Five-year Horizon Research Articles

Consensus in uncertainty. A group Delphi study on the impact of digitalisation on the continuing education of low-qualified adults in Germany

ABSTRACT This paper conducts Group Delphi-study and foresight approach within a five-year horizon in the field of digital education, with a specific focus on Continuing Education (CE) in a post-pandemic society. The study examines the impact of increasing digitalisation on the significant population of low-qualified individuals (approximately five million in Germany). The project identifies both opportunities and risks associated with digitalisation in CE for the low-qualified. The study focuses on 1) the impact of digitalisation on the participation of low-qualified people in CE, 2) the impact of accelerated digitalisation on the planning of programmes and services for this target group, 3) the transformation of programmes and services for low-qualified people due to digitalisation, and 4) methodological innovations for predicting the impact of digitalisation in the CE sector.

Environmental regulation and productivity growth in the euro area: Testing the porter hypothesis

This paper examines the impact of changes in the stringency of environmental regulations on productivity growth. We exploit several data sources, including the OECD Environmental Policy Stringency Index and balance sheet information from ORBIS and iBACH, to test the Porter hypothesis, according to which firms’ productivity can benefit from more stringent environmental policies. We estimate the regulatory impact over a five-year horizon using panel local projections. To identify the direction of the effects, we estimate CO2 equivalent emissions for all firms in our sample using a machine learning algorithm. As suggested by the country-level analysis and confirmed by the firm-level analysis, policy tightening negatively affects productivity growth of high-polluting firms and to a larger extent than that of their low-polluting peers. Hence, we do not find support for the Porter hypothesis in general. However, not all policies have the same impact – non-market based policies are the most detrimental to productivity growth – and not all highly polluting firms are affected in the same way – the negative impact is mitigated for large firms, which may benefit from easier access to finance and greater innovativeness.

Economic evaluation of a business model of a Vanilla planifolia bio-factory using BIT® bioreactors

Objective: To evaluate the economic and financial viability for the implementation of a biofactory responsible for the in vitro propagation of Vanilla planifolia with TIB® bioreactors. Design/methodology/approach: A completely randomized design was used. The data were processed with the IBM SPSS Statistics software (version 21). A Mann-Whitney U test was performed (p≤ 0.05). An Economic-Financial Evaluation was carried out, determining the main economic indicators: Profitability, Minimum Acceptable Rate of Return (MARR), Internal Rate of Return (IRR), Net Present Value (NPV) and Benefit-Cost Ratio (B/C R). Results: TIB® temporary immersion bioreactors were used in this study. An average multiplication rate of 18.37 shoots per explant was obtained. When performing the economic-financial analysis of this agribusiness model over a five-year horizon, it yielded an Internal Rate of Return of 12.36%, a Benefit-Cost Ratio of 1.81, and a Net Present Value of MX$286,506.73 pesos (US$ 14,474.93), with a payback period of two years and seven months. Limitations on study/implications: Using semi-solid culture media in the multiplication stage in vanilla decreases the production capacity and significantly lowers the profitability of the biofactory. Findings/conclusions: The profitability of a biofactory for the production of vanilla depends on the multiplication rate, achieved in this case satisfactorily through the use of TIB®. This vanilla biofactory agribusiness model using bioreactors can be adopted by investors as an economic development strategy.

