Parameter Restrictions Research Articles

Fiscal Policy, Chartal Money, Mark‐up Dynamics and Unemployment Insurance in a Model of Growth and Distribution

AbstractGiven one parameter restriction, an output‐stabilization rule for the provision of public services turns a Kaldor–Kalecki–Steindl growth model with unstable, catastrophe‐prone dynamics into one with a stable limit cycle. In contrast, using a budget‐balancing rule produces a saddle point, along with closed orbits near the boundaries of the state space. Adding Kaleckian mark‐up dynamics destabilizes the equilibrium, with a spiraling path followed by a spin‐out found in simulation. A final exercise establishes the possibility of adding a variable workforce and a public unemployment insurance system. Throughout, an identity governs the dynamics of the stocks of public financial liabilities.

The Flexible Coefficient Multinomial Logit Model of Demand for Differentiated Products

We show FC-MNL is flexible in the sense of Diewert (1974), thus its parameters can be chosen to match a well-defined class of possible own- and cross-price elasticities of demand. In contrast to models such as Probit and Random Coefficient-MNL models, FC-MNL does not require estimation via simulation; it is fully analytic. Under well-defined and testable parameter restrictions, FC-MNL is shown to be an unexplored member of McFadden’s class of Multivariate Extreme Value discrete-choice models. Therefore, FC-MNL is fully consistent with an underlying structural model of heterogeneous, utility-maximizing consumers. We provide a Monte-Carlo study to establish its properties and we illustrate the use by estimating the demand for new automobiles in Italy.

Implementation Fidelity of Self-administered Transcutaneous Electrical Nerve Stimulation (TENS) in Patients With Chronic Back Pain

The efficacy of transcutaneous electrical nerve stimulation (TENS) for pain relief has not been reliably established. Inconclusive findings could be due to inadequate TENS delivery and inappropriate outcome assessment. Electronic monitoring devices were used to determine patient compliance with a TENS intervention and outcome assessment protocol, to record pain scores before, during, and after TENS, and measure electrical output settings. Patients with chronic back pain consented to use TENS daily for 2 weeks and to report pain scores before, during, and after 1-hour treatments. A ≥ 30% reduction in pain scores was used to classify participants as TENS responders. Electronic monitoring devices "TLOG" and "TSCORE" recorded time and duration of TENS use, electrical settings, and pain scores. Forty-two patients consented to participate. One of 35 (3%) patients adhered completely to the TENS use and pain score reporting protocol. Fourteen of 33 (42%) were TENS responders according to electronic pain score data. Analgesia onset occurred within 30 to 60 minutes for 13/14 (93%) responders. It was not possible to correlate TENS amplitude, frequency, or pulse width measurements with therapeutic response. Findings from TENS research studies depend on the timing of outcome assessment; pain should be recorded during stimulation. TENS device sophistication might be an issue and parameter restriction should be considered. Careful protocol design is required to improve adherence and monitoring is necessary to evaluate the validity of findings. This observational study provides objective evidence to support concerns about poor implementation fidelity in TENS research.

The flexible coefficient multinomial logit (FC‐MNL) model of demand for differentiated products

We show FC‐MNL is flexible in the sense of Diewert (), thus its parameters can be chosen to match a well‐defined class of possible own‐ and cross‐price elasticities of demand. In contrast to models such as Probit and Random Coefficient‐MNL models, FC‐MNL does not require estimation via simulation; it is fully analytic. Under well‐defined and testable parameter restrictions, FC‐MNL is shown to be an unexplored member of McFadden's class of Multivariate Extreme Value discrete‐choice models. Therefore, FC‐MNL is fully consistent with an underlying structural model of heterogeneous, utility‐maximizing consumers. We provide a Monte‐Carlo study to establish its properties and we illustrate its use by estimating the demand for new automobiles in Italy.

Spectral action and gravitational effects at the Planck scale

We discuss the possibility to extend the spectral action up to energy close to the Planck scale, taking also into account the gravitational effects given by graviton exchange. Including this contribution in the theory, the coupling constant unification is not compromised but is shifted to the Planck scale rendering all gauge couplings asymptotically free. In the scheme of noncommutative geometry, the gravitational effects change the main standard model coupling constants, leading to a restriction of the free parameters of the theory compatible with the Higgs and top mass prediction. We also discuss consequences for the neutrino mass and the see-saw mechanism.

