The Philadelphia story: a new forecasting model

Several years ago, the Philadelphia Fed developed a small forecasting model for each of the three states in the Third Federal Reserve DistrictCPennsylvania, New Jersey, and Delaware. This article introduces a similar model that forecasts major economic variables for the Philadelphia metropolitan area and the city of Philadelphia. Read this article and find out what the model predicts for the metro area and the cityForecasting ; Philadelphia (Pa.)

A Bayesian VAR forecasting model for the Philadelphia Metropolitan Area

Vector-autoregression (VAR) forecast models have been developed for many state economies, including the three states in the Third Federal Reserve District--Pennsylvania, New Jersey, and Delaware. This paper extends that work by developing a Bayesian VAR forecast model for the Philadelphia metropolitan area and the city of Philadelphia.Forecasting ; Philadelphia (Pa.)

Risk and return within the single-family housing market

The trade-off between risk and return in equity markets is well established. This paper examines the existence of the same trade-off in the single-family housing market. That market is dominated by homeowners, who constitute about two-thirds of U.S. households. For them the choice about how much housing and what house to buy is a joint consumption/investment decision. Furthermore, owner-occupied housing is by nature a lumpy investment whose risk cannot be completely diversified. Does this consumption/investment link negate the risk/return trade-off within the single-family housing market? Theory suggests the link still holds. This paper supplies empirical evidence in support of that theoretical result.Housing

The Impact of the COVID-19 Pandemic on Esports Viewership Trends

Abstract Multi-player gameplay competitions, live streaming of gameplay, and viewing gameplay are significant segments of esports’ rapidly growing consumer online gaming community. In 2021, the esports industry was forecast to generate over $1 billion USD worldwide in revenue (Esports Earnings, 2019). Twitch.tv, the largest esports online platform, integrates multiple user-to-player, user-to-user, and user-to-community communication tools, thus creating social interaction opportunities. This study explored online or digital esports viewership activity and the importance of community interaction opportunities on the Twitch.tv digital platform. For the purpose of this study, a broad definition of esports viewership and community participation is used because esports roles may easily change during a single user’s session on esports platforms. A competitor in a tournament may easily and quickly become a streamer of content. An esports streamer may become the viewer of a tournament, or a viewer may become a streamer. The Twitch.tv platform usage data for analysis is limited and does not distinguish between the user’s role or geographic location. This is a known limitation of this research. There are few rigorous statistical examinations of English-language Twitch.tv esports platform data in the current literature beyond the presentation of histograms in trade media, especially on how esports platform viewership changed during the COVID-19 pandemic. This study seeks to inform reviewers on changes in esports viewership and participation before-, during-, and after- the unprecedented COVID-19 pandemic stay-at-home orders, public health advisory and social restrictions in 2020 using academic methods. It draws on social identity theory and habit theory to explain the motivation for changes in consumer esports viewership trends. This mixed-methods study analyzes esports viewership on the largest platform, Twitch.tv, based on peak viewership accessed in the English language. According to Streamlabs’ Q1 2021 Report, Twitch.tv leads the global market with live stream viewers in 4Q 2020 and 1Q 2021, of 6.34 billion hours, representing 72.3% of the market share of esports hours viewed. This study defines pre-COVID as October 2019-February 2020, during- as March-July 2020, and post- as August to December 2020, see Figures 7 and 8 for additional details (CDC, 2021). This study includes a quantitative analysis of peak Twitch.tv platform viewership data and qualitative interviews with active esports viewers during the same period. Whether you are a game designer, platform creator, marketing, or media executive, this study documents the continued growth of Twitch.tv as an important go-to platform and medium for entertainment and social interactions, as demonstrated by its popularity among people isolated during the COVID-19 pandemic in 2020. This engaged scholarship study documents, both quantitatively and qualitatively, the change in esports content viewership resulting from the COVID-19 pandemic. This may signal a significant change in consumer media consumption behavior and media expectations where consumers seek integrated entertainment and community interactions

