Longer Time Horizon Research Articles

A Systematic Review of the Impact of Changes to Urban Green Spaces on Health and Education Outcomes, and a Critique of Their Applicability to Inform Economic Evaluation

Several reviews have consolidated the evidence on the impact of living near an urban green space on improving health and education outcomes and reducing mortality. However, there is limited evidence on the effectiveness or cost-effectiveness of specific improvements to these urban green spaces, which would help decision-makers make informed decisions on how to invest in urban green spaces. Therefore, this review synthesizes the impact of more specific changes to, or investments in, urban green spaces on health and education outcomes, synthesizes the cost-effectiveness of these interventions, and critiques the applicability of the evidence for an economic evaluation. We find that interventions targeted towards improving play areas or fitness equipment tended to have mostly positive impacts on physical activity, while interventions on improving walking path, or the overall greenery showed a more mixed impact on physical activity. There were only two studies on the impact of changes to urban green spaces on mental health, with only one finding a positive association of the intervention with depression, and there were no studies measuring the impact of changes to urban green spaces and educational outcomes. From a cost-effectiveness perspective, we find that typically very small improvements are required to make the interventions a cost-effective policy choice; however, we found several limitations with using the existing evidence to estimate the cost-effectiveness of the intervention. Overall, we found that most of the evidence does suggest that improvements to urban green spaces can lead to improvements in physical activity, but further research is needed on the impact on mental health and educational outcomes. Furthermore, additional evidence with longer time horizons, multi-sectoral benefits, distributional outcomes, and more consistent outcome measures would assist in informing cost-effectiveness and may ultimately lead to improved decision-making around investments for urban green spaces in specific contexts.

Higher Precision Is Not Always Better: Search Algorithm and Consumer Engagement

On decentralized e-commerce platforms, search algorithms play a critical role in matching buyers and sellers. A typical search algorithm routinely refines and improves its catalog of data to increase search precision, but the effects of a more precise search are little known. We evaluate such effects via a 2019 quasiexperiment on a world-leading e-commerce platform in which the search algorithm refined some product categories into finer subgroups to allocate consumer queries to more relevant product listings. Our data cover millions of consumers’ search and purchase behaviors over six months across multiple search sessions and product categories, enabling us to investigate trade-offs over time and across categories. We find that a more precise search algorithm improves consumers’ click-through and purchase rates drastically and instantaneously, but it comes at the cost of a significant decrease in consumer engagement and unplanned purchases over a longer time horizon. On average, consumers who used to spend more time searching now conduct 5.5% fewer searches, spend 4.1% less time on the platform, and decrease their spending on related categories by 2.2% in the week after the search precision increases. Our examination of the mechanisms behind these consequences calls for more careful search algorithm designs that account for not only instant conversion based on search precision but also consumer engagement and sellers’ strategic responses in the longer horizon. This paper was accepted by Anindya Ghose, information systems. Funding: This work was supported by the Key Program of the National Natural Science Foundation of China [Grants 72141305 and 72192803] and the Ministry of Education, People’s Republic of China (Fundamental Research Funds for the Central Universities), both to L. Fang. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.00478 .

Low density lipoprotein cholesterol and cardiovascular disease risk in patients with absence of coronary artery calcification: a multicenter cohort study

