Local Investment Research Articles

The Efficiency of Domestic Savings and Its Impact on The Average Per Capita GDP In Iraq For the Period (2003-2022)

Local savings are an essential source for financing sustainable development. The research is based on careful analysis due to the importance of local savings in the Iraqi economy for the period (2003-2022) to provide the necessary local financing necessary for development investments in infrastructure and investments that enhance economic growth and productivity, generate job opportunities, and achieve The goals and indicators of sustainable development and the extent of the efficiency of those local savings and their impact on the average per capita share of GDP. The research aims to examine the effect of the efficiency of local savings on the level of per capita income of GDP. Moreover, it analyzes the potential impact on income distribution in the local community. The research adopts a multi-faceted approach that uses quantitative data to analyze the statistical relationships between the level of efficiency of local savings and the average per capita income from the gross domestic product, as local savings constitute an essential part of the local and national economy. The research starts from the hypothesis that the efficiency of local savings is represented by both the Local resource gap and the financing gap, which impacts the average per capita output and is linked to a causal relationship with the efficiency of local savings. The importance of this significant impact on the average per capita income, as local savings rates, the efficiency of these savings, and the local savings and financing gaps in Iraq were analyzed by cointegration analysis. The most important results showed that increasing the efficiency of local saving is linked to an increase in local investments, thus improving the level of per capita income and that there is a direct relationship between the Local resource gap and the average per capita share of GDP and an inverse relationship between the financing gap and the average per capita share of GDP.

Do local government investment preferences influence renewable energy technology innovation? Evidence from China

Local government investment can influence renewable energy technology innovation (RETI). Based on the panel data of 30 provinces in China from 2007 to 2019, this paper uses fixed effect models, partial linear generalized function coefficient models, and other methods to test the impact of local government investment preferences (LGIP) on RETI. The results are: (1) Productive investment preferences significantly inhibit RETI. (2) The impact of productive investment preferences on RETI is heterogeneous across economic development stages and regions. (3) With economic growth, the negative impact of productive investment preferences on RETI gradually decreases. The findings suggest that local governments should adjust investment patterns and appropriately reduce productive investment to improve RETI.

Mitigating Financial Risks in Sustainable Public–Private Partnership Infrastructure Projects: A Quantitative Analysis

Economic recession from the coronavirus outbreak continues to have negative rippling effects on local and international financial investments in public–private partnership (PPP) projects in Ghana, a developing country. Together with poor reports on operating cash-inflows for PPP projects such as those covering schools, hospitals, railways, fishing harbors, cocoa warehouses, recreational parks and affordable housing, there is an urgent need to develop and institutionalise sustainable and robust financial risk management measures. These measures are meant to mitigate financial losses, promote sustainability practices and prolong the longevity of infrastructure developments within PPP pacts. Therefore, this study aims to assess the mitigation measures of PPP infrastructure management in Ghana. Primary data from survey questionnaires were utilised in this study, with the data obtained from PPP practitioners and experts. Data were grouped into project type, sectors and practitioners of PPP projects to aid the analysis using tools such as the Kruskal–Wallis test, the Mann–Whitney U test and factor analysis. The results demonstrate sustainable and green finance, the innovative skills and competencies of project teams, green financial risk models and inclusive cost reduction strategies as crucial to minimising financial risks in PPP project delivery. These findings have significant implications for PPP practitioners and researchers in Ghana and similar developing countries to understand and develop measures to respond to financial risks for sustainable PPP project development and future research studies.