Arbitrage-Free Models of Stocks and Bonds

A small but ambitious literature uses affine arbitrage-free models to estimate jointly U.S. Treasury term premiums and the term structure of equity risk premiums. Within this approach, this paper identifies the parameter restrictions that are consistent with a simple dividend discount model, extends the cross-section to Germany and France, averages across multiple observable-factor and market prices of risk specifications, and considers alternative samples for parameter estimation. The results produce intuitive trajectories for both sets of premiums given standard samples starting from July 1993. However, the decomposition of nominal U.S. Treasury yields, but not long-run equity risk premiums, is sensitive to data beyond 2008, which raises some questions about the net effects of unconventional monetary policy measures. Nonetheless, the rotation from sharp inversion during the financial crisis to an upward-sloping term structure of equity risk premiums more recently, with modest readings at the front end, is not inconsistent with some net moderation in required compensation for equity risk in the United States.

On New Similarity Solutions of the Boiti—Leon—Pempinelli System

In the present work, the new exact solutions of the Boiti—Leon—Pempinelli system have been found. The system has extensive physical background. The exact solutions of the Boiti—Leon—Pempinelli system are investigated using similarity transformation method via Lie group theory. Lie symmetry generators are used for constructing similarity variables for the given system of partial differential equations, which lead to the new system of partial differential equations with one variable less at each step and eventually to a system of ordinary differential equations (ODEs). Finally, these ODEs are solved exactly. The exact solutions are obtained under some parametric restrictions. The elastic behavior of the soliton solutions is shown graphically by taking some appropriate choices of the arbitrary functions involved in the solutions.

On a Stochastic SEIS Model with Treatment Rate of Latent Population

The asymptotic dynamics of a stochastic SEIS epidemic model with treatment rate of latent population is investigated. First, we show that the system provides a unique positive global solution starting from the positive initial value. Then, the long-term asymptotic behavior of the model is studied: ifR0, which is called the basic reproduction number of the corresponding deterministic model, is not more than unity, the solution of the model is oscillating around the disease-free equilibrium of the corresponding deterministic system, whereas ifR0is larger than unity, we show how the solution spirals around the endemic equilibrium of deterministic system under certain parametric restrictions. Finally, numerical simulations are carried out to support our theoretical findings.

Exact Solutions of the Dirac Hamiltonian on the Sphere under Hyperbolic Magnetic Fields

Two-dimensional massless Dirac Hamiltonian under the influence of hyperbolic magnetic fields is mentioned in curved space. Using a spherical surface parameterization, the Dirac operator on the sphere is presented and the system is given as two supersymmetric partner Hamiltonians which coincides with the position dependent mass Hamiltonians. We introduce two ansatzes for the component of the vector potential to acquire effective solvable models, which are Rosen-Morse II potential and the model given Midya and Roy, whose bound states are JacobiX1type polynomials, and we adapt our work to these special models under some parameter restrictions. The energy spectrum and the eigenvectors are found for Rosen-Morse II potential. On the other hand, complete solutions are given for the second system. The vector and the effective potentials with their eigenvalues are sketched for each system.

Ethnic Conflicts, Rumours and an Informed Agent

Rumours often precipitate ethnic conflicts. There may exist an agent (player b) who has additional information about the veracity of the rumour. We explore the role that such agents play in negating the effects of a bad rumour. Two cases are analysed - b is non-strategic i.e. he reveals his information truthfully and b is strategic and has a commonly known bias towards one ethnicity 1 . When b is nonstrategic, our model suggests that conflict caused by a false rumour is unlikely to happen when b can meet a large fraction of the population (as in rural areas). This is due to two effects - not only do the players who meet b know that the rumour is false, they also estimate (from the commonly known meeting process) that a large part of the population must also know. This allows them to coordinate, not fight and enjoy the high peace time payoff as opposed to the lower conflict payoff. This could be a possible explanation for the commonly observed phenomenon that ethnic conflicts in India are largely an urban phenomenon. 2 When b is allowed to be strategic and it is known that he has a bias towards one ethnicity, we show that, under parametric restrictions, there are only two equilibrium outcomes possible. In one outcome, everyone fights and conflict occurs with probability one. In the other equilibrium outcome, there may not be conflict when b believes that peace is possible. If b believes that conflict is inevitable, he reveals information in a way which gives his own ethnicity a higher probability of winning. The latter equilibrium outcome is from a knife edge equilibrium. This highlights the difficulty in preventing rumour induced conflicts when the informed agent is biased.