Abstract Background Low-density lipoprotein cholesterol (LDL-C) plays a central role in the development of coronary heart disease (CHD). Absence of coronary artery calcification (CAC 0), as assessed by coronary computed tomography angiography (CCTA), is associated with a favorable outcome as it indicates a low burden of atherosclerosis. However, questions remain regarding the risk of non-calcified plaque and CHD in younger patients with CAC zero, as atherosclerosis tends to be non-calcified in earlier stages. Purpose To assess if LDL-C is associated with presence of non-calcified plaque and future cardiovascular events in patients with CAC zero across the age spectrum. Methods This observational multicenter cohort study included patients aged 18 years or more who underwent CCTA between January 2008 and May 2021 with CAC zero. LDL-C was measured prior to CCTA. Patients were followed from date of CCTA to occurrence of cardiovascular event, death, or 1st of October 2022. No patients were lost to follow-up. We assessed the association between LDL-C and presence of non-calcified plaque on CCTA as adjusted odds ratios, and risk for myocardial infarction and CHD (myocardial infarction or coronary revascularization) as adjusted hazard ratios using Cox regression analyses, across different age groups. Results A total of 23,776 patients with CAC zero were included in the study. Median age was 54 years (IQR 47-61) and 14,605 (61%) were women. During median follow-up of 5.5 years, 165 (0.7%) and 427 (1.8%) experienced myocardial infarction and CHD, respectively. Overall, the prevalence of non-calcified plaque was 11.1% (n=2,650). Higher LDL-C was associated with presence of non-calcified plaque with an odds ratio of 1.21 (95% CI 1.16-1.27) per 1 mmol/L higher LDL-C. Individuals aged ≤45 years had a higher odds ratio for non-calcified plaque per 1 mmol/L higher LDL-C compared to individuals aged 46-60 and >60 years; 1.36 (95% CI 1.22-1.52), 1.22 (95% CI 1.15-1.30) and 1.13 (95% CI 1.04-1.22), respectively, p value for interaction between the youngest and oldest age group was <0.05. Overall, LDL-C was associated with higher risk for myocardial infarction and CHD with hazard ratios of 1.29 (95% CI 1.10-1.52) and 1.26 (95% CI 1.14-1.39) per 1 mmol/L higher LDL-C, despite CAC zero. Conclusions Particularly in younger patients with absence of CAC, elevated LDL-C is associated with presence of non-calcified plaque and increased risk for future cardiovascular events. These data are important for clinical practice, as they demonstrate the importance of managing LDL-C in younger individuals over the long-time horizon despite CAC zero.

Dependence, power imbalance, and value gains in business process outsourcing

AbstractWe examine the impact of interdependencies in business process outsourcing (BPO) relationships on client and vendor firm values both in the short term and over a longer time horizon. Drawing from recent research incorporating the resource dependence theory, which appertains the interdependence to both mutual dependence and power imbalance in interfirm relationships, we posit the value proposition of BPO to be greater for mutually dependent engagements, and more so for the vendor than for the client. In addition, we posit the power imbalance in BPO relationships to be detrimental for clients and vendors, and thus, the value proposition of such BPO is expected to be lower for both. We empirically examine these issues through an event study of 285 publicly announced BPO engagements and find that mutually dependent BPO relationships, which were difficult to decouple, are value enhancing for both clients and vendors, and more so for vendors. In addition, although the power imbalances were expected to be detrimental to both, we find this power imbalance to negatively affect only the vendors but had a positive effect on clients.

Computational Methods of Ruin Probability: Actuarial Comparison of De-Vylder and Tijim’s Models

The underwriting operation of insurance firms is to assume the risk of the insured in return of premium received. In order to shield itself against extreme losses and avoid the risk of insolvency, it becomes necessary to examine how the portfolio is expected to perform over a long-time horizon. The surplus process is connected with the excess of the premium received over claims outgo of the insurer’s portfolio to enable it predict the level at which the insurer could survive. When the surplus approaches a defined lower limit irrespective of the initial reserve, then the insurer is ruined. The probability of ruin apparently defines the volatility embedded in underwriting process as a useful tool of risk measurement in long range planning of premium rate. This paper is anchored on the following objectives: solve the adjustment co-efficient using the moment generating function, compute the De-Vylder’s ruin, compute the Tijim’s ruin approximation and then compare the two. Although it was verified that as the initial capital increases, the probability of ruin decreases under the two models, computational evidence from our results in tables 2 and 3 shows that the Tijim’s approximation to ruin probability is higher than the De-Vylder’s approximation at the same level of initial capital and safety loading. The implication is that the De-Vylder’s approximation to ruin probabilities is an improvement over Tijim’s ruin model and hence De-Vylder’s approximation is recommended for the insurer’s ruin assessment

Revisiting immunity vs. exposure in schistosomiasis: A mathematical modeling study of delayed concomitant immunity.

