Central bank independence and the monetary instrument problem

We study the monetary instrument problem in a model of optimal discretionary fiscal and monetary policy. The policy problem is cast as a dynamic game between the central bank, the fiscal authority, and the private sector. We show that, as long as there is a conflict of interest between the two policy-makers, the central bank's monetary instrument choice critically affects the Markov-perfect Nash equilibrium of this game. Focusing on a scenario where the fiscal authority is impatient relative to the monetary authority, we show that the equilibrium allocation is typically characterized by a public spending bias if the central bank uses the nominal money supply as its instrument. If it uses instead the nominal interest rate, the central bank can prevent distortions due to fiscal impatience and implement the same equilibrium allocation that would obtain under cooperation of two benevolent policy authorities. Despite this property, the welfare-maximizing choice of instrument depends on the economic environment under consideration. In particular, the money growth instrument is to be preferred whenever fiscal impatience has positive welfare effects, which is easily possible under lack of commitment

Optimal Fiscal and Monetary Policy Without Commitment

This paper studies optimal fiscal and monetary policy in a stochastic economy with imperfectly competitive product markets and a discretionary government. We find that, in the flexible price economy, optimal time-consistent policy implements the Friedman rule independently of the degree of imperfect competition. This result is in contrast to the Ramsey literature, where the Friedman rule emerges as the optimal policy only if markets are perfectly competitive. Second, once nominal rigidities are introduced, the Friedman rule ceases to be optimal, inflation rates are low and stable, and tax rates are relatively volatile. Finally, optimal time-consistent policy under sticky prices does not generate the near-random walk behavior of taxes and real debt that can be observed under optimal policy in the Ramsey problem. A common reason for these results is that the discretionary government, in an effort to asymptotically eliminate its time-consistency problem, accumulates a large net asset position such that it can finance its expenditures via the associated interest earnings

Inflation dynamics under optimal discretionary fiscal and monetary policies

We examine the dynamic properties of inflation in a model of optimal discretionary fiscal and monetary policies. The lack of commitment and the presence of nominally risk-free debt provide the government with an incentive to implement policies which induce positive and persistent inflation rates. We show that this property obtains already in an environment with flexible prices and perfectly competitive product markets. Introducing nominal rigidities and imperfect competition has no qualitative but important quantitative implications. In particular, with a modest degree of price stickiness our model generates inflation dynamics very similar to those experienced in the U.S. since the Volcker disinflation of the early 1980s

Quantification of the resilience of primary care networks by stress testing the health care system

There are practically no quantitative tools for understanding how much stress a health care system can absorb before it loses its ability to provide care. We propose to measure the resilience of health care systems with respect to changes in the density of primary care providers. We develop a computational model on a 1-to-1 scale for a countrywide primary care sector based on patient-sharing networks. Nodes represent all primary care providers in a country; links indicate patient flows between them. The removal of providers could cause a cascade of patient displacements, as patients have to find alternative providers. The model is calibrated with nationwide data from Austria that includes almost all primary care contacts over 2 y. We assign 2 properties to every provider: the “CareRank” measures the average number of displacements caused by a provider’s removal (systemic risk) as well as the fraction of patients a provider can absorb when others default (systemic benefit). Below a critical number of providers, large-scale cascades of patient displacements occur, and no more providers can be found in a given region. We quantify regional resilience as the maximum fraction of providers that can be removed before cascading events prevent coverage for all patients within a district. We find considerable regional heterogeneity in the critical transition point from resilient to nonresilient behavior. We demonstrate that health care resilience cannot be quantified by physician density alone but must take into account how networked systems respond and restructure in response to shocks. The approach can identify systemically relevant providers