Impacts of Capital Formation and Investment Sources on Total Factor Productivity: The Example of Nigeria’s Agriculture

The study was designed to analyse the impact of capital formation and investment sources on Nigeria's agricultural productivity from the period 1980 - 2021. The time series data were analysed with Malmquist Data Envelopment Analysis (DEA) and the tobit regression models using DEA, the Total Factor Productivity Change, which quantifies the degree of productivity, was estimated at 1.022, which implies an average productivity progress of 2.2% annually. Again, since the value of technical efficiency change is less than technological change, it implies that the productivity gains are mainly attributable to technological progress instead of efficiency improvements in the periods under the study. The results of tobit regression indicate that domestic capital formation significantly influences agricultural TFP, highlighting the importance of government expenditure on agriculture (GEA) and gross fixed capital formation (GFCF) in enhancing productivity, although with minimal effects. Human capital formation (HCF) also showed positive impacts on Total Factor Productivity TFP, suggesting that improvements in workforce skills and knowledge are crucial for agricultural efficiency. However, FDI exhibited no significant correlation with TFP, implying that local investments are more beneficial than foreign aids in the context of Nigeria's agricultural sector. The findings emphasize the need for robust policy frameworks that align capital disbursements with agricultural production periods to optimize TFP. This study contributes to the discourse on agricultural productivity by providing empirical evidence on the critical role of capital investments in enhancing TFP within developing economies like Nigeria.

The impact of energy prices on industrial investment location: Evidence from global firm level data

This study examines the influence of relative energy prices on the geographical distribution of industrial investments across 41 countries. Employing a gravity model framework to analyse firms’ investment location decisions, we estimate the model using global bilateral investment flows derived from firm-level M&A data. Our findings reveal that a 10% increase in the energy price differential between two countries results in a 3.2% rise in cross-border acquisitions. This effect is most pronounced in energy-intensive industries and transactions targeting emerging economies. Furthermore, policy simulations suggest that the impact of unilateral carbon pricing on cross-border investments is modest.

Is US farm sector debt underestimated? Evidence from equipment lending

PurposeThe growth of lending from nontraditional lenders may pose challenges for official US Department of Agriculture (USDA) farm sector debt estimates, but it is difficult to find data to assess official estimates. The purpose of this study is to examine whether debt provided by nontraditional lenders is accurately accounted for in official estimates.Design/methodology/approachWe compare traditional and nontraditional lending data from farm equipment lien collateral values and the USDA Agricultural Resource Management Survey (ARMS). After analyzing trends in equipment lending implied by farm equipment lien data and ARMS, we estimate whether changes in farm equipment lien values predict changes in equipment debt reported in ARMS and whether lender type influences that relationship.FindingsWe find that credit provided by nontraditional lenders is likely underreported in ARMS. Our econometric model shows that equipment debt volumes for nontraditional lenders are consistently lower than traditional loan volumes in ARMS across a variety of model specifications. We also find that an increase in lien values for nontraditional lenders is less likely to predict an increase in ARMS equipment debt volumes than an increase for traditional lenders.Practical implicationsOfficial farm sector debt estimates may not fully account for nontraditional lenders.Originality/valueThis study demonstrates how the growth of nontraditional lending poses challenges for estimating US farm sector debt. We evaluate farm sector debt estimates and advance knowledge of the role of nontraditional lenders in farm equipment credit provision. The farm equipment lien dataset provides a rich source of novel data for research on local and national equipment debt and investment.

The Geography of Investor Attention

Abstract Local companies attract significantly more attention from investors than nonlocal companies, especially at times of news releases and high volatility. This attention gap widens especially when news is firm-specific rather than aggregate, and in response to idiosyncratic rather than market risk. Attention is causally related to perceived proximity: after a firm is acquired by a nonlocal one, local investors, compared with nonlocal investors, are more likely to reallocate attention away from it; conversely, COVID-19 travel restrictions led investors to reallocate attention toward local companies and away from nonlocal ones, especially those difficult to reach. Finally, local attention predicts volatility, bid-ask spreads, and nonlocal attention, but not vice versa. Our findings suggest that the geography of attention matters and is shaped by local investors’ information-processing advantage, not familiarity bias. (JEL D83, G11, G12, G14, L86, R32) Received: 2 January 2024; Editorial decision: 13 March 2024 Editor: Isil Erel Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Factors that affect a better fiscally autonomous government: Evidence from an Indonesian newly autonomous region

