The young, the old, and the restless: demographics and business cycle volatility

We investigate the consequences of demographic change for business cycle analysis. We find that changes in the age composition of the labor force account for a significant fraction of the variation in business cycle volatility observed in the U.S. and other G7 economies. During the postwar period, these countries experienced dramatic demographic change, although details regarding extent and timing differ from place to place. Using panel-data methods, we exploit this variation to show that the age composition of the workforce has a large and statistically significant effect on cyclical volatility. We conclude by relating these findings to the recent decline in U.S. business cycle volatility. Using both simple accounting exercises and a quantitative general equilibrium model, we find that demographic change accounts for a significant part of this moderation.Business cycles - Econometric models ; Demography

Growth and business cycles

We present a class of convex endogenous growth models and analyze their performance in terms of both growth and business cycle criteria. The models we study have close analogs in the real business cycle literature. We interpret the exogenous growth rate of productivity as an endogenous growth rate of human capital. This perspective allows us to compare the strengths of the two classes of models. ; To highlight the mechanism that gives endogenous growth models the ability to improve upon their exogenous growth relatives, we study models that are symmetric in terms of human and physical capital formation—our two engines of growth. More precisely, we analyze models in which the technology used to produce human capital is identical to the technologies used to produce consumption and investment goods and in which the technology shocks in the two sectors are perfectly correlated.Business cycles ; Technological innovations ; Human capital

Turning Everyday Activities into Play: Building Relationships and Fostering Connections for Adopted Children and Children in Foster Care

The purpose of this capstone project was to create a program for community members, foster families, and adoptive families. In this project, community members was defined as any professional that works with foster and adoptive families in the community or in their profession. This included school staff, school administrators, therapists, and day care or respite providers. The goal of this program was to use play to build stronger family bonds and relationships while also supporting the development of children in foster care and adopted children. By providing this program as a tool that can be used by families and community members, this can help bridge the gap and inconsistencies with current trainings and programming. Turning Everyday Activities into Play affirmed that play can be a powerful tool especially when working with foster and adoptive youth who have been exposed to trauma at a young age. This program provided information on some of the effects of childhood trauma while providing specific strategies to help support self-regulation, child development, and foster the connection between adult and child

Simulating Epidemics and Interventions on High Resolution Social Networks

Mathematical models of disease spreading are a key factor of ensuring that we are prepared to deal with the next epidemic. They allow us to predict how an infection will spread throughout a population, thereby allowing us to make intelligent choices when attempting to contain the disease. Whether due to a lack of empirical data, a lack of computational power, a lack of biological understanding, or some combination thereof, traditional models must make sweeping assumptions about the behavior of a population during an epidemic. In this thesis, we implement granular epidemic simulations using a rich social network constructed from real-world interactions. We develop computational models for three diseases, and we use these simulations to demonstrate the effects of twelve potential intervention strategies, both before and during a hypothetical epidemic. We show how representing a population as a temporal graph and applying existing graph metrics can lead to more effective interventions

Variable frequency microwave (VFM) processing facilities and application in processing thermoplastic matrix composites

Microwave processing of materials is a relatively new technology advancement alternative that provides new approaches for enhancing material properties as well as economic advantages through energy savings and accelerated product development. Factors that hinder the use of microwaves in materials processing are declining, so that prospect for the development of this technology seem to be very promising. The two mechanisms of orientation polarisation and interfacial space charge polarisation, together with dc conductivity, form the basis of high frequency heating. Clearly, advantages in utilising microwave technologies for processing materials include penetration radiation, controlled electric field distribution and selective and volumetric heating. However, the most commonly used facilities for microwave processing materials are of fixed frequency, e.g. 2.45 GHz. This paper presents a state-of-the-art review of microwave technologies, processing methods and industrial applications, using variable frequency microwave (VFM) facilities. This is a new alternative for microwave processing

Effective algebraic degeneracy

We prove that any nonconstant entire holomorphic curve from the complex line C into a projective algebraic hypersurface X = X^n in P^{n+1}(C) of arbitrary dimension n (at least 2) must be algebraically degenerate provided X is generic if its degree d = deg(X) satisfies the effective lower bound: d larger than or equal to n^{{(n+1)}^{n+5}}

Extrapolated High-Order Propagators for Path Integral Monte Carlo Simulations

We present a new class of high-order imaginary time propagators for path-integral Monte Carlo simulations by subtracting lower order propagators. By requiring all terms of the extrapolated propagator be sampled uniformly, the subtraction only affects the potential part of the path integral. The negligible violation of positivity of the resulting path integral at small time steps has no discernable affect on the accuracy of our method. Thus in principle arbitrarily high order algorithms can be devised for path-integral Monte Carlo simulations. We verify this claim is by showing that fourth, sixth, and eighth order convergence can indeed be achieved in solving for the ground state of strongly interacting quantum many-body systems such as bulk liquid $^4$He.Comment: 9 pages and 3 figures. Submitted to J. Chem. Phy

Time consistent monetary policy with endogenous price rigidity

I characterize time consistent equilibrium in an economy with price rigidity and an optimizing> monetary authority operating under discretion. Firms have the option to increase their frequency> of price change, at a cost, in response to higher inflation. Previous studies, which assume a constant> degree of price rigidity across inflation regimes, find two time consistent equilibria ? one with low> inflation, the other with high inflation. In contrast, when price rigidity is endogenous, the high> inflation equilibrium ceases to exist. Hence, time consistent equilibrium is unique. This result> depends on two features of the analysis: (1) a plausible quantitative specification of the fixed cost> of price change, and (2) the presence of an arbitrarily small cost of inflation that is independent of> price rigidity.Monetary policy

A novel shape descriptor based on empty morphological skeleton

Los Alamitos, US

Structure and Collective Excitations of He-4 Clusters

Journals published by the American Physical Society can be found at http://journals.aps.org/We compute zero-temperature ground-state energies, one- and two-body densities, collective-excitation spectra, transition densities, and static and dynamic structure functions of He-4 clusters up to a cluster size of N = 112 particles. The ground-state properties are computed using a second-order diffusion Monte Carlo algorithm with Jastrow and triplet trial functions used for importance sampling. Excitation energies, transition densities, and dynamic structure functions are obtained by solving a generalized Feynman eigenvalue equation. We determine the systematic variation of collective energies with cluster size, demonstrate the existence of persistent oscillations in transition densities, evaluate the strength of collective modes quantitatively, and show how the cluster continuum excitation spectrum can be directly mapped by the dynamic structure function. By comparison with the full static structure function, the collective quadrupole state is found to exhaust approximately 25% of the total strength