Multivariate Linear and Non-Linear Causality Tests

2009 ◽  
Author(s):  
Zhidong Bai ◽  
Bingzhi Zhang ◽  
Wing-Keung Wong
Keyword(s):  
Non Linear ◽  
Causality Tests

UK House Prices – Connectedness or Ripple Effect?

2021 ◽  
Author(s):  
Taufiq Choudhry ◽  
Syed S. Hassan ◽  
Sarosh Shabi
Keyword(s):  
Northern Ireland ◽  
Housing Market ◽  
Economic Activity ◽  
House Prices ◽  
Ripple Effect ◽  
Non Linear ◽  
Causality Tests ◽  
Effect Hypothesis

The performance of the housing market is currently considered a measure of economic activity. This research explores the connectedness vs. the ripple effect hypothesis in the current house pricing literature. Using linear causality and nonlinear causality tests we show significant bidirectional dependence between the London house prices and other UK regions’ house prices except for Northern Ireland and Wales in contrast to the existing literature where more evidence of ripple effect is reported. Furthermore, linear and non-linear forecasting tests back these results. This result has important implications for policymakers and investors.

scholarly journals Bitcoin and Fiat Currency Interactions: Surprising Results from Asian Giants

Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1395
Author(s):  
Samet Gunay ◽  
Kerem Kaskaloglu ◽  
Shahnawaz Muhammed
Keyword(s):  
Regime Switching ◽  
Market Timing ◽  
Harmful Effect ◽  
Downward Trend ◽  
Switching Regression ◽  
Indian Rupee ◽  
Non Linear ◽  
Causality Tests ◽  
Causal Nexus ◽  
Chinese Yuan

This study examines the interaction of Bitcoin with fiat currencies of three developed (euro, pound sterling and yen) and three emerging (yuan, rupee and ruble) market economies. Empirical investigations are executed through symmetric, asymmetric and non-linear causality tests, and Markov regime-switching regression (MRSR) analysis. Results show that Bitcoin has a causal nexus with Chinese yuan and Indian rupee for price and various return components. The MRSR analysis justifies these findings by demonstrating the presence of interaction in contractionary regimes. Accordingly, it can be stated that when markets display a downward trend, appreciation of the Chinese yuan and Indian rupee positively and strongly affects the value of Bitcoin, possibly due to the market timing. The MRSR analysis also exhibits a transition from a tranquil to a crisis regime in March 2020 because of the pandemic. However, a shorter duration spent in the crisis regime in 2020 indicates the limited and relatively less harmful effect of the pandemic on the cryptocurrency market when compared to the turmoil that occurred in 2018.

scholarly journals Non-linear Causality Between Stock Returns And Inflation Uncertainty: Evidence From The US And The UK

2012 ◽  
Vol 12 (1) ◽  
pp. 63
Author(s):  
Esin Cakan
Keyword(s):  
Stock Returns ◽  
Granger Causality ◽  
Predictive Power ◽  
Inflation Uncertainty ◽  
The Us ◽  
Non Linear ◽  
Causality Tests ◽  
Granger Causality Tests ◽  
The Uk ◽  
Dynamic Relationships

This study analyzes the dynamic relationships between inflation uncertainty and stock returns by employing the linear and non-linear Granger causality tests for the US and the UK. Using GARCH model to generate a measure of inflation uncertainty, it does not have a predictive power for stock returns, as predicted by Friedman, and it does not support the opportunistic central bank hypothesis suggested by Cukierman-Meltzer. However, the findings from non-linear Granger causality put forth that there is a bi-directional non-linear predictive power between these variables. Stock market is used as a hedge against inflation uncertainty.

scholarly journals The co-movement and asymmetry between energy and grain prices: Evidence from the crude oil and corn markets

Energies ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1373 ◽  
Author(s):  
Chen ◽  
Wang ◽  
Zhang ◽  
Zheng
Keyword(s):  
Crude Oil ◽  
Granger Causality ◽  
Price Change ◽  
Oil Price ◽  
Oil Market ◽  
Non Linear ◽  
Causality Tests ◽  
Causality Relationship ◽  
Granger Causality Tests ◽  
Grain Prices

This paper investigates the co-movement and asymmetric interactions between energy and grain prices, based on the evidence from the crude oil and corn markets, the most important energy and grain markets, respectively. Time series analysis indicates that there is a consistent trend between the crude oil price and corn price with a significant positive correlation coefficient 0.7471 during the sampling period, from January 2008 to February 2016. In addition, we find that there is a long-run equilibrium relationship between the two commodities’ prices. Moreover, while linear Granger causality tests suggest that there is a two-way Granger causality relationship between the price changes in the two markets, non-linear Granger causality tests suggest that there is only a one-way causality relationship from corn to oil price. However, both linear and non-linear Granger causality tests indicate the asymmetry of causality relationship between the two markets (the price change in corn market can more significantly Granger cause the change in crude oil market). Further analysis suggests that the contribution of the corn market to price discovery in a large commodity market is larger than that of the crude oil market.

