This study set out to investigate the interactions between business cycles, financial cycles and monetary policy in South Africa. Explicitly, the study aims to examine the role of financial factors in business cycle models and the possibility of a unified macroeconomic framework in South Africa. Further, the study assesses the effects of demand shocks, supply shocks, interest rate shocks, and financial shocks on macroeconomic fluctuations. The study applied an analytical approach integrating the Generalised Method of Moments and System Generalised Method of Moments with a Structural New Keynesian Dynamic Stochastic General Equilibrium framework. Accordingly, it was concluded that the financial cycle plays a significant role in business cycle models and is a main driver of macroeconomic fluctuations in South Africa. Further, a unified macroeconomic framework for monetary policy analysis that links the financial system to the real economy in South Africa possibly exists. This study contributes to the South African Reserve Bank’s efforts by deepening understanding of the interactions between the financial system and the real economy and their implications for monetary policy in South Africa. By comparing the standard Taylor rule with a finance-augmented Taylor rule in a DSGE framework, the study helps answer the question of whether financial stability should be adopted as a second objective of monetary policy.

Depression is an increasingly severe public health challenge worldwide, causing substantial health losses and profoundly impacting national economies. As China, India and the USA bear the largest share of the global depression burden and have different developmental and demographic profiles, quantifying the condition's long-term macroeconomic effects in these countries is crucial for gaining insight into the relationship between mental health and economic development worldwide. We used a health-augmented macroeconomic model to assess the macroeconomic impact of depression, comparing the difference in gross domestic product (GDP) between a status quo scenario and a counterfactual scenario in which depression was assumed to be completely eliminated between 2025 and 2050. The model incorporated human and physical capital channels, capturing productivity losses, reduced labour supply and declines in household savings caused by medical expenditures. Data were drawn from multiple publicly available sources, including literature, the Global Burden of Disease Study and the World Bank. From 2025 to 2050, the cumulative macroeconomic burden of depression is projected to reach INT $3,340billion across the three countries. The USA is expected to bear the largest total and per capita losses, at INT $1,416billion and INT $4,110 per person respectively. India would follow with INT $1,100billion and INT $762 per person, while China would account for INT $873billion and INT $615 per person. Across different economic models, depression has a significant and sustained negative impact on long-term macroeconomic development. Policymakers should take prompt action to implement effective prevention and management strategies to curb the growing health and economic impacts of depression.

This study examines degrowth pathways as an alternative socio-economic approach that challenges the assumption that continuous economic growth is a prerequisite for human well-being and environmental sustainability. The central question is whether an intentional reduction in production and consumption could be compatible with a sustainable and equitable society. However, despite rising academic interest, quantitative tools to assess degrowth remain limited. To address this gap, this study compares three macroeconomic models based on different modelling typologies: International Futures (IFs), LowGrow SFC, and EUROGREEN. Each model’s structure, assumptions, and capacity to simulate degrowth-oriented policies were analysed in the context of the energy sector and energy transition. In IFs, a tailored degrowth scenario was created by adjusting 60 parameters obtained from the degrowth literature. In LowGrow SFC, a smaller but highly specific set of parameters was modified through its interactive interface. EUROGREEN directly enabled degrowth simulations via predefined policy packages, emphasizing sufficiency, redistribution, and behavioural change. The analysis shows that the models capture degrowth in distinct ways, reflecting their structural foundations. While IFs struggle with conceptual coherence, LowGrow SFC offers a consistent post-growth framework, and EUROGREEN aligns most closely with degrowth principles. Across models, degrowth scenarios consistently reduced CO 2 emissions to meet climate targets. The results suggest that abandoning a growth-oriented paradigm can support both social well-being and the energy transition, provided it is accompanied by robust redistributive and labour policies.

