The Role of Money in Monetary Policy at the Lower Bound

In light of the current low-interest-rate environment, we reconsider the merits of strict money growth targeting (MGT) relative to conventional inflation targeting (IT) and to price level targeting (PLT). We evaluate these policies in terms of social welfare through the lens of a New Keynesian model and accounting for a zero lower bound (ZLB) constraint on the nominal interest rate. Although MGT makes monetary policy vulnerable to money demand shocks, MGT contributes to achieving price level stationarity and significantly reduces the incidence and severity of the ZLB relative to both IT and PLT. Furthermore, MGT lessens the need for fiscal expansions to supplement monetary policy in fighting recessions.     

Deep empirical risk minimization in finance: Looking into the future

Many modern computational approaches to classical problems in quantitative finance are formulated as empirical loss minimization (ERM), allowing direct applications of classical results from statistical machine learning. These methods, designed to directly construct the optimal feedback representation of hedging or investment decisions, are analyzed in this framework demonstrating their effectiveness as well as their susceptibility to generalization error. Use of classical techniques shows that over-training renders trained investment decisions to become anticipative, and proves overlearning for large hypothesis spaces. On the other hand, nonasymptotic estimates based on Rademacher complexity show the convergence for sufficiently large training sets. These results emphasize the importance of synthetic data generation and the appropriate calibration of complex models to market data. A numerically studied stylized example illustrates these possibilities, including the importance of problem dimension in the degree of overlearning, and the effectiveness of this approach.     

Neither market nor hierarchy—coordination costs in the allocation of track capacity in the Swedish railway network

Transaction costs have been an issue since the advent of the deregulation of the European railway markets in the 1990s. Transaction cost economics received renewed attention in research on the deregulated railway markets in the EU after the publications of two influential reports in the early 2010s. In this article, we develop a model that enables classification and measurement of transaction costs and other coordination costs in deregulated markets. This model is then used to analyze the costs of path allocation in the Swedish railway sector and to compare the results with findings in previous research. We also discuss the economic rationale of the distribution of coordination costs among the involved parties. Our key empirical findings are that the total coordination costs in the Swedish market-mimicking path allocation process are as low as or lower than the most cost-efficient market coordination processes studied in railway markets, and that the state administrations take on nearly all the coordination costs in order to minimize the effects of opportunism, rent-seeking and information impactedness. Another finding is that the size of the coordination costs found by different studies seems to be dependent on whether a bottom-up or a top-down approach is used.     

Evaluating the effectiveness of labor market interventions on reducing the impacts of the COVID-19 pandemic

This paper evaluates whether different labor market policy interventions taken in response to the COVID-19 pandemic have been effective in reducing its adverse impacts. We construct a database covering 165 countries and 39 labor market interventions grouped into four pillars: stimulating the economy and jobs (pillar 1); supporting enterprises, employment, and incomes (pillar 2); protecting workers (pillar 3); and social dialogue (pillar 4). The results revealed that measures taken under pillars 1, 2, and 3 have reduced the impacts of the pandemic on economic growth; measures under pillar 4 were significantly associated with reducing its impacts on employment and those under pillar 2 with reducing its impacts on working hours.     

How Social Structures Influence the Labour Market Participation of Individuals with Mental Illness: A Bourdieusian Perspective

Adopting a Bourdieusian perspective, this paper examines the social structures that influence the labour market participation of individuals with mental illness. We draw on 257 qualitative surveys completed by individuals with diagnosed mental health conditions in Europe, North America, Oceania, Africa, and Asia. We employed thematic analysis to analyse the data. The findings reveal that the interplay of capital endowments, symbolic violence, habitus and illusio shape the labour market participation of individuals with mental illness. Capital endowments of individuals with mental illness are afforded less value in the labour market and these individuals internalize, legitimize and normalize their disadvantaged position, blaming themselves rather than questioning the social structures leading to the challenges they encounter. We highlight that social structures condition the opinion these individuals have of themselves and how this affects how they navigate the labour market. In sum, we show that Bourdieu's concepts provide a useful lens to study inequalities in the labour market, as they reveal the social structures that produce, sustain and reinforce the social order that disadvantages individuals with mental illness.