Traditional Economic Indicators Research Articles

Higher Education Investment, Human Capital Level, and High-Quality Economic Development: Evidence from Chinese Provincial Data

While extensive research has examined economic growth in China, the complex relationship between knowledge-based inputs and comprehensive development remains poorly understood, particularly at the provincial level. Previous studies have largely focused on traditional economic indicators, overlooking how education investment and human capital collectively shape multidimensional development outcomes across China's diverse regions. To address this gap, we construct a novel development index incorporating innovation, sustainability, and social progress metrics, analyzing panel data from 31 Chinese provinces (2000-2020) through two-way fixed effects models with instrumental variables. Our findings reveal that higher education investment significantly enhances comprehensive development, with this effect amplified in regions with greater human capital accumulation. Notably, regional heterogeneity analysis demonstrates stronger investment effectiveness in eastern provinces compared to central regions, while western provinces show no significant relationship. These results underscore the importance of regionally differentiated approaches to educational investment and human capital development, offering valuable insights for policymakers seeking to promote balanced growth across China's economically diverse landscape.

Exploring economic activity from outer space: A Python notebook for processing and analyzing satellite nighttime lights

Nighttime lights (NTL) data are widely recognized as a useful proxy for monitoring national, subnational, and supranational economic activity. These data offer advantages over traditional economic indicators such as GDP, including greater spatial granularity, timeliness, lower cost, and comparability between regions regardless of statistical capacity or political interference. However, despite these benefits, the use of NTL data in regional science has been limited. This is in part due to the lack of accessible methods for processing and analyzing satellite images. To address this issue, this paper presents a user-friendly geocomputational notebook that illustrates how to process and analyze satellite NTL images. First, the notebook introduces a cloud-based Python environment for visualizing, analyzing, and transforming raster satellite images into tabular data. Next, it presents interactive tools to explore the space-time patterns of the tabulated data. Finally, it describes methods for evaluating the usefulness of NTL data in terms of their cross-sectional predictions, time-series predictions, and regional inequality dynamics.

From economic wealth to well-being: exploring the importance of happiness economy for sustainable development through systematic literature review

AbstractThe pursuit of happiness has been an essential goal of individuals and countries throughout history. In the past few years, researchers and academicians have developed a huge interest in the notion of a ‘happiness economy’ that aims to prioritize subjective well-being and life satisfaction over traditional economic indicators such as Gross Domestic Product (GDP). Over the past few years, many countries have adopted a happiness and well-being-oriented framework to re-design the welfare policies and assess environmental, social, economic, and sustainable progress. Such a policy framework focuses on human and planetary well-being instead of material growth and income. The present study offers a comprehensive summary of the existing studies on the subject, exploring how a happiness economy framework can help achieve sustainable development. For this purpose, a systematic literature review (SLR) summarised 257 research publications from 1995 to 2023. The review yielded five major thematic clusters, namely- (i) Going beyond GDP: Transition towards happiness economy, (ii) Rethinking growth for sustainability and ecological regeneration, (iii) Beyond money and happiness policy, (iv) Health, human capital and wellbeing and (v) Policy push for happiness economy. Furthermore, the study proposes future research directions to help researchers and policymakers build a happiness economy framework.

THE WELL-BEING OF NIGERIA’S RURAL POPULATION: A REVIEW OF LITERATURE

There is increasing relevance and interest in the concept of well-being in economics with economists and policy makers viewing it as very critical in gauging the pulse of an economy. It is seen as a key component in the evaluation of the performance and progress of an economy in addition to traditional economic indicators such as Gross Domestic Product (GDP) and Income per capita. This paper, based on a detailed review of literature aims to present the contributory factors of subjective perception of well-being among Nigeria’s rural inhabitants. It focuses on papers which examine the concept of well-being from renowned academic databases like Elsevier and ScienceDirect. This review provides a background to the complexities and variations of the concept of well-being as well as gaining an in-depth understanding of existing research and opinions on the subject matter. The conclusions from the research show that subjective well-being is multi-dimensional and understanding its multi-dimensional nature can help in shaping economic policies. With respect to rural Nigeria, housing, infrastructure, community engagements and financial security are highly contributory to the subjective perception of an individual’s well-being. With a holistic grasp of these factors, local government authorities may device means to create an environment of prosperity and fulfillment in order for the inhabitants to thrive and contribute to the economic development of their communities.

