Hasil untuk "Capital. Capital investments"

R. Gulati, M. Higgins

E. Mendoza

Luyi Gui, Tinglong Dai

AI and renewable energy are increasingly framed as a "power couple" -- the idea that surging AI electricity demand will accelerate clean-energy investment -- yet concerns persist that AI will instead entrench fossil-fuel carbon lock-in. We reconcile these views by modeling the equilibrium interaction between AI growth and renewable investment. In a parsimonious game, a policymaker invests in renewable capacity available to AI and an AI developer chooses capability; the equilibrium depends on scaling regimes and market incentives. When the market payoff to capability is supermodular and performance gains are near-linear in compute, developers push toward frontier scale even when the marginal megawatt-hour is fossil-based. In this regime, renewable expansion can primarily relax scaling constraints rather than displace fossil generation one-for-one, weakening incentives to build enough clean capacity and reinforcing fossil dependence. This yields an "adaptation trap": as climate damages rise, the value of AI-enabled adaptation increases, which strengthens incentives to enable frontier scaling while tolerating residual fossil use. When AI faces diminishing returns and lower scaling efficiency, energy costs discipline capability choices; renewable investment then both enables capability and decarbonizes marginal compute, generating an "adaptation pathway" in which climate stress strengthens incentives for clean-capacity expansion and can support a carbon-free equilibrium. A calibrated case study illustrates these mechanisms using observed magnitudes for investment, capability, and energy use. Decarbonizing AI is an equilibrium outcome: effective policy must keep clean capacity binding at the margin as compute expands.

Nathan Engelman Lado, Ahmed Alahmed, Audun Botterud et al.

We examine the joint investment and operational decisions of a prosumer, a customer who both consumes and generates electricity, under net energy metering (NEM) tariffs. Traditional NEM schemes provide temporally flat compensation at the retail price for net energy exports over a billing period. However, ongoing reforms in several U.S. states are introducing time-varying prices and asymmetric import/export compensation to better align incentives with grid costs. While prior studies treat PV capacity as exogenous and focus primarily on consumption behavior, this work endogenizes PV investment and derives the marginal value of solar capacity for a flexible prosumer under asymmetric NEM tariffs. We characterize optimal investment and show how optimal investment changes with prices and PV costs. Through this analysis, we identify a PV effect: changes in NEM pricing in one period can influence net demand and consumption in generating periods with unchanged prices through adjustments in optimal PV investment. The PV effect weakens the ability of higher import prices to increase prosumer payments, with direct implications for NEM reform. We validate our theoretical results in a case study using simulated household and tariff data derived from historical conditions in Massachusetts.

Lazat Spankulova, Bulat Mukhamediyev, Azamat Kerimbayev et al.

Type of the article: Research Article AbstractThis study investigates the relationship between tourism development and income inequality across regions of the Republic of Kazakhstan, using regional panel data for 2003–2024. The empirical analysis is based on an unbalanced panel of 16 regions, comprising 367 region–year observations. Fixed-effects regression models are employed to examine how two distinct dimensions of tourism development (tourism services per capita and tourist accommodation places per capita) affect income inequality measured by the regional Gini coefficient.The results indicate that the intensity of tourism service provision does not have a statistically significant effect on income inequality, even after controlling for cross-sectional dependence. In contrast, tourism accommodation infrastructure capacity is positively and statistically significantly associated with regional income inequality across all model specifications. Additional results show that income inequality is significantly influenced by poverty incidence, income polarization, healthcare expenditures, and the share of the rural population.The coefficients on the per-capita tourist accommodation variable are positive across all specifications. This indicates that the growth of this indicator contributes to increased income inequality. Moreover, the coefficients for the indicators ShServPop and ShServPop(–1) are significant. However, they cannot be relied upon, as Pesaran’s test rejects the hypothesis of cross-sectional independence for these specifications. This suggests that the growth of tourism infrastructure may exacerbate, rather than reduce, regional income differences due to capital concentration, skill-labor-oriented employment, and price effects.The results highlight the need for complementary policies that promote inclusive tourism development and mitigate inequality-enhancing effects of tourism-related infrastructure investment. AcknowledgmentThis study was funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan within the framework of the IRN grant project AP26198345 “Reducing socio-economic inequality in the regions of Kazakhstan through investments in health and improving the organization of the healthcare system.”

