Ahmed, Mumtaz Khan, Atif Maqbool Bibi, Salma and Zakaria, Muhammad 2016. Convergence of per capita CO2 emissions across the globe: Insights via wavelet analysis. Renewable and Sustainable Energy Reviews,
Almasri, A. Månsson, K. Sjölander, P. and Shukur, G. 2016. A wavelet-based panel unit-root test in the presence of an unknown structural break and cross-sectional dependency, with an application of purchasing power parity theory in developing countries. Applied Economics, p. 1.
Aye, Goodness C. Chang, Tsangyao and Gupta, Rangan 2016. Is gold an inflation-hedge? Evidence from an interrupted Markov-switching cointegration model. Resources Policy, Vol. 48, p. 77.
Bailey, Natalia and Giraitis, Liudas 2016. Spectral approach to parameter-free unit root testing. Computational Statistics & Data Analysis, Vol. 100, p. 4.
Bekiros, Stelios Nguyen, Duc Khuong Uddin, Gazi Salah and Sjö, Bo 2016. On the time scale behavior of equity-commodity links: Implications for portfolio management. Journal of International Financial Markets, Institutions and Money, Vol. 41, p. 30.
Chang, Shinhye Gupta, Rangan and Miller, Stephen M. 2016. Causality Between Per Capita Real GDP and Income Inequality in the U.S.: Evidence from a Wavelet Analysis. Social Indicators Research,
Duchesne, Pierre and Hong, Yongmiao 2016. Advances in Time Series Methods and Applications.
Hansen, Bjørn Gunnar and Li, Yushu 2016. An Analysis of Past World Market Prices of Feed and Milk and Predictions for the Future. Agribusiness,
Olayeni, Olaolu Richard 2016. Causality in Continuous Wavelet Transform Without Spectral Matrix Factorization: Theory and Application. Computational Economics, Vol. 47, Issue. 3, p. 321.
Pogorelenko, Nataliia Lyashenko, Vyacheslav V. and Ahmad, Mohammad Ayaz 2016. Wavelet Coherence as a Research Tool for Stability of the Banking System (the Example of Ukraine). Modern Economy, Vol. 07, Issue. 09, p. 955.
Raza, Syed Ali Sharif, Arshian Wong, Wing Keung and Karim, Mohd Zaini Abd 2016. Tourism development and environmental degradation in the United States: evidence from wavelet-based analysis. Current Issues in Tourism, p. 1.
Shahzad, Syed Jawad Hussain Kumar, Ronald Ravinesh Ali, Sajid and Ameer, Saba 2016. Interdependence between Greece and other European stock markets: A comparison of wavelet and VMD copula, and the portfolio implications. Physica A: Statistical Mechanics and its Applications, Vol. 457, p. 8.
Tiwari, Aviral K. Albulescu, Claudiu T. and Gupta, Rangan 2016. Time–frequency relationship between US output with commodity and asset prices. Applied Economics, Vol. 48, Issue. 3, p. 227.
Trokić, Mirza 2016. Wavelet energy ratio unit root tests. Econometric Reviews, p. 1.
Yang, Lu Cai, Xiao Jing Zhang, Huimin and Hamori, Shigeyuki 2016. Interdependence of foreign exchange markets: A wavelet coherence analysis. Economic Modelling, Vol. 55, p. 6.
Bekiros, Stelios Nguyen, Duc Khuong Uddin, Gazi Salah and Sjö, Bo 2015. Business cycle (de)synchronization in the aftermath of the global financial crisis: implications for the Euro area. Studies in Nonlinear Dynamics & Econometrics, Vol. 19, Issue. 5,
Bouoiyour, Jamal Selmi, Refk Tiwari, Aviral Kumar and Shahbaz, Muhammad 2015. The nexus between oil price and Russia's real exchange rate: Better paths via unconditional vs conditional analysis. Energy Economics, Vol. 51, p. 54.
Caraiani, Petre 2015. Estimating DSGE models across time and frequency. Journal of Macroeconomics, Vol. 44, p. 33.
Chakrabarty, Anindya De, Anupam Gunasekaran, Angappa and Dubey, Rameshwar 2015. Investment horizon heterogeneity and wavelet: Overview and further research directions. Physica A: Statistical Mechanics and its Applications, Vol. 429, p. 45.
Chen, Yi-Ting Sun, Edward W. and Yu, Min-Teh 2015. Improving model performance with the integrated wavelet denoising method. Studies in Nonlinear Dynamics & Econometrics, Vol. 19, Issue. 4,
This paper develops a wavelet (spectral) approach to testing the presence of a unit root in a stochastic process. The wavelet approach is appealing, since it is based directly on the different behavior of the spectra of a unit root process and that of a short memory stationary process. By decomposing the variance (energy) of the underlying process into the variance of its low frequency components and that of its high frequency components via the discrete wavelet transformation (DWT), we design unit root tests against near unit root alternatives. Since DWT is an energy preserving transformation and able to disbalance energy across high and low frequency components of a series, it is possible to isolate the most persistent component of a series in a small number of scaling coefficients. We demonstrate the size and power properties of our tests through Monte Carlo simulations.
This list contains references from the content that can be linked to their source. For a full set of references and notes please see the PDF or HTML where available.
Email your librarian or administrator to recommend adding this journal to your organisation's collection.
Full text views reflects the number of PDF downloads, PDFs sent to Google Drive, Dropbox and Kindle and HTML full text views.
Abstract views reflect the number of visits to the article landing page.
* Views captured on Cambridge Core between September 2016 - 28th March 2017. This data will be updated every 24 hours.