Sentiment-Driven Exchange Rate Forecasting: Integrating Twitter Analysis with Economic Indicators

Abstract This study focuses on predicting the USD/TL exchange rate by integrating sentiment analysis from Twitter with traditional economic indicators. With the dynamic nature of global finance, accurate exchange rate forecasting is crucial for financial planning and risk management. While economic indicators have traditionally been used for this purpose, the increasing influence of public sentiment, particularly on digital platforms like Twitter, has prompted the exploration of sentiment analysis as a complementary tool. Our research aims to evaluate the effectiveness of combining sentiment analysis with economic indicators in predicting the USD/TL exchange rate. We employ machine learning techniques, including LSTM Neural Network, xgboost, and RNN, to analyze Twitter data containing keywords related to the Turkish economy alongside TL/USD exchange rate data. Our findings demonstrate that integrating sentiment analysis from Twitter enhances the predictive accuracy of exchange rate movements. This study contributes to the evolving landscape of financial forecasting by highlighting the significance of sentiment analysis in exchange rate prediction and providing insights into its potential applications in financial decision-making processes. JEL classification numbers: C53, F31, E60. Keywords: Twitter narratives, LSTM, XGBoost, RNN, USD/TL FX rate, Narrative economics.

MEASURING AND IMPLEMENTING SOCIAL PROGRESS IN THE TERRITORY

The article in question addresses the methodological perspective of the Social Progress Index (IPS), critically evaluating how it can support democratic and inclusive public policies, leveling social well-being in the territory. The IPS represents a measure that assesses the social well-being and progress of a society in a territory, going beyond the Gross Domestic Product (GDP) or traditional economic indicators. It can measure and compare the social performance and quality of life of different regions and countries. The case study of the city of Rio de Janeiro is presented in the article, to highlight the many difficulties in implementing public policies that level social well-being in the territory. Historical and structural aspects matter, but they do not condemn us eternally. Investing in social capital is the transformative line of action predicted in academic literature.

Promotion of green economic growth in post-Soviet countries: Role of foreign direct and portfolio investments

Green economic growth ensures the country’s wealth and population well-being with decreasing ecological damages. This strategy requires effective government policy to push economic agents to environmentally friendly behavior and significant financial resources to invest in technological modernization. The study aims to assess whether promotion of green economic growth in post-Soviet countries depends on direct and portfolio investment. The paper develops the index of green economic growth performance considering traditional economic growth, social, and environmental indicators. To determine the contribution of direct and portfolio investments in the promotion of green economic growth performance, regression equations (for the panel of countries as a whole and each country in particular) are developed. All models are supplemented with traditional economic growth control variables (GDP growth, inflation, gross fixed capital formation, trade). The information base is public data from the World Bank for the sample of 13 post-Soviet countries for 2000–2021. It was revealed that Estonia and Latvia have the highest level of green economic growth performance, while Ukraine, Uzbekistan, and Kazakhstan have the lowest. The most effective country (Latvia) uses its green economic growth potential only for 62.33%. Modeling results do not confirm the significance of foreign and portfolio investment contributions in promoting green economic growth in most post-Soviet countries (portfolio investments boost green economic growth in Estonia and Moldova, while foreign direct investments contribute to green economic growth in Ukraine). These results might be explained by a lack of institutional capacity and government efficiency to ensure effective absorption of investments.

Beyond Economics! The (Evolving) Role of Law in the Eradication of Extreme Poverty

Extreme poverty is a complex and multifaceted challenge that cannot be solely addressed through economic interventions. Traditional economic indicators, such as GDP, do not fully capture the realities of vulnerable populations who often experience discrimination and social exclusion. This has legal and human rights implications, particularly in regions such as Sub-Saharan Africa where extreme poverty is concentrated. In light of these concerns, this article critically examines the existing literature on poverty economics and law and presents an analysis of key data. Ultimately, the article argues for a comprehensive approach that prioritises law and justice as crucial components of efforts to achieve target 1 of the United Nations’ Agenda 2030 for Sustainable Development. This approach should entail the establishment of legal frameworks that promote accountability for political actors and protect the rights of the poor.

Cross Reference of GDP Decrease with Nighttime Light Data via Remote Sensing Diagnosis

