pwc-archive/papers-with-abstracts huggingface dataset:
Has the Recession Started?
Authors: Pascal Michaillat, Emmanuel Saez
Date: 2024-08-11 00:00:00

To answer this question, we develop a new Sahm-type recession indicator that combines vacancy and unemployment data. The indicator is the minimum of the Sahm indicator -- the difference between the 3-month trailing average of the unemployment rate and its minimum over the past 12 months -- and a similar indicator constructed with the vacancy rate -- the difference between the 3-month trailing average of the vacancy rate and its maximum over the past 12 months. We then propose a two-sided recession rule: When our indicator reaches 0.3pp, a recession may have started; when the indicator reaches 0.8pp, a recession has started for sure. This new rule is triggered earlier than the Sahm rule: on average it detects recessions 0.8 month after they have started, while the Sahm rule detects them 2.1 months after their start. The new rule also has a better historical track record: it perfectly identifies all recessions since 1929, while the Sahm rule breaks down before 1960. With August 2024 data, our indicator is at 0.54pp, so the probability that the US economy is now in recession is 48%. In fact, the recession may have started as early as March 2024.
Maximal Social Welfare Relations on Infinite Populations Satisfying Permutation Invariance
Authors: Jeremy Goodman, Harvey Lederman
Date: 2024-08-11 00:00:00
Tasks: Relation

We study social welfare relations (SWRs) on an infinite population. Our main result is a new characterization of a utilitarian SWR as the \emph{largest} SWR (in terms of subset when the weak relation is viewed as a set of pairs) which satisfies Strong Pareto, Permutation Invariance (elsewhere called ``Relative Anonymity'' and ``Isomorphism Invariance''), and a further ``Quasi-Independence'' axiom.
Measuring and Controlling Fishing Capacity for Chinese Inshore Fleets
Authors: Yi Zheng
Date: 2024-08-10 00:00:00

The fishing capacity and capacity utilization for Chinese inshore fleets over the latest 13 years were measured using the DEA method. Relevant models were then established to analyze the relationships between capacity output, capacity utilization, and income, and the function of collecting taxes to control fishing capacity was quantitatively simulated. It was pointed out that the tax system would be effective for curtailing fishing capacity and improving the efficiency of the entire fishing industry in China, provided that the tax rate is not too low. Finally, it was suggested that collecting taxes at a proper rate be implemented for Chinese inshore fishing fleets.
Evaluation to Chinese marine economy in the coastal areas
Authors: Yi Zheng
Date: 2024-08-10 00:00:00

For promoting the development of the marine economy more sustainably, based on the data envelopment analysis method and combined with the impact of the marine environment, the environmental performance of the marine economy was evaluated for Chinese coastal provinces. Firstly, the classical CCR model was used. Then, a model that considered undesirable outputs was developed to suit the Chinese marine economy. Using the two models, the economic efficiencies without environmental consideration and the environmental performance index were calculated and compared. According to the results, the empirical relationship between EPI and EE, per capita GDP, and the industrial structure was analyzed. It is useful for guiding the coastal local economy of China to a healthy way.
Evaluation methods and empirical research on coastal environmental performance for Chinese harbor cities
Authors: Yi Zheng
Date: 2024-08-10 00:00:00

For controlling pollution of the marine environment while developing coastal economy, the coastal environmental performance was proposed and measured in static and dynamic methods combined with DEA and efficiency theory in this paper. With the two methods, 16 harbor cities were evaluated. The results showed the index designed in this paper can better reflect the effect to the marine environment for economy of the coastal cities.
The Economic Analysis of the Common Pool Method through the HARA Utility Functions
Authors: Mu Lin, Di Zhang, Ben Chen, Hang Zheng
Date: 2024-08-09 00:00:00

Water market is a contemporary marketplace for water trading and is deemed to one of the most efficient instruments to improve the social welfare. In modern water markets, the two widely used trading systems are an improved pair-wise trading, and a 'smart market' or common pool method. In comparison with the economic model, this paper constructs a conceptual mathematic model through the HARA utility functions. Mirroring the concepts such as Nash Equilibrium, Pareto optimal and stable matching in economy, three significant propositions are acquired which illustrate the advantages of the common pool method compared with the improved pair-wise trading.
Democratic Favor Channel
Authors: Ziho Park
Date: 2024-08-09 00:00:00
Tasks: Philosophy

