Kostantinos A. Stamoulis, Simon J. Pittman, Jade M. S. Delevaux
et al.
Abstract Blue carbon nature-based solutions (NbS) can mitigate climate change through carbon sequestration and storage, and support climate change adaptation and resilience by supplying ecosystem benefits. We apply a scenario-based natural capital assessment to support the design of NbS for climate mitigation and adaptation, by considering tourism and coastal protection in two large coastal lagoons in the United Arab Emirates. Under future sea-level rise, ecosystem services are greatly reduced with impacts on habitat quality leading to reductions in blue carbon storage, coastal protection, and tourism in both study sites. While ecosystem service production from NbS differs between sites, mangrove expansion contributed to more types of ecosystem services, while conservation resulted in the greatest benefits for habitat quality and tourism. Safeguarding key areas for natural mangrove expansion can greatly enhance multiple ecosystem service benefits. Our findings can guide investments in blue carbon NbS that mitigate climate change, enhance climate resilience and adaptation, and deliver environmental and economic benefits.
Relevance. Implementation of the program "Development of agriculture and regulation of markets for agricultural products, raw materials and food in the Saratov region"; introduction of new types of equipment for obtaining high-quality seedlings and vegetables requires an increase in labor, material costs and additional capital investments. Methods. Statistical data were collected from the “Accounting reports” of the Saratov region (SR): Form No. 5APK, Form No. 9APK, etc. General scientific methods of induction and deduction were used to calculate and analyze the main cost and physical indicators: economic, statistical, mathematical.Results. The results of the analysis of the main economic and financial indicators of greenhouse complexes - leaders of the Saratov region for the period 2014-2023 were demonstrated. Overall, the region has seen an increase in areas, including: by 50.34 p.p., 28.04 p.p., 27.12 p.p., 2.28 p.p. in REHN LLC, Volga JSC, Leto-2002 LLC, and Sovkhoz-Vesna JSC, respectively. Income also has an upward trend, which is associated with higher growth rates of consumer prices over the growth rates of unit cost of production by 14.77 percentage points in the region as a whole. Direct labor costs per 1 centner of vegetables averaged 4.26 man-hours for 2014–2023, which is 6.9 times higher than labor costs per unit of grain production; however, over the past decade, there has been a trend toward a significant reduction by 43.37% (from 6.13 to 3.47 man-hours).Conclusion. An in-depth analysis of the company's financial and economic activities, including a forecast based on a polynomial equation and planning using the least-squares trending method, revealed changes in the industry's economic parameters for the purpose of shaping investment potential.
The industrial sector dominates global energy usage, accounting for approximately 50% of total energy demand, with process heat representing two-thirds of this consumption. Although renewable energy technologies have become increasingly cost-competitive, industrial users have been hesitant to replace fossil fuels to meet heat generation requirements. This study presents a practical framework for industrial energy transition, proposing a phased approach toward sustainable manufacturing practices, processes, and energy technologies. The framework emphasises that while energy efficiency measures form the foundation, strategic technological investment priorities should target the replacement of fossil fuels with sustainable and renewable energy technologies. The formulation of the three-phased energy technology advancement framework is informed by techno-economic analyses across a range of technical interventions available to plant operators, namely beverage manufacturers. For South African conditions, cost–benefit analyses suggest that the industry will prioritise investments in photovoltaic and battery energy storage systems, driven by attractive returns on investment, which are expected to improve. However, sustainability plans and efforts must extend beyond immediate financial returns, particularly in terms of future space requirements and capital allocation. This more holistic approach will ensure long-term sustainability while meeting increasingly stringent environmental commitments.
We study a consumption-investment problem in a multi-asset market where the returns follow a generic rank-based model. Our main result derives an HJB equation with Neumann boundary conditions for the value function and proves a corresponding verification theorem. The control problem is nonstandard due to the discontinuous nature of the coefficients in rank-based models, requiring a bespoke approach of independent mathematical interest. The special case of first-order models, prescribing constant drift and diffusion coefficients for the ranked returns, admits explicit solutions when the investor is either (a) unconstrained, (b) abides by open market constraints or (c) is fully invested in the market. The explicit optimal strategies in all cases are related to the celebrated solution to Merton's problem, despite the intractability of constraint (b) in that setting.
