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The purpose of this paper is to examine the price–volume relationship in the bitcoin market to validate near-stock properties of bitcoin.

Daily data of bitcoin returns, returns volatility and trading volume (TV) are utilized for the period August 17, 2010–April 16, 2017. Linear and non-linear causality tests are employed to examine price–volume relationship in the bitcoin market.

The linear causality analysis indicates that the bitcoin TV cannot be used to predict return; however, the reverse causality is significant. In contrast, the non-linear causality analysis shows that there are non-linear feedbacks between the bitcoin TV and returns. The bitcoin TV, which represents new information, leads to price changes, and large positive price changes lead to increased trading activity. Similarly, in recent periods (post-break period), the results of the non-linear causality test show a unidirectional causality from TV to the volatility of returns.

This study uses the average index value of major bitcoin exchanges. But further research on this relationship using data from different bitcoin exchanges may provide further insights into the price–volume relationship of bitcoin and its near-stock properties.

These findings from the non-linear causality analysis, therefore, suggest that investors cannot simply base their decisions on the linear dynamics of the bitcoin market. This is because new information in terms of the TV is neither linearly related to the price nor it is a one-to-one kind of relationship as most investors commonly understand it to be. Rather, investors’ decisions should be based on non-linear models, in general, and the best-fitting non-linear model, in particular.

The study examines bitcoin’s near-stock properties in a price–volume relationship framework with the help of both linear and non-linear causality tests, which to the best of the authors’ knowledge remains unexplored.

This paper aims to examine the destabilization effect in the case of India’s agricultural commodity market for the sample period of 01 January 2009 to 31 May 2013.

The daily data of eight agricultural commodities traded on the National Commodity & Derivatives Exchange, viz., barley, castor seed, chana (chickpea), chilli, potato, pepper, refined soya and soybean, have been used in this study. At the first stage of the empirical analysis, the study estimates the time-varying spot market volatility by using the exponential generalized autoregressive conditional heteroscedasticity model and applies three different high and band-pass filters, viz., the two-sided linear band-pass filter by Hodrick and Prescott (1997), the fixed-length symmetric band-pass filter by Baxter and King (1999) and the asymmetric band-pass filter by Christiano and Fitzgerald (2003), to calculate the unexpected liquidity of sample commodities. At the second stage of the empirical analysis, the study applies linear Granger causality and recently developed non-linear causality given by Diks and Panchenko (2006) to examine the cause and effect between time-varying volatility of spot market and futures market liquidity of sample commodities.

The linear and non-linear causality results suggest the destabilizing effect of commodity futures on the underlying spot market for chana, chilli and pepper. The empirical findings are in contrast with the recommendations of Abhijit Sen’s committee and provide important direction for further policy research.

The study has a limitation in that it is based on the daily data. The use of intra-day data would have been more suitable for such type of analysis.

The study has strong policy implications from a financial policy perspective, as there is already disagreement among researchers and policy makers with regard to the functioning of commodity derivatives markets in India. There have been many occasions when commodity market regulators have to undertake decisions of suspension of trading of many commodities. The study also provides new directions of policy research with regards to the restructuring of the commodity derivatives market in India.

The findings of this study may further help the regulators and policy makers to undertake decisions about how to provide an alternative platform for farmers to sell their agricultural produce more efficiently. This will certainly have some impact on the socioeconomic set-up of the country, as India is primarily an agriculture-dominated country.

So far not many studies have investigated the destabilization hypothesis in the case of emerging markets. This study is a novel attempt to fill the gap. In the case of emerging markets and especially in the case of India’s commodity derivatives market, this is the first study that examines the destabilization hypothesis in the case of India by applying new methods of high and band-pass filters and non-linear causality.

The purpose of this paper is to examine the relationship between stock prices and exchange rates in 12 OECD countries.

The authors examine the nexus of stock prices and exchange rates for 12 OECD countries by using the vector error correction model, the bounds testing methodology and linear and non‐linear Granger causality methods.

