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We investigate the Bayesian approach to model comparison within a two-country framework with nominal rigidities using the workhorse New Keynesian open-economy model of Martínez-García and Wynne (2010). We discuss the trade-offs that monetary policy – characterized by a Taylor-type rule – faces in an interconnected world, with perfectly flexible exchange rates. We then use posterior model probabilities to evaluate the weight of evidence in support of such a model when estimated against more parsimonious specifications that either abstract from monetary frictions or assume autarky by means of controlled experiments that employ simulated data. We argue that Bayesian model comparison with posterior odds is sensitive to sample size and the choice of observable variables for estimation. We show that posterior model probabilities strongly penalize overfitting, which can lead us to favor a less parameterized model against the true data-generating process when the two become arbitrarily close to each other. We also illustrate that the spillovers from monetary policy across countries have an added confounding effect.

A systemic risk measure is proposed accounting for links and mutual dependencies between financial institutions utilizing tail event information. Financial Risk Meter (FRM) is based on least absolute shrinkage and selection operator quantile regression designed to capture tail event co-movements. The FRM focus lies on understanding active set data characteristics and the presentation of interdependencies in a network topology. Two FRM indices are presented, namely, FRM@Americas and FRM@Europe. The FRM indices detect systemic risk at selected areas and identify risk factors. In practice, FRM is applied to the return time series of selected financial institutions and macroeconomic risk factors. The authors identify companies exhibiting extreme “co-stress” as well as “activators” of stress. With the SRM@EuroArea, the authors extend to the government bond asset class, and to credit default swaps with FRM@iTraxx. FRM is a good predictor for recession probabilities, constituting the FRM-implied recession probabilities. Thereby, FRM indicates tail event behavior in a network of financial risk factors.

The efficient distribution of bank notes is a first-order responsibility of central banks. The authors study the distribution patterns of bank notes with an administrative dataset from the Bank of Canada’s Currency Inventory Management Strategy. The single note inspection procedure generates a sample of 900 million bank notes in which the authors can trace the length of the stay of a bank note in the market. The authors define the duration of the bank note circulation cycle as beginning on the date the bank note is first shipped by the Bank of Canada to a financial institution and ending when it is returned to the Bank of Canada. In addition, the authors provide information regarding where the bank note is shipped and later received, as well as the physical fitness of the bank note upon return to the Bank of Canada’s distribution centers. K–prototype clustering classifies bank notes into types. A hazard model estimates the duration of bank note circulation cycles based on their clusters and characteristics. An adaptive elastic net provides an algorithm for dimension reduction. It is found that while the distribution of the duration is affected by fitness measures, their effects are negligible when compared with the influence exerted by the clusters related to bank note denominations.

Most studies on work–life support at workplaces consider work–life balance to be a women’s issue, either explicitly or implicitly. This chapter analyses how fathers who are involved caregivers are supported or hindered in attaining work–life balance by their workplaces. It explores the following three questions: (1) why fathers value some job adaptations over others compared with mothers; (2) how organizational cultures influence the work–life balance of new fathers and (3) what differences exist across public and private sectors as well as large versus small companies. A qualitative approach with three discussion groups and 22 involved fathers enables us to explore these issues for large companies, public sector workplaces and small businesses. We find that tight time schedules, flextime, telework, schedule control and fully paid nontransferable leaves of absence constitute policies that favor involved fatherhood, while measures without wage replacement generate fear of penalization in the workplace and do not fit the persistent relevance of the provider role. In addition, un-similar supervisors, envy, lack of understanding and gender stereotypes among co-workers and clients constitute cultural barriers at the workplace level. Contrary to our expectations, small businesses may offer a better work–life balance than large companies, while the public sector is not always as family-friendly as assumed.

This chapter investigates the performance of different dimension reduction approaches for large vector autoregressions in multi-step ahead forecasts. The authors consider factor augmented VAR models using principal components and partial least squares, random subset regression, random projection, random compression, and estimation via LASSO and Bayesian VAR. The authors compare the accuracy of iterated and direct multi-step point and density forecasts. The comparison is based on macroeconomic and financial variables from the FRED-MD data base. Our findings suggest that random subspace methods and LASSO estimation deliver the most precise forecasts.

