Languages and future-oriented economic behavior-Experimental evidence for causal effects.

Studies have shown that the use of languages which grammatically associate the future and the present tends to correlate with more future-oriented behavior. We take an experimental approach to go beyond correlation. We asked bilingual research participants, people fluent in two languages (12 language pairs) which differ in the way they encode time, to make a set of future-oriented economic decisions. We find that participants addressed in a language in which the present and the future are marked more distinctly tended to value future events less than participants addressed in a language in which the present and the future are similarly marked. In an additional experiment, bilingual research participants (seven language pairs) were asked to choose whether they wish to complete a more enjoyable task first or later (delayed gratification). When addressed in a language in which the present and the future are marked more distinctly, participants tended to prefer immediate gratification more than when addressed in a language in which the present and the future are marked less distinctly. We shed light on the mechanism in a within-person experiment in which bilingual research participants (nine language pairs) were asked to spatially mark the distance between the present and the future. When participants were addressed in a language in which the present and the future are marked more distinctly, they tended to express more precise temporal beliefs compared with when addressed in a language in which the present and the future are marked less distinctly.

Characteristics of Prescription Drug Fills Using Pharmacy-Pharmacy Benefit Manager Discount Programs: The "GoodRx" Model.

OBJECTIVES: This study aimed to characterize products using pharmacy-pharmacy benefit manager (PBM) discounts and to estimate the association among such discounts, prescription utilization, and out-of-pocket costs. METHODS: This is a retrospective cohort study using IQVIA's Formulary Impact Analyzer, which contains anonymized, individual-level pharmacy claims representing US retail pharmacy transactions. We focused on 20 products with the greatest number of transactions using a pharmacy-PBM discount. Our unit of analysis was a treatment episode, defined as the length of time from an incident fill to no continuous use for 60 consecutive days after allowing for indefinite stockpiling. Outcome measures included products with greatest pharmacy-PBM discount use, characteristics of treatment episodes, and out-of-pocket costs with and without pharmacy-PBM discount. RESULTS: Across all products, 3.82% of transactions and 7.69% of treatment episodes were accompanied by a pharmacy-PBM discount. Commonly discounted products included generic treatments for chronic disease (lisinopril, levothyroxine, metformin) and neuropsychiatric conditions (alprazolam, amphetamine, buprenorphine, hydrocodone). The median postdiscount out-of-pocket cost was >2.5-fold higher during treatment episodes with a discount than those without ($15.15, interquartile range [IQR] $8.53-32.00, vs $5.88, IQR $1.40-15.00). Median treatment episode duration was 249 days (IQR 132-418) with discount use compared with 236 days (IQR 121-396) without discount use, although treatment episodes that began with a discount had fewer transactions per treatment episode and were shorter (median 212 days, IQR 114-360) than those that did not (313 days, IQR 178-500). CONCLUSIONS: Pharmacy-PBM discounts may foster market competition and improve access for under- and uninsured individuals; however, these programs may not generate savings for many insured individuals.

It Is Time to Reconsider the 3% Discount Rate.

OBJECTIVES: Health technology assessment (HTA) guidance often recommends a 3% real annual discount rate, the appropriateness of which has received limited attention. This article seeks to identify an appropriate rate for high-income countries because it can influence projected cost-effectiveness and hence resource allocation recommendations. METHODS: The author conducted 2 Pubmed.gov searches. The first sought articles on the theory for selecting a rate. The second sought HTA guidance documents. RESULTS: The first search yielded 21 articles describing 2 approaches. The "Ramsey Equation" sums contributions by 4 factors: pure time preference, catastrophic risk, wealth effect, and macroeconomic risk. The first 3 factors increase the discount rate because they indicate future impacts are less important, whereas the last, suggesting greater future need, decreases the discount rate. A fifth factor-project-specific risk-increases the discount rate but does not appear in the Ramsey Equation. Market interest rates represent a second approach for identifying a discount rate because they represent competing investment returns and hence opportunity costs. The second search identified HTA guidelines for 32 high-income countries. Twenty-two provide no explicit rationale for their recommended rates, 8 appeal to market interest rates, 3 to consistency, and 3 to Ramsey Equation factors. CONCLUSIONS: Declining consumption growth and real interest rates imply HTA guidance should reduce recommended discount rates to 1.5 to 2+%. This change will improve projected cost-effectiveness for therapies with long-term benefits and increase the impact of accounting for long-term drug price dynamics, including reduced prices attending loss of market exclusivity.

