Economic Indicators Research Articles

AI-driven robo-advisors on personal financial management and investment strategies

The advent of AI-driven robo-advisors has revolutionized personal financial management and investment strategies. Leveraging sophisticated algorithms and machine learning, these platforms offer personalized financial advice and automated portfolio management with minimal human intervention. By analyzing vast datasets, including market trends, economic indicators, and individual client preferences, robo-advisors can create tailored investment plans that optimize returns and manage risks effectively. This paper explores the transformative impact of AI in democratizing financial advice, enhancing decision-making processes, and making investment management accessible to a broader audience. The integration of AI in robo-advisory services not only improves efficiency but also provides a scalable solution to meet the diverse financial needs of individuals.

Innovation and infrastructure: driving forces for entrepreneurship development and economic opportunities

Purpose. To determine the relationship between innovation and infrastructure to support entrepreneurship as factors of growth of economic opportunities, based on the results of empirical research. Methodology. The case method and modern tools of econometric research were used to create an economic-mathematical model that assesses the relationship between economic opportunities and indicators of economic innovation. The research is based on the results of the Gallup 75 Years Anniversary Survey on current and future economic opportunities, as well as Global Innovation Index (GII) indicators. Findings. Creating favorable conditions for doing business and developing entrepreneurship is critically important for the economic recovery of Ukraine. The high level of entrepreneurial activity among Ukrainians emphasizes the importance of the development of innovative infrastructure and business support. The developed models can be used to forecast the economic capabilities of the population, which will contribute to the return of citizens and the development of the national economy. Thus, innovations and an effective infrastructure to support entrepreneurship play a key role in ensuring sustainable economic growth and social well-being in Ukraine. The results of the study can become the basis for developing strategies for economic development and solving migration problems in the post-war period. Determinants of the growth of economic opportunities of the population (human capital) are determined. The suggested GII parameters most correlate to positive feedback on economic opportunities and growth over the next 25 years. Originality. For the first time, the relationship between economic opportunities, the development of innovations and the development of infrastructure at the enterprise has been empirically proven. Statistically significant predictors of current and future economic opportunities of the population are substantiated and relevant economic and mathematical models for their evaluation and forecasting are developed. Practical value. The results of the study are particularly relevant in the context of solving the migration crisis caused by Russia’s military aggression against Ukraine. The return of citizens who have left the country depends on the creation of favorable conditions for business and the development of entrepreneurship. The developed models can be used to forecast the economic opportunities of the population in different countries, which will allow effective management of migration processes and promote the development of national economies. This will ensure the creation of a favorable business environment, which is critical for sustainable economic growth and social well-being.

Results of Economic Tendency Surveys in Nowcasting GDP Growth

The article proves the usefulness of including aggregate information from economic tendency surveys in the system of nowcasting of economic growth. The authors compare the efficiency of vector autoregressive models that include the economic sentiment indicator based on the results of Rosstat business activity and consumer expectations surveys, and the business climate indicator based on the results of the Bank of Russia enterprise monitoring.Statistical testing of time series of composite indicators and GDP volume index confirmed a significant correlation and causality between them, as well as the similarity of their cyclical profiles. Both indices pass cyclical turning points synchronously or ahead of the GDP volume index, their predictive capabilities are enhanced by the early availability of information. The capabilities of GDP growth nowcasting using survey information are assessed in three specifications of the vector autoregressive model with dummy variables. On the in-sample period, the model including two composite indicators and the GDP volume index demonstrates the highest accuracy.The proposed approach allows us to obtain flash estimates of GDP growth prospects that are significantly ahead of the official statistical information

Community-based economic romance and integration: assessing the feasibility of a currency union in South Asia