Gholamhossein Golarzi, Mahnaz Khorasani

This research examined the asymmetric effects of domestic economic policy uncertainty (DEPU) and global economic policy uncertainty (GEPU) on stock market index returns in Iran. The study focused on simultaneous analysis of economic policy uncertainty originating from both domestic and global sources within a nonlinear framework, as well as the stock market’s asymmetric responses to these uncertainties. It used the nonlinear autoregressive distributed lag (NARDL) model, as it enables dynamic analysis and distinguishes the market’s reactions to positive and negative shocks across different time horizons. The dataset consisted of quarterly observations from 1997 to 2024. In addition to the uncertainty indices, the model incorporated several control variables, including the exchange rate, global oil prices, the consumer price index, money supply, real non-oil GDP, and stock market liquidity. Before estimating the model, the statistical properties of the data—such as nonlinearity, stationarity, the presence of long-term relationships, and response symmetry—were examined to ensure the suitability of the NARDL approach and the validity of the results. The results indicated that positive and negative shocks to DEPU have significant positive and negative effects, respectively, on stock market index returns in both the short and long run. Furthermore, GEPU shocks exert significant short-term effects with a time lag: positive shocks increase, while negative shocks decrease stock market index returns. In the long term, however, only positive GEPU shocks have a significant positive impact. The control variables also exhibited significant effects on stock market index returns.IntroductionEconomic policy uncertainty (EPU) is widely recognized as a critical factor influencing financial markets, including stock market returns. In today’s interconnected global economy, both domestic and global sources of policy uncertainty play a pivotal role in shaping investor behavior, economic decision-making, and overall market stability. Given Iran’s repeated exposure to policy shifts, economic sanctions, and geopolitical tensions, the country presents a unique setting for analyzing the impacts of policy uncertainty. Uncertainties—whether originating domestically or globally—can affect the stock market in diverse ways, varying in timing, direction, and intensity. This study aimed to investigate the asymmetric effects of domestic economic policy uncertainty (DEPU) and global economic policy uncertainty (GEPU) on stock market returns in Iran over the period 1997–2024. The primary objective was to examine how different forms of policy uncertainty influence the behavior of the Iranian stock market, while accounting for the non-linear and dynamic nature of these relationships. Market responses are not only asymmetric but are also shaped by the specific nature of each uncertainty source and the market’s sensitivity to these factors. Therefore, a nuanced analytical approach is required to capture the interactions between policy uncertainty and stock market performance. To this end, the present study employed the nonlinear autoregressive distributed lag (NARDL) model, an advanced econometric technique designed to capture asymmetric responses to positive and negative shocks in EPU. The findings can provide valuable insights into the role of EPU in shaping stock market returns in an emerging market such as Iran.Materials and MethodsThe present study used the nonlinear autoregressive distributed lag (NARDL) model, an appropriate method for analyzing nonlinear relationships in economic time series data. The NARDL model allows for the differentiation between positive and negative shocks, offering a more nuanced understanding of how various forms of uncertainty impact market behavior. Unlike traditional linear models, which assume symmetric effects of shocks, the NARDL approach enables the examination of distinct effects arising from positive and negative policy uncertainty shocks on stock market returns. This asymmetry is central to the study, as it reveals how market responses vary depending on the intensity and direction of uncertainty—an essential aspect for comprehensively assessing the effects of EPU on stock market performance. The analysis used quarterly time series data spanning the period 1997 to 2024. Key variables included DEPU and GEPU, Iran’s stock market returns, the exchange rate, global oil prices, the consumer price index (CPI), money supply, real non-oil GDP, and stock market liquidity. The DEPU and GEPU indices were constructed using content analysis of news reports, a widely accepted method for measuring EPU. Based on the theoretical framework and following the model proposed by Shin et al. (2014), the nonlinear long-term specification for Iran’s stock market index returns is presented in Equation (1): (1)The analysis aimed to simultaneously analyze the asymmetric short-term and long-term effects of the variables, so Equation (1) was reformulated as a NARDL model in the form of an error correction model (ECM), as presented in Equation (2):+(2)Before estimating the NARDL model, several preliminary tests were conducted to ensure its statistical validity and the suitability of applying this nonlinear model. These