pwc-archive/papers-with-abstracts huggingface dataset:
Stochastic Equilibrium the Lucas Critique and Keynesian Economics
Authors: David Staines
Date: 2023-12-23 00:00:00

In this paper, a mathematically rigorous solution overturns existing wisdom regarding New Keynesian Dynamic Stochastic General Equilibrium. I develop a formal concept of stochastic equilibrium. I prove uniqueness and necessity, when agents are patient, with general application. Existence depends on appropriately specified eigenvalue conditions. Otherwise, no solution of any kind exists. I construct the equilibrium with Calvo pricing. I provide novel comparative statics with the non-stochastic model of mathematical significance. I uncover a bifurcation between neighbouring stochastic systems and approximations taken from the Zero Inflation Non-Stochastic Steady State (ZINSS). The correct Phillips curve agrees with the zero limit from the trend inflation framework. It contains a large lagged inflation coefficient and a small response to expected inflation. Price dispersion can be first or second order depending how shocks are scaled. The response to the output gap is always muted and is zero at standard parameters. A neutrality result is presented to explain why and align Calvo with Taylor pricing. Present and lagged demand shocks enter the Phillips curve so there is no Divine Coincidence and the system is identified from structural shocks alone. The lagged inflation slope is increasing in the inflation response, embodying substantive policy trade-offs. The Taylor principle is reversed, inactive settings are necessary, pointing towards inertial policy. The observational equivalence idea of the Lucas critique is disproven. The bifurcation results from the breakdown of the constraints implied by lagged nominal rigidity, associated with cross-equation cancellation possible only at ZINSS. There is a dual relationship between restrictions on the econometrician and constraints on repricing firms. Thus, if the model is correct, goodness of fit will jump.
Discounting the distant future: What do historical bond prices imply about the long term discount rate?
Authors: J. Doyne Farmer, John Geanakoplos, Matteo G. Richiardi, Miquel Montero, Josep Perelló, Jaume Masoliver
Date: 2023-12-28 00:00:00

We present a thorough empirical study on real interest rates by also including risk aversion through the introduction of the market price of risk. With the view of complex systems science and its multidisciplinary approach, we use the theory of bond pricing to study the long term discount rate. Century-long historical records of 3 month bonds, 10 year bonds, and inflation allow us to estimate real interest rates for the UK and the US. Real interest rates are negative about a third of the time and the real yield curves are inverted more than a third of the time, sometimes by substantial amounts. This rules out most of the standard bond pricing models, which are designed for nominal rates that are assumed to be positive. We therefore use the Ornstein-Uhlenbeck model which allows negative rates and gives a good match to inversions of the yield curve. We derive the discount function using the method of Fourier transforms and fit it to the historical data. The estimated long term discount rate is $1.7$ \% for the UK and $2.2$ \% for the US. The value of $1.4$ \% used by Stern is less than a standard deviation from our estimated long run return rate for the UK, and less than two standard deviations of the estimated value for the US. All of this once more reinforces the support for immediate and substantial spending to combat climate change.
Further Education During Unemployment
Authors: Pauline Leung, Zhuan Pei
Date: 2023-12-28 00:00:00

Evidence on the effectiveness of retraining U.S. unemployed workers primarily comes from evaluations of training programs, which represent one narrow avenue for skill acquisition. We use high-quality records from Ohio and a matching method to estimate the effects of retraining, broadly defined as enrollment in postsecondary institutions. Our simple method bridges two strands of the dynamic treatment effect literature that estimate the treatment-now-versus-later and treatment-versus-no-treatment effects. We find that enrollees experience earnings gains of six percent three to four years after enrolling, after depressed earnings during the first two years. The earnings effects are driven by industry-switchers, particularly to healthcare.
Health-related Quality of life, Financial Toxicity, Productivity Loss and Catastrophic Health Expenditures After Lung Cancer Diagnosis in Argentina
Authors: Lucas Gonzalez, Andrea Alcaraz, Carolina Gabay, Monica Castro, Silvina Vigo, Eduardo Carinci, Federico Augustovski
Date: 2023-12-27 00:00:00
Tasks: Lung Cancer Diagnosis

