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Investment in emerging and developing economies
No full textThe world faces a pressing challenge to meet key development objectives amid slowing growth and rising macroeconomic and geopolitical risks. With the number of job seekers rising rapidly, infrastructure shortfalls continuing to be large, and climate costs mounting, the case for a significant investment push has never been stronger. Yet the capacity to respond in many emerging market and developing economies (EMDEs) has eroded. Since the global financial crisis, investment growth has slowed to about half its pace in the 2000s, with both public and private investment weakening. Foreign direct investment inflows—a critical source of capital, technology, and managerial know-how—have also fallen sharply and become increasingly concentrated, leaving low-income countries (LICs) with only a marginal share. The risks of further retrenchment are significant, as trade tensions, policy uncertainty, and elevated debt levels continue to weigh on investment. Reigniting momentum will require ambitious domestic reforms to strengthen institutions, rebuild macro-fiscal stability, and deepen trade and investment integration—the foundations of a supportive business climate. At the same time, international cooperation is indispensable. A renewed commitment to a predictable system of cross-border trade and investment flows, combined with scaled-up financial support and sustained technical assistance, is essential to help EMDEs—especially LICs and economies in fragile and conflict situations—bridge financing gaps and implement the domestic reforms needed to restore investment as an engine of growth, jobs, and development
Artificial Intelligence and Financial Stability Risks in Nigeria
No full textArtificial intelligence is disrupting the financial sector globally. Artificial intelligence will also affect financial regulation and financial system stability in several ways. Little is known about how artificial intelligence might affect the stability of the financial system. Using a contextual framework and discourse analysis methodology, this article identifies some risks that artificial intelligence could pose to financial system stability in Nigeria. The study focused on how AI risks affect those directly involved in financial stability work in Nigeria. If these risks are mitigated, the adoption of AI for financial stability work will yield positive benefits for financial stability in Nigeria
Modelling Tourism-Environmental Pollution-Health Outcomes Nexus in Africa
No full textThis study used JKS Granger non-causality and 3SLS to examine causal interactions among tourism arrivals, environmental pollution and health outcomes in Africa. The causality results revealed a Granger-caused relationship between tourism arrivals, environmental pollution, and health outcomes. The 3SLS results indicated that tourism is positively linked with health outcomes and environmental pollution, while tourism and health outcomes are also positively related to environmental pollution. Our findings suggest that the government should prioritise sustainable tourism
New Production Function (which is Supported by Empirical Evidences) for an Economy with Deployed Self-Learning Technologies
No full textThe purpose of this paper is to introduce a new production function that takes into account self-learning AI, which can improve itself and therefore productivity without any additional human capital or labor, even though it still requires physical capital. The difference between my production function and any other existing production function is that my production function separates technologies into self-learning and non-self-learning technologies. The value of exponent for the self-learning technologies depends on the value of its base and this is the unique recursive feature of my production function. Unlike in the Mankiw-Romer-Weil production function, in my production function, technology and labor force are separated and this is allowed because I make the technology endogenous. My production function leads to only two possibilities, which are an economy that is in balanced growth path (BGP), and an economy that is in accelerating growth path. The determining factor that decides whether an economy is in BGP or not is the exponent for the self-learning technologies in my production function. If the sum of all exponents is less or equal to 1, then the economy is in BGP, which is consistent with Mankiw-Romer-Weil (1992). If the sum of all exponents is greater than 1, then the economy is in accelerating growth path, which is consistent with Romer (1986). There is no steady state in my production function. I also rule out the possibility of singularity. I support my production function with empirical evidences that confirm that my production function is quite accurate and quite useful for cross-countries comparison. Furthermore, I conduct simulations that show how the U.S economy will transition from balanced growth path to accelerating growth path
Systemic Digitalization of Economic Mechanisms: The Impact of Information Technologies and Artificial Intelligence
No full textMost existing studies of generative artificial intelligence (AI) and information technologies (IT) impact on the economy, focused on the automation of work processes with implications for employment, wages, and productivity. This article broadens the analytical perspective by examining how IT/AI influence the economy through the transformation of economic mechanisms—regulatory structures that ensure coordination and management of joint activities. Drawing on the Institutional Analysis and Development framework, the paper proposes a methodology for describing the universal functions of economic mechanisms and their associated information processes. The information processes are conceptualized as the targets of digitalization, aimed at reducing transaction costs, enhancing productivity, and improving the adaptability of the economy to external changes. The study presents an approach for selecting IT/AI solutions capable of increasing the efficiency of economic mechanisms and introduces the concept of systemic digitalization as a tool for sustainable economic growth. Finally, the paper outlines a “social order” directed at the IT/AI industry—a set of solutions whose implementation may yield substantial positive macroeconomic effects
Regime-Dependent Housing Valuations: Price-Rent Ratios, Volatility, and Structural Breaks in U.S. Markets
