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This paper aimed to explore the impact of the dynamic relationship between broiler price and pig price on the healthy and stable development of the livestock and poultry breeding industry. Selecting monthly data on broiler price and pig price from January 2020 to August 2023, this study empirically explores the dynamic correlation between broiler price and pig price using VAR models, impulse response functions, and Granger causality. The results showed that an increase in the price change rate of broiler can effectively increase the price change rate of pig, and an increase in the price change rate of pig can also effectively increase the price change rate of broiler. There is a bidirectional causal relationship between the price of broiler and the price of pig. Compared to the price of pig, the price change rate of broiler is mainly influenced by their own prices. The price change rate of pig is mainly influenced by both the price change rate of broiler and their own price change rate, and the degree of influence of the price change rate of broiler is higher than that of their own. The price change rate of broiler plays a dominant role in the fluctuations of broiler price and pig price. The research shows that there is a dynamic correlation between the price of broiler and the price of pig, which can effectively improve the information judgment ability of price changes, in order to help the livestock breeding industry to improve quality and efficiency. [ABSTRACT FROM AUTHOR]

Knowledge of the causality between Energy Consumption and GDP is important because it leads to the future actions of policymakers, such as developing infrastructure in case GDP growth depends on Energy Consumption. Hence, the Granger Causality between the Gross Domestic Product and Energy Consumption of Ecuador is analysed in this research. For this purpose, a VAR model was developed with data from 1965 to 2022. Before including the time series inside the VAR model, ARIMA models were evaluated so that the need for differentiation and the use of dummy variables was detected. To ensure that the models include all possible information from the available data, the residuals were diagnosed until they did not have any autocorrelation between each other, there was no evidence of heteroskedasticity, and the residuals had a normal distribution. The Akaike Information Criteria and the Schwarz criteria indexes were compared to detect causality. The Granger p-value was also used to detect the probability of having null coefficients in the added time series. In the end, it was shown that Energy Consumption Granger causes Gross Domestic Product growth, but the same does not happen in the reverse direction. As a consequence, the government could support the development of energy infrastructure to incentivise economic growth. [ABSTRACT FROM AUTHOR]

BackgroundDengue fever is a serious public health issue in Bangladesh, where its incidence rises with the monsoon. Meteorological variables are believed to be responsible factors among others. Therefore, this study examines the effects of meteorological variables (temperature, rainfall, and humidity) on dengue incidence in Bangladesh. While previous studies have examined the relationship between dengue and meteorological variables using single model approaches, this study employs advanced econometric techniques to capture dynamic interactions. Furthermore, in the case of Bangladesh, this type of analysis is necessary due to the fact that dengue outbreak become one of the major issues. However, the analysis related to this issue is not available.MethodsFor estimation purposes, the Augmented Dickey-Fuller (ADF) test, Vector Autoregressive (VAR) model, Granger causality tests, Impulse Response Function (IRF), Variance Decomposition (VDC), and Vector Error Correction Model (VECM) are employed.ResultsRainfall has a significant impact on dengue incidence compared to temperature and humidity. The Granger causality test demonstrates that rainfall and dengue incidence are causally related unidirectionally. Rainfall can potentially have a short-term and long-term effect on the incidence of dengue, as per the estimates of the VECM model.ConclusionsThese findings will assist policymakers in Bangladesh in developing a dengue fever early warning system depending on climate change. In order to efficiently avoid the spread of dengue in Bangladesh's dengue-endemic urban areas, this study suggests societal monitoring.

Knowledge of the causality between Energy Consumption and GDP is important because it leads to the future actions of policymakers, such as developing infrastructure in case GDP growth depends on Energy Consumption. Hence, the Granger Causality between the Gross Domestic Product and Energy Consumption of Ecuador is analysed in this research. For this purpose, a VAR model was developed with data from 1965 to 2022. Before including the time series inside the VAR model, ARIMA models were evaluated so that the need for differentiation and the use of dummy variables was detected. To ensure that the models include all possible information from the available data, the residuals were diagnosed until they did not have any autocorrelation between each other, there was no evidence of heteroskedasticity, and the residuals had a normal distribution. The Akaike Information Criteria and the Schwarz criteria indexes were compared to detect causality. The Granger p-value was also used to detect the probability of having null coefficients in the added time series. In the end, it was shown that Energy Consumption Granger causes Gross Domestic Product growth, but the same does not happen in the reverse direction. As a consequence, the government could support the development of energy infrastructure to incentivise economic growth.