This study aims to investigate the influence of fiscal decentralization and socio-economic determinants on fiscal autonomy, taking into account anti-corruption efforts as a moderating variable. This study uses a dataset that spans 5 years and focuses specifically on 74 recently established autonomous regions in Indonesia after the year 2004. This study shows that the factors that indicate fiscal decentralization, such as locally created sources of funds and means of profit sharing, have a favorable and significant influence on fiscal autonomy. In contrast, total allocated funds have a detrimental and significant impact, but the special fund has a negligible impact on fiscal autonomy. This study shows a strong and statistically significant correlation between local investment and fiscal autonomy when socio-economic aspects are taken into account. However, the analysis showed that inward investment has an unfavorable impact that is not statistically significant. Furthermore, this study shows that anti-corruption, when treated as a separate factor, has a favorable and notable influence. Furthermore, when used as a moderating variable, it can serve as a quasi-moderator for the relationship between each of the independent variables and fiscal autonomy, which acts as the dependent variable. His study contributes to the existing body of knowledge on fiscal decentralization by providing a more comprehensive understanding of its influence on fiscal autonomy.

Robust co-planning of transmission expansion and merchant energy storage investments considering long- and short-term uncertainties

The decreasing cost of energy storage technologies and the increasing utilization of renewable energy sources have made distributed transmission-scale energy storage economically viable. Merchant energy storage investors can collect significant profits through spatiotemporal energy arbitrage from congested transmission lines. This paper formulates a three-stage, four-level min–min–max–min problem from the viewpoint of power system operators and planners such that they will build new transmission lines and identify potential locations for profitable merchant energy storage investments. The first level determines transmission expansion decisions from the system operator’s perspective. The second level plans potential investments in merchant energy storage to ensure profitability at a desired rate of return. The third level realizes the worst-case situations of long-term uncertainties related to the expansion of wind farms and peak load growth in each regional zone, while the fourth level simulates market clearing for representative days, modeling short-term uncertainties. A novel iterative nested column and constraint generation (C&CG) technique is adopted to cope with numerical issues caused by binary variables of transmission lines and storage blocks and the enormous size of the problem. The case study of a modified IEEE 24-bus test system was used to assess the effectiveness of the proposed algorithm.

Public governance, public investment and regional economic growth: Evidence from Vietnam

The article provides evidence on the effect of local public governance on the impact of public investment on local and regional economic growth, using spatial and regional logic. The research uses the spatial Durbin model and produces a panel data set that was conducted on 63 provinces of Vietnam from 2006 to 2022. Based on the interaction between public governance and public investment, the main findings indicate that their interaction plays an important role in adjusting the effects of public investment and public governance on economic growth not only in the locality but also spillover to neighboring localities in both the short and long terms. It suggests that local public governance not only hampers the impact of local public investment on local economic growth but also has spillover effects on the growth of neighboring provinces or regions in Vietnam. Additionally, the results of detailed analysis of PCI component indicators show that many aspects of local public governance are hindering local economic growth but contributing to promoting neighboring localities economic growth. Or, it has no effect the locality but promote or hinder the regional economic growth. The findings in this study implies that authorities of localities need to be cautious when using resources to improve the various aspects of public governance when designing strategies to enhance the quality of local public governance. It also suggests that this spillover effect is a crucial factor in advocating for more redistributive fiscal policies and regional governance policies aimed at reducing economic disparities caused by territorial boundaries. Therefore, authorities should prioritize regional cooperation strategies in their decisions regarding public governance and public capital allocation.

