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This dissertation contains three essays on monetary policy, dynamics of the interest rates and spillovers across economies. In the first essay I examine the effects of monetary policy and its interaction with financial regulation within a micro-founded macroeconometric framework for a closed economy with a heterogeneous banking system, facing a period of low interest rates. I analyse the interplay between monetary policy and banking regulation and study the role of agents’ expectations for the effectiveness of unconventional monetary policy tools. In the next essay, I argue that openness is crucial for understanding the dynamics of the term structure. In an empirical application, I show that my model of the term structure fits well the yield curve in-sample and has a sound ability to forecast interest rates out-of-sample. The model accounts for the expectations hypothesis, replicates the forward premium anomaly and reconciles the uncovered interest rate parity implications. The last essay is concerned with the dynamics of co-movement among macroeconomic aggregates and the degree of convergence or decoupling amongst economies. The model includes measures of financial and trade-based interdependencies and incorporates feedback between macroeconomic variables and time-varying weights. The findings point at the importance of asset price movements and financial linkages.
In the euro area, monetary policy is conducted by a single central bank for 20 member countries. However, countries are heterogeneous in their economic development, including their inflation rates. This paper combines a New Keynesian model and a neural network to assess whether the European Central Bank (ECB) conducted monetary policy between 2002 and 2022 according to the weighted average of the inflation rates within the European Monetary Union (EMU) or reacted more strongly to the inflation rate developments of certain EMU countries.
The New Keynesian model first generates data which is used to train and evaluate several machine learning algorithms. They authors find that a neural network performs best out-of-sample. They use this algorithm to generally classify historical EMU data, and to determine the exact weight on the inflation rate of EMU members in each quarter of the past two decades. Their findings suggest disproportional emphasis of the ECB on the inflation rates of EMU members that exhibited high inflation rate volatility for the vast majority of the time frame considered (80%), with a median inflation weight of 67% on these countries. They show that these results stem from a tendency of the ECB to react more strongly to countries whose inflation rates exhibit greater deviations from their long-term trend.
We study the redistributive effects of inflation combining administrative bank data with an information provision experiment during an episode of historic inflation. On average, households are well-informed about prevailing inflation and are concerned about its impact on their wealth; yet, while many households know about inflation eroding nominal assets, most are unaware of nominal-debt erosion. Once they receive information on the debt-erosion channel, households update upwards their beliefs about nominal debt and their own real net wealth. These changes in beliefs causally affect actual consumption and hypothetical debt decisions. Our findings suggest that real wealth mediates the sensitivity of consumption to inflation once households are aware of the wealth effects of inflation.
As of today, estimating interest rate reaction functions for the Euro Area is hampered by the short time span since the conduct of a single monetary policy. In this paper we circumvent the common use of aggregated data before 1999 by estimating interest rate reaction functions based on a panel including actual EMU Member States. We find that exploiting the cross-section dimen- sion of a multi-country panel and accounting for cross-country heterogeneity in advance of the single monetary policy pays off with regard to the estimated reaction functions' ability to describe actual interest rate dynamics. We retrieve a panel reaction function which is demonstrated to be a valuable tool for evaluating episodes of monetary policy since 1999. JEL - Klassifikation: E43 , E58 , C33
The complexity resulting from intertwined uncertainties regarding model misspecification and mismeasurement of the state of the economy defines the monetary policy landscape. Using the euro area as laboratory this paper explores the design of robust policy guides aiming to maintain stability in the economy while recognizing this complexity. We document substantial output gap mismeasurement and make use of a new model data base to capture the evolution of model specification. A simple interest rate rule is employed to interpret ECB policy since 1999. An evaluation of alternative policy rules across 11 models of the euro area confirms the fragility of policy analysis optimized for any specific model and shows the merits of model averaging in policy design. Interestingly, a simple difference rule with the same coefficients on inflation and output growth as the one used to interpret ECB policy is quite robust as long as it responds to current outcomes of these variables.