157 Budget impact analysis of Holter monitors provision in an outpatient clinic

Abstract Background Outpatient clinic attendees (aged >64) commonly present with falls, dizziness, syncope and palpitations. The most common non-invasive investigation ordered includes continuous ambulatory electrocardiography monitoring, namely the Holter monitor. The clinic is outsourcing Holter monitor requests to the Cardiology Department, with a long waiting list. If the patient wishes the test to be done sooner in a private hospital, it costs between 160 to 295 euros, covered by the patient’s private healthcare insurance. Methods A budget analysis was carried out to further evaluate by provisioning 5 Holter monitors in the outpatient clinic to quicken patient turnover and reduce the cardiology department waiting list. The intervention scope was limited to the designated clinic of approximately 450 patients a month. The intervention is not for generating revenue for the clinic. The budget analysis doesn’t include sensitivity analysis from the best-case towards worst-case scenarios of Holter frequency usage and duration of Holter monitoring. The objectives of the proposed change are to lessen the turnaround time by 20% for the patients from being assessed until discharge from the clinic without having delayed investigation of the Holter monitor, to have a timely and accurate diagnosis of suspected arrhythmia and the appropriate management within the new intervention. Results The decision tree, utilising the Decision analytic modelling, resource identification, cost implication, estimated changes including 2-hour staff training, capital, year one to year five costs, potential cost savings year-on-year, cost-per-wear comparison against the private hospital provider, pre and post-intervention scenario analysis were constructed. Conclusion The budget impact analysis designed a simple cost calculator to add additional tests of Holter monitors that rely on the decision model approach. It shows a potential cost saving within a five-year horizon and increases the number of patients’ attendance by optimising patient turnover. Apart from the cost and organisation, there are other positive impacts towards financial and clinical areas, ensuring high-quality service for the population.

Market participants or the random walk – who forecasts better? Evidence from micro-level survey data

We analyse micro-level data concerning four financial variables in Sveriges Riksbank's Prospera Survey to evaluate the precision of forecasts provided by professionals active in the Swedish fixed-income market. Our results indicate that for the SEK/EUR and SEK/USD exchange rates, and the five-year government bond yield, none of the market participants that frequently participate in the survey manage to significantly outperform the random-walk forecast. For the central bank's policy rate, the market participants typically have a statistically significant higher forecast precision than the random-walk forecast at the three-month horizon; however, at the two- and five-year horizons, the random-walk forecast typically outperforms the market participants.

Optimizing investment and transportation decisions for the European natural gas supply chain

We address the European natural gas supply chain with several tiers, including producers, mid-streamers, and consumers, where natural gas and Liquefied Natural Gas (LNG) could be traded via long-term contracts or spot markets. This network problem is formulated as a non-linear mixed-integer programming model which provides the optimal production and export decisions of producers, import and storage decisions of mid-streamers, and infrastructure investment decisions of European Union (EU) countries with respect to new pipelines and LNG regasification terminals that maximize the total social welfare in the EU natural gas market over a five-year horizon. We conduct several case studies to examine this network under different conditions. We first compare the actual and optimal decisions to provide insights. Then, we examine the effect of infrastructure decisions on social welfare. Our results reveal that new infrastructure investments increase the total social welfare by nearly three billion. In addition, we examine its sensitivity to the exclusion of Russian gas supply from the market with and without the infrastructure decisions. Results suggest that if Russian gas supply is excluded from the market, then the social welfare and cumulative natural gas consumption of 26 EU countries decrease by 10% and 15%, respectively and that considering infrastructure investments on LNG terminals and pipelines would reduce supply risk of consumer countries.

El Plan de Recuperación, Transformación y Resiliencia y su impacto macroeconómico desde una perspectiva sectorial

Rationale The Recovery, Transformation and Resilience Plan (RTRP), linked to Next Generation EU, details an investment programme that represents a unique opportunity to facilitate the structural transformation of the Spanish economy, on account of both the plan’s envelope (around €69.5 billion or 5.6% of GDP in 2019) and its emphasis on the challenges posed by digitalisation and the green transition. A sectoral classification of how those investments are allocated is therefore interesting in order to quantify their macroeconomic impact, taking into account the interplay between the different sectors of activity. Takeaways •According to the findings, fully absorbing the RTRP funds would have a direct impact on GDP of 1.15% in annual average terms over a five-year horizon, although this figure could rise to 1.75% when considering spillover effects between sectors. •The estimated effects are heterogeneous across sectors; the sectors benefiting the most are those linked to the digitalisation process (information and communication, and professional and technical services) and the construction sector, owing to investment in public infrastructures related to the green transition. •However, rigidities in the reallocation of resources between sectors of activity could limit the macroeconomic effect of the investments envisaged in the RTRP. These factors could reduce the estimated impact from 1.75% to 1.3% of GDP.

Advances in the eradication of foot-and-mouth disease in South America: 2011-2020.

