Nonlinear Causal Relationships Research Articles

US non-linear causal effects on global equity indices in Normal times versus unconventional eras

This paper examines global spillover Quantitative Easing (QE) impacts of US on stock market indices by employing apart from a classical Granger causality, also a non-linear quantile regression approach for detecting causality on the tails of the stock indices’ distributions. Before US unconventional monetary policies, the non-linear causal relationship between the Fed’s balance sheet and stock markets is found to be not significant for most indices over the middle level of quantiles, whereas significant causal relationships are present in tails. There is non-linear evidence that the Fed’s assets were mainly influenced by US, Latin American, Australian and some Asian indices while the other stock indices did not Granger cause balance sheet enlargement for any quantile interval before 2008. Nevertheless, almost all domestic and foreign stock indices are found to exert feedback effects during US QE. We argue that US total assets exert non-linear causality towards all stock indices under scrutiny at least at one level of quantile and tighter links of the Fed mainly with advanced economies are found, as impacts on the upper quantile are stronger during US QE.

The problem of “harm” in the theory of international relations

The article provides an analytical review of the literature on the issue of harm in the theory of international relations, as a result of which this issue has been supplemented and expanded. The issue has initially been posed by Andrew Linklater as a question of physical harm to humans in the context of a state-centered international system. Audra Mitchell entered into a discussion with A. Linklater from the standpoint of post-humanism. From her point of view, harm should be evaluated not only and not so much from the human point of view, but from the perspective the whole world, the totality of animate and inanimate nature, including humanity. Alex Hoseason called into question the nature of causal relations in the theories of A. Linklater and A. Mitchell. From his point of view, in complex social systems, such as international system, non-linear causal relationships and multiple causality prevail. In addition, based on the philosophy of critical realism, Alex Hoseason suggested that not only actors in international relations, but also social structures can cause harm. This narrative is further developed by problematique of biopolitics. Political governance of biological aspects of the life of the population is directly related to the problem of physical harm in the sense that biopolitics, on the one hand, is aimed at maintaining the physical health of the population, on the other hand, politics is still at the core of biopolitics, so sometimes it can turn against all or part of its population as happened in Nazi Germany. Today, biopolitics at the global level is implemented in the UN development programs, in various international and transnational initiatives to promote international development, as well as in global health governance. Expanding the problematique of harm to biopolitics brings us back to the original anthropocentric model of harm proposed by A. Linklater, nevertheless, this step allows us to analyze not only the causes of harm, but also approaches to reducing it.

Nonlinear dependence and information spillover between electricity and fuel source markets: New evidence from a multi-scale analysis

This study identifies nonlinear causality between electricity and fuel source returns based on a new multi-scale framework. The empirical results show that the causality direction between electricity and fuel returns behaves differently across time scales. Generally speaking, linear or nonlinear causality relationship between the electricity and gas markets exists for most time scales. The study also explores the magnitude of the feedback effects between electricity and fuel returns using the connectedness network. The results show that the degree of feedback effects between the electricity and fuel markets is relatively weak at the original data level. Across various time scales, there is positive but weak information spillover from the oil and uranium to electricity markets and reciprocal information spillover between the electricity and gas/coal markets at most time horizons. The information spillover from the gas to electricity returns is relatively strong.

Investment Sustained by Consumption: A Linear and Nonlinear Time Series Analysis

This paper studies the dynamic relationship between consumption and investment in the United States between 1947 and 2018. Our findings support the postulates of Keynesian economics—while they are contrary to the theoretic background on which the numerous empirical studies on the saving-investment nexus are based. We find a long-run nexus between consumption and investment, and positive linear Granger-causality running unidirectionally from consumption to investment. Therefore, investment is sustained by consumption. Further, we find that the variables have nonlinear structures and, thus, we apply nonlinear causality tests. We provide evidence of nonlinear causality running unidirectionally from consumption to investment. Nevertheless, after controlling for Government Expenditure, this nonlinear causal relationship disappears, indicating that Government Expenditure drives the nonlinear causal relationship between private consumption and investment. We argue that this finding is consistent with the notion that investment decisions are guided by permanent aggregate demand, because public expenditure allows private consumption to have a sufficiently permanent trajectory to be considered as a guide for investment decisions. Our results do not support the austerity and deflation measures implemented in the last years (especially in the European Union). On the other hand, our findings call for the incentive of final public expenditure, since it favours the long-run link between the private decisions to consume and invest.