Explaining empirically observed wealth and income distributions, featuring power-law tails alongside gamma or log-normal bulk shapes, challenges models that focus on either pairwise competition or individual investment mechanisms. This study proposes and analyzes a unified model that integrates pairwise competition and individual investment via an adjustable parameter, $α$. Numerical simulations are conducted to analyze the model's Gini coefficient and distributional shapes using the complementary cumulative distribution function and goodness-of-fit tests. Results show that the model captures a systematic transition in the bulk distribution from gamma like (low $α$) to log-normal like (high $α$). Additionally, intermediate levels of mechanism mixing can reduce inequality compared with the original mechanisms. However, it is difficult to distinguish heavy tails consistent with power-laws from log-normal tails. These findings highlight the importance of considering the interaction between different economic mechanisms but suggest that accurately replicating the empirical power-law tail requires more than the simple combination investigated.
Luca De Gennaro Aquino, Sascha Desmettre, Yevhen Havrylenko
et al.
We study a continuous-time portfolio choice problem for an investor whose state-dependent preferences are determined by an exogenous factor that evolves as an Itô diffusion process. Since risk attitudes at the end of the investment horizon are uncertain, terminal wealth is evaluated under a set of utility functions corresponding to all possible future preference states. These utilities are first converted into certainty equivalents at their respective levels of terminal risk aversion and then (nonlinearly) aggregated over the conditional distribution of future states, yielding an inherently time-inconsistent optimization criterion. We approach this problem by developing a general equilibrium framework for such state-dependent preferences and characterizing subgame-perfect equilibrium investment policies through an extended Hamilton-Jacobi-Bellman system. This system gives rise to a coupled nonlinear partial integro-differential equation for the value functions associated with each state. We then specialize the model to a tractable constant relative risk aversion specification in which the preference factor follows an arithmetic Brownian motion. In this setting, the equilibrium policy admits a semi-explicit representation that decomposes into a standard myopic demand and a novel preference-hedging component that captures incentives to hedge against anticipated changes in risk aversion. Numerical experiments illustrate how features of the preference dynamics -- most notably the drift of the preference process and the correlation between preference shocks and asset returns -- jointly determine the sign and magnitude of the hedging demand and the evolution of the equilibrium risky investment over time.
This paper studies the macroeconomic impact of economic freedom on foreign direct investments inflows in both global and regional panel analyses involving 156 countries through the period of 1995-2016. Unlike to prior literature, it includes often neglected nations such as Fragile and Conflict-Affected states, Sub-Saharan, Oceanian, and Post-Soviet countries. The paper finds a positive impact of economic freedom on FDI under fixed-effects model in global case where a unit change in economic freedom scales FDI inflows up to 1.15 units. More specifically, all 9 regions also refer to positive and significant impact of economic freedom on FDI. The highest impact is recorded in European countries, whereas the lowest ones are documented in Fragile-Conflict affected states, Sub-Saharan zone, and Oceanian countries.
In financial markets, agents often mutually influence each other's investment strategies and adjust their strategies to align with others. However, there is limited quantitative study of agents' investment strategies in such scenarios. In this work, we formulate the optimal investment differential game problem to study the mutual influence among agents. We derive the analytical solutions for agents' optimal strategies and propose a fast algorithm to find approximate solutions with low computational complexity. We theoretically analyze the impact of mutual influence on agents' optimal strategies and terminal wealth. When the mutual influence is strong and approaches infinity, we show that agents' optimal strategies converge to the asymptotic strategy. Furthermore, in general cases, we prove that agents' optimal strategies are linear combinations of the asymptotic strategy and their rational strategies without others' influence. We validate the performance of the fast algorithm and verify the correctness of our analysis using numerical experiments. This work is crucial to comprehend mutual influence among agents and design effective mechanisms to guide their strategies in financial markets.
