Development Economics Research Articles

Analysis of Policy Options Based on Data-Driven Economic Cycles and Industrial Structure Upgrading

China's economy has achieved a high growth rate of 9.8% in cyclical fluctuations, and the industrial structure has been continuously improved with growth. However, the irrationality of the tertiary industry structure and its internal structure still restricts the sustainable development. The optimization of the industrial structure depends on many factors, such as government policies, economic growth mode, resource constraints, economic development stage and economic cycle stage. Based on data-driven analysis, this paper analyzes the general path and policy choice of economic cycle to adjust China's industrial structure, and the impact of economic cycle on the upgrading of industrial structure. After the actual analysis, we found that the threshold of economic growth in economically developed regions is high, the role of financial development in stimulating industrial structure is not prominent, and industrial upgrading is relatively difficult. Industrial upgrading is difficult.

Coupling and interaction mechanism between green urbanization and tourism competitiveness based an empirical study in the Yellow River Basin of China

Exploring the spatial coupling relationship and interaction mechanism between green urbanization (GU) and tourism competitiveness (TC) is of great significance for promoting urban sustainable development. However, the lack of research on the interaction mechanism between GU and TC limits the formulation of effective environmental management policy and urban planning. Taking 734 counties in the Yellow River Basin (YRB) as the study area, this paper analyzes the spatial coupling relationship between GU and TC on the basis of comprehensive evaluation of GU and TC. Then, the interactive mechanism between GU and TC is systematically discussed, and the synergistic development strategy of the two is proposed. The results show that the GU level presents a multicore circle structure, with provincial capitals, prefecture-level urban districts and economically developed counties in east-central regions as high-value centers. The TC at county scale presents a multi-center spatial structure. Additionally, there is a significant positive spatial coupling between GU and TC in the YRB. The analysis further reveals that green urbanization level, social progress, population development, infrastructure construction, economic development quality, and eco-environmental protection has a observably influence on TC. Tourism competitiveness, service competitiveness, location competitiveness, resource competitiveness, market competitiveness, environmental influence, and talent competitiveness has a observably influence on GU. TC can promote GU, and the improvement of green urbanization level can support the development of tourism competitiveness. According to the spatial zoning method, 734 counties are divided into 6 categories, and the coordinated development strategy of GU and TC for each type of district is proposed.

Spatiotemporal dynamics and determinants of medical service efficiency in China

BackgroundMedical service efficiency is an important indicator for measuring the equity of medical services. Therefore, this study primarily focuses on investigating the spatiotemporal domain to explore both spatial and temporal characteristics, as well as influencing factors that affect medical service efficiency across diverse provinces in China.MethodsThe super Epsilon-based Measure (EBM) unexpected model has previously been utilized to quantify energy eco-efficiency, carbon emission efficiency, and green development efficiency. However, limited studies have applied this method to assess the efficiency of healthcare services. Therefore, this study investigates the application of the super-EBM-unexpected model in evaluating medical service efficiency, and further integrates spatial econometric models to explore the influencing factors of medical service efficiency and aims to identify potential avenues for improvement.ResultsThe average efficiency of medical services in the 31 provinces of China ranges from 0.6 to 0.7, indicating predominantly low efficiency values. However, economically developed coastal areas exhibit relatively high efficiency levels above 1. Conversely, regions with relatively lower levels of economic development demonstrate lower efficiency rates at approximately 0.3. Evidently, substantial regional disparities exist. For the influencing factors, the enhancement of residents' living standards can effectively foster the medical service efficiency, while residential living standards of nearby areas can also exert an impact in this region. The influence of educational attainment on medical service efficiency exhibits a significant inhibitory effect.ConclusionsThe majority of China's 31 provinces exhibit suboptimal medical service efficiency, with notable regional disparities. Future policy initiatives should be tailored to address the unique challenges faced by regions with lower levels of economic development, prioritizing enhancements in both the efficacy and quality of their healthcare systems.