tests included the BDS test for nonlinear dependence, the ADF and PP tests for stationarity, the Zivot–Andrews test for structural breaks, the cointegration test of Pesaran et al. (2001) for long-run relationships, and the Wald test for asymmetry. The results confirmed that the data satisfied the necessary assumptions for valid estimation and that the NARDL model was appropriate for the analysis. Following the estimation of the NARDL model, several diagnostic tests were performed to assess the reliability of the results. These included the ARCH and Breusch–Godfrey tests to detect heteroscedasticity and autocorrelation in the residuals, as well as the CUSUM and CUSUMQ to check for parameter stability. The outcomes of these diagnostic tests indicated that the model was correctly specified and that the findings were robust and reliable.Results and DiscussionThe results from the dynamic NARDL model (Table 1) showed that, in the short term, the lagged value of the stock market index has a significant positive effect on its returns. This indicates that past market growth can stimulate future growth. In the short term, DEPU displayed asymmetric effects: positive shocks have a significant positive impact, while negative shocks have a significant negative effect. GEPU also showed delayed and asymmetric effects. Positive GEPU shocks are statistically insignificant, but their first and second lags exert significant positive impacts on stock market returns. Negative GEPU shocks are also statistically insignificant, although their first lag has a significant negative effect. Regarding the control variables, the exchange rate had a positive and significant effect in the current period, while its lag was statistically insignificant. Moreover, global oil prices can exert positive effects in the second and third lags, but not in the current period or the first lag.Table 1. Results of Dynamic NARDL Model Estimationp-valuet-StatisticStandard errorCoefficientVariable 0.003.120.090.30LSP(-1) 0.022.320.100.23LDEPU_POS 0.720.340.930.32LDEPU_POS)-1) 0.01-2.510.08-0.22LDEPU_NEG 0.141.450.701.02LGEPU_POS 0.032.150.521.12LGEPU_POS(-1) 0.022.300.561.29LGEPU_POS(-2) 0.101.640.390.64LGEPU_NEG 0.00-2.660.54-1.45LGEPU_NEG)-1) 0.042.070.440.93LEX 0.14-1.450.51-0.75LEX(-1) 0.25-1.150.30-0.35LOIL 0.231.180.440.53LOIL (-1) 0.032.170.450.98LOIL (-2) 0.004.820.291.42LOIL (-3) 0.002.700.471.27LCPI 0.72-0.342.11-0.73LMS 0.60-0.522.46-1.29LMS)-1) 0.022.490.411.03LMS)-2) 0.69-0.404.55-1.82LMS)-3) 0.540.600.170.10LRNOGDP 0.720.350.100.03LLIQ 0.042.000.100.20LLIQ (-1)  =0.88            F-statistic=7.6836              Prob (F-statistic) =0.0000       Source: Research ResultsThe consumer price index was found to have a significant positive impact on stock market returns. Money supply has a significant positive effect only in the second lag. Real non-oil GDP is not statistically significant in the short term, whereas market liquidity is significant only in its first lag. The overall model significance was confirmed by the F-statistic.The long-term results from the NARDL model (Table 2) indicated that DEPU exhibits significant asymmetric effects: positive shocks lead to a positive long-term impact on stock market returns, whereas negative shocks produce a negative long-term effect. GEPU also showed asymmetric long-term behavior, with only positive shocks having a statistically significant influence. Among the control variables, the exchange rate and real non-oil GDP exert positive and significant long-term effects on stock market returns, while global oil prices and the consumer price index have negative long-term effects. The ECM coefficient confirmed that, following any shock, the market gradually adjusts back to its long-term equilibrium.Table 2. Long-Term Relationships and the Error Correction Model (ECM) Results From NARDLp-valuet-StatisticStandard errorCoefficientVariable0.012.410.140.34LDEPU_POS0.002.920.09-0.28LDEPU_NEG0.002.700.371.02LGEPU_POS0.11-1.600.55-0.89LGEPU_NEG0.002.870.240.69LX0.04-2.040.45-0.92LOIL0.01-2.390.80-1.93LCPI0.40-0.830.75-0.63LMS0.012.470.561.38LRNOGDP0.330.970.220.21LLIQ0.02-2.20.11-0.25ECMSource: Research ResultsConclusionAccording to the findings, both DEPU and GEPU exert significant and asymmetric effects on stock market returns in Iran. The results highlighted the importance of recognizing non-linear relationships when examining the impact of EPU, particularly in emerging markets such as Iran. In light of the findings, it is recommended that economic policymakers proceed with greater caution when announcing policies and avoid issuing contradictory or ambiguous signals that could trigger short-term market overreactions and instability. Moreover, achieving long-term economic stability requires careful attention to fundamental factors such as exchange rates, oil prices, and economic growth. The results also indicated that, in the short term, speculative and emotional behaviors play a substantial role in market fluctuations. These behaviors can be curbed by improving regulatory frameworks, for example by facilitating short-selling, futures contracts, and options trading. In the long term, enhancing investors’ financial literacy and encouraging long-term investment strategies can help reduce volatility driven by short-term speculation.

