Does household debt affect the size of the fiscal multiplier? We investigate the effects of household debt on government spending multipliers using a smooth transition vector autoregression model. Through generalized impulse response functions, we measure whether the effect of government spending on GDP is conditioned by different levels of household debt in Australia, Sweden, and Norway, three countries with high levels of household indebtedness, and in the world’s seven largest economies. Our results indicate that the short-term effects of government spending tend to be higher if fiscal expansion takes place during periods of low household debt. On average, the fiscal multiplier (on impact) is 0.70, 0.61, and 0.79 (percent of GDP) larger when the increase in government spending takes place during periods of low household debt for Australia, Norway, and the United States.

Ultrafast laser pulses provide unique tools to manipulate magnetization dynamics at femtosecond timescales, where the interaction of the electric field usually dominates over the magnetic field. Recent proposals using structured laser beams have demonstrated the possibility to produce regions where intense oscillating magnetic fields are isolated from the electric field. In these conditions, we show that technologically feasible tesla-scale circularly polarized high-frequency magnetic fields induce purely precessional nonlinear magnetization dynamics. This fundamental result not only opens an avenue in the study of laser-induced ultrafast magnetization dynamics, but also sustains technological implications as a route to promote all-optical non-thermal magnetization dynamics both at shorter timescales – towards the sub-femtosecond regime – and at THz frequencies.

Flexible cables in cable-driven parallel robots (CDPRs) are easy to be excited and vibrate. Cable vibration will react on the end-effector, causing attitude deviation of the end-effector. The main objective of this study is to accurately model axially moving flexible cables and characterize the dynamic behaviors of associated compliant CDPRs. Firstly, a model for transverse vibration of the axially moving length-variable cable is developed. On this basis, an original nonlinear dynamic model of the CDPRs able to capture the vibration of the cables and the dynamics of the end-effector is proposed. Secondly, the frequency–amplitude relationship of the CDPR is obtained. Moreover, the significance of the excitation effect caused by the axially moving length-variable cables is demonstrated, by comparing the results with and without excitation effect at different frequencies. It turns out that, as the oscillation frequency of the end-effector increases, the end-effector and cables exhibit the dynamics process from steady state to unstable large-amplitude vibration and finally to stable small-amplitude vibration. This indicates that the dynamics of the CDPR exhibit non-linear characteristics, due to the influence of flexible cables. Finally, the proposed dynamic model of compliant CDPRs is validated by experiments performed in the laboratory.

We investigate structural features and processes associated with the onset of systemic conflict using an approach which integrates complex systems theory with network modeling and analysis. We present a signed network model of cooperation and conflict dynamics in the context of international relations between states. The model evolves ties between nodes under the influence of a structural balance force and a dyad-specific force. Model simulations exhibit a sharp bifurcation from peace to systemic war as structural balance pressures increase, a bistable regime in which both peace and war stable equilibria exist, and a hysteretic reverse bifurcation from war to peace. We show how the analytical expression we derive for the peace-to-war bifurcation condition implies that polarized network structure increases susceptibility to systemic war. We develop a framework for identifying patterns of relationship perturbations that are most destabilizing and apply it to the network of European great powers before World War I. We also show that the model exhibits critical slowing down, in which perturbations to the peace equilibrium take longer to decay as the system draws closer to the bifurcation. We discuss how our results relate to international relations theories on the causes and catalysts of systemic war.

In this paper, a novel statistical application of large deviation principle (LDP) to the robot trajectory tracking problem is presented. The exit probability of the trajectory from stability zone is evaluated, in the presence of small-amplitude Gaussian and Poisson noise. Afterward, the limit of the partition function for the average tracking error energy is derived by solving a fourth-order system of Euler–Lagrange equations. Stability and computational complexity of the proposed approach is investigated to show the superiority over the Lyapunov method. Finally, the proposed algorithm is validated by Monte Carlo simulations and on the commercially available Omni bundleTM robot.

