Economic Indicators Research Articles

An empirical investigation into dynamics of growth of Indian economy impacted by public and private sector investment: Is there evidence of crowding out effect?

This study examines the dynamic effects of public and private investments on India’s economic growth, focusing on disaggregating public sector investments into infrastructure and non-infrastructure Gross Fixed Capital Formation (GFCF). Key questions include: How do public infrastructure and non-infrastructure investments impact economic and private sector growth? What roles do Foreign Direct Investment (FDI), labour force participation, and the real interest rate play in shaping economic growth? The study uses the Autoregressive Distributed Lag (ARDL) model to analyze 40 years of macroeconomic data from 1980–81–2019–2020, offering insights into both short- and long-term effects. Findings reveal a crowding-out effect of public infrastructure investment on private investment in the short term but a crowding-in effect in the long run. FDI, labour participation, and the real interest rate significantly influence GDP growth, confirming their roles as critical drivers of economic expansion. Disaggregating public investments shows infrastructure and non-infrastructure investments play distinct roles in shaping economic outcomes. This study contributes by addressing the gap in understanding how different types of public investments affect private sector activity in India and broadens investment analysis by incorporating FDI, labour participation, and the real rate of interest, offering new evidence for research and policy formulation.

Development Coordination of Chinese Megacities Using the Node–Place–Value Model: A Case Study of Changsha

With the acceleration of urbanization, urban regeneration has become a critical strategy for megacities to address spatial fragmentation and inefficient resource allocation. However, the mismatch between transportation nodes and land development potential remains a key barrier to sustainable urban renewal. This research takes the urban renewal areas in Changsha as a typical case. Based on the “Node–Place–Value” (NPV) model, a multi-dimensional evaluation system was constructed. Through multiple empirical analysis methods such as spatial data analysis, field research, and economic indicator evaluation, this study deeply explores how this evaluation system provides a theoretical and data basis for detailed planning and further provides guidance for meeting the needs of urban renewal. Through the empirical analysis of the urban renewal areas in Changsha, this study quantifies the matching relationship among transportation nodes, land use, and economic value and reveals the current imbalance issues of these elements in the areas. For example, there is a common mismatch between the functions of transportation nodes and the potential of land development. Specifically, the land use in transportation hub areas fails to fully utilize their transportation advantages, resulting in the waste of transportation resources and low economic benefits. The results reveal significant imbalances in the following areas: Transportation–Land Mismatch: High-accessibility areas (e.g., Martyrs’ Park and Railway Station ) exhibit underdeveloped land use and low economic conversion efficiency. Peripheral Lag: Remote areas (e.g., Wang Xin and Sunshine 100 ) lack both transportation infrastructure and land development potential, leading to resource waste. Value Dimension Impact: The added “value” dimension highlights thatareas with cultural assets (e.g., Martyrs’ Park) achieve higher comprehensive scores despite spatial constraints. The findings of this study not only provide a scientific basis for urban renewal in Changsha but also offer crucial theoretical support and practical references for other megacities in China to address similar issues and achieve sustainable development.

The Impact of Economic Indicators on Renewable Energy Consumption in Southern Africa: Evidence from Residual Augmented Least Squares Cointegration and Method of Moments Quantile Regression Models

Renewable energy has emerged as a transformative and essential alternative in the global energy sector. Many countries are striving to achieve the Sustainable Development Goals (SDGs) established by the United Nations for 2030, particularly the goal of ensuring that all individuals have access to clean and affordable energy. This paper re-examines the impact of economic growth (EG), trade openness (TO), exchange rates (ER), foreign direct investment (FDI), green finance (GF), and oil prices (OL) on renewable energy consumption (REC) across 14 Southern African countries: South Africa, Botswana, Lesotho, Namibia, Tanzania, Madagascar, Mauritius, Kenya, the Comoros, Zambia, Eswatini, Rwanda, Angola, and Mozambique, during the period of 2000 to 2022. This study employed cointegration and unit root tests, as well as the RALS-EG and MMQR models, to estimate the long-run relationships among the variables. The results reveal that renewable energy consumption is positively and directly related to economic growth, trade openness, exchange rates, green finance, and foreign direct investment across all quantiles (q05–q95), with no evidence of asymmetric effects. These findings suggest that economic growth, green finance, and foreign direct investment are crucial for fostering renewable energy innovation in Southern African countries. Policymakers are encouraged to prioritize strategies that enhance these factors as a foundation for achieving sustainable energy solutions.