Recurrent neural networks for reconstructing complex directed brain connectivity.

While Granger Causality(GC)-based approaches have been widely employed in a vast number of problems in network science, the vast majority of GC applications are based on linear multivariate autoregressive (MVAR) models. However, it is well known that real-life system (and biological networks in particular) exhibit notable nonlinear behavior, hence undermining that validity of MVAR-based approaches to estimating GC (MVAR-GC). In this paper, we define a novel approach to estimating nonlinear, directed within-network interactions based on a specific class of recurrent neural networks (RNN) termed echo-state networks (ESN). We reformulate the classical GC framework in terms of ESN-based models for multivariate signals generated by arbitrarily complex networks, and characterize the ability of our ESN-based Granger Causality (ES-GC) to capture nonlinear causal relations by simulating multivariate coupling in a network of nonlinearly interacting, noisy Duffing oscillators operating in a chaotic regime. Synthetic validation shows a net advantage of ES-GC over all other estimators in detecting nonlinear, causal links. We then explore the structure of EC-GC networks in the human brain in functional MRI data from 1003 healthy subjects scanned at rest at 3T, discovering previously unknown between-network interactions. In summary, ES-GC performs significantly better than commonly used and recently developed GC detection tools, making it a superior tool for the analysis of e.g. multivariate biological networks.

INCLUSIVE FINANCE, GROWTH AND SOCIO-ECONOMIC DEVELOPMENT IN SAUDI ARABIA: A THRESHOLD COINTEGRATION APPROACH

Empirical literature argues that financial inclusion has positive impact on growth, reduce inequality and poverty. This paper has twofold. First, it aims to provide a measurement of financial inclusion in the Kingdom of Saudi Arabia (KSA) as an oil-rich economy during the period 1980-2016 by the construction of a comprehensive index. Second, we study the incidence of financial inclusion on growth and human development through a set of socioeconomic leading variables. Using GMM methodology, our results suggest that financial inclusion is highly and positively correlated to human development index, and to employed share of adult population. Conversely, financial inclusion is insignificantly negatively correlated to per capita real GDP and highly negatively correlated to the share of rural population and to the share of women in adult population. In this study we take in consideration the non-linearity between inclusive finance, economic growth and human development by performing threshold cointegration and Granger-causality tests. Our findings show that there is non-linear causal relationship between financial inclusion, human development and economic growth in the long-run while in the short-run neither financial inclusion nor economic growth Granger-causes each other. This result is in concordance with previous empirical studies in the case of oil-based economies. Our findings could help policy-makers and regulators in KSA to design an inclusive financial sector taking into account the specificities of the Saudi economy.

NCREANN: Nonlinear Causal Relationship Estimation by Artificial Neural Network; Applied for Autism Connectivity Study.

Quantifying causal (effective) interactions between different brain regions are very important in neuroscience research. Many conventional methods estimate effective connectivity based on linear models. However, using linear connectivity models may oversimplify the functions and dynamics of the brain. In this paper, we propose a causal relationship estimator called nonlinear Causal Relationship Estimation by Artificial Neural Network (nCREANN) that identifies both linear and nonlinear components of effective connectivity in the brain. Furthermore, it can distinguish between these two types of connectivity components by calculating the linear and nonlinear parts of the network input-output mapping. The nCREANN performance has been verified using synthesized data and then it has been applied on EEG data collected during rest in children with autism spectrum disorder (ASD) and typically developing (TD) children. The results show that overall linear connectivity in TD subjects is higher, while the nonlinear connectivity component is more dominant in ASDs. We suggest that our findings may represent different underlying neural activation dynamics in ASD and TD subjects. The results of nCREANN may provide new insight into the connectivity between the interactive brain regions.

On the relation between global food and crude oil prices: An empirical investigation in a nonlinear framework

The research explores the dynamic relationship between global crude oil price and food price indices on a sample of monthly data spanning from January 1990 to June 2017 within a nonlinear framework. Linear methods are applied first to examine the stationarity, co-integration and linear Granger causality of the variables of crude oil and food price indices. Moreover, a series of nonlinear tests are used to detect the nonlinearity of the univariate and oil-food prices link. Finally, the asymmetric adjustment analyses are made to understand the dynamic vary mechanism depending on the considered regime of the threshold vector autoregressive model (TVAR), and the threshold vector error correction model (TVECM) is integrated to check how the variables respond to the deviations from the equilibrium. The findings of systematic tests and analyses confirm the fact that there is a nonlinear causal relationship between global crude oil and food price indices. The co-movement of crude oil and food price has obvious structural break features, which is relevant to the underlying regime. Furthermore, the results also show that the adjustment process of the food price indices towards equilibrium is highly persistent and grows faster than oil price when a threshold is reached.

