Cheers to anxiety: Granger causality insights on alcohol consumption patterns across 13 South American countries.

BACKGROUND: The relationship between alcohol consumption and mental health is complex; drinking may exacerbate anxiety, and in turn, anxiety can lead to excessive drinking. This study explores the relationship between alcohol consumption patterns including wine, beer, and spirits, and anxiety prevalence in selected 13 South American nations. METHODS: This study utilises secondary data spanning 29 years from 1991 to 2019 obtained from the Our World in Data database. It investigates the causal link between the prevalence of anxiety and alcohol consumption in the selected countries using the Granger causality test. RESULTS: Anxiety was found to have a unidirectional effect on wine and beer consumption in Chile, Suriname, Uruguay, and Trinidad and Tobago. Additionally, drinking alcohol consumption appears to impact anxiety levels in Brazil. Argentina demonstrates a bidirectional relationship between anxiety and all three types of alcohol consumption, with similar patterns observed in Brazil (wine and beer), Chile (spirits), and Paraguay (spirits). CONCLUSION: No significant causal relationships for alcohol consumption patterns were found in other nations. The identified Granger causal links follow four distinct directions in this study. These findings provide valuable insights for policymakers, governments, and international investors for informed decision-making regarding regulation and policy tools.

Impact of the Global Fear Index (COVID-19 Panic) on the S&P Global Indices Associated with Natural Resources, Agribusiness, Energy, Metals, and Mining: Granger Causality and Shannon and Rényi Transfer Entropy.

The Global Fear Index (GFI) is a measure of fear/panic based on the number of people infected and deaths due to COVID-19. This paper aims to examine the interconnection or interdependencies between the GFI and a set of global indexes related to the financial and economic activities associated with natural resources, raw materials, agribusiness, energy, metals, and mining, such as: the S&P Global Resource Index, the S&P Global Agribusiness Equity Index, the S&P Global Metals and Mining Index, and the S&P Global 1200 Energy Index. To this end, we first apply several common tests: Wald exponential, Wald mean, Nyblom, and Quandt Likelihood Ratio. Subsequently, we apply Granger causality using a DCC-GARCH model. Data for the global indices are daily from 3 February 2020 to 29 October 2021. The empirical results obtained show that the volatility of the GFI Granger causes the volatility of the other global indices, except for the Global Resource Index. Moreover, by considering heteroskedasticity and idiosyncratic shocks, we show that the GFI can be used to predict the co-movement of the time series of all the global indices. Additionally, we quantify the causal interdependencies between the GFI and each of the S&P global indices using Shannon and Rényi transfer entropy flow, which is comparable to Granger causality, to confirm directionality more robustly The main conclusion of this research is that financial and economic activity related to natural resources, raw materials, agribusiness, energy, metals, and mining were affected by the fear/panic caused by COVID-19 cases and deaths.

Partial Directed Coherence and the Vector Autoregressive Modelling Myth and a Caveat.

Here we dispel the lingering myth that Partial Directed Coherence is a Vector Autoregressive (VAR) Modelling dependent concept. In fact, our examples show that it is spectral factorization that lies at its heart, for which VAR modelling is a mere, albeit very efficient and convenient, device. This applies to Granger Causality estimation procedures in general and also includes instantaneous Granger effects. Care, however, must be exercised for connectivity between multivariate data generated through nonminimum phase mechanisms as it may possibly be incorrectly captured.

Frequency Domain Repercussions of Instantaneous Granger Causality.

Using directed transfer function (DTF) and partial directed coherence (PDC) in the information version, this paper extends the theoretical framework to incorporate the instantaneous Granger causality (iGC) frequency domain description into a single unified perspective. We show that standard vector autoregressive models allow portraying iGC's repercussions associated with Granger connectivity, where interactions mediated without delay between time series can be easily detected.

Partial directed coherence: twenty years on some history and an appraisal.