The relative contributions of exposure vs. acquired immunity to the epidemiology of human schistosomiasis has been long debated. While there is considerable evidence that humans acquire partial immunity to infection, age- and sex-related contact patterns with water bodies contaminated with infectious cercarial schistosome larvae also contribute to typical epidemiological profiles of infection. Here, we develop a novel schistosome transmission model that incorporates both partially protective "delayed concomitant" acquired immunity-stimulated by dying worms-and host age- and sex-dependent patterns of exposure. We use a contemporary Bayesian approach to fit the model to historical individual data on exposure to infectious cercaria, eggs per gram of feces, and immunoglobulin E antibodies specific to Schistosoma mansoni Tegumental-Allergen-Like protein 1 collected from a highly endemic community in Uganda, estimating the relative contributions of exposure and acquired immunity. We find that model variants incorporating or omitting delayed concomitant immunity describe equally well the age- and sex-specific immunoepidemiological patterns observed before intervention and 18 months after treatment. Over longer time horizons, we find that acquired immunity creates subtle differences in immunoepidemiological profiles during routine mass drug administration that may confer resilience against elimination. We discuss our findings in the broader context of the immunoepidemiology of schistosomiasis.

The utility of wastewater surveillance for monitoring SARS-CoV-2 prevalence

Abstract Public health authorities have increasingly used wastewater-based epidemiology (WBE) to monitor community transmission of SARS-CoV-2 and other agents. In this study, we evaluate the utility of WBE during the COVID-19 pandemic in England for estimating SARS-CoV-2 prevalence. We use wastewater data from the Environmental Monitoring for Health Protection program and prevalence data from the REal-time Assessment of Community Transmission-1 study. Across the pandemic, we describe how wastewater-based modeling can achieve representative SARS-CoV-2 prevalence estimates in fine and coarse spatial resolutions for relatively short-time horizons (of up to 1 month), and thus assist in filling temporal gaps in surveillance. We infer a temporally evolving relationship between wastewater and prevalence which may limit the utility of WBE for estimating SARS-CoV-2 prevalence over longer time horizons without a concurrent prevalence survey. Exploring further our finding of time-varying, population-level fecal shedding, we characterize WBE for SARS-CoV-2 prevalence as (i) vaccination coverage dependent and (ii) variant- specific. Our research suggests that these factors are important considerations in future uses of WBE by public health authorities in infectious disease outbreaks. We further demonstrate that WBE can improve both the cost efficiency and accuracy of community prevalence surveys which on their own may have incomplete geographic coverage and/or small sample sizes. Therefore, in England, for the objective of high spatial resolution prevalence monitoring, strategic use of SARS-CoV-2 wastewater concentration data nationally could have enhanced, but not replaced, community prevalence survey programs.

Short- and long-term cost-effectiveness of abrocitinib versus dupilumab in adults with moderate-to-severe atopic dermatitis in China

Background Biologics and JAK inhibitors were the most effective innovative systemic treatments for moderate-to-severe atopic dermatitis (AD). However, their cost-effectiveness in China remains unclear. This study aims to compare both the short- and long-term cost-effectiveness of abrocitinib and dupilumab in adults with moderate-to-severe AD from the perspective of the Chinese healthcare system. Methods A hybrid decision tree and Markov model were developed to simulate the costs and health outcomes of interventions on both short-term and long-term horizons. Short- and long-term horizons were employed to reflect the 26-week induction treatment and model the extended 10-year maintenance treatment period, respectively. The cost-effectiveness of strategies was measured by incremental cost-effectiveness ratios (ICERs), which were then compared with the willingness-to-pay threshold (WTP) that was equivalent to the gross domestic product (GDP) per capita of China in 2023 ($12,681 [€11,679.26]). One-way and probabilistic sensitivity analyses were conducted to validate the robustness of the model. Results Over the short-term horizon, the QALYs (quality-adjusted life years) gained were 0.43 for the abrocitinib group and 0.42 for the dupilumab group, with the costs being $2,716.01 (€2,501.46) and $3,940.33 (€3,629.06), respectively. Over the long-time horizon, abrocitinib therapy yields higher QALYs (6.60 versus 6.53) and incurs a lower cost ($22,765.15 [€20,966.81] versus $30,683.38 [€28,259.54]) compared to dupilumab. The probability of abrocitinib being cost-effective was nearly 100% under the current WTP. Both short- and long-term results showed that abrocitinib was more effective and less costly than dupilumab, making abrocitinib the dominant option. Conclusions Abrocitinib was dominant compared to dupilumab both over the short- and long-term horizon for moderate-to-severe AD in China. Future research incorporating real-world evidence and long-term efficacy outcomes could further refine these economic evaluations.