Scale and rate heterogeneity in the EQ-5D-5L valuation.

OBJECTIVES: To estimate values on a quality-adjusted life year (QALY) scale using individual preference evidence, choice analyses typically include ancillary parameters, such as scale factors and discount rates. These parameters potentially differ among respondents. In this study, we investigated how allowing heterogeneity in scale and rate affects the estimation of EQ-5D-5L values. METHODS: Using the first wave of the 2016 EQ-5D-5L valuation study (N = 1017), we estimated a conditional logit (CL) model and three mixed logit models: random scale, random rate, and bivariate. Prior to the exploratory study, we hypothesized that scale and rate are correlated and that allowing heterogeneity in both parameters decreases the number of insignificant incremental effects. We confirmed the exploratory findings by re-estimating these models using paired comparison responses from a second wave (N = 1229). RESULTS: Scale and rate exhibited significant heterogeneity and were positively correlated. As hypothesized, allowing this heterogeneity improved the face validity of the EQ-5D-5L value set by reducing the number of insignificant incremental effects (from 6 to 2 p-values > 0.05; out of 20). Nevertheless, the CL and bivariate mixed logit estimates are highly correlated and concordant (Pearson correlation coefficient of 0.897, Spearman correlation coefficient of 0.888, Lin's concordance coefficient of 0.763). CONCLUSIONS: Allowing this heterogeneity adds three parameters to the estimation (two variances and a correlation) and improves the face validity of the EQ-5D-5L values. This finding may influence experimental design and choice analysis in health valuation more generally.

A systematic review on the appropriate discounting rates for the economic evaluation of gene therapies: whether a specific approach is justified to tackle the challenges?

OBJECTIVES: Discounting the cost and effect for health intervention is a controversial topic over the last two decades. In particular, the cost-effectiveness of gene therapies is especially sensitive to the discount rate because of the substantial delay between the upfront cost incurred and long-lasing clinical benefits received. This study aims to investigate the influence of employing alternative discount rates on the incremental cost-effectiveness ratio (ICER) of gene therapies. METHODS: A systematic review was conducted to include health economic evaluations of gene therapies that were published until April 2023. RESULTS: Sensitivity or scenario analysis indicated that discount rate represented one of the most influential factors for the ICERs of gene therapies. Discount rate for cost and benefit was positively correlated with the cost-effectiveness of gene therapies, that is, a lower discount rate significantly improves the ICERs. The alternative discount rate employed in some cases could be powerful to alter the conclusion on whether gene therapies are cost-effective and acceptable for reimbursement. CONCLUSIONS: Although discount rate will have substantial influence on the ICERs of gene therapies, there lacks solid evidence to justify a different discounting rule for gene therapies. However, it is proposed that the discount rate in the reference case should be updated to reflect the real-time preference, which in turn will affect the ICERs and reimbursement of gene therapies more profoundly than conventional therapies.

Enhancing supply chain relationships in the circular economy: Strategies for a green centralized supply chain with deteriorating products.

This article introduces a green centralized supply chain in a two-stage stochastic programming model using deteriorating products. The model reduces the cost of purchasing, transporting, storing, product recovery and shortages. This cuts down on greenhouse emission related to transportation, product recovery, and recycling programs. On the basis of this, we explore the utilization of the circular economy to the damages that could occur from used products. Furthermore, revenue sharing and quantity discount contracts are examined in the business models between the members of the supply chain and the external manufacturer. Demand is assumed to be uncertain, and scenarios are created to account this. The model specifies the optimal order quantities, transportation modes and contract terms that minimize costs and environmental impacts. Numerical examples analyze the trade-offs between economic and environmental objectives under different supply chain parameters. The results provide insights for circular supply chains that reconcile economic incentives with environmental responsibility for deteriorating product.