Purpose This purpose of this study aims to critically evaluate the feasibility of establishing a single currency area within the South Asian Association for Regional Cooperation (SAARC) by examining the economic integration of its member states. The analysis focuses on the extent to which the region meets the criteria of the optimum currency area (OCA) theory, particularly in terms of business cycle synchronization, labor mobility and capital flows. Design/methodology/approach Using a vector autoregression (VAR) model within the aggregate demand-aggregate supply framework, this research investigates the symmetry of supply and demand shocks across SAARC economies. The study analyzes the synchronization of business cycles and the mobility of labor and capital to determine the readiness of SAARC for a unified currency. Findings The results indicate significant asymmetries in business cycles among SAARC countries, with substantial disparities in economic responses to shocks. These findings suggest that the region lacks the necessary economic synchronization required for a successful single currency area. Limited labor and capital mobility further complicate the potential for economic integration within SAARC. Research limitations/implications The study is constrained by data inconsistencies and the limited range of economic indicators available for SAARC countries. Future research should expand the analysis to include a broader set of socioeconomic factors and more comprehensive data sets to better assess the region’s potential for monetary integration. Practical implications The study highlights the challenges of forming a currency union in South Asia due to economic disparities and limited mobility. However, gradual steps toward deeper regional integration, improved financial infrastructure and enhanced cross-border collaboration could foster long-term economic stability, growth and social cohesion in the SAARC region. Social implications The research highlights the potential social benefits of enhanced economic integration, such as increased community resilience and social cohesion, while also warning of the risks associated with premature monetary union in a region with significant economic disparities. Originality/value This study provides a detailed analysis linking the theoretical framework of the OCA to the practical realities of economic integration in South Asia. By focusing on the specific economic conditions of SAARC member states, the research offers valuable insights for policymakers considering regional monetary integration.

A CDSS based Integrated Pathway for Influenza Vaccination Across Primary and Secondary Care

Abstract Background In Italy, influenza vaccination coverage in people ≥ 65 years is unsatisfactory (56.7%), underlining the need to improve current vaccination strategies. The objectives of this study have been: to define a novel pathway to increase influenza vaccination adherence among ≥ 65 years population in the Lazio region; to provide a predictive estimate of the epidemiological and economic pathway’s potential impact. Methods A multidisciplinary working group (WG) featuring cross-sectoral expertise was created and WG periodic meetings were held to define the patient journey and its flow-chart representation. The pathway’s potential impact was assessed through epidemiological and economic indicators and scenario analyses. Results An integrated pathway across primary and secondary care was defined, based on the active patient in-Hospital recruitment and vaccination and enhanced by a Clinical Decision Support System relying on a digital algorithm to identify eligible patients. Assuming an increase of influenza vaccination coverage from the current rate of 60% (scenario 1) to 65% (scenario 2) in ≥ 65 years population in the Lazio region thanks to the pathway implementation, an increase of 8% in avoided influenza cases, influenza- or pneumonia-related hospitalizations and influenza-related outpatient visits was estimated with a relative increase in savings for hospitalizations and outpatients visits of up 2,367,310 euros. Setting the vaccination coverage at 70% (scenario 3), an increase of 16% in avoided influenza cases, hospitalizations and outpatient visits was estimated with a relative increase in savings for hospitalizations and outpatients’ visits of up to 4,833,259 euros. Conclusions Alongside offering a predictive estimate of the relevant pathway’s potential impact, both epidemiological and economic, this project, with its robust methodology, may serve as a scalable and transferable model for enhancing vaccination coverage at national and international level. Key messages • The proposed pathway, offering the option of receiving flu vaccination within the Hospital, supports the paradigm shift towards primary prevention pathways in secondary care settings. • Another relevant aspect of the integrated pathway is the adoption of an Artificial Intelligence tool to identify suitable patients and improve their recruitment and adherence to vaccination.

Demonetization and its effects on Indian economy

Indian government has taken a bold decision on note ban on 08/11/2016. Central government was a judicious, well-thought out and well-implemented step, and whether it would really eradicate all the existing black money. Here I have utilized the opinions of great expert on economics, financial economist and intellectual politicians. This study will help us to know about the positive and negative impact of note ban decision taken by Indian government. This study is purely based on secondary data, which is collected from news papers, magazines, websites from internet, some useful books related to topic etc. This paper entails the problems related to pre and post demonetization period and thereby to find out solutions and to provide suggestions in order to overcome the problem. Demonetization is the process of withdrawal of a particular form of currency from circulation. The purpose of the study is to compare and analyse the impact of demonetization on Indian economy during pre and post period. The older denominations must be replaced with the new ones. The findings of the study reveal that India will achieve a significant growth by adopting the demonetization strategy and will create a huge positive impact on the entire economy in a long run. This paper also shows that it was quick step taken by the government of India without any measures which people had to face a lot of consequences in standing in the long queues to exchange their older denominations.

