pwc-archive/papers-with-abstracts huggingface dataset:
Quantile Autoregression-based Non-causality Testing
Authors: Weifeng Jin
Date: 2023-01-07 00:00:00
Tasks: Gaussian Processes, Time Series Analysis

Non-causal processes have been drawing attention recently in Macroeconomics and Finance for their ability to display nonlinear behaviors such as asymmetric dynamics, clustering volatility, and local explosiveness. In this paper, we investigate the statistical properties of empirical conditional quantiles of non-causal processes. Specifically, we show that the quantile autoregression (QAR) estimates for non-causal processes do not remain constant across different quantiles in contrast to their causal counterparts. Furthermore, we demonstrate that non-causal autoregressive processes admit nonlinear representations for conditional quantiles given past observations. Exploiting these properties, we propose three novel testing strategies of non-causality for non-Gaussian processes within the QAR framework. The tests are constructed either by verifying the constancy of the slope coefficients or by applying a misspecification test of the linear QAR model over different quantiles of the process. Some numerical experiments are included to examine the finite sample performance of the testing strategies, where we compare different specification tests for dynamic quantiles with the Kolmogorov-Smirnov constancy test. The new methodology is applied to some time series from financial markets to investigate the presence of speculative bubbles. The extension of the approach based on the specification tests to AR processes driven by innovations with heteroskedasticity is studied through simulations. The performance of QAR estimates of non-causal processes at extreme quantiles is also explored.
Optimal social security timing
Authors: A. Y. Aydemir
Date: 2023-01-10 00:00:00

The optimal age that a retiree claims social security retirement benefits is in general a complicated function of many factors. However, if the beneficiary's finances and health are not the constraining factors, it is possible to formally derive mathematical models that maximize a well-defined measure of his total benefits. A model that takes into account various factors such as the increase in the benefits for delayed claims and the penalties for early retirement, the advantages of investing some of the benefits in the financial markets, and the effects of cost-of-living adjustments shows that not waiting until age 70 is almost always the better option. The optimal claiming age that maximizes the total benefits, however, depends on the expected market returns and the rate of cost-of-living adjustments, with the higher market rates in general pushing the optimal age lower. The models presented here can be easily tailored to address the particular circumstances and goals of any individual.
How effective are covid-19 vaccine health messages in reducing vaccine skepticism? Heterogeneity in messages effectiveness by just world beliefs
Authors: Juliane Wiese, Nattavudh Powdthavee
Date: 2023-01-09 00:00:00

To end the COVID-19 pandemic, policymakers have relied on various public health messages to boost vaccine take-up rates amongst people across wide political spectra, backgrounds, and worldviews. However, much less is understood about whether these messages affect different people in the same way. One source of heterogeneity is the belief in a just world (BJW), which is the belief that in general, good things happen to good people, and bad things happen to bad people. This study investigates the effectiveness of two common messages of the COVID-19 pandemic: vaccinate to protect yourself and vaccinate to protect others in your community. We then examine whether BJW moderates the effectiveness of these messages. We hypothesize that just-world believers react negatively to the prosocial pro-vaccine message, as it charges individuals with the responsibility to care for others around them. Using an unvaccinated sample of UK residents before vaccines were made widely available (N=526), we demonstrate that the individual-focused message significantly reduces overall vaccine skepticism, and that this effect is more robust for individuals with a low BJW, whereas the community-focused message does not. Our findings highlight the importance of individual differences in the reception of public health messages to reduce COVID-19 vaccine skepticism.
The COVID-19 vaccination, preventive behaviors and pro-social motivation: panel data analysis from Japan
Authors: Eiji Yamamura, Yoshiro Tsutsui, Fumio Ohtake
Date: 2023-01-09 00:00:00