For more than 70 years, the countries of South America have been attempting to eliminate foot-and-mouth disease (FMD), but a regional strategy had not been established by all the affected countries until 1988. The Action Plan 1988-2009 of the Hemispheric Program for the Eradication of Foot-and-Mouth Disease (PHEFA 1988-2009) resulted in an FMD-free status in 88.4% of the bovine population of South America. However, countries of the Andean sub-region maintained an FMD endemic. In addition, sporadic outbreaks in vaccinated cattle populations have been reported in countries of the Southern Cone, endangering the disease-free status in these countries. Within this context, the PHEFA 2011-2020 was approved to eliminate FMD from the subcontinent, and this review describes the most important milestones during its execution. FMD in Ecuador and sporadic outbreaks in the Southern Cone sub-region were effectively eliminated. The outbreaks that occurred in Colombia in 2017 and 2018 were successfully controlled. The type C virus was removed from the vaccines in use in most countries, based on a risk assessment. This review also describes the progress made by the countries advancing toward official recognition as FMD-free in all their territories, with Bolivia, Brazil, and Peru leading the progressive suspension of vaccination to achieve FMD-free status without vaccination. Consequently, at the end of PHEFA 2011-2020, Venezuela was, and still is, the only country in the region whose control program has suffered setbacks, and no evidence has suggested that the transmission and infection of the bovine population have been eliminated. At the end of 2020, a new PHEFA Action Plan 2021-2025 was approved with a five-year horizon, to complete the eradication of the disease in the Americas.

The effect of screening on the health burden of chlamydia: An evaluation of compartmental models based on person-days of infection.

Sexually transmitted diseases (STDs) are detrimental to the health and economic well-being of society. Consequently, predicting outbreaks and identifying effective disease interventions through epidemiological tools, such as compartmental models, is of the utmost importance. Unfortunately, the ordinary differential equation compartmental models attributed to the work of Kermack and McKendrick require a duration of infection that follows the exponential or Erlang distribution, despite the biological invalidity of such assumptions. As these assumptions negatively impact the quality of predictions, alternative approaches are required that capture how the variability in the duration of infection affects the trajectory of disease and the evaluation of disease interventions. So, we apply a new family of ordinary differential equation compartmental models based on the quantity person-days of infection to predict the trajectory of disease. Importantly, this new family of models features non-exponential and non-Erlang duration of infection distributions without requiring more complex integral and integrodifferential equation compartmental model formulations. As proof of concept, we calibrate our model to recent trends of chlamydia incidence in the U.S. and utilize a novel duration of infection distribution that features periodic hazard rates. We then evaluate how increasing STD screening rates alter predictions of incidence and disability adjusted life-years over a five-year horizon. Our findings illustrate that our family of compartmental models provides a better fit to chlamydia incidence trends than traditional compartmental models, based on Akaike information criterion. They also show new asymptomatic and symptomatic infections of chlamydia peak over drastically different time frames and that increasing the annual STD screening rates from 35% to 40%-70% would annually avert 6.1-40.3 incidence while saving 1.68-11.14 disability adjusted life-years per 1000 people. This suggests increasing the STD screening rate in the U.S. would greatly aid in ongoing public health efforts to curtail the rising trends in preventable STDs.

Projected impact of treatment intensification with statin, ezetimibe, and statin plus ezetimibe fixed-dose combination on MACE across six countries.