Diabetes imposes a substantial health burden, yet its macroeconomic consequences remain incompletely quantified. Here we use a health-augmented macroeconomic model to estimate output losses attributable to diabetes across 190 countries and territories during 2021-2050. We project that diabetes could reduce cumulative global output by 5.177 trillion international dollars over this period, with substantial heterogeneity in relative losses as a share of GDP across countries. Country-level burdens vary markedly, reflecting heterogeneity in demographic trends, macroeconomic conditions, diabetes prevalence, health-system capacity and treatment costs. Most projected output loss is attributable to diabetes-related disability rather than premature mortality. In this work, we provide comparable cross-country estimates of the long-run macroeconomic burden of diabetes, informing prioritization of prevention, treatment policies, and related investments.

The supposed regressivity of primarily price-based climate protection policy instruments often hampers an evidence-based discussion at the political level and is used as an argument against the implementation of corresponding measures. To assess the distributional implications of decarbonization, we developed climate policy scenarios for the buildings and mobility sectors including targeted compensation measures in close cooperation with stakeholders to identify socially acceptable pathways. Subsequently, three bottom-up sectoral models (for transport demand, vehicle choice and the building stock) were linked to a macroeconomic model to analyze the emission impact, the macroeconomic ramifications and the distributional effects of the policy portfolios on different household types. Our modeling results show that full decarbonization of housing and mobility in Austria by 2040 is achievable but requires (1) a comprehensive policy portfolio with rapid implementation to ensure the phase-out of fossil fuels and (2) targeted compensation for low- and middle-income households to enhance fairness and public acceptance. While climate policies have positive macroeconomic effects, they risk exacerbating income inequalities unless compensation measures, such as recycling revenues from carbon pricing, are implemented. These measures can help mitigate adverse distributional effects and enable investments in renovation, new heating systems and sustainable transport infrastructure, ensuring a just transition. • We analyze two policy portfolios for decarbonizing mobility and housing in Austria. • We engage stakeholders to design compensation measures for vulnerable households. • Our novel approach links one macroeconomic and three sectoral bottom-up models. • We explore macroeconomic impacts, vertical and horizontal distributional effects. • Results provide guidance for designing effective and equitable climate policies.

Abstract People are increasingly feeling global warming's effects through extreme heat and natural disasters. How do these climate shocks affect political attitudes? We argue that the effect of climate‐related experiences depends significantly on self‐interest. People in more vulnerable locations are more likely to respond to climate shocks with greater concern and more support for mitigation policy. We test this hypothesis with a macroeconomic model of climate change, geospatial data on climate shocks, and survey data of 148,712 people across 137 countries, and over time with the same 9,500 individuals in the United States. The results show that climate shocks heighten risk perceptions and lead to greater support for mitigation policies only among people in climate‐vulnerable places. This responsiveness to experience is most evident in democratic countries and among people whose livelihoods depend on the weather. Integrating political economy and behavioral theories helps to explain how political attitudes change.

Application of Statistical Learning in Macroeconomic Uncertainty Modeling

Abstract. Integrated Assessment Models (IAMs) provide low-carbon scenarios at a global scale or for broad economic aggregates, as running these models for every country would be computationally demanding. Lack of national results from IAMs, hinders the enhancement of NDCs (Nationally Determined Contributions) and LTS (Long Term Strategies) in accordance with the 1.5 °C target and best available science. To address this limitation, we have developed DSCALE (Downscaling Scenarios to the Country level for Assessment of Low carbon Emissions), a novel algorithm designed to downscale regional IAMs outcomes to the country level. In this paper we present the methodology and show results for both current policy and 1.5 °C scenarios from the NGFS 2023 release. This downscaling tool provides insights for energy and emission developments and targets at the country level consistent with global scenarios from IAMs. Moreover, this tool facilitates the integration of IAMs results with other models and tools requiring energy and emissions data at the country level, such as the macroeconomic NiGEM model.

Abstract Entrepreneurship is crucial for job creation and economic growth. But not all entrepreneurs are alike. For instance, firms of serial entrepreneurs — owners of multiple businesses — have been documented to outperform other businesses. In this paper, we provide novel evidence showing that firms of serial entrepreneurs are also important for macroeconomic outcomes. Using unique administrative data from Portugal, we document that serial entrepreneur firms (i) disproportionately contribute to aggregate job creation and productivity growth, (ii) help shape aggregate business dynamism, and (iii) are more likely to be high-growth (“gazelles”). This superior performance is largely driven by entrepreneurs’ education, ability, past managerial experience, and lower indebtedness of their firms. We discuss the implications of our findings for macroeconomic models — which typically ignore serial entrepreneurs.

