This paper offers a novel contribution to the literature on Marginal Emission Factors (MEF) by proposing a robust empirical methodology for their estimation across both time and space. Our Autoregressive Integrated Moving Average models with time-effects not only outperforms the established models in the economics literature but it also proves more reliable than variations adopted in the field of engineering. Utilising half-hourly data on carbon emissions and generation in Great Britain, the results allow us to identify a more stable path of MEFs than obtained with existing methodologies. We also estimate marginal emission effects over subsequent time periods (intra-day), rather than focussing only on individual settlement periods (inter-day). This allows us to evaluate the annual cycle of emissions as a result of changes in the economic and social activity which drives demand. Moreover, the reliability of our approach is further confirmed upon exploring the cross-country context. Indeed, our methodology proves reliable when applied to the case of Italy, which is characterised by a different data generation process. Crucially, we provide a more robust basis for valuing actual carbon emission reductions, especially in electricity systems with high penetration of intermittent renewable technologies.

Where did the time (series) go? Estimation of marginal emission factors with autoregressive components / Beltrami, F.; Burlinson, A.; Giulietti, M.; Grossi, L.; Rowley, P.; Wilson, G.. - In: ENERGY ECONOMICS. - ISSN 0140-9883. - 91:(2020), pp. 104905.1-104905.14. [10.1016/j.eneco.2020.104905]

Where did the time (series) go? Estimation of marginal emission factors with autoregressive components

Grossi L.;
2020-01-01

Abstract

This paper offers a novel contribution to the literature on Marginal Emission Factors (MEF) by proposing a robust empirical methodology for their estimation across both time and space. Our Autoregressive Integrated Moving Average models with time-effects not only outperforms the established models in the economics literature but it also proves more reliable than variations adopted in the field of engineering. Utilising half-hourly data on carbon emissions and generation in Great Britain, the results allow us to identify a more stable path of MEFs than obtained with existing methodologies. We also estimate marginal emission effects over subsequent time periods (intra-day), rather than focussing only on individual settlement periods (inter-day). This allows us to evaluate the annual cycle of emissions as a result of changes in the economic and social activity which drives demand. Moreover, the reliability of our approach is further confirmed upon exploring the cross-country context. Indeed, our methodology proves reliable when applied to the case of Italy, which is characterised by a different data generation process. Crucially, we provide a more robust basis for valuing actual carbon emission reductions, especially in electricity systems with high penetration of intermittent renewable technologies.
2020
Where did the time (series) go? Estimation of marginal emission factors with autoregressive components / Beltrami, F.; Burlinson, A.; Giulietti, M.; Grossi, L.; Rowley, P.; Wilson, G.. - In: ENERGY ECONOMICS. - ISSN 0140-9883. - 91:(2020), pp. 104905.1-104905.14. [10.1016/j.eneco.2020.104905]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/2997215
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