A New Evidence Weight Combination and Probability Allocation Method in Multi-Sensor Data Fusion.

A single sensor is prone to decline recognition accuracy in the face of a complex environment, while the existing multi-sensor evidence theory fusion methods do not comprehensively consider the impact of evidence conflict and fuzziness. In this paper, a new evidence weight combination and probability allocation method is proposed, which calculated the degree of evidence fuzziness through the maximum entropy principle, and also considered the impact of evidence conflict on fusing results. The two impact factors were combined to calculate the trusted discount and reallocate the probability function. Finally, Dempster's combination rule was used to fuse every piece of evidence. On this basis, experiments were first conducted to prove that the existing weight combination methods produce results contrary to common sense when handling high-conflicting and high-clarity evidence, and then comparative experiments were conducted to prove the effectiveness of the proposed evidence weight combination and probability allocation method. Moreover, it was verified, on the PAMAP2 data set, that the proposed method can obtain higher fusing accuracy and more reliable fusing results in all kinds of behavior recognition. Compared with the traditional methods and the existing improved methods, the weight allocation method proposed in this paper dynamically adjusts the weight of fuzziness and conflict in the fusing process and improves the fusing accuracy by about 3.3% and 1.7% respectively which solved the limitations of the existing weight combination methods.

Should Severity Assessments in Healthcare Priority Setting be Risk- and Time-Sensitive?

BACKGROUND: Severity plays an essential role in healthcare priority setting. Still, severity is an under-theorised concept. One controversy concerns whether severity should be risk- and/or time-sensitive. The aim of this article is to provide a normative analysis of this question. METHODS: A reflective equilibrium approach is used, where judgements and arguments concerning severity in preventive situations are related to overall normative judgements and background theories in priority-setting, aiming for consistency. Analysis, discussion, and conclusions: There is an argument for taking the risk of developing a condition into account, and we do this when we consider the risk of dying in the severity assessment. If severity is discounted according to risk, this will 'dilute' severity, depending on how well we are able to delineate the population, which is dependent on the current level of knowledge. This will potentially have a more far-reaching effect when considering primary prevention, potentially the de-prioritisation of effective preventive treatments in relation to acute, less-effective treatments. The risk arguments are dependent on which population is being assessed. If we focus on the whole population at risk, with T0 as the relevant population, this supports the risk argument. If we instead focus on the population of as-yet (at T0) unidentified individuals who will develop the condition at T1, risk will become irrelevant, and severity will not be risk sensitive. The strongest argument for time-sensitive severity (or for discounting future severity) is the future development of technology. On a short timescale, this will differ between different diagnoses, supporting individualised discounting. On a large timescale, a more general discounting might be acceptable. However, we need to also consider the systemic effects of allowing severity to be risk- and time-sensitive.

Identifying essential proteins from protein-protein interaction networks based on influence maximization.

BACKGROUND: Essential proteins are indispensable to the development and survival of cells. The identification of essential proteins not only is helpful for the understanding of the minimal requirements for cell survival, but also has practical significance in disease diagnosis, drug design and medical treatment. With the rapidly amassing of protein-protein interaction (PPI) data, computationally identifying essential proteins from protein-protein interaction networks (PINs) becomes more and more popular. Up to now, a number of various approaches for essential protein identification based on PINs have been developed. RESULTS: In this paper, we propose a new and effective approach called iMEPP to identify essential proteins from PINs by fusing multiple types of biological data and applying the influence maximization mechanism to the PINs. Concretely, we first integrate PPI data, gene expression data and Gene Ontology to construct weighted PINs, to alleviate the impact of high false-positives in the raw PPI data. Then, we define the influence scores of nodes in PINs with both orthological data and PIN topological information. Finally, we develop an influence discount algorithm to identify essential proteins based on the influence maximization mechanism. CONCLUSIONS: We applied our method to identifying essential proteins from saccharomyces cerevisiae PIN. Experiments show that our iMEPP method outperforms the existing methods, which validates its effectiveness and advantage.

