Learning and Shifts in Long-Run Growth

Shifts in the long-run rate of productivity growth--such as those those experienced by the U.S. economy in the 1970s and 1990s--are difficult in real time to distinguish from transitory fluctuations. In this paper, we explore how economists' projections of trend productivity growth gradually evolved during the 1970s and 1990s, and examine the consequences of such real-time learning on the dynamic responses to shifts in trend growth in the context of a dynamic stochastic general equilibrium model. We find that a simple updating rule based on an estimated Kalman filter model using real-time data describes the evolution of economists' long-run growth expectations extremely well. We then show that incorporating learning in this fashion has profound implications for the dynamic effects of shifts in trend productivity growth, whether they are concentrated in the investment-goods sector or affect the entire economy. If immediately recognized, increases in the trend growth rate cause long-term interest rates to rise and produce a sharp decline in employment and investment. In contrast, with learning, a productivity acceleration sets off a sustained boom in employment and investment, and long-term interest rates rise only gradually in a pattern consistent with the experience of the 1990sKalman filter, real-time data, signal extraction

The role of forecasts in monetary policy

Forecasts of future economic developments play an important role for the monetary policy decisions of central banks. For example, forecasts of goal variables can help central banks achieve their goals and make them more accountable to the public. There are two primary explanations for the benefits of forecasts. The first is that monetary policy affects goal variables such as inflation and output only with substantial lags. Policy actions should, therefore, be based on forecasts of goal variables at horizons consistent with policy lags and be taken when these forecasts are inconsistent with policy goals. Under such an approach, the quality of a central bank's forecasts and the effectiveness of its actions to bring forecasts into alignment with targets provide a basis for judging the performance of policymakers and for holding them accountable.> The second, and less intuitive, explanation is that by focusing on a forecast of only one variable -- inflation -- a central bank can potentially achieve multiple goals. This approach can be successful even if there are tradeoffs among the various goal variables. For example, the approach can combine a commitment to long-run price stability with concern for the effects of monetary policy on output.> Amato and Laubach argue that the lagged effects of monetary policy make the use of forecasts necessary. They also argue that delegating a single goal—such as inflation stabilization—to the central bank facilitates accountability, but at the risk of not achieving other goals. They then examine how the Eurosystem and the Bank of England, both of which have been assigned a single goal, address the existence of tradeoffs among goals. Finally, the authors provide evidence that a monetary policy aimed primarily at stabilizing inflation forecasts—as practiced by the Bank of England, for example—can, in fact, achieve multiple goals.Forecasting ; Monetary policy ; Banks and banking, Central

The value of interest rate smoothing : how the private sector helps the Federal Reserve

Most central banks conduct monetary policy by setting targets for overnight interest rates. During the 1990s, central banks have tended to move these interest rates in small steps without reversing direction quickly, a practice called interest rate smoothing. For example, the majority of Federal Reserve policy moves in the last decade and a half have come in a sequence of 25 basis point moves, in striking contrast to the early 1980s, when short-term interest rates fluctuated widely. In light of this historical contrast, it is natural to ask whether interest rate smoothing is a desirable way to conduct monetary policy.> Amato and Laubach argue that interest rate smoothing is beneficial because the private sector is forward-looking. The private sector bases its decisions on expectations of the future. Thus, a monetary policy move today will be more effective if it is expected to persist over time. By smoothing interest rates, the size of changes in interest rates required to reduce fluctuations in the economy can be smaller than would otherwise be necessary.Monetary policy ; Interest rates ; Monetary policy - United States

Long-run growth expectations and "global imbalances" : [January 5, 2011]

This paper examines to what extent the build-up of "global imbalances" since the mid-1990s can be explained in a purely real open-economy DSGE model in which agents’ perceptions of long-run growth are based on filtering observed changes in productivity. We show that long-run growth estimates based on filtering U.S. productivity data comove strongly with long-horizon survey expectations. By simulating the model in which agents filter data on U.S. productivity growth, we closely match the U.S. current account evolution. Moreover, with household preferences that control the wealth effect on labor supply, we can generate output movements in line with the data. JEL Classification: E13, E32, D83, O4

Long-run growth expectations and 'global imbalances'

This paper examines to what extent the build-up of 'global imbalances' since the mid-1990s can be explained in a purely real open-economy DSGE model in which agents' perceptions of long-run growth are based on filtering observed changes in productivity. We show that long-run growth estimates based on filtering U.S. productivity data comove strongly with long-horizon survey expectations. By simulating the model in which agents filter data on U.S. productivity growth, we closely match the U.S. current account evolution. Moreover, with household preferences that control the wealth effect on labor supply, we can generate output movements in line with the data. --open economy DSGE models,trend growth,Kalman filter,real-time data,news and business cycles,current account

Three-band Hubbard model for Na2_2IrO3_3: Topological insulator, zigzag antiferromagnet, and Kitaev-Heisenberg material