The outbreak of the oil crisis in the 1970s had an extremely profound impact on the world economy. The use of computer simulation is employed in this paper to explore how the oil crisis led to the restructuring of the world economy in the 1970s. Taking the United States as a representative, we study its main economic characteristics, such as price and currency in the 1970s oil crisis, and analyze the changes in economic characteristics before and after the oil crisis to provide data support for this paper to simulate the impact of the oil crisis on the structure of the world economy. Adopt the VAR model for computer simulation research. The GDP and CPI data of the United States, Europe, Japan, and other countries in the 1970s are selected to construct the variables of the world economic structure. After analyzing the processed data in terms of the Granger causality test, impulse response, and variance decomposition, this paper concludes that the oil crisis triggered by the increase of oil prices in the 1970s has had a significant impact on the world economic structure and the long-term oil crisis will force countries around the world to actively adjust their economic structure in order to cope with the downturn of the economy caused by the oil crisis.

The aim of this study is to examine the association between the capital flows of foreign institutional investors (FIIs) in the equity derivatives market in India and the implied volatility of options. Previous studies on FIIs and realized volatility in the equity market provide the basis for this study. Covering a period of ten years (2012–2021), this study established the importance of FII capital flows in explaining the implied volatility of options. The Granger causality test confirms the unidirectional flow of causality between FII and implied volatility (VIX) in the Indian stock market. The vector autoregression model developed in the study confirms the dynamic relationship between implied volatility and the investment behavior of foreign institutional investors (FIIs). The outcome of this study will help options traders to understand the mispricing of options because of FII's buying pressure on implied volatility. The results will also help policymakers understand how institutional investors influence option pricing so that appropriate decisions can be made. [ABSTRACT FROM AUTHOR]

This study uses time series data from the World Bank database to examine the relationship between unemployment and entrepreneurship in Namibia. We applied the Augmented Dickey–Fuller and Phillips–Perron tests for unit root testing and found all the variables to be stationary after the first difference. Given that, we employed the Johansen–Juselius test to measure cointegration, which revealed the absence of long-run relationships between the variables. Hence, we performed a Vector Autoregressive model to estimate the short-run relationships and found that Namibia exhibits both the refugee and Schumpeter effects. Finally, we measured the direction of causality using the Pairwise Granger causality test, and the results revealed that none of the variables Granger causes the other, implying that they are all independent of each other. This implies that the significance of entrepreneurship in addressing unemployment in Namibia is limited in the long run, mostly owing to the absence of sustainable business ventures. Therefore, we recommend prioritizing the development of policies to tackle unemployment through sustainable entrepreneurship. [ABSTRACT FROM AUTHOR]

Copyright of Omer Halisdemir Universitesi Iktisadi ve Idari Bilimler Fakültesi Dergisi is the property of Omer Halisdemir University, Faculty of Economics & Admistrative Sciene 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 re-examined the effect of official development assistance (ODA) of five major donor countries (France, Germany, Japan, the United Kingdom, and the United States) on foreign direct investment (FDI) using panel data from 2003 to 2020. In addition to the system Generalized Method of Moments (GMM) with the gravity model, the Granger causality test and impulse response analysis with the panel VAR model was conducted. It was concluded that ODA did not necessarily have an effect on FDI since the 2000s. It is also suggested that the vanguard effect of Japanese ODA, as indicated by some previous studies, appeared mainly in the 1990s and may not be sustainable. The novelty of this study is to verify the effects of the ODA of major donors on FDI using new data from the 2000s onward, especially to reveal that the vanguard effect of Japanese ODA has not been observed since the 2000s. A limitation of this study is to determine only the presence or absence of a general trend at a statistically significant level. Therefore, further research on individual cases is expected to find how ODA has affected the investment decisions of individual companies. [ABSTRACT FROM AUTHOR]

