RANKING FIRMS USING REVEALED PREFERENCE.
Ontology highlight
ABSTRACT:
SUBMITTER: Sorkin I
PROVIDER: S-EPMC6070162 | biostudies-literature | 2018 Aug
REPOSITORIES: biostudies-literature
Publications
RANKING FIRMS USING REVEALED PREFERENCE.
The quarterly journal of economics 20180117 3
This article estimates workers' preferences for firms by studying the structure of employer-to-employer transitions in U.S. administrative data. The article uses a tool from numerical linear algebra to measure the central tendency of worker flows, which is closely related to the ranking of firms revealed by workers' choices. There is evidence for compensating differentials when workers systematically move to lower-paying firms in a way that cannot be accounted for by layoffs or differences in re ...[more]
Similar Datasets
Project description:Evidence-based STI (science, technology, and innovation) policy making requires accurate indicators of innovation in order to promote economic growth. However, traditional indicators from patents and questionnaire-based surveys often lack coverage, granularity as well as timeliness and may involve high data collection costs, especially when conducted at a large scale. Consequently, they struggle to provide policy makers and scientists with the full picture of the current state of the innovation system. In this paper, we propose a first approach on generating web-based innovation indicators which may have the potential to overcome some of the shortcomings of traditional indicators. Specifically, we develop a method to identify product innovator firms at a large scale and very low costs. We use traditional firm-level indicators from a questionnaire-based innovation survey (German Community Innovation Survey) to train an artificial neural network classification model on labelled (product innovator/no product innovator) web texts of surveyed firms. Subsequently, we apply this classification model to the web texts of hundreds of thousands of firms in Germany to predict whether they are product innovators or not. We then compare these predictions to firm-level patent statistics, survey extrapolation benchmark data, and regional innovation indicators. The results show that our approach produces reliable predictions and has the potential to be a valuable and highly cost-efficient addition to the existing set of innovation indicators, especially due to its coverage and regional granularity.
| S-EPMC8016297 | biostudies-literature
Project description:In this article we describe the contingent valuation and behavior methods scenario developed in the 1995 Albemarle-Pamlico Sounds Survey. The survey elicits revealed and stated preference recreation behavior data which are used to estimate the value of water quality improvements [4,8]. The survey elicits willingness to pay data which are used to conduct a split-sample scope test [7]. The data are used to jointly estimate revealed and stated preference recreation and willingness to pay data [2,6]. The data has been, and can continue to be, used to investigate econometric specification [3], bid design and other nonmarket valuation issues. The data have been used as illustrations and examples in three books that develop nonmarket valuation methods [1,5,9]. Data are supplied with this article.
| S-EPMC4510052 | biostudies-literature
Project description:BackgroundCataplexy is a loss of muscle tone that can lead to postural collapse, disturbing the daily life of narcolepsy patients; it is often triggered by positive emotions such as laughter in human patients. Narcolepsy model mice also show cataplexy, and its incidence increases in response to positive emotion-inducing stimuli such as chocolate and female courtship. Although such observation indicates a positive emotion-related nature of cataplexy in narcolepsy mice, they also show cataplexy without any apparent triggering stimulus ~ (spontaneous cataplexy). Therefore, we hypothesized that some spontaneous cataplexy in narcoleptic mice might indicate the remembering of happy moments.ResultsTo test our hypothesis, we did a conditioned place preference test on orexin/hypocretin neuron-ablated (ORX-AB) mice, one of the animal models of human narcolepsy, and counted the number of cataplexy-like behaviors. ORX-AB mice successfully remembered the chocolate-associated chamber, and the number of cataplexy-like behaviors significantly increased in the chocolate-associated chamber but not in the control chamber. In addition, ORX-AB mice remembered the aversive odor-associated chamber and avoided entering without affecting the number of cataplexy-like behaviors. Finally, similar activation of the nucleus accumbens, a positive emotion-related nucleus, was observed during both spontaneous and chocolate-induced cataplexy behaviors.ConclusionsThese results support our hypothesis and will promote the usefulness of a narcolepsy mice model in emotion research and serve as a basis for a better understanding of cataplexy in narcolepsy patients.