The 2019 European Society of Cardiology/European Atherosclerosis Society (ESC/EAS) dyslipidaemia guidelines recommend achievement of low-density lipoprotein cholestrol (LDL-C) goals based on an individual's risk. We aimed to evaluate the impact of guideline adoption with statin, ezetimibe, and statin plus ezetimibe fixed-dose combination (FDC) on LDL-C goal achievement and incidence of major adverse cardiovascular events (MACE) across six countries. A simulation model with a five-year horizon (2020-2024) was developed based on Institute for Health Metrics and Evaluation Global Burden of Disease Study database with a business-as-usual (BAU) scenario representing status quo, intervention scenario-1 representing treatment with statin and ezetimibe as separate agents, and intervention scenario-2 representing treatment with statin or statin plus ezetimibe FDC. MACE was defined as the composite of myocardial infarction, ischaemic stroke, and cardiovascular death. The mean population LDL-C was reduced from 4.25 mmol/L in the BAU scenario, to 3.65 mmol/L and 3.59 mmol/L in intervention scenarios-1 and -2, respectively. Compared with BAU, intervention scenarios-1 and-2 resulted in relative reduction of MACE by 5.4% and 6.4% representing ∼3.7 and 4.4 million MACE averted, respectively, across six countries over 5 years. The absolute benefit in terms of MACE averted was highest for China, whereas France had highest relative reduction in MACE with both intervention scenarios compared with BAU. The 2019 ESC/EAS guideline-based treatment intensification with strategies based on statin, ezetimibe, and statin plus ezetimibe FDC is estimated to result in a substantial population-level benefit in terms of MACE averted compared with BAU.

Long-horizon stock valuation and return forecasts based on demographic projections

We incorporate low-frequency information from demographic variables into a simple predictive model to forecast stock valuations and returns using demographic projections. The demographics appear to be an important determinant of stock valuations, such as the dividend–price ratio. The availability of long-term demographic projections allows us to provide (very) long-horizon forecasts of stock market valuations and returns. We also exploit the strong contemporaneous correlation between returns and valuations to improve return forecasts — something which is not possible in a predictive regression with only lagged predictors. Extensive pseudo out-of-sample forecast comparisons and tests demonstrate the predictive value that an accurate demographic projection can deliver. Although the availability of historical Census Bureau projections is limited, we demonstrate that they could have been employed in real time to improve true long-horizon stock return prediction. We show how the model can be used to adjust predictions under alternative demographic assumptions, incorporating, for example, the demographic impact of COVID-19 or recent changes to immigration policy. • Demographic ratios help predict valuation ratios, such as the dividend–price ratio. • Models including future demographic projections can outperform a model containing only current demographic information. • Traditional predictive regression can be augmented to include predicted values of demographic ratios. • Demographic predictions improve both pseudo and true out-of-sample stock return prediction at the five-year horizon.

Mechanical Thrombectomy for Acute Ischemic Stroke Due to Large Vessel Occlusion in Argentina: An Economic Analysis

ObjectivesMechanical thrombectomy (MT) after intravenous thrombolysis (IV-tPA) is an effective and cost-saving treatment for stroke due to large vessel occlusion. However, rates of MT use are low in Argentina. This study was designed to estimate the economic value and the budget impact of incorporating MT after thrombolysis, simulating scenarios from Argentinian compulsory social health insurance (Obras Sociales) and private insurances (Empresas de Medicina Prepaga). Materials and methodsWe adapted a previously published cost-utility and budget-impact (CUA and BIA) model to the Argentinian setting. The CUA was carried out for a lifetime horizon with efficacy inputs from the SWIFT PRIME clinical trial. For seven possible health states, we identified local costs (Argentinian Pesos AR$), utility (QALY), and transition/distribution probabilities (5% discounted rate) and performed deterministic and probabilistic sensitivity analyses. The BIA was based on a six-step approach and a static model for a five-year horizon, and two scenarios (staggered growth and no growth). ResultsDespite higher incremental procedure costs, IV-tPA and MT was dominant over IV-tPA alone (AR$1,049,062 overall savings). Cost-effectiveness remained in the deterministic sensitivity analysis (100% probability of cost-effectiveness). Increased MT procedure volume resulted in savings in years three (0.96%), four (2.6%), and five (4.4%). By year five, 1,280 patients were treated with MT (versus 480) with overall savings of 1.8% (AR$817,244,417). ConclusionsMT after IV-tPA is cost-effective in Argentina. Savings offset the incremental hospitalization and long-term costs from the third year onwards. With increased, access the superior efficacy of MT mitigates future disability and comorbidity, reducing overall expenses.