Randomized Controlled Trial Based US Commercial Payor Cost-Effectiveness Analysis of Endoscopic Sleeve Gastroplasty Versus Lifestyle Modification Alone for Adults With Class I/II Obesity.

Endoscopic sleeve gastroplasty (ESG) is a minimally invasive day procedure that the MERIT randomized controlled trial (RCT) has demonstrated to be an effective and safe method of weight loss versus lifestyle modification alone. We sought to evaluate the cost-effectiveness of ESG from the perspective of a US commercial payer in a cohort of adults with class II and class I obesity with diabetes based on this RCT. We used a Markov modelling approach with BMI group health states and an absorbing death state. Baseline characteristics, utilities, BMI group transition probabilities, and adverse events (AEs) were informed by patient-level data from the MERIT RCT. Mortality was estimated by applying BMI-specific hazard ratios to US general population mortality rates. We used BMI-based health state utilities to reflect the impact of obesity comorbidities and applied disutilities due to ESG AEs. Costs included intervention costs, AE costs, and BMI-based annual direct healthcare costs to account for costs associated with obesity comorbidities. A willingness-to-pay threshold of $100,000 per quality-adjusted life year (QALY) was assumed. In our base-case analysis over a 5-year time horizon, ESG was cost-effective versus lifestyle modification alone with an incremental cost-effectiveness ratio of $23,432/QALY. ESG remained cost-effective in all sensitivity analyses we conducted and was dominant in analyses with longer time horizons. ESG is a cost-effective treatment option for people living with obesity and should be considered in commercial health plans as an additional treatment option for clinically eligible patients.

Futures empathy for foresight research and practice

Foresight methods help us to think about the future and overcome a bias toward short-term thinking in decision making. However, many approaches to investigating the future tend to leave implicit how individuals involved in the interventions relate to the present and to the future in practice and over time. To address this gap, our study highlights the affordances of two methodologies —Scenario Planning and Future Design. In a pilot study combining these methods, we report the results of the novel hybridized approach applied in strategic planning workshops across four corporations. Initial reflections and learnings from the pilot case study and literature review helps to build understandings of the practical and theoretical workings of the methodological innovation. By investigating this combination of foresight methodologies, this research opens up new ways for thinking about futuring and proposes a theory of Futures Empathy. Futures Empathy harnesses a person’s capacity for empathy in a novel way by applying it toward a future context. It consists of an iterative double looping process between self and a not yet existent future. Through imagination and reflection, foresight methods that build Futures Empathy can enhance personal connection and integration with a longer time horizon, thus overcoming presentism. By proposing a theory of Futures Empathy, we hope to contribute to better present and future relating in practice and over time across a multitude of foresight interventions.

Impression management, forward-looking strategy-related disclosure, and excess executive compensation: Evidence from China

We investigate whether overpaid executives in Chinese listed firms engage in impression management by using forward-looking strategy-related disclosure (FLSD) in management discussion and analysis (MD&A) narratives to justify their excess compensation. Using a sample of 8437 firm-year observations of Chinese nonfinancial listed firms from 2007 to 2016, we find a significant and positive relationship between executive overpayment and impression management in FLSD. This positive relationship is more pronounced in state-owned enterprises (SOEs) than non-SOEs. We also find that a higher degree of board independence, higher institutional shareholdings, auditors, analysts, and the introduction of the anti-corruption campaign could lower such a positive relationship. These findings suggest that impression management in FLSD is reduced when corporate governance is strengthened. We also find that CEO duality could enhance this positive relationship. Further examining how the market reacts to such impression management, we find an immediate positive and significant market reaction to such impression management at the time of the annual report filing, which could further mitigate the negative perceptions from stakeholders due to excessive pay. Such a positive market reaction is reversed over a longer time horizon, which supports the opportunistic/symbolic nature of impression management in FLSD.