The impact of local wind and spatial conditions on geometry blade of wind turbine

AbstractThe research addresses the pressing need to understand wind conditions for optimal wind energy utilization, a crucial aspect of achieving global energy sustainability. While previous studies have focused on assessing wind energy potential and terrain roughness, gaps persist in understanding how wind and spatial conditions affect blade geometry. Therefore, this study aims to investigate the impact of local wind conditions on wind turbine blade geometry, integrating nonuniform wind inflow due to wind shear into the theoretical model. Through the paper, it explores blade design for varying inflow conditions and analyses the relationship between terrain type and blade designs. A novel approach to wind turbine blade design, utilizing a theoretical model that combines the local momentum theorem with insights from propeller vortex theory was adopted. Through the analysis, the authors demonstrate that variations in terrain significantly influence blade geometry, underscoring the necessity for tailored turbine designs based on local conditions. The findings reveal discrepancies in blade geometry across different turbine capacities and terrain types, offering novel insights into wind turbine performance optimization. By tailoring blade geometry to specific locations enhances resource utilization, offering insights for energy policymakers. The research provides validated methods for optimizing turbine geometric parameters, opening avenues for increased local investment in wind energy and promoting distributed energy development. Illustrated with wind plants examples, the paper concludes by outlining future research directions in this field.

Optimizing Trade Strategies: The Interactive Trade Decision Making Using Weighted Sum Method

The interactive nature of trade decision making enables us to navigate the complexities of international commerce with agility and precision. Through the power of technology and data-driven analysis, we can optimize our strategies, adapt to market conditions, and seize opportunities in real-time. Interactive trade decision making involves a dynamic process that integrates various factors such as market trends, economic indicators, risk assessment, and competitive analysis. It empowers traders to actively engage with the market, gather crucial information, and respond swiftly to changing circumstances. By harnessing advanced tools and algorithms, we can analyse vast amounts of data, uncover patterns, and make informed decisions that maximize profitability and minimize risks. This interactive approach transcends traditional models, allowing us to actively participate in trade negotiations, explore different scenarios, and assess the potential outcomes of our decisions. It encourages collaboration and knowledge sharing, enabling us to leverage collective intelligence and gain valuable insights from experts and peers. With real-time market data and interactive platforms at our fingertips, we can simulate, test, and refine our strategies, ensuring that our trade decisions are based on accurate information and thoughtful analysis.The significance of interactive trade decision making in research lies in its ability to revolutionize the way businesses and individuals approach international trade. We will use the Weighted Sum Method (WSM) in this study, which is a research approach that gives weights to various factors and combines them to make conclusions based on their relative relevance in a weighted way. Alternative parameters taken as Policy, Environment, Economy, Ability. Evaluation parameters parameters taken as Local investment, Technology transfer, Local procurement, Cooperate with R&D, Training, International marketing assistance”. show the final rank of this paper the Economy is in 2nd rank, the Environment is in 4th rank, the Ability is in 3rd rank, the Policy is in 1st rank, The final result is done by using the WSM method. In conclusion, interactive trade decision making is a powerful approach that leverages technology, real-time market information, and data analysis to enable informed and agile decision making in international trade.

Optimizing Trade Strategies: The Interactive Trade Decision Making Using Weighted Sum Method

The interactive nature of trade decision making enables us to navigate the complexities of international commerce with agility and precision. Through the power of technology and data-driven analysis, we can optimize our strategies, adapt to market conditions, and seize opportunities in real-time. Interactive trade decision making involves a dynamic process that integrates various factors such as market trends, economic indicators, risk assessment, and competitive analysis. It empowers traders to actively engage with the market, gather crucial information, and respond swiftly to changing circumstances. By harnessing advanced tools and algorithms, we can analyse vast amounts of data, uncover patterns, and make informed decisions that maximize profitability and minimize risks. This interactive approach transcends traditional models, allowing us to actively participate in trade negotiations, explore different scenarios, and assess the potential outcomes of our decisions. It encourages collaboration and knowledge sharing, enabling us to leverage collective intelligence and gain valuable insights from experts and peers. With real-time market data and interactive platforms at our fingertips, we can simulate, test, and refine our strategies, ensuring that our trade decisions are based on accurate information and thoughtful analysis.The significance of interactive trade decision making in research lies in its ability to revolutionize the way businesses and individuals approach international trade. We will use the Weighted Sum Method (WSM) in this study, which is a research approach that gives weights to various factors and combines them to make conclusions based on their relative relevance in a weighted way. Alternative parameters taken as Policy, Environment, Economy, Ability. Evaluation parameters parameters taken as Local investment, Technology transfer, Local procurement, Cooperate with R&D, Training, International marketing assistance”. show the final rank of this paper the Economy is in 2nd rank, the Environment is in 4th rank, the Ability is in 3rd rank, the Policy is in 1st rank, The final result is done by using the WSM method. In conclusion, interactive trade decision making is a powerful approach that leverages technology, real-time market information, and data analysis to enable informed and agile decision making in international trade.

