With the development of large and long panel databases, the theory surrounding
panel causality evolves quickly, and empirical researchers might find it
difficult to run the most recent techniques ...developed in the literature. In this
article, we present the community-contributed command
xtgcause, which implements a procedure proposed by
Dumitrescu and Hurlin (2012, Economic Modelling 29: 1450–1460)
for detecting Granger causality in panel datasets. Thus, it constitutes an
effort to help practitioners understand and apply the test.
xtgcause offers the possibility of selecting the
number of lags to include in the model by minimizing the Akaike information
criterion, Bayesian information criterion, or Hannan–Quinn information
criterion, and it offers the possibility to implement a bootstrap procedure to
compute p-values and critical values.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, OILJ, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
This study employs Fully Modified Ordinary Least Squares, Common Correlated Effects and Dumitrescu-Hurlin panel causality techniques to investigate the environmental impacts of nuclear energy ...generation in European Union countries from 1990 to 2022. The ongoing debate within the European Union and the empirical contradictions in the literature, coupled with the overall singular-dimensionality surrounding the impacts of nuclear energy on the environment, necessitate a broader and comprehensive examination of its effects across various environmental dimensions. These dimensions include the presence of CO2 emissions and the ecological footprint generated. The findings reveal that nuclear energy adoption by countries tends to affect CO2 emissions but this relationship goes from CO2 to nuclear energy consumption as per the causality test, while the ecological footprint variable does not exhibit a causal relationship with nuclear energy consumption. We estimated that a higher presence of air pollutants promotes the generation of nuclear energy as an alternative to fossil fuel energy sources. The study highlights that while nuclear energy generation produces no air pollution, it does impose significant land use requirements, potentially leading to ecosystem degradation. Factors such as uranium extraction, nuclear waste management, disposal, and accidents contribute to this impact. Further research is needed to understand the specific mechanisms and factors contributing to the observed environmental degradation associated with nuclear energy generation.
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•It is performed a comparative analysis of nuclear energy generation impacts on environment.•European Union members were examined between the period 1990 and 2022.•Fully Modified OLS, Common Correlated Effects and Dumitrescu-Hurling Panel causality estimation were performed.•A negative impact of nuclear energy generation is estimated on ecological footprint, while CO2 emissions decrease.•A higher presence of air pollutants promotes the generation of nuclear energy as an alternative to fossil fuel energy.
This study discusses the various hypotheses associated with the causal relationship between electricity consumption and economic growth along with a survey of the empirical literature. The survey ...focuses on country coverage, variables selected and model specification, econometric approaches, various methodological issues, and empirical results. The results for the specific countries surveyed show that 31.15% supported the neutrality hypothesis; 27.87% the conservation hypothesis; 22.95% the growth hypothesis; and 18.03% the feedback hypothesis.
This paper examines the long run and causal relationship issues between economic growth, carbon emissions, energy consumption and employment ratio in Turkey by using autoregressive distributed lag ...bounds testing approach of cointegration. Empirical results for Turkey over the period 1968-2005 suggest an evidence of a long-run relationship between the variables at 5% significance level in Turkey. The estimated income elasticity of carbon emissions per capita is -0.606 and the income elasticity of energy consumption per capita is 1.375. Results for the existence and direction of Granger causality show that neither carbon emissions per capita nor energy consumption per capita cause real GDP per capita, but employment ratio causes real GDP per capita in the short run. In addition, EKC hypothesis at causal framework by using a linear logarithmic model is not valid in Turkish case. The overall results indicates that energy conservation policies, such as rationing energy consumption and controlling carbon dioxide emissions, are likely to have no adverse effect on the real output growth of Turkey.
•The paper presents a new data-driven time series method for diagnosing the sources of plant-wide oscillations.•The proposed method combines the Granger causality, spectral Granger causality, and ...principal component feature selection.•Simulation and industrial case studies demonstrate that the effectiveness of the proposed method.
Oscillations are common in closed-loop controlled processes which, once generated, can propagate along process flows and feedback paths of the whole plant. It is important to detect and diagnose such oscillations to maintain high control performance. This paper presents a new data-driven time series method for diagnosing the sources and propagation paths of plant-wide oscillations. The proposed method first uses a latent variable method to select features which carry significant common oscillations, then applies both time-domain Granger causality and spectral Granger causality to provide reliable diagnosis of oscillation sources and propagations. Simulation tests and an industrial case study are shown to demonstrate the effectiveness of the proposed method.
China has proposed the Belt and Road Initiative to promote the cooperation of energy production and trade between the relevant countries. This paper investigates the relationship between the energy ...consumption and economic growth of the countries along the Belt and Road using a panel of data for 69 countries during the period between 1970 and 2013. Both of the renewable and traditional fossil energy consumptions are investigated in this study. By employing vector error correction model (VECM), fully modified OLS (FMOLS) and dynamic OLS (DOLS) approaches, the estimation results indicate that the nexuses of the energy consumption and economic developments vary across different subgroups. For the entire group, there is evidence of long−run bidirectional causalities among carbon emissions, energy use, industry value added and GDP per capita. For the energy−importing countries along the Belt and Road, there exists unidirectional short−run causality running from GDP to renewable energy and long−run causality in the reverse direction. In contrast, for the energy−exporting countries, there is a bidirectional causality between the energy use and GDP per capita in the long run. These findings suggest significant cooperation potential in the economies and trades of China and the Belt and Road countries.