Explainable hypoglycemia prediction models through dynamic structured grammatical evolution

Effective blood glucose management is crucial for people with diabetes to avoid acute complications. Predicting extreme values accurately and in a timely manner is of vital importance to them. People with diabetes are particularly concerned about suffering a hypoglycemia (low value) event and, moreover, that the event will be prolonged in time. It is crucial to predict hyperglycemia (high value) and hypoglycemia events that may cause health damages in the short term and potential permanent damages in the long term. This paper describes our research on predicting hypoglycemia events at 30, 60, 90, and 120 minutes using machine learning methods. We propose using structured Grammatical Evolution and dynamic structured Grammatical Evolution to produce interpretable mathematical expressions that predict a hypoglycemia event. Our proposal generates white-box models induced by a grammar based on if-then-else conditions using blood glucose, heart rate, number of steps, and burned calories as the inputs for the machine learning technique. We apply these techniques to create three types of models: individualized, cluster, and population-based. They all are then compared with the predictions of eleven machine learning techniques. We apply these techniques to a dataset of 24 real patients of the Hospital Universitario Principe de Asturias, Madrid, Spain. The resulting models, presented as if-then-else statements that incorporate numeric, relational, and logical operations between variables and constants, are inherently interpretable. The True Positive Rate and True Negative Rate metrics are above 0.90 for 30-minute predictions, 0.80 for 60 min, and 0.70 for 90 min and 120 min for the three types of models. Individualized models exhibit the best metrics, while cluster and population-based models perform similarly. Structured and dynamic structured grammatical evolution techniques perform similarly for all forecasting horizons. Regarding the comparison of different machine learning techniques, on the shorter forecasting horizons, our proposals have a high probability of winning, a probability that diminishes on the longer time horizons. Structured grammatical evolution provides advanced forecasting models that facilitate model explanation, modification, and retesting, offering flexibility for refining solutions post-creation and a deeper understanding of blood glucose behavior. These models have been integrated into the glUCModel application, designed to serve people with diabetes.

A Regional Analysis of the Impacts of Changes in Housing Values on Property Tax Assessment During and After the 2008 Financial Crisis

This study examines the relationship between changing house prices and assessed value in the Detroit Michigan region. Using parcel-level data from 2008 through 2016, we construct a Hedonic Housing Price Index and an Assessed Value Index for 120 Michigan assessing jurisdictions in the five-county region surrounding Detroit (Macomb, Monroe, Oakland, Washtenaw, and Wayne). Our findings are consistent with the literature, indicating at least a three-year lag between changes in house prices and changes in property assessments. Communities considered to be distressed tended to over-assess properties before the crisis, but these communities recalibrated assessments to better align with market conditions after the financial crisis. Our evaluation also shows that while assessed values decreased more slowly than housing prices fell during the crisis, assessed values tended to fall to even deeper levels than housing prices over a longer time horizon. JEL Codes: H71, H83, G01

An energy management system to schedule the optimal participation to electricity markets and a statistical analysis of the bidding strategies over long time horizons

This paper presents a tool that allows to perform an ex-ante estimation of the profitability to participate to the electric energy and service markets for a microgrid or a polygeneration power plant. The tool is the evolution of an Energy Management System (EMS) previously developed by the University of Genoa and Renantis Solutions Srl. Constraints are added to the original EMS to model the Ancillary Service Market (ASM) and Day Ahead Market (DAM) mechanisms in the framework of a planning tool that allows to get estimates of the microgrid/plant costs and revenues over a long-time horizon. As the market outcome strongly depends on the Transmission System Operator (TSO) acceptance/rejection of bids and offers, a statistical approach is proposed. The optimization process is split in two steps: the first one optimally dispatches the energy units and proposes DAM offers and ASM bid and offers over a specified time horizon. Then, a Monte Carlo method is launched; at each extraction the TSO acceptance/rejection of each ASM bid and offer is simulated and there is a second step of optimization in which the energy sources are optimally re-dispatched to meet the bidding program and so to avoid imbalance power exchange that would increase the energy cost. The cost/revenue is thus computed at each extraction. The result is the probability density function of the costs/revenues that allows to estimate the profitability of the participation to the electricity markets. One test performed on a real microgrid shows that the computational time needed to complete one iteration related to a time horizon of one month is approximately 20 s. Moreover, the comparison of the outcomes with two independent launches to define the set of bids and offers to be accepted in ASM demonstrates that the statistical analysis allows to avoid misleading conclusions on the costs/revenues. Consequently, the fact that the developed EMS allows to perform a statistical analysis in a reasonable time enables the possibility of comparing multiple scenarios and gives an indication related to the range of cost/revenues in which the microgrid/plant may incur. Finally, the computational efficiency of the proposed approach allows to conclude that the developed EMS is appropriate to perform a long-time horizon (of the order of magnitude of years) analysis and, at the same time, allows to model all the involved components with a high level of details.