Terahertz response of patterned epitaxial graphene

We study the interaction between polarized terahertz (THz) radiation and micro-structured large-area graphene in transmission geometry. In order to efficiently couple the radiation into the two-dimensional material, a lateral periodic patterning of a closed graphene sheet by intercalation doping into stripes is chosen. We observe unequal transmittance of the radiation polarized parallel and perpendicular to the stripes. The relative contrast, partly enhanced by Fabry-Perot oscillations reaches 20 %. The effect even increases up to 50 % when removing graphene stripes in analogy to a wire grid polarizer. The polarization dependence is analyzed in a large frequency range from < 80 GHz to 3 THz, including the plasmon-polariton resonance. The results are in excellent agreement with theoretical calculations based on the electronic energy spectrum of graphene and the electrodynamics of the patterned structureThe authors thank J. Jobst for fruitful discussions. The research was performed in the framework of the Sonderforschungsbereich 953 "Synthetic carbon allotropes", funded by Deutsche Forschungsgemeinschaft. We acknowledge support from the EC under Graphene Flagship (contract no. CNECT-ICT-604391)

Modeling a Snap-Action, Variable-Delay Switch Controlling Extrinsic Cell Death

When exposed to tumor necrosis factor (TNF) or TNF-related apoptosis-inducing ligand (TRAIL), a closely related death ligand and investigational therapeutic, cells enter a protracted period of variable duration in which only upstream initiator caspases are active. A subsequent and sudden transition marks activation of the downstream effector caspases that rapidly dismantle the cell. Thus, extrinsic apoptosis is controlled by an unusual variable-delay, snap-action switch that enforces an unambiguous choice between life and death. To understand how the extrinsic apoptosis switch functions in quantitative terms, we constructed a mathematical model based on a mass-action representation of known reaction pathways. The model was trained against experimental data obtained by live-cell imaging, flow cytometry, and immunoblotting of cells perturbed by protein depletion and overexpression. The trained model accurately reproduces the behavior of normal and perturbed cells exposed to TRAIL, making it possible to study switching mechanisms in detail. Model analysis shows, and experiments confirm, that the duration of the delay prior to effector caspase activation is determined by initiator caspase-8 activity and the rates of other reactions lying immediately downstream of the TRAIL receptor. Sudden activation of effector caspases is achieved downstream by reactions involved in permeabilization of the mitochondrial membrane and relocalization of proteins such as Smac. We find that the pattern of interactions among Bcl-2 family members, the partitioning of Smac from its binding partner XIAP, and the mechanics of pore assembly are all critical for snap-action control

Comparing Signaling Networks between Normal and Transformed Hepatocytes Using Discrete Logical Models

Substantial effort in recent years has been devoted to constructing and analyzing large-scale gene and protein networks on the basis of “omic” data and literature mining. These interaction graphs provide valuable insight into the topologies of complex biological networks but are rarely context specific and cannot be used to predict the responses of cell signaling proteins to specific ligands or drugs. Conversely, traditional approaches to analyzing cell signaling are narrow in scope and cannot easily make use of network-level data. Here, we combine network analysis and functional experimentation by using a hybrid approach in which graphs are converted into simple mathematical models that can be trained against biochemical data. Specifically, we created Boolean logic models of immediate-early signaling in liver cells by training a literature-based prior knowledge network against biochemical data obtained from primary human hepatocytes and 4 hepatocellular carcinoma cell lines exposed to combinations of cytokines and small-molecule kinase inhibitors. Distinct families of models were recovered for each cell type, and these families clustered topologically into normal and diseased sets.National Institutes of Health (U.S.) (Grant GM68762)National Institutes of Health (U.S.) (Grant CA112967

Complexity, transparency and time pressure: practical insights into science communication in times of crisis

A global crisis such as the COVID-19 pandemic that started in early 2020 poses significant challenges for how research is conducted and communicated. We present four case studies from the perspective of an interdisciplinary research institution that switched to “corona-mode” during the first two months of the crisis, focussing all its capacities on COVID-19-related issues, communicating to the public directly and via media, as well as actively advising the national government. The case studies highlight the challenges posed by the increased time pressure, high demand for transparency, and communication of complexity and uncertainty. The article gives insights into how these challenges were addressed in our research institution and how science communication in general can be managed during a crisis