Bu çalışmanın amacı BIST Turizm endeksi, USD/TL, faiz oranı ve petrol fiyatları arasındaki karşılıklı ilişkiyi araştırmaktır. Çalışmada Ocak2008-Aralık 2020 dönemi aylık verileri kullanılmıştır. BIST Turizm endeksinin döviz kuru, faiz oranı ve petrol fiyatlarında meydana gelebilecek bir artışa tepkisini değerlendirmek için Vektör Otoregresif Modeller (VAR) modeline dayalı etki-tepki fonksiyonlarından yararlanılmıştır. Ayrıca değişkenler arasında herhangi bir nedensellik ilişkisinin olup olmadığını tespit edebilmek için VAR Granger nedensellik testi uygulanmıştır. Etki-tepki fonksiyonlarına göre Turizm endeksinin dolar şokuna pozitif tepki verdiği tespit edilmiştir. Faiz oranının ise BIST Turizm endeksi üzerindeki etkisinin 4. döneme kadar zayıf formda negatif olduğu saptanmıştır. Petrol fiyatlarının ise BIST Turizm endeksi üzerindeki etkisinin zayıf formda pozitif yönde olduğu belirlenmiştir. Çalışmadan elde edilen sonuçlar turizm endeksini etkileyebilecek makroekonomik faktörleri ele alarak incelenmesi ve etkilerinin belirlenmesi açısından önemlidir.

Human perceptual and affective responses change dynamically when stimuli are experienced. In this study, we developed a method for modeling the causal structures of affective dynamics using time-series data. Using the temporal dominance of sensations method, perceptual and affective data were collected from individuals eating strawberries, and the resulting time-series data were mathematically represented using a vector auto-regression model. Multihierarchical and multidimensional causality structures that explain the temporal evolution of perceptual and affective responses were then established based on Granger causality and the information criterion. The established model suggests how affective and preferential responses are triggered following exposure to stimuli. We also assessed the quantitative and semantic validity of the model. [ABSTRACT FROM AUTHOR]

The paper used a cointegration test, the Granger causality test, and a vector autoregression (VAR) model to determine the relationship between the international coffee price on the spot market and the Vietnamese coffee export price from January 2004 to December 2017. The study found international coffee prices to have a significant effect on Vietnamese coffee export prices, but not vice versa. The two variables are not cointegrated with each other at the 99 percent confidence level, but the Granger causality test confirmed that the Vietnamese coffee export price is influenced by the international market price, while the international market price is not influenced by the Vietnamese coffee export price. The results from the VAR model also showed that the dependent variable is mainly impacted by two independent variables in lag 1 and other lags. Overall, the Vietnamese coffee export price did not have an effect on the international coffee spot market price. Therefore, the relationship between the international coffee price and the Vietnamese coffee export price is asymmetric. These results are in accordance with the actual situation since Vietnam is the largest exporter of robusta coffee in the world, but Vietnam is only a “small” country that has no market power in the international coffee market.

Purpose – The purpose of this paper is to evaluate the influence of VND/USD exchange rate on Vietnamese coffee export price (PVN). Design/methodology/approach – The study uses cointegration test, Granger causality test and vector autoregression (VAR) model. Findings – The results reveal that there is no co-integrating equation between two variables. It means the exchange rate does not have an effect on PVN in the long run. Furthermore, there is one Granger causality relationship between VND/USD exchange rate and PVN in the short run, but not vice versa. The study suggests that the first previous period of PVN is the most closely related variable which has the greatest impact on the variation of PVN among the selected variables, meanwhile the effect of VND/USD exchange rate on it, contrarily, is positive and very trivial. Originality/value – In overall, the impact of VND/USD exchange rate on Vietnamese coffee export price (PVN) has been analyzed deeply in this research by applying new approaches.

