Latviešu valodas versija nav pieejama
Haroon Mumtaz
- 4 October 2023
- WORKING PAPER SERIES - No. 2849Details
- Abstract
- In this paper, we assess how risk-sharing channels have evolved over time in the United States and the Euro Area, and whether they have operated as ‘complements’ or ‘substitutes’. In particular, we focus on the capital channel (income from cross-border ownership of productive assets), the credit channel (interstate or cross-country bank lending), and the fiscal channel (federal or international fiscal transfers). We offer three main contributions. First, we propose a time-varying parameter panel VAR model, with stochastic volatility, which allows us to formally quantify time variation in risk-sharing channels. Second, we develop a new test of the complementarity vs. substitutability hypothesis of the three risk-sharing channels, based on the correlation between the impulse responses of these channels to idiosyncratic output shocks. Third, for the United States, we explain time variation in the risk-sharing channels based on some key macroeconomic and financial variables.
- JEL Code
- C11 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Bayesian Analysis: General
C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
E21 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Consumption, Saving, Wealth
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
- 30 April 2018
- WORKING PAPER SERIES - No. 2147Details
- Abstract
- We build a dynamic factor model with time-varying parameters and stochastic volatility and use it to decompose the variance of a large set of financial and macroeconomic variables for 22 OECD countries spanning from 1960 onwards into contributions from country-specific uncertainty, region-specific uncertainty and uncertainty common to all countries. We find that common global uncertainty plays a primary role in explaining the volatility of inflation, interest rates and stock prices, although to a varying extent over time. Region-specific uncertainty drives most of the exchange rate volatility for all Euro Area countries and for countries in North-America and Oceania. All uncertainty estimates (global, regional, country-specific and idiosyncratic) play a non-negligible role for real economic activity, credit and money for most countries. We also find that all uncertainty measures display significant recurrent fluctuations, that the recent peaks in uncertainty found for most estimates around 2008/2009 are comparable to those seen in the mid-1970s and early 1980s, and that all uncertainty measures appear to be strongly countercyclical and positively correlated with inflation.
- JEL Code
- C15 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Statistical Simulation Methods: 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
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
- 7 April 2011
- WORKING PAPER SERIES - No. 1320Details
- Abstract
- This paper uses a time-varying Factor Augmented VAR to investigate the evolving transmission of monetary policy and demand shocks in the UK. Simultaneous estimation of time-varying impulse responses of a large set of macroeconomic variables and disaggregated prices suggest that the response of inflation, money supply and asset prices to monetary policy and demand shocks has changed over the sample period. In particular, during the post-1992 inflation targeting period, monetary policy shocks started having a bigger impact on prices, a smaller impact on activity and began contributing more to overall volatility. In contrast, demand shocks had the largest impact on these variables before the 1990s. We also document changes in the response of disaggregated prices, with the median reaction to contractionary policy shocks becoming more negative and the distribution more dispersed post-1992.
- JEL Code
- C38 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Classification Methods, Cluster Analysis, Principal Components, Factor Models
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
- 24 April 2007
- WORKING PAPER SERIES - No. 746Details
- Abstract
- We fit a Bayesian time-varying parameters structural VAR with stochastic volatility to the Federal Funds rate, GDP deflator inflation, real GDP growth, and the rate of growth of M2. We identify 4 shocks-monetary policy, demand non-policy, supply, and money demand-by imposing sign restrictions on the estimated reduced-form VAR on a period-by-period basis. The evolution of the monetary rule in the structural VAR accords well with narrative accounts of post-WWII U.S. economic history, with (e.g.) significant increases in the long-run coefficients on inflation and money growth around the time of the Volcker disinflation. Overall, however, our evidence points towards a dominant role played by good luck in fostering the more stable macroeconomic environment of the last two decades. First, the Great Inflation was due, to a dominant extent, to large demand non-policy shocks, and to a lower extent to supply shocks. Second, imposing either Volcker or Greenspan over the entire sample period would only have had a limited impact on the Great Inflation episode, while imposing Burns and Miller would have resulted in a counterfactual inflation path remarkably close to the actual historical one. Although the systematic component of monetary policy clearly appears to have improved over the sample period, this does not appear to have been the dominant influence in post-WWII U.S. macroeconomic dynamics.
- JEL Code
- E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E47 : Macroeconomics and Monetary Economics→Money and Interest Rates→Forecasting and Simulation: Models and Applications
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