The COVID-19 vaccine reduces infection risk: even if one contracts COVID-19, the probability of complications like death or hospitalization is lower. However, vaccination may prompt people to decrease preventive behaviors, such as staying indoors, handwashing, and wearing a mask. Thereby, if vaccinated people pursue only their self-interest, the vaccine's effect may be lower than expected. However, if vaccinated people are pro-social (motivated toward benefit for the whole society), they might maintain preventive behaviors to reduce the spread of infection.
Inflation and Value Creation: An Economic and Philosophic Investigation
Authors: Gennady Shkliarevsky
Date: 2023-01-08 00:00:00

The subject of this study is inflation, a problem that has plagued America and the world over the last several decades. Despite a rich trove of scholarly studies and a wide range of tools developed to deal with inflation, we are nowhere near a solution of this problem. We are now in the middle of the inflation that threatens to become a stagflation or even a full recession; and we have no idea what to prevent this outcome. This investigation explores the real source of inflation. Tracing the problem of inflation to production, it finds that inflation is not a phenomenon intrinsic to economy; rather, it is a result of inefficiencies and waste in our economy. The investigation leads to a conclusion that the solution of the problem of inflation is in achieving full efficiency in production. Our economic production is a result of the evolution that is propelled by the process of creation. In order to end economic inefficiencies, we should model our economic practice on the process that preceded production and has led to its emergence. In addition, the study will outline ways in which our economic theory and practice must be changed to achieve full efficiency of our production. Finally, the study provides a critical overview of the current theories of inflation and remedies that are proposed to deal with it.
Health Wearables, Gamification, and Healthful Activity
Authors: Muhammad Zia Hydari, Idris Adjerid, Aaron D. Striegel
Date: 2023-01-07 00:00:00

Health wearables in combination with gamification enable interventions that have the potential to increase physical activity -- a key determinant of health. However, the extant literature does not provide conclusive evidence on the benefits of gamification, and there are persistent concerns that competition-based gamification approaches will only benefit those who are highly active at the expense of those who are sedentary. We investigate the effect of Fitbit leaderboards on the number of steps taken by the user. Using a unique data set of Fitbit wearable users, some of whom participate in a leaderboard, we find that leaderboards lead to a 370 (3.5%) step increase in the users' daily physical activity. However, we find that the benefits of leaderboards are highly heterogeneous. Surprisingly, we find that those who were highly active prior to adoption are hurt by leaderboards and walk 630 fewer steps daily after adoption (a 5% relative decrease). In contrast, those who were sedentary prior to adoption benefited substantially from leaderboards and walked an additional 1,300 steps daily after adoption (a 15% relative increase). We find that these effects emerge because sedentary individuals benefit even when leaderboards are small and when they do not rank first on them. In contrast, highly active individuals are harmed by smaller leaderboards and only see benefit when they rank highly on large leaderboards. We posit that this unexpected divergence in effects could be due to the underappreciated potential of noncompetition dynamics (e.g., changes in expectations for exercise) to benefit sedentary users, but harm more active ones.
Action needed to make carbon offsets from tropical forest conservation work for climate change mitigation
Authors: Thales A. P. West, Sven Wunder, Erin O. Sills, Jan Börner, Sami W. Rifai, Alexandra N. Neidermeier, Andreas Kontoleon
Date: 2023-01-05 00:00:00
Tasks: Attribute, Causal Inference

Carbon offsets from voluntarily avoided deforestation projects are generated based on performance vis-\`a-vis ex-ante deforestation baselines. We examined the impacts of 27 forest conservation projects in six countries on three continents using synthetic control methods for causal inference. We compare the project baselines with ex-post counterfactuals based on observed deforestation in control sites. Our findings show that most projects have not reduced deforestation. For projects that did, reductions were substantially lower than claimed. Methodologies for constructing deforestation baselines for carbon-offset interventions thus need urgent revisions in order to correctly attribute reduced deforestation to the conservation interventions, thus maintaining both incentives for forest conservation and the integrity of global carbon accounting.
Randomization advice and ambiguity aversion
Authors: Christoph Kuzmics, Brian W. Rogers, Xiannong Zhang
Date: 2023-01-09 00:00:00
Tasks: Decision Making, Position

