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In this paper, we show the causal influence of the launch of generative AI in the form of ChatGPT on the search behavior of young people for apprenticeship vacancies. There is a strong and long-lasting decline in the intensity of searches for vacancies, which suggests great uncertainty among the...
Persistent link: https://www.econbiz.de/10014437989
In this paper, we show the causal influence of the launch of generative AI in the form of ChatGPT on the search behavior of young people for apprenticeship vacancies. There is a strong and long-lasting decline in the intensity of searches for vacancies, which suggests great uncertainty among the...
Persistent link: https://www.econbiz.de/10014444041
In this paper, we show the causal influence of the launch of generative AI in the form of ChatGPT on the search behavior of young people for apprenticeship vacancies. There is a strong and long-lasting decline in the intensity of searches for vacancies, which suggests great uncertainty among the...
Persistent link: https://www.econbiz.de/10014469812
In this paper, we show the causal influence of the launch of generative AI in the form of ChatGPT on the search behavior of young people for apprenticeship vacancies. There is a strong and long-lasting decline in the intensity of searches for vacancies, which suggests great uncertainty among the...
Persistent link: https://www.econbiz.de/10014469847
Persistent link: https://www.econbiz.de/10012001308
Matching-type estimators using the propensity score are the major workhorse in active labour market policy evaluation. This work investigates if machine learning algorithms for estimating the propensity score lead to more credible estimation of average treatment effects on the treated using a...
Persistent link: https://www.econbiz.de/10012060603
Persistent link: https://www.econbiz.de/10012098947
Persistent link: https://www.econbiz.de/10012216299
Based on administrative data of unemployed in Belgium, we estimate the labour market effects of three training programmes at various aggregation levels using Modified Causal Forests, a causal machine learning estimator. While all programmes have positive effects after the lock-in period, we find...
Persistent link: https://www.econbiz.de/10012219355
We investigate heterogenous employment effects of Flemish training programmes. Based on administrative individual data, we analyse programme effects at various aggregation levels using Modified Causal Forests (MCF), a causal machine learning estimator for multiple programmes. While all...
Persistent link: https://www.econbiz.de/10012153340