Here while we reminisce about how partial directed coherence was proposed, its motivation and evolution, we take the opportunity to relate it to some of its kin quantities and some of its offspring. Emphasis is placed on our development of asymptotic criteria to place it as a reliable investigation tool, where the connectivity detection problem is completely solved as opposed to what we call the characterization problem. We end by musing over some points now on our wishlist.

Causal relationship of CA3 back-projection to the dentate gyrus and its role in CA1 fast ripple generation.

BACKGROUND: Pathophysiological evidence from temporal lobe epilepsy models highlights the hippocampus as the most affected structure due to its high degree of neuroplasticity and control of the dynamics of limbic structures, which are necessary to encode information, conferring to it an intrinsic epileptogenicity. A loss in this control results in observable oscillatory perturbations called fast ripples, in epileptic rats those events are found in CA1, CA3, and the dentate gyrus (DG), which are the principal regions of the trisynaptic circuit of the hippocampus. The present work used Granger causality to address which relationships among these three regions of the trisynaptic circuit are needed to cause fast ripples in CA1 in an in vivo model. For these purposes, male Wistar rats (210-300 g) were injected with a single dose of pilocarpine hydrochloride (2.4 mg/2 µl) into the right lateral ventricle and video-monitored 24 h/day to detect spontaneous and recurrent seizures. Once detected, rats were implanted with microelectrodes in these regions (fixed-recording tungsten wire electrodes, 60-µm outer diameter) ipsilateral to the pilocarpine injection. A total of 336 fast ripples were recorded and probabilistically characterized, from those fast ripples we made a subset of all the fast ripple events associated with sharp-waves in CA1 region (n = 40) to analyze them with Granger Causality. RESULTS: Our results support existing evidence in vitro in which fast ripple events in CA1 are initiated by CA3 multiunit activity and describe a general synchronization in the theta band across the three regions analyzed DG, CA3, and CA1, just before the fast ripple event in CA1 have begun. CONCLUSION: This in vivo study highlights the causal participation of the CA3 back-projection to the DG, a connection commonly overlooked in the trisynaptic circuit, as a facilitator of a closed-loop among these regions that prolongs the excitatory activity of CA3. We speculate that the loss of inhibitory drive of DG and the mechanisms of ripple-related memory consolidation in which also the CA3 back-projection to DG has a fundamental role might be underlying processes of the fast ripples generation in CA1.

Bidirectional intrinsic modulation of EEG band power time series and spectral components of heart rate variability.

Some hypotheses relate oscillations of EEG band power with autonomic processes derived from homeostatic control modulated by structures like the Central Autonomic Network and the Autonomic Nervous System. This research project studies the causal relationships between fluctuations of an autonomic process marker like the Heart Rate Variability (HRV) and the proposed EEG band power time series (BPts). To verify the existence of directional causal relationships, using Granger Causality (GC) test between HRV and BPts. Analyses were performed using two databases, of 9 and 14 subjects respectively. Experiments consisted of spontaneous breathing and a controlled breathing task (CBT). GC was tested over Intrinsinc Mode Functions of HRV derived from Empirical Mode Decomposition and BPts computed over α, ß and γ bands. Positive GC tests were observed through each experimental task, channels, IMFs, EEG band, and direction. The largest number of positive GC relationships were found from BPts to HRV when testing, higher EEG band and IMF with lower spectral content. Opposite direction achieves lower total counts, but more related with IMFs of higher spectral content. Its presence also suggests that some homeostatic condition alters the BPts course given its increment under the CBT. It is important to notice that in both cases γ band achieves larger values for almost all of the studied conditions. Suggesting that such band has an important influence over HRV, but alterations on breathing condition also produce changes on BPts evolution, suggesting that the closed loop for homeostatic control alters neural dynamics at cortical level.

COVID-19, stock market and sectoral contagion in US: a time-frequency analysis.