Radiative MHD Heat and Mass Transfer Nanofluid Flow Past a Horizontal Plate in a Rotating System

Unsteady radiative MHD heat and mass transfer nanofluid flow through horizontal plate under the action of magnetic field have been investigated. To obtain the non-similar coupled nonlinear momentum, energy and concentration equations, usual non-dimensional variables have been used. The explicit finite difference method with stability and convergence analysis has been used to solve the obtained numerical solutions of the above problem. The stability and convergence analyses have been used for measuring the restriction of the useful parameters. The obtained numerical results have been presented graphically and discussed in details. Finally, a qualitative comparison of our results with published results has been explained in conclusion section.

Mining for critical stock price movements using temporal power laws and integrated autoregressive models

This paper investigates the practical applicability of the log-periodic power law model to forecast large drawdowns of stock prices and compares its performance with the performance of the classical integrated autoregressive time series model. Both models are fitted to the daily closing prices of the Dow Jones index. In the case of the log-periodic power law model an alarm is issued if any fit conforming to theoretically motivated parameter restrictions can be found. In the case of the integrated autoregressive model an alarm is issued if structural breaks are observed at the end of the fit interval. It is shown that both models are successful in predicting upcoming stock market crises. The log-periodic power law model is superior in filtering out extreme drawdowns. However, its performance is highly dependent on the fit procedure.

Job Scheduling for Cloud Computing Using Neural Networks

Cloud computing aims to maximize the benefit of distributed resources and aggregate them to achieve higher throughput to solve large scale computation problems. In this technology, the customers rent the resources and only pay per use. Job scheduling is one of the biggest issues in cloud computing. Scheduling of users’ requests means how to allocate resources to these requests to finish the tasks in minimum time. The main task of job scheduling system is to find the best resources for user’s jobs, taking into consideration some statistics and dynamic parameters restrictions of users’ jobs. In this research, we introduce cloud computing, genetic algorithm and artificial neural networks, and then review the literature of cloud job scheduling. Many researchers in the literature tried to solve the cloud job scheduling using different techniques. Most of them use artificial intelligence techniques such as genetic algorithm and ant colony to solve the problem of job scheduling and to find the optimal distribution of resources. Unfortunately, there are still some problems in this research area. Therefore, we propose implementing artificial neural networks to optimize the job scheduling results in cloud as it can find new set of classifications not only search within the available set.

Statistical analysis of multipole-model-derived structural parameters and charge-density properties from high-resolution X-ray diffraction experiments

A comprehensive analysis of various properties derived from multiple high-resolution X-ray diffraction experiments is reported. A total of 13 charge-density-quality data sets of α-oxalic acid dihydrate (C2H2O4·2H2O) were subject to Hansen-Coppens-based modelling of electron density. The obtained parameters and properties were then statistically analysed yielding a clear picture of their variability across the different measurements. Additionally, a computational approach (CRYSTAL and PIXEL programs) was utilized to support and examine the experimental findings. The aim of the study was to show the real accuracy and interpretation limits of the charge-density-derived data. An investigation of raw intensities showed that most of the reflections (60-70%) fulfil the normality test and the lowest ratio is observed for weak reflections. It appeared that unit-cell parameters are determined to the order of 10(-3) Å (for cell edges) and 10(-2) ° (for angles), and compare well with the older studies of the same compound and with the new 100 K neutron diffraction data set. Fit discrepancy factors are determined within a 0.5% range, while the residual density extrema are about ±0.16 (3) e Å(-3). The geometry is very well reproducible between different data sets. Regarding the multipole model, the largest errors are present on the valence shell charge-transfer parameters. In addition, symmetry restrictions of multipolar parameters, with respect to local coordinate systems, are well preserved. Standard deviations for electron density are lowest at bond critical points, being especially small for the hydrogen-bonded contacts. The same is true for kinetic and potential energy densities. This is also the case for the electrostatic potential distribution, which is statistically most significant in the hydrogen-bonded regions. Standard deviations for the integrated atomic charges are equal to about 0.1 e. Dipole moments for the water molecule are comparable with the ones presented in various earlier studies. The electrostatic energies should be treated rather qualitatively. However, they are quite well correlated with the PIXEL results.

