the value of surveys and make them fit for the 21st century, although it may also put a question mark over the survival of surveys as self - contained sets of information. as a data producer, the bank of italy is trying to exploit some of the new opportunities. the sampling design of the last wave of the shiw has changed thanks to newly available administrative information on households ’ income and indebtedness. this change has materially improved our ability to observe segments of the population that, though small, account for a high share of the target variables, such as wealth or debt. this helps to reconcile survey - based data with aggregate variables and to compute more accurate distributional statistics. our income, consumption and wealth joint project with the national institute of statistics ( istat ) aims at creating a synthetic database for three different surveys, 3 using statistical matching techniques that rely on a common set of administrative records. together with the ecb, we have also started a distributional wealth accounts project that is meant to bridge the gap between two survey waves by linking macro and micro data. many similar experiments are taking place across the world, and this meeting is a good opportunity to exchange experiences, including beyond or between formal sessions. we look forward to the new and valuable insights that this conference will surely provide. let me reiterate my welcome to all participants, including those following remotely. i wish you a fruitful two days of discussions. ( 1 ) the survey on income and living conditions ( eu - silc ) for income ; ( 2 ) the household budget survey ( hbs ) for consumption ; and ( 3 ) the survey on household income and wealth for wealth.

often differ across jurisdictions and data domains. therefore, international cooperation is to be encouraged as far as possible. technologies enabling the processing of personal data are already available. in 2019, google made available its differential privacy library, which allows sensitive data to be processed privately. to reach these welfare - improving goals, further investment from both the public and the private sector are required. close cooperation between the private sector, which typically owns most of the new data, and the public sector, which uses ( or would like to use ) such data for policy reasons and for the common good, will also be essential. this is why central banks have always made great efforts when it comes to collecting and analysing data. throughout its history, banca d ’ italia has drawn extensively on data published by the national statistical institute and other national and international agencies. it has also been an active producer of statistics, not only on banking, financial and fiscal variables, but also on firms and households. banca d ’ italia has been collecting micro - level statistical information on companies since the early 1950s. these data are now enriched with non - traditional sources such as social media, blogs, newspapers, and private company datasets6. 5. conclusions let me conclude my talk by thanking, once again, all the speakers and participants for joining us today, even in this virtual fashion. we hope to welcome you here in rome in person in the near future. special thanks go to those who have helped to organize this workshop, which brings together leading economists, statisticians, artificial intelligence and machine - learning specialists, data scientists from about fifty - five central banks and fifteen participants from universities and government agencies. this guarantees a broad variety of perspectives and a lively discussion. i am sure that you are going to have a very interesting and productive workshop. such as the real estate website, immobiliare. it, and the mortgage website, mutuionline.