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Author:Amstad, Marlene 

Journal Article
Do macroeconomic announcements move inflation forecasts?
This paper presents an empirical strategy that bridges the gap between event studies and macroeconomic forecasts based on common-factor models. Event studies examine the response of financial variables to a market-sensitive "surprise" component using a narrow event window. The authors argue that these features - narrow event window and surprise component - can be easily embedded in common-factor models that study the real-time impact of macroeconomic announcements on key policy variables such as inflation or gross domestic product growth. Demonstrative applications are provided for Swiss inflation that show that (i) the communication of monetary policy announcements generates an asymmetric response for inflation forecasts, (ii) the pass-through effect of import price releases on inflation forecasts is weak, and (iii) macroeconomic releases of real and nominal variables generate nonsynchronized effects for inflation forecasts.
AUTHORS: Fischer, Andreas M.; Amstad, Marlene
DATE: 2009

Journal Article
Monetary policy implementation: common goals but different practices
While the goals that guide monetary policy in different countries are very similar, central banks diverge in their methods of implementing policy. This study of the policy frameworks of four central banks?the Federal Reserve, the European Central Bank, the Bank of England, and the Swiss National Bank?focuses on two notable areas of difference. The first is the choice of an interest rate target, a standard feature of conventional monetary policy. The second is the choice of instruments for managing the central banks? expanded balance sheets?a decision made necessary by the banks? unconventional practice of acquiring large quantities of assets during the financial crisis.
AUTHORS: Amstad, Marlene; Martin, Antoine
DATE: 2011

Journal Article
The New York Fed Staff Underlying Inflation Gauge (UIG)
A measure of underlying inflation that uses all relevant information, is available in real time, and forecasts inflation better than traditional underlying inflation measures?such as core inflation measures?would greatly benefit monetary policymakers, market participants, and the public. This article presents the New York Fed Staff Underlying Inflation Gauge (UIG) for the consumer price index and the personal consumption expenditures deflator. Using a dynamic factor model approach, the UIG is derived from a broad data set that extends beyond price series to include a wide range of nominal, real, and financial variables. This modeling approach also makes it possible to combine information simultaneously from the cross-sectional and time dimensions of the sample in a unified framework. In addition, the UIG can be updated on a daily basis to closely monitor changes in underlying inflation?a feature that is especially useful when sudden and large economic fluctuations occur, as was the case during the 2008 global financial crisis. Lastly, the UIG displays greater forecast accuracy than many measures of core inflation. Editor?s note: This article?s data appendix has been updated to reflect the removal of a duplicate price series (CPI-U: Other fresh vegetables). The article?s conclusions remain the same. (December 2017)
AUTHORS: Amstad, Marlene; Potter, Simon M.; Rich, Robert W.
DATE: 2017

Report
Real time underlying inflation gauges for monetary policymakers
Central banks analyze a wide range of data to obtain better measures of underlying inflationary pressures. Factor models have widely been used to formalize this procedure. Using a dynamic factor model this paper develops a measure of underlying inflation (UIG) at time horizons of relevance for monetary policymakers for both CPI and PCE. The UIG uses a broad data set allowing for high-frequency updates on underlying inflation. The paper complements the existing literature on U.S. "core" measures by illustrating how UIG is used and interpreted in real time since late 2005.
AUTHORS: Amstad, Marlene; Potter, Simon M.
DATE: 2009

Report
The FRBNY staff underlying inflation gauge: UIG
Monetary policymakers and long-term investors would benefit greatly from a measure of underlying inflation that uses all relevant information, is available in real time, and forecasts inflation better than traditional underlying inflation measures such as core inflation measures. This paper presents the ?FRBNY Staff Underlying Inflation Gauge (UIG)? for CPI and PCE. Using a dynamic factor model approach, the UIG is derived from a broad data set that extends beyond price series to include a wide range of nominal, real, and financial variables. It also considers the specific and time-varying persistence of individual subcomponents of an inflation series. An attractive feature of the UIG is that it can be updated on a daily basis, which allows for a close monitoring of changes in underlying inflation. This capability can be very useful when large and sudden economic fluctuations occur, as at the end of 2008. In addition, the UIG displays greater forecast accuracy than traditional measures of core inflation.
AUTHORS: Amstad, Marlene; Potter, Simon M.; Rich, Robert W.
DATE: 2014-04-22

Report
Shock identification of macroeconomic forecasts based on daily panels
This paper proposes a new procedure for shock identification of macroeconomic forecasts based on factor analysis. Our identification scheme for information shocks relies on data reduction techniques for daily panels and the recognition that macroeconomic releases exhibit a high level of clustering. A large number of data releases on a single day is of considerable practical interest not only for the estimation but also for the identification of the factor model. The clustering of cross-sectional information facilitates the interpretation of the forecast innovations as real or as nominal information shocks. An empirical application is provided for Swiss inflation. We show that (i) the monetary policy shocks generate an asymmetric response to inflation, (ii) the pass-through for consumer price index inflation is weak, and (iii) the information shocks to inflation are not synchronized.
AUTHORS: Amstad, Marlene; Fischer, Andreas M.
DATE: 2005

Report
Time-varying pass-through from import prices to consumer prices: evidence from an event study with real-time data
This paper analyzes the pass-through from import prices to consumer price index (CPI) inflation in real time. Our strategy follows an event-study approach that compares inflation forecasts before and after import price releases. Inflation forecasts are modeled using a dynamic factor procedure that relies on daily panels of Swiss data. We find strong evidence that monthly import price releases provide important information for CPI inflation forecasts, and that the behavior of updated forecasts is consistent with a time-varying pass-through. The robustness of this latter result is supported by an alternative CPI measure that excludes price components subject to administered pricing as well as by panels capturing difference levels of information breadth. Finally, our empirical findings cast doubt on a prominent role for sticky prices in the low pass-through findings.
AUTHORS: Amstad, Marlene; Fischer, Andreas M.
DATE: 2005

Working Paper
Monthly pass-through ratios
This paper estimates monthly pass-through ratios from import prices to consumer prices in real time. Conventional time series methods impose restrictions to generate exogenous shocks on exchange rates or import prices when estimating pass-through coefficients. Instead, a natural experiment based on data releases defines our shock to foreign prices. Our estimation strategy follows an event-study approach based on monthly releases in import prices. Projections from a dynamic common factor model with daily panels before and after monthly releases of import prices define the shock. This information shock allows us to recover a monthly pass-through ratio. We apply our identification procedure to Swiss prices and find strong evidence that the monthly pass-through ratio is around 0.3. Our real-time estimates yield higher pass-through ratios than time series estimates.
AUTHORS: Amstad, Marlene; Fischer, Andreas M.
DATE: 2009

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