Based on a behavioral stock-flow housing market model in which the expectation formation behavior of boundedly rational and heterogeneous investors may generate endogenous boom-bust cycles, we explore whether central banks can stabilize housing markets via the interest rate. Using a mix of analytical and numerical tools, we find that the ability of central banks to tame housing markets by increasing the base (target) interest rate, thereby softening the demand pressure on house prices, is rather limited. However, central banks can greatly improve the stability of housing markets by dynamically adjusting the interest rate with respect to mispricing in the housing market.

A susceptible–exposed–infectious theoretical model describing Tasmanian devil population and disease dynamics is presented and mathematically analysed using a dynamical systems approach to determine its behaviour under a range of scenarios. The steady states of the system are calculated and their stability analysed. Closed forms for the bifurcation points between these steady states are found using the rate of removal of infected individuals as a bifurcation parameter. A small-amplitude Hopf region, in which the populations oscillate in time, is shown to be present and subjected to numerical analysis. The model is then studied in detail in relation to an unfolding parameter which describes the disease latent period. The model’s behaviour is found to be biologically reasonable for Tasmanian devils and potentially applicable to other species.

The aim of this paper is to discuss the effect on returns to scale on the local determinacy properties of the steady state in a continuous-time two-sector economy with endogenous labor supply and sector-specific externalities. First we show that when labor is inelastic and the elasticity of intertemporal substitution in consumption is large enough, for any configuration of the returns to scale, local indeterminacy is obtained if there is a capital intensity reversal between the private and the social levels. Second, we prove that when labor is infinitely elastic, saddlepoint stability is obtained if the investment good sector has constant social returns, whereas local indeterminacy arises if the investment good sector has increasing social returns and the elasticity of intertemporal substitution in consumption admits intermediate values. Finally, our main conclusion shows that local indeterminacy requires a low elasticity of labor when the investment good has constant social returns, but requires either a low enough or a large enough elasticity of labor when the investment good has increasing social returns.

This paper reviews some of the literature on the macroeconomic effects of oil price shocks with a particular focus on possible nonlinearities in the relation and recent new results obtained by Kilian and Vigfusson [http://www-personal.umich/~lkilian/kvsubmission.pdf (2009)].

In order to overcome the loss of performances issue when scaling resonant sensors down toNEMS, it proves extremely useful to study the behavior of resonators up to largedisplacements and hence high nonlinearities. A comprehensive nonlinear multiphysics modelbased on the Euler-Bernoulli equation which includes both mechanical and electrostaticnonlinearities in the case of a capacitive doubly clamped beam is presented. This purelyanalytical model captures all the nonlinear phenomena present in NEMS resonatorselectrostatically actuated including bistability, multistability which can lead to severalphysical limitations such as noise mixing, frequency stability deterioration as well asdynamic pull-in. Moreover, close-form expressions of the critical amplitudes and pull-indomain initiation amplitude are provided which can potentially serve for NEMS designers asquick design rules.

Recent “connectionist” models provide a new explanatory alternative to the digital computer as a model for brain function. Evidence from our EEG research on the olfactory bulb suggests that the brain may indeed use computational mechanisms like those found in connectionist models. In the present paper we discuss our data and develop a model to describe the neural dynamics responsible for odor recognition and discrimination. The results indicate the existence of sensory- and motor-specific information in the spatial dimension of EEG activity and call for new physiological metaphors and techniques of analysis. Special emphasis is placed in our model on chaotic neural activity. We hypothesize that chaotic behavior serves as the essential ground state for the neural perceptual apparatus, and we propose a mechanism for acquiring new forms of patterned activity corresponding to new learned odors. Finally, some of the implications of our neural model for behavioral theories are briefly discussed. Our research, in concert with the connectionist work, encourages a reevaluation of explanatory models that are based only on the digital computer metaphor.