Objective: About 12,000 people are diagnosed with lung cancer (LC) each year in Argentina, and the diagnosis has a significant personal and family. The objective of this study was to characterize the Health-Related Quality of Life (HRQoL) and the economic impact in patients with LC and in their households. Methods: Observational cross-sectional study, through validated structured questionnaires to patients with a diagnosis of Non-Small Cell Lung Cancer (NSCLC) in two referral public health care centers in Argentina. Questionnaries used: Health-Related Quality of life (EuroQol EQ-5D-3L questionnaire); financial toxicity (COST questionnaire); productivity loss (WPAI-GH, Work Productivity and Activity Impairment Questionnaire: General Health), and out-of-pocket expenses. Results: We included 101 consecutive patients (mean age 67.5 years; 55.4% men; 57.4% with advanced disease -stage III/IV-). The mean EQ-VAS was 68.8 (SD:18.3), with 82.2% describing fair or poor health. The most affected dimensions were anxiety/depression, pain, and activities of daily living. Patients reported an average 59% decrease in their ability to perform regular daily activities as measured by WPAI-GH. 54.5% reported a reduction in income due to the disease, and 19.8% lost their jobs. The annual economic productivity loss was estimated at USD 2,465 per person. 70.3%) of patients reported financial toxicity. The average out-of-pocket expenditure was USD 100.38 per person per month, which represented 18.5% of household income. Catastrophic expenditures were present in 37.1% of households. When performing subgroup analysis by disease severity, all outcomes were worse in the subpopulation with advanced disease. Conclusions Patients with NSCLC treated in public hospitals in Argentina have significant health-related quality of life and economic impact, worsening in patients with advanced disease.
The Green Advantage: Analyzing the Effects of Eco-Friendly Marketing on Consumer Loyalty
Authors: Erfan Mohammadi, MohammadMahdi Barzegar, Mahdi Nohekhan
Date: 2023-12-27 00:00:00
Tasks: Marketing

The idea that marketing, in addition to profitability and sales, should also consider the consumer's health is not and has not been a far-fetched concept. It can be stated that there is no longer a way back to producing environmentally harmful products, and gradually, governmental pressures, competition, and changing customer attitudes are obliging companies to adopt and implement a green marketing approach. Over time, concepts such as green marketing have penetrated marketing literature, making environmental considerations one of the most important activities of companies. For this purpose, this research examines the effects of green marketing strategy on brand loyalty (case study: food exporting companies). The population of this study consists of 345 employees and managers of companies like Kalleh, Solico, Pemina, Sorben, Mac, Pol, and Casel, out of which 182 were randomly selected as a sample using Cochran's formula. This research is practical; the required data were collected through a survey and questionnaire. The research results indicate that (1) green marketing strategy significantly affects brand loyalty. (2) Green products have a significant positive effect on brand loyalty. (3) Green promotion has a significant positive effect on brand loyalty. (4) Green distribution has a significant positive effect on brand loyalty. (5) Green pricing has a significant positive effect on brand loyalty.
Valuing Open Defecation Free Surroundings: Experimental Evidence from a Norm-Based Intervention in India
Authors: Sania Ashraf, Cristina Bicchieri, Upasak Das. Alex Shpenev
Date: 2023-12-23 00:00:00

Open defecation, which is linked with poor health outcomes, lower cognitive ability and productivity, has been widespread in India. This paper assesses the impact of a randomized norm-centric intervention implemented in peri-urban areas of Tamil Nadu in India on raising the value attached to residence in areas with a lower prevalence of open defecation, measured through Willingness to Pay (WTP). The intervention aimed to change social expectations about toilet usage through audio announcements, wall paintings, household visits, and community meetings. The findings indicate a significant increase in the WTP for relocating to areas with lower prevalence of open defecation. The results are consistent when using local average treatment effect estimations wherein the possibility of spillovers in the control areas is accounted for. They are also robust to potential bias due to local socio-political events during the study period and COVID-led attrition. We further observe a significant increase in toilet ownership and usage. While assessing the mechanism, we find that change in empirical expectations through the intervention (what one believes about the prevalence of toilet usage in the community) is one of the primary mediating channels. Normative expectations (what one believes about community approval of toilet usage) are found to have limited effect. The findings underscore the need for norm-centric interventions to propel change in beliefs and achieve long-term and sustainable sanitation behavior.
Image Restoration by Denoising Diffusion Models with Iteratively Preconditioned Guidance
Authors: Tomer Garber, Tom Tirer
Date: 2023-12-27 00:00:00
Proceeding: CVPR 2024 1
Tasks: Deblurring, Denoising, Image Deblurring, Image Restoration, Super-Resolution

