Future Economic Scenarios Research Articles

A machine learning approach to rapidly project climate responses under a multitude of net-zero emission pathways

Navigating a path toward net-zero, requires the assessment of physical climate risks for a broad range of future economic scenarios, and their associated carbon concentration pathways. Climate models typically simulate a limited number of possible pathways, providing a small fraction of the data needed to quantify the physical risk. Here machine learning techniques are employed to rapidly and cheaply generate output mimicking these climate simulations. We refer to this approach as QuickClim, and use it here to reconstruct plausible climates for a multitude of concentration pathways. Higher mean temperatures are confirmed to coincide with higher end-of-century carbon concentrations. The climate variability uncertainty saturates earlier, in the mid-century, during the transition between current and future climates. For pathways converging to the same end-of-century concentration, the climate is sensitive to the choice of trajectory. In net-zero emission type pathways, this sensitivity is of comparable magnitude to the projected changes over the century.

On the adoption of stricter energy efficiency standards for residential air conditioners: Case study Guayaquil, Ecuador

Space cooling is the fastest-growing energy end-use in buildings worldwide, and Ecuador is no exception. Nevertheless, the last update of the Minimum Energy Performance Standards (MEPS) for air conditioners was in 2013 (EER 3.2W/W); since then, no new standards have been proposed in Ecuador. This study is the first assessment of stricter MEPS and estimation of benefits for the consumers and society of the residential sector in Guayaquil, Ecuador. The life cycle cost, payback time, net present value, electricity savings, and CO2 mitigation are the outputs from the Policy Analysis Modeling System (PAMS) methodology followed. The analysis considers future economic scenarios until 2035. Also, a new engineering approach based on linear optimization defines ACs designs in compliance with the proposed MEPS at the lowest cost. Therefore we can avoid setting less ambitious energy-efficiency targets when efficiency options are limited in the market (this is the Ecuadorian case). The analyzed MEPS are those proposed by UNEP and by the renewal program of inefficient equipment of the Ecuadorian Government. Our estimates show that AC demand can reach 17.3% of the total residential electricity demand in the business-as-usual scenario and 21.4% in the high economic growth scenario until 2035.Furthermore, the results show a significant gap between the proposed MEPS which can be progressively bridged. The best standard from the consumer perspective is EER 4.3W/W, while from the societal perspective, it is EER 5.5W/W. Stricter MEPS can reduce AC electricity demand and energy-related emissions between 5.7% and 31%, depending on the selected scenario. Therefore, stricter MEPS for AC represents a cost-effective option to reduce energy needs and emissions from air conditioners and a concrete action to support the national energy efficiency policies and nationally determined contributions for the residential sector.

Financial analytics for interlinking stock market and macroeconomic performance- post financial crisis 2008

Financial analytics has been highly crucial in forecasting possible future economic scenarios. The relationship between a country’s macroeconomic indicators and its stock market has been extensively studied in the literature. Stock prices should be used as leading indications of future economic activity if they accurately reflect the underlying fundamentals. On the contrary, if economic activity follows stock price movement, the outcomes should be the opposite, i.e., economic activity should lead stock price movement. The paper attempts to make use of financial descriptive analytics to explore the interconnection between prominent macroeconomic indicators and stock market activity post ten years of financial crisis 2008. The study’s range is constrained to explore the aforementioned interconnection for the period from September’ 2008 to August’ 2018. The following factors have been found to be related over the long term: GDP, Production Index, Inflation, Exchange Rate, Money Supply, Imports, Exports, FDI, and Stock Market Returns. Shockingly FII has not shown any cointegrating equation. Also causality was observed between stock market and economic indicators. Impulse Response Function (IRF) and Variance Decomposition (VDC) techniques of VAR model are applied to decompose or fractionalize the variability caused by macroeconomic indicators on the BSE Sensex returns which has given some interesting results.

How do stock prices respond to the leading economic indicators? Analysis of large and small shocks

Leading economic indicators provide a glimpse into the future economic scenario, which help predict future business conditions. Do changes in leading economic indicators help predict future stock volatility? Do different shock sizes of this indicator caused by an uncertain financial environment provide valid information for forecasting stock market volatility? To answer this question, this paper investigates the predictive performance of composite leading indicator (CLI) shock sizes on stock price volatility under the framework of the GARCH-MIDAS model from an innovative perspective. Interestingly, we find that the asymmetric shock sizes of the CLI perform best both in a statistical and economic sense.