We assess the conditional relationship in the time-frequency domain between the return on S&P 500 and confirmed cases and deaths by COVID-19 in Hubei, China, countries with record deaths and the world, for the period from January 29 to June 30, 2020. Methodologically, we follow Aguiar-Conraria et al. (2018), by using partial coherencies, phase-difference diagrams, and gains. We also perform a parametric test for Granger-causality in quantiles developed by Troster (2018). We find that short-term cycles of deaths in Italy in the first days of March, and soon afterwards, cycles of deaths in the world are able to lead out-of-phase US stock market. We find that low frequency cycles of the US market index in the first half of April are useful to anticipate in an anti-phasic way the cycles of deaths in the US. We also explore sectoral contagion, based on dissimilarities, Granger causality and partial coherencies between S&P sector indices. Our findings, such as the strategic role of the energy sector, which first reacted to the pandemic, or the evidence about predictability of the Telecom cycles, are useful to tell the history of the pass-through of this recent health crises across the sectors of the US economy.

Assessing Granger-Causality in the Southern Humboldt Current Ecosystem Using Cross-Spectral Methods.

The southern Humboldt Current ecosystem is an important topic among researchers working on the drivers of pelagic species' biological indicators. While sea surface temperature is believed to be a major driver in anchovies' (Engraulis ringens) reproductive and body condition indicators, this paper shows that regional drivers such as Pacific decadal oscillation anomalies also influence these biological processes. In addition, a warm condition could trigger increased gonad development of anchovies and synchronization of body condition dynamics with local environmental conditions stemming from sea turbulence and Ekman transport. To test the statistical significance of causality between two time series and determine the direction of causality, the frequency-domain Granger-causality method is considered. Therefore, this study provides additional predictive information, derived from past data on anchovy reproductive and feeding activities. The study could be useful for researchers working on relationships of environmental conditions and pelagic species to predict biological processes' maximum and minimum peak movements and anchovy abundance in the southern Humboldt Current ecosystem.

Revisiting the Relationship Between Suicide and Unemployment in Mexico: Evidence From Linear and Non-linear Co-integration.

This study attempts to investigate if suicide is interlinked with unemployment in Mexico by making use of a recently developed Bootstrap ARDL bound test over the years of 1981-2016. To avoid omitting variable bias, we use economic growth rate as a control variable. The empirical results indicate that no co-integration among these three variables and there is a positively bidirectional causality between suicide rate and the unemployment rate. This study will showcase that the economic growth rate negatively affects unemployment rate and unidirectional Granger causality running from economic growth rate to the unemployment rate in Mexico. The findings presented in this study could provide with valuable information for society and health policy makers to formulate the policies on suicide prevention in Mexico.

The impact of electric generation capacity by renewable and non-renewable energy in Brazilian economic growth.

Renewable sources are relevant in a country's energy planning because they are linked to the creation of opportunities for technological, economic, and productive development guided by the principles of sustainability. Thus, the aim of this study was to investigate the relation between electric generation capacity by renewable and non-renewable energies and Brazilian socioeconomic variables. The analysis of the interrelationships between electricity generation capacity and economic growth in Brazil, from April 2009 to March 2017, was carried out by the vector autoregressive and autoregressive distributed lag methodologies. It was verified that the variance of employment is explained by renewable sources: hydroelectric in 7.71%, biomass in 1.99%, wind energy in 3.13%, and solar energy in 10.58%. While, the GDP variance is explained in 3.15% by hydroelectric energy, 0.06% by biomass, 1.70% by wind energy, and 17.38% by solar energy. The export variance is explained by renewable sources: hydroelectric 2.48%, biomass 0.39%, wind energy 2.34%, and solar energy 17.58%. Finally, the variance of the minimum wage is explained by hydroelectric energy in 1.48%, biomass in 5.09%, wind energy in 9.09%, and solar energy in 10.67%. An ARDL (1, 1, 2, 0, 0, 0, 3, 2, 0, 2, 0, 2) model was also adjusted for natural gas, with AIC (13.082) and BIC (13.739), and the ARDL (1, 0, 1, 0, 0, 0, 0, 0, 3, 0, 0, 4) model adjusted for hydroelectric power, with AIC (13.633) and BIC (14.189), considering the variables' order cited above. Through the adjustment of the ARDL model, it was verified that there is a long-term influence of socioeconomic variables on electricity production variables, both renewable and non-renewable ones. The analysis of the impulse response function and the variance decomposition allowed us to verify that the installed capacity for production of electric energy exerts influence on Brazilian socioeconomic variables considered in this study.