Reflections of Economic Shocks and Price of Crude Oil on Gold Price Volatility within Asian Nations

The focus of this study is to examine the effects of economic shocks along with the crude oil price on gold prices in Asian countries. This study utilizes a regression analysis to measure the relationship between the macroeconomic indicators, crude oil price, and gold price in six selected nations from 1990 until 2022. The validity of the data was diagnostically checked by performing a VIF procedure, autocorrelation test, and normality test on residual, and data were analyzed via EViews software. The analysis showed mixed findings, however, a major variable that positively affects the fluctuation of the gold price is “the crude oil price” and it reflects global economic stability in the six countries. A sudden rise in crude oil prices might trigger conflicts in oil-exporting countries and limit access to material sources. This situation may force investors to move their funds into a safe-haven commodity like gold. The fluctuations in crude oil prices are not only a response to current market conditions but also alarming a lot more fundamental problems in an economy, which include approaching economic recessions, currency devaluation and a major financial crisis. For practical implications, this study suggests that policymakers pay extra attention to this commodity besides other economic indicators like inflation, interest and currency rates, and a GDP rate to ensure a sustainable economic condition. To the best of the authors’ knowledge, this study is the first that examines the economic shocks along with crude oil prices pre-and-post COVID-19 pandemic focusing on a few Asian countries.

A Bibliometric Analysis of Sustainability in MSME

This research paper examines the role of Micro, Small, and Medium Enterprises (MSMEs) in the Indian economy and their sustainability. It analyses 85 Scopus documents from 66 sources between 2014 and 2024, revealing a peak in scientific production in 2023. The study emphasizes the importance of sustainable practices for long-term success. This comprehensive research paper rigorously examines the pivotal role of Micro, Small, and Medium Enterprises (MSMEs) in the Indian economy and emphasizes the critical importance of sustainable practices for long-term success. Through meticulous analysis of 85 Scopus documents from 66 sources between 2014 and 2024, the study conclusively reveals a peak in scientific production in 2023 and robust ties between India and various other countries in this domain.

Euroization of the Economy and the Negative Impact of the Strengthening of the Local Currency on Exports and Other Economic Indicators in Albania

The Albanian economy is a small and open economy. As such, it is quickly influenced by the turbulence of the global, European, and regional economies. Economic theory emphasizes the link between the exchange rate, exports, the consumer price index, and the balance of foreign trade. The purpose of this article is to study the impact of the exchange rate, primarily at the export level, while also considering other economic factors within the framework of the overvaluation of the Albanian currency (ALL) against the currencies of partner countries, mainly the Euro. The overvaluation of the Albanian currency has led to discouraging exports and increasing imports, influencing the rise in the Consumer Price Index, meaning higher consumer prices. This is due to the fact that the Albanian economy is mainly dependent on imports. The empirical and econometric models used, along with the factors included in this study according to the hypotheses raised, are related to assessing the mutual relationships of the exchange rate with other economic factors for the time period 2018-2023.The results imply and depict the integrated relationship between the exchange rate and exports and other economic factors, as well as supporting the fact that the real exchange rate (RER) has deviated from its equilibrium level. The conclusions in this study confirm that an overvalued domestic currency has increased costs for operations conducted in the local currency ALL, reducing income for operations conducted in Euro and other currencies. This overvaluation of the domestic currency has resulted in losses for exporting companies, impacting the trade balance. Based on the findings in this study, it is crucial for financial institutions and policymakers to be consistent in monitoring the exchange rate, especially EUR/ALL, to improve the long-term relationships between the exchange rate, exports, and other economic factors.