Nighttime light data is a mainstay method in confirming and supporting other traditional economic data indicators, which in turn influence business and policy-making decisions. Accuracy in and clear definition of economic data and its related indicators are thus of great importance not only for analysis of urban development and related policies seeking sustainable development, but also plays a key role in whether or not these policies are successful. Discovering and recognizing the applications and limitations of nighttime light and other peripheral data could prove helpful in future data analysis and sustainable development policy. One possible limitation could exist in GDP decrease, and whether or not nighttime light would decrease accordingly, as most studies show nighttime light increase confirms economic growth, thus affecting the reliability of the data’s correlation with economic data. This study utilizes nighttime light data in a cross-reference with GDP data during instances of global GDP shrinkage over the years of 2007–2017, split between 2007–2012 for the DMSP dataset and 2013–2017 for the VIIRs dataset. It seeks to establish through linear regression whether or not yearly average nighttime light data products show a positive correlation even during periods of economic decline, thereby providing a clearer understanding of the strengths and limitations of NTL as an economic validation indicator. Analysis shows that both years of global GDP decrease in turn also displayed global nighttime light decrease, in addition to linear regression giving satisfactory results pointing to a positive correlation over the timespan. The VIIRS data series resulted in higher regression coefficients, which is in line with the results of previous literature.

A comprehensive methodology to support decision-making for additive manufacturing of short carbon-fiber reinforced polyamide 12 from energy, cost and mechanical perspectives

Additive manufacturing (AM) technologies have transformed manufacturing, by providing greater control over material deposition and consumption. Thanks to greater customization and their high strength-to-mass ratio, the AM of composite materials has significantly grown over the past few years. The main focus in this research area is improving printing precision and higher production rates. However, there is a lack of thorough analysis on the energy consumption of fused filament fabrication (FFF) machines for composite manufacturing, especially when associated with mechanical and economic aspects. We designed an experimental method, based on flow analysis for measuring the impact of temperature parameters on total cost, energy consumption, and tensile resistance of composite parts made by FFF. The user should be able to improve FFF efficiency regarding economic, energy, and technical aspects and obtain recommendations for setting up and using the machine. This study confirms that combining traditional economic and technical indicators (total cost and tensile resistance) with emerging energy indicators (specific energy consumption) can be successfully applied to additive manufacturing to provide an overview of printing parameters impact. Results are yielding information to support optimization investigations depending on the need and goal. For example, two tested parameter combinations that offer similar tensile properties (4% reduction in tensile resistance compared to the best combination) show a 20% difference with lower energy consumption.

Reliability specification of crack opening in flexural reinforced concrete elements

The paper focuses on the reliability specification of trouble-free operation crack opening in flexural reinforced concrete structures. The opening width is considered based on the reinforcement safety, i.e., safety due to corrosion.The probabilistic approach is used in this paper. Instead of traditional economic indicators, abstract values were used, i.e., measures of safety and corrosion damage of reinforcement. Both values range from 0 to 1. Basic formulas, calculation sequence and results are given herein. The probability of trouble-free operation is calculated under the assumption that all initial design parameters and external influences are distributed according to the normal law. Calculations are performed depending on the crack opening duration and maximum permissible values of crack opening width. The obtained values of the reliability specification of trouble-free operation depend on the maximum permissible values of the standard crack opening width. They not depend on the crack opening duration. Calculation results can be used in the probabilistic approach to reinforced concrete structures.

A network analysis of the structure and dynamics of FX derivatives markets

This work leverages inter-connectivity patterns and dynamics of the FX Options and Non-Delivery Forwards (NDF) to uncover temporal changes in the structure and dynamics of these FX markets via network representations during the period between December 2018 to October 2020. We find considerable structural changes to the NDF market weeks before the volatility increase of financial indices such as VIX or VXEFA and the World Health Organisation pandemic declaration on 11th of March 2020. The NDF market shows evident structural changes, such as an increment in the diversity of operations and the strength of preferential attachment activity. In contrast, the OPT market shows significant changes in its dynamics rather than its structure. Comparing each market dynamics indicates an increased divergence in the specificity of trade operations and distribution of funds, reflecting each market’s contract flexibility. Lastly, this study finds that the network representations provide a simple and insightful understanding of the NDF and OPT markets, and provide a potential avenue for the development of methodologies that provide earlier warning signs of economic instability than traditional economic indicators.

Альтернативный подход к измерению благосостояния населения России, или Почему ВВП для этого не подходит

The subject of the study is the state of welfare of the Russian population in the conditions of interaction between nature and society. The purpose of the work is to estimate the size of Russia's true savings through one of the alternative GDP instruments in the form of the size of true savings, which amounted to 18.5% of the gross national income of the Russian Federation for the period 2000-2018. A significant discrepancy between the author's estimates of true savings obtained and the estimates of the World Bank performed annually for a number of countries, including Russia, has been revealed, and possible causes of inconsistencies have been identified. It was found that in the period under study, the level of true savings in Russia remained positive, which indicates that the economic (optimal) limit of growth has not yet been reached and the current economic development of Russia meets the requirements of resistance to climatic influences, and the level of well-being of the country's population as a whole is acceptable. At the same time, the heterogeneity of true savings in the context of territories deserves attention, since the resource-surplus regions of Russia are leaders in traditional economic indicators, but outsiders in indicators of sustainable development and the true well-being of the population. Conclusions are drawn that the World Bank's methodology for assessing the damage caused by humanity to the natural environment does not ensure the correctness of cross-country comparisons in the main directions of economic development, and also blocks the possibility of scaling estimates to other levels of management.