The empirical results substantiate that a long‐run level equilibrium relationship among the exchange rates and stock prices exists in only seven out of twelve countries. The results of the linear causality tests indicate that significant short‐run and long‐run causal relationships exist between the two financial markets. The results of the tests for non‐linear Granger causality suggest that unidirectional and bidirectional non‐linear causal relationships exist between stock prices and exchange rates among these OECD countries.

The findings from this paper suggest the causal relationships between stock prices and exchange rates are not only linear, but also non‐linear.

The purpose of this paper is to analyse the adaptive market efficiency in the price–volume (P–V) relationship of the stocks listed in the Mexican Stock Exchange. The period under study goes from 1982 to 2015. In order to detect causality and, thus, determine adaptive efficiency in the market, one linear and two non-linear tests are applied. There are few papers in the literature that study the P–V relationship in Latin American markets; as such, this paper may be of interest and importance to financial academics and practitioners alike.

The Diks and Panchenko (DP) non-parametric Granger causality and the Brooks and Hinich (BH) cross-bicorrelation tests are applied.

Derived from the DP test, the findings show that there exists bi-directional non-linear Granger causality in 25.71 per cent of the firms studied, compared to 8 per cent when applying the linear Granger causality test. Therefore, there is evidence of weak-form efficiency in the market. From the BH test, evidence is shown of the adaptive market efficiency, since 71.42 per cent of firms exhibited some form of non-linear dependence in certain periods of time. With these results, the information process should be better studied for a greater comprehension of regulatory policies in the market and better decision-making tools for the investors.

This paper complements studies on the P–V relationship and efficiency in a Latin American market.

Este documento analiza la eficiencia adaptativa del mercado para la relación precio-volumen de las empresas que cotizan en la Bolsa Mexicana de Valores. El periodo bajo estudio es de 1982 a 2015. Para detectar causalidad y determinar la eficiencia adaptativa del mercado, se aplicó una prueba lineal y dos no-lineales. Existen pocos documentos en la literatura que estudien la relación precio-volumen en mercados latinoamericanos. Como tal, este documento puede ser de interés e importancia tanto para académicos como para profesionales de las finanzas.

Se aplicó la prueba de causalidad no-paramétrica de Diks y Panchenko y la prueba de bicorrelación cruzada de Brooks y Hinich.

Derivado de la prueba DP, los hallazgos muestran que existe causalidad no-lineal bidireccional en 25.71% de las empresas bajo estudio, comparado a un 8% cuando se aplica la prueba de causalidad lineal de Granger. Por lo tanto, existe evidencia de eficiencia en forma débil del mercado. De la pruba BH, se muestra evidencia de eficiencia adaptativa del mercado, dado que el 71.42% de las empresas exhibieron alguna forma de dependencia no-lineal en ciertos periodos de tiempo. Con estos resultados, el proceso de información debe ser mejor estudiado para una mayor comprensión de las políticas regulatorias del mercado y mejores herramientas para la toma de decisiones por los inversionistas.

Este documento complementa los estudios sobre la relación precio-volumen y la eficiencia en un mercado latinoamericano.

This study aims to investigate the dynamic relationship between renewable and non-renewable energy sources on the economic growth of eight countries, the capital stock and labour force being used as control variables in each case. Questions that need to be asked include the following: Is there is an asymmetric and, hence, a non-linear relationship between variables? If yes, how does economic growth interact with both renewable and non-renewable energy consumption (EC)? How different are these relationships in the countries highly rated in the performance of renewable EC compared to those lowly rated?

This paper uses asymmetric quantile-based methods to extract possible asymmetric and, hence, non-linear relationships between the underlying variables.

A newly developed asymmetric panel quantile approach suggests that EC has a significant effect on economic growth in both directions of shocks as well as for the considered sample. The results further support the findings in recent literature on renewable energy deployment, given the importance of renewable EC for economic growth with the increased levels of renewable EC, although the initial investments may have a negative effect on economic growth for some countries.