Adapting paths against zero-determinant strategies in repeated prisoner's dilemma games.

Long-term cooperation, competition, or exploitation among individuals can be modeled through repeated games. In repeated games, Press and Dyson discovered zero-determinant (ZD) strategies that enforce a special relationship between two players. This special relationship implies that a ZD player can unilaterally impose a linear payoff relationship to the opponent regardless of the opponent's strategies. A ZD player also has a property that can lead the opponent to an unconditional cooperation if the opponent tries to improve its payoff. This property has been mathematically confirmed by Chen and Zinger. Humans often underestimate a payoff obtained in the future. However, such discounting was not considered in their analysis. Here, we mathematically explored whether a ZD player can lead the opponent to an unconditional cooperation even if a discount factor is incorporated. Specifically, we represented the expected payoff with a discount factor as the form of determinants and calculated whether the values obtained by partially differentiating each factor in the strategy vector become positive. As a result, we proved that the strategy vector ends up as an unconditional cooperation even when starting from any initial strategy. This result was confirmed through numerical calculations. We extended the applicability of ZD strategies to real world problems.

Adaptive Discount Factor for Deep Reinforcement Learning in Continuing Tasks with Uncertainty.

Reinforcement learning (RL) trains an agent by maximizing the sum of a discounted reward. Since the discount factor has a critical effect on the learning performance of the RL agent, it is important to choose the discount factor properly. When uncertainties are involved in the training, the learning performance with a constant discount factor can be limited. For the purpose of obtaining acceptable learning performance consistently, this paper proposes an adaptive rule for the discount factor based on the advantage function. Additionally, how to use the advantage function in both on-policy and off-policy algorithms is presented. To demonstrate the performance of the proposed adaptive rule, it is applied to PPO (Proximal Policy Optimization) for Tetris in order to validate the on-policy case, and to SAC (Soft Actor-Critic) for the motion planning of a robot manipulator to validate the off-policy case. In both cases, the proposed method results in a better or similar performance compared with cases using the best constant discount factors found by exhaustive search. Hence, the proposed adaptive discount factor automatically finds a discount factor that leads to comparable training performance, and that can be applied to representative deep reinforcement learning problems.

Measurement of China's provincial social cost of carbon under the integrated socioeconomic-climate framework.

The social cost of carbon is a tool for assessing the appropriateness of emission reduction measures and climate policy, and is affected by socioeconomic and climatic factors. This study aimed to explore the impact of socioeconomic factors and climate on the social cost of carbon; to this end, this study considered Chinese provinces as the focus of research. This study constructed an integrated framework for carbon emissions considering socioeconomic and climatic factors, which consisted of shared socioeconomic pathways (SSPs) and representative concentration pathways (RCPs). Subsequently, social cost of the carbon estimation model was used to calculate the social cost of carbon for China's provinces from 2022 to 2100 under different carbon emission scenarios. The results show that: under most carbon emission scenarios, provinces with a high social cost of carbon are located in the eastern developed region. For instance, Jiangsu and Guangdong had the highest values of 6.31 $/tC. Second, SSPs that are highly dependent on fossil fuels have a high social cost of carbon, which is higher than 60 $/tC in 2022 in China. The social cost of carbon under other SSPs is at a fluctuating value of 40 $/tC. Third, in terms of RCPs, the social cost of carbon for the middle baseline emission scenario (RCP6.0) is considerably lower than that for the high baseline emission scenario (RCP8.0), and the difference between them is 3.7 times that of two medium emission scenarios (RCP6.0 and RCP4.5). Fourth, there is a substantial difference between the dynamic and fixed discount rates in the social cost of carbon in the same scenario. Studying the impact of socioeconomic and climatic factors on the social cost of carbon will help in its regulation and provide a scientific basis for Chinese provinces to optimize climate policies and emission reduction measures.

You are not in the army now! A field study on the impact of a Preparation for Civilian Life program on young soldiers.

