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Understanding the Relationship between Digital Currencies and Search Engines
Published in Amina Omrane, Khalil Kassmi, Muhammad Wasim Akram, Ashish Khanna, Md Imtiaz Mostafiz, Sustainable Entrepreneurship, Renewable Energy-Based Projects, and Digitalization, 2020
Naveed Ahmad Lone, Yousfi Karima, Hurmat Sumaiya Binti Bashir
For all series we tested the null hypothesis of the unit root, using Augmented Dickey-Fuller (ADF), the Phillips-Perron (PP) test, and the Kwiatkowski, Phillips, Schmidt, and Shin (KPSS) unit root test (Maddala & Kim, 1998). Each series was tested for the presence of a unit root. The unit root test statistics suggest the presence of a unit root in the level, while first differencing the series yields the apparent lack of a unit root in the two variables, the Bitcoin price index and Google Trends in the log. From these results, we can conclude that each series has a unit root at levels and it is stationary when the first difference is taken. It can be said that all variables are integrated of order 1, I(1). We then check for the presence of cointegrating relations between these variables (Table 9.3).
Economic Development, Environmental Degradation and Sustainability
Published in Uday Chatterjee, Arindam Biswas, Jenia Mukherjee, Dinabandhu Mahata, Sustainable Urbanism in Developing Countries, 2022
Nilendu Chatterjee, Bappaditya Koley, Anindita Nath, Uday Chatterjee
We also have applied panel unit root tests for smooth supervision or conduction of estimation. The generalized method of moments (GMM)8 has been used to estimate the relationships with the help of simultaneous equations. Again, panel unit root tests have been applied for the overall panel. The following panel unit root tests have been applied: LLC test (Levin et al., 2002), IPS test (Im et al., 2003), PP-Fisher chi-square (Maddala & Wu, 1999) and Fisher-type augmented Dicky Fuller (ADF) test.
Complexity Analysis of Pathogenesis of Coronavirus Epidemiological Spread in the China Region
Published in Jyoti Mishra, Ritu Agarwal, Abdon Atangana, Mathematical Modeling and Soft Computing in Epidemiology, 2020
Rashmi Bhardwaj, Aashima Bangia, Jyoti Mishra
Basically, a unit root test is used to check stationarity as these unit roots can cause unpredictable results in the autoregressive models of time-series analysis. Time series is different in comparison with the predictive modeling. As in modeling, the assumptions exist that summary statistics of observations are consistent. In context with time series, these expectations are referred as time domain, which is stationary.
Examining the non-linear stochastic behavior of the European energy market: evidence from nonlinear unit root tests
Published in Energy Sources, Part B: Economics, Planning, and Policy, 2022
Ceyda Aktan, Tolga Omay, Eyyüp Ensari Şahin
While past research on the topic is limited, Silvapulle and Moosa (1999), Taback (2003), Coimbra and Esteves (2004), Serletis and Rangel-Ruiz (2004), and Maslyuk and Smyth (2008) have investigated the efficiency of the Brent and WTI crude oil prices and found these markets to be efficient. However, our results have shown that the Oil and Gas indices of Austria, Denmark, Finland, France, Greece, Italy, Netherlands, Poland, Russia, and the UK are stationary. One of the reasons for the differences in findings could be related to the types of tests utilized. Majority of the studies were seen to utilize conventional linear unit root tests, which are shown to be insufficient when applied to time-series data that does not follow a linear path. Existence of financial crises, market frictions, transaction costs, the interaction of heterogeneous agents, and other behavioral factors can cause a nonlinear movement in this financial data (Hasanov and Omay 2008). Other reasons can include the time frame tested, significant events, such as wars, terror attacks, pandemics that can cause variations in results. Also, without taking into account the structural break or business cycle and therefore financial cycles of the countries may have affected the results obtained and hence, caused wrong policies to be made. This study improves and adds to the policies of previous research by including information on nonlinearity, structural breaks, and financial cycles.
Correlation between COVID-19 cases and gold price fluctuation
Published in International Journal of Mining, Reclamation and Environment, 2022
Roshan Gautam, Yoochan Kim, Erkan Topal, Michael Hitch
The Augmented Dicky Fuller (ADF) test was used to determine whether the series has a unit root or not [15] to investigate the relationship between global COVID-19 cases and their influence on the value of gold price. The Augmented Dicky Fuller (ADF) test is applicable for large and complex set of time series autoregressive model to test whether time series prices contain unit root or not. There are alternative tests to ADF test such as the Phillips–Perron test (PP) or the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) Test. The null hypothesis for the KPSS test is opposite to the ADF test and essentially exhibits the same outcome as ADF. The performance of PP test on finite samples is lower compared to ADF test, [16] which is hence the reason why ADF test is employed in this research. The purpose of unit root test is to ensure both the gold price and COVID-19 cases contain unit roots, because co-integration test is applicable when the variables contain unit roots. Unit root is a stochastic trend in a time series, sometimes called a ‘random walk with drift.’ If a time series has a unit root, it shows a systematic pattern that is unpredictable. The unit root test formula [17] is stated as:
Economic growth and sectoral level electricity consumption nexus in India: new evidence from combined cointegration and frequency domain causality approaches
Published in International Journal of Sustainable Energy, 2022
Mohammed Shameem P, Muhammed Ashiq Villanthenkodath, Krishna Reddy Chittedi
After analyzing the trend of the variables, we have explored the possible unit root problem in each series under investigation since the presence of unit root may produce spurious regression outcomes. To this end, this study employs the Augmented Dicky Fuller (ADF) test of Dickey and Fuller (1979) and the Phillips-Perron (PP) test of Phillips and Perron (1988) test to uncover the unit root problem in the study variables. Employment of these tests on the series helps understand the level of association and also the long-short run dynamics. The emanated outcomes are reported in Table 3, which shows that all the study variables are stationary at their first difference, but they are stationary at their level.