Ownership Concentration and Fund Performance in Conventional and Shariah Malaysian Mutual Funds

This study investigates the ownership concentration comprises managerial ownership, director ownership, and institutional ownership between Conventional and Shariah mutual fund (SMF) toward enhancing fund performance by employing the traditional method of considering a non-linear causal relationship. Overall, the results support the notion of a non-linear relation between managerial ownership and fund performance. Although the ownership by managers is more concentrated and significantly different in SMF, the positive relation is more pronounced in conventional fund. More importantly, the relation remains strong non-linear significantly and jointly determined by fund performance in a two-way relationship when endogeneity, simultaneity, and heterogeneity unobserved issues are considered. The study also finds that institutional ownership with conflicting interest in mutual fund signals negative effect on fund performance. The findings suggest that ownership by managers plays an effective role of agency control and value-enhancing at certain depth of concentration to align the interest between managers and shareholders.

Can onshore spot market progress influence offshore N.D.F. market development for the C.N.Y?

This study utilises a time-varying wavelet analysis to examine the relationship between the onshore spot market and the offshore non-deliverable forward (N.D.F.) market of the Chinese Yuan (C.N.Y.). Given the presence of structural changes in the two markets, we did not find any stable causality during the sample period. However, in some sub-samples, we found that there is a strong nonlinear causal relationship running from the onshore spot market to the offshore N.D.F. market. Ties between the two markets are closer after the widening of the onshore trading band, first in April 2012, second in March 2014 and again in August 2015. The onshore spot market is heavily influenced by interventions by the People's Bank of China (P.B.C.). These findings imply that offshore N.D.F. market development is not divorced from onshore development, as developments in the onshore spot market influence the offshore N.D.F. market. The results show that the exchange rate markets for the C.N.Y. are not efficient. Thus, to successfully internationalise the C.N.Y., financial expansion of the onshore spot market should keep pace with the growing offshore N.D.F. market to minimise destabilisation of the C.N.Y.

Re-assessing causality between energy consumption and economic growth.

The energy consumption-growth nexus has been widely studied in the empirical literature, though results have been inconclusive regarding the direction, or even the existence, of causality. These inconsistent results can be explained by two important limitations of the literature. First, the use of bivariate models, which fail to detect more complex causal relations, or the ad hoc approach to selecting variables in a multivariate framework; and, second, the use of linear causal models, which are unable to capture more complex nonlinear causal relationships. In this paper, we aim to overcome both limitations by analysing the energy consumption-growth nexus using a Flexible Fourier form due to Enders and Jones (2016). The analysis focuses on the US over the period 1949 to 2014. From our results we can conclude that, where the linear methodology supports the neutrality hypothesis (no causality between energy consumption and growth), the Flexible Fourier form points to the existence of causality from energy consumption to growth. This is contrary to the linear analysis, suggesting that lowering energy consumption would adversely affect US economic growth. Thus, by employing the Flexible Fourier form we find the conclusions can be quite different.

Does exchange rate management affect the causality between exchange rates and oil prices? Evidence from oil-exporting countries

The bi-directional causality between exchange rates and oil prices of oil-exporting countries has been widely investigated since the oil crisis in the 1970s. The classical theoretical framework assumes that countries adopt free-floating exchange rate arrangements, and empirical studies seldom consider exchange rate restrictions when investigating oil exporters that always manage exchange rates. To address these limitations, this study designs a comparative analysis for three groups of oil-exporting economies that adopt different foreign exchange rate policies. The analysis aims to examine whether and how intervention behavior may distort the causal relationship between exchange rates and oil prices. We first show the non-linear causality relationships for countries with “free-floating exchange rate arrangements” in both long and short terms. Then, we establish how the managed floating policy can eliminate the impact of oil prices on exchange rates in bull markets but fail to prevent exchange rate depreciation in bear markets. In bear markets, a negative non-linear feedback from exchange rates to oil prices prevails in these countries. However, contrary to common wisdom, the strict “soft-pegged exchange rate arrangement” cannot remove all the linkages between exchange rates and oil prices. A small but significant response of exchange rates toward oil prices is detected for Kuwait and Saudi Arabia. A similar effect for Kazakhstan is only found in bear markets. In addition, this study re-investigates the relationship between exchange rate and the domestic currency price of oil. The conclusions are similar, except that the relationship is weakened in free-floating countries but strengthened in managed floating countries during the bear market periods.

