Tracking activity in real time with Google Trends

Abstract

This document, as well as any data and map included herein, are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. 2  ECO/WKP(2020)42 TRACKING ACTIVITY IN REAL TIME WITH GOOGLE TRENDS UnclassifiedOECD Working Papers should not be reported as representing the official views of the OECD or of its member countries. The opinions expressed and arguments employed are those of the author(s).Working Papers describe preliminary results or research in progress by the author(s) and are published to stimulate discussion on a broad range of issues on which the OECD works.

An age-structured SEIR model for COVID-19 incidence in Dublin, Ireland with framework for evaluating health intervention cost

“…[ 25 ] produce initial estimates of the medium-term impact of the crisis on the Irish economy. Relating to Ireland, we draw on the work of [ 26 ] in order to construct weekly estimates of year on year (same week in different years) growth rate of Gross Domestic Product (GDP). This existing approach makes forecasts based on a neural network modelling framework, with training of the model done via quarterly GDP and Google Trends search intensity data gathered over forty six countries from the beginning of 2005 for sixty one quarters.…”

“…This existing approach makes forecasts based on a neural network modelling framework, with training of the model done via quarterly GDP and Google Trends search intensity data gathered over forty six countries from the beginning of 2005 for sixty one quarters. The quarterly data is used to construct a forecasting model corresponding to a weekly resolution making an assumption of frequency neutrality [ 26 ].…”

“…While GDP is understood for example by [ 29 ] as being a relatively poor measure of the health of the Irish economy due to the influence of large multinational companies on the economy, these companies, particularly in the pharmaceutical and ICT sectors, helped keep the government’s budget deficit lower than it otherwise would have been. Finally, the weekly GDP calculations of [ 26 ] enable the production of a measure of the overall economic impact of COVID–19 relative to each lockdown period. A weekly tracker of economic activity allows for matching of economic predictions with the timescale of typical lockdown duration.…”

Effects of mobility restrictions during COVID19 in Italy

“…More on that in Sup. section S3, we next compare OECD data which calculates economic activity based on multiple attainable sources on the national level 55 to produce an estimated GDP (EGDP) with our mobility metrics. While this is an approximate metric, it analyzes various Internet search patterns related to economic activity and shows a close prediction (to within its margin of error) to the officially published quarterly national GDP 56 .…”

3D printing and International Trade

“…To assess the extent to which adoption of 3D printing technology through imports is associated with exports of 3D printable items, proxy measures for these variables are needed. 38 For imports of 3D printers, HS code 847780 is used based on WCO recommendations for classifying existing trade in 3D printers (Box 3) 38 An alternative methodological approach involves the use of difference-in-difference techniques which compare trends before and after the adoption of 3D printing to draw observations on its impact on the period following adoption (Freund, Mulabdic and Ruta, 2019 [3]). While this sidesteps the need for proxy measures, it requires a relatively fast adoption and strong knowledge of when 3D printing was widely adopted in specific sectors.…”