Evolution Pattern of Rural Tourism Investment Location Choice from the Perspective of Human-Land Relationship System: Based on a Case Study of Zhejiang Province, China

Evolution Pattern of Rural Tourism Investment Location Choice from the Perspective of Human-Land Relationship System: Based on a Case Study of Zhejiang Province, China

Assessment of Wind Energy Potential at Three Prime Locations in Saudi Arabia: Analysis of Sharma, Qurayyat and Sakaka Sites

Purpose: The research aims to assess the wind energy potential at three chosen sites in Saudi Arabia Sharma, Al Qurayyat, and Sakaka over a five-year period from 2019 to 2023. The main goal is to determine the most favorable locations for wind farm development based on wind speed characteristics, Weibull distribution parameters, and wind power density (WPD). Materials and Methods: The wind speed data for the chosen locations was obtained from NASA's wind website and analyzed using the Weibull distribution to determine the shape (k) and scale (c) parameters, which are indicative of wind speed distribution. Critical metrics such as mean wind speed, WPD, and the most probable wind speed were computed to evaluate the wind energy potential. The Vestas V150-4.2 MW turbine was utilized to estimate potential energy output, considering the variability and reliability of wind resources at the specified locations. The study utilized tables, figures, and wind rose diagrams to highlight important wind parameters like mean wind speed, Weibull parameters, WPD, and Vmax for each location. Flowcharts were also used to summarize the methodology and conclusions, ensuring a clear and comprehensive presentation of the data. Findings: The analysis showed that Qurayyat consistently had the highest mean wind speed and WPD, indicating excellent wind energy potential. Sharma and Sakaka also displayed significant wind resources, with high mean wind speeds and substantial WPD values. The Weibull parameters indicated that all three sites have favorable wind characteristics for energy production. The estimated energy output using the Vestas V150-4.2 MW turbine ranged from 12,809 to 17,807 MWh/yr at Site 18, 14,095 to 15,170 MWh/yr at Site 24, and 14,013 to 15,832 MWh/yr at Site 31. Implications to Theory, Practice and Policy: The study presents a thorough evaluation of the wind energy potential in the Al-Jawf and Tabuk regions of Saudi Arabia. It contributes to a deeper understanding of wind resource distribution and its significance for the development of renewable energy. The study provides valuable insights for wind farm developers and policymakers by identifying the most promising locations for investment in wind energy infrastructure. Furthermore, it emphasizes the need for detailed site-specific analyses to optimize wind energy deployment, aligning with Saudi Arabia's broader renewable energy objectives.

Dividend policy and residual dividend theory: evidence from Indonesia

PurposeUsing the residual dividend theory, this study examines the impact of capital expenditures and working capital on the dividend policies of publicly listed companies in Indonesia.Design/methodology/approachUsing data on public companies (other than those in the financial sector) listed on the Indonesia Stock Exchange from 2011 to 2020, this study collected 870 observations (firm-years). This study employs a regression analysis technique using the STATA application program. The main variables in this study are capital expenditure and working capital, and the control variables are sales growth, firm size, leverage, profitability, liquidity and dummy variables for state-owned enterprises. The dependent variable of dividend policy is proxied by the dividend payout ratio.FindingsThis study’s results support the residual dividend theory’s hypothesis, in which capital expenditure negatively affects a company’s dividend policy. This study also analyzes this effect on companies that pay cash dividends at quantile positions of 25, 30, 50 and 60. The results show that the effect of capital expenditure on cash dividend payments is more pronounced in the case of companies whose cash dividends are in the 50th quantile. This result holds across different specification and endogeneity tests.Originality/valueThis study analyzes the residual dividend theory in Indonesian companies, focusing on localized factors and investment priorities. It challenges traditional Western dividend policies and provides empirical data that enhances the theory’s robustness. The findings have practical implications for investors, policymakers and corporate decision-makers in the Indonesian market.