Pengyu Wei, Wei Wei

This paper employs an intra-personal game-theoretic framework to investigate how decreasing impatience influences irreversible investment behaviors in a continuous-time setting. We consider a capacity expansion problem under weighted discount functions, a class of nonexponential functions that exhibit decreasing impatience, including the hyperbolic discount function as a special case. By deriving the Bellman system that characterizes the equilibrium, we establish the framework for analyzing investment behaviors of agents subject to decreasing impatience. From an economic perspective, we demonstrates that decreasing impatience prompts early investment. From a technical standpoint, we warn that decreasing impatience can lead to the failure of the smooth pasting principle.

John Armstrong, Cristin Buescu, James Dalby

We study the optimal investment problem for a homogeneous collective of $n$ individuals investing in a Black-Scholes model subject to longevity risk with Epstein--Zin preferences. %and with preferences given by power utility. We compute analytic formulae for the optimal investment strategy, consumption is in discrete-time and there is no systematic longevity risk. We develop a stylised model of systematic longevity risk in continuous time which allows us to also obtain an analytic solution to the optimal investment problem in this case. We numerically solve the same problem using a continuous-time version of the Cairns--Blake--Dowd model. We apply our results to estimate the potential benefits of pooling longevity risk over purchasing an insurance product such as an annuity, and to estimate the benefits of optimal longevity risk pooling in a small heterogeneous fund.

Nilay Utlu, Damla Ayduğ

Nowadays, it has become increasingly important for businesses that want to have a sustainable competitive advantage to engage in entrepreneurial activities by using business resources because of changing environmental conditions and increasing competition intensity. This research develops a decision-making model by analyzing the factors influencing entrepreneurial success through a resource-based approach. The resource-based approach to entrepreneurship of Alvarez and Busenitz (2001) is based on financial, social, and human capital factors. According to this approach, financial capital includes initial investments and access to financial resources; social capital includes networks, trust, and shared vision; and human capital includes education and experience. The SWARA method, a multi-criteria decision-making method, was used. Financial, social, and human capital criteria, which are effective for entrepreneurial success, were prioritized because of the answers given by experts using the SWARA method. As a result of the research, it was found that the most important criteria affecting entrepreneurial success with a resource-based approach is experience, followed by shared vision, networks, access to finance, education, initial investment, and trust.

Nicola Valentino Canessa

In 1992 the cities of Barcelona and Genoa both began their recent transformation journey, the former with the Olympics and the latter with the Colombians. While the former capitalised on its transformations, beginning an extensive path of both public and private investments, the latter focused on processes related to major events, happenings or funding (G8, Genoa Capital of Culture, Morandi Viaduct collapse, the national resilience and recovery plan (NRRP), etc.). It is interesting to note that, to date, in both cities, citizen participation or activation largely depends on how much the city seeks consensus on transformation operations more than on design choices by adopting a top-down approach, which is similarly configured in all large and medium-sized European cities. They hardly give space or importance to bottom-up processes except when synergistic to an already planned strategy.

