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Oxford Bulletin of Economics and Statistics ; 2023.
Article in English | Scopus | ID: covidwho-2293616

ABSTRACT

We introduce a Bayesian mixed frequency VAR model for the aggregate euro area labour market that features a structural identification via sign restrictions. The purpose of this paper is twofold: we aim at (i) providing reliable and timely forecasts of key labour market variables and (ii) enhancing the economic interpretation of the main movements in the labour market. We find satisfactory results in terms of nowcasting and forecasting, especially for employment growth. Furthermore, we look into the shocks that drove the labour market and macroeconomic dynamics from 2002 to 2022, with an insight also on the COVID-19 recession. While demand shocks were the main drivers during the Global Financial Crisis, technology and wage bargaining factors, reflecting the degree of lockdown-related restrictions and job retention schemes, have been important drivers of key labour market variables during the pandemic. © 2023 Oxford University and John Wiley & Sons Ltd.

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