AgroVision AI

Agriculture remains the backbone of India's economy, yet farmers continue to face challenges related to unpredictable crop prices, inefficient water usage, climate variability, and lack of actionable market intelligence. AgroVision AI is an integrated, AI-powered agricultural intelligence platform designed to empower farmers with data-driven insights. Leveraging advanced machine learning models such as LSTM and CatBoost, AgroVision AI predicts crop prices, recommends efficient irrigation schedules, offers precise crop health analysis, and provides real-time weather forecasting. The platform integrates external APIs for dynamic market price updates and weather conditions, while delivering user-friendly dashboards and visual insights through a modern web interface. By synthesizing market trends, soil conditions, climatic factors, and historical data, AgroVision AI enhances agricultural decision-making, optimizes resources, and maximizes profitability for farmers. This research paper presents the design, methodology, and potential impact of AgroVision AI in revolutionizing the agricultural ecosystem through predictive analytics and smart farming technologies.

The Financial Economic Development Agenda of the SADC Region

Financial markets have been used in developing economies to raise and maintain these economies social stability level, and to facilitate economic development. Economic development is about the upliftment of the living standards and freedom of the citizens by upgrading the quality of human lives. The study strove to realise the objective of determining if different forms of financial markets can influence economic development in selected Southern Africa Development Community (SADC) countries. Panel econometric techniques were utilised and periods examined spanned from 2007 to 2021. Economic development may not be quantified using a single indicator. Economic development as the dependent variable was measured by the Economic Development Index (EDI) which was constructed using indicators such as the Human Development Index, Economic Complexity Index and Gross Domestic Product per capita. The money market, stock market and foreign exchange market were found to negatively influence EDI in the long-run. Financial markets can be stated to influence the development and economic performance of the selected SADC countries. Based on the findings, it is recommended that monetary authorities and regulatory authorities ensure that the monetary, fiscal, and financial policies are well managed, and that these policies are implemented to develop the social and economic level of the country.

Goods and Services Tax: An Inflationary Reform or a Myth for the Indian Economy? Empirical Insights Using Intervention Modeling

Taxation reforms often create speculative environments, enabling undue advantages for producers and suppliers. In India, the adoption of the goods and services tax (GST) marked a significant shift in the indirect tax mechanism. The international experiences with GST raised concerns that this reform might lead to inflationary pressures in the Indian economy. Therefore, this study aims to examine the impact of GST implementation on inflation in India using the Box and Tiao Intervention methodology. The findings indicate that the GST reform did not lead to a significant increase in the prices of various commodities in the Consumer Price Index basket in India. The initial rise in the general price level was transitory, peaking around the introduction of GST and then gradually subsiding as misconceptions about inflationary pressure from GST implementation were dispelled in Indian society. The results confirm that the GST reform successfully removed market distortions and improved the efficiency of resource allocation. The findings assert that by lowering the overall tax burden compared to pre-reform conditions, GST fostered price stabilization across different commodity baskets in India. JEL Classification Code: C32, E62, H21, H25, H20 .

The Transformation of Economic Structure in Developing Countries: Evidence of Financial Development as a Source of Financing

ABSTRACTThis article examines the influence of financial development (FD) on the transformation of the economic structure in 89 developing countries (21 low‐income countries and 68 middle‐income countries) during 1996–2018. Different FD indicators are grouped and ungrouped: FD, financial institutions (FI) and financial markets (FM), each assessed through depth (FID, FMD), access (FIA, FMA) and efficiency (FIE, FME). An Economic Structure Transformation Index (ESTI) encompasses four dimensions: manufacturing, manufacturing trade, innovation and manufacturing employment. Empirical results demonstrate that FD stimulates economic transformation. Moreover, the mediation analysis reveals that FD not only has a direct positive effect on the transformation of the economic structure but also has a positive indirect effect through its impact on agricultural productivity, digitalization of the economy, and commercial openness. To accelerate the positive effects of FD on the transformation of the economic structure, governments should formulate policies aimed at improving productivity in the agricultural sector, thereby encouraging the migration of surplus labour from this sector to the manufacturing sector. Additionally, promoting the digitalization of the economy would be beneficial for fostering the adoption of advanced technologies. Furthermore, encouraging commercial openness aims to enhance the production and quality of goods and services by exploiting comparative advantages between countries.