Analysis of Children’s Online Reading Behavior Oriented for Family Education

Aiming at the problem of supply-demand matching of online reading, an analysis method of children’s online reading behavior oriented for family education has been put forward. The data-based classification method is constructed to classify the sample population by statistical methods, and the traditional index classification is carried out by using K-medoids clustering and logistic regression analysis. The matching degree of population classification is discussed through comparison. R language and Mplus are used to analyze the data for the objective classification of the sample data set. Based on the reading response behavior of children’s online reading users, a differential item functioning (DIF) test of socioeconomic status is carried out. At the same time, the population is divided by traditional economic classification indicators to carry out a DIF test and explore the differences in the reading ability of different classification groups. By comparing the results of the two grouping methods, the main family socioeconomic status factors affecting reading performance are explored and targeted countermeasures are put forward. The experimental results show that when analyzing children’s online reading behavior, using machine learning algorithms such as cluster analysis, logistic regression analysis, and so on can get consistent results and then using the DIF test to explore the responses of category groups can effectively distinguish group differences.

CORRELATION AND INTERACTION OF ECONOMIC CREATIVITY FACTORS AS A DETERMINANT OF SUSTAINABLE DEVELOPMENT (ON THE EXAMPLE OF THE EU COUNTRIES)

The creative economy is currently demonstrating quite intensive development indicators, and the share of the creative sector in GDP creation is constantly growing. The aim of this article is to reveal the interrelation and interdependence of socio-economic development factors and to clarify the place of the creative sector in ensuring sustainable economic growth. On the basis of 19 variables, the economies of the EU countries were analyzed by means of cluster analysis, which allowed the authors to single out 8 clusters in the constructed dendrogram, united by the nature and trends, as well as the role of the creative sector in these processes. In addition, the degree of correlation and interaction between the influencing factors themselves was described. Using RStudio, the authors built two multiple regression models, where the dependent variables were GDP and the global creativity index, and the factors were the indicators used to calculate the creativity index. Innovations and creativity are one of priorities of the program of socio-economic development of the European Union. There is a universal approach to understanding the importance of creative economy in the EU. However, the practical implementation of the strategy of development and activity of the creative industries by the EU countries is carried out in the following different directions – the foreign economic expansion of the creative industries themselves; the promotion of all national culture at the international level; export-oriented development of the creative sector of the economy; the lack of a separate comprehensive strategy of foreign economic activity for the creative industries, but the implementation of various programs and measures aimed at promoting exports of products of these industries as part of a national development strategy. Overall, the active functioning of the EU creative sector directly or indirectly affects the economy by improving its performance and creating jobs, stimulating innovation, and contributing to social and sustainable development. As a result, it was found that the global creativity index is largely dependent on the share of the creative class. It has also been proved that the creative and cultural industries determine the growth of a country's economy in terms of traditional economic and employment indicators. Investments in the creative economy will increase the qualitative and quantitative indicators of sustainable economic development.

Using Multi-Source Nighttime Lights Data to Proxy for County-Level Economic Activity in China from 2012 to 2019

The use of nighttime lights (NTL) data to proxy for local economic activity is well established in remote sensing and other disciplines. Validation studies comparing NTL data with traditional economic indicators, such as Gross Domestic Product (GDP), underpin this usage in applied studies. Yet the most widely cited validation studies do not use the latest NTL data products, may not distinguish between time-series and cross-sectional uses of NTL data, and usually are for aggregated units, such as nation-states or the first sub-national level, yet applied studies increasingly focus on smaller and lower-level spatial units. To provide more updated and disaggregated validation results, this study examines relationships between GDP and NTL data for 2657 county-level units in China, observed each year from 2012 to 2019. The NTL data used were from three sources: the Defense Meteorological Satellite Program (DMSP), whose time series was recently extended to 2019; and two sets of Visible Infrared Imaging Radiometer Suite (VIIRS) data products. The first set of VIIRS products is the recently released version 2 (V.2 VNL) annual composites, and the second is the NASA Black Marble annual composites. Contrasts were made between cross-sectional predictions for GDP differences between areas and time-series predictions of economic activity changes over time, and also considered different levels of spatial aggregation.