A large body of literature in economics and political science examines the impact of democracy and political freedoms on various outcomes using cross-country comparisons. This paper explores the possibility that any positive impact of democracy observed in these studies might be attributed to powerful democratic nations, their allies, and international organizations treating democracies more favorably than nondemocracies, a concept I refer to as democratic favor channel. Firstly, after I control for being targeted by sanctions from G7 or the United Nations and having military confrontations and cooperation with the West, most of the positive effects of democracy on growth in cross-country panel regressions become insignificant or negatively significant. Secondly, using the same empirical specification as this literature for demonstrating intermediating forces, I show that getting sanctioned, militarily attacked, and not having defense cooperation with the West are plausible channels through which democracy causes growth. Lastly, in the pre-Soviet-collapse period, which coincides with the time when democracy promotion was less often used as a justification for sanctions, the impact of democracy on GDP per capita is already weak or negative without any additional controls, and it becomes further negative once democratic favor is controlled. These findings support the democratic favor channel and challenge the idea that the institutional qualities of democracy per se lead to desirable outcomes. The critique provided in this paper applies to the broader comparative institutions literature in social sciences and political philosophy.
Relationships between six cultural scales and ten ageism dimensions: Correlation analysis using data from 31 countries
Authors: Keisuke Kokubun
Date: 2024-08-08 00:00:00

As the aging of the world accelerates, clarifying the relationship between cultural differences and ageism is an urgent issue. Therefore, in this study, we conducted a correlation analysis between the six cultural scales of Hofstede et al. [1] and the 10 ageism scales calculated from data on 35,232 people from 31 countries included in the World Values Survey Wave 6 by Inglehart et al. [2]. The results of a partial correlation analysis controlling for economic and demographic factors showed that the cultural scales were correlated with ageism. This is the first study to show that diverse cultural scales are related to multiple dimensions of ageism.
Scarce Workers, High Wages?
Authors: Erik-Benjamin Börschlein, Mario Bossler, Martin Popp
Date: 2024-08-08 00:00:00

Labor market tightness tremendously increased in Germany between 2012 and 2022. We analyze the effect of tightness on wages by combining social security data with unusually rich information on vacancies and job seekers. Instrumental variable regressions reveal positive elasticities between 0.004 and 0.011, implying that higher tightness explains between 7 and 19 percent of the real wage increase. We report greater elasticities for new hires, high-skilled workers, the Eastern German labor market, and the service sector. In particular, tightness raised wages at the bottom of the wage distribution, contributing to the decline in wage inequality over the last decade.
Lower Bounds of Uncertainty of Observations of Macroeconomic Variables and Upper Limits on the Accuracy of Their Forecasts
Authors: Victor Olkhov
Date: 2024-08-02 00:00:00

This paper defines theoretical lower bounds of uncertainty of observations of macroeconomic variables that depend on statistical moments and correlations of random values and volumes of market trades. Any econometric assessments of macroeconomic variables have greater uncertainty. We consider macroeconomic variables as random that depend on random values and volumes of trades. To predict random macroeconomic variables, one should forecast their probabilities. Upper limits on the accuracy of the forecasts of probabilities of macroeconomic variables, prices, and returns depend on the number of predicted statistical moments. We consider economic obstacles that limit by the first two the number of predicted statistical moments. The accuracy of any forecasts of probabilities of random macroeconomic variables, prices, returns, and market trades doesn't exceed the accuracy of Gaussian approximations. Any forecasts of macroeconomic variables have uncertainty higher than one determined by predictions of coefficients of variation of random values and volumes of trades.
Identifying Restrictions on the Random Utility Model
Authors: Peter P. Caradonna, Christopher Turansick
Date: 2024-08-13 00:00:00
Tasks: model

We characterize those ex-ante restrictions on the random utility model which lead to identification. We first identify a simple class of perturbations which transfer mass from a suitable pair of preferences to the pair formed by swapping certain compatible lower contour sets. We show that two distributions over preferences are behaviorally equivalent if and only if they can be obtained from each other by a finite sequence of such transformations. Using this, we obtain specialized characterizations of which restrictions on the support of a random utility model yield identification, as well as of the extreme points of the set of distributions rationalizing a given data set. Finally, when a model depends smoothly on some set of parameters, we show that under mild topological assumptions, identification is characterized by a straightforward, local test.
Protected Income and Inequality Aversion
Authors: Marc Fleurbaey, Eduardo Zambrano
Date: 2024-08-09 00:00:00

We discover a fundamental and previously unrecognized structure within the class of additively separable social welfare functions that makes it straightforward to fully characterize and elicit the social preferences of an inequality-averse evaluator. From this structure emerges a revealing question: if a large increment can be given to one individual in a society, what is the maximal sacrifice that another individual can be asked to bear for its sake? We show that the answer uncovers the evaluator's degree of inequality aversion. In particular, all translation-invariant evaluators would sacrifice the full income of the sacrificed individual if their income were low enough and a constant amount of their income otherwise. Scale-invariant evaluators would sacrifice the full income of the sacrificed individual at all income levels if their inequality aversion was no greater than one, and a constant fraction of their income otherwise. Motivated by these findings, we propose a class of social preferences that, starting from a minimum-income level of protection, ensure a higher fraction of the sacrificed individual's income is protected the lower their income.
Dynamic choices, temporal invariance and variational discounting
Authors: Bach Dong-Xuan, Philippe Bich
Date: 2024-08-10 00:00:00

