Policy Risk and the Business Cycle

The argument that policy risk, i.e. uncertainty about monetary and fiscal policy, has been holding back the economic recovery in the U.S. during the Great Recession has a large popular appeal. We analyze the role of policy risk in explaining business cycle fluctuations by using an estimated New Keynesian model featuring policy risk as well as uncertainty about technology. We directly measure uncertainty from aggregate time series using Sequential Monte Carlo Methods. While we find considerable evidence of policy risk in the data, we show that the "pure uncertainty"-effect of policy risk is unlikely to play a major role in business cycle fluctuations. With the estimated model, output effects are relatively small due to i) dampening general equilibrium effects that imply a low amplification and ii) counteracting partial effects of uncertainty. Finally, we show that policy risk has effects that are an order of magnitude larger than the ones of uncertainty about aggregate TFP.Policy Risk; Uncertainty; Aggregate Fluctuations; Particle Filter; General Equilibrium.

Fiscal News and Macroeconomic Volatility

This paper analyzes the contribution of anticipated capital and labor tax shocks to business cycle volatility in an estimated New Keynesian DSGE model. While fiscal policy accounts for 12 to 20 percent of output variance at business cycle frequencies, the anticipated component hardly matters for explaining fluctuations of real variables. Anticipated capital tax shocks do explain a sizable part of inflation and interest rate fluctuations, accounting for between 5 and 15 percent of total variance. In line with earlier studies, news shocks in total account for 20 percent of output variance. Further decomposing this news effect, we find that it is mostly driven by stationary TFP and non-stationary investment-specific technology.Anticipated Tax Shocks; Sources of Aggregate Fluctuations; Bayesian Estimation

Fiscal News, Uncertainty, and the Business Cycle

The recent "Great Recession" has thrown macroeconomic research into a state of disarray and has clearly shown the need to go beyond traditional business cycle explanations. However, many of the recently proposed business cycle explanations rely on factors that are not directly observed by the econometrician. One promising way to deal with this issue of unobserved state variables has been the use of structural estimation. The present work contributes to the literature on non-traditional business cycle explanations by using structural macroeconomic modeling and structural estimation to analyze the role of fiscal news (Chapter 1), policy risk (Chapter 2), and terms of trade uncertainty (Chapter 3) for explaining macroeconomic fluctuations. Chapter 1 investigates the role of news about fiscal policy, and in particular the anticipation of tax rate changes, for macroeconomic fluctuations in the United States. To deal with the problem that news shocks are not observed by the econometrician, we resort to structural estimation of a New Keynesian DSGE model. We find that while fiscal policy accounts for 12 to 20 percent of output variance at business cycle frequencies, the anticipated components hardly matter for explaining fluctuations of real variables. In contrast, anticipated capital tax shocks do explain a sizable part of inflation and nominal interest rate fluctuations, accounting for 5 to 15 percent of their total variance. Consistent with earlier studies, we find that news shocks account for 20 percent of output variance, driven by news about stationary TFP and non-stationary investment-specific technology. Chapter 2 analyzes the role of policy risk in explaining business cycle fluctuations by using an estimated New Keynesian model featuring policy risk as well as uncertainty about technology. To deal with the unobserved state "uncertainty", we directly measure uncertainty from aggregate time series by structurally estimating a stochastic volatility model using Sequential Monte Carlo Methods. While we find considerable evidence of policy risk in the data, we show that the "pure uncertainty"-effect of policy risk is unlikely to play a major role in business cycle fluctuations. In the estimated model, output effects are relatively small due to i) dampening general equilibrium effects that imply a low amplification and ii) counteracting partial effects of uncertainty. Chapter 3 analyzes the effects of terms of trade uncertainty on Chilean business cycles through the lens of a small open economy DSGE model. My findings are fourfold. First, there is considerable evidence for time-varying terms of trade uncertainty in the Chilean data, with the variance of terms of trade shocks more than doubling in a short period of time. Second, I show that the ex-ante and ex-post effects of increased terms of trade uncertainty can account for about one fifth of Chilean output fluctuations at business cycle frequencies. Third, I find that a two-standard deviation terms of trade risk shock, i.e. a 54 percent increase in uncertainty, leads to a 0.1 percent drop in output. The fact that terms of trade uncertainty more than doubled during the recent commodities boom suggests that the contribution of terms of trade risk during this more recent period may have been substantial. Finally, I show that the economic mechanisms that attenuated the negative output effects of uncertainty in Chapter 2 also dampen the negative impact of terms of trade uncertainty

Different no more: Country spreads in advanced and emerging economies

Interest-rate spreads fluctuate widely across time and countries. We illustrate this on the basis of about 3,100 quarterly observations for 21 advanced and 17 emerging economies since the early 1990s. Prior to the financial crisis, spread fluctuations in advanced economies are an order of magnitude smaller than in emerging economies. After 2008 their behavior has largely converged along a number of dimensions. We also provide evidence on the transmission of spread shocks and find it similar across sample periods and country groups. The importance of spread shocks as a source of output fluctuations in advanced economies has increased after 2008