Training deep neural networks has become a common approach for addressing image restoration problems. An alternative for training a "task-specific" network for each observation model is to use pretrained deep denoisers for imposing only the signal's prior within iterative algorithms, without additional training. Recently, a sampling-based variant of this approach has become popular with the rise of diffusion/score-based generative models. Using denoisers for general purpose restoration requires guiding the iterations to ensure agreement of the signal with the observations. In low-noise settings, guidance that is based on back-projection (BP) has been shown to be a promising strategy (used recently also under the names "pseudoinverse" or "range/null-space" guidance). However, the presence of noise in the observations hinders the gains from this approach. In this paper, we propose a novel guidance technique, based on preconditioning that allows traversing from BP-based guidance to least squares based guidance along the restoration scheme. The proposed approach is robust to noise while still having much simpler implementation than alternative methods (e.g., it does not require SVD or a large number of iterations). We use it within both an optimization scheme and a sampling-based scheme, and demonstrate its advantages over existing methods for image deblurring and super-resolution.
Toward Accurate and Temporally Consistent Video Restoration from Raw Data
Authors: Shi Guo, jianqi ma, Xi Yang, Zhengqiang Zhang, Lei Zhang
Date: 2023-12-25 00:00:00
Tasks: Demosaicking, Denoising, Video Denoising, Video Restoration

Denoising and demosaicking are two fundamental steps in reconstructing a clean full-color video from raw data, while performing video denoising and demosaicking jointly, namely VJDD, could lead to better video restoration performance than performing them separately. In addition to restoration accuracy, another key challenge to VJDD lies in the temporal consistency of consecutive frames. This issue exacerbates when perceptual regularization terms are introduced to enhance video perceptual quality. To address these challenges, we present a new VJDD framework by consistent and accurate latent space propagation, which leverages the estimation of previous frames as prior knowledge to ensure consistent recovery of the current frame. A data temporal consistency (DTC) loss and a relational perception consistency (RPC) loss are accordingly designed. Compared with the commonly used flow-based losses, the proposed losses can circumvent the error accumulation problem caused by inaccurate flow estimation and effectively handle intensity changes in videos, improving much the temporal consistency of output videos while preserving texture details. Extensive experiments demonstrate the leading VJDD performance of our method in term of restoration accuracy, perceptual quality and temporal consistency. Codes and dataset are available at \url{https://github.com/GuoShi28/VJDD}.
A Generalization of the Convolution Theorem and its Connections to Non-Stationarity and the Graph Frequency Domain
Authors: Alberto Natali, Geert Leus
Date: 2023-12-28 00:00:00

In this paper, we present a novel convolution theorem which encompasses the well known convolution theorem in (graph) signal processing as well as the one related to time-varying filters. Specifically, we show how a node-wise convolution for signals supported on a graph can be expressed as another node-wise convolution in a frequency domain graph, different from the original graph. This is achieved through a parameterization of the filter coefficients following a basis expansion model. After showing how the presented theorem is consistent with the already existing body of literature, we discuss its implications in terms of non-stationarity. Finally, we propose a data-driven algorithm based on subspace fitting to learn the frequency domain graph, which is then corroborated by experimental results on synthetic and real data.
Reconfigurable Intelligent Surface Deployment for Wideband Millimeter Wave Systems
Authors: Xiaohao Mo, Lin Gui, Kai Ying, Xichao Sang, Xiaqing Diao
Date: 2023-12-28 00:00:00