Living emission abolish filters (LEAFs) for methane mitigation: design and operation

As one of the most potent greenhouse gases, methane is a critical target for the near-term mitigation of global warming. Efficient, scalable, easy-to-implement, and robust mitigation technologies are urgently needed to assist in reaching methane abolishment. The goal of this research was to test the applicability of active, extremophilic methanotrophic cells as a baseline concept for engineered systems aiming at methane capturing. The system, named living emission abolish filters (LEAFs), represents an array of immobilized biomaterials capable of capturing methane directly from vent streams. The biomaterials were made using cells of Methylotuvimicrobium alcaliphilum 20ZR, a robust halophilic methanotrophic bacterium with the ability to consume methane gas at low concentrations. Several critical parameters were tested, including (i) the composition of the matrix and optimal immobilization to increase catalyst load, (ii) the stability of methanotrophic cells, and (iii) the toxicity of trace gases (i.e. CO). We found that hydrogels coated with 2.3 mg cell dry weight/cm3 methanotrophic cells represent the best-performing biomaterials. The methane reduction potential of LEAFs fluctuated from 20% to 95% and depended on the methane concentration in the gas stream and the stream flow rates. The potential for commercial-scale deployment and emissions reductions was also evaluated. Total greenhouse gas emissions (combined using the global warming potential GWP100) from an example using a ventilation air methane source over a one-year period was shown to be reduced in two LEAF scenarios by 51% and 75%. Over longer time horizons, more significant reductions are possible as consistent methane consumption can be sustained. The study highlights the overall potential of the liquid-free bio-based composite methane mitigation system. Further improvements essential for system assembly and implementations should include (a) optimization of the cell immobilization protocols to improve cell load and the shelf-life of the system and (b) implementation of matrix moldings for cell immobilization to achieve optimal gas flow and increase the cell-gas interface.

Impact of immune evasion, waning and boosting on dynamics of population mixing between a vaccinated majority and unvaccinated minority.

We previously demonstrated that when vaccines prevent infection, the dynamics of mixing between vaccinated and unvaccinated sub-populations is such that use of imperfect vaccines markedly decreases risk for vaccinated people, and for the population overall. Risks to vaccinated people accrue disproportionately from contact with unvaccinated people. In the context of the emergence of Omicron SARS-CoV-2 and evolving understanding of SARS-CoV-2 epidemiology, we updated our analysis to evaluate whether our earlier conclusions remained valid. We modified a previously published Susceptible-Infectious-Recovered (SIR) compartmental model of SARS-CoV-2 with two connected sub-populations: vaccinated and unvaccinated, with non-random mixing between groups. Our expanded model incorporates diminished vaccine efficacy for preventing infection with the emergence of Omicron SARS-CoV-2 variants, waning immunity, the impact of prior immune experience on infectivity, "hybrid" effects of infection in previously vaccinated individuals, and booster vaccination. We evaluated the dynamics of an epidemic within each subgroup and in the overall population over a 10-year time horizon. Even with vaccine efficacy as low as 20%, and in the presence of waning immunity, the incidence of COVID-19 in the vaccinated subpopulation was lower than that among the unvaccinated population across the full 10-year time horizon. The cumulative risk of infection was 3-4 fold higher among unvaccinated people than among vaccinated people, and unvaccinated people contributed to infection risk among vaccinated individuals at twice the rate that would have been expected based on the frequency of contacts. These findings were robust across a range of assumptions around the rate of waning immunity, the impact of "hybrid immunity", frequency of boosting, and the impact of prior infection on infectivity in unvaccinated people. Although the emergence of the Omicron variants of SARS-CoV-2 has diminished the protective effects of vaccination against infection with SARS-CoV-2, updating our earlier model to incorporate loss of immunity, diminished vaccine efficacy and a longer time horizon, does not qualitatively change our earlier conclusions. Vaccination against SARS-CoV-2 continues to diminish the risk of infection among vaccinated people and in the population as a whole. By contrast, the risk of infection among vaccinated people accrues disproportionately from contact with unvaccinated people.