The receptive-field properties of retinal ganglion cells (RGCs) provide information about early visual processing. In the primate retina, P cells form the largest class of RGCs (Rodieck, 1988). A detailed exploration of the dynamics of the two subdivisions of the P-cell receptive field—the center and the surround—was undertaken. In the preceding paper (Benardete & Kaplan, 1996), the first-order responses of the center and the surround of P cells were described, which were obtained with a new technique, the multiple m-sequence stimulus (Benardete & Victor, 1994). In this paper, the investigation of P-cell responses measured as S-potentials in the lateral geniculate nucleus (LGN) is continued, and significant nonlinear, second-order responses from the center and the surround are described. These responses are quantified by fitting a mathematical model, the linear-nonlinear-linear (LNL) model (Korenberg, 1973; Korenberg & Hunter, 1986; Victor, 1988) to the data. In a second series of experiments, demonstration that steady illumination of the surround modifies the gain of the center to contrast signals (see also Kaplan & Shapley, 1989) is made. In P ON cells, increasing the steady illumination of the surround decreases the gain and speeds up the center's first-order response. In P OFF cells, increasing the steady illumination of the surround increases the gain of the center while speeding up the response. The results of both sets of experiments are related to the known anatomy and physiology of the P cell.

This paper presents a mathematical model of a robot with one degree of freedom and numerical investigation of its dynamics in a particular parameter scan which is close to the upper boundary of the estimates for the parameters of rigidity and friction, while the length parameter L is treated as a free control parameter. In this L-scan the quasiperiodic and frequency locked solutions, their pattern and order of appearance are studied in the interval from the parameter range of immediate engineering significance to the point of appearance of transient chaos. In particular, a fractaltype multiple splitting of Arnold tongues is found in the parameter region bordering the range of engineering significance.

In this paper we investigate the effects of herding on asset price dynamics during continuous trading. We focus on the role of interaction among traders, and we investigate the dynamics emerging when we allow for a tendency to mimic the actions of other investors, that is, to engage in herd behavior. The model, built as a mean field in a binary setting (buy/sell decisions of a risky asset), is expressed by a three-dimensional discrete dynamical system describing the evolution of the asset price, its expected price, and its excess demand. We show that such dynamical system can be reduced to a unidirectionally coupled system. In line with the rational herd behavior literature [Bikhchandani, S., Sharma, S. (2000), Herd Behavior in Financial Markets: A Review. Working paper, IMF, WP/00/48], situations of multistability are observed, characterized by strong path dependence; that is, the dynamics of the system are strongly influenced by historical accidents. We describe the different kinds of dynamic behavior observed, and we characterize the bifurcations that mark the transitions between qualitatively different time evolutions. Some situations give rise to high sensitivity with respect to small changes of the parameters and/or initial conditions, including the possibility of invest or reject cascades (i.e., sudden uncontrolled increases or crashes of the prices).

The assembly of the Paul Trap Simulator Experiment (PTSX) is now complete and experimental operations have begun. The purpose of PTSX, a compact laboratory facility, is to simulate the nonlinear dynamics of intense charged particle beam propagation over a large distance through an alternating-gradient transport system. The simulation is possible because the quadrupole electric fields of the cylindrical Paul trap exert radial forces on the charged particles that are analogous to the radial forces that a periodic focusing quadrupole magnetic field exert on the beam particles in the beam frame. By controlling the waveform applied to the walls of the trap, PTSX will explore physics issues such as beam mismatch, envelope instabilities, halo particle production, compression techniques, collective wave excitations, and beam profile effects.

This paper examines the quantitative implications of government fiscal policy in a discrete-time one-sector growth model with a productive externality that generates social increasing returns to scale. Starting from a laissez-faire economy that exhibits local indeterminacy, we show that the introduction of a constant capital tax or subsidy can lead to various forms of endogenous fluctuations, including stable 2-, 4-, 8-, and 10-cycles, quasiperiodic orbits, and chaos. In contrast, a constant labor tax or subsidy has no effect on the qualitative nature of the model's dynamics. We show that the use of local steady-state analysis to detect the presence of multiple equilibria in this class of models can be misleading. For a plausible range of capital tax rates, the log-linearized dynamical system exhibits saddle-point stability, suggesting a unique equilibrium, whereas the true nonlinear model exhibits global indeterminacy. This result implies that stabilization policies designed to suppress sunspot fluctuations near the steady state may not prevent sunspots, cycles, or chaos in regions away from the steady state. Overall, our results highlight the importance of using a model's nonlinear equilibrium conditions to fully investigate global dynamics.