The performance of wireless communication systems is fundamentally constrained by random and uncontrollable wireless channels. Recently, reconfigurable intelligent surfaces (RIS) has emerged as a promising solution to enhance wireless network performance by smartly reconfiguring the radio propagation environment. While significant research has been conducted on RIS-assisted wireless systems, this paper focuses specifically on the deployment of RIS in a wideband millimeter wave (mmWave) multiple-input-multiple-output (MIMO) system to achieve maximum sum-rate. First, we derive the average user rate as well as the lower bound rate when the covariance of the channel follows the Wishart distribution. Based on the lower bound of users' rate, we propose a heuristic method that transforms the problem of optimizing the RIS's orientation into maximizing the number of users served by the RIS. Simulation results show that the proposed RIS deployment strategy can effectively improve the sum-rate. Furthermore, the performance of the proposed RIS deployment algorithm is only approximately 7.6\% lower on average than that of the exhaustive search algorithm.
On Chernoff Lower-Bound of Outage Threshold for Non-Central $χ^2$-Distributed Beamforming Gain in URLLC Systems
Authors: Jinfei Wang, Yi Ma, Rahim Tafazolli, Zhibo Pang
Date: 2023-12-28 00:00:00

The cumulative distribution function (CDF) of a non-central $\chi^2$-distributed random variable (RV) is often used when measuring the outage probability of communication systems. For ultra-reliable low-latency communication (URLLC), it is important but mathematically challenging to determine the outage threshold for an extremely small outage target. This motivates us to investigate lower bounds of the outage threshold, and it is found that the one derived from the Chernoff inequality (named Cher-LB) is the most effective lower bound. This finding is associated with three rigorously established properties of the Cher-LB with respect to the mean, variance, reliability requirement, and degrees of freedom of the non-central $\chi^2$-distributed RV. The Cher-LB is then employed to predict the beamforming gain in URLLC for both conventional multi-antenna systems (i.e., MIMO) under first-order Markov time-varying channel and reconfigurable intellgent surface (RIS) systems. It is exhibited that, with the proposed Cher-LB, the pessimistic prediction of the beamforming gain is made sufficiently accurate for guaranteed reliability as well as the transmit-energy efficiency.
6D Radar Sensing and Tracking in Monostatic Integrated Sensing and Communications System
Authors: Hongliang Luo, Feifei Gao, Fan Liu, Shi Jin
Date: 2023-12-27 00:00:00
Tasks: ISAC

In this paper, we propose a novel scheme for sixdimensional (6D) radar sensing and tracking of dynamic target based on multiple input and multiple output (MIMO) array for monostatic integrated sensing and communications (ISAC) system. Unlike most existing ISAC studies believing that only the radial velocity of far-field dynamic target can be measured based on one single base station (BS), we find that the sensing echo channel of MIMO-ISAC system actually includes the distance, horizontal angle, pitch angle, radial velocity, horizontal angular velocity, and pitch angular velocity of the dynamic target. Thus we may fully rely on one single BS to estimate the dynamic target's 6D motion parameters from the sensing echo signals. Specifically, we first propose the long-term motion and short-term motion model of dynamic target, in which the short-term motion model serves the single-shot sensing of dynamic target, while the long-term motion model serves multiple-shots tracking of dynamic target. As a step further, we derive the sensing channel model corresponding to the short-term motion. Next, for singleshot sensing, we employ the array signal processing methods to estimate the dynamic target's horizontal angle, pitch angle, distance, and virtual velocity. By realizing that the virtual velocities observed by different antennas are different, we adopt plane fitting to estimate the radial velocity, horizontal angular velocity, and pitch angular velocity of dynamic target. Furthermore, we implement the multiple-shots tracking of dynamic target based on each single-shot sensing results and Kalman filtering. Simulation results demonstrate the effectiveness of the proposed 6D radar sensing and tracking scheme.
Electromagnetic Property Sensing: A New Paradigm of Integrated Sensing and Communication
Authors: Yuhua Jiang, Feifei Gao, Shi Jin
Date: 2023-12-27 00:00:00
Tasks: Compressive Sensing, Integrated sensing and communication, ISAC, Material Classification