Time series modeling analysis is one of the methods to forecast based on past data and conditions. The analytical tool that is commonly used to forecast multivariate time series data is the Vector Autoregressive (VAR) model. However, when the variables have cointegration and stationary at the first difference value, then the VAR model is modified into the Vector Error Correction Model (VECM). In VECM, all variables can be used as endogenous variables. If exogenous variables are involved in the VECM model, then the model is called as Vector Error Correction Model with Exogenous variables (VECMX). In the present study, a time series modeling analysis was used to analyze the price of gasoline, the money supply in a broad sense (M2), oil and gas exports, and consumption imports over the years from 2012 to 2020. By using information on the criteria of Akaike Information Criterion Corrected, Hannan–Quinn Criterion, Akaike Information Criterion, and Schwarz Bayesian Criterion, the best VAR(p) model is obtained with order 3, or lag 3. Based on the VAR(3) model, the cointegration test is conducted, and the result shows that there is a long-term relationship among variables, namely, there is a cointegration relationship between variables with rank = 1. Based on the cointegration rank = 1 and the smallest value of the information criteria and comparison of some candidate best models, namely, VECMX(2,1), VECMX(2,2), VECMX(3,1), VECMX(3,2), and VECMX(4,1), we found that the best model is VECMX(3,1) with lag 3 for endogenous variables and lag 1 for exogenous variables. Based on this best model, further analysis of Granger causality, Impulse Response Function (IRF), and forecasting is discussed.

This study examines causality shifts in the revenue–expenditure nexus in Brazil during the years 1996–2019. The literature usually assumed a time-invariant causality link between government revenues and expenditures. Such assumption becomes often implausible when the sample period covers significant economic, political and policy changes, like the case of Brazil in the last two decades. Based on time-varying Granger causality tests, we found three distinct causality episodes: fiscal synchronization in 2005–2008, spend-and-tax in 2010–2013, and a tax-and-spend in 2015–2018. These episodes are intercalated with periods of no causality that coincides with economic crisis, political turmoil and major shifts in fiscal policy. The findings suggest that the interplay between fiscal policy orientation and primary surplus targeting is an important factor in the revenue–expenditure nexus. The most recent causality episode suggests stronger effects running from revenues to expenditures in the Brazilian primary budget dynamics. In this context, according to the tax-and-spend hypothesis, cutting spending seems to be the right course of action to restore fiscal balance in Brazil. A tax increase should be considered with caution because it may only incentive the government to grow its expenditures. [ABSTRACT FROM AUTHOR]

Downloads and citations of papers are regarded as significant metrics of the academic level of researchers and the influence of journals. Besides, exploring the association between them helps grease the wheels of the academic evaluation system. In this paper, we select 7552 articles published in The Lancet from January 2007 to October 2017 as the research sample and conduct Granger causal inference to investigate the relationship and directionality between downloads and citations. Furthermore, based on the download-citation patterns of articles, this study stratifies articles to explore the directionality between the downloads and citations of articles with different patterns. The results show that 75.86% of the articles have Granger causality between download and citation counts, suggesting that there is a significant causal relationship between downloads and citations. Specifically, the proportion of articles with bilateral Granger causality between download counts and citation counts is the highest, accounting for 35.51%; the proportion of articles whose download counts affect citation counts unilaterally accounts for 14.3%; and the proportion of articles whose citation counts affect download counts unilaterally accounts for 26.05%; 24.14% of the articles have no Granger causality between downloads and citations. Further, most Lancet articles are downloaded more at the early stage after publication, while the citations mainly appear after a period of time, making the slope trend of downloads and citations inconsistent throughout the citation life cycle. Meanwhile, the Granger causal relationship between downloads and citations is related to the slope of their curves. That is, the metric with a lower slope tends to be influenced by the metric with a higher slope. [ABSTRACT FROM AUTHOR]

The Western Balkans (WB) countries registered an increase in the current account (CA) deficit and net capital inflow in the period before the outbreak of the global financial crisis of 2008. The external debt of these countries has increased. The aim of this paper is to examine the causality relationship between the CA and financial accounts (FA) balance of Serbia. A framework for the empirical analysis is the vector autoregression (VAR) model and the vector error correction (VEC) model. Using the Johansen cointegration test, we find the existence of a long-run causality relationship between these two variables. The estimated long-run coefficient on the FA variable as an independent variable shows that an increase of Serbia's FA balance by 1% leads to an increase in the CA deficit of Serbia by 0.58%. Applying the Granger causality test, it was found that causality runs from FA to the CA, which implies recommendations for economic policymakers. The finding indicates the need to continuously check the sustainability of the CA deficit of Serbia, as well as to monitor the level of presence of foreign capital in the Serbian economy.

