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Jonas Dovern

27 February 2023
We propose to treat survey-based density expectations as compositional data when testing either for heterogeneity in density forecasts across different groups of agents or for changes over time. Monte Carlo simulations show that the proposed test has more power relative to both a bootstrap approach based on the KLIC and an approach which involves multiple testing for differences of individual parts of the density. In addition, the test is computaionally much faster than the KLIC-based one, which relies on simulations, and allows for comparisons across multiple groups. Using density expectations from the ECB Survey of Professional Forecasters and the U.S. Survey of Consumer Expectations, we show the usefulness of the test in detecting possible changes in density expectations over time and across different types of forecasters.
JEL Code
C12 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Hypothesis Testing: General
D84 : Microeconomics→Information, Knowledge, and Uncertainty→Expectations, Speculations
E27 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Forecasting and Simulation: Models and Applications
25 January 2017
This paper analyses the distribution of long-term inflation expectations in the euro area using individual density forecasts from the ECB Survey of Professional Forecasters. We exploit the panel dimension in this dataset to examine whether this distribution became less stable following the Great Recession, subsequent sovereign debt crisis and period when the lower bound on nominal interest rates became binding. Our results suggest that the distribution did change along several dimensions. We document a small downward shift in mean long-run expectations toward the end of our sample although they remain aligned with the ECB definition of price stability. More notably, however, we identify a trend toward a more uncertain and negatively skewed distribution with higher tail risk. Another main finding is that key features of the distribution are influenced by macroeconomic news, including the ex post historical track record of the central bank.
JEL Code
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
Task force on low inflation (LIFT)
24 August 2009
Using the Consensus Economics dataset with individual expert forecasts from G7 countries we investigate determinants of disagreement (crosssectional dispersion of forecasts) about six key economic indicators. Disagreement about real variables (GDP, consumption, investment and unemployment) has a distinct dynamic from disagreement about nominal variables (inflation and interest rate). Disagreement about real variables intensifies strongly during recessions, including the current one (by about 40 percent in terms of the interquartile range). Disagreement about nominal variables rises with their level, has fallen after 1998 or so (by 30 percent), and is considerably lower under independent central banks (by 35 percent). Cross-sectional dispersion for both groups increases with uncertainty about the underlying actual indicators, though to a lesser extent for nominal series. Country-by-country regressions for inflation and interest rates reveal that both the level of disagreement and its sensitivity to macroeconomic variables tend to be larger in Italy, Japan and the United Kingdom, where central banks became independent only around the mid-1990s. These findings suggest that more credible monetary policy can substantially contribute to anchoring of expectations about nominal variables; its effects on disagreement about real variables are moderate.
JEL Code
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
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
23 September 2008
We estimate the sticky information Phillips curve model of Mankiw and Reis (2002) using survey expectations of professional forecasters from four major European economies. Our estimates imply that inflation expectations in France, Germany and the United Kingdom are updated about once a year, in Italy about once each six months.
JEL Code
E62 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook→Fiscal Policy
H20 : Public Economics→Taxation, Subsidies, and Revenue→General
H50 : Public Economics→National Government Expenditures and Related Policies→General
H62 : Public Economics→National Budget, Deficit, and Debt→Deficit, Surplus