Multi-Level Nowcasting: Estimation in a Post-COVID Landscape

With the economic upheaval brought by COVID-19, it was very difficult to understand economic events as they unfolded in real time, during unprecedented pandemic conditions. Since existing methods did not adequately address the rapid changes to the economy on a statewide basis, we felt compelled to create a novel approach to (a) bring current critical data and (b) to evaluate the varying impacts of changes occurring in real time. As practitioners, this created actionable data to forecast future economic scenarios using public datasets and readily available spreadsheet software, giving guidance on an economy in conditions with no direct analogue. This paper describes a way to integrate public data to assess present economic changes and describes the approach using straightforward processes and accessible tools. By comparing and contrasting findings in Arizona and Colorado, our analysis of this approach reveals that the updated data showing the current state of the economy (the Nowcast) is a robust approach for creating accurate, current data, and the various methods for further dissection (the Multi-Level component) create informative datasets for a detailed analysis, with the caveat that structural changes to the economy need to be kept in mind so as not to confuse what is firmly known with what is an overly broad application of the method.

Landscape pattern simulation for ecosystem service value regulation of Three Gorges Reservoir Area, China

Landscape pattern regulation would alter regional ecosystem structure, thus affecting ecosystem function and service provision. We analyzed the impact of landscape pattern change on ecosystem service value (ESV) of the Three Gorges Reservoir Area (TGRA). The CA-Markov model was used to map three future (ecological, economic, and eco-economic) scenarios of the TGRA in 2030, then we predicted and compared ESV changes among three scenarios. Our results documented that the total forestland area increased significantly in the ecological scenario, but decreased in the economic scenario. Meanwhile, the construction land area increased in the economic scenario. For the eco-economic scenario, the forestland area change was consistent with the ecological scenario, while the construction land area change was similar to the economic scenario. The ESV of TGRA in 2030 is the highest in the ecological scenario, followed by the eco-economic scenario. Compared to 2015, the total ESV increased in 2030 for both the ecological and eco-economic scenarios, while decreased in the economic scenario. Eco-economic scenario focuses on the coordinated development of ecological protection and economic construction, meeting the needs of economic construction in ecologically fragile areas. This development model will be greatly welcomed by policy makers and effectively promotes sustainable land use in the region. So, we proposed a landscape planning scheme for ecological restoration and economic construction of the TGRA, providing valuable information for decision and policy making and minimizing negative impacts through targeted management measures. Our findings can provide a scientific basis and theoretical practice for environmentally friendly land management.

Narratives of the Future Affect Fertility: Evidence from a Laboratory Experiment

In recent years, fertility rates have declined in most wealthy countries. This phenomenon has largely been explained by focusing on the rise of economic uncertainty. We contribute to this debate by arguing that, under uncertain conditions, narratives of the future—i.e., socially conveyed imagined futures—impact individuals’ decision-making about childbearing. To assess this impact, we conducted (for the first time in fertility intention research) a controlled laboratory experiment in two contrasting settings: Florence (Italy, N = 800) and Oslo (Norway, N = 874). Individuals were randomly exposed to a specific positive or negative future economic scenario (treatments) and were compared with individuals who were not exposed to any scenario (control group). Participants were then asked whether they intended to have a child in the next three years. The results showed a clear causal impact of narratives of the future on fertility intentions among the participants. Moreover, when the actual economic condition at the macro- (country context) or micro-level (labor-market status and characteristics) was more favorable, negative narratives of the future played a more crucial role. Conversely, when the actual economic conditions were less favorable, positive narratives of the future proved especially important. We conclude that, in the era of global uncertainty, individuals respond to more than their actual situation and constraints; narratives of the future create a distance experience from the daily routine that plays a potent role by inhibiting or facilitating fertility decision-making.

