Information of fiscal origin has become a fundamental element to understand the economic reality of the country. The case of current information is no exception. In this sense, the daily sales obtained from the Immediate Information Supply (SII) system of the VAT stand out. Some 65 thousand companies are covered by this system, a small number compared to other indicators, also from the Tax Agency, such as, for example, the sales of Large Companies and corporate SMEs that offer information on more than one million companies. However, sales from SII account for more than two-thirds of the turnover of the total number of VAT reporting companies and, above all, the information is available in real time, so the indicator The resulting one is the most closely linked to the recent evolution of the activity.

Last Wednesday, the last weekly report was published, which included the first estimate of sales for the month of April ( Tax Agency: Daily inside sales ). Chart 1 allows us to place the result in the context of what the sales trend has been in recent months.

In September, a process of gradual slowdown in growth began, in real and nominal terms, more acute in this case as it coincided with lower inflationary pressure. The minimum was reached at the beginning of the year and data for February and March showed improvement. The rebound was especially intense in March, but has not lasted into April. What has happened in these two months for such disparate behavior to occur?

Part of the answer is found in graph 2, which shows the daily sales for the months of February, March and April of the last two years. The graph shows the start of the strike in the road freight transport sector in 2022.

The start of the strike meant a shock to the decline in sales from which they only recovered from the second week of April. The March figure benefited from that fact, just as the April figure has now been harmed.

This is one of the virtues of daily information, being able to detect with certain precision events that occurred on specific dates and give them appropriate treatment. On the other hand, the daily series are very irregular, difficult to interpret. In fact, these dates are one of the many factors that introduce noise into the economic series, the more so the higher the frequency of observation; Hence, we must resort to some modulation factor, as happens in the previous graph with the 28-day moving average, trying to clean up that noise. But this is not new: The quarterly series are more irregular than the annual series and the monthly series more than the quarterly series. The daily series remind us that in economic analysis we always have to debate between having information early, but with noise, or without noise, but late. The problem is that decisions cannot always wait to have irrefutable data and in those cases it is of little use to know with certainty in two years what happened yesterday.