The effective rate of exchange is one of the most important factors in international competitiveness. The more it increases, the better the competitiveness of exports is. So, keeping or raising the real effective exchange rate has a positive effect on the country's trade balance, but reducing it will have a negative effect. The aim of this study is to investigate the effect of exchange rate on the non-oil exports of Iran with the time series analysis approach. The data on the variables were extracted from databases for the period of 1991-2012, and the Dickey-Fuller test was used to evaluate the reliability of the variables. Also, the Granger causality test and the VAR model were used to test the hypothesis. The results showed that the variable of exchange rates had significant adverse effects on non-oil exports during the studied period; with an increase in the exchange rate in that period, non-oil exports declined. It was also shown that the impacts of GDP, the degree of economic openness and non-oil export facilities granted to the private sector were positive.

This study re-examined the effect of official development assistance (ODA) of five major donor countries (France, Germany, Japan, the United Kingdom, and the United States) on foreign direct investment (FDI) using panel data from 2003 to 2020. In addition to the system Generalized Method of Moments (GMM) with the gravity model, the Granger causality test and impulse response analysis with the panel VAR model was conducted. It was concluded that ODA did not necessarily have an effect on FDI since the 2000s. It is also suggested that the vanguard effect of Japanese ODA, as indicated by some previous studies, appeared mainly in the 1990s and may not be sustainable. The novelty of this study is to verify the effects of the ODA of major donors on FDI using new data from the 2000s onward, especially to reveal that the vanguard effect of Japanese ODA has not been observed since the 2000s. A limitation of this study is to determine only the presence or absence of a general trend at a statistically significant level. Therefore, further research on individual cases is expected to find how ODA has affected the investment decisions of individual companies.

In February 2020, Japan began experiencing outbreaks of COVID-19 infection and deaths due to the disease. Open data on the number of positive PCR test results are available from the Ministry of Health, Labour and Welfare (MHLW). We applied the SARIMA models to these time series data and selected an ARIMA(1,1,2) model as the best model among this class of models for the number of infection deaths during the main period, which includes the period covered by the declaration of emergency. We applied bivariate VAR models to the data of the number of PCR-positive persons and the number of infection deaths and selected a VAR(15) model as the best model for the main period. With regards to Granger's causality of the number of PCR-positive persons relative to the number of infected persons and deaths, we obtain clear causality in the data only up until June 17, with causality not so clear after June 18, when MHLW changed the definition of fatalities. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Financial Researches & Studies / Finansal Araştirmalar ve Çalişmalar Dergisi is the property of Marmara University, School of Banking & Insurance 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.)

Copyright of Bankarstvo Magazine is the property of Association of Serbian Banks 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.)

Copyright of Istanbul Commerce University Journal of Social Sciences / İstanbul Ticaret Üniversitesi Sosyal Bilimler Dergisi is the property of Istanbul Commerce University Journal 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.)

Politicians are always seeking popularity, and they use several tools to try to influence their approval rate. We investigate the dynamic relationship between French executive politicians' approval rates and three types of legislative acts (laws, ordonnances, and decrees) that they can use to signal their policy stance. Given the persistent debate over causality between public opinion and policy, our results show that a strong President (in terms of popularity) can rely more on ordonnances without damaging his/her popularity. Moreover, the use of ordonnances also benefits the Prime Minister's popularity. Decrees are more beneficial to the Prime Minister than to the President. In terms of the agenda, if there is a honeymoon effect, legislative activism does nothing to prevent the fall in popularity at the end of a mandate. A winning strategy is thus to 'wait and see.' The results are robust to the inclusion of economic performance indicators, political and institutional factors. [ABSTRACT FROM AUTHOR]