Recent years have seen the implementation of educational programs aimed at developing future orientation and better employability skills, mostly for people new to or returning to the job market. In a field study, we investigated the impact of a 5-day program on reintegration to civilian life on young Israeli combat soldiers' time preferences, gratitude, patriotism, and perceptions of their combat experience. Questionnaires administered before and after the program revealed a positive effect on future orientation but a negative effect on gratitude and perceptions of the combat experience. Although the positive effect on future orientation is in line with the program design, the negative effects found should be taken into consideration when planning or improving similar educational programs.

A New Strategy in Boosting Information Spread.

Finding a seed set to propagate more information within a specific budget is defined as the influence maximization (IM) problem. The traditional IM model contains two cardinal aspects: (i) the influence propagation model and (ii) effective/efficient seed-seeking algorithms. However, most of models only consider one kind of node (i.e., influential nodes), ignoring the role of other nodes (e.g., boosting nodes) in the spreading process, which are irrational. Specifically, in the real-world propagation scenario, the boosting nodes always improve the spread of influence from the initial activated seeds, which is an efficient and cost-economic measure. In this paper, we consider the realistic budgeted influence maximization (RBIM) problem, which contains two kind of nodes to improve the diffusion of influence. Facing the newly modified objective function, we propose a novel B-degree discount algorithm to solve it. The novel B-degree discount algorithm which adopts the cost-economic boosting nodes to retweet the influence from the predecessor nodes can greatly reduce the cost, and performs better than other state-of-the-art algorithms in both effect and efficiency on RBIM problem solving.

Analysis of IBNR Liabilities with Interevent Times Depending on Claim Counts.

We extend a recently proposed stochastic loss reserving model for liabilities from incurred but not reported (IBNR) micro-level claims. We propose viewing the number of claims from an event as a measure of catastrophic severity. This view covers catastrophes with arbitrarily many classes of magnitude. Our Markovian model allows the time between disasters to depend on the previous event's level of severity. Simultaneously, we let the discount rate vary in the same manner. First, we find the moments of IBNR liabilities in our model. Then, we permit a later time horizon for IBNR claims when considered jointly with incurred and reported claims.

Comparison of Discounted and Undiscounted Cash Prices for Cardiovascular Medications by Type of US Community Pharmacy.

BACKGROUND: Cash prices for prescription drugs vary among community pharmacies in the USA. GoodRx is a discount platform that provides coupons for use in community pharmacies without a membership requirement. Analytical pharmacy is a new type of pharmacy that tests drugs before dispensing to verify medication quality. OBJECTIVE: To compare undiscounted and GoodRx-discounted cash prices for common cardiovascular (CV) drugs by pharmacy type. DESIGN: A cross-sectional study. SETTING: GoodRx-discounted and GoodRx-undiscounted cash price data; analytical pharmacy cash price data (all data collected in July 2020). MEASUREMENTS: GoodRx cash price data for 30 units of 41 generic and 16 brand-name common cardiovascular medications at mass merchandiser, regional supermarket, two national chains, and analytical pharmacy (only one of its kind in the USA). RESULTS: The average (SD) undiscounted generic CV medication cash price was $42.41 (44.1). The average GoodRx-discounted generic CV medication cash prices were $11.01 (8.6), $9.88 (6.7), $17.85 (10.5), and $21.73 (14.1) in mass merchandiser, supermarket, and two national chain pharmacies, respectively. The average generic CV medication cash price was $20.84 (25.7) at the analytical pharmacy. The average (SD) undiscounted brand-name CV medication cash price was $368.33 (127.00). The average GoodRx-discounted brand-name CV medication cash prices were $269.16 (118.1), $258.84 (108.6), $270.28 (118.4), and $274.60 (122.50) for mass merchandiser, supermarket, and two national chain pharmacies, respectively. The average (SD) brand-name CV medication cash price was $365.12 (116.20) at the analytical pharmacy. CONCLUSIONS: GoodRx-discounted cash prices of generic CV medications were significantly lower than undiscounted cash prices at supermarket, mass merchandiser, and national chain pharmacies. Analytical pharmacy cash prices too were significantly lower than traditional pharmacy undiscounted cash prices. GoodRx-discounted prices for brand-name CV medications did not differ significantly from undiscounted cash prices and between pharmacy types.