How do private digital currencies affect government policy?

We provide a systematic classification and evaluation of the different types of digital currencies. We express skepticism regarding centralized digital currencies and focus our economic analysis on private digital currencies. We specifically highlight the potential for private digital currencies to improve welfare within an emerging market with a selfish government. In that setting, we demonstrate that a private digital currency not only improves citizen welfare but also encourages local investment and enhances government welfare. The fact that a private digital currency enhances government welfare implies a permissive regulatory policy which enables citizens to realize the previously referenced welfare gains.

Local corruption and SME investment

Prior research shows that corruption negatively affects corporate investment in large firms. However, we posit that this effect may be opposite in the context of SMEs. This paper investigates the relationship between local corruption and SME investment in a transition economy. With a sample of 262,767 observations, we document that local corruption is positively related to both SME investment expenditure and investment efficiency.

Evaluating Urban Green Space Inequity to Promote Distributional Justice in Portland, Oregon

Access and exposure to urban green space—the combination of parks and vegetative cover in cities—are associated with various health benefits. As urban green space is often unequally distributed throughout cities, understanding how it is allocated across socio-demographic populations can help city planners and policy makers identify and address urban environmental justice and health equity issues. To our knowledge, no studies have yet combined assessments of park quality, park availability, and green cover to inform equitable urban green space planning. To this end, we developed a comprehensive methodology to identify urban green space inequities at the city scale and applied it in Portland, OR, USA. After auditing all public parks in Portland and gathering green cover data from publicly accessible repositories, we used a suite of statistical tests to evaluate distribution of parks and green cover across Census block groups, comprising race, ethnicity, income, and educational attainment characteristics. Right-of-way tree canopy cover was the most significant urban green space inequity identified in bivariate analysis (rs = −0.73). Spatial autoregressive models identified that right-of-way, private, and overall tree canopy cover (Nagelkerke pseudo-R2 = 0.66, 0.77, and 0.67, respectively) significantly decreased with the proportion of minoritized racial population and increased with median income. The results were then used to identify priority locations for specific urban green space investments. This research establishes a process to assess intra-urban green space inequities, as well as identify data-informed and spatially explicit planning priorities to promote health equity and environmental justice.

Government infrastructure investment stimulation through booming natural resources: Evidence from a lower-middle-income country.

The dynamics of central government funding to regions depend on local investments. In regional autonomy, local governments are encouraged to be more self-reliant from the central government. For regions with high natural resource yields, they will not encounter difficulties in meeting their fiscal needs. Community welfare can be realized through fulfilling basic needs, one of which is infrastructure development. High-quality infrastructure will be able to contribute to further progress in trade, thus enhancing production efficiency. The objective of this research is to analyze the extent of the influence of central government transfer funds, especially the Natural Resource Revenue Sharing Funds (DBH SDA), on local government investments in infrastructure across 508 districts/cities in Indonesia. The method used is dynamic panel regression using the Generalized Method of Moment (GMM) Arellano-Bond approach. This study finds that the role of DBH SDA is still low in infrastructure spending. The role of the central government remains significant in determining infrastructure spending at the district/city level in Indonesia. This indicates that local governments rely more on other sectors in infrastructure investment. By enhancing the role of DBH SDA through technological advancements, it is hoped that the market value of natural resources can be higher through resource downstreaming. This strategy will have broader impacts, as labor needs can be absorbed not only in raw material production activities but also in the processing technology sector. Furthermore, the utilization of natural resources with modern technology can increase extraction efficiency, support sustainable development, and minimize environmental impacts.