Adaptive laser link reconfiguration using constraint propagation

This paper describes Harris AI research performed on the Adaptive Link Reconfiguration (ALR) study for Rome Lab, and focuses on the application of constraint propagation to the problem of link reconfiguration for the proposed space based Strategic Defense System (SDS) Brilliant Pebbles (BP) communications system. According to the concept of operations at the time of the study, laser communications will exist between BP's and to ground entry points. Long-term links typical of RF transmission will not exist. This study addressed an initial implementation of BP's based on the Global Protection Against Limited Strikes (GPALS) SDI mission. The number of satellites and rings studied was representative of this problem. An orbital dynamics program was used to generate line-of-site data for the modeled architecture. This was input into a discrete event simulation implemented in the Harris developed COnstraint Propagation Expert System (COPES) Shell, developed initially on the Rome Lab BM/C3 study. Using a model of the network and several heuristics, the COPES shell was used to develop the Heuristic Adaptive Link Ordering (HALO) Algorithm to rank and order potential laser links according to probability of communication. A reduced set of links based on this ranking would then be used by a routing algorithm to select the next hop. This paper includes an overview of Constraint Propagation as an Artificial Intelligence technique and its embodiment in the COPES shell. It describes the design and implementation of both the simulation of the GPALS BP network and the HALO algorithm in COPES. This is described using a 59 Data Flow Diagram, State Transition Diagrams, and Structured English PDL. It describes a laser communications model and the heuristics involved in rank-ordering the potential communication links. The generation of simulation data is described along with its interface via COPES to the Harris developed View Net graphical tool for visual analysis of communications networks. Conclusions are presented, including a graphical analysis of results depicting the ordered set of links versus the set of all possible links based on the computed Bit Error Rate (BER). Finally, future research is discussed which includes enhancements to the HALO algorithm, network simulation, and the addition of an intelligent routing algorithm for BP

Detecting a Z2Z_2 topologically ordered phase from unbiased infinite projected entangled-pair state simulations

We present an approach to identify topological order based on unbiased infinite projected entangled-pair states (iPEPS) simulations, i.e. where we do not impose a virtual symmetry on the tensors during the optimization of the tensor network ansatz. As an example we consider the ground state of the toric code model in a magnetic field exhibiting $Z_2$ topological order. The optimization is done by an efficient energy minimization approach based on a summation of tensor environments to compute the gradient. We show that the optimized tensors, when brought into the right gauge, are approximately $Z_2$ symmetric, and they can be fully symmetrized a posteriori to generate a stable topologically ordered state, yielding the correct topological entanglement entropy and modular S and U matrices. To compute the latter we develop a variant of the corner-transfer matrix method which is computationally more efficient than previous approaches based on the tensor renormalization group.Comment: 16 pages, 14 figure

Competition between intermediate plaquette phases in SrCu2_2(BO3_3)2_2 under pressure

Building on the growing evidence based on NMR, magnetization, neutron scattering, ESR, and specific heat that, under pressure, SrCu$_2$(BO$_3$)$_2$ has an intermediate phase between the dimer and the N\'eel phase, we study the competition between two candidate phases in the context of a minimal model that includes two types of intra- and inter-dimer interactions without enlarging the unit cell. We show that the empty plaquette phase of the Shastry-Sutherland model is quickly replaced by a quasi-1D full plaquette phase when intra- and/or inter-dimer couplings take different values, and that this full plaquette phase is in much better agreement with available experimental data than the empty plaquette one.Comment: 19 page

Persistence and Quiescence of Seismicity on Fault Systems

We study the statistics of simulated earthquakes in a quasistatic model of two parallel heterogeneous faults within a slowly driven elastic tectonic plate. The probability that one fault remains dormant while the other is active for a time Dt following the previous activity shift is proportional to the inverse of Dt to the power 1+x, a result that is robust in the presence of annealed noise and strength weakening. A mean field theory accounts for the observed dependence of the persistence exponent x as a function of heterogeneity and distance between faults. These results continue to hold if the number of competing faults is increased. This is related to the persistence phenomenon discovered in a large variety of systems, which specifies how long a relaxing dynamical system remains in a neighborhood of its initial configuration. Our persistence exponent is found to vary as a function of heterogeneity and distance between faults, thus defining a novel universality class.Comment: 4 pages, 3 figures, Revte