No full textWe propose a present value model with structural breaks to explain why U.S. house prices remain persistently high relative to rents—a pattern that standard time-invariant models struggle to capture. Our model uses quarterly data from 1975 to 2023 and incorporates the time-varying volatility of the net discount factor as a key priced risk factor. We find five distinct periods with very different pricing patterns. During the Great Moderation (1981-2001), the usual textbook logic held: higher expected rent growth pushed valuations up, while higher discount rates pulled them down. But in the stagflation era of the late 1970s and again in the recent period (2016-2023), these relationships reversed-higher expected rent growth actually lowered valuations. The two big housing booms of the 2000s and the recent period arose through different forces: the 2000s boom saw prices break free from rents, while the recent period showed an unusually strong reaction to discount rates and a new positive role for volatility, suggesting that uncertainty itself made housing more attractive. These shifting patterns show that what once looked like model failures are better understood as signs of changing market regimes
Assessing the Impact of Sustainability Initiatives on Greenhouse Gas Emissions in Sweden and Finland
No full textClimate change has become a central concern in global policy discourse over the past two decades, motivating nations to adopt a wide range of sustainability initiatives. Analyzing the specific measures implemented and their effectiveness in promoting environmental sustainability is therefore critical. This study aims to evaluate the contribution of various sustainability actions to environmental preservation by focusing on Sweden and Finland, recognized for their leadership in sustainable development. Employing panel least squares and generalized method of moments methodologies using 2010-2020 data, the research rigorously assesses the impact of sustainability initiatives on environmental performance, with a particular focus on greenhouse gas emissions as the primary indicator. The empirical findings reveal that the expansion of renewable energy sources delivers the most prompt and significant reductions in greenhouse gas emissions among the interventions examined. Additionally, investments in green technologies and the issuance of green bonds are shown to enhance environmental quality, with their benefits projected to increase over time. These results highlight the necessity of prioritizing renewable energy development in national climate strategies. Building on these insights, the study presents targeted policy recommendations for Sweden and Finland. It advocates for a strategic shift from compliance-oriented environmental reporting towards the adoption of actionable policies that produce measurable emission reductions. Recommended policy measures include the promotion of sector-specific emission abatement, accelerated development of renewable energy infrastructure, and the encouragement of clean technology innovation through public investment and fiscal incentives. By comparing two Nordic sustainability leaders, Sweden and Finland, this study clarifies which targeted environmental measures are most effective within advanced institutional contexts
Artificial Intelligence and Economic Transformation: Implications for Growth, Employment, and Policy in the Digital Age
No full textThe rapid advancement of Artificial Intelligence (AI) has significantly influenced various industries, labor markets, and government institutions across the globe. This study explores the multifaceted impact of AI on economic growth, employment, and workforce skills. Drawing on sectoral data and comparative literature, the paper analyzes how AI-driven technologies shape growth and labor outcomes. While technological progress creates new opportunities for individuals equipped with advanced skills, it simultaneously displaces traditional, routine-based jobs, resulting in potential unemployment for less adaptable segments of the workforce. The study emphasizes the critical role of governance in addressing the challenges posed by AI and underscores the importance of proactive policy measures to ensure inclusive growth. It further explores the potential of AI in education, particularly in developing countries, where its integration can enhance students' employability skills. However, challenges such as affordability, ethical concerns, and overdependence on technology are also highlighted. The paper advocates for increased investment in reskilling initiatives, AI literacy programs, and the development of adaptive governance structures to facilitate the equitable integration of AI technologies. Overall, the findings offer strategic guidance for policymakers to design adaptive governance structures and reskilling programs
Market Concentration and Innovation Horizon: Evidence from the US Firms
No full textThis study investigates how market concentration, specifically, the degree of competition within a sector impacts different innovation strategies, with particular emphasis on the distinction between long-term and short-term innovation approaches adopted by corporations. The research utilizes a dataset comprising an unbalanced panel of U.S based firms. To generate robust and valid conclusions, the analysis incorporates a suite of statistical and econometric methodologies, such as regression analysis, multicollinearity diagnostics, tests for endogeneity, and comprehensive robustness assessments. These tools are employed to examine the connection between market concentration, measured by the Herfindahl-Hirschman Index, and the innovation horizon, defined as the interval between initial research and development investments and the attainment of innovative outcomes. Furthermore, the robustness analyses confirm the reliability of the findings across various modeling specifications, providing empirical evidence that heightened market concentration correlates significantly with a reduced innovation horizon. The results reveal that firms operating in markets characterized by high concentration are inclined toward short-term innovation strategies, likely as a result of intense competitive dynamics among a limited number of dominant players striving to retain market share. These insights advance the understanding of how market structure shapes the strategic timing of innovation within firms, yielding important implications for innovation policy as well as managerial decision-making
Digital Finance and Institutional Trust in the DRC: Building the Foundations of Inclusive Growth
Get PDFFinancial inclusion has become a cornerstone of development policy, yet progress across low-income and fragile states remains uneven. This paper examines the evolution of financial inclusion in the Democratic Republic of the Congo (DRC) using recent data from the World Bank’s Global Findex 2025 and the GSMA’s 2025 Mobile Money Report. Despite global account ownership reaching 79 percent of adults, fewer than 40 percent of Congolese adults hold a formal financial account. The study situates the DRC within an institutional economics framework and highlights structural constraints including informality, weak trust in financial institutions, limited infrastructure, and low financial literacy. The analysis finds that while mobile money is expanding access, its impact depends on improvements in digital infrastructure, governance, and consumer protection. The paper concludes that inclusive finance in the DRC requires not only technological diffusion but also the rebuilding of institutional credibility and human capital