Modeling persistence of carbon emission allowance prices

Abstract

This study reexamines the issue of persistence in carbon emission allowance spot prices, using daily data, and covering the period from 28/2/2007 to 14/05/2014. For this purpose we use techniques based on the concept of long memory accounting for structural breaks and non-linearities in the data, with both of these aspects potentially affecting the degree of persistence. Our results indicate that, while there is no evidence of non-linearity, when allowing for structural breaks, persistence of shocks to the carbon emission allowance is markedly reduced, with the same being transitory in nature for recent sub-samples.JEL classification: C22, G13, G14, Q50

Persistence, Mean-Reversion and Non-linearities in $$\hbox {CO2}$$ CO2 Emissions: Evidence from the BRICS and G7 Countries

“…Complete details of these results are available upon request from the authors. However, some discussion of the relevant results can be found in Footnote 2. root tests have low power when a series is characterized by a fractional integration process (for a detailed discussion in this regard and more, see Gil-Alana et al, 2015).…”

“…Thus, a growing literature has examined the stationarity of CO 2 series using different time series techniques, different sample of countries and time periods. For example, Heil and Selden (1999) Although the inclusion of structural breaks in the univariate analysis of CO 2 series is common in the literature, only a few papers include non-linear deterministic trends when calculating the fractional integration order of the series (Gil-Alana et al, 2015). These authors analyze the issue of persistence in carbon emission allowance spot prices using daily data for the period 2007-2014 accounting for structural breaks and nonlinearities in the data.…”

Particulate matter 10 (PM10): persistence and trends in eight European capitals

“…Long memory is a feature of time series that are characterised by a high degree of dependence between observations which are far apart in time. It has been found to be displayed by many time series in different fields such as climatology (Gil-Alana 2005, 2008Vyushin and Kushner 2009;Franzke 2012;Ludescher et al 2016;Bunde 2017;Yuan et al 2019;Bruneau et al 2020), environmental sciences (Barros et al 2016;Gil-Alana et al 2016;Tiwari et al 2016;Solarin 2018, Gil-Alana andTrani 2019;Xayasouk et al 2020) and economics and finance (Gil-Alana and Moreno 2012;Abritti et al 2017;Kalemkerian and Sosa 2020;Murialdo et al 2020;Qiu et al 2020).…”

CO2 emissions converge in China and G7 countries? Further evidence from Fourier quantile unit root test

“…G7 countries and China are not only the biggest energy producers globally but also the largest CO 2 emission groups of countries among the world, and as pointed by Gil-Alana et al., 1 more than 60% of the total CO 2 emissions around the world come from these eight countries in 2014. The reduction of greenhouse gas emissions is a global imperative, making thus each country responsible in the fight of the global warming phenomenon.…”