The Relationship Between the Development of the Art Industry and the Turnover of Economic Cycles

Abstract: In recent years, the area has grown significantly, creating a trend in art appreciation. This boom has led to a surge in the popularity of museums such as the National Gallery. This project aims to find out more about the economic contribution of art exhibitions. Using advanced time series analysis models including the intervention analysis model and vector autoregressive model, we obtained the following conclusions. First, the positive impact of low levels of economic development and high levels of government expenditure on the arts industry is obvious. Second, the growth of the arts industry has a small impact on most economic indicators. Third, the final impact of GDP on the arts industry is still uncertain due to the complex pattern of the model, with the possibility of a positive correlation with ln (art prices) being observed in the early stages of small GDP growth, while a quadratic pattern may be observed when the GDP index grows above a certain level and art prices fall Conclusion. Further research is needed to investigate the complex relationship between inflation and art prices. Our academic contribution mainly focuses on the multiple-way causal relationships between the economy, art exhibition, tourism, and education, which reveals the underlying mechanism of how art exhibitions promote the economy.

Research on the Impact of Economic Policy Uncertainty and Investor Sentiment on the Growth Enterprise Market Return in China—An Empirical Study Based on TVP-SV-VAR Model

This study employs the economic policy uncertainty index to gauge the level of economic policy uncertainty in China. Utilizing textual data from the growth enterprise market internet community, we construct the growth enterprise market investor sentiment index by applying the deep learning ERNIE (Enhanced Representation through Knowledge Integration) model, thereby capturing investors’ sentiment within the growth enterprise market. The dynamic interplay between economic policy uncertainty, investor sentiment, and returns of the growth enterprise market is scrutinized via the TVP-SV-VAR (time-varying parameter stochastic volatility vector auto-regression) model, and the asymmetric response of different industries’ stock returns within the growth enterprise market to economic policy uncertainty and investor sentiment shock. The findings of this research are that economic policy uncertainty exerts a negative influence on both investor sentiment and returns of the growth enterprise market. While it may trigger a temporary decline in stock prices, the empirical evidence suggests that the impact is of short duration. The influence of investor sentiment on the growth enterprise market returns is characterized by a reversal effect, suggesting that improved sentiment may initially boost stock prices but could lead to a subsequent decline over the long term. The relationship between economic policy uncertainty, investor sentiment, and returns of the growth enterprise market is time-variant, with heightened sensitivity observed during bull markets. Lastly, the effects of economic policy uncertainty and investor sentiment on the returns of different industries within the growth enterprise market are found to be asymmetric. These conclusions contribute to the existing body of literature on the Chinese capital market, offering a deeper understanding of the complex dynamics and the factors influencing market behavior.

Migration and Economic Development: The Role of Migrant Flows in Shaping Turkey’s Emerging Economy and Uncovering Hidden Conflicts and Challenges

This research examines the economic impact of migration on Turkey's emerging economy, with a particular focus on the contributions of migrant remittances, labor market dynamics, and the socio-political challenges associated with large-scale migrant flows. By employing econometric models and field research, the study explores the relationship between remittance inflows and key economic indicators such as GDP growth, employment rates, and poverty reduction. Additionally, the research uncovers hidden conflicts and social tensions that arise from migration, including labor market inequalities and integration challenges faced by both migrants and Turkish workers. The project evaluates government policies, such as the EU-Turkey refugee agreement, and their effects on economic development and social stability. Field research in migrant-receiving communities reveals the complexities of labor competition and the social dynamics created by migrant dependency in sectors such as agriculture and construction. Findings highlight the need for inclusive migration policies that balance the economic benefits of remittances with the social integration challenges faced by migrant populations. This study also advocates for stronger labor protections and regulatory reforms to mitigate tensions and reduce exploitation in low-wage sectors. The research contributes to the broader understanding of migration’s role in shaping Turkey’s economy and provides insights for policymakers seeking to address both the economic and social dimensions of migration.

Macro Indicators and Housing Prices in the U.S.