Inequitable Industrialization: Metal mineral-based development in India, 1950 to 1980

We appraise the simultaneous development of industrialization and increase in inequality in India, 1950-1980, through the organizational lens of MR Bhagavan (1985). Some contradictions from the period persist into the 21st century and we, constructively, employ the framework of Samir Amin (2012) to recommend a refocussing of attention to agriculture in the Indian economy.

Towards Resilience: A Comprehensive Risk Assessment of Natural Hazards in Uttarakhand, India

In the previous decade the Himalayan state of Uttarakhand in India, though located in Seismic Gap of 1905 and 1934 earthquakes, has been spared by major seismic events. The state has however witnessed a number of other major hazards that include 2013 Mandakini – Alaknanda floods that devastated Kedarnath and Rambara, and 2021 avalanche triggered winter season Rishiganga – Dhauliganga floods that devastated hydro-power projects at Rini and Tapoban. In order to help policymakers prioritise resource allocation for disaster risk reduction and building resilience, this study assesses the risk of natural hazards on the constituent districts of the state, and the same is considered as being a function of hazard and vulnerability. The hazard is assessed by the impact of natural incidences in terms of human casualties, infrastructure damage, and livestock loss over the previous decade (2015-2024), while vulnerability is assessed through demographic, economic, and infrastructural indicators. The analysis reveals significant variations in risk levels across districts, with Champawat unexpectedly emerging as the highest-risk district, followed by Chamoli, Uttarkashi, Bageshwar, and Pithoragarh. This finding underscores the importance of comprehensive risk assessments that incorporate both hazard and vulnerability factors, challenging the common perception of certain districts as being relatively safe. The study recommends prioritizing high-risk districts for targeted disaster risk reduction interventions, including investment on infrastructure, capacity building, and community-based preparedness, while also addressing underlying vulnerabilities such as poverty, limited access to services, and economic dependence on climate-sensitive livelihoods to enhance resilience and promote sustainable development in Uttarakhand.

Time-Varying Causality Impact of Global Economic Conditions Index on Remittances in Lebanon

Abstract Using the recently developed Global Economic Conditions Index, a time-varying Granger causality approach, as well as relying on the monthly dataset from January 2002 to June 2021, we investigate both symmetric and asymmetric causality between the Global Economic Condition Index and remittances in Lebanon, a small open economy significantly reliant on remittances. Rather than being asymmetric, we find a statistically significant, symmetric, time-varying causality between the Global Economic Conditions Index and remittances. Several robustness tests validate our findings. Given this finding, we propose relevant policy recommendations.

Enhancing lithium recovery from spent lithium-ion batteries: Techno-economic analysis comparison with and without extractant recovery process.

Enhancing lithium recovery from spent lithium-ion batteries: Techno-economic analysis comparison with and without extractant recovery process.

The role of green commodities in the sports industry imports: shaping green growth in high-income countries

The sustainability of the sports industry and the use of green commodities are pressing global issues. This study explores the dynamics of importing eco-friendly sports equipment across 15 high-income countries from 2001 to 2019, using an autoregressive distributed lag model. Results underscore the importance of governance: even slight improvements significantly increase green sports equipment imports by streamlining trade and boosting consumer confidence. Social factors like education have limited influence, while poverty levels are a critical factor, reflecting economic limitations on consumer spending. Economic indicators reveal that larger GDP correlates with lower import levels, while exchange rate volatility negatively impacts imports. Additionally, higher CO2 emissions reduce import demand, pointing to growing environmental awareness. These findings suggest key policy actions for high-income countries, including strengthening governance, addressing economic and social constraints, and promoting sustainable education to foster environmental responsibility.