Falls contribute to substantial and growing health losses worldwide, yet how they relate to economic output has not been quantified at the global level. Here we estimated the macroeconomic losses attributable to falls in 190 countries and territories for 2020-2050 using a health-augmented macroeconomic model capturing reduced labour supply from mortality and morbidity; heterogeneity in human capital by age, education and experience; and lower capital accumulation from treatment spending. Under the main specification, falls are projected to reduce global output by INT$3.939 trillion (95% uncertainty interval, 3.788-4.096), or 0.088% of the cumulative world gross domestic product. The largest absolute losses occur in the USA, followed by China and Germany. Low- and middle-income countries account for 74.8% of fall-related disability-adjusted life years but only 32.6% of the estimated economic loss, indicating a marked mismatch between health burden and monetized macroeconomic burden. The macroeconomic burden of falls is unevenly distributed globally, underscoring the need for stronger prevention efforts.

ABSTRACT We propose a demand‐led heterogeneous firm macroeconomic model to study the impact of an exchange rate devaluation on output and financial stability. We simulate the model and find that, in the presence of foreign debt, a devaluation can have contractionary effects. This effect is mediated by the responsiveness of exports to the exchange rate and is attenuated when the traditional trade channel is stronger. Still, the balance sheet effect operates increasing indebtedness and financial instability.

This paper proposes an improved methodology for measuring weighted average interest rates on loans to non-financial corporations in Russia. Recognising that current aggregates – focused on newly issued fixed-rate loans to non-affiliated borrowers – omit key market developments, the study segments loans by rate type (fixed vs. floating) and timing of rate-setting relative to disbursement. Using granular bank-level data, we show these refinements can shift rate estimates by up to 2–3 percentage points. Incorporating these indicators into macroeconomic models highlights potential underestimation of monetary policy transmission effects. The findings emphasize the analytical value of richer loan rate aggregates for policy and research.

Estimating the economic burden of lower respiratory infections in China from 2020 to 2040: a health-augmented macroeconomic modelling study.

Effect of an mHealth-assisted multifaceted lifestyle intervention on body-mass index, hepatic fat content and stiffness in children with overweight or obesity: a cluster randomised controlled trial.

Cross-border tourism in North America: A hybrid deep learning framework with macroeconomic indicators

We develop a heterogeneous-firm macroeconomic model to investigate how tax evasion affects the productivity distribution in general equilibrium. In our model, entrepreneurs choose capital and labor to produce with their firms, invest in bonds, and evade taxes to maximize their intertemporal utility, derived from dividends. Firms face leverage constraints and uninsurable productivity shocks. The results reveal that tax evasion redistributes capital toward low-productivity firms, relaxing their leverage constraints. It also increases public debt, raising the cost of capital and crowding out firms at the margin. As a result of these forces, we demonstrate that (i) the decline in high-productivity firms’ average productivity drives the negative correlation between the size of the shadow economy and aggregate productivity, and (ii) the productivity gains from reduced tax evasion are smaller in economies with higher public debt and stricter leverage constraints. • Tax evasion redistributes capital from high- to low-productivity firms. • Tax evasion raises public debt and debt crowding-out hits firms at the margin. • High-productivity firms drive shadow economy impact on Total Factor Productivity. • TFP gains from reduced evasion are smaller in financially underdeveloped economies.