Inspection based risk management of electric distribution overhead lines

This paper introduces a comprehensive process based on inspection for determination of medium voltage (MV) overhead line condition and it was tried that all factors influencing the outage of distribution network integrated into one index that called condition index. A condition based failure rate model has been proposed and its unknown parameters are calculated based on historical data. Shortest path problem (SPP) model has been proposed for the long term scheduling of maintenance and reinvestment. Objective function includes sum of the reinvestment, maintenance costs, failure costs and energy not supplied (ENS) costs with considering budget and labor constraints. Finally, as a result of this research, optimal combination of various actions such as reinvestment, preventive maintenance (PM) and tree trimming and it’s scheduling has been determined over the ten and five-year horizon. Results confirmed acceptable performance of proposed method because of compliance with actual condition and engineering judgment.

Towards a target employment rate within age and gender groups

Abstract Quarterly employment rates in European countries are analysed in terms of the likelihood of achieving a specific employment rate within age and gender groups in a five-year horizon. The German employment rate serves as a benchmark for this research. The likelihood is estimated by a Monte-Carlo simulation based on the class of exponential smoothing models. The research presents a pessimistic prognosis of employment rates in European countries with respect to young and partly to older workers.

Comparative economic evaluation of renal replacement therapies in Argentina, Costa Rica, and UruguayAvaliação econômica comparativa de terapias de substituição renal na Argentina, na Costa Rica e no Uruguai

RESUMENObjetivo.Evaluar las diferencias de costos y prevalencia de las terapias de remplazo renal (TRR) como el trasplante, la diálisis peritoneal y la hemodiálisis en Argentina, Costa Rica y Uruguay, mediante estrategias costo-efectivas de difusión.Métodos.Costos y prevalencia de principales financiadores y prestadores por país, y análisis de costo-efectividad mediante modelo de Markov a 5 años, evaluando estrategias de asignación de recursos expresadas por razón incremental de costo-efectividad en costo por año de vida ajustado por calidad.Resultados.Se observa dispersión entre los países en el acceso y los valores prestacionales de TRR, que afectan su prevalencia y el punto de equilibrio monetario. Desde el punto de vista de los costos, es más eficiente promover la realización de trasplantes y de diálisis peritoneal, y desalentar la indicación de hemodiálisis, aunque la disponibilidad de cada TRR por país requirió evaluaciones particulares.Conclusiones.Promover la realización de trasplantes ahorra costos, aunque los puntos de equilibrio variables requieren determinar diferentes umbrales de costo-efectividad por país. En Argentina y Uruguay, la administración de TRR mejoraría su eficiencia si se aumentan la cantidad de pacientes en diálisis peritoneal y las tasas de donación para trasplantes. En Costa Rica (donde hay tasas elevadas de trasplantes y margen presupuestario), la incorporación de técnicas dialíticas se ajusta por demanda e incidencia de pacientes con ERCT.

Sovereign Default Forecasting in the Era of the COVID-19 Crisis

The COVID-19 crisis has revealed the economic vulnerability of various countries and, thus, has instigated the systematic exploration and forecasting of sovereign default risks. Multivariate statistical and stochastic process-based sovereign default risk forecasting has a 50-year developmental history. This article describes a continuous, non-homogeneous Markov chain method as the basis for a COVID-19-related sovereign default risk forecast model. It demonstrates the estimation of sovereign probabilities of default (PDs) over a five-year horizon period with the developed model reflecting the impact of the COVID-19 crisis. The COVID-19-adopted Markov model estimates PDs for most countries, including those that are advanced with AAA and AA ratings, to suggest that no sovereign nation’s economy is secure from the financial impact of the COVID-19 pandemic. The dynamics of the estimated PDs are indicative of contemporary evidence as experienced in the recent financial crisis. The empirical results of this article have policy implications for foreign investors, sovereign lenders, export finance institutions, foreign trade experts, risk management professionals, and policymakers in the field of finance. The developed model can be used to timely recognize potential problems with sovereign entities in the current COVID-19 crisis and to take appropriate mitigating actions.

