E58 Central Banks and Their Policies
Expectation Shocks and Learning as Drivers of the Business Cycle
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EABCN/CEPR Discussion Paper 52/2010
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Date published:
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March 9, 2010
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Abstract:
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Psychological factors, market sentiments, and shifts in beliefs are believed by many to play a nontrivial role in inducing and amplifying economic fluctuations. Yet, these forces are rarely considered in macroeconomic models. This paper provides an attempt to evaluate the empirical role of expectational shocks on business cycle fluctuations. The paper relaxes the conventional assumption of rational expectations to exploit observed data on survey and market expectations in the estimation of a benchmark New Keynesian model. The observed expectations are modeled as formed from a near-rational
expectation formation mechanism, which assumes that economic agents use a linear perceived law of motion for economic variables that has the same structural form as the model solution under rational expectations and that they need to learn model coefficients over time. In addition to the typical structural demand, supply, and policy disturbances, the model incorporates expectation shocks, which affect the formation of expectations by the private sector. Both the best-fitting learning process and the expectations shocks are identified from the expectations data and from the interaction between expectations and realized data. The expectations shocks capture waves of optimism and pessimism that lead agents to form forecasts that deviate from those implied by their learning model and by the state of the economy. The empirical results uncover a crucial role for these novel expectations shocks as a major driving force of the U.S. business cycle. Expectation shocks regarding future real activity are the main source of economic fluctuations, since they can account for roughly half of business cycle fluctuations.
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An Area-Wide Real-Time Database for the Euro Area
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EABCN/CEPR Discussion Paper 50/2010
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January 21, 2010
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This paper describes how we constructed a real-time database for the euro area covering more than 200 series regularly published in the European Central Bank Monthly Bulletin, as made available ahead of publication to the Governing Council members before their first meeting of the month. We describe the database in details and study the properties of the euro area realtime data flow and data revisions, also providing comparisons with the United States and Japan. We finally illustrate how such revisions can contribute to the uncertainty surrounding key macroeconomic ratios and the NAIRU.
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A Defence of the FOMC
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EABCN/CEPR Discussion Paper 47/2009
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Date published:
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October 1, 2009
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We defend the forecasting performance of the FOMC from the recent criticism of Christina and David Romer. Our argument is that the FOMC forecasts a
worst-case scenario that it uses to design decisions that will work well enough (are robust) despite possible misspecification of its model. Because these
FOMC forecasts are not predictions of what the FOMC expects to occur under its model, it is inappropriate to compare their performance in a horse race
against other forecasts. Our interpretation of the FOMC as a robust policymaker can explain all the findings of the Romers and rationalises differences between FOMC forecasts and forecasts published in the Greenbook by the staff of the Federal Reserve System.
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Nowcasting, Business Cycle Dating and the Interpretation of New Information when Real-Time Data are Available
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EABCN/CEPR Discussion Paper 44/2009
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Date published:
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September 1, 2009
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A canonical model is described which reflects the real-time informational context of decision-making. Comparisons are drawn with ‘conventional’ models that incorrectly omit market-informed insights on future macroeconomic conditions and inappropriately incorporate information that was not available at the time. It is argued that conventional models are misspecified and misinterpret news but that these deficiencies will not be exposed either by diagnostic tests applied to the conventional models or by typical impulse response analyses. This is demonstrated through an analysis of quarterly US data 1968q4-2008q4. However, estimated real-time models considerably improve out-ofsample forecasting performance, provide more accurate ‘nowcasts’ of the current state of the macroeconomy and provide more timely indicators of the business cycle. The point is illustrated through an analysis of the US recessions of 1990q3-1991q2 and 2001q1-2001q4 and the most recent experiences of 2008.
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