Geography or skills: What explains Fed watchers’ forecast accuracy of US monetary policy?

The paper shows that there is a substantial degree of heterogeneity in forecast accuracy among Fed watchers. Based on a novel database for 268 professional forecasters since 1999, the average forecast error of FOMC decisions varies 5 to 10 basis points between the best and worst-performers across the sample. This heterogeneity is found to be related to both the skills of analysts – such as their educational and employment backgrounds – and to geography. In particular, there is evidence that forecasters located in regions which experience more idiosyncratic economic conditions perform worse in anticipating monetary policy. Moreover, systematic forecaster heterogeneity is economically important as it leads to greater financial market volatility after FOMC meetings. Finally, Fed communication may exert an influence on forecast accuracy. JEL Classification: E52, E58, G14communication, Federal Reserve, FOMC, forecast, geography, heterogeneity, monetary policy, skills, survey data, United States

Geography or skills: what explains Fed Wachters' forecast accuracy of US monetary policy?

The paper shows that there is a substantial degree of heterogeneity in the ability of Fed watchers to forecast US monetary policy decisions. Based on a novel database for 268 professional forecasters since 1999, the average forecast error of FOMC decisions varies 5 to 10 basis points between the best and worstperformers across the sample. This heterogeneity is found to be related to both the skills of analysts - such as their educational and employment backgrounds - and to geography. In particular, forecasters located in regions which experience more idiosyncratic economic conditions perform worse in anticipating monetary policy. This evidence is indicative that limited attention and heterogeneous priors are present even for anticipating important events such as monetary policy decisions. Moreover, the paper shows that such heterogeneity is economically important as it leads to greater financial market volatility after FOMC meetings. Finally, policy-makers are not impotent in influencing such heterogeneity as Fed communication is found to affect forecast accuracy significantly. --Monetary policy,forecast,Federal Reserve,FOMC,geography,skills,heterogeneity,survey data,communication,United States.

Forecasting ECB monetary policy: accuracy is (still) a matter of geography

Monetary policy in the euro area is conducted within a multi-country, multicultural, and multi-lingual context involving multiple central banking traditions. How does this heterogeneity affect the ability of economic agents to understand and to anticipate monetary policy by the ECB? Using a database of surveys of professional ECB policy forecasters in 24 countries, we find remarkable differences in forecast accuracy, and show that they are partly related to geography and clustering around informational hubs, as well as to country-specific economic conditions and traditions of independent central banking in the past. In large part this heterogeneity can be traced to differences in forecasting models. While some systematic differences between analysts have been transitional and are indicative of learning, others are more persistent. JEL Classification: E52, E58, G14ECB, forecast, geography, heterogeneity, History, monetary policy

Monetary policy in the media

Media coverage of monetary policy actions is a central channel of a central bank’s communication with the wider public, and thus an important factor for its credibility and policy effectiveness. This paper analyses the coverage which ECB monetary policy decisions receive in the print media, and the determinants of its extent and of its favorableness. We find that that the press critically discusses the ECB’s policy decisions in the context of prior market expectations and of the inflation environment, and that the media’s coverage of decisions is generally highly responsive to ECB communication – in particular its Press Conference on meeting days. However, the paper also finds clear limitations in this regard, thus underlining the critical monitoring role assumed by the media. JEL Classification: E52, E58accountability, communication, coverage, ECB, media, monetary policy, press, transparency

Altered microRNA and target gene expression related to Tetralogy of Fallot

MicroRNAs (miRNAs) play an important role in guiding development and maintaining function of the human heart. Dysregulation of miRNAs has been linked to various congenital heart diseases including Tetralogy of Fallot (TOF), which represents the most common cyanotic heart malformation in humans. Several studies have identified dysregulated miRNAs in right ventricular (RV) tissues of TOF patients. In this study, we profiled genome-wide the whole transcriptome and analyzed the relationship of miRNAs and mRNAs of RV tissues of a homogeneous group of 22 non-syndromic TOF patients. Observed profiles were compared to profiles obtained from right and left ventricular tissue of normal hearts. To reduce the commonly observed large list of predicted target genes of dysregulated miRNAs, we applied a stringent target prediction pipeline integrating probabilities for miRNA-mRNA interaction. The final list of disease-related miRNA-mRNA pairs comprises novel as well as known miRNAs including miR-1 and miR-133, which are essential to cardiac development and function by regulating KCNJ2, FBN2, SLC38A3 and TNNI1. Overall, our study provides additional insights into post-transcriptional gene regulation of malformed hearts of TOF patients

On Forging SPHINCS+^{+}-Haraka Signatures on a Fault-Tolerant Quantum Computer

SPHINCS$^{+}$ is a state-of-the-art hash based signature scheme, the security of which is either based on SHA-256, SHAKE-256 or on the Haraka hash function. In this work, we perform an in-depth analysis of how the hash functions are embedded into SPHINCS$^+$ and how the quantum pre-image resistance impacts the security of the signature scheme. Subsequently, we evaluate the cost of implementing Grover’s quantum search algorithm to find a pre-image that admits a universal forgery. In particular, we provide quantum implementations of the Haraka and SHAKE-256 hash functions in Q# and consider the efficiency of attacks in the context of fault-tolerant quantum computers. We restrict our findings to SPHINCS$^+$-128 due to the limited security margin of Haraka. Nevertheless, we present an attack that performs better, to the best of our knowledge, than previously published attacks. We can forge a SPHINCS$^+$-128-Haraka signature in about $1.5\cdot 2^{90}$ surface code cycles and $2.03\cdot 10^6$ physical qubits, translating to about $1.55\cdot 2^{101}$ logical-qubit-cycles. For SHAKE-256, the same attack requires $8.65\cdot 10^6$ qubits and $1.6\cdot 2^{84}$ cycles resulting in about $2.65\cdot 2^{99}$ logical-qubit-cycles

accuracy is (still) a matter of geography

Monetary policy in the euro area is conducted within a multi-country, multi- cultural, and multi-lingual context involving multiple central banking traditions. How does this heterogeneity affect the ability of economic agents to understand and to anticipate monetary policy by the ECB? Using a database of surveys of professional ECB policy forecasters in 24 countries, we find remarkable differences in forecast accuracy, and show that they are partly related to geography and clustering around informational hubs, as well as to country-specific economic conditions and traditions of independent central banking in the past. In large part this heterogeneity can be traced to differences in forecasting models. While some systematic differences between analysts have been transitional and are indicative of learning, others are more persistent

What explains Fed Wachters’ forecast accuracy of US monetary policy?

The paper shows that there is a substantial degree of heterogeneity in the ability of Fed watchers to forecast US monetary policy decisions. Based on a novel database for 268 professional forecasters since 1999, the average forecast error of FOMC decisions varies 5 to 10 basis points between the best and worstperformers across the sample. This heterogeneity is found to be related to both the skills of analysts – such as their educational and employment backgrounds – and to geography. In particular, forecasters located in regions which experience more idiosyncratic economic conditions perform worse in anticipating monetary policy. This evidence is indicative that limited attention and heterogeneous priors are present even for anticipating important events such as monetary policy decisions. Moreover, the paper shows that such heterogeneity is economically important as it leads to greater financial market volatility after FOMC meetings. Finally, policy-makers are not impotent in influencing such heterogeneity as Fed communication is found to affect forecast accuracy significantly