Impacts of woody invasive alien plant species on rural livelihood: Generalized propensity score evidence from Prosopis spp. invasion in Afar Region in Ethiopia

This study applied a generalized propensity score method to evaluate the impact of Prosopis invasion on Afar pastoralist and agro-pastoralist households’ annual per capita consumption expenditure, as a proxy of rural livelihoods. The analysis was based on cross-sectional survey data collected in mid-2016 from 250 households in the Afar National Regional State in Ethiopia. The method was applied to match households with similar covariates with different Prosopis invasion levels. The method was effective in teasing out non-linear causal relationships between Prosopis invasion dose and household per capita consumption expenditure. Average dose-response or impact function was obtained by estimating average annual household per capita consumption expenditure at different levels of Prosopis invasion. Initially, the plants’ impact was positive, but turned negative after an optimum invasion dose. The optimal invasion dose of Prosopis was found to be 22.23%. The corresponding optimum level of annual household per capita consumption expenditure was found to be 4,500.50 Ethiopian Birr (USD 198). The results suggest that to maximize the benefits of Prosopis and minimize its adverse effects on the livelihoods of the pastoral and agro-pastoral communities, diverse management strategies that take into account not only the intensity of invasion, but also patterns of dryland economy should be implemented.

Oil Prices and Chinese Stock Market: Nonlinear Causality and Volatility Persistence

ABSTRACTThis article mainly focuses on investigating the nonlinear co-integration and nonlinear causality relationships between oil prices and Chinese stock market at the overall and sectoral levels by using nonlinear autoregressive distributed lags (NARDL) model and Diks and Panchenko (DP) test. The empirical results show that there are not significantly asymmetric co-integration effects between oil prices and Chinese stock market for the overall and sectoral levels. However, the significantly nonlinear causality between oil prices and Chinese stock market can be found. Specifically, oil prices can widely affect Chinese stock indices through nonlinear channel. The cases in the reverse also work for overall indices and Mining, Utilities, Financial and Real Estate sectors. Furthermore, the potential sources of these nonlinear causality linkages are examined. The results suggest that volatility persistence rather than asymmetrical co-integration is the major factor that accounts for the nonlinear causality between oil prices and Chinese stock market.

Markov-switching vector autoregressive neural networks and sensitivity analysis of environment, economic growth and petrol prices.

The paper aims at evaluating the nonlinear and complex relations between CO2 emissions, economic development, and petrol prices to obtain new insights regarding the shape of the environmental Kuznets curve (EKC) in the USA and in the UK in addition to introducing a newly proposed nonlinear approach. Within this respect, the paper has three purposes: the first one is to combine the multilayer perceptron neural networks (MLP) with Markov-switching vector autoregressive (MS-VAR) type nonlinear models to obtain the MS-VAR-MLP model. The second is to utilize one of the largest datasets in the literature covering the 1871-2016 period, a long span of data starting from the late eighteenth century. Since the emission, economic development, and petrol price relation is subject to nonlinearity and trajectory changes due to many historical events, the development of the MS-VAR-MLP model is a necessity to contribute to the ongoing debate regarding the shape of the EKC curve and the stability of the relation. The third purpose is to develop the MS-VAR-MLP-based regime-dependent sensitivity analysis, which eases the visual interpretation of the nonlinear causal relationships, which are allowed to have asymmetric interactions in different phases of the expansionary and recessionary periods of the business cycles. Our results provide clear deviations from the findings in the literature: (i) the shape of the EKC curve cannot be assumed to be stable and is subject to regime dependency, nonlinearity, and magnitude dependency; (ii) the forecast results suggest that incorporation of regime switching and neural networks provide significant improvement over the MS-VAR counterpart; and (iii) for both USA and UK and for the 1871-2016 period, the positive impacts of economic growth on emissions cannot be rejected for the majority of the phases of the business cycles; however, the magnitude of this effect is at various degrees. In addition, the incorporation of petrol price provides significant findings considering its effects on emission and economic growth rates. The analysis suggest clear deviations from the expected shape of the EKC curve and puts forth the necessity to utilize more complex empirical methodologies to evaluate the EKC since the emissions-economic development relation is more complex than it was assumed. Following these findings, several policy recommendations are provided. Lastly, the proposed MS-VAR-MLP methodology is compared with the MS-VAR model and various advantages and disadvantages are enumerated.