We design and implement lab experiments to evaluate the normative appeal of behavior arising from models of ambiguity-averse preferences. We report two main empirical findings. First, we demonstrate that behavior reflects an incomplete understanding of the problem, providing evidence that subjects do not act on the basis of preferences alone. Second, additional clarification of the decision making environment pushes subjects' choices in the direction of ambiguity aversion models, regardless of whether or not the choices are also consistent with subjective expected utility, supporting the position that subjects find such behavior normatively appealing.
Strategic Environmental Corporate Social Responsibility (ECSR) Certification and Endogenous Market Structure
Authors: Ajay Sharma, Siddhartha Rastogi
Date: 2023-01-09 00:00:00

This paper extends the findings of Liu et al. (2015, Strategic environmental corporate social responsibility in a differentiated duopoly market, Economics Letters), along two dimensions. First, we consider the case of endogenous market structure a la Vives and Singh (1984, Price and quantity competition in a differentiated duopoly, The Rand Journal of Economics). Second, we refine the ECSR certification standards in differentiated duopoly with rankings. We find that optimal ECSR certification standards by NGO are the highest in Bertrand competition, followed by mixed markets and the lowest in Cournot competition. Next, NGO certifier will set the ECSR standards below the optimal level. Also, we show that given the ECSR certification standards, there is a possibility of both price and quantity contracts choices by the firms in endogenous market structure.
A responsibility value for digraphs
Authors: Rosa van den Ende, Dylan Laplace Mermoud
Date: 2023-01-06 00:00:00

There is an increasing need to hold players responsible for negative or positive impact that take place elsewhere in a value chain or a network. For example, countries or companies are held more and more responsible for their indirect carbon emissions. We introduce a responsibility value that allocates the total impact of the value chain among the players, taking into account their direct impact and their indirect impact through the underlying graph. Moreover, we show that the responsibility value satisfies a set of natural yet important properties.
Preferences on Ranked-Choice Ballots
Authors: Brian Duricy
Date: 2023-01-06 00:00:00

This paper formalizes the lattice structure of the ballot voters cast in a ranked-choice election and the preferences that this structure induces. These preferences are shown to be counter to previous assumptions about the preferences of voters, which indicate that ranked-choice elections require different considerations for voters and candidates alike. While this model assumes that voters vote sincerely, the model of ranked-choice elections this paper presents allows for considerations of strategic voting in future work.
Sensing the Environment with 5G Scattered Signals (5G-CommSense): A Feasibility Analysis
Authors: Sandip Jana, Amit Kumar Mishra, Mohammed Zafar Ali Khan
Date: 2023-01-10 00:00:00

By making use of the sensors and AI (SensAI) algorithms for a specialized task, Application Specific INstrumentation (ASIN) framework uses less computational overhead and gives a good performance. This work evaluates the feasibility of the ASIN framework dependent Communication based Sensing (CommSense) system using 5th Generation New Radio (5G NR) infrastructure. Since our proposed system is backed up by 5G NR infra, this system is termed as 5G-CommSense. In this paper, we have used NR channel models specified by the 3rd Generation Partnership Project (3GPP) and added white Gaussian noise (AWGN) to vary the signal to noise ratio at the receiver. Finally, from our simulation result, we conclude that the proposed system is practically feasible.
RIS-Assisted Joint Uplink Communication and Imaging: Phase Optimization and Bayesian Echo Decoupling
Authors: Shengyu Zhu, Zehua Yu, Qinghua Guo, Jinshan Ding, Qiang Cheng, Tie Jun Cui
Date: 2023-01-10 00:00:00
Tasks: Integrated sensing and communication, ISAC