Integrated sensing and communication (ISAC) has opened up numerous game-changing opportunities for future wireless systems. In this paper, we develop a novel scheme that utilizes orthogonal frequency division multiplexing (OFDM) pilot signals in ISAC systems to sense the electromagnetic (EM) property of the target and thus also identify the material of the target. Specifically, we first establish an end-to-end EM propagation model by means of Maxwell equations, where the EM property of the target is captured by a closed-form expression of the ISAC channel, incorporating the Lippmann-Schwinger equation and the method of moments (MOM) for discretization. We then model the relative permittivity and conductivity distribution (RPCD) within a specified detection region. Based on the sensing model, we introduce a multi-frequency-based EM property sensing method by which the RPCD can be reconstructed from compressive sensing techniques that exploits the joint sparsity structure of the EM property vector. To improve the sensing accuracy, we design a beamforming strategy from the communications transmitter based on the Born approximation that can minimize the mutual coherence of the sensing matrix. The optimization problem is cast in terms of the Gram matrix and is solved iteratively to obtain the optimal beamforming matrix. Simulation results demonstrate the efficacy of the proposed method in achieving high-quality RPCD reconstruction and accurate material classification. Furthermore, improvements in RPCD reconstruction quality and material classification accuracy are observed with increased signal-to-noise ratio (SNR) or reduced target-transmitter distance.
Radar detection of wake vortex behind the aircraft: the detection range problem
Authors: Jiangkun Gong, Jun Yan, Deyong Kong, Deren Li
Date: 2023-12-27 00:00:00

In this study, we showcased the detection of the wake vortex produced by a medium aircraft at distances exceeding 10 km using an X-band pulse-Doppler radar. We analyzed radar signals within the range profiles behind a Boeing 737 aircraft on February 7, 2021, within the airspace of the Runway Protection Zone (RPZ) at Tianhe Airport, Wuhan, China. The findings revealed that the wake vortex extended up to 6 km from the aircraft, which is 10 km from the radar, displaying distinct stages characterized by scattering patterns and Doppler signatures. Despite the wake vortex exhibiting a scattering power approximately 10 dB lower than that of the aircraft, its Doppler Signal-to-Clutter Ratio (DSCR) values were only 5 dB lower, indicating a notably strong scattering power within a single radar bin. Additionally, certain radar parameters proved inconsistent in the stable detection and tracking of wake vortex, aligning with our earlier concept of cognitive micro-Doppler radar.
K-Space Beamforming for an Array of Quantum Sensors
Authors: Peter Vouras
Date: 2023-12-27 00:00:00

In this paper we present a novel beamforming technique that can be used with an array of quantum sensors. The transmit waveform is a short-duration frequency comb constructed using a finite number of sinusoidal tones separated by a fixed offset. Each element in the array is tuned to one of the tones. When the radiated signal is received by the aperture, each array element accumulates phase at a different rate since it is matched to only one frequency component of the comb waveform. The result is that over the duration of the received pulse, progressively higher spatial frequencies are generated across the aperture. By summing the outputs of all the array elements, a strong peak is created in k-space at the precise time instant when the phases of all the array elements align. The k-space coordinates of the output can then be transformed to angles as discussed in the paper. This paper also describes how to set waveform parameters and the separation between array elements. A desirable advantage of the proposed approach is that the received signal is amplified by the coherent integration gain of the entire spatial aperture.
Sharp inequality for $\ell_p$ quasi-norm and $\ell_q$-norm with $0<p\leq 1$ and $q>1$
Authors: Zenghui Zhang
Date: 2023-12-27 00:00:00

A sharp inequality for $\ell_p$ quasi-norm with $0<p\leq 1$ and $\ell_q$-norm with $q>1$ is derived, which shows that the difference between $\|\textbf{\textit{x}}\|_p$ and $\|\textbf{\textit{x}}\|_q$ of an $n$-dimensional signal $\textbf{\textit{x}}$ is upper bounded by the difference between the maximum and minimum absolute value in $\textbf{\textit{x}}$. The inequality could be used to develop new $\ell_p$-minimization algorithms.