Indirect Variational Inference: Applications to Earnings Dynamics -- by Neele L. Balke, Stéphane Bonhomme, Thibaut Lamadon

Researchers introduced indirect variational inference to estimate latent-variable models without computing intractable likelihoods. The method uses machine learning variational approximations as an auxiliary step and corrects the resulting parameter bias. This gives researchers a way to estimate complex models of earnings dynamics reliably.

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