ENERGY CONSUMPTION AND GROWTH: NEW EVIDENCE FROM A NON-LINEAR PANEL AND A SAMPLE OF DEVELOPING COUNTRIES

2015 ◽  
Vol 60 (02) ◽  
pp. 1550018 ◽  
Author(s):  
TOLGA OMAY ◽  
NICHOLAS APERGIS ◽  
HÜLYA ÖZÇELEBI
Keyword(s):  
Developing Countries ◽  
Energy Consumption ◽  
Panel Cointegration ◽  
Smooth Transition ◽  
Vector Error Correction ◽  
Vector Error ◽  
Long Run ◽  
Cointegration Tests ◽  
Non Linear ◽  
Causality Tests

This paper investigates the relationship between economic growth and energy consumption through non-linear causality tests. Eight developing countries from Europe and Central Asia spanning the period 1993 to 2008 are selected for the purpose of panel empirical analysis. Panel unit root and panel cointegration tests with and without considering cross section dependency (CD) problems are implemented. Next, linear panel cointegration tests are employed and, finally, a two-regime Dynamic Panel Smooth Transition Vector Error Correction (PSTRVEC) model is estimated for testing the presence of non-linear short- and long-run causality. To this end, a new estimator, called the Dynamic Non-linear Pooled Common Correlated Effect Estimator (DNPCCEE) is proposed. The empirical findings indicate that short and long-run causalities are regime-dependent.

Is bitcoin a near stock? Linear and non-linear causal evidence from a price–volume relationship

2019 ◽  
Vol 15 (4) ◽  
pp. 533-545 ◽  
Author(s):  
Pradipta Kumar Sahoo ◽  
Dinabandhu Sethi ◽  
Debashis Acharya
Keyword(s):  
Linear Models ◽  
Causality Analysis ◽  
Reverse Causality ◽  
Causality Test ◽  
Price Changes ◽  
Content Type ◽  
New Information ◽  
Volume Relationship ◽  
Non Linear ◽  
Causality Tests

PurposeThe purpose of this paper is to examine the price–volume relationship in the bitcoin market to validate near-stock properties of bitcoin.Design/methodology/approachDaily 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.FindingsThe 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.Research limitations/implicationsThis 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.Practical implicationsThese 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.Originality/valueThe 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.

Technological development, financial development, and economic growth in India: Is there a non-linear and asymmetric relationship?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Arun Kumar Giri ◽  
Geetilaxmi Mohapatra ◽  
Byomakesh Debata
Keyword(s):  
Economic Growth ◽  
Financial Development ◽  
Technological Development ◽  
Content Type ◽  
Significance Level ◽  
Long Run ◽  
Non Linear ◽  
Causality Tests ◽  
Asymmetric Causality

PurposeThe main purpose of the present research is to analyze the relationship between technological development, financial development and economic growth in India in a non-linear and asymmetric framework.Design/methodology/approachThe study employs the nonlinear autoregressive distributed lags model (NARDL) and Hetemi J asymmetric causality tests to explore nonlinearities in the dynamic interaction among the variables. The stationarity properties of data are checked by using Ng–Perron and ADF structural break unit root tests. The unit root test confirms that the variables are non-stationarity in level and are differenced stationary.FindingsThe study finds that there is a cointegrating relationship between technological development, financial development and economic growth in the long run. The findings suggest that a positive shock in technological development increases economic growth (coefficient value 1.497 at 1% significance level) and a negative shock will harm economic performance (coefficient value −0.519 at 1% significance level). A long-term positives shock in financial development boosts the economy (coefficient value 1.08 at 5% significance level) and negative shock hampers the economic performance (coefficient value −1.09 at 5% significance level). The asymmetric causality test result confirms bi-directional causality between technological development and economic growth and unidirectional causality from negative economic growth to negative technological development and bi-directional causality between economic growth and financial development, unidirectional negative financial development to economic growth.Research limitations/implicationsThe results of this research can significantly facilitate stakeholders and policymakers in devising short-term as well as long-term policies for financial development and technological innovation to achieve sustainable long-run economic growth in India.Originality/valueThis paper is the first of its kind to empirically examine the cointegrating and causal relationship between technology, financial development and economic growth in India using non-linear asymmetric cointegration and causality tests.

B. The Non-Linear Calculations for Pulsating Stars

1967 ◽  
Vol 28 ◽  
pp. 105-176
Author(s):  
Robert F. Christy
Keyword(s):  
Major Part ◽  
Afternoon Session ◽  
Discussion Session ◽  
Pulsating Stars ◽  
Fourth Symposium ◽  
Non Linear ◽  
Considerable Discussion ◽  
Informal Approach ◽  
Preceding Session

(Ed. note: The custom in these Symposia has been to have a summary-introductory presentation which lasts about 1 to 1.5 hours, during which discussion from the floor is minor and usually directed at technical clarification. The remainder of the session is then devoted to discussion of the whole subject, oriented around the summary-introduction. The preceding session, I-A, at Nice, followed this pattern. Christy suggested that we might experiment in his presentation with a much more informal approach, allowing considerable discussion of the points raised in the summary-introduction during its presentation, with perhaps the entire morning spent in this way, reserving the afternoon session for discussion only. At Varenna, in the Fourth Symposium, several of the summaryintroductory papers presented from the astronomical viewpoint had been so full of concepts unfamiliar to a number of the aerodynamicists-physicists present, that a major part of the following discussion session had been devoted to simply clarifying concepts and then repeating a considerable amount of what had been summarized. So, always looking for alternatives which help to increase the understanding between the different disciplines by introducing clarification of concept as expeditiously as possible, we tried Christy's suggestion. Thus you will find the pattern of the following different from that in session I-A. I am much indebted to Christy for extensive collaboration in editing the resulting combined presentation and discussion. As always, however, I have taken upon myself the responsibility for the final editing, and so all shortcomings are on my head.)

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