People often face trade-offs between costs and benefits occurring at various points in time. The predominant discounting approach is to use the exponential form. Central to this approach is the discount rate, a unique parameter that converts a future value into its present equivalent. However, a universally accepted discount rate remains a matter of ongoing debate and lacks consensus. This paper provides a robust solution for resolving conflicts in discount rates, which recommends considering all discount rates but aims to assign varying degrees of importance to these rates. Moreover, a considerable number of economists support a theory that suggests equal consideration of future and present utilities. In response to this debate, we introduce a general criterion capable of accommodating situations where it is feasible not to discount future utilities. This criterion encompasses and extends various existing criteria in the literature.
Recurrent Stochastic Fluctuations with Financial Speculation
Authors: Tomohiro Hirano
Date: 2024-08-09 00:00:00

Throughout history, many countries have repeatedly experienced large swings in asset prices, which are usually accompanied by large fluctuations in macroeconomic activity. One of the characteristics of the period before major economic fluctuations is the emergence of new financial products; the situation prior to the 2008 financial crisis is a prominent example of this. During that period, a variety of structured bonds, including securitized products, appeared. Because of the high returns on such financial products, many economic agents were involved in them for speculative purposes, even if they were riskier, producing macro-scale effects. With this motivation, we present a simple macroeconomic model with financial speculation. Our model illustrates two points. First, stochastic fluctuations in asset prices and macroeconomic activity are driven by the repeated appearance and disappearance of risky financial assets, rather than expansions and contractions in credit availability. Second, in an economy with sufficient borrowing and lending, the appearance of risky financial assets leads to decreased productive capital, while in an economy with severely limited borrowing and lending, it leads to increased productive capital.
Revealed Invariant Preference
Authors: Peter Caradonna, Christopher P. Chambers
Date: 2024-08-08 00:00:00
Tasks: Automated Theorem Proving

We consider the problem of rationalizing choice data by a preference satisfying an arbitrary collection of invariance axioms. Examples of such axioms include quasilinearity, homotheticity, independence-type axioms for mixture spaces, constant relative/absolute risk and ambiguity aversion axioms, stationarity for dated rewards or consumption streams, separability, and many others. We provide necessary and sufficient conditions for invariant rationalizability via a novel approach which relies on tools from the theoretical computer science literature on automated theorem proving. We also establish a generalization of the Dushnik-Miller theorem, which we use to give a complete description of the out-of-sample predictions generated by the data under any such collection of axioms.
Robust Market Design with Opaque Announcements
Authors: Aram Grigoryan, Markus Möller
Date: 2024-08-08 00:00:00

We introduce a framework where the announcements of a clearinghouse about the allocation process are opaque in the sense that there can be more than one outcome compatible with a realization of type reports. We ask whether desirable properties can be ensured under opacity in a robust sense. A property can be guaranteed under an opaque announcement if every mechanism compatible with it satisfies the property. We find an impossibility result: strategy-proofness cannot be guaranteed under any level of opacity. In contrast, in some environments, weak Maskin monotonicity and non-bossiness can be guaranteed under opacity.
SaSLaW: Dialogue Speech Corpus with Audio-visual Egocentric Information Toward Environment-adaptive Dialogue Speech Synthesis
Authors: Osamu Take, Shinnosuke Takamichi, Kentaro Seki, Yoshiaki Bando, Hiroshi Saruwatari
Date: 2024-08-13 00:00:00
Tasks: Speech Synthesis, Spoken Dialogue Systems, text-to-speech, Text to Speech

This paper presents SaSLaW, a spontaneous dialogue speech corpus containing synchronous recordings of what speakers speak, listen to, and watch. Humans consider the diverse environmental factors and then control the features of their utterances in face-to-face voice communications. Spoken dialogue systems capable of this adaptation to these audio environments enable natural and seamless communications. SaSLaW was developed to model human-speech adjustment for audio environments via first-person audio-visual perceptions in spontaneous dialogues. We propose the construction methodology of SaSLaW and display the analysis result of the corpus. We additionally conducted an experiment to develop text-to-speech models using SaSLaW and evaluate their performance of adaptations to audio environments. The results indicate that models incorporating hearing-audio data output more plausible speech tailored to diverse audio environments than the vanilla text-to-speech model.
Towards a Quantitative Analysis of Coarticulation with a Phoneme-to-Articulatory Model
Authors: Chaofei Fan, Jaimie M. Henderson, Chris Manning, Francis R. Willett
Date: 2024-08-10 00:00:00

