Drawing on available real-time data, the model estimates the historical statistical relationship between these indicators and hours worked per person aged 15–64, and uses the resulting coefficients to predict how hours worked adjusted for population aged 15–64 change in response to the most recent observed values of the nowcasting indicators. Multiple candidate relationships were evaluated on the basis of their prediction accuracy and performance around turning points to construct a weighted average nowcast.
For countries for which high frequency data on economic activity were available, but either data on the target variable itself were not available or the above methodology did not work well, the estimated coefficients and data from the panel of countries were used to produce an estimate.
An indirect approach is applied for the remaining countries: this involves extrapolating the change in hours adjusted for population aged 15–64 from countries with direct nowcasts. The basis for this extrapolation is the observed mobility decline from the Google Community Mobility Reports and the Oxford Stringency Index, since countries with comparable drops in mobility and similar stringent restrictions are likely to experience a similar decline in hours worked adjusted for population aged 15–64. From the Google Community Mobility Reports, an average of the workplace and “retail and recreation” indices was used. The stringency and mobility indices were combined into a single variable using principal component analysis. Estimates from the first quarter of 2023 and onwards incorporate other high-frequency variables, such as quarterly GDP growth projections.
Additionally, for countries without data on restrictions, mobility data, if available, and up-to-date data on the incidence of COVID-19 were used to extrapolate the impact on hours worked adjusted for population aged 15–64. Because of countries’ different practices in counting cases of COVID-19 infection, the more homogenous concept of deceased patients was used as a proxy of the extent of the pandemic. The variable was computed at an equivalent monthly frequency, but the data were updated daily based on the Our World in Data online repository.
Finally, for a small number of countries with no readily available data at the time of estimation, the regional average was used to impute the target variable.
See the Annex of the latest ILO Monitor: COVID-19 and the world of work for information and statistical approach used to estimate the target variable for each country.