Nie je k dispozícii v slovenčine.
Boris Hofmann
- 22 July 2010
- WORKING PAPER SERIES - No. 1230Details
- Abstract
- This paper explores time variation in the dynamic effects of technology shocks on U.S. output, prices, interest rates as well as real and nominal wages. The results indicate considerable time variation in U.S. wage dynamics that can be linked to the monetary policy regime. Before and after the "Great Inflation", nominal wages moved in the same direction as the (required) adjustment of real wages, and in the opposite direction of the price response. During the "Great Inflation", technology shocks in contrast triggered wage-price spirals, moving nominal wages and prices in the same direction at longer horizons, thus counteracting the required adjustment of real wages, amplifying the ultimate repercussions on prices and hence increasing inflation volatility. Using a standard DSGE model, we show that these stylized facts, in particular the estimated magnitudes, can only be explained by assuming a high degree of wage indexation in conjunction with a weak reaction of monetary policy to inflation during the "Great Inflation", and low indexation together with aggressive inflation stabilization of monetary policy before and after this period. This means that the monetary policy regime is not only captured by the parameters of the monetary policy rule, but importantly also by the degree of wage indexation and resultant second round effects in the labor market. Accordingly, the degree of wage indexation is not structural in the sense of Lucas (1976).
- JEL Code
- C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
E24 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Employment, Unemployment, Wages, Intergenerational Income Distribution, Aggregate Human Capital
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E42 : Macroeconomics and Monetary Economics→Money and Interest Rates→Monetary Systems, Standards, Regimes, Government and the Monetary System, Payment Systems
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
- 21 April 2010
- WORKING PAPER SERIES - No. 1178Details
- Abstract
- This paper uses a factor-augmented vector autoregressive model (FAVAR) estimated on U.S. data in order to analyze monetary transmission via private sector balance sheets, credit risk spreads and asset markets in an integrated setup and to explore the role of monetary policy in the three imbalances that were observed prior to the global financial crisis: high house price inflation, strong private debt growth and low credit risk spreads. The results suggest that (i) monetary policy shocks have a highly significant and persistent effect on house prices, real estate wealth and private sector debt as well as a strong short-lived effect on risk spreads in the money and mortgage markets; (ii) monetary policy shocks have contributed discernibly, but at a late stage to the unsustainable developments in house and credit markets that were observable between 2001 and 2006; (iii) financial shocks have influenced the path of policy rates prior to the crisis, and the feedback effects of financial shocks via lower policy rates on property and credit markets are found to have probably been considerable.
- JEL Code
- E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
C3 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables
E3 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles
E43 : Macroeconomics and Monetary Economics→Money and Interest Rates→Interest Rates: Determination, Term Structure, and Effects
- 19 October 2009
- WORKING PAPER SERIES - No. 1098Details
- Abstract
- This paper conducts a comparative analysis of the performances of the forward guidance strategies adopted by the Reserve Bank of New Zealand, the Norges Bank and the Riksbank, with the aim to gauge whether forward guidance via publication of an own interest rate path enhances a central bank’s ability to steer market expectations. Two main results emerge. First, we find evidence that all three central banks have been highly predictable in their monetary policy decisions and that long-term inflation expectations have been well anchored in the three economies, irrespective of whether forward guidance involved publication of an own interest rate path or not. Second, for New Zealand, we find weak evidence that a publication of a path could potentially enhance a central bank’s leverage on the medium term structure of interest rates.
- JEL Code
- E40 : Macroeconomics and Monetary Economics→Money and Interest Rates→General
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
- 30 April 2008
- WORKING PAPER SERIES - No. 888Details
- Abstract
- This paper assesses the linkages between money, credit, house prices and economic activity in industrialised countries over the last three decades. The analysis is based on a fixed-effects panel VAR estimated using quarterly data for 17 industrialized countries spanning the period 1970-2006. The main results of the analysis are the following: (i) There is evidence of a significant multidirectional link between house prices, monetary variables and the macroeconomy. (ii) The link between house prices and monetary variables is found to be stronger over a more recent sub-sample from 1985 till 2006. (iii) The effects of shocks to money and credit are found to be stronger when house prices are booming. The last two results are, however, in general not statistically significant due to the large confidence bands of the impulse responses.
- JEL Code
- E47 : Macroeconomics and Monetary Economics→Money and Interest Rates→Forecasting and Simulation: Models and Applications
E50 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→General
R21 : Urban, Rural, Regional, Real Estate, and Transportation Economics→Household Analysis→Housing Demand
R31 : Urban, Rural, Regional, Real Estate, and Transportation Economics→Real Estate Markets, Spatial Production Analysis, and Firm Location→Housing Supply and Markets
E21 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Consumption, Saving, Wealth
E22 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Capital, Investment, Capacity
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
- 23 February 2008
- WORKING PAPER SERIES - No. 867Details
- Abstract
- This paper assesses the performance of monetary indicators as well as of a large range of economic and financial indicators in predicting euro area HICP inflation out-of-sample over the period first quarter 1999 till third quarter 2006 considering standard bivariate forecasting models, factor models, simple combination forecasts as well as trivariate two-pillar Phillips Curve forecasting models using both ex-post revised and real-time data. The results suggest that the predictive ability of money-based forecasts relative to a simple random walk benchmark model was high at medium-term forecasting horizons in the early years of EMU, but has substantially deteriorated recently. A significantly improved forecasting performance vis-à-vis the random walk can, however, be achieved based on the ECB’s internal M3 series corrected for the effects of portfolio shifts and by combining monetary and economic indicators.
- JEL Code
- E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E40 : Macroeconomics and Monetary Economics→Money and Interest Rates→General
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes