Essays in dynamic macroeconometrics
- Autores: Tatjana Dahlhaus
- Directores de la Tesis: Luca Gambetti (dir. tes.)
- Lectura: En la Universitat Autònoma de Barcelona ( España ) en 2013
- Idioma: inglés
- Tribunal Calificador de la Tesis: Gabriel Pérez-Quirós (presid.), Máximo Camacho (secret.), Kristoffer Nimark (voc.)
- Materias:
- Enlaces
- Tesis en acceso abierto en: TESEO
- Resumen
This dissertation, titled "Essays in Dynamic Macroeconometrics", is comprised of three essays and analyzes macroeconomic dynamics from an empirical perspective.
The first chapter, titled "Technology Shocks and Hours Worked: New Evidence from a Structural Factor Model" studies the effects of technology shocks on hours worked. So far, the analysis has been exclusively conducted using Structural Vector Autoregression (SVAR) models and the results obtained differ strongly depending on the specification for hours worked. In levels, the hours worked increase; in growth rates, the hours fall. Here a different approach is taken. The effects on hours are estimated using a structural dynamic factor model. The analysis is performed with a data set containing 102 quarterly U.S. macroeconomic time series over the period 1959Q1-2007Q4. In line with former VAR analysis, the technology shock is identified assuming that it is the only shock having a permanent effect on the level of labor productivity. The main result is that a positive technology shock increases hours worked in the medium and long run while having no effect on impact. The finding is in contrast with that obtained in SVAR models with hours in growth rates since there the response is negative. The difference is attributable to the fact that the technology shock is nonfundamental for the growth rates of labor productivity and hours, implying that a VAR model with a finite number of lags cannot be used to recover the technology shock.
The second chapter of this dissertation, titled "The Determinants of Credit-less Recoveries" is written together with my co-author Martin Bijsterbosch and aims to shed light on the characteristics and particularly the determinants of credit-less recoveries. After building a dataset and documenting some stylized facts of credit-less recoveries in emerging market economies, this analysis uses panel probit models to study key determinants of credit-less recoveries. Our main findings are the following: first, our frequency analysis confirms earlier findings that credit-less recoveries are not at all rare events. Moreover, our analysis shows that the frequency of credit-less recoveries doubles after a banking or currency crisis. Second, results from estimated panel probit models suggest that credit-less recoveries are typically preceded by large declines in economic activity and financial stress, in particular if private sector indebtedness is high and the country is reliant on foreign capital inflows. Finally, we find that the predicted probability of a credit-less recovery in central and eastern European EU Member States during the coming years varies across countries, but is relatively high in the Baltic States.
Finally, the third chapter, titled "Monetary Policy Transmission during Financial Crises: An Empirical Approach" aims to answer the question of whether the transmission of monetary policy in the United States has been different during the financial crises of the last forty years. In particular, I analyze the effects of a monetary policy expansion, i.e., a decrease in the Federal Funds rate, in times of high financial stress and in good or "normal" times. As the question at hand demands a non-linear environment, the analysis is carried out by introducing a Smooth Transition Factor Model (STFM). In this model the transition between states ("normal" times and financial crises) depends on a financial condition index summarizing information from financial markets. The STFM is estimated using Bayesian MCMC methods. Employing a quarterly dataset over the period 1970Q1-2009Q2 containing 108 U.S. macroeconomic and financial time series I find that a monetary expansion has stronger and more persistent effects on macroeconomic variables such as output, consumption and investment during financial crises than during "normal" times. Differences in effects among the regimes seem to originate from non-linearities in the credit channel.