Kernel Methods for Nonlinear Connectivity Detection.

In this paper, we show that the presence of nonlinear coupling between time series may be detected using kernel feature space F representations while dispensing with the need to go back to solve the pre-image problem to gauge model adequacy. This is done by showing that the kernelized auto/cross sequences in F can be computed from the model rather than from prediction residuals in the original data space X . Furthermore, this allows for reducing the connectivity inference problem to that of fitting a consistent linear model in F that works even in the case of nonlinear interactions in the X -space which ordinary linear models may fail to capture. We further illustrate the fact that the resulting F -space parameter asymptotics provide reliable means of space model diagnostics in this space, and provide straightforward Granger connectivity inference tools even for relatively short time series records as opposed to other kernel based methods available in the literature.

Nonlinear Granger Causality between Health Care Expenditure and Economic Growth in the OECD and Major Developing Countries.

Differing from previous studies ignoring the nonlinear features, this study employs both the linear and nonlinear Granger causality tests to examine the complex causal relationship between health care expenditure and economic growth among 15 Organisation for Economic Co-operation and Development (OECD) and 5 major developing countries. Some interesting findings can be obtained as follows: (1) For Australia, Austria, and UK, linear and nonlinear Granger causality does not exist between them. A unidirectional linear or nonlinear causality running from economic growth to health care expenditure can be found for Ireland, Korea, Portugal, and India. For these seven countries, health or fiscal policy related to health spending will not have an impact on economic growth; (2) For Belgium, Norway, and Mexico, only a unidirectional linear causality runs from health care expenditure to economic growth, while bidirectional linear causality can be found for Canada, Finland, Iceland, New Zealand, Spain, Brazil, and South Africa. Especially for the US, China, and Japan, a unidirectional nonlinear causality exists from health spending to economic growth. To improve the quality of national health, life quality and happiness, these 13 countries should actively look to optimise policy related to health care expenditure, such as by enhancing the efficiency of health costs to promote sustainable economic development.

The dependency analysis between energy consumption, sanitation, forest area, financial development, and greenhouse gas: a continent-wise comparison of lower middle-income countries.

This study explored the long-run association among greenhouse gases (GHGs), financial development, forest area, improved sanitation, renewable energy, urbanization, and trade in 24 lower middle-income countries from Asia, Europe, Africa, and America (South and North) by using panel data from 1990 to 2015. Granger causality was tested by Toda and Yamamoto approach. The bi-directional causality was established among urbanization and GHGs (Asia), financial development and forest (Asia), energy use and renewable energy (Asia), renewable energy and forest (Asia), improved sanitation and forest (Asia, Africa, America), urbanization and forest (Asia), and improved sanitation and financial development (Europe). The GHG emission also shows one-way causality is running from financial development to GHG (America), energy to GHG (Asia), renewable energy to GHG (America), forest area to GHG (America), trade openness to GHG (Africa), urbanization to GHG (Europe), GHG to financial development (Europe), GHG to energy use (Europe, Africa, and America), and GHG to trade openness (Asia). On the basis of fully modified ordinary least square and generalized method of moment, the reciprocal relationship of GHGs was observed due to financial development in Asia and Africa; renewable energy in all panels; forest area in Asia, Europe, and America; improved sanitation in Asia, Africa, and America; trade openness in Africa; and urbanization in Europe and America. Policymakers should concentrate on these variables for the reduction in GHGs. The annual convergence towards long-run equilibrium was 50.5, 31.9, and 20.9% for America, Asia, and Africa, respectively.

Olfactory bulb drives respiration-coupled beta oscillations in the rat hippocampus.