The paper contributes to the existing literature through analysis of relationship between labour productivity and government spending on research and development in the eurozone countries as a whole. In particular, small and medium enterprises should aim to increase the labour productivity and use the possibilities of funding from the structural funds. The purpose of this paper is to empirically investigate the relationship between labour productivity and government spending on research and development in the eurozone. In particular, its purpose is to investigate this relationship in the case of small and medium enterprises. By utilizing causality tests and error correction models, the results suggest that support of research and development is the cause of labour productivity growth in the long-term period. However, for the short-term period changes in labour productivity precede changes in government spending on research and development. Based on the findings, the study has several theoretical and practical implications. The data sources were the Eurostat database. The data used have the character of annual time series in the period between 2004 and 2016. GRETL software was used for the calculations. [ABSTRACT FROM AUTHOR]

This study examines the dynamic interaction between three macroeconomic imbalances (current account, output gap, and exchange rate misalignment) affecting Egypt. The interaction between these imbalances is critical given their interdependence. Vector Auto Regression (VAR) analysis is employed over the period 1990 to 2015 and interpreted through impulse response functions and variance decomposition. The Granger causality test is also applied. The main findings are that positive shocks in real exchange rate misalignment result in a deficit in the current account and there is a causal relationship running from real exchange rate misalignment and the output gap to the current account. Policy recommendations emphasize the vital need to increase productivity and domestic industrial output to reduce the output gap and improve the situation of the current account. Accordingly, this will help, in the context of the current liberalised Egyptian exchange rate, to deliver more positive effects for the Egyptian economy. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the factors that affect multi-segments automobile sales in Greece. Various relevant quantitative techniques have been employed, such as stationarity, causality and cointegration. A Vector Autoregressive (VAR) model was also developed and long-term impacts of the different variables of interest on car sales have been estimated through generalized impulse response functions (GIRF). The impact of the current financial crisis on the Greek automobile market was also taken into account. The results show that fuel prices Granger cause total car sales. The results also indicate the absence of long run cointegrating relationships among the variables. The full blown model shows that demand for new automobiles depends on the existing social, financial and political conditions of the local economy and that the various shocks observed have a temporary medium-run character on car sales, whereas the system is found to be stable. [ABSTRACT FROM AUTHOR]

This study examines the effect of oil price on the volatility of food price in Nigeria. It specifically considers the long-run, short-run, and causal relationship between these variables. Annual data on oil price and individual prices of maize, rice, sorghum, soya beans, and wheat spanning from 2000 to 2013 were used. The price volatility for each crop was obtained using Generalized Autoregressive Conditional Heteroskedascity (GARCH (1, 1)) model. Our measure of oil price is the Refiner acquisition cost of imported crude oil. The Augmented Dickey–Fuller and Phillip–Perron unit root tests show that all the variables are integrated of order one, I (1). Therefore, we use the Johansen co-integration test to examine the long-run relationship. Our results show that there is no long-run relationship between oil price and any of the individual food price volatility. Thus, we implement a VAR instead of a VECM to investigate the short-run relationship. The VAR model result revealed a positive and significant short-run relationship between oil price and each of the selected food price volatility with exception of that of rice and wheat price volatility. These results were further confirmed by the impulse response functions. The Granger causality test result indicates a unidirectional causality from oil price to maize, soya bean, and sorghum price volatilities but does not show such relationship for rice and wheat price volatilities. We draw some policy implications of these findings.

With the frequent fluctuations of international crude oil prices and China's increasing dependence on foreign oil in recent years, the volatility of international oil prices has significantly influenced China domestic refined oil price. This paper aims to investigate the transmission and feedback mechanism between international crude oil prices and China's refined oil prices for the time span from January 2011 to November 2015 by using the Granger causality test, vector autoregression model, impulse response function and variance decomposition methods. It is demonstrated that variation of international crude oil prices can cause China domestic refined oil price to change with a weak feedback effect. Moreover, international crude oil prices and China domestic refined oil prices are affected by their lag terms in positive and negative directions in different degrees. Besides, an international crude oil price shock has a significant positive impact on domestic refined oil prices while the impulse response of the international crude oil price variable to the domestic refined oil price shock is negatively insignificant. Furthermore, international crude oil prices and domestic refined oil prices have strong historical inheritance. According to the variance decomposition analysis, the international crude oil price is significantly affected by its own disturbance influence, and a domestic refined oil price shock has a slight impact on international crude oil price changes. The domestic refined oil price variance is mainly caused by international crude oil price disturbance, while the domestic refined oil price is slightly affected by its own disturbance. Generally, domestic refined oil prices do not immediately respond to an international crude oil price change, that is, there is a time lag. [ABSTRACT FROM AUTHOR]