Growth or Development Trap

In this essay, we explore how to obtain a more accurate picture not only of the growth situation as measured by traditional economic indicators, but also of the level of development, which also raises the possibility of becoming trapped. We distinguish between development and growth, pointing out that Hungary has good growth figures, but lags behind in terms of development indicators. This discrepancy requires further, more detailed analysis in order to define desirable targets for development indicators that are independent of growth indicators, and to avoid the development trap by achieving them. This is also justified because, in the longer term, the evolution of development indicators also affects the chances of sustainable growth and allows for more general, systemic qualitative progress. Based on the statistical data presented in relation to the issues raised, we conclude that it would be necessary to construct a mathematical model of growth and development to illustrate and econometrically analyse the dynamic relationship. But this is not undertaken in the context of this essay.

The role of social identity in improving access to water, sanitation and hygiene (WASH) and health services: Evidence from Nepal

SummaryMotivationCOVID‐19 has revived focus on improving equitable access to water, sanitation and hygiene (WASH) and health services in developing countries. Most public programming tends to rely on economic indicators to identify and target vulnerable groups. Can expanded targeting criteria that include social status help to improve not only targeting, but also equity in access to WASH and health services?PurposeThis article assesses the role of social identity in mediating access to WASH and health services, controlling for economic disadvantages such as household wealth, income sources, and assets.Methods and approachWe use regression analysis applied to the 2016 Nepal Demographic and Health Survey (DHS) to estimate the relationships between social identity and access to WASH and health services, controlling for wealth (using wealth index quantiles) and remittances (using indicator variables for domestic and international remittances).FindingsWe find that differences in access are mediated in large part by caste, and religious and ethnic identity, especially in rural areas, suggesting that the supply of such services is lower for historically disadvantaged communities. In addition, communities with least access are not necessarily the most economically disadvantaged, indicating that relying solely on traditional economic indicators to target programmes and interventions may not be sufficient to improve equity in access to public health services.Policy implicationsThe results make a case for broadening indicators beyond the economic criteria for improving targeting of public funds for more inclusive development.

Regulating motherhood through markets: Filipino women’s engagement with microcredit

The Philippines is a global leader in deploying microcredit to address poverty. These programmes are usually directed at women. Research on these programmes focuses on traditional economic indicators such as loan repayment rates but neglects impacts on women’s agency and well-being, or their position in the household and relationships with their partners and children. It is taken for granted that access to microcredit leads to enhanced gender freedoms. In line with the growing body of work in feminist scholarship that critiques the instrumentalist logic of microfinance institutions (MFIs) in relation to women, this research foregrounds stories from interviews with female borrowers in Zamboanga City in Southern Philippines to provide grounded illustrations of how microcredit is reshaping relationships between women and their families, women and poverty and women and the state. Borrowers used loans to meet their family’s needs even at the cost of harassment from creditors, indebtedness, increased workloads and conflict with partners. These narratives challenge the dominant neoliberal discourse of female empowerment through access to credit by exposing how microcredit is part of a complex set of regulations around ‘good motherhood’ and consumption, where women’s moral worth is based on their willingness and ability to lift their families out of poverty.

Экономическая эффективность «умного производства»: от целевых установок к регламентации

The article deals with the problems of assessing the economic efficiency of smart production and ways to resolve them. It has been found that Smart Manufacturing is currently becoming a goal in itself and a guarantor of successful development of industrial business. A comparative analysis of scientific publications to clarify the content of the concept of Smart Manufacturing is carried out, it is revealed that it is necessary to distinguish between intelligent and smart production, which are currently used as synonyms. Analysis of the practice of organizing smart manufacturing has shown that often the process of creating Smart Manufacturing pursues the goal of participating in a popular, useful process with the expectation of future “blurry” positive results; but there are also the actual results in the form of cost savings (better organization of the production process), an increase in production and an increase in labor productivity. All enterprises and organizations quite clearly understand the process of creating a specific smart production with detailing of individual stages, therefore, the specific goals of Smart Manufacturing should be specified taking into account a specific enterprise, but at the same time, standardized for the possibility of a comparative assessment of economic efficiency. It has been proved that traditional economic indicators of efficiency are used to assess the economic efficiency of Smart Manufacturing; but for the organization it is necessary to form a special system of performance indicators based on the theory of management by goals. It is determined that the main factor of Smart Manufacturing is innovative capital, since smart manufacturing is innovative by definition. Possible options for the formation and combination of goals and objectives of Smart Manufacturing and innovation capital are considered. The content and structure of the regulation for assessing the economic efficiency of Smart Manufacturing are proposed