Practical Applications of The Outlook for Endowment and Pension Funds

For decades, a 60/40 equity/bond allocation has been the favored allocation method for endowment and pension fund managers. In <ext-link><italic><bold>The Outlook for Endowment and Pension Funds</bold></italic></ext-link>, from the Summer 2021 issue of <italic><bold>The Journal of Wealth Management</bold></italic>, <bold>Haim Mozes</bold>, a professor of accounting at <bold>Fordham University’s Gabelli School of Business,</bold> and <bold>John Steffens</bold>, a founder and managing member of <bold>Spring Mountain Capital</bold>, formulate an outlook for the future performance of the 60/40 allocation. Mozes and Steffens identify the economic conditions that drove the 60/40 allocation’s past success and then forecast future economic scenarios. Most significant to the future performance of endowment and pension funds is the possible scenario of continued low bond yields coupled with low economic growth. In that scenario, low bond yields would produce weak returns on bonds while weak economic growth would produce poor returns on equities; the overall performance of the 60/40 allocation would be weak. The authors assess the strategies that funds are considering in order to meet their target objectives in the event of such a scenario, including increasing allocations to public equities and other risky assets.

The impact of narratives of the future on fertility intentions in Norway

AbstractObjectiveThis study examines the effect of exposure to different economic narratives of the future on fertility intentions of Norwegian couples.BackgroundFertility patterns should not only be interpreted in relation to economic uncertainty conceptualized as objective constraints. One should also consider that subjective narratives of economic uncertainty may have a significant role in fertility decision‐making.MethodData were collected from a controlled laboratory experiment of both partners in heterosexual couples in fall 2019 in Oslo, Norway (N = 838). The participants were randomly assigned to read either a negative or a positive future economic scenario, while a control group was not assigned to any scenario.ResultsThe economic scenarios influenced couples' fertility intentions, with the negative scenario causing a clear decrease in fertility intentions and the positive scenario causing an increase in fertility intentions. Men and women responded in similar ways to the scenarios. The effect of exposure to the scenarios is not moderated by objective measures such as couple employment status and income, except in one case.ConclusionOur experimental setting demonstrates that people's fertility intentions are shaped by their subjective view of the future economic situation.

The impact of agricultural trade approaches on global economic modeling

Researchers explore future economic and climate scenarios using global economic and integrated assessment models to understand long-term interactions between human development and global environmental changes. However, differences in trade modeling approaches are an important source of uncertainty in these types of assessments, particularly for regional projections. In this study, we modified the Global Change Analysis Model (GCAM) to include a novel logit-based Armington trade structure, to examine two approaches to modeling trade: (1) an approach that represents segmented regional markets (SRM), and (2) an approach that represents integrated world markets (IWM). Our results demonstrate that assuming IWM, i.e., homogeneous product modeling and neglecting economic geography, could lead to lower cropland use (i.e., by 115 million hectares globally) and terrestrial carbon fluxes (i.e., by 25%) by the end of the century under the default GCAM scenario, compared with the logit-based Armington SRM structure. The results are highly heterogeneous across regions, with more pronounced regional trade responses driven by global market integration. Our study highlights the critical role that assumptions about future trade paradigms play in global economic and integrated assessment modeling. The results imply that closer harmonization of trade modeling approaches and trade parameter values could increase the convergence of regional results among models in model intercomparison studies.

Dynamic economic resilience scenarios for measuring long-term community housing recovery

ABSTRACT The research measures post-disaster long-term housing recovery to assess community resilient recovery using the case of Broadmoor, a community located in New Orleans. Dynamic economic resilience scenarios calculate post-disaster housing recovery and differences of rebuilding using three housing recovery scenarios (baseline, reference recovery and dynamic economic resilience). The baseline scenario projects changes in housing market values without a disaster. The reference recovery scenario calculates post-disaster housing reconstruction values (e.g. repair rates and housing rebuilding permits), and a hypothetical housing recovery profile using damage assessments and building permits for rebuilding based on available investments (insurance and buy-outs). The dynamic economic resilience scenario models all potential and accelerated investments (uninsured versus insured, or buyouts for homeowners). A future dynamic economic resilience recovery scenario takes into account the benefits of housing reconstruction improvements, (e.g. levee and pump investments). The results identify an ideal sustainable long-term recovery threshold of three years after the disaster event. The results reveal the conceptualised dynamic economic resilience scenarios leads to shorter time-paths for recovery, and that the sustainable long-term recovery threshold is approximately three years after the disaster event.

