Data Uncertainty and the Role of Money as an Information Variable for Monetary Policy

By Guenter Coenen, Andrew T. Levin, Volker Wieland. Social Science Research Network, 2005

204 citations recorded by the source corpus.

In this study, we perform a quantitative assessment of the role of money as an indicator variable for monetary policy in the euro area. We document the magnitude of revisions to euro area-wide data on output, prices, and money, and find that monetary aggregates have a potentially significant role in providing information about current real output. We then proceed to analyze the information content of money in a forward-looking model in which monetary policy is optimally determined subject to incomplete information about the true state of the economy. We show that monetary aggregates may have substantial information content in an environment with high variability of output measurement errors, low variability of money demand shocks, and a strong contemporaneous linkage between money demand and real output. As a practical matter, however, we conclude that money has fairly limited information content as an indicator of contemporaneous aggregate demand in the euro area.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/fc480cec229c06c9b3ea606506ef6eb31ace3adb

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Citations in the corpus

Introducing the Euro-STING: Short Term INdicator of Euro Area Growth (2010, unknown): “vjt = cj1vjt 1 + :::+ cjm3vjt m3 + vj t ; (10)”
Putting "M" Back in Monetary Policy (2003, unknown): “…but it does have observations on the money stock, then money may help the Fed infer current values of the variables it cares about directly.3 Coenen, Levin, and Wieland (2001) show that when output and price data are measured with error and subject to revision, money can help to predict…”
Using Taylor Rules to Understand European Central Bank Monetary Policy (2007, background): “In accordance with Coenen et al. (2002), one way to solve this problem is to take real-time data from the ECB Monthly Bulletin statistics for the HICP and industrial production.”
Central Bank Misperceptions and the Role of Money in Interest Rate Rules (2008, background): “This information role of monetary ggregates is investigated by Coenen et al. (2005).”
Using Taylor Rules to Understand ECB Monetary Policy (2003, methodology): “In accordance with Coenen et al. (2002), one way to solve this problem is to take real- time data from the ECB’s Monthly Bulletin statistics for the HICP and industrial production.”
Markov-switching dynamic factor models in real time (2018, unknown): “y T+1=T = 1 1 3 h (i;j) T+1jT (1) + 2 3 h (i;j) T+1jT (2) + h (i;j) T+1jT (3) + 2 3 h (i;j) T+1jT (4) + 1 3 h (i;j) T+1jT (5) + 1 3 h (i;j) T+1jT (13) + 2 3 h (i;j) T+1jT (14) + h (i;j) T+1jT (15) + 2 3 h (i;j) T+1jT (16) + 1 3 h (i;j) T+1jT (17) ; (43) It is worth noting that including a missing ob”
How the ECB and the US Fed set interest rates (2007, background): “This may reflect the leading indicator properties of money growth both for inflation (Altimari, 2001) and for the output gap (Coenen et al., 2001).”
Imperfect Information, Real‐Time Data and Monetary Policy in the Euro Area (2012, unknown): “This result has been recently emphasised by Collard and Dellas (2010), who show that the assumption of imperfect information introduces per se a source of endogenous persistence that enhances the empirical fit of estimated small-scale New Keynesian models.”