The role of uncertainty as one of the key channels for transmission of shocks, such as financial shocks in 2008-2009, pandemic in 2020-2022, or sanctions, is regularly highlighted by experts and international organizations. How to measure uncertainty and its effects in practice? Indicators based on financial variables, text analysis of media publications, variance in expert forecasts or firms' expectations have been traditionally used for these purposes. This paper uses an alternative approach for the Russian case. Uncertainty is estimated as "unforecastibility" of future economic dynamics, that is, as a weighted average of standard deviations of forecast errors for the wide range of macroeconomic and macrofinancial variables. The forecasts are constructed through a factor model based on "big data". The estimated uncertainty indicators for 1, 3 and 12 months ahead show stronger persistence and countercyclicality compared to alternative indicators. Significant impact of uncertainty shocks on output and CPI is demonstrated, underscoring the need for analysis of mutual impact of uncertainty and effectiveness of countercyclical economic policies.