Improving pension savings investing: The case of Russia

Many countries seek to improve their pension systems by introducing corporate and individual savings plans to address the challenges of demography, social security, and economy. However, the establishing of a long-term, reliable savings system encounters multiple impediments. The retrospective analysis of Russian pension reforms offers some recommendations on solving the typical problems faced by reformers. Thus, in 2002 the Russian pension system was implemented by a mandatory savings pillar, which 20 years later the Ministry of Finance substituted by voluntary savings­. As this period appeared shorter than the average life span, this measure proved ­ineffective in increasing pension payouts for future retirees. The frequent regulatory changes and the shrinking workforce coverage as the state prioritized the welfare of the current pension recipients also infringed upon the interests of future retirees. Pension savings investments were further affected by the economic policy aimed at the minimal return requirements which resulted in a more conservative asset allocation strategy and inefficient active management in non-state pension funds. The study demonstrates that policy actions to overcome these impediments and to raise the replacement rates for future retirees should include (a) steady regulations within a pension savings system of no shorter than 40 years; (b) the savings pillar covering no less than 80% of the workforce; and (c) the asset allocation strategy involving a bigger share of equity, longer time horizon and clear benchmarks. These recommendations can be applied to emerging market economies concerned with improving and reforming their pension systems.

Eco-foresight research in shaping country’s science development strategy regarding the green economy

This article focuses on the importance of eco- foresight research in shaping the country’s science development strategy in the field of green economy. The transition to a green economy requires balancing economic growth with environmental conservation, and finding a balanced model is a complex task that many specialists are actively working on. Ecoforesight, which involves the use of foresight methodology in the environmental field, plays a crucial role in identifying potential opportunities and risks for the natural environment associated with landmark innovations and global economic trends. The study aims to assess the long-term environmental impacts of current industrial activities and strategic planning of national industrial policies regarding green technologies. Scenario modeling, especially in the field of green technologies, is an important aspect of environmental forecasting due to its long-time horizons and numerous uncertainties. The article emphasizes the importance of eco- foresight research in ensuring sustainable development and innovation in the context of global strategic trends.

Digital Alcohol Interventions Could Be Part of the Societal Response to Harmful Consumption, but We Know Little About Their Long-Term Costs and Health Outcomes.

Alcohol consumption causes both physical and psychological harm and is a leading risk factor for noncommunicable diseases. Digital alcohol interventions have been found to support those looking for help by giving them tools for change. However, whether digital interventions can help tackle the long-term societal consequences of harmful alcohol consumption in a cost-effective manner has not been adequately evaluated. In this Viewpoint, we propose that studies of digital alcohol interventions rarely evaluate the consequences of wider dissemination of the intervention under study, and that when they do, they do not take advantage of modeling techniques that allow for appropriately studying consequences over a longer time horizon than the study period when the intervention is tested. We argue that to help decision-makers to prioritize resources for research and dissemination, it is important to model long-term costs and health outcomes. Further, this type of modeling gives important insights into the context in which interventions are studied and highlights where more research is required and where sufficient evidence is available. The viewpoint therefore invites the researcher not only to reflect on which interventions to study but also how to evaluate their long-term consequences.

GEOPOLITICS, UNCERTAINTY, AND CRYPTOCURRENCY: A LOVE TRIANGLE GONE WRONG

This study aims to investigate the spillover effects from geopolitical risks (proxied by the geopolitical risk index GPRD) and cryptocurrencies-related uncertainty (proxied by the Cryptocurrency Uncertainty Index UCRY) to cryptocurrencies. We utilize the Baruník and Křehlík (2018) framework to detect time-frequency connectedness. Our investigation for the period 2017 to 2022 discovers significant spillover effects from both indices (GPRD and UCRY) to cryptocurrencies. Utilizing the information transmission theory and network graphs, our findings reveal that some cryptocurrencies function as net receivers of spillovers from geopolitical risks and uncertainty in the short-term, while over longer time horizons they transform into net transmitters of spillovers to uncertainty. The study underscores the importance of comprehending how uncertainty due to various factors (geopolitical, policy changes, regulatory changes, etc.) could affect the cryptocurrencies’ markets.