Background Discovering effective connectivity between brain regions gained a lot of attention recently. A vector autoregressive model is a simple and flexible approach for exploratory structural modeling where the involvement of a large number of brain regions is crucial to avoid confounding. The non-zero coefficients of the VAR model are interpreted as actual effective connectivity between brain regions. Thus methods for a higher correct discovery rate are crucial for neuroscience. New method We propose an improved version of the FDR analysis procedure which would be more suitable to fMRI data. The estimates of the VAR coefficients are often not symmetric about 0 with non-zero modes. In this case, we suggest to estimate the null distribution of the estimates which is assumed symmetric about 0 in two steps: use one side of the estimates and then both sides under some condition. Results A theoretical argument is provided for the proposed procedure with a theorem and two types of experiments are made. In a simulation experiment, we show via ROC curves improvement over previous methods. We apply the proposed method to analyze real fMRI data with results interpreted in the language of cognitive neuroscience. Comparison with existing method(s) The proposed method outperforms the standard method in the simulation experiment with a VAR model of dimension up to 100 over a wide range of sample sizes. The improvement is made in the context of the true positive rate and performance consistency. Conclusions The proposed method is more appropriate for analyzing fMRI data with VAR models when the estimates of the VAR coefficients are not symmetric about 0 and have non-zero modes. [ABSTRACT FROM AUTHOR]

Copyright of Informe Gepec is the property of Informe Gepec 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.)

Multivariate time series describing relative contributions to a total (like proportional data) are called compositional time series. They need to be transformed first to the usual Euclidean geometry before a time series model is fitted. It is shown how an appropriate transformation can be chosen, resulting in coordinates with respect to the Aitchison geometry of compositional data. Using vector autoregressive models, the standard approach based on raw data is compared with the compositional approach based on transformed data. The results from the compositional approach are consistent with the relative nature of the observations, while the analysis of the raw data leads to several inconsistencies and artifacts. The compositional approach is extended to the case when also the total of the compositional parts is of interest. Moreover, a concise methodology for an interpretation of the coordinates in the transformed space together with the corresponding statistical inference (like hypotheses testing) is provided. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Czech commodity market with wheat underwent significant changes since the beginning of the market economy. In 2004, opening of the EU market brought new business opportunities for Czech plant producers. As a result, nearly third of the country's wheat production is currently realized in foreign markets. This paper focuses on exploration of Granger causality relationships among average wheat price of human consumption quality; animal feed quality and the average price of wheat in the world market (source: World Bank). Monthly time series from July 1993 to August 2013 (T=242) were subjected to stationarity and cointegration tests. Due to nonexistence of equilibrium relationships, the multivariate data were analyzed by Vector Autoregressive (VAR) model in first differences. Separate VAR models were fitted in periods before EU entry and after to verify assumptions of differential short-term dynamic relationships between the prices, as a result of country's accession to EU. Further, orthogonal impulse-response function was prepared to quantify impact of innovation shocks in the source series upon the target series. Differences in relationships were found due to exposure of the Czech market to fluctuations in the world wheat price. [ABSTRACT FROM AUTHOR]

The relationship between the foreign direct investments received by a country and its system of higher education is not yet completely clarified. Also, due to the fact that aspects related to the system of higher education are not directly linked with the economical performance of a country, the linkages between variables from this domain and the level of foreign direct investments received by a country has not been a major topic in the scientific literature, neither at global nor national level. In this study we propose a quantitative approach destined to describe and quantify the connection between inflows of FDI and the number of students enrolled in the tertiary education level for the case of Romania. Based on yearly data for the period 1990 - 2012 the study uses a VAR approach in order to study the bidirectional linkage between the two variables. The study provides some evidence that the level of the FDI attracted in Romania can be regarded as having a short term influence on the number of students enrolled in tertiary education and also the fact that the reverse is not true. [ABSTRACT FROM AUTHOR]