Conditions for the existence of zero-determinant strategies under observation errors in repeated games.

Repeated games are useful models to analyze long term interactions of living species and complex social phenomena. Zero-determinant (ZD) strategies in repeated games discovered by Press and Dyson in 2012 enforce a linear payoff relationship between a focal player and the opponent. This linear relationship can be set arbitrarily by a ZD player. Hence, a subclass of ZD strategies can fix the opponent's expected payoff and another subclass of the strategies can exceed the opponent for the expected payoff. Since this discovery, theories for ZD strategies are extended to cope with various natural situations. It is especially important to consider the theory of ZD strategies for repeated games with a discount factor and observation errors because it allows the theory to be applicable in the real world. Recent studies revealed their existence of ZD strategies even in repeated games with both factors. However, the conditions for the existence has not been sufficiently analyzed. Here, we mathematically analyzed the conditions in repeated games with both factors. First, we derived the thresholds of a discount factor and observation errors which ensure the existence of Equalizer and positively correlated ZD (pcZD) strategies, which are well-known subclasses of ZD strategies. We found that ZD strategies exist only when a discount factor remains high as the error rates increase. Next, we derived the conditions for the expected payoff of the opponent enforced by Equalizer as well as the conditions for the slope and base line payoff of linear lines enforced by pcZD. As a result, we found that, as error rates increase or a discount factor decreases, the conditions for the linear line that Equalizer or pcZD can enforce become strict.

Relationship among psychological distress, food dependence, and the time discount rate: a pilot mediation analysis.

Psychological distress (PD) was shown to be associated with food dependence and higher time discount rate; however, few studies have clarified the relationship among these three variables. To clarify whether time discount rate mediated a relationship between food dependence and PD. In this study, the subjects were 91. We evaluated food dependence scores and time discount rate using self-administered questionnaires as well as PD using K6 questionnaires. Simple correlation and mediation analyses were performed by Structural Equation Modelling (SEM) to clarify relationships among PD, food dependence, and time discount rate. By SEM, a significant relationship was found between food dependence and K6 scores (standardized coefficient (ß)=0.341, p=0.001). Moreover, a significant correlation was found between food dependence scores and time discount rate (ß=0.345, p=0.001) as well as between time discount rate and K6 scores (ß=0.419, p<0.001). By having time discount rate as a parameter, the correlation coefficients between food dependence and K6 scores varied between 0.341 (p=0.001) and 0.197 (p=0.045). After bootstrapping, 0 was not included in the 99% confidence interval [0.013, 0.139]. Time discount rate may mediate the relationship between food dependence and PD. To improve PD, food dependence as well as time discount rate should be reduced.

The examination of Fama-French Model during the Covid-19.

This paper evaluates the performance of Fama-French models on US stock markets during the selected events by studying the R 2 of the models. We find that the influence of Dotcom bubble to the R 2 of growth model is statistically significant. The R 2 of growth portfolios decreases rapidly during the Financial crisis of 2008. The latest Covid-19 outbreak drop has led to a substantial in the R 2 during this event. Furthermore, we find that all of the beta model parameters are insignificant in the GMM model.

Understanding and adjusting for the selection bias from a proof-of-concept study to a more confirmatory study.

It has long been noticed that the efficacy observed in small early phase studies is generally better than that observed in later larger studies. Historically, the inflation of the efficacy results from early proof-of-concept studies is either ignored, or adjusted empirically using a frequentist or Bayesian approach. In this article, we systematically explained the underlying reason for the inflation of efficacy results in small early phase studies from the perspectives of measurement error models and selection bias. A systematic method was built to adjust the early phase study results from both frequentist and Bayesian perspectives. A hierarchical model was proposed to estimate the distribution of the efficacy for a portfolio of compounds, which can serve as the prior distribution for the Bayesian approach. We showed through theory that the systematic adjustment provides an unbiased estimator for the true mean efficacy for a portfolio of compounds. The adjustment was applied to paired data for the efficacy in early small and later larger studies for a set of compounds in diabetes and immunology. After the adjustment, the bias in the early phase small studies seems to be diminished.