Identifying Monetary Policy Shocks Via Changes in Volatility
By Markku Lanne, H. Luetkepohl. Social Science Research Network, 2008
231 citations recorded by the source corpus.
A central issue of monetary policy analysis is the specification of monetary policy shocks. In a structural vector autoregressive setting there has been some controversy about which restrictions to use for identifying the shocks because standard theories do not provide enough information to fully identify monetary policy shocks. In fact, to compare different theories it would even be desirable to have over-identifying restrictions which would make statistical tests of different theories possible. It is pointed out that some progress towards overidentifying monetary policy shocks can be made by using specific data properties. In particular, it is shown that changes in the volatility of the shocks can be used for identification. Based on monthly US data from 1965-1996 different theories are tested and it is found that associating monetary policy shocks with shocks to nonborrowed reserves leads to a particularly strong rejection of the model whereas assuming that the Fed accommodates demand shocks to total reserves cannot be rejected.
Subfields: Economics and Econometrics
View Paper: https://www.semanticscholar.org/paper/5f2c075e112e4d6a5c6f5408d0f2a4550bd53a97
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Helmut Lütkepohl
- Pentti Saikkonen
- Muhammad Shahbaz
- Markku Lanne
- Katarzyna Maciejowska
- Aleksei Netsunajev
- H. Luetkepohl
- Mika Meitz
Citations in the corpus
- Panel Vector Autoregressive Models: A Survey (2013, unknown): “Domestic interdependencies have been known to produce domestic business cycle fluctuations from idiosyncratic sectoral shocks at least since Long and Plosser (1983). Spillovers from the financial sector to the real economy are key to understanding the recent global crisis (e.”
- Identification and estimation of non-Gaussian structural vector autoregressions (2015, background): “In contrast, identification by unconditional heteroskedasticity that has also been entertained in the recent SVAR literature (see, e.g., Rigobon (2003) and Lanne and Lütkepohl (2008)) is not covered.”
- Real Effects of Quantitative Easing at the Zero-Lower Bound: Structural VAR-Based Evidence from Japan (2011, background): “The particular channel that these models rely on is the portfolio rebalancing effect along the lines of Meltzer (1995, 2001) and Mishkin (2001) implying a rebalancing of investors’ portfolios following a base money injection.”
- The role of the log transformation in forecasting economic variables (2010, methodology): “, Sims and Zha (2006), Sims, Waggoner and Zha (2008), Lanne and Lütkepohl (2008)).”
- Structural Vector Autoregressions with Markov Switching (2010, methodology): “Our first example uses a small system of US macro variables from Binswanger (2004) which has also been used by Lanne and Lütkepohl (2009). The purpose of Binswanger’s analysis was to determine the impact of fundamental shocks on the stock market. The issue has been discussed previously in the litera”