-term swings in these three markets were affected by the cross-interaction in the markets. Additionally, as opposed to the case in the positive news, it was observed that pieces of negative news affected the markets. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao is the property of Chinese Journal of Applied Ecology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article aims first to investigate the main determinants of the informal economy (IE) in Algeria using the Multiple Indicator Multiple Causes (MIMIC) approach, second to estimate its size and development, third analyse the relationship in the short and long run between the informal and formal economy, and finally to explore the causality direction by employing the Granger causality test from 1980 to 2017. The results showed that the tax burden, the agricultural sector, the quality of institutions, and the GDP per capita are the main determinants of the IE in Algeria. The average IE size is 33.48% of official GDP, and it has been increasing in size over the past 15 years. Furthermore, it has been found that the IE positively affects the formal economy in the short run, while in the long run, this effect is reversed. Moreover, unidirectional Granger causality from GDP to IE is found. As for policy implications, in order to lower the size of IE in Algeria, the government needs to reconsider its tax policies, including the re-examination of policies implemented to stimulate the agricultural sector, which half of their effects are absorbed by the IE, and the generalization of the use of electronic transactions in economic activities. • This article estimates the size and development of the informal economy in Algeria. • The relationship between formal and informal economy is investigated. • Average size is 33.48% over the period of 1980 to 2017. • Short and long run asymmetric effect between IE and GDP is found. • There is a unidirectional Granger causality from GDP to the informal economy. [ABSTRACT FROM AUTHOR]

The present study investigates the role of international tourist arrivals, structural change, consumption of energy, international trade, and economic growth on CO2 emissions in Pakistan over a period of 1980–2017. The study employed ARDL model, which revealed that there is a strong positive long-run association between CO2 emission and its determinants except for structural changes and trade that have no significant impact on CO2 emissions. Results reveal that tourism activities in Pakistan are environment friendly and it can add to preserve the scenic areas and major visitors' spots in the country to attract more visitors to increase the revenue of the country. The study further applied Granger causality test and ratifies unidirectional causality from structural change, international tourist arrivals, and consumption of energy towards CO2 except from international trade. Moreover, this study employed DOLS technique to get long-run robust estimates. [ABSTRACT FROM AUTHOR]

In this article we use econometric methods to identify and analyze the causal links between budget revenue collected in Romania and various economic variables, including macrofinancial variables. The data set used consists of quarterly frequency values for the 2000 quarter 1 - 2019 quarter 4. The methods used in the analysis are simple and multiple linear regression, the Granger causality test and simple and multiple nonlinear regression models. The results obtained show that the economic variables, as a whole, explain only a quarter of the variation of the share of tax revenue in GDP. [ABSTRACT FROM AUTHOR]

Over the past several decades, obesity has grown into a major global epidemic. This dramatic rise in rates is more pronounced in developing countries, as compared to more industrialized societies. In Peru, obesity rates are escalating. In this paper, Granger Causality Test in Panel Data, Dynamic Panel Data Analysis, and Cointegration Analysis in Panel Data from 2008 - 2020 in 24 regions with a sample size of 312 data points - is used. We find that there is a cointegration among obesity, poverty, and economic growth, which ensures a long-run relationship between the variables. In addition, our analysis found that regarding the initiative of government regulation, which introduces technical parameters of processed foods and nonalcoholic beverages and which was approved in terms of sugar, sodium and saturated fat content, is not effective. Finally, the results obtained show that the quarantine period in the context of the COVID-19 pandemic also has contributed to an increase in obesity rates in the regions of Peru during the 2008 - 2020 period. [ABSTRACT FROM AUTHOR]

Copyright of Industria Textila is the property of Institutul National de Cercetare-Dezvoltare pentru Textile si Pielarie and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study examines the market and price behavior is the supreme problem of commodity investors and trader. The present study spotlights the price behavior/movement and market behavior/volatile in Indian agricultural commodity market (MCX). The study aims to study the volatility and caused effect between cotton futures price and cotton spot price from the period 2017 to 2019 daily data were collected from Multi Commodity Exchange (MCX). This study also analyzed the correlation and cointegration between the cotton spot price and cotton futures price in Multi Commodity Exchange (MCX). The study employed statistics tools such as descriptive statistics, unit root test (ADF test), correlation test, OLS regression test, cointegration test, granger causality test, and GRACH Test. The study found that existence of normality and absence of unit root in time series data, also risk was higher than the mean return of cotton futures and spot price. There was low positive correlation between cotton futures price and cotton spot price. Produced very low and least positive impact of cotton spot price on cotton futures price whereas low and positive impact of cotton futures price on cotton spot price. The GARCH test evidenced that low volatility secured both cotton futures price and cotton spot price and absence of cause and effect during the study period. The investors have to consider the high volatility commodity futures price which make effective in trading and investments in the aspect of price discovery. The result replicates that each commodity traded or invested in exchange has different price effectiveness concept and the investors and trader should recognize the commodity to hedge price risk. [ABSTRACT FROM AUTHOR]