Modelling the impact of Artificial Intelligence on the labour market in Czechia

Abstract This article describes an original model developed in the Technology Centre CAS for the estimation of the impact of Artificial Intelligence (AI) on the labour market in Czechia. On the contrary to the previous estimates, this model is based on the comparison of projected future technical capabilities of AI with a mix of capabilities needed in different job categories. Both the importance and the level of capabilities are taken into account in order to assess the impact of AI on jobs in three different time horizons. Based on the model calculations, it can be expected that on the five-year horizon the AI will be able to replace more than 50% of the required capabilities in 11 % of the occupations. On the thirty-year horizon, AI can replace over 50% of capabilities in the vast majority of the current professions. At the same time, new professions will continuously emerge, though they will place different demands on their performers and will require different skills and capabilities in comparison to current professions. The model and its results may be effectively used for efficient adaptation of education, lifelong learning and retraining to the changing nature of work, and related new demand for workers’ capabilities.

The economic impact of sudden cardiac arrest

BackgroundThere are 20,000 sudden cardiac arrests (SCAs) in Australia annually, with 90% case-fatality. ObjectiveThe present study calculated both the health and economic impact of SCAs in Victoria, Australia. MethodsData on all SCAs attended by Ambulance Victoria from July 2017 to June 2018 were collected regarding age, gender, and survival to hospital, discharge and 12 months. Pre-SCA employment status of all patients was modelled using age and gender-matched Australian economic data. A Markov state-transition model with a five-year horizon calculated health and economic impact in years of life lived (YLL), productivity-adjusted life years (PALYs) and gross domestic product (GDP) lost. A counterfactual Markov state-transition model assessed outcomes of an identical cohort of patients who did not experience SCA. All values were discounted by 5%. ResultsIn 12 months, 4637 people suffered SCAs in Victoria, of whom 1516 (32.7%) were working at the time. 695 patients (15.0%) survived to hospital, 325 (7.0%) to discharge, and 303 (6.5%) to 12 months. In five years following their SCA, the cohort lost 15,922 years of life and 2327 PALYs. Reduced productivity led to GDP losses of AUD$448 million (92.8% relative reduction). Extrapolated to the 20,000 SCAs occurring across all of Australia, total GDP losses approached AUD$2 billion. ConclusionThe health and economic burden of SCAs is high, predominantly underpinned by very high mortality. Annual national losses approach AUD$2 billion (USD$1.42 billion) and are comparable to productivity losses from all cancers combined. Prioritising research and state-of-the-art care for SCA patients appears economically sound.

Macroprudential Policy Analysis via an Agent Based Model of the Real Estate Sector

In this paper, we extend and calibrate with Italian data the Agent-based model of the real estate sector described in Baptista et al., 2016. We design a novel calibration methodology that is built on a multivariate moment-based measure and a set of three search algorithms: a low discrepancy series, a machine learning surrogate and a genetic algorithm. The calibrated and validated model is then used to evaluate the effects of three hypothetical borrower-based macroprudential policies: an 80 per cent loan-to-value cap, a 30 per cent cap on the loan-service-to-income ratio and a combination of both policies. We find that, within our framework, these policy interventions tend to slow down the credit cycle and reduce the probability of defaults on mortgages. However, with respect to the Italian housing market, we only find very small effects over a five-year horizon on both property prices and mortgage defaults. This latter result is consistent with the view that the Italian household sector is financially sound. Finally, we find that restrictive policies lead to a shift in demand toward lower quality dwellings.

The Impact of past Pandemics on CO2 Emissions and Transition to Renewable Energy

We estimate the short- to medium term impact of six major past pandemic crises on the CO2 emissions and energy transition to renewable electricity. The results show that the previous pandemics led on average to a 3.4-3.7% fall in the CO2 emissions in the short-run (1-2 years since the start of the pandemic). The effect is present only in the rich countries, as well as in countries with the highest pandemic death toll (where it disappears only after 8 years) and in countries that were hit by the pandemic during economic recessions. We found that the past pandemics increased the share of electricity generated from renewable sources within the fiveyear horizon by 1.9-2.3 percentage points in the OECD countries and by 3.2-3.9 percentage points in countries experiencing economic recessions. We discuss the implications of our findings in the context of CO2 emissions and the transition to renewable energy in the post-COVID-19 era.