Identifying Systemically Important Banks: A temporal approach for macroprudential policies

Contrary to the general belief, systemic risk does not only regard the risk posed by balance sheet relationships and interdependencies among institutions. It also features a temporal dimension related to the inappropriate responses of financial market participants to changes in risk over time. This paper proposes a method to simultaneously address the cross-sectional and the time dimension in which systemic risk materializes. The method is based on the TOPHITS algorithm. It provides three scores, namely borrowing, lending and time scores: the first two represent the systemic importance of the borrowing and the lending activity associated with each financial institution,while the third represents an empirical Early Warning Signal of the financial crisis. Our findings reveal that the identification of the time score as an indicator for an incoming market distress could be relevant to design macro prudential policies.     

Inflation projections for monetary policy decision making

Many central banks set inflation targets over the medium term and inflation projections are a key input for monetary policy decision making. In this paper, we present the procedures used by the Spanish Central Bank staff to project consumer price inflation. We also provide some illustrations of their policy uses, such as fan charts, deflation probabilities and the monitoring of inflation targets.     

Resolving Rabin’s paradox

We present a theoretical model of Rabin’s famous calibration paradox that resolves confusions in the literature and that makes it possible to identify the causes of the paradox. Using suitable experimental stimuli, we show that the paradox truly violates expected utility and that it is caused by reference dependence. Rabin already showed that utility curvature alone cannot explain his paradox. We, more strongly, do not find any contribution of utility curvature to the explanation of the paradox. We find no contribution of probability weighting either. We conclude that Rabin’s paradox underscores the importance of reference dependence.

     

SOLVING A COMBINED PART-SELECTION,MACHINE-LOADING,AND TOOL-CONFIGURATION PROBLEM IN FLEXIBLE MANUFACTURING SYSTEMS*

Loading too many or too few copies of tools may result in waste of tool magazine slots and unnecessary machine shutdowns. This is a consequence of not integrating the tool-configuration problem with other flexible manufacturing system (FMS) planning problems. Solving part-selection, machine-loading and tool-configuration problems independently may cause entire solutions to be infeasible. We propose both an approach to the explicit formulation of tool configuration problems and the simultaneous solution of part-selection, machine-loading and tool-configuration problems. We developed and solved sequentially some associated bicriteria models sequentially. We also discussed the effects of considering some secondary objectives on system performance and described the concepts of critical magazine size and critical machining time using an example problem. Unnecessary allocation and under-use of tool magazine capacity and machining time could be reduced by considering the critical magazine size and machining time. Finally, we suggest using a method based on Lagrangian relaxation for solving large size problems.     

The Impact of Learning and Labor Attrition on Worker Flexibility in Dual Resource Constrained Job Shops

This study investigates the impact of worker learning, worker flexibility, and labor attrition on the system performance of a dual resource constrained (DRC) job-shop. The effects of learning and labor attrition have not been previously addressed in DRC literature. Results from the study, consistent with previous literature, show that the greatest benefits are achieved when inter-departmental worker flexibility is incrementally introduced into the system. In addition, the learning environment, which depends on the initial processing time of jobs and the learning rates of workers, is shown to impact the acquisition of flexibility. The study also shows that the impact of labor attrition on system performance under certain shop conditions may be significant.     

Zero-inflated sum of Conway-Maxwell-Poissons (ZISCMP) regression

While excess zeros are often thought to cause data over-dispersion (i.e. when the variance exceeds the mean), this implication is not absolute. One should instead consider a flexible class of distributions that can address data dispersion along with excess zeros. This work develops a zero-inflated sum-of-Conway-Maxwell-Poissons (ZISCMP) regression as a flexible analysis tool to model count data that express significant data dispersion and contain excess zeros. This class of models contains several special case zero-inflated regressions, including zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB), zero-inflated binomial (ZIB), and the zero-inflated Conway-Maxwell-Poisson (ZICMP). Through simulated and real data examples, we demonstrate class flexibility and usefulness. We further utilize it to analyze shark species data from Australia's Great Barrier Reef to assess the environmental impact of human action on the number of various species of sharks.