This chapter aims at shedding light upon how transforming or detrending a series can substantially impact predictions of mixed causal-noncausal (MAR) models, namely dynamic processes that depend not only on their lags but also on their leads. MAR models have been successfully implemented on commodity prices as they allow to generate nonlinear features such as locally explosive episodes (denoted here as bubbles) in a strictly stationary setting. The authors consider multiple detrending methods and investigate, using Monte Carlo simulations, to what extent they preserve the bubble patterns observed in the raw data. MAR models relies on the dynamics observed in the series alone and does not require economical background to construct a structural model, which can sometimes be intricate to specify or which may lack parsimony. The authors investigate oil prices and estimate probabilities of crashes before and during the first 2020 wave of the COVID-19 pandemic. The authors consider three different mechanical detrending methods and compare them to a detrending performed using the level of strategic petroleum reserves.

Recently, star variables and the post-crisis nature of cyclical fluctuations have attracted a great deal of interest. In this chapter, the authors investigate different methods of assessing business cycles (BCs) for the European Union in general and the euro area in particular. First, the authors conduct a Monte Carlo (MC) experiment using a broad spectrum of univariate trend-cycle decomposition methods. The simulation aims to examine the ability of the analysed methods to find the observed simulated cycle with structural properties similar to actual macroeconomic data. For the simulation, the authors used the structural model’s parameters calibrated to the euro area’s real gross domestic product (GDP) and unemployment rate. The simulation outcomes indicate the sufficient composition of the suite of models (SoM) consisting of popular Hodrick–Prescott, Christiano–Fitzgerald and structural trend-cycle-seasonal filters, then used for the real application. The authors find that: (i) there is a high level of model uncertainty in comparing the estimates; (ii) growth rate (acceleration) cycles have often the worst performances, but they could be useful as early-warning predictors of turning points in growth and BCs; and (iii) the best-performing MC approaches provide a reasonable combination as the SoM. When swings last less time and/or are smaller, it is easier to pick a good alternative method to the suite to capture the BC for real GDP. Second, the authors estimate the BCs for real GDP and unemployment data varying from 1995Q1 to 2020Q4 (GDP) or 2020Q3 (unemployment), ending up with 28 cycles per country. This analysis also confirms that the BCs of euro area members are quite synchronized with the aggregate euro area. Some major differences can be found, however, especially in the case of periphery and new member states, with the latter improving in terms of coherency after the global financial crisis. The German cycles are among the cyclical movements least synchronized with the aggregate euro area.

Drastic reductions in financial and personal support for public education over the last years in Germany seem to open gateways to ‘new’ acceptance of punishment in the realm of pedagogy. This ‘discourse’ is clandestine in theory, hidden from the public but real in institutions of the child and young people welfare system. They intensify the penalisation of their ‘drop-out’ clientele. The special schools for pupils with social, emotional and behavioural difficulties (SEBD) tend to act in that way, too. Particularly children and young people living in poverty are on the agenda of this new trend to penalise ‘deviant’ behaviour.

Programmes, trainings and drills are available. They are meant to help social workers and teacher in their position with new aims and functions. In their daily routine, most of them are overburdened and overloaded, because classes are overfilled and the number of families in the communal welfare system is growing rapidly, due to the so-called ‘Hartz IV’ legislative for unemployed families. This new trend is also a market place for the media; they launched an emergency call on education.

Some punitive praxis is contradictory to the human rights and the children rights, so that all professors for SEBD in Germany published a public declaration against the breaking up of the agreement of an education without violence. There is no empirical evidence for any positive outcome of such ‘pedagogy’. Despite all ‘modern’ promises, working with fear, anxiety, shame and punishment doesn't pay in the long run.

This chapter clarifies the relationship between socio-economic development and this ‘law and order’ pedagogy, the loss of professional standards and the psychodynamic consequences for pupils labelled as ‘deviant’.