Dynare: Reference Manual Version 4

Dynare is a software platform for handling a wide class of economic models, in particular dynamic stochastic general equilibrium (DSGE) and overlapping generations (OLG) models. The models solved by Dynare include those relying on the rational expectations hypothesis, wherein agents form their expectations about the future in a way consistent with the model. But Dynare is also able to handle models where expectations are formed differently: on one extreme, models where agents perfectly anticipate the future; on the other extreme, models where agents have limited rationality or imperfect knowledge of the state of the economy and, hence, form their expectations through a learning process. Dynare offers a user-friendly and intuitive way of describing these models. It is able to perform simulations of the model given a calibration of the model parameters and is also able to estimate these parameters given a dataset. Dynare is a free software, which means that it can be downloaded free of charge, that its source code is freely available, and that it can be used for both non-profit and for-profit purposes.Dynare; Numerical methods; Perturbation; Rational expectations

Effectiveness of an Attachment-Informed Working Alliance in Interdisciplinary Pain Therapy

Attachment theory provides a useful framework for understanding individual differences inpain patients, especially with insecure attachment shown to be more prevalent in chronic pain patients compared to the general population. Nevertheless, there is little evidence of attachment-informed treatment approaches for this population. The present study compares outcomes from two different attachment-informed treatment modalities for clinicians, with outcomes from treatment as usual (TAU). In both intervention groups (IG1 and IG2), clinicians received bi-monthly training sessions on attachment. Additionally, clinicians in IG1 had access to the attachment diagnostics of their patients. All treatments lasted for four weeks and included a 6-month follow up. A total of 374 chronic pain patients were recruited to participate in this study (TAU = 159/IG1 = 163/IG2 = 52). Analyses were carried out using multilevel modeling with pain intensity as the outcome variable. Additionally, working alliance was tested as a mediator of treatment efficacy. The study was registered under the trial number DRKS00008715 on the German Clinical Trials Register (DRKS). Findings show that while IG2 was efficient in enhancing treatment outcomes, IG1 did not outperform TAU. In IG2, working alliance was a mediator of outcome. Results of the present study indicate that attachment-informed treatment of chronic pain can enhance existing interdisciplinary pain therapies; however, caveats are discussed.Fil: Pfeifer, Ann Christin. Ruprecht Karls Universitat Heidelberg.; AlemaniaFil: Meredith, Pamela. University of Queensland; AustraliaFil: Schröder Pfeifer, Paul. Ruprecht Karls Universitat Heidelberg.; AlemaniaFil: Gómez Penedo, Juan Martín. Universidad de Buenos Aires. Facultad de Psicología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Ehrenthal, Johannes. Ruprecht Karls Universitat Heidelberg.; AlemaniaFil: Schroeter, Corinna. Ruprecht Karls Universitat Heidelberg.; AlemaniaFil: Neubauer, Eva. Ruprecht Karls Universitat Heidelberg.; AlemaniaFil: Schiltenwolf, Marcus. Ruprecht Karls Universitat Heidelberg.; Alemani

Hydrazone-based boron difluoride complexes as triplet photosensitizers for singlet oxygen generation

Due to the highly selective nature of singlet oxygen as an oxidant, it has received considerable interest in various areas of (organic) chemistry. Two green light activated hydrazone-based boron difluoride triplet photosensitizers possessing high quantum yields for 1O2 formation are reported. These photostable complexes are promising in applications in synthesis and catalysis

Study protocol - efficacy of an attachment-based working alliance in the multimodal pain treatment

Background: The concept of attachment is relevant for the onset and development of chronic pain. Insecure attachment styles negatively affect therapeutic outcome. Insecurely attached patients seem to be less able to sustain positive effects of a multimodal treatment program. However, it has never been tested before if an attachment-oriented approach can improve treatment results of insecurely attached patients in a multimodal outpatient setting. To test this assumption, we compare the short- and long-term outcomes for pain patients who will receive multidisciplinary, attachment-oriented treatment with the outcomes for patients in a control group, who will receive the multidisciplinary state-of-the-art treatment. Methods: Two patient groups (baseline, attachment intervention) are assessed before treatment, after treatment, and at a 6 month follow-up. The study is conducted in a block design: After data collection of the first block (controls) and before as well as during data collection for the second block (treatment group), the health care personnel of the outpatient pain clinic receives training on attachment theory and its use in the therapeutic context. Pain intensity as measured with visual analogue scales and physical functioning will serve as the primary outcome measures. Discussion: The design of our study allows for a continuous exchange of experienced team members, which may help bring about concrete attachment related guidelines for the enhancement of therapeutic outcome. This would be the first attempt at an attachment-oriented improvement of multimodal pain programs. Conclusion: An attachment-based approach may be a promising way to enhance long-term treatment outcomes for insecurely attached pain patients. Trial registration: DRKS00008715 (registered on the 3rd of June 2015)