Achieving integrated sensing and communication (ISAC) via uplink transmission is challenging due to the unknown waveform and the coupling of communication and sensing echoes. In this paper, a joint uplink communication and imaging system is proposed for the first time, where a reconfigurable intelligent surface (RIS) is used to manipulate the electromagnetic signals for echo decoupling at the base station (BS). Aiming to enhance the transmission gain in desired directions and generate required radiation pattern in the region of interest (RoI), a phase optimization problem for RIS is formulated, which is high dimensional and nonconvex with discrete constraints. To tackle this problem, a back propagation based phase design scheme for both continuous and discrete phase models is developed. Moreover, the echo decoupling problem is tackled using the Bayesian method with the factor graph technique, where the problem is represented by a graph model which consists of difficult local functions. Based on the graph model, a message-passing algorithm is derived, which can efficiently cooperate with the adaptive sparse Bayesian learning (SBL) to achieve joint communication and imaging. Numerical results show that the proposed method approaches the relevant lower bound asymptotically, and the communication performance can be enhanced with the utilization of imaging echoes.
Analysis and Empirical Validation of Visible Light Path Loss Model for Vehicular Sensing and Communication
Authors: Hisham Abuella, Md Zobaer Islam, Russ Messenger, John F. O'Hara, Sabit Ekin
Date: 2023-01-09 00:00:00

Advancements in lighting systems and photodetectors provide opportunities to develop viable alternatives to conventional communication and sensing technologies, especially in the vehicular industry. Most of the studies that propose visible light in communication or sensing adopt the Lambertian propagation (path loss) model. This model requires knowledge and utilization of multiple parameters to calculate the path loss such as photodetector area, incidence angle, and distance between transmitter and receiver. In this letter, a simplified path loss model that is mathematically more tractable is proposed for vehicular sensing and communication systems that use visible light technology. Field measurement campaigns are conducted to validate the performance and limits of the developed path loss model. The proposed model is used to fit the data collected at different ranges of incident angles and distances. Further, this model can be used for designing visible light-based communication and sensing systems to minimize the complexity of the Lambertian path loss model, particularly for cases where the incident angle between transmitter and receiver is relatively small.
High-resolution Power Doppler Using Null Subtraction Imaging
Authors: Zhengchang Kou, Matthew Lowerison, Qi You, Yike Wang, Pengfei Song, Michael L. Oelze
Date: 2023-01-09 00:00:00
Tasks: Vocal Bursts Intensity Prediction

To improve the spatial resolution of power Doppler (PD) imaging, we explored null subtraction imaging (NSI) as an alternative beamforming technique to delay-and-sum (DAS). NSI is a nonlinear beamforming approach that uses three different apodizations on receive and incoherently sums the beamformed envelopes. NSI uses a null in the beam pattern to improve the lateral resolution, which we apply here for improving PD spatial resolution both with and without contrast microbubbles. In this study, we used NSI with three types of singular value decomposition (SVD)-based clutter filters and noise equalization to generate high-resolution PD images. An element sensitivity correction scheme was also proposed as a crucial component of NSI-based PD imaging. First, a microbubble trace experiment was performed to evaluate the resolution improvement of NSI-based PD over traditional DAS-based PD. Then, both contrast-enhanced and contrast free ultrasound PD images were generated from the scan of a rat brain. The cross-sectional profile of the microbubble traces and microvessels were plotted. FWHM was also estimated to provide a quantitative metric. Furthermore, iso-frequency curves were calculated to provide a resolution evaluation metric over the global field of view. Up to six-fold resolution improvement was demonstrated by the FWHM estimate and four-fold resolution improvement was demonstrated by the iso-frequency curve from the NSI-based PD microvessel images compared to microvessel images generated by traditional DAS-based beamforming. A resolvability of 39 um was measured from the NSI-based PD microvessel image. The computational cost of NSI-based PD was only increased by 40 percent over the DAS-based PD.
Physical Layer Security in Satellite Communication: State-of-the-art and Open Problems
Authors: Nora Abdelsalam, Saif Al-Kuwari, Aiman Erbad
Date: 2023-01-09 00:00:00