This study contributes to the literature in twofold. Firstly, it aims to contribute to the ongoing debate in literature by incorporating both renewable and non-renewable energy resources in the production function with labour and capital to test their asymmetric impact on economic growth. Secondly, this paper uses asymmetric quantile-based methods to extract possible asymmetric and, hence, non-linear relationships between the underlying variables. Another point that should be emphasised in this study is the need for studies analysing economic growth and EC for a sample of G20 countries based on a comparative view for the renewable and non-renewable EC in literature.

Highlighting the need for a profound move towards desecularisation of Islamic scholarship, this conceptual paper aims to clarify the concept of causality from the Islamic marketing research perspective and extends a number of suggestions for improving theory building and hypothesis development in the field.

The approach taken is largely conceptual. In addition, this study collates the stated hypotheses in the articles published in this journal in the past five years and analyses the structure of causal statements to uncover key tendencies.

The review of historical and current views on causality indicates that most commentators agree that assuming the existence of the necessary connection between cause and effect is misleading. The Islamic traditions based on occasionalism and modern science agree that causal statements reflect, at best, probabilistic assumptions.

This paper offers a number of insights and recommendations for theory building and hypothesis development in Islamic marketing. By following the occasionalism perspective and the notion of Sunnah of Allah, researchers will be able to build methodologically coherent and genuine Islamic marketing knowledge.

Correctly stated and tested hypotheses can be used by public policymakers to enforce effective consumer and market policies.

This paper tackles a complex issue of causality in Islamic marketing research which has not hitherto been discussed well in the literature. This research is also a unique step towards developing pioneering avenues within the domain of Islamic marketing research methodology.

The purpose of this paper is to show how non-linear causal modelling knowledge, already accumulated by other disciplines, is central to unravelling wicked problem scoping and definition in social marketing.

The paper is an illustrative case study approach, highlighting three real-world exemplars of causal modelling for wicked problem definition.

The findings show how the traditional linear research methods of social marketing are not sensitive enough to the dynamics and complexities of wicked problems. A shift to non-linear causal modelling techniques and methods, using interaction as the unit of analysis, provides insight and understanding into the chains of causal dependencies underlying social marketing problems.

This research extends the application of systems thinking in social marketing through the illustration of three non-linear causal modelling techniques, namely, collective intelligence, fuzzy cognitive mapping and system dynamics modelling. Each technique has the capacity to visualise structural and behavioural properties of complex systems and identify the central interactions driving behaviour.

Non-linear causal modelling methods provide a robust platform for practical manifestations of collaborative-based strategic projects in social marketing, when used with participatory research, suitable for micro, meso, macro or systems wide interventions.

The paper identifies non-linear causality as central to wicked problem scoping identification, documentation and analysis in social marketing. This paper advances multi-causal knowledge in the social marketing paradigm by using fuzzy, collective and interpretative methods as a bridge between linear and non-linear causality in wicked problem research.

This paper aims to focus on the contribution of segregated renewable energy (RE) sources such as solar, wind, bagasse, biomass, small hydropower (SHP) and waste to heat in driving sustainable industrial production in India.

This study uses non-linear modelling techniques such as quantile regression and the non-linear Granger causality test to explore the interplay between segregated RE generation and industrial production in India.

The study findings support the role of segregated RE sources generation, especially SHP and bagasse, on industrial production in India. This paper finds unidirectional non-linear Granger causality running from segregated RE sources to industrial production. Bidirectional non-linear Granger causality has been established from biomass, waste-heat to index of industrial production and vice versa, supporting an asymmetric feedback hypothesis.

The study findings will aid the energy policymaker in framing policies for RE sources, especially bagasse-based and SHP generation for the sustainable industrial growth of India.

To the best of the authors’ knowledge, this is one of the first studies to explore the role of segregated RE sources generation to drive sustainable industrial growth in India using non-linear techniques.