Nonlinear Granger causality between grains and livestock

Linear and nonlinear Granger causality between three grains: corn, soybean, wheat and two livestock commodities: live cattle and lean hogs, was verified. Weak evidence of linear causal relationships was found, supporting the results published in other studies. However, strong nonlinear causal relationships between grain and livestock returns were found, which had not yet been documented in the literature on this subject. The revealed relationships have different patterns and features, and in some cases, they arise from second moment dependencies, but nonlinearities of a different type were also found. Most of the discovered nonlinear relationships are bidirectional.

An Empirical Analysis of the Relationships between Crude Oil,Gold and Stock Markets

Oil and gold are used as investment assets and so they are closely related to the evolution of stock market indices, given that any influence on decisions about investment portfolios can affect stock market returns. Consequently, it is important for investors to analyze the direction of influence between crude oil, gold and stock markets when designing and implementing their investment strategies.Thus, this paper studies the direction of the causality among the three markets for the US case. In doing so, we apply linear and non-linear Granger causality tests for daily data from the Great Moderation onwards. Evidence is provided as to the importance of considering the possibility of nonlinear relationships between the three markets, a feature which cannot be revealed using conventional linear causality tests which would therefore lead to an information loss about the true link.The results for the full sample indicate that the causality goes in all directions, which implies that changes in the stock market returns may be monitored by observing changes in the returns of the two commodity markets considered (and vice versa). This may help to design substitution investment strategies. The results also indicate that the direction of influence between markets does not exhibit material differences between various subsamples, with the exception of the causality relationship between the two commodity markets. This may in part help explain the contradictory results and mixed conclusions found in previous related literature.

How Real Oil Prices and Domestic Financial Instabilities are Good for GCC Countries Tourism Demand in Malaysia?

Malaysia, located in the heart of Southeast Asia, is a multicultural country whose ‘green’ and ‘blue’ tourism attractions have become the main tourism spot for the Cooperation Council for the Arab States of the Gulf (GCC) tourists. We employed the Threshold Error Correction (TECM) cointegration and the nonlinear causality estimates to capture the nexus between real energy prices and financial stability for the GCC countries’ tourism demand in Malaysia using the monthly-based dataset covering the period since 1995 till 2017. The main TECM estimate shows that real energy price fluctuations and financial instability condition in Malaysia positively boost tourists’ arrivals from the GCC countries to Malaysia. Indeed, there is evidence of an asymmetric speed of adjustment of the GCC countries’ tourism demand with 25.9% and 36.7% of positive and negative deviations, respectively. In addition, this study found a strong evidence of unidirectional nonlinear causal relations running from real energy prices to tourism demands; and also bidirectional causalities running from tourism demand to financial stability. These findings will be helpful for tourism policy makers in Malaysia while drawing a future roadmap to increase the numbers of the GCC tourists’ arrivals in future years.

아파트 가격과 거래량의 비선형 인과관계 분석

아파트 가격과 거래량의 비선형 인과관계 분석

Linear and nonlinear causal relationship between energy consumption and economic growth in China: New evidence based on wavelet analysis.

The energy-growth nexus has important policy implications for economic development. The results from many past studies that investigated the causality direction of this nexus can lead to misleading policy guidance. Using data on China from 1953 to 2013, this study shows that an application of causality test on the time series of energy consumption and national output has masked a lot of information. The Toda-Yamamoto test with bootstrapped critical values and the newly proposed non-linear causality test reveal no causal relationship. However, a further application of these tests using series in different time-frequency domain obtained from wavelet decomposition indicates that while energy consumption Granger causes economic growth in the short run, the reverse is true in the medium term. A bidirectional causal relationship is found for the long run. This approach has proven to be superior in unveiling information on the energy-growth nexus that are useful for policy planning over different time horizons.