Prior coarticulation studies focus mainly on limited phonemic sequences and specific articulators, providing only approximate descriptions of the temporal extent and magnitude of coarticulation. This paper is an initial attempt to comprehensively investigate coarticulation. We leverage existing Electromagnetic Articulography (EMA) datasets to develop and train a phoneme-to-articulatory (P2A) model that can generate realistic EMA for novel phoneme sequences and replicate known coarticulation patterns. We use model-generated EMA on 9K minimal word pairs to analyze coarticulation magnitude and extent up to eight phonemes from the coarticulation trigger, and compare coarticulation resistance across different consonants. Our findings align with earlier studies and suggest a longer-range coarticulation effect than previously found. This model-based approach can potentially compare coarticulation between adults and children and across languages, offering new insights into speech production.
Preserving spoken content in voice anonymisation with character-level vocoder conditioning
Authors: Michele Panariello, Massimiliano Todisco, Nicholas Evans
Date: 2024-08-08 00:00:00
Tasks: Automatic Speech Recognition, speech-recognition, Speech Recognition

Voice anonymisation can be used to help protect speaker privacy when speech data is shared with untrusted others. In most practical applications, while the voice identity should be sanitised, other attributes such as the spoken content should be preserved. There is always a trade-off; all approaches reported thus far sacrifice spoken content for anonymisation performance. We report what is, to the best of our knowledge, the first attempt to actively preserve spoken content in voice anonymisation. We show how the output of an auxiliary automatic speech recognition model can be used to condition the vocoder module of an anonymisation system using a set of learnable embedding dictionaries in order to preserve spoken content. Relative to a baseline approach, and for only a modest cost in anonymisation performance, the technique is successful in decreasing the word error rate computed from anonymised utterances by almost 60%.
Subjective and Objective Quality Assessment of Rendered Human Avatar Videos in Virtual Reality
Authors: Yu-Chih Chen, Avinab Saha, ALEXANDRE CHAPIRO, Christian Häne, Jean-Charles Bazin, Bo Qiu, Stefano Zanetti, Ioannis Katsavounidis, Alan C. Bovik
Date: 2024-08-13 00:00:00
Tasks: Video Compression, Video Quality Assessment, Visual Question Answering (VQA)

We study the visual quality judgments of human subjects on digital human avatars (sometimes referred to as "holograms" in the parlance of virtual reality [VR] and augmented reality [AR] systems) that have been subjected to distortions. We also study the ability of video quality models to predict human judgments. As streaming human avatar videos in VR or AR become increasingly common, the need for more advanced human avatar video compression protocols will be required to address the tradeoffs between faithfully transmitting high-quality visual representations while adjusting to changeable bandwidth scenarios. During transmission over the internet, the perceived quality of compressed human avatar videos can be severely impaired by visual artifacts. To optimize trade-offs between perceptual quality and data volume in practical workflows, video quality assessment (VQA) models are essential tools. However, there are very few VQA algorithms developed specifically to analyze human body avatar videos, due, at least in part, to the dearth of appropriate and comprehensive datasets of adequate size. Towards filling this gap, we introduce the LIVE-Meta Rendered Human Avatar VQA Database, which contains 720 human avatar videos processed using 20 different combinations of encoding parameters, labeled by corresponding human perceptual quality judgments that were collected in six degrees of freedom VR headsets. To demonstrate the usefulness of this new and unique video resource, we use it to study and compare the performances of a variety of state-of-the-art Full Reference and No Reference video quality prediction models, including a new model called HoloQA. As a service to the research community, we publicly releases the metadata of the new database at https://live.ece.utexas.edu/research/LIVE-Meta-rendered-human-avatar/index.html.
Feature-Preserving Rate-Distortion Optimization in Image Coding for Machines
Authors: Samuel Fernández Menduiña, Eduardo Pavez, Antonio Ortega
Date: 2024-08-13 00:00:00
Tasks: Dimensionality Reduction

With the increasing number of images and videos consumed by computer vision algorithms, compression methods are evolving to consider both perceptual quality and performance in downstream tasks. Traditional codecs can tackle this problem by performing rate-distortion optimization (RDO) to minimize the distance at the output of a feature extractor. However, neural network non-linearities can make the rate-distortion landscape irregular, leading to reconstructions with poor visual quality even for high bit rates. Moreover, RDO decisions are made block-wise, while the feature extractor requires the whole image to exploit global information. In this paper, we address these limitations in three steps. First, we apply Taylor's expansion to the feature extractor, recasting the metric as an input-dependent squared error involving the Jacobian matrix of the neural network. Second, we make a localization assumption to compute the metric block-wise. Finally, we use randomized dimensionality reduction techniques to approximate the Jacobian. The resulting expression is monotonic with the rate and can be evaluated in the transform domain. Simulations with AVC show that our approach provides bit-rate savings while preserving accuracy in downstream tasks with less complexity than using the feature distance directly.