| S-EPMC9798626 | biostudies-literature
Project description:Many agricultural research and development programs aiming at enhancing tradeoffs related to different adoption, management and policy decisions face a methodological problem in which multi-criteria ranking is used to reach acceptable compromises between different objectives (e.g. those of farms, research managers, donors or policy makers). A typical situation is where many farm management options will result in different conflicting economic, social and environmental impacts. Ranking these options and the choice of those to promote is challenging. The literature provides a set of methodological solutions that need background data organization and simulation through coding using different computing software. Here, we provide a generic solution and friendly interface, made on Shiny (an R-package) based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). We apply this method for ranking different crop technological products of grain legumes and dry cereals based on their respective impacts on poverty, child malnutrition and economic benefits in more than 40 countries in eight different geographic zones across South Asia and Sub-Saharan Africa. • The developed algorithms and interface can help rank different options based on the weights (preferences) of their respective outcome indicators. • The interface allows for changing the weights (preferences) and automatically generates new ranking tables and graphs accordingly, which can serve for scenario simulations, which saves time compared to manually performing these calculations.
| S-EPMC8563658 | biostudies-literature
Project description:We analyze the cost of quality improvement in hospitals, dealing with two challenges. Hospital quality is multidimensional and hard to measure, while unobserved productivity may influence quality supply. We infer the quality of hospitals in Los Angeles from patient choices. We then incorporate ‘revealed quality’ into a cost function, instrumenting with hospital demand. We find that revealed quality differentiates hospitals, but is not strongly correlated with clinical quality. Revealed quality is quite costly, and tends to increase with hospital productivity. Thus, non-clinical aspects of the hospital experience (perhaps including patient amenities) play important roles in hospital demand, competition, and costs.
| S-EPMC3989349 | biostudies-literature
Project description:The distribution of firms' growth and firms' sizes is a topic under intense scrutiny. In this paper, we show that a thermodynamic model based on the maximum entropy principle, with dynamical prior information, can be constructed that adequately describes the dynamics and distribution of firms' growth. Our theoretical framework is tested against a comprehensive database of Spanish firms, which covers, to a very large extent, Spain's economic activity, with a total of 1,155,142 firms evolving along a full decade. We show that the empirical exponent of Pareto's law, a rule often observed in the rank distribution of large-size firms, is explained by the capacity of economic system for creating/destroying firms, and that can be used to measure the health of a capitalist-based economy. Indeed, our model predicts that when the exponent is larger than 1, creation of firms is favoured; when it is smaller than 1, destruction of firms is favoured instead; and when it equals 1 (matching Zipf's law), the system is in a full macroeconomic equilibrium, entailing 'free' creation and/or destruction of firms. For medium and smaller firm sizes, the dynamical regime changes, the whole distribution can no longer be fitted to a single simple analytical form and numerical prediction is required. Our model constitutes the basis for a full predictive framework regarding the economic evolution of an ensemble of firms. Such a structure can be potentially used to develop simulations and test hypothetical scenarios, such as economic crisis or the response to specific policy measures.
| S-EPMC4685849 | biostudies-other
Project description:The purpose of this article is to suggest a (preliminary) taxonomy and research agenda for the topic of "firms, crowds, and innovation" and to provide an introduction to the associated special issue. We specifically discuss how various crowd-related phenomena and practices-for example, crowdsourcing, crowdfunding, user innovation, and peer production-relate to theories of the firm, with particular attention on "sociality" in firms and markets. We first briefly review extant theories of the firm and then discuss three theoretical aspects of sociality related to crowds in the context of strategy, organizations, and innovation: (1) the functions of sociality (sociality as extension of rationality, sociality as sensing and signaling, sociality as matching and identity), (2) the forms of sociality (independent/aggregate and interacting/emergent forms of sociality), and (3) the failures of sociality (misattribution and misapplication). We conclude with an outline of future research directions and introduce the special issue papers and essays.