Predicting economists: Generating scenarios for stress testing future loss reserves

Stress testing under the US Comprehensive Capital Analysis and Review (CCAR) regulations and those of many other countries seeks to assess the full possible financial position of a lender through an economic crisis. The introduction of lifetime loan loss reserves under FASB’s Current Expected Credit Loss (CECL) and IASB’s International Financial Reporting Standards 9 (IFRS 9) rules complicates the task of stress testing, because lenders need to estimate future losses using scenarios that are contingent on the stress testing scenario, but without perfect foresight of the future stress test scenario. This work casts the CECL and IFRS 9 stress testing problem as one of generating future economic scenarios that are consistent with how future economists would create scenarios. To that end, we obtained historic consensus economic scenarios for testing. The results here demonstrate that a second-order Ornstein–Uhlenbeck model fits historic scenarios well and could be used to generate future scenarios that would be a realistic representation of what economists would predict given economic conditions up to that point. This approach was tested for US real gross domestic product (RGDP) and unemployment rate scenarios through the 2009 recession. The RGDP modeling was straight-forward, but we discovered that consensus economic scenarios for unemployment rate appear to be conditional on the phase of the economy.

Business Transformation on Retail Operations Due to COVID-19 and Its Impact on Indian Economy

Year 2020 brought a huge challenge in business environment all over the world due to COVID-19. India is not an exception and faced similar challenges which impacted heavily on the economy. India has a huge retail market being the second largest populous country in the world with huge potential and young workforce. It is an important factor for the GDP growth of any country. The aim of this paper is to compare the past, present and predict the future economic scenario by considering various factors which majorly impacted the retail market due to COVID-19. A huge transformation observed in the retail business. Buyers’ choices shifted away from local retail purchases to online. Buying behaviour and consumer spending have shifted towards online purchases and also card transactions. This research also aims to study the impact of COVID-19 on Indian economy and way out of the downfall. Keywords: Buying Behaviour, Economic Growth, India, Pandemic, Retail Business.

A Large-Scale Optimization Model for Replicating Portfolios in the Life Insurance Industry

Replicating Portfolios for Economic Capital Calculations

Robust Policy in Times of Pandemic

The pandemic exposes policymakers to fundamental uncertainties about future economic scenarios. While policymakers have to act forcefully to mitigate the impact on the economy, these conditions call for policy strategies that are also robust to uncertainty. This article compares two concepts of robust strategies: robust control and robust satisficing. It argues that a robust satisficing strategy is preferred and shows that the crisis responses of governments and central banks in Europe share features of robust satisficing in several dimensions.

Anxiety levels among social work students during the COVID-19 lockdown in Spain

ABSTRACT The COVID-19 pandemic has compelled university students to adapt to remote learning modalities resulting in increased of anxiety symptoms. This study explores levels of anxiety, and risk and protection factors among Social Work students at two universities in southern Spain. Thirty four percent were experiencing severe anxiety, and 28.5% mild to moderate, revealing that anxiety levels had increased significantly. Greater concern about academic situation and future economic scenario, living in an urban area and leave the habitual residence increased anxiety symptoms. By contrast, family income stability and higher social support from relatives reduced anxiety symptoms. These results support the planning of emotional support services for college students, as well as the incorporation in the study plans the acquisition of skills to live better in these conditions.

The Impact of High-quality Development of China’s Economy and the Change of Industrial Structure on Energy consumption in Transportation

This paper explores the impact of high-quality economic development orientation and changes in China’s industrial structure on sustainable transportation development, including the impact of changes in transportation volume, transportation demand characteristics, and transportation energy consumption. the quantitative model of the relationship between macroeconomic factors like industrial structure changes with transportation demand and energy consumption is constructed. On this basis, traffic energy consumption is predicted under the future economic development scenarios. The research shows that the economic development model and the change of industrial structure are highly correlated with the energy consumption of transportation. The economic high-quality development scenario, following the corresponding change of transportation modes will increase the transportation energy consumption per transportation volumes, and the total amount transportation volumes and its energy consumption will decline.