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•The nexus of CO2 emissions and GDP is reinvestigated using a specific dataset.•The countries/regions along China's “the Belt and Road” initiative are examined.•The vector correction model, fully modified OLS and dynamic OLS approaches are employed.•Long−run bidirectional causalities between CO2 emissions, energy use and GDP exit.•Renewable energy contributes to long−run growth in the energy−importing countries.
•The bilateral contagion effects across oil and gold are verified by time-varying Granger causality tests.•We find contagion effects of bubbles from oil to gold markets during the 2014/2015 crash and ...the COVID-19 outbreak.•We find contagion effects of bubbles from gold to oil markets during 2019’s collapsing U.S. dollar (October 9, 2019, to March 13, 2020) and during the COVID-19 outbreak period (March 19 to 27, 2020, and from April 9 to 17, 2020).
This paper examines the causal relationship between crude oil and gold spot prices to assess how the economic impact of COVID-19 has affected them. We analyze West Texas Light crude oil (WTI) and gold prices from January 4, 2010, to May 4, 2020. We detect common periods of mild explosivity in WTI and gold markets. More importantly, we find a bilateral contagion effect of bubbles in oil and gold markets during the recent COVID-19 outbreak.
Increasing trends in summer-time temperature maxima (Tmax) over India, show consequent increases in the intensity and frequency of heatwave events in recent years. Heat waves have been largely ...attributed to large-scale meteorological blocking, characterized by subsidence, clear skies and low soil moisture, in observational studies, or greenhouse gas enhancements in model studies. While radiative effects of absorbing aerosols are acknowledged, the association of absorbing aerosols with temperature maxima has not been investigated comprehensively. In the current study, statistical tools (such as correlation and Granger causality) were applied to long term (1979–2013) satellite and ground based observations to evaluate influence of absorbing aerosols on Tmax in north-west India (Tmax-NW). Regional absorbing aerosol index (AAI) in the north-west (AAI-NW) and central-India (AAI-CI) showed co-variability with Tmax-NW, implying connections to both local and non-local absorbing aerosols. The effects persisted on seasonal and heatwave event scales, becoming stronger on heatwave days with presence of enhanced AAI loadings. Causal effects of AAI-NW and AAI-CI were identified on Tmax-NW with a lag of 1–11 days, across multiple years, thereby establishing the influence of absorbing aerosols on heatwave events. The absence of confounding effects of surface pressure on these links suggests that, even during heat wave events linked to atmospheric blocking, absorbing aerosols can further enhance temperature maxima and related heatwave intensity.
•Temperature maxima in northwest India correlate with absorbing aerosol abundance.•Absorbing aerosols enhance local and non-local temperature maxima.•The effect, lasting 1–11 days, exacerbates Tmax-2m during heatwave conditions.
Oscillatory neuronal activity may provide a mechanism for dynamic network coordination. Rhythmic neuronal interactions can be quantified using multiple metrics, each with their own advantages and ...disadvantages. This tutorial will review and summarize current analysis methods used in the field of invasive and non-invasive electrophysiology to study the dynamic connections between neuronal populations. First, we review metrics for functional connectivity, including coherence, phase synchronization, phase-slope index, and Granger causality, with the specific aim to provide an intuition for how these metrics work, as well as their quantitative definition. Next, we highlight a number of interpretational caveats and common pitfalls that can arise when performing functional connectivity analysis, including the common reference problem, the signal to noise ratio problem, the volume conduction problem, the common input problem, and the sample size bias problem. These pitfalls will be illustrated by presenting a set of MATLAB-scripts, which can be executed by the reader to simulate each of these potential problems. We discuss how these issues can be addressed using current methods.
Municipal solid waste (MSW) is one of the most urgent issues associated with economic growth and urban population. When untreated, it generates harmful and toxic substances spreading out into the ...soils. When treated, they produce an important amount of Greenhouse Gas (GHG) emissions directly contributing to global warming. With its promising path to sustainability, the Danish case is of high interest since estimated results are thought to bring useful information for policy purposes. Here, we exploit the most recent and available data period (1994–2017) and investigate the causal relationship between MSW generation per capita, income level, urbanization, and GHG emissions from the waste sector in Denmark. We use an experiment based on Artificial Neural Networks and the Breitung-Candelon Spectral Granger-causality test to understand how the variables, object of the study, manage to interact within a complex ecosystem such as the environment and waste. Through numerous tests in Machine Learning, we arrive at results that imply how economic growth, identifiable by changes in per capita GDP, affects the acceleration and the velocity of the neural signal with waste emissions. We observe a periodical shift from the traditional linear economy to a circular economy that has important policy implications.
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•In-depth assessment of Municipal Solid Waste Sustainability is presented.•We assess the effect of wealth and urban sprawl on sustainable waste management.•We observe that urbanization is the backbone of GHG emissions from waste.•We find a gradual shift from linear economy to circular economy.•Other countries can learn from Denmark's path towards sustainable waste management.
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