Съдържанието не е налично на български език.
Günter W. Beck
- 22 April 2024
- WORKING PAPER SERIES - No. 2930Details
- Abstract
- We study how millions of granular and weekly household scanner data combined with machine learning can help to improve the real-time nowcast of German inflation. Our nowcasting exercise targets three hierarchy levels of inflation: individual products, product groups, and headline inflation. At the individual product level, we construct a large set of weekly scanner-based price indices that closely match their official counterparts, such as butter and coffee beans. Within a mixed-frequency setup, these indices significantly improve inflation nowcasts already after the first seven days of a month. For nowcasting product groups such as processed and unprocessed food, we apply shrinkage estimators to exploit the large set of scanner-based price indices, resulting in substantial predictive gains over autoregressive time series models. Finally, by adding high-frequency information on energy and travel services, we construct competitive nowcasting models for headline inflation that are on par with, or even outperform, survey-based inflation expectations.
- JEL Code
- E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
C55 : Mathematical and Quantitative Methods→Econometric Modeling→Modeling with Large Data Sets?
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods - Network
- Price-setting Microdata Analysis Network (PRISMA)
- 2 May 2011
- WORKING PAPER SERIES - No. 1334Details
- Abstract
- We use a novel disaggregate sectoral euro area data set with a regional breakdown to investigate price changes and suggest a new method to extract factors from over-lapping data blocks. This allows us to separately estimate aggregate, sectoral, country-specific and regional components of price changes. We thereby provide an improved estimate of the sectoral factor in comparison with previous literature, which decomposes price changes into an aggregate and idiosyncratic component only, and interprets the latter as sectoral. We find that the sectoral component explains much less of the variation in sectoral regional inflation rates and exhibits much less volatility than previous findings for the US indicate. We further contribute to the literature on price setting by providing evidence that country- and region-specific factors play an important role in addition to the sector-specific factors. We conclude that sectoral price changes have a “geographical” dimension, that leads to new insights regarding the properties of sectoral price changes.
- JEL Code
- E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
C38 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Classification Methods, Cluster Analysis, Principal Components, Factor Models
D4 : Microeconomics→Market Structure and Pricing
F4 : International Economics→Macroeconomic Aspects of International Trade and Finance
- 20 May 2010
- WORKING PAPER SERIES - No. 1191Details
- Abstract
- In the New-Keynesian model, optimal interest rate policy under uncertainty is formulated without reference to monetary aggregates as long as certain standard assumptions on the distributions of unobservables are satisfied. The model has been criticized for failing to explain common trends in money growth and inflation, and that therefore money should be used as a cross-check in policy formulation (see Lucas (2007)). We show that the New-Keynesian model can explain such trends if one allows for the possibility of persistent central bank misperceptions. Such misperceptions motivate the search for policies that include additional robustness checks. In earlier work, we proposed an interest rate rule that is near-optimal in normal times but includes a cross-check with monetary information. In case of unusual monetary trends, interest rates are adjusted. In this paper, we show in detail how to derive the appropriate magnitude of the interest rate adjustment following a significant cross-check with monetary information, when the New-Keynesian model is the central bank’s preferred model. The cross-check is shown to be effective in offsetting persistent deviations of inflation due to central bank misperceptions.
- JEL Code
- E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E41 : Macroeconomics and Monetary Economics→Money and Interest Rates→Demand for Money
E43 : Macroeconomics and Monetary Economics→Money and Interest Rates→Interest Rates: Determination, Term Structure, and Effects
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
- 17 November 2008
- WORKING PAPER SERIES - No. 967Details
- Abstract
- Research with Keynesian-style models has emphasized the importance of the output gap for policies aimed at controlling inflation while declaring monetary aggregates largely irrelevant. Critics, however, have argued that these models need to be modified to account for observed money growth and inflation trends, and that monetary trends may serve as a useful cross-check for monetary policy. We identify an important source of monetary trends in form of persistent central bank misperceptions regarding potential output. Simulations with historical output gap estimates indicate that such misperceptions may induce persistent errors in monetary policy and sustained trends in money growth and inflation. If interest rate prescriptions derived from Keynesian-style models are augmented with a cross-check against money-based estimates of trend inflation, inflation control is improved substantially.
- JEL Code
- E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E41 : Macroeconomics and Monetary Economics→Money and Interest Rates→Demand for Money
E43 : Macroeconomics and Monetary Economics→Money and Interest Rates→Interest Rates: Determination, Term Structure, and Effects
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
- 13 October 2006
- WORKING PAPER SERIES - No. 681Details
- Abstract
- We investigate co-movements and heterogeneity in inflation dynamics of different regions within and across euro area countries using a novel disaggregate dataset to improve the understanding of inflation differentials in the European Monetary Union. We employ a model where regional inflation dynamics are explained by common euro area and country specific factors as well as an idiosyncratic regional component. Our findings indicate a substantial common area wide component, that can be related to the common monetary policy in the euro area and to external developments, in particular exchange rate movements and changes in oil prices. The effects of the area wide factors differ across regions, however. We relate these differences to structural economic characteristics of the various regions. We also find a substantial national component. Our findings do not differ substantially before and after the formal introduction of the euro in 1999, suggesting that convergence has largely taken place before the mid 90s. Analysing US regional inflation developments yields similar results regarding the relevance of common US factors. Finally, we find that disaggregate regional inflation information, as summarised by the area wide factors, is important in explaining aggregate euro area and US inflation rates, even after conditioning on macroeconomic variables. Therefore, monitoring regional inflation rates within euro area countries can enhance the monetary policy maker's understanding of aggregate area wide inflation dynamics.
- JEL Code
- E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models