| S-EPMC5480604 | biostudies-other
Project description:Competition is ubiquitous in many complex biological, social, and technological systems, playing an integral role in the evolutionary dynamics of the systems. It is often useful to determine the dominance hierarchy or the rankings of the components of the system that compete for survival and success based on the outcomes of the competitions between them. Here we propose a ranking method based on the random walk on the network representing the competitors as nodes and competitions as directed edges with asymmetric weights. We use the edge weights and node degrees to define the gradient on each edge that guides the random walker towards the weaker (or the stronger) node, which enables us to interpret the steady-state occupancy as the measure of the node's weakness (or strength) that is free of unwarranted degree-induced bias. We apply our method to two real-world competition networks and explore the issues of ranking stabilization and prediction accuracy, finding that our method outperforms other methods including the baseline win-loss differential method in sparse networks.
| S-EPMC4269436 | biostudies-literature
Project description:Multi-morbidity, the health state of having two or more concurrent chronic conditions, is becoming more common as populations age, but is poorly understood. Identifying and understanding commonly occurring sets of diseases is important to inform clinical decisions to improve patient services and outcomes. Network analysis has been previously used to investigate multi-morbidity, but a classic application only allows for information on binary sets of diseases to contribute to the graph. We propose the use of hypergraphs, which allows for the incorporation of data on people with any number of conditions, and also allows us to obtain a quantitative understanding of the centrality, a measure of how well connected items in the network are to each other, of both single diseases and sets of conditions. Using this framework we illustrate its application with the set of conditions described in the Charlson morbidity index using data extracted from routinely collected population-scale, patient level electronic health records (EHR) for a cohort of adults in Wales, UK. Stroke and diabetes were found to be the most central single conditions. Sets of diseases featuring diabetes; diabetes with Chronic Pulmonary Disease, Renal Disease, Congestive Heart Failure and Cancer were the most central pairs of diseases. We investigated the differences between results obtained from the hypergraph and a classic binary graph and found that the centrality of diseases such as paraplegia, which are connected strongly to a single other disease is exaggerated in binary graphs compared to hypergraphs. The measure of centrality is derived from the weighting metrics calculated for disease sets and further investigation is needed to better understand the effect of the metric used in identifying the clinical significance and ranked centrality of grouped diseases. These initial results indicate that hypergraphs can be used as a valuable tool for analysing previously poorly understood relationships and information available in EHR data.
| S-EPMC8524321 | biostudies-literature
Project description:Different consumer groups accept new energy vehicles sequentially from the perspective of innovation diffusion theory, and the early adopter group has recently been identified. By assuming that the density of early adopters is increasing at minimum acceptable quality thresholds, this paper proposes a vertical quality differentiation model of product R&D with product subsidies. The impact of product subsidies on the R&D investment of new energy vehicle firms is discussed. We show that the early adopters' characteristics may affect the stagnant marginal R&D investment of new energy vehicle firms by increasing sales, which determines the impact mechanism of product subsidies. For firms with decreasing marginal R&D investments, insufficient R&D investments result from financial constraints. If insufficient R&D resources deter firms from conducting R&D, substantial unit subsidies invariably incentivize firms to spend their entire R&D budget. Firms with increasing marginal R&D investments, insufficient R&D profits, or financial constraints are prevented from increasing R&D investment. Product subsidies generally have a crowding-in effect on firms not subject to financial constraints, and this effect increases with the unit subsidy. However, the existence of a crowding-in effect may require sufficiently large unit subsidies. In both situations, product subsidies cannot modulate financial constraints if the firm has spent its entire R&D budget. In the first situation, we also show that product subsidies should be replaced by a funding support policy. In contrast, the second situation shows that a funding support policy should be coordinated with product subsidies.
| S-EPMC7394409 | biostudies-literature