The synchronization of neuronal oscillations has been suggested as a mechanism to coordinate information flow between distant brain regions. In particular, the olfactory bulb (OB) and the hippocampus (HPC) have been shown to exhibit oscillations in the beta frequency range (10-20 Hz) that are likely to support communication between these structures. Here, we further characterize features of beta oscillations in OB and HPC of rats anesthetized with urethane. We find that beta oscillations simultaneously appear in HPC and OB and phase-lock across structures. Moreover, Granger causality analysis reveals that OB beta activity drives HPC beta. The laminar voltage profile of beta in HPC shows the maximum amplitude in the dentate gyrus (DG), spatially coinciding with olfactory inputs to this region. Finally, we also find that the respiratory cycle and respiration-coupled field potential rhythms (1-2 Hz)-but not theta oscillations (3-5 Hz)-modulate beta amplitude in OB and HPC. In all, our results support the hypothesis that beta activity mediates the communication between olfactory and hippocampal circuits in the rodent brain.

Identification of Directed Interactions in Kinematic Data during Running.

The knowledge of motion dynamics during running activity is crucial to enhance the development of rehabilitation techniques and injury prevention programs. Recent studies investigated the interaction between joints, using several analysis techniques, as cross-correlation, sensitivity analysis, among others. However, the direction of the joints pairing is still not understood. This paper proposes a study of the influence direction pattern in healthy runners by using kinematic data together with partial directed coherence, a frequency approach of Granger causality. The analysis was divided into three anatomical planes, sagittal, frontal, and transverse, and using data from ankle, knee, hip, and trunk segments. Results indicate a predominance of proximal to distal influence during running, reflecting a centralized anatomic source of movements. These findings highlight the necessity of managing proximal joints movements, in addition to motor control and core (trunk and hip) strengthening training to lumbar spine, knee, and ankle injuries prevention and rehabilitation.

Extravagance in the commons: Resource exploitation and the frontiers of ecosystem service depletion in the Amazon estuary.

Estuaries hold major economic potential due their strategic location, close to seas and inland waterways, thereby supporting intense economic activity. The increasing pace of human development in coastal deltas over the past five decades has also strained local resources and produced extensive changes across both social and ecological systems. The Amazon estuary is located in the Amazon Basin, North Brazil, the largest river basin on Earth and also one of the least understood. A considerable segment of the population living in the estuary is directly dependent on the local extraction of natural resources for their livelihood. Areas sparsely inhabited may be exploited with few negative consequences for the environment. However, recent and increasing pressure on ecosystem services is maximised by a combination of factors such as governance, currency exchange rates, exports of beef and forest products. Here we present a cross methodological approach in identifying the political frontiers of forest cover change in the estuary with consequences for ecosystem services loss. We used a combination of data from earth observation satellites, ecosystem service literature, and official government statistics to produce spatially-explicit relationships linking the Green Vegetation Cover to the availability of ecosystems provided by forests in the estuary. Our results show that the continuous changes in land use/cover and in the economic state have contributed significantly to changes in key ecosystem services, such as carbon sequestration, climate regulation, and the availability of timber over the last thirty years.

On the statistical performance of Granger-causal connectivity estimators.

In this article, we extend the statistical detection performance evaluation of linear connectivity from Sameshima et al. (in: Slezak et al. (eds.) Lecture Notes in Computer Science, 2014) via brand new Monte Carlo simulations of three widely used toy models under different data record lengths for a classic time domain multivariate Granger causality test, information partial directed coherence, information directed transfer function, and include conditional multivariate Granger causality whose behaviour was found to be anomalous.

Unified asymptotic theory for all partial directed coherence forms.

This paper presents a unified mathematical derivation of the asymptotic behaviour of the three main forms of partial directed coherence (PDC). Numerical examples are used to contrast PDC, gPDC (generalized PDC) and iPDC (information PDC) as to meaning and applicability and, more importantly, to show their essential statistical equivalence insofar as connectivity inference is concerned.