<p>A five dimensional time series model which is commonly used to analyze the interaction between monetary policy and the stock market.
  <br>
  Monthly observations from 1970M1 to 2007M6:</p><table class="table">
<tr><td>q</td><td>Linearly detrended log of an industrial production index</td></tr>
<tr><td>pi</td><td>Annual change in the log of consumer prices (CPI index) (x100)</td></tr>
<tr><td>c</td><td>annual change in the log of the World Bank (non energy) commodity price index (x100)</td></tr>
<tr><td>s</td><td>Log of the real S&amp;P500 stock price index deflated by the consumer price index
    to measure the real stock prices; the series is first differenced to represent monthly returns</td></tr>
<tr><td>r</td><td>Interest rate on Federal funds</td></tr>
</table>
<p>All series, with exception of the commodity price index (c), are taken from the FRED database and transformed as in Luetkepohl &amp; Netsunajev (2017). The commodity price index comes from the World Bank. A more detailed description of the data and a corresponding VAR model implementation can be found in Luetkepohl &amp; Netsunajev (2017).</p>

Implements data-driven identification methods for structural vector autoregressive (SVAR) models as described in Lange et al. (2021) <doi:10.18637/jss.v097.i05>.
Based on an existing VAR model object (provided by e.g. VAR() from the 'vars' package), the structural
impact matrix is obtained via data-driven identification techniques (i.e. changes in volatility (Rigobon, R. (2003) <doi:10.1162/003465303772815727>),  patterns of GARCH (Normadin, M., Phaneuf, L. (2004) <doi:10.1016/j.jmoneco.2003.11.002>),
independent component analysis (Matteson, D. S, Tsay, R. S., (2013) <doi:10.1080/01621459.2016.1150851>), least dependent innovations (Herwartz, H., Ploedt, M., (2016) <doi:10.1016/j.jimonfin.2015.11.001>),
smooth transition in variances (Luetkepohl, H., Netsunajev, A. (2017) <doi:10.1016/j.jedc.2017.09.001>) or non-Gaussian maximum likelihood (Lanne, M., Meitz, M., Saikkonen, P. (2017) <doi:10.1016/j.jeconom.2016.06.002>)).

Alexander Lange

svars

Data-Driven Identification of SVAR Models

Bernhard Dalheimer

Helmut Herwartz

Simone Maxand

Hannes Riebl

LN function

<p>A <code>data.frame</code> containing 450 observations on 5 variables.</p>

Format

<p>A five dimensional time series model which is commonly used to analyze the interaction between monetary policy and the stock market.
  <br />
  Monthly observations from 1970M1 to 2007M6:</p><table class='table'>
<tr><td>q</td><td>Linearly detrended log of an industrial production index</td></tr>
<tr><td>pi</td><td>Annual change in the log of consumer prices (CPI index) (x100)</td></tr>
<tr><td>c</td><td>annual change in the log of the World Bank (non energy) commodity price index (x100)</td></tr>
<tr><td>s</td><td>Log of the real S&amp;P500 stock price index deflated by the consumer price index
    to measure the real stock prices; the series is first differenced to represent monthly returns</td></tr>
<tr><td>r</td><td>Interest rate on Federal funds</td></tr>
</table>
<p>All series, with exception of the commodity price index (c), are taken from the FRED database and transformed as in Luetkepohl &amp; Netsunajev (2017). The commodity price index comes from the World Bank. A more detailed description of the data and a corresponding VAR model implementation can be found in Luetkepohl &amp; Netsunajev (2017).</p>

State of Data and AI Literacy Report 2025

LN: Interaction between monetary policy and the stock market

Description

Usage

Arguments

Format

q	Linearly detrended log of an industrial production index
pi	Annual change in the log of consumer prices (CPI index) (x100)
c	annual change in the log of the World Bank (non energy) commodity price index (x100)
s	Log of the real S&P500 stock price index deflated by the consumer price index to measure the real stock prices; the series is first differenced to represent monthly returns
r	Interest rate on Federal funds