Lezhi Li, Ting-Yu Chang, Hai Wang

This report outlines a transformative initiative in the financial investment industry, where the conventional decision-making process, laden with labor-intensive tasks such as sifting through voluminous documents, is being reimagined. Leveraging language models, our experiments aim to automate information summarization and investment idea generation. We seek to evaluate the effectiveness of fine-tuning methods on a base model (Llama2) to achieve specific application-level goals, including providing insights into the impact of events on companies and sectors, understanding market condition relationships, generating investor-aligned investment ideas, and formatting results with stock recommendations and detailed explanations. Through state-of-the-art generative modeling techniques, the ultimate objective is to develop an AI agent prototype, liberating human investors from repetitive tasks and allowing a focus on high-level strategic thinking. The project encompasses a diverse corpus dataset, including research reports, investment memos, market news, and extensive time-series market data. We conducted three experiments applying unsupervised and supervised LoRA fine-tuning on the llama2_7b_hf_chat as the base model, as well as instruction fine-tuning on the GPT3.5 model. Statistical and human evaluations both show that the fine-tuned versions perform better in solving text modeling, summarization, reasoning, and finance domain questions, demonstrating a pivotal step towards enhancing decision-making processes in the financial domain. Code implementation for the project can be found on GitHub: https://github.com/Firenze11/finance_lm.

Spyros Makridakis, Evangelos Spiliotis, Ross Hollyman et al.

The M6 forecasting competition, the sixth in the Makridakis' competition sequence, is focused on financial forecasting. A key objective of the M6 competition was to contribute to the debate surrounding the Efficient Market Hypothesis (EMH) by examining how and why market participants make investment decisions. To address these objectives, the M6 competition investigated forecasting accuracy and investment performance on a universe of 100 publicly traded assets. The competition employed live evaluation on real data across multiple periods, a cross-sectional setting where participants predicted asset performance relative to that of other assets, and a direct evaluation of the utility of forecasts. In this way, we were able to measure the benefits of accurate forecasting and assess the importance of forecasting when making investment decisions. Our findings highlight the challenges that participants faced when attempting to accurately forecast the relative performance of assets, the great difficulty associated with trying to consistently outperform the market, the limited connection between submitted forecasts and investment decisions, the value added by information exchange and the "wisdom of crowds", and the value of utilizing risk models when attempting to connect prediction and investing decisions.

B. N. Kausik

We argue that the recent growth in income inequality is driven by disparate growth in investment income rather than by disparate growth in wages. Specifically, we present evidence that real wages are flat across a range of professions, doctors, software engineers, auto mechanics and cashiers, while stock ownership favors higher education and income levels. Artificial Intelligence and automation allocate an increased share of job tasks towards capital and away from labor. The rewards of automation accrue to capital, and are reflected in the growth of the stock market with several companies now valued in the trillions. We propose a Deferred Investment Payroll plan to enable all workers to participate in the rewards of automation and analyze the performance of such a plan. JEL Classification: J31, J33, O33

Hooman Karami Khoramabadi, Alireza Erfani, Hosein Tavakolian

This paper investigates the effectiveness of monetary policy in recession and expansion periods of business cycles in Iran. It uses the distribution of price changes over time using micro-data of producer and consumer price indices from March 2004 to March 2007 and March 1990 to March 2017. Results show that the observed distribution price changes at the producer and consumer levels change significantly over time. Whereas price flexibility (or, similarly, price stickiness) is closely related to the impact of monetary policy, the variable distribution of price changes over time suggests that the effectiveness of monetary policy should also change over time. We estimated the related parameters using the Ss model and the observed facts from the distribution of price changes, the price flexibility index, which shows how prices react to a monetary policy shock. The correlation coefficient and regression analysis results showed that the price flexibility index is counter-cyclical; this means that during periods of economic recession, the index of price flexibility increases. Therefore, the impact of monetary policy on real output decreases. However, during periods of economic expansion, the impact of monetary policy increases.

Hongguang Sui, Xijie Li, Ali Raza et al.

An increase in trade policy uncertainty raises policymakers’ concerns, as it can be harmful to investments and growth globally. This study examines the impact of reducing trade policy uncertainty on export product quality. Based on the ASEAN–China Free Trade Area (ACFTA), the difference-in-difference, two-way fixed, and triple difference methods were used to conduct benchmark tests. The results show that reducing trade policy uncertainty improves export product quality. Social capital has strengthened the role of the changing trade environments. The results were robust after the PSM-DID, placebo test, and deletion of outliers. Furthermore, the role of social capital is incorporated into the regression model. From the perspective of informal internal systems, this study expands the theoretical view of regional trade integration research and answers the current trade strategy adjustment and export transformation policy concerns.