The Role of Sustainable Development in Emerging Economies: An Examination of Environmental and Economic Indicators

The Role of Sustainable Development in Emerging Economies: An Examination of Environmental and Economic Indicators

THE PROBLEM OF THE INFLUENCE OF TECHNOLOGICAL CHANGE ON ACCELERATION OF LABOR MOBILITY IN SOUTH AMERICA (ARGENTINA, BOLIVIA, CHILE)

South America continues to experience major socioeconomic changes that are influencing global trends. They are caused by the need for a global transition to environmental and alternative energy technologies. South America’s mineral resources are important to the region, driving major changes in the region’s labor market. Instability and imbalances in the labor market have an impact on accelerating labor mobility.The relevance of this study is to try to explain the factors of increased internal migration within South American countries and a decrease in population in metropolitan cities. The purpose of the study is to clarify the role of technological and industrial development on labor mobility in Latin America. The subject is the growing influence of demand for mineral resources on deurbanization and labor mobility.To determine the impact of the role of industry on labor mobility the authors used the data on personnel movements in 2022–2023 and salary changes from 2022 to 2024. For this purpose, a method of comparative analysis of economic and statistical indicators on labor movements was applied, which allows us to understand how salaries in industry can affect the personnel migration movements. The author came to the conclusion that technological changes have a major impact on migration processes in South America. The need to develop and extract new minerals and increase the scale of extraction of unexplored ones is becoming a factor in wage growth in this sector, which contributes to an increase in the movement of labor.

Economic performance of organic dairy farms during and after conversion

Abstract Empirical research on the economic performance of organic farming yields conflicting results. The findings vary by region, agricultural sector, economic performance indicators and methodologies used. This study compares the economic and financial performance of conventional and organic dairy farms by specifically examining the performance trends during the period when conventional farms got converted into organic farms. Using a difference-in-differences estimator within a panel regression model, we analysed the microdata of 1,016 farms in Ille-et-Vilaine (Brittany, France) between 2007 and 2018, including 62 farms that had converted from conventional farming to organic farming during this period. Our results show that, contrary to expectations, the financial performance of the farms did not reduce significantly during the conversion. However, after the two-year conversion period, the profitability and return on assets of organic farms exceeded those of conventional farms. Considering the limited sample size of organic farms analysed in this study, these findings require further validation.

Problems and prospects for the development of the tourism industry in the region (using the example of the Republic of Khakassia)

The article provides an in-depth review and analysis of statistical data on tourist flow in the region and related economic indicators. A comparative analysis of the tourism industry development in the regions of the SFD: Tyva, Krasnoyarsk Krai, Altai and Khakassia; the dynamics of changes in the indicators is given in the period from 2014 to 2024. The review of available scientific literature on the stated problematic allowed us to identify a number of factors that have a significant impact on the development of the tourism industry in the regions of the Russian Federation. This made it possible to highlight the negative factors and their consequences for the tourism industry of the Republic of Khakassia. It was concluded that tourism with the realization of all factors of its effective functioning is one of the most universal and rapidly developing sectors of the national economy. At the same time, in order for the tourism industry to get a point of growth, its driver should be investments and special attention and support from the regional authorities. The effectiveness of the tourism industry development for the regional budget revenue, creation of additional jobs and socialization of society is shown.

The link between the shadow economy and the happiness economy in EU euro area countries

