The role of financial journalists in the expectations channel of the monetary transmission mechanism

Monetary policy relies on managing the inflation expectations of the public in order to influence prices (inflation). Relying on the South African experience, we argue that most of the general public are exposed to the communication of the South African Reserve Bank (SARB) only via the media. This state of affairs is fairly typical around the globe. We explored the role and biases of the journalists in transmitting the SARB’s communications to the rationally inattentive general public. Our aim was to obtain insights about the factors that influence media articles that deal with monetary policy issues. Using interviews and qualitative content analysis, we explored the extent of the journalists’ knowledge about inflation and monetary policy, their views concerning the credibility of the SARB, the sources of information they use, and the constraints and incentives they face in writing their articles.     

Investor behaviour and reaching for yield: Evidence from the sterling corporate bond market

We provide evidence on how corporate bond investors react to a change in yields, and how this behaviour differs in times of market‐wide stress. We also investigate ‘reaching for yield’ across investor types, as well as providing insights into the structure of the corporate bond market. Using proprietary sterling corporate bond transaction data, we show that insurance companies, hedge funds and asset managers are typically net buyers when corporate bond yields rise. Dealer banks clear the market by being net sellers. However, we find evidence for this behaviour reversing in times of stress for some investors. During the 2013 ‘taper tantrum’, asset managers were net sellers of corporate bonds in response to a sharp rise in yields, potentially amplifying price changes. At the same time, dealer banks were net buyers. Finally, we provide evidence that insurers, hedge funds and asset managers tilt their portfolios towards higher risk bonds, consistent with ‘reaching for yield’ behaviour.     

The Politics of Inequality as Organised Spectacle: Why the Swiss Do Not Want to Tax the Rich

In 2015, Swiss voters had the opportunity to impose a tax on the super rich in a popular vote and thereby fund a redistributive policy. However, a large majority voted against its seemingly obvious self-interest and rejected the tax. We propose an explanation for this puzzling outcome, bridging the usually separate behavioralist and institutionalist perspectives on the politics of inequality. We start from the observation that political economy tends to neglect processes of preference formation. Theorising preferences as socially constructed, we show that interest groups played a major role in shaping the outcome of the vote. Business frames were multiplied through allied parties and the media and had a major impact on individual voting behaviour. In addition, we demonstrate that interest groups representing business interests derive the content of their communication from business’s structurally privileged position in the capitalist economy. Specifically, creating uncertainty about possible perverse effects of government policies on jobs and growth is a powerful tool to undermine popular support. Frames based on this structural power ultimately explain why the Swiss refrained from ‘soaking the rich.’     

Is bank staff interaction associated with customer saving behavior in banks?

Major changes are underway in the U.S. retail banking sector toward heavy investments in technology and fewer in personnel. Using the 2017 survey of household economics and decision‐making (SHED) (n = 11,359), we examine the relationship between saving behavior related to emergency, long‐term and periodic expenses and personal, technological, and hybrid bank account access methods. Binary logistic regression models were used to estimate the odds of reporting various saving behaviors in relation to various banking access methods. Findings suggest that the personal access method is positively associated with savings behavior for periodic expenses for the general population, and negatively associated with emergency savings in people with lower education attainment. Technology is associated with all types of saving behavior, while the hybrid access method is associated only with saving for periodic expenses. As investments in self‐service technology increase, the importance of access methods to savings behavior must be considered.     

Testing the asymmetric effects of exchange rate pass‐through in BRICS countries: Does the state of the economy matter?

This paper investigates not only the question of whether there is exchange rate pass‐through (ERPT) but also the extent to which the pass‐through is asymmetric or state‐dependent in the BRICS countries. Using monthly data from 1999:M1 to 2019:M12 and non‐linear smooth transition vector autoregressive (STVAR) model, our results provide evidence of period‐specific ERPT between the upper and lower regime periods, governed by the selected transition variables. The results further suggest that the pass‐through of exchange rate is higher when the economy is experiencing large appreciations and expansions as well as large depreciations and recessions. Theimplication for these findings is that ERPT is strongly affected by the state of the economy.     

State‐Dependent Forward Guidance and the Problem of Inconsistent Announcements

Forward guidance can be provided as an unconditional promise, i.e. commitment to a specific low policy rate. Alternatively, the promise may include an escape clause, i.e. a condition defining the state of the economy under which the central bank would not keep such a low rate and, instead, it would revert to setting policy under discretion. The escape clause can be expressed as a threshold in terms of a specific variable. The present paper shows that, when such a threshold is expressed in terms of an endogenous variable (e.g. output, inflation), there are cases where it becomes impossible for the central bank to act in a way that is consistent with its promise. Consistency imposes limits on the policy rate that can be set since reverting immediately to the optimal discretionary rate can be incompatible with exceeding the threshold.     

A Statistical Model to Investigate the Reproducibility Rate Based on Replication Experiments

The reproducibility crisis, that is, the fact that many scientific results are difficult to replicate, pointing to their unreliability or falsehood, is a hot topic in the recent scientific literature, and statistical methodologies, testing procedures and p‐values, in particular, are at the centre of the debate. Assessment of the extent of the problem–the reproducibility rate or the false discovery rate–and the role of contributing factors are still an open problem. Replication experiments, that is, systematic replications of existing results, may offer relevant information on these issues. We propose a statistical model to deal with such information, in particular to estimate the reproducibility rate and the effect of some study characteristics on its reliability. We analyse data from a recent replication experiment in psychology finding a reproducibility rate broadly coherent with other assessments from the same experiment. Our results also confirm the expected role of some contributing factor (unexpectedness of the result and room for bias) while they suggest that the similarity between original study and the replica is not so relevant, thus mitigating some criticism directed to replication experiments.     

Deep learning for modeling the collection rate for third-party buyers

This study evaluates a wide range of machine learning techniques such as deep learning, boosting, and support vector regression to predict the collection rate of more than 65,000 defaulted consumer credits from the telecommunications sector that were bought by a German third-party company. Weighted performance measures were defined based on the value of exposure at default for comparing collection rate models. The approach proposed in this paper is useful for a third-party company in managing the risk of a portfolio of defaulted credit that it purchases. The main finding is that one of the machine learning models we investigate, the deep learning model, performs significantly better out-of-sample than all other methods that can be used by an acquirer of defaulted credits based on weighted-performance measures. By using unweighted performance measures, deep learning and boosting perform similarly. Moreover, we find that using a training set with a larger proportion of the dataset does not improve prediction accuracy significantly when deep learning is used. The general conclusion is that deep learning is a potentially performance-enhancing tool for credit risk management.     

Health screening strategies for international air travelers during an epidemic or pandemic

Air travelers can carry an infectious disease's pathogenic microorganism in their bodies and spread the disease from one country to another in a few days. To delay the spread, health screening stations may be set up at airport terminals to screen travelers. This research tested three different health screening strategies, each with a different combination of screening stations at trip origins, destinations and connecting airports. Discrete event simulations were performed, based on the 2014 to 2016 Ebola virus epidemic, with special focus on travelers from the West African countries traveling to the United States, including travelers who transferred flights at airports in European Union member states. The effectiveness of the screening strategies was analyzed in terms of correct detection, missed detection and false alarm rate. The results showed that exit screening at trip origins brought big improvements in the performance measurements compared to no screening. However, additional screening at the destinations and connecting airports contributed marginal benefits.