Satellite communications emerged as a promising extension to terrestrial networks in future 6G network research due to their extensive coverage in remote areas and ability to support the increasing traffic rate and heterogeneous networks. Like other wireless communication technologies, satellite signals are transmitted in a shared medium, making them vulnerable to attacks, such as eavesdropping, jamming, and spoofing. A good candidate to overcome these issues is physical layer security (PLS), which utilizes physical layer characteristics to provide security, especially due to its suitability for resource-limited devices such as satellites and IoT devices. In this paper, we provide a thorough and up-to-date review of PLS solutions for securing satellite communication. We classify main satellite applications into five domains, namely: Satellite-terrestrial, satellite-based IoT, Satellite navigation systems, FSO-based, and inter-satellite. In each domain, we discuss and investigate how PLS can be used to improve the system's overall security, preserve some desirable security properties and resist popular attacks. Finally, we highlight a few gaps in the related literature and discuss open research problems and opportunities for leveraging PLS in satellite communication.
RISs and Sidelink Communications in Smart Cities: The Key to Seamless Localization and Sensing
Authors: Hui Chen, Hyowon Kim, Mustafa Ammous, Gonzalo Seco-Granados, George C. Alexandropoulos, Shahrokh Valaee, Henk Wymeersch
Date: 2023-01-09 00:00:00

A smart city involves, among other elements, intelligent transportation, crowd monitoring, and digital twins, each of which requires information exchange via wireless communication links and localization of connected devices and passive objects (including people). Although localization and sensing (L&S) are envisioned as core functions of future communication systems, they have inherently different demands in terms of infrastructure compared to communications. Wireless communications generally requires a connection to only a single access point (AP), while L&S demand simultaneous line-of-sight propagation paths to several APs, which serve as location and orientation anchors. Hence, a smart city deployment optimized for communication will be insufficient to meet stringent L&S requirements. In this article, we argue that the emerging technologies of reconfigurable intelligent surfaces (RISs) and sidelink communications constitute the key to providing ubiquitous coverage for L&S in smart cities with low-cost and energy-efficient technical solutions. To this end, we propose and evaluate AP-coordinated and self-coordinated RIS-enabled L&S architectures and detail three groups of application scenarios, relying on low-complexity beacons, cooperative localization, and full-duplex transceivers. A list of practical issues and consequent open research challenges of the proposed L&S systems is also provided.
Time-Varying Graph Mode Decomposition
Authors: Naveed Ur Rehman
Date: 2023-01-09 00:00:00
Tasks: Functional Connectivity

Time-varying graph signals are alternative representation of multivariate (or multichannel) signals in which a single time-series is associated with each of the nodes or vertex of a graph. Aided by the graph-theoretic tools, time-varying graph models have the ability to capture the underlying structure of the data associated with multiple nodes of a graph -- a feat that is hard to accomplish using standard signal processing approaches. The aim of this contribution is to propose a method for the decomposition of time-varying graph signals into a set of graph modes. The graph modes can be interpreted in terms of their temporal, spectral and topological characteristics. From the temporal (spectral) viewpoint, the graph modes represent the finite number of oscillatory signal components (output of multiple band-pass filters whose center frequencies and bandwidths are learned in a fully data-driven manner), similar in properties to those obtained from the empirical mode decomposition and related approaches. From the topological perspective, the graph modes quantify the functional connectivity of the graph vertices at multiple scales based on their signal content. In order to estimate the graph modes, a variational optimization formulation is designed that includes necessary temporal, spectral and topological requirements relevant to the graph modes. An efficient method to solve that problem is developed which is based on the alternating direction method of multipliers (ADMM) and the primal-dual optimization approach. Finally, the ability of the method to enable a joint analysis of the temporal and topological characteristics of time-varying graph signals, at multiple frequency bands/scales, is demonstrated on a series of synthetic and real time-varying graph data sets.