Purpose – the aim of this study is to assess the relationship and influence between the shadow economy and the level of happiness in the Euro area economies of the European Union by highlighting the theoretical assumptions behind the concept and expression of the shadow economy and happiness. Research methodology – to calculate the size of the shadow economy will be used Gutmann’s index. To calculate the happiness of the economies will used the Happiness Economy Index from the World Happiness Report (2022) including the following 6 indicators (GDP per capita, healthy life expectancy (that derives to life expectancy and mental health evaluation), social support, freedom index, generosity (do-nations to charity), and corruption index. To determine the relationship between the shadow and happiness economy, the Granger causality method. Research limitations – the study’s limitations include data reliability and accuracy, methodological limitations, geographical and cultural differences, and time constraints. The estimation of the size of the shadow economy and the happiness economy index may contain inaccuracies, and the Granger causality method cannot fully confirm causality. The study is limited to the euro area countries of the European Union; therefore, the results may not be fully applicable to other countries. Additionally, the data may not fully capture long-term trends or developments. Practical implications – the results of this study can help policymakers and economists better understand how to reduce the size of the shadow economy and thereby increase people’s happiness. The study’s findings indicate a positive correlation between a country’s Happiness Economy Index and the size of its shadow economy. This suggests that investing in people’s well-being can positively impact the formal economy. Furthermore, the study’s findings can inform the development of effective strategies to combat the informal economy. For instance, strategies such as enhancing social support, increasing the freedom index, and combating corruption can potentially reduce the size of the informal economy and improve the overall economic situation in a country. Findings/Value – the research confirmed the hypothesis that the size of the shadow economy is smaller in countries with a higher happiness economy index. And Granger causality tests show that the shadow economy has a relatively strong effect on happiness in the EU euro area countries.

External and Domestic Debt: Which is More Beneficial for Long-term Economic Growth?

From 1991 to 2022, the impact of public debt on India's economic growth is a multifaceted issue including a variety of social, political, and economic factors. Some argue that India's economy is suffering as a result of global economic concerns like recessions or depressions in other countries. As a result, the government must obtain loans to compensate the loss. The study attempted to explore the impact of public debt on India's economic growth between 1991 and 2022. It highlights two main perspectives on the debt crisis: global economic changes and domestic policy errors. Domestic debt has a coefficient of 0.056 and a p-value of 0.027, suggesting a positive and significant association with the dependent variable. External debt has a coefficient of 0.926 and a p-value of 0.0003, showing a strong and statistically significant positive association with the dependent variable. While borrowing is essential for capital-scarce economies like India to stimulate development, empirical research often shows a negative correlation between public debt and long-term growth. The study found that prudent debt management and using borrowed funds to diversify the economy can help generate resources to repay obligations without harming economic stability. Policymakers should use borrowed funds to diversify productive capacities, discourage excessive foreign borrowing, and balance fiscal stimulus with sustainable debt levels.

The Capitalist Discount Rate in India Or Anti-Working Class Strategies of the Ruling Class in India

While driven by the experience of India, the following remarks apply to any country of the world. Investment in plant and machinery, even if multipurpose and driven by cloud computing and Artificial Intelligence (AI), is a purposeful thrust into the future. In order to earn profits, expected demand must justify the considerable costs incurred today. If the future is clouded by the portent of shocks that cannot be forecasted, investment plans are stillborn. The contemporary twist is options that are available to corporations. Nonfinancial firms can transmute into financial firms. Stock market returns remain high, even if volatile, through financial crises. The cost of subdued real activity is unemployment. The labor market remains in a long twilight with no work and flat or falling wages. Clearly, the state must bridge the present and a perilous future. An imaginative industrial policy for India, for instance, would connect failing agriculture and soporific industry. However, the state and monopoly capital are in cahoots and at war with the Indian people. In this article, we share our diary of recording events as they unfold in the Indian economy. The mere reporting of incoherence and contradictions underscores the irrationality of Indian capitalism.

Co-creation to measure what matters: The case of Venserpolder, Amsterdam

ABSTRACT In light of widening urban inequalities, the use of top-down policy approaches and narrowly defined economic indicators is criticized for overlooking broader and divergent well-being needs, in objective and subjective terms. Despite growing calls for a human-centered and multidimensional approach to urban policy, there is a dearth in empirical research addressing required instruments. This paper presents a pilot study in which citizens identify broader well-being indicators and co-create a local policy instrument (Wellbeing Dashboard) in Venserpolder, a marginalized Amsterdam neighborhood. A transferable bottom-up method is derived, entailing co-creation, face-to-face surveys and experimental dialogs, that supports citizen empowerment. Findings indicate how the process empowers citizens through social learning and capacity building. Moreover, the Wellbeing Dashboard provides credible data on well-being needs and priorities, otherwise ill-captured in formal economic indicators, and facilitates citizen empowerment once embedded in policy practice.