Recent studies highlight an increasing focus on models that incorporate a wide range of economic data, which is made possible by enhancing traditional vector autoregression (VAR) models with one or more factors. The present study aimed to apply the self-explanatory model of the generalized factor vector autoregressive (FAVAR) to investigate macroeconomic and housing market shocks from 1991 to 2022, on a relatively small annual scale. It examined the effects of production shocks, inflation, exchange rates, oil revenues, and the money supply. Housing price levels were estimated using four indices: housing price, fuel and lighting, real estate, rent, and business activity. Additionally, the rental housing index in Tehran and the price index of construction services were used to estimate investment levels in the housing sector. The analysis also included data on new housing investment in major cities, total investment in new houses in Tehran, the number of permits issued by municipalities in urban areas, and the number of permits issued in Tehran. The results revealed that macroeconomic shocks (inflation, production, exchange rates, money supply, and oil revenues) create a wave-like effect in the housing sector, with this effect lasting approximately 6 to 8 years. Inflation, money supply, and exchange rates, compared to GDP and oil revenues, have a greater impact on the housing market. Given the varying effects of these macroeconomic shocks, the central bank and monetary authorities should consider the responses of all sectors to develop more accurate housing plans during monetary policy formulation.IntroductionPlaying a key role in intensifying economic booms and busts, the housing market is a crucial component of the Iranian economy, which can be influenced by macroeconomic shocks. A significant portion of housing demand stems from its function as an asset. When macroeconomic shocks occur, they impact the opportunity cost of holding durable goods (e.g., housing) by increasing inflation, money supply, exchange rates, and oil revenues. These shocks influence both the demand for housing as an asset and the demand for housing services, altering the relative returns on housing investments. As a result, individuals adjust their asset portfolios, including housing, in response to these economic shifts. Consequently, housing demand as an asset fluctuates accordingly. The current study highlighted the conflict between two economic objectives: fostering production and investment growth versus managing inflation, macroeconomic shocks, and their adverse social and distributional effects. The expansion of the housing market can mitigate macroeconomic shocks by improving housing availability for households, contributing to sectoral and national economic growth. However, it may also drive up housing prices. Using the self-explanatory model of the generalized factor vector autoregressive (FAVAR), this empirical research aimed to examine the impact of macroeconomic shocks on housing prices in Iran’s economy.Materials and MethodsThe present study used time series data on macroeconomic variables and bank stability from 1991 to 2022. The data selection followed the general classification outlined in Bernanke et al. (2005), which includes production, inflation, money supply, oil revenues, exchange rates, and the housing market. Since the estimation of factors using the FAVAR requires stationarity, tests such as the generalized Dickey-Fuller unit root test were conducted on the variables. The modeling of FAVAR was based on Bernanke et al. (2005), while the model estimation followed the expectation-maximization algorithm as proposed by Dempster et al. (1977) and Shumway and Stoffer (1982). All variables were obtained from the time series databases of the Central Bank and the Ministry of Housing and Urban Development. After estimating the FAVAR model using EViews and SPSS software, the study presented the instantaneous response analysis of the model variables concerning the key variables over ten periods. The variables were transformed into logarithmic form, and their growth rates were calculated.Results and DiscussionThe response of housing prices and investment in the housing sector to a one-standard-deviation shock was immediate and significant, indicating that the economy quickly adjusts to the shock’s influence in the initial years. As shown in Figure (1), shocks related to production, money supply, exchange rates, oil revenues, and inflation created a wave-like effect in the housing sector, with a duration of approximately 15 years (15 periods), reflecting a period fluctuation. A one-standard-deviation shock in the exchange rate initially caused both housing investment and prices to rise. However, the impact gradually diminished, with investment converging to zero after 9 periods and housing prices after 8 periods—which aligns with expectations. Similarly, a one-standard-deviation shock in money supply initially increased investment in the housing sector while causing housing prices to decline. After 4 periods, both investment and prices converged towards zero, as anticipated. In the case of inflation, a one-standard-deviation shock initially reduced investment in the housing sector, followed by an increase. At the same time, housing prices rose with the inflation shock but gradually declined, with both investment and prices converging towards zero after 8 periods. A shock to GDP led to an initial increase in housing investment and a decline in housing prices. Over time, these effects diminished, with investment and prices converging towards zero after 4 periods and 3 periods, respectively. A one-standard-deviation shock in oil prices resulted in an increase in both housing investment and prices. However, these effects waned, with investment converging to zero after 4 periods and housing prices after 3 periods. Overall, the impact of these shocks diminished over time and eventually converged to zero, as it was anticipated. Figure 1. Macroeconomic shocks ConclusionAccording on the results of the FAVAR model, macroeconomic shocks have both direct and indirect effects on the housing sector and other markets. Macroeconomic shocks were found to increase demand in the housing sector, as housing is an asset that can absorb shocks over the long term and helps preserve the value of money to some extent. The housing channel also exhibited a consistent degree of price stickiness in response to these shocks. The analysis of macroeconomic shocks on housing prices and investment suggested that increasing demand for smaller housing units would drive future demand toward compact-sized homes. This shift is largely due to the declining purchasing power of the middle class, which has been severely impacted by recent shocks of inflation, monetary supply, exchange rates, and oil revenues. As a result, lower-income groups are left with little financial strength to afford housing. The growing gap between housing costs and household income further contributes to this trend. Moreover, the increasing share of housing costs in household expenditures—observed even during periods without economic sanctions—underscores this financial strain.