The main goal of this research is to improve the degree of accuracy for inflation rate forecasts in Romania. The inflation was forecasted using a vectorialautoregressive model. According to Granger test for causality, the relationship between the two variables is reciprocal. The inflation rate volatility is due mainly to the evolution of this indicator, the influence decreasing insignificantly in time, not descending under 96%. More than 87% of the variation in unemployment rate is explained by the own volatility for all lags. For the first lag the inflation is explained only by its evolution, the contribution of the unemployment rate to inflation variation being null. The inflation rate dynamic simulations (deterministic and stochastic) on the horizon 2011-2013 were more accurate than the predictions based on Dobrescu model. The combined forecasts proved to be a good strategy of improving the VAR forecasts and those based on Dobrescu model only if the dynamic and deterministic simulations were combined with Dobrescu's anticipations on the horizon 2011-2013. [ABSTRACT FROM AUTHOR]

This article aims to examine the causal and dynamic relationship between trading activity and stock returns, using detailed intraday data from Euronext Paris. We distinguish between two measures of trading activity: the raw volume metric (the nondirectional volume) and the directional volume. In line with the existing literature, we find a unidirectional causality running from stock returns to nondirectional volume. Furthermore, we highlight a strong bidirectional relation between stock returns and directional volume. This result is interesting and has several implications. First, it provides evidence that the directional volume is more informative than the nondirectional volume. Second, it shows that the directional volume helps predict stock returns. Third, it provides an empirical test for the Mixture Distribution Hypothesis (MDH) and the sequential arrival hypothesis, which posit that the information content of the trading activity affects future returns. [ABSTRACT FROM PUBLISHER]

Oil price shocks affect the macroeconomy through the supply side (higher production costs) and the demand side (income effects, uncertainties). Negative supply shocks could lower economic growth and increase inflation. This study investigates the effects of oil price changes on Turkey's macroeconomic variables such as growth and inflation. To this end, vector autoregressive model (VAR) is employed using monthly data for the period of 1987:1- 2010:9. According to the results of Granger causality analysis that is based on the VAR model; it is observed that there is one way causality running from oil prices to economic growth and no causality between oil prices and inflation. Impulse responses fonctions showed that a positive oil price shock increase both the growth of GDP and inflation [ABSTRACT FROM AUTHOR]

This paper examines the causal relationship between democracy and economic growth in Portugal over the period 1960-2001 within a VAR model with four variables: output, physical and human capital, and an index of democracy. We apply Granger causality tests and impulse-response functions to analyze causality and check how unexpected changes influence growth. Our main findings point to a bi-directional causality between democracy and growth. The impulse-response analysis suggests that in the short run democracy has a negative effect on growth in Portugal, but in the long run this effect is positive. Furthermore, we find that democracy also causes economic growth by increasing educational attainment. [ABSTRACT FROM AUTHOR]

This paper is an empirical assessment of various aspects regarding interconnections among the largest world stock markets. The study investigates the dynamic connection structure of ten major stock markets using partial directed coherence (PDC) and graphical models. Recently, PDC has been introduced for a frequency domain analysis of linear Granger-causality based on modeling the underlying dynamics by vector autoregressive processes. It constitutes a powerful tool to explore the causal influence between complex multivariate processes in neuroscience area. The paper proposes using this tool to study the information flow and causal influence between international financial markets. The novel proposed approach offers many advantages and superiorities compared to the conventional methodologies for investigating financial links across stock markets. Applying PDC to ten opening and closing major stock index data allows the discrimination between directed and induced causality connections between financial markets. The graphical model summarizing the PDC results and instantaneous causality analysis shows the US, UK, Germany and Hong Kong have a consistently strong causality impact on price movements in major financial markets. The strong connection between the ten major financial markets supported by the empirical results tends to reduce the gain of international diversification and intensifies the risk of the international financial system instability. [ABSTRACT FROM AUTHOR]