But the social costs, the damage to the public and the confusion it creates, the harm to the integrity of the institutions and their credibility is enormous. Uninformed agent can base their financial decision on unsound grounds, thus incurring personal  2/3  BIS - Central bankers' speeches  economic losses. And we as institutions might suffer erosion of our credibility that could hamper us in delivering on our public goods. What can be done to mitigate the impact of misinformation in the modern world? Let me refer on this note on the Study on "Societal Costs of Fake News in the Digital Single Market"3 and transpose it to economics. First, it is the self-regulation of the industry – raising awareness of misinformation, costs that it can entail for the society and need of fact-checking. Second is the regulation – creating clear and transparent rules of game. Third, education - media and information literacy can lead to increased public awareness and capacity to critically asses the news, including fake news. Against this background, how can we as producers of statistics contribute in this regard? It appears that adequate communication of our data to the public can help crowd out low quality statistics. We need to consider how to bring closer the statistical products of our work to the public. It is true, that we as central banks have provided to the public a vast portfolio of statistical data, with many dimensions, metadata and public explanations.
We as a central bank also vested enormous efforts making many adjustments in data collection, production and communication process that helped us smoothing the pandemics effect on the production and dissemination of statistics. The pandemic in the initial phase tested the resilience of the statistical system, i.e., the ability to continue with timely supply of statistical data. But it also created demand pressures for new data that was not produced by the official statistics. Data on the epidemiological curve became highly needed as they are leading indicator on how the economy will evolve and how economic and social policies should be calibrated. At the same time, there has been growing demand for real-time high-frequency data on the economy, as many of the historical systematic linkages that policy decisions were based on were broken. For instance, we have been intensively using google mobility data during the lockdowns to assess the behaviour of consumers. We have also leveraged on the private sector data for payment card transactions, as an indicator to assess the personal consumption dynamics and its structure. Although highly useful, the abundance of data also poses a challenge for statisticians, as accentuated by the health crisis. As we go further down the road, the need for quick and granular data, for example on the changes of the economic behaviour of the agents, the longer term scarring to the economy, or the impact of the policy actions on economy will be a "must".