“…Methodologically speaking, in the present study, we have employed the partial and multiple wavelet coherence method by Aguiar-Conraria et al (2008, 2012 to investigate the association between tourism development, transportation, economic growth, and CO 2 emissions. 1 Following Dima et al (2015), Balli et al (2018), Das and Kumar (2018) and Singh et al (2018), This approach allows to examine the wavelet coherence of different time series, while controlling for their mutual related factors described by the effect of multiple predictor variables (Ng and Chan, 2012). Assuming the possible complication of the hypothesized association, this method can suggest inclusive outcomes about the interactions both in time and frequency realm.…”
The present paper endeavors to analyze and provide fresh insights from the dynamic association between tourism, transportation, economic growth and carbon emission in the United States. The analysis employs a novel Morlet's Wavelet Approach. Precisely, the paper implements Partial and Multiple Wavelet Coherence techniques to the monthly data spanning from 2001-2017. From the frequency domain point of view, the study discovers remarkable wavelet coherence and robust lead and lag linkages. The analysis discovers significant progress in variables over frequency and time. The variables display strong but inconsistent associations between them. There exist a strong co-movement among the variables considered, which is not equal across the time scales. The study may help the policymakers and regulars to devise strategies and formulate policies pertaining to tourism development, which can contribute towards environmentally sustainable economic growth.
“…Methodologically speaking, in the present study, we have employed the partial and multiple wavelet coherence method by Aguiar-Conraria et al (2008, 2012 to investigate the association between tourism development, transportation, economic growth, and CO 2 emissions. 1 Following Dima et al (2015), Balli et al (2018), Das and Kumar (2018) and Singh et al (2018), This approach allows to examine the wavelet coherence of different time series, while controlling for their mutual related factors described by the effect of multiple predictor variables (Ng and Chan, 2012). Assuming the possible complication of the hypothesized association, this method can suggest inclusive outcomes about the interactions both in time and frequency realm.…”
The present paper endeavors to analyze and provide fresh insights from the dynamic association between tourism, transportation, economic growth and carbon emission in the United States. The analysis employs a novel Morlet's Wavelet Approach. Precisely, the paper implements Partial and Multiple Wavelet Coherence techniques to the monthly data spanning from 2001-2017. From the frequency domain point of view, the study discovers remarkable wavelet coherence and robust lead and lag linkages. The analysis discovers significant progress in variables over frequency and time. The variables display strong but inconsistent associations between them. There exist a strong co-movement among the variables considered, which is not equal across the time scales. The study may help the policymakers and regulars to devise strategies and formulate policies pertaining to tourism development, which can contribute towards environmentally sustainable economic growth.
“…Mediante un modelo VARMA-GARCH-DCC, López, Ortiz y Cabello (2009) ofrecen evidencia de integración en los mercados accionarios de la región del Tratado de Libre Comercio de América del Norte (TLCAN). Mediante la metodología wavelet, Dima, Dima y Barna (2015) encontraron integración y procesos de sincronización de corto y mediano plazo en los mercados de México, Brasil y Chile.…”
En el presente artículo se estudian los spillovers (derrames) entre el S&P500 y el Mercado Integrado Latinoamericano para verificar si el inicio de la epidemia por COVID-19 y el entorno de ese momento cambiaron la dinámica de su nivel de conectividad. Usando la metodología propuesta por Diebold y Yilmaz se estimaron y analizaron índices de spillovers, desde y hacia, los mercados de Estados Unidos y del Mercado Integrado Latinoamericano. Los resultados confirman la existencia de spillovers provenientes del S&P500, sin que hayan sido mayores que los que se presentaron durante los años previos a 2020, con excepción del mercado mexicano, que recibió una mayor influencia. Los resultados pueden ser útiles para orientar decisiones de financiamiento e inversión en los mercados bursátiles de la región en el Mercado Integrado Latinoamericano.
“…1, gives an information on time changes in causality direction (phase lead of x(t) over y(t)), as well as an information on time changes in sign of co-movement between two analysed time series after controlling for third time series z(t) and is defined as [1,8,[44][45][46]:…”
The objective of this study is to verify the existence of the spillover effects within the complex system of internationally co-integrated real estate and financial markets in the case of the growth rates of the price indices of the direct real estate and indirect real estate investment markets within the selected national economies in the CEE region and to discuss the time stability of their directions, using research methods with physics and econometrics origins. The article considers the case of potential spillover effects between the Polish and Austrian national economies. Presented results have been obtained using wavelet analysis methods, such as wavelet coherency, wavelet phase difference, and wavelet partial phase difference analyses, enabling to check the indicated stability both in the time and frequency domains and to detect any potential structural changes dates. The results have not confirmed the hypotheses that the directions of the mentioned spillover effects displayed time stability in the examined period (Q4 2004-Q4 2014), which disproves the usefulness of the knowledge of the current directions of the indicated effects in the scope of performing long term investment policy, as well as in the scope of projecting the long term internal housing policies and long term internal macroprudential policies within the complex system.
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