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Insight

SALA DATI, a Terna podcast on electricity consumption #4

Electricity consumption and the economy: what Terna's data tell us. With Elena Degli Innocenti and Alessandro Venturi from the Terna Statistics Office.

Electricity consumption and the economy: what Terna’s data tell us. Every month, the national transmission grid operator publishes a report that provides an overview of the Italian electricity sector. But that’s not all, because its Statistics Office also analyses data by adding a valuable element: it deseasonalises the monthly historical series of electricity demand, and the industrial electricity consumption index. This allows us to provide an interpretative reading of Italy’s economic climate.

We find out why in the fourth episode of Sala Dati ("data room") podcast with Elena Degli Innocenti and Alessandro Venturi from the Terna Statistics Office.

[Elena Degli Innocenti] «The enormous wealth of data on electricity consumption and demand also allows Terna to have an advantageous observation point of how the Italian economy is faring. As a matter of fact, electricity consumption has historically been considered a good macro-indicator of how the economy is doing in general terms, and as closely related to GDP. Adjustments for seasonal, temperature and calendar effects make a difference».

«We are Elena Degli Innocenti [Venturi] and Alessandro Venturi, and we work in the Statistics Team. Today we’re talking about how to provide an economic interpretation of electricity data».

[Jingle with speaker] Sala Dati, the monthly podcast by Terna that explores the world of electricity consumption in Italy

[Venturi] «Terna publishes a monthly report that provides an overview of Italy’s electricity sector. But that’s not all, because the Statistics Office also analyses data by adding a valuable element: it deseasonalises the monthly historical series of electricity demand, and the industrial electricity consumption index. This allows us to provide an interpretative reading of Italy’s economic climate. Elena, what does it mean to deseasonalise data?».

[Degli Innocenti] «It means adjusting for seasonal effects, it’s a method used in statistics to remove seasonal fluctuations from the data in a historical series. Seasonality means the occurrence of all those fluctuations that repeat at regular intervals over time and which are determined by social and environmental factors. This process is usually used alongside another, which corrects the raw data of the calendar and temperature effects. Alessandro, can you explain more about what these components are?».

[Venturi] «The calendar effect is determined by several factors: the number of working days present in a given month, leap years, national, civil and religious holidays, including “movable feasts” like Easter, and how they fall within the reference period. All these elements influence electricity demand: for example, in August we expect a drop in industrial electricity consumption due to the closure of many factories and businesses for the summer holidays, while in February volumes generally decrease because it has fewer working days than other months. The temperature effect, on the other hand, means the monthly average value and the changes compared to average historical data. We also find a direct correlation with electricity demand in this case. For example, in the summer months, the high temperatures usually drive up energy demand, including as a result of the air conditioning systems in our homes. On the other hand, in winter the low temperatures keep demand down. Elena, I'll leave it to explain why these processes constitute added value».

[Degli Innocenti] «So… As you know, these measures make it possible to ‘standardise’ data and purify it of effects unrelated to the economic cycle of interest. Deseasonalised data are essential for analyses, because they make it possible to identify the underlying structural changes in the historical series and compare data over space and time. For this reason, this method is applied to the official statistics of various countries. To make data homogeneous and comparable at international level, Terna’s Statistics Office uses JDemetra+, the software officially recommended by Eurostat, and in particular the TRAMO-SEATS method».

[Venturi] «And it’s thanks to this technique that every month Terna promptly suggests analysis points. Today, thanks to experience gained in data analysis and processing, it is possible to show that electricity demand, and in particular the component related to industrial electricity consumption, is closely linked to two main economic indicators: GDP and the Industrial Production Index. Therefore, thanks to deseasonalised electricity consumption data, Terna is able to provide everyone with an almost immediate overview of how Italy’s economy is doing».

[Degli Innocenti] «We’ve been Elena Degli Innocenti and Alessandro Venturi and you’ve been listening to the fourth episode of Sala Dati, the podcast about electricity consumption in Italy explained by Terna professionals».