This study examines the influence of macroeconomic indicatorsU.S. GDP, tax rates, population, and interest rateson housing prices across the United States, utilizing data from 1982 to 2018 sourced from the Federal Reserve Economic Data (FRED). Employing a comprehensive analytical framework, including multiple linear regression, time series analysis, and a mixed-effects model, the research identifies GDP and tax rates as significant factors affecting housing prices. GDP positively correlates with housing prices, whereas higher tax rates have a negative impact. The study highlights the importance of accounting for regional variations through mixed-effects modeling, which captures the diverse impacts of economic indicators across different states. This approach offers nuanced understandings to the real estate market's dynamics, emphasizing the role of economic growth and fiscal policies. The findings aid policymakers in understanding the economic forces shaping housing markets and suggest further research avenues, particularly in incorporating recent global economic events like the COVID-19 pandemic.

Evaluating the Role of GCC Nations in Sustainable Energy Investment Using an Enhanced Low-Carbon Economy Index

In the past decade, environmental, social and country governance (ESG) aspects as well as economy have become key factors for decisions in the investment and future development of renewable energy industry. The abundancy of renewable resources and widely accessible technology are the key drivers for the renewable energy business in the GCC. However, lack of effective policies and regulations, along with subsidized fuel prices, are slowing down the implementation of renewable resource options. This study will illustrate the potential, the challenges, and the barriers of implementing renewable energy technologies in the GCC region. In addition, this research empirically examines the impact of renewable energy sources and other factors in the GCC countries. This study can be used as a screening tool, decision making tool, benchmarking tool and guidance of sustainable development.

Sustainability assessment of additive manufacturing end-of-life material management

Additive manufacturing (AM) methods enable complex, customized, and on-demand production of many products from different material types across various industries. The growing demand for flexible and more sustainable manufacturing solutions places AM in the mix of processes considered for non-commodities. However, AM processes also present unintentional environmental releases in end-of-life (EoL) material management, compromising overall sustainability. Data availability to assess the sustainability of individual EoL material management from individual AM processes is limited. Even so, EoL materials generated across AM practices frequently overlap, supporting high-level assessment as an alternative approach. Therefore, a holistic AM EoL material management sustainability analysis was completed using a customized list of efficiency, environmental, energy, and economic indicators from the Gauging Reaction Effectiveness for the Environmental Sustainability of Chemistries with a multi-Objective Process Evaluator (GREENSCOPE) methodology. Subsequently, this assessment identified low material recycling rates and high energy costs in some EoL material management processes, such as incineration and recovery. Subsequently, a trade-off analysis was performed to determine process modification opportunities, including implementing recycling to reduce the amount of hazardous waste at the expense of additional energy and cost investment. The AM EoL-specific sustainability analysis serves as a resource to offer insights and empower policymakers and stakeholders to enhance pollution prevention strategies and optimize the existing EoL material management processes.

Integrated Systematic Framework for Forecasting China’s Consumer Confidence: A Machine Learning Approach

This study aims to introduce a novel approach for predicting China’s consumer confidence index (CCI), a key economic indicator that reflects consumers’ confidence in current and future economic conditions. While traditional statistical models and economic indicators are the primary tools for forecasting CCI, their reliance on linear assumptions limits their ability to capture the complex, dynamic relationships inherent in economic systems. In response, this study proposes a two-step method that integrates social network analysis (SNA) and machine learning (ML) to enhance prediction accuracy by accounting for the nonlinear interactions and systemic interdependencies that drive consumer confidence. The use of SNA enables the identification of critical variables and their interconnected roles in shaping consumer sentiment, while ML models, specifically the gradient boosting decision tree (GBDT), leverage these relationships to provide more precise predictions. Utilizing monthly data from 1999 to 2023, the combined SNA and GBDT approach significantly improves the accuracy of CCI forecasts, particularly during periods of high volatility. The results of this study hold substantial value for policymakers, market analysts, and economists, as they offer a systems-oriented framework for economic forecasting. By demonstrating the effectiveness of combining SNA with ML technologies, this research not only advances the methodological toolkit for economic forecasting, but also provides a new lens through which the complex, adaptive nature of economic systems can be better understood and managed. This integrated approach paves the way for future developments in forecasting models that more accurately reflect the evolving dynamics of consumer confidence in a rapidly changing economic environment.

