Essays on monetary economics and applied macroeconomics
This thesis consists three chapters on topics in monetary economics and applied macroeconomics. In the first chapter, I consider a framework where the central bank has private information about future economic conditions. Agents update their beliefs according to Bayes’ theorem. Policy actions play a...
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| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2018 |
| País: | España |
| Institución: | CBUC, CESCA |
| Repositorio: | TDR. Tesis Doctorales en Red |
| OAI Identifier: | oai:www.tdx.cat:10803/662937 |
| Acceso en línea: | http://hdl.handle.net/10803/662937 |
| Access Level: | acceso abierto |
| Palabra clave: | Monetary economics 33 |
| Sumario: | This thesis consists three chapters on topics in monetary economics and applied macroeconomics. In the first chapter, I consider a framework where the central bank has private information about future economic conditions. Agents update their beliefs according to Bayes’ theorem. Policy actions play a signaling role, and may therefore have an impact on both short and long-term interest rates. I discuss the implications of information frictions for the design of optimal simple rule. In the second chapter, I explore the role of market power for the optimal choice of infla-tion index for a central bank to stabilize In a framework with cross-sector heterogeneities in both nominal rigidity and market power. The optimal weight attached to inflation in a sector is increasing in this sector’s: i)price stickiness (stickiness channel) and ii) degree of market competition (competition channel). Moreover, if firms in a more competitive sector adjust their price more frequently as predicted by costly price adjustment models, the competition channel offsets the stickiness channel. In the third chapter, I show that for short horizon exchange rate predictability, the simple random walk model outperforms professional forecasts. A new puzzle arises: why do professional forecasters not adopt the simple random walk model to provide a more accurate estimate? I provide an explanation based on ambiguity averse forecasters. |
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