Frequency domain generalized empirical likelihood method

This paper is concerned with a version of empirical likelihood method for spectral restrictions, which handles stationary time series data via the frequency domain approach. The asymptotic properties of frequency domain generalized empirical likelihood are studied for either strictly stationary processes with vanishing cumulant spectral density function of order 4 or linear processes generated by iid innovations with possibly non‐zero fourth order cumulant. Several statistics for testing parametric restrictions, over‐identified spectral restrictions, and additional spectral restrictions are shown to have the limiting chi‐squared distributions. Some numerical results are presented to investigate the finite sample performance of the proposed procedures. Copyright © 2013 John Wiley & Sons, Ltd.

Frequency domain generalized empirical likelihood method

This paper is concerned with a version of empirical likelihood method for spectral restrictions, which handles stationary time series data via the frequency domain approach. The asymptotic properties of frequency domain generalized empirical likelihood are studied for either strictly stationary processes with vanishing cumulant spectral density function of order 4 or linear processes generated by iid innovations with possibly non-zero fourth order cumulant. Several statistics for testing parametric restrictions, over-identified spectral restrictions, and additional spectral restrictions are shown to have the limiting chi-squared distributions. Some numerical results are presented to investigate the finite sample performance of the proposed procedures. Copyright © 2013 John Wiley & Sons, Ltd.

Nonparametric Identification in Structural Economic Models

Structural economic models allow one to analyze counterfactuals when economic systems change and to evaluate the well-being of economic agents. A key element in such analysis is the ability to identify the primitive functions and distributions of the economic models that are employed to describe the economic phenomena under study. Recent developments have provided ways to achieve identification of these primitive functions and distributions without imposing parametric restrictions. In this article, I consider a small set of stylized models and provide insight into some of the approaches that have been taken to develop nonparametric identification results in those models.

Parameter Design of Damping Networks for the Superbuck Converter

A simple parameter design method for damping networks of superbuck topology to avoid right-half-plane (RHP) zeros is presented in this paper. It is proved that the existence of RHP zeros in output voltage models of the individual- or coupled-inductor superbuck converter is related to the duty ratio and the inductor parameters when there are no damping networks in the circuit. The constraints are tough for cancellation of RHP zeros when the duty ratio is extremely large. So, the output voltage models of the superbuck converter with damping networks are analyzed in this paper. It is proved that the parameter restrictions for no RHP zeros can be relaxed by using damping networks in the circuit. By simple assumptions, the restrictions can be easy to satisfy by proper design of damping network parameters. Both situations of resistor load and battery load have been considered individually. RHP zeros of output current models can be also canceled when the same design conditions are satisfied. The computed model analysis and experiment results verified the conclusions.

Numerical solution of dynamic equilibrium models under Poisson uncertainty

We propose a simple and powerful numerical algorithm to compute the transition process in continuous-time dynamic equilibrium models with rare events. In this paper we transform the dynamic system of stochastic differential equations into a system of functional differential equations of the retarded type. We apply the Waveform Relaxation algorithm, i.e., we provide a guess of the policy function and solve the resulting system of (deterministic) ordinary differential equations by standard techniques. For parametric restrictions, analytical solutions to the stochastic growth model and a novel solution to Lucas' endogenous growth model under Poisson uncertainty are used to compute the exact numerical error. We show how (potential) catastrophic events such as rare natural disasters substantially affect the economic decisions of households.

A Generalized Class of k-Starlike Functions Involving a Calculus Operator

In this paper, involving a calculus operator \( \tilde{I}^{\delta ,\nu } , \) a generalized class \( {\text{US}}(k,\delta ,\nu ) \) of k-starlike functions is defined and an estimate for coefficients of functions belonging to this class is determined. For this class, coefficient inequality is given and is applied to find certain mappings of the operator \( \tilde{I}^{\delta ,\nu } , \) under some parametric restrictions. Results based on inclusion property and convolution property, are also derived. Further, for a subclass \( \overline{\text{US}} (k,\delta ,\nu ) \) of \( {\text{US}}(k,\delta ,\nu ), \) results on bounds, extreme points and radius of starlikeness are obtained.