Water scarcity is increasingly recognized as a systemic economic constraint, with impacts that extend far beyond directly water-using sectors. Computable General Equilibrium (CGE) models constitute a powerful tool for capturing the indirect and structural effects of water scarcity across interconnected markets, yet their application to water resources poses distinctive conceptual, methodological, and data challenges. This paper reviews how water has been conceptualized and operationalized within CGE models, focusing on the treatment of water scarcity, allocation mechanisms, and economic valuation under conditions characterized by weak or missing price signals. Rather than providing an exhaustive catalogue of applications, the analysis compares alternative modelling strategies—embedding water in land, treating water as an independent production factor, representing water implicitly through productivity effects, and modelling water as a produced commodity—highlighting their respective advantages, limitations, and suitability for different policy questions. The review shows that no single approach dominates across contexts: implicit representations are often sufficient for climate-impact assessments, whereas explicit formulations are required to analyse water markets, allocation rules, and infrastructure investments. A central challenge across all approaches is the fundamentally non-market nature of water, which complicates calibration, pricing, and the interpretation of economic rents. Additional difficulties arise from spatial and temporal heterogeneity, basin-level constraints, return flows, and water quality differentiation, which standard CGE structures struggle to represent. The paper also shortly discusses recent advances in hybrid modelling frameworks that couple CGE models with hydro-economic models (HEMs). The paper concludes by outlining key directions for future research, emphasizing the need for improved water accounts, dynamic and seasonal modelling, and closer integration between economic and hydrological modelling communities.

Type of the article: Research ArticleAbstractMoney laundering poses serious risks for small open economies by weakening financial stability and reducing trust in the financial system. This paper investigates how central bank digital currencies (CBDCs) can enhance the enforcement of anti-money laundering (AML) policies in these economies. We develop a simple macroeconomic model to examine the trade-offs between stronger financial control and household welfare when digital enforcement tools are introduced. A dynamic model is constructed in which a representative household chooses consumption, labor, and foreign savings under a capital account that allows illicit transfers. The government enforces AML rules by increasing detection probability through CBDC infrastructure. The model compares scenarios with and without CBDCs to assess changes in behavior, illegal outflows, and welfare outcomes. The findings show that CBDCs can reduce money laundering by making transactions more transparent and harder to hide. As detection becomes more likely, the household’s incentive to move funds illegally declines, and the resulting loss of hidden income leads to slightly higher labor effort and lower consumption. The welfare effects depend on the balance between enforcement strength and households’ need for economic flexibility. Policymakers in small open economies can use CBDCs to improve the integrity of financial flows, especially when evasion risks are high. However, effective CBDC design must consider the trade-off between tighter control and households’ ability to manage their finances. This study provides one of the first theoretical frameworks showing how CBDCs reshape the interaction between financial transparency and household welfare in vulnerable economies.AcknowledgmentsWe sincerely thank the Academic Editor for their guidance and support throughout the review process. We are also grateful to the anonymous referees for their constructive and thoughtful comments, which significantly improved the quality of this manuscript.

System-level risks generate volatility that can threaten the stability of public health systems and jeopardise population health. In financial terms, these risks may be systematic, arising from macroeconomic shocks, or systemic, arising from cascading failures due to interconnectedness. Interventions such as disease elimination and eradication (DEE) play a crucial role in mitigating the aggregate impact of such risks. However, conventional health economic evaluations often overlook these broader benefits realised during periods of instability, focusing instead on programme-specific risks under steady-state assumptions. Insights from financial economics can help capture this value and inform a more robust economic appraisal. This paper explores how concepts from financial economics can strengthen conventional health economic methods for evaluating programmes that reduce the aggregate impact of such system-level risks, using DEE as a primary example. It draws on asset pricing theory, macroeconomic models of rare disasters, real options analysis, and discounting practices. Key recommendations include recognising the added value of programmes that perform better during downturns due to the protection they offer against macroeconomic shocks or catastrophic events; using 'real options' thinking to manage uncertainty and preserve flexibility in long-term, high sunk cost projects; and accounting for equity considerations when setting discount rates for programmes with significant intergenerational impacts. The financial economics tools highlighted here could serve as key components of a broader analytical framework, supporting investment decisions that recognise and more accurately capture the value of investments that reduce the aggregate impact of system-level risks.

In this article, the author examines the regional features of the strategic development of the region. From the position of the system approach, the region is considered as a management object consisting of six interconnected macro-subsystems. It provides a social concept for the development of strategic management, explains the goals and criteria for the development of the region, as well as strategic aspects of development. At the end of the article, briefly explains the forecast of the socio-economic development of the region and provides a block forecasting system.