Dimitri Percia David, Alain Mermoud, Sébastien Gillard

Cyber-security breaches inflict significant costs on organizations. Hence, the development of an information-systems defense capability through cyber-security investment is a prerequisite. The question of how to determine the optimal amount to invest in cyber-security has been widely investigated in the literature. In this respect, the Gordon-Loeb model and its extensions received wide-scale acceptance. However, such models predominantly rely on restrictive assumptions that are not adapted for analyzing dynamic aspects of cyber-security investment. Yet, understanding such dynamic aspects is a key feature for studying cyber-security investment in the context of a fast-paced and continuously evolving technological landscape. We propose an extension of the Gordon-Loeb model by considering multi-period and relaxing the assumption of a continuous security-breach probability function. Such theoretical adaptations enable to capture dynamic aspects of cyber-security investment such as the advent of a disruptive technology and its investment consequences. Such a proposed extension of the Gordon-Loeb model gives room for a hypothetical decrease of the optimal level of cyber-security investment, due to a potential technological shift. While we believe our framework should be generalizable across the cyber-security milieu, we illustrate our approach in the context of critical-infrastructure protection, where security-cost reductions related to risk events are of paramount importance as potential losses reach unaffordable proportions. Moreover, despite the fact that some technologies are considered as disruptive and thus promising for critical-infrastructure protection, their effects on cyber-security investment have been discussed little.

Daeyung Gim, Hyungbin Park

This paper treats the Merton problem how to invest in safe assets and risky assets to maximize an investor's utility, given by investment opportunities modeled by a $d$-dimensional state process. The problem is represented by a partial differential equation with optimizing term: the Hamilton-Jacobi-Bellman equation. The main purpose of this paper is to solve partial differential equations derived from the Hamilton-Jacobi-Bellman equations with a deep learning algorithm: the Deep Galerkin method, first suggested by Sirignano and Spiliopoulos (2018). We then apply the algorithm to get the solution of the PDE based on some model settings and compare with the one from the finite difference method.

Ivashechkin V.V., Medvedeva J.A., Satsuta E.S.

Boreholes are the most versatile and technically advanced structural type of water intake structures. In this article, the authors propose the design of a water intake well with filters located at two levels, capable of simultaneously performing the functions of a working and reserve wells, the use of which will reduce energy consumption for lifting water, reduce capital investments for construction and ensure uninterrupted water supply. The methodology for calculating the inflow of water, constructing hydrodynamic grids, determining the function of lowering the pressure and filtering features during the operation of a two-level well in a confined aquifer is also presented.

Muharrem Afşar, Başak Özarslan Doğan, Emrah Doğan

The acceleration of capital transfers between countries after globalization has increased the importance of foreign direct investments in developing countries. Lack of capital in developing countries such as Turkey, constitute obstacles to investment. In this context, foreign direct investments that will come to the country are important in terms of eliminating the negativities caused by the lack of capital. Foreign direct investments are affected by many factors. One of them is the country's geopolitical risk. In this study, it is aim to investigate the impact of geopolitical risk on foreign direct investment in Turkey by using ARDL Bound Test for the 1998-2018 period. In addition to the geopolitical risk, real exchange rate, labor force, real GDP and savings that affect foreign direct investments were also included in the study. According to the analysis re-sults obtained, while geopolitical risk and labor force had a negative effect on FDI; real GDP, real exchange rate and savings have and positive effect on FDI.

Giancarlo Paganin

Enabling sustainable growth is highly dependent on the ability of private capital to invest in projects capable of achieving sustainability objectives divided into the three economic, environmental and social components. The international financial system has defined criteria for assessing the sustainability of investments, also applicable in the construction sector. Still, these criteria do not always appear integrated with the sustainability assessment systems developed by the AEC (architecture, engineering and construction) industry. This article proposes reflections on the relationships between the sustainability indicators of sustainable finance and those typically used in the AEC industry with the purpose of identifying possible impacts on the disciplines involved in the design process.