Available for interviews at
European Job Market for Economists (EEA)
Allied Social Science Associations (ASSA)
Geert Mesters (Advisor) [email protected]
"Quasi-Bayesian Inference for Grouped Panels" (Job Market Paper)
This paper considers the problem of conducting inference in panel data models with latent group structures. I introduce a quasi-Bayesian framework that combines a general class of loss functions and priors for conducting joint inference on the latent group structures, including group-level parameters and group assignments. Theoretically I establish consistency of the proposed framework, and derive posterior contraction rates for the quasiBayesian posterior distribution. Simulation evidence shows large improvements in bias and coverage relative to existing methods, especially when the group assignments cannot be precisely estimated, e.g., when the signal-to-noise ratio is low. With the quasi-Bayesian clustering approach, I study the heterogeneous income risks of households and document a group whose income increases in response to higher unemployment rate. Importantly, the revealed group patterns are missed by pre-defined grouping criteria and k-means clustering methods.
Research in Progress
“Group Local Projections"
This paper considers the estimation of heterogeneous impulse responses in large panels. I introduce an efficient data-driven clustering methodology for grouping heterogeneous responses within the local projectionIV framework. The proposed group local projection (GLP) estimator consistently recovers the latent group structure and the group-specific impulse responses when the panel dimensions increase. Simulation evidence illustrates the reliable finite sample performance of the estimator even under misspecification of the group structure. With the GLP estimator I revisit the debate on the effects of monetary policy shocks on house prices and document significant price appreciation after a contractionary shock in an economically large cluster of MSAs in the US. Importantly, this cluster is ignored by conventional grouping criteria.
R&R at the Review of Economics and Statistics
This paper models the joint dynamics of macro aggregates and distribution functions within the Structural VAR framework and reduces the dimension of the system using functional PCA. The proposed functional VAR (FVAR) model is easy to implement and fully compatible with conventional SVAR tools. I show that FVAR consistently recovers the responses of distributions and it performs satisfactorily in finite samples. Applying FVAR to study the impact of tax shocks on income distributions in the UK. I find that tax cuts persistently reduce the density of lower-middle class households, which is compensated for by a large increase in the richer range and only a moderate rise in the extremely poor range. However, the pattern is missed in VARs with inequality measures.
"Firm Hierarchy and Wage Cylicality"(with Y. Fan)
This paper considers the role of firm hierarchy on aggregate unemployment fluctuations. Using matched employer-employee data in Germany for 1975-2010, we document a novel set of facts about the labor market cyclicality: wages are significantly less cyclical at higher hierarchical level of the firms. Moreover, firms with more layers reduce both wages and employment more aggressively during recessions.