Sharp decline in July for industrial production which also shows a decrease on a quarterly basis.
The seasonally adjusted index confirms high monthly variability in 2018, with a downward trend.
In trend terms, the change in the index adjusted for calendar effects becomes negative for the first time since June 2016.
Production levels held to a certain degree only for capital goods: it is also the only grouping of industries to maintain moderate trend growth in July.
The sectors of economic activity that recorded the highest trend growth are mining (+2.8%), the manufacture of electrical appliances and non-electrical household appliances (+1.8%) and the manufacture of machinery and equipment nec ( +1.3%). The greatest decreases were instead recorded in the manufacture of coke and refined petroleum products (-6.4%), in the wood, paper and printing industry (-5.8%), in metallurgy and metal products (excluding machinery and plants) ( -2.8%) and in the manufacture of rubber and plastic products, other non-metallic mineral products (-2.8%).
Production of basic pharmaceutical products and pharmaceutical preparations
Seasonally adjusted data
Short-term percentage changes
Jul 18/Jun 18: -5,2
May 18-Jul 18/Feb 18-Apr 18: +0,5
Data corrected for calendar effects
Trend percentage changes
Jul 18/Jul 17: -2,5
Jan-Jul 18/Jan-Jul 17: +5,8
ISTAT. Full text
Tuscan exports at +2.3% driven by pharmaceuticals
Note:
Corrected data for calendar effects:
data purged, using specific statistical techniques, of the variability attributable to the composition of the calendar in the individual periods (months or quarters) of the year, due to the different number of working days or specific days of the week contained therein and to the presence of public holidays national civil and religious, fixed and mobile (Easter holidays) as well as leap year. The use of this data transformation allows for a more adequate understanding of both the trend variations (calculated with respect to the same period of the previous year) and the average annual variations
Seasonally adjusted data: data purged, using specific statistical techniques, of fluctuations attributable to the seasonal component (due to meteorological, customary, legislative factors, etc.) and, if significant, of calendar effects. This data transformation is the most suitable for capturing the cyclical evolution of an indicator.