The direction of the causality relationship between Foreign Direct Investment (FDI) and economic growth is a highly controversial issue in the literature. There are two basic approaches advocating different causal directions between FDI and growth, which are called hypotheses of FDI-led Growth and Growth-led FDI. The aim of this study is to analyze the causality relationship between FDI and economic growth in RCEP countries and thus make a new contribution to the discussions in the relevant literature. In addition, the results of the study are expected to provide important implications for the policies to be designed for economic growth based on FDI flows to RCEP countries. Thus, by examining the direction of causality between FDI and economic growth in RCEP countries, we aim to provide a new contribution to related literature and make some implications for the policy design process of economic growth in the RCEP area.

We empirically examined the direction of a causal link between FDI and economic growth in the context of Regional Comprehensive Economic Partnership (RPEC) countries in order to test the hypothesis of FDI-led growth and Growth-led FDI. Accordingly, as our main variables of interest, we incorporated the inward foreign direct investment stock to gross domestic product ratio (FDI) and gross domestic product per capita (GDP). Hatemi-J (2012) asymmetric causality test has been employed in the investigation of the direction of causality between FDI and GDP over the period of 1980–2020. Thus, unlike most of the studies investigating the direction of causality between FDI and growth using the linear causality analysis method, our study performed a nonlinear causality analysis.

Empirical results reveal that the causal relationship between FDI and national income in RPEC countries is non-linear or asymmetric . The results of the symmetric causality test for both from FDI to national income and from national income to FDI are statistically insignificant for all countries. Therefore, this finding obtained from the study provided an important guide to the econometric methods to be used in other studies to be conducted in the same region in the future. Concerning the asymmetric causality relationship from FDI to growth, positive FDI shocks are an important cause of national income in most RCEP countries. However, the effect of negative FDI shocks on national income is quite weak compared to positive shocks. Regarding the asymmetric causality relationship from growth to FDI, positive national income shocks do not create a significant causal relationship with FDI. Similarly, the effects of negative national income shocks on FDI are statistically insignificant. Overall, asymmetric causality test results reveal that positive FDI shocks have an important causal impact on economic growth in most RCEP countries. Thus, the results of econometric analysis mostly support the argument that the FDI-led growth hypothesis rather than the Growth-led FDI hypothesis in RCEP countries. Accordingly, policy-makers in most of the RCEP countries should continue to provide more incentives and facilities to multinational companies in order to ensure constant economic growth.

Our study brings a significant difference in the econometric method used compared to most of the other studies in the literature. Existing empirical studies on the direction of causality between FDI and growth mostly use standard Granger-linear causality-type tests to detect the direction of causality among FDI and growth. Unlike most of the studies in the literature, our study adopted a different methodological approach, namely the Hatemi J test to detect the non-linear causality between FDI and economic growth in RCEP countries. Therefore, this paper made a new methodological contribution significantly to the literature focusing on the causal relationship between FDI and economic growth by using a non-linear causality method rather than a linear causality one.

The commonly adopted view of the relationship between government spending and economic growth follows the Keynesian approach, in which government spending is considered to determine economic growth. However, there is another theory, which suggests that economic growth in fact determines government spending. This is Wagner’s hypothesis. The purpose of this paper is to investigate which of the two approaches applies to South Africa, and further observes the level of non-linearity between the two variables.

This study was carried out using quarterly time series data from 1980Q1 to 2015Q1. Granger causality technique was used to observe the direction of causality between the two variables, while regression error specification test (RESET) was employed to determine whether the variables exhibit linear or non-linear behaviour. This was followed by observing the threshold band, using two techniques, namely, sample splitting threshold regression and quadratic generalised method of moments.

The causality result shows that South Africa follows Wagner’s law, whereby government spending is determined by economic growth, supporting Odhiambo (2015). The RESET result shows that the variables depict a non-linear relationship, thus the government spending economic growth model is non-linear. It was found that if positive economic development is to be achieved, economic growth should preferably be kept within the −1.69 and 3.0 per cent band, and specifically above 1 per cent band.

The unique contribution of this study is that no previous study has attempted the non-linear government spending-economic growth nexus whether within the Keynesian or Wagner law for South Africa.