Essays in Macroeconometrics
The thesis consists of three chapters on macroeconometric analysis with heterogeneity. Chapter 1 introduces an efficient data-driven clustering methodology for grouping heterogeneous responses within the local projection-IV framework. The proposed group local projection (GLP) estimator consistently...
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| Format: | doctoral thesis |
| Status: | Published version |
| Publication Date: | 2024 |
| Country: | España |
| Institution: | CBUC, CESCA |
| Repository: | TDR. Tesis Doctorales en Red |
| OAI Identifier: | oai:www.tdx.cat:10803/691968 |
| Online Access: | http://hdl.handle.net/10803/691968 |
| Access Level: | Embargoed access |
| Keyword: | Macroeconometrics 33 |
| Summary: | The thesis consists of three chapters on macroeconometric analysis with heterogeneity. Chapter 1 introduces an efficient data-driven clustering methodology for grouping heterogeneous responses within the local projection-IV framework. The proposed group local projection (GLP) estimator consistently recovers the latent group structure and the group-specific impulse responses. Chapter 2 introduces a quasi-Bayesian framework that combines general classes of loss functions and priors for joint inference on the latent group structures, including group-level parameters and group assignments. Simulation results demonstrate significant improvements in bias and coverage for group-level parameters compared to existing methods, particularly when group assignments cannot be precisely estimated. Chapter 3 models the joint dynamics of macro aggregates and functional variables within the Structural VAR framework. The proposed functional VAR (FVAR) is easy to implement and fully compatible with conventional SVAR tools. Simulation evidence shows that it performs satisfactorily in finite samples. |
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