This paper introduces the OECD Weekly Tracker of economic activity for 46 OECD and G20 countries using Google Trends search data. The Tracker performs well in pseudo-real time simulations including around the COVID-19 crisis. The underlying model adds to the previous Google Trends literature in...

New data sources, commonly referred to as “Big Data”, have attracted growing interest from National Statistical Institutes. They have the potential to complement official and more conventional statistics used, for instance, to determine progress towards the Sustainable Development Goals...

The forecasting uncertainty around point macroeconomic forecasts is usually measured by the historical performance of the forecasting model, using measures such as root mean squared forecasting errors (RMSE). This measure, however, has the major drawback that it is constant over time and hence...

This paper explores one distinctive form of the ‘big data’ of economics – individual tax record microdata – and its potential for tax policy analysis. The paper draws on OECD collaborations with Slovenia and Ireland in 2018 where tax microdata was used. Most empirical economics is based...

This report examines how big data from mobile phones and other sources can help to forecast travel demand. It identifies the strengths and potential use-cases for big data in transport modelling and mobility analysis. It also examines potential biases, commercial sensitivities and threats to...

Uncertainty is inherent to forecasting and assessing the uncertainty surrounding a point forecast is as important as the forecast itself. Following Cornec (2010), a method to assess the uncertainty around the indicator models used at OECD to forecast GDP growth of the six largest member...