Future economic scenarios of Iran and Russia under sanctions and oil price shocks

The two main current economic problems in Russia and Iran are Western sanctions and oil price spikes. On the one hand, the West introduced economic sanctions against these two countries, which affected the national economy of these two countries. On the other hand, since Iran and Russia are heavily dependent on revenues from oil exports, any sharp changes in world oil prices significantly affect the budgets of these two countries. Despite the implementation of the various strategies of the two countries against sanctions and the collision with oil price shocks, their economies are sensitive to these two hyper problems. The main goal of this work is to study probable scenarios for the future economies of Iran and Russia under the conditions of Western sanctions and oil price fluctuations. Our article shows that for the future economies of Iran and Russia there are four economic scenarios in the form of transformation of the economic structure, rapid economic growth, economic stagnation and economic crisis. In the first scenario, there is an increase in sanctions by the West and its allies against the economies of Iran and Russia, and on the other hand, the price of oil is increasing. This scenario is the most possible future for the economies of Russia and Iran. The second possible scenario for the future economies of Russia and Iran is the rapid economic development and economic growth that will arise as a result of a decrease in political tension with the West, which ended with the lifting of economic sanctions and rising world oil prices. The third option that can be foreseen for the future economies of Russia and Iran is economic stagnation, which will occur if the sanctions of the West and its allies are reduced and world oil prices are reduced again. The fourth possible scenario for the economies of Iran and Russia is an economic crisis. Such a scenario appears when the conflict with the West increases and global oil prices fall, resulting in a large-scale decline and as a result of the economic crisis for the future economies of Iran and Russia. By the way, these two economies must adapt to such unpredictable economic events. They can accelerate import substitution, multilateralism in the Eurasian region, and so on.

Optimal spatial budget distribution of forest carbon payments that balances the returns and risks associated with conservation costs

We determine the optimal spatial budget distribution of forest carbon payments that balances the returns and risks associated with conservation costs (opportunity cost of forestland) affected by future economic growth scenarios using a case study of the central and southern Appalachian region of the USA. A further focus is to evaluate the county-level tradeoffs between the returns and risks of future economic growth that affect the expected benefits and variance of forest carbon storage by constructing a mean–variance tradeoff frontier. Because of concavity of the mean–variance tradeoff frontier, mitigating risk by dispersing budget allocations among counties is advisable, particularly if conservation agencies focus on the returns with little or no regard for the risks associated with future growth at the initial policy-making stage. The different dispersions of the budget among counties for different weights placed on risk minimization provide clear evidence that spatial targeting for conservation and restoration investments such as forest carbon payments needs to consider the risk preferences of conservation agencies regarding conservation costs. Our findings suggest that failing to anticipate the potential risks will lead to suboptimal conservation targets and budget allocations, if conservation agencies are risk averse with little or no regard for the return-maximizing objective.

Energy system analysis for evaluation of sector coupling technologies

Presently no technology for long-term storage of surplus of big quantities of electrical energy is available. Polygeneration power plants with energy storage allow re-conversion of produced energy fuels and contribute to the energy supply security for industry and private households. Further the production of bulk chemicals with low carbon dioxide emissions is possible assuming the availability of hydrogen from renewable energy.The outstanding benefit of such polygeneration power plants is the high load flexibility of plant operation. This advantage over other sector coupling technologies is hardly evaluated by common operating figures. To assess these technologies, which allow crosslinking of power generation, fuel and chemical feedstock supply, they were modeled by quasi-dynamical process simulation. By integration of these models in an energy system analysis different energy storage technologies can be rated in a comparative study. An objective and reliable data base is created in this way for a future energy policy design and for strategic investment decisions in industry.Based on published data a simplified model of the German energy system was established with MatlabSIMULINK® and validated on behalf of data for the year 2015. The model is able to reproduce typical phenomena within German energy sector, e. g. merit order principle and formation of electricity rates at European Energy Exchange (EEX). The model can be adjusted to different (future) economic and social scenarios by different parameter settings.In an energy system analysis for 2030 the energy system model was applied to evaluate the impact of the energy transition from fossil to renewable energy supply system of Germany (the so called “Energiewende”) to the German energy system. Simulation results allow conclusions to future situation of energy system, e. g. development of exchange prices for energy caused by rising residual loads.Subsequently the effects of three polygeneration concepts with energy storage in the energy system of 2030 were investigated under equal boundary conditions. Calculations show lower import/export quantities and changed power plant operation times. So power production from lignite decreases while generation by pumped storage power stations rises. Lower import/export quantities indicating electrical grid reliefs.