Диалектика централизации и децентрализации управления в СССР и современной России

The examination of the evolution and modernization of the governance system of socialist industry and, in particular, the alternation of its centralized and decentralized forms within the command system will make it possible to understand the reasons for the rise and fall of the Soviet economic system, as well as the resulting difficulties of the modern stage of the country’s development. In this regard, the aim of this article is to investigate the causes and factors influencing the transition between centralized and decentralized governance in the USSR and transitional Russia. This study involved a review of literature detailing the most notable periods of centralization, such as the industrialization in the USSR (1928–1937) and the state reforms of the 2000s in the Russian Federation, as well as periods of decentralization, including the establishment of local People’s Commissariats of governance (1953–1964) and the market reforms of the 1990s. The research was based on the works of both domestic and international scholars. The analysis revealed a systemic need for alternating waves of centralized and decentralized governance. Using the examples of the Soviet Union and the Russian Federation, the article delineates the main phases of governance transition, economic indicators, and the factors influencing these processes.

From Field to Market: The Challenges Faced by Onion Growers in Chitradurga, Karnataka, India

Horticultural crops are integral to the Indian economy, serving as a major source of employment, and supplying vital raw materials to the food processing sector. Their cultivation leads to enhanced farm profitability, driven by increased yields and improved market opportunities. Moreover, the export of horticultural produce significantly contributes to foreign exchange earnings, further strengthening India's economic framework. Onion grows extensively across the nation in a variety of climates. India is the world's second-largest producer of onions. It ranks first in terms of acreage, third in terms of exports, and contributes roughly 22.83% to global production. The present study was conducted in 2023 in the Chitradurga district of Karnataka, aimed to identify the challenges faced by onion growers and gather their recommendations for addressing these issues. A total of 120 farmers were selected for the study, comprising sixty small and sixty big farmers. Utilizing an ex post facto research design, data were collected through a pre-tested, structured interview method. The findings highlighted several key constraints in onion cultivation, including limited awareness of nutrient management, price fluctuations in the market, and inadequate access to credit. The majority of farmers recommended the implementation of a minimum support price for onions and timely provision of credit at low-interest rate to mitigate these challenges.

Reduction of production delay cost in underground coal mines: An FMEA-based method study approach

Coal is the backbone of the Indian economy, essential for electricity, steel, cement, and other vital items. Although India aims to be carbon emission-free by 2070, it must rely on coal for a few more decades. In the fiscal year 2021–22, India produced 96 percent of its coal from open-cast (OC) mines, whereas 70 percent of India's total coal reserve is in deep undergrounds. Despite underground (UG) coal mining being eco-friendly and yielding richer coal, its production cost is nearly four times higher than OC mining. Therefore, further research on UG mines is necessary to address these challenges. This study analyzed an underground coal mine production system in India and identified production delays as a major cost driver. Causes of delays were categorized by their association with machine, material, and man. An innovative technique, the Machine Criticality Score (MCS), has been developed to quantify production delay costs and guide management in mitigating them. Additional methods like failure mode and effects analysis (FMEA), standard operating procedure (SOP), inventory management tools, and method study were also used in this study to reduce production delay costs.

Analysis of economic indicators of four drying methods applied on three apple cultivars

Fruits are one of the main components of a healthy diet. They have many benefits and are recommended for regular consumption as part of a varied healthy diet. However, they are seasonal fruits, some need to be processed to ensure more extended storage and consumption throughout the year. The research aims to analyse the economic indicators of three apple cultivars (Golden Delicious, Florina and Freedom) dried by four methods (sun-died, shade-dried, dehydration, lyophilization). The methodological framework of the study includes: (1) Theoretical overview of apple drying methods; (2) Analysis of the economic indicators of apple drying – gross output, production and additional costs, net income, and rate of return; (3) Determining the benefits and drawbacks of drying apple products. It was found that the drying methods – sun-dried, shade-dried, and lyophilization – have a higher rate of profitability, while dehydration has a lower rate. The lyophilization method is the most profitable for production with Florina, followed by Freedom and Golden Delicious. Keywords: dried apple method, gross output, rate of return, production costs, net income