Abstract:
The present work has the aim to analyze monetary policy shocks and stock price shocks within the US economic cycle, throughout the estimate of Vector Autoregression models (VAR).
The variables into account in our analysis are the following:
- the financial index S&P 500;
- the inflation rate;
- the real domestic product per capita;
- the interest rate.
The time series refer to the US and they were found on the Federal Reserve’s website.
All the time series analyzed are quarterly series and the observation sample goes from the first quarter of 1980 to the fourth quarter of 2019.
The reason behind the timeframe considered is that from the 1980s the US monetary policy has undergone major changes, as is known from literature (among them: Robert L. Hetzel, 2017; Judd and Rudebusch, 1998; Cogley and Sargent, 2005).
This work has two main objectives:
- understanding the effect of financial shocks on the economy (measured as inflation and domestic product per capita) and how the monetary policy reacts to this sort of shocks;
- how the economy reacts to monetary policy, that is the decisions taken by the FED to pursue its goals.
The work is articulated in the following way: the first chapter is about the Literature, addressed at first from a purely economic point of view, so as to provide useful bases for a thematic and chronological contextualization; then the tools and the models used by economists in the analysis of shocks will be briefly discussed, with particular reference to the VAR, which will be the main topic of the second chapter.
In the second chapter, as mentioned above, we will present the VAR, analyzing the literature (among them: Sims, 1980; Christiano, 2012; Stock and Watson, 2001) about the history of the model, the statistical and econometric application of the model, the fields in which it has been used overtime and the different currents of thought on the pros and cons of the model.
The fourth chapter will be divided into two sub-sessions.
The first session will be dedicated to the description of the data: an overview of each variable considered in the analysis, the source of the variables, the main economic characteristics.
In addition, the tools used to perform the analysis will be indicated: there will therefore be a further reference to VAR and will be briefly presented the programming language R, through which the model has been implemented.
In the second session there will be a first descriptive analysis of the data (TSA) and then the application of the models according to the formulas described in the chapter 3.
Finally, the results obtained will be illustrated and explained.
Chapter 5 contains the conclusions of the thesis project.
