2022
DOI: 10.3233/sji-220055
|View full text |Cite
|
Sign up to set email alerts
|

The ILO nowcasting model: Using high-frequency data to track the impact of the COVID-19 pandemic on labour markets1

Abstract: The impact of the COVID-19 pandemic resulted in unprecedented labour market disruption, triggering the most severe global labour market crisis on record. The speed and depth of the crisis rendered labour force survey data unable to provide timely information. The ILO nowcasting model was designed to track the disruption in the world of work caused by the pandemic. This required: 1) filling data gaps, 2) increasing the timeliness of available data, and 3) focusing on an indicator that captured well the pandemic… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2023
2023
2023
2023

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(2 citation statements)
references
References 18 publications
0
2
0
Order By: Relevance
“…The quarterly projections for the unemployment rate, the EPR, the LFPR and the ratio of hours worked to population aged 15-64 use high-frequency data such as confidence indices in addition to economic growth forecasts in order to test a series of models. The approach is very much in line with the direct nowcasting approach used to estimate hours worked (Gomis et al 2022). These models are evaluated using the model search routines described above, including splitting the data into training and evaluation samples.…”
Section: Step 1 Projections At Quarterly Frequencymentioning
confidence: 69%
See 1 more Smart Citation
“…The quarterly projections for the unemployment rate, the EPR, the LFPR and the ratio of hours worked to population aged 15-64 use high-frequency data such as confidence indices in addition to economic growth forecasts in order to test a series of models. The approach is very much in line with the direct nowcasting approach used to estimate hours worked (Gomis et al 2022). These models are evaluated using the model search routines described above, including splitting the data into training and evaluation samples.…”
Section: Step 1 Projections At Quarterly Frequencymentioning
confidence: 69%
“…For an in-depth methodological description please consult Gomis et al (2022). The model produces an estimate of the change in hours worked adjusted for population aged 15-64 relative to this baseline.…”
Section: Hours Workedmentioning
confidence: 99%