Na$_2$IrO$_3$ was one of the first materials proposed to feature the Kane-Mele type topological insulator phase. Contemporaneously it was claimed that the very same material is in a Mott insulating phase which is described by the Kitaev-Heisenberg (KH) model. First experiments indeed revealed Mott insulating behavior in conjunction with antiferromagnetic long-range order. Further refined experiments established antiferromagnetic order of zigzag type which is not captured by the KH model. Since then several extensions and modifications of the KH model were proposed in order to describe the experimental findings. Here we suggest that adding charge fluctuations to the KH model represents an alternative explanation of zigzag antiferromagnetism. Moreover, a phenomenological three-band Hubbard model unifies all the pieces of the puzzle: topological insulator physics for weak and KH model for strong electron-electron interactions as well as a zigzag antiferromagnet at intermediate interaction strength.Comment: 5 pages, 3 figures; v2 (as published): added discussion about kinetic energy scale C; more realistic values of C shift the zigzag AFM phase to larger values of

Evaluating the Feasibility of Practice Change: The Use of the PHQ-2 in the Urgent Care Setting

Adolescents in the United States may go unscreened for mental health disorders, such as depression, despite current recommendations. This population has an increased use of urgent care clinics (UCC) for their acute and primary care needs, where they might not be screened for depression at regular intervals. This project looked at determining the feasibility of implementing a two-question depression screener in the urgent care setting – the PHQ-2. Additional aims were to increase screening rates and to determine barriers to screening. Healthcare providers at a pediatric urgent care setting used the PHQ-2 to screen all adolescent patients over a two-week period. Data from a retrospective chart review showed an increase in overall screening rates and identification rates of depression in this population. Barriers to screening included wait time, confusion, patient saturation, and decreased care for acute complaint. Data from the post intervention questionnaire showed that further research will be needed in order to determine the feasibility of implementing the PHQ-2 in the UCC setting

Assoziationen zwischen exekutivem Funktionieren und dem Volumen der kortikalen grauen Substanz bei Älteren

Introduction: Preserved executive functioning (EF) promotes superior daily functioning in the elderly and protects against dementia development. In this study, we sought to clarify the role of atrophy-corrected cortical grey matter (GM) volume as a potential brain reserve (BR) marker for EF in the elderly. Methods: In total, 206 pre-surgical subjects without any evidence for neuropsychiatric disorders (72.50 ± 4.95 years; mean MMSE score 28.50) from the BioCog cohort study (www.biocog.eu) were investigated. EF was assessed with Trail Making Test B (TMT B). Global/lobar GM volumes were acquired with T1 MP-RAGE using a 3.0 Tesla Siemens scanner with a 32-channel headcoil. The brain imaging software package FreeSurfer was used to quantify GM volumes of the frontal, temporal, occipital and parietal brain lobes. Adjusting for key covariates including a brain atrophy index, multiple regression analysis was used to study associations of MRI markers and TMT B. Results: All lobar/global GM volumes significantly predicted the TMT B score independently of brain atrophy (ß = −0.201 to −0.275, p = 0.001–0.012). Atrophy-corrected global GM volume was the most accurate predictor (ß = −0.275, p=0.001). Conclusion: Our results indicate that atrophy-corrected GM volume as an archaeological estimate of maximal GM size in youth may serve as a future BR predictor for cognitive decline in the elderly.Einleitung: Um im Alter einen normalen Tagesablauf gewährleisten zu können, ist vor allem der Erhalt exekutiver Funktionen (EF) grundlegend; diese scheinen zudem dementielle Entwicklungen vorhersagen zu können. Wir untersuchten die Assoziation zwischen atrophie-korrigierter grauer Substanz (GS), als Reserve für Gehirnkapazität, und dem Aufrechterhalten von EF im Alter. Material und Methoden: Insgesamt wurden 206 präoperative Probanden ohne Anhalt für das Vorliegen neuropsychiatrischer Erkrankungen (72.50 ± 4.95 Jahre; durchschnittlicher MMSE Wert 28.50) im Rahmen der BioCog Kohortstudie (www.biocog.eu) untersucht. EF wurde primär beurteilt durch die Anwendung des Trail Making Test B (TMT B). Ein 3.0 Tesla Siemens Scanner mit einer 32-Kanal Kopfspule wurde zur Akquisition von T1 MP-RAGE Daten genutzt. Zur Bestimmung des globalen Volumens sowie der Volumina der GS der einzelnen Hirnlappen wurde die Software FreeSurfer angewendet. Mittels multipler linearer Regressionsanalysen, mit Korrektur für entscheidende Kovariaten, einschließlich eines Index für Hirnatrophie (Anteil von Hirnparenchym am intrakraniellen Volumen), wurden Volumina der GS mit dem TMT B assoziiert. Ergebnisse: Alle Volumina der GS, insbesondere das Volumen der globalen GS, waren, unabhängig von der vorliegenden Hirnatrophie, signifikant mit dem TMT B assoziiert (ß = −0.201 bis −0.275, p = 0.001–0.012). Schlussfolgerung: In künftigen Studien zur morphologischen Reservekapazität bei Älteren könnte das atrophie-korrigierte Volumen der GS, als eine Schätzung des maximalen Umfangs der GS in der Jugend, herangezogen werden und als Prädiktor für den Rückgang des kognitiven Vermögens dienen