Models of quality costs by A. Feigenbaum, J. Juran, F. Crosby in the concept of the development of quality economics

Aim. Consider the specifics and features of quality cost models by A. Feigenbaum, J. Juran, F. Crosby in the context of increasing the efficiency of cost management.Objectives. Describe Joseph M. Juran's model (Juran's Spiral); classify quality costs by J. Juran — A. Feigenbaum; describe the classification of costs by F. Crosby.Methods. This work uses general scientific research methods: deduction, induction, generalization, comparative analysis, synthesis (unification), study and theoretical analysis.Results. In the modern economy, product quality plays a critical role, influencing the competitiveness and stability of the country's economic system, which makes quality management not just a formality, but a strategic necessity. Active implementation and development of quality systems is considered by enterprises as a means to improve reputation, increase market share and strengthen customer loyalty, and such systems help reduce costs by preventing defects and optimizing processes.Conclusions. An analysis of quality cost models was carried out as one of the key methods in increasing the economic efficiency of the organization. In modern quality management practice, special attention is paid not only to the identification and assessment of quality costs, but also to their role in the process of making managerial and technical decisions. This is especially true when planning the production activities of an enterprise. Quality cost analysis is becoming an important tool to help management formulate economically sound decisions.

Research on multiscale OpenStreetMap in China: data quality assessment with EWM-TOPSIS and GDP modeling

ABSTRACT OpenStreetMap (OSM) is a voluntary platform designed to provide free and up-to-date geographic data. Since OSM is based on multisource geographic data provided by the public, the quality of the data has become a concern of researchers. In this study, a unified measure for evaluating OSM data quality was constructed, and the entropy weight method (EWM) and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) model were used to evaluate the quality of multiscale OSM data in China from 2014 to 2020. In addition to evaluating the data quality, the use of OSM data quality index factors in economic modeling at different spatial scales in China was explored by using a geographic information system (GIS) analysis method and a geographically and temporally weighted regression (GTWR) model. Four machine learning models, SVM, RF, XGBoost and CatBoost, were used to simulate the grid-scale GDP, and the effectiveness of these simulations was discussed. The results showed that (1) the weights of OSM data quality indicator factors vary across different spatial scales. (2) From 2014 to 2020, the quality of national-scale OSM data first increased, then decreased and then gradually stabilized. In addition, the quality of OSM data at the provincial and municipal scales is significantly different, and the distribution is affected by the population and geographical environment. (3) Over time, the spatial clustering characteristics of OSM data quality at different spatial scales in China has continuously strengthened. In addition, the quality of Chinese OSM data displays obvious local spatial autocorrelation characteristics, which are dominated by H-H clustering and L-L clustering. (4) The GTWR model performs well in predicting and revealing the spatiotemporal correlation characteristics between GDP and OSM data quality indicators at the provincial and municipal scales in China. The correlations increase with decreasing spatial scale (provincial to municipal). Moreover, the GDP modeling ability is better in economically underdeveloped Northwest China and economically developed East China. (5) Four machine learning models coupled with road network length completeness, relative linear density, road name attribute completeness, POI name attribute completeness, road network accuracy, road network update frequency, POI update frequency, topological consistency and directional similarity yielded the best grid-scale GDP simulation values. Notably, the CatBoost model provided the best accuracy, and the results further verified that it is feasible to use the proposed OSM data quality index system to predict the regional economic development level in China.

Analysis of spatial patterns and influencing factors of farmland transfer in China based on ESDA-GeoDetector

Farmland transfer is a critical component in facilitating agricultural scale management and improving agricultural production efficiency. This study examines the spatial distribution of farmland transfer in China and identifies the factors influencing it, offering valuable guidance for advancing China’s farmland transfer practices. Through the application of mathematical statistics and GIS spatial analysis, the study investigates changes in spatial patterns related to the scale, rate, mode, and recipients of farmland transfer across China's 30 provinces from 2015 to 2020. Geographical detectors are also employed to identify the key factors influencing the extent and pace of farmland transfer. The study reveals that between 2015 and 2020, China's farmland transfer area increased from 29,789 to 37,638 million hectares. Provinces with abundant farmland resources generally experienced larger farmland transfers, while economically developed regions and major grain-producing areas saw higher rates of farmland transfers. The predominant mode of farmland transfer in China was leasing (subcontracting), accounting for over 80% of the total transferred area. Large-scale grain growers and family farms were significant participants in farmland transfers, acquiring approximately 60.1% of the transferred lands, followed by professional cooperatives (21.5%), enterprises (10.4%), and other entities (7.9%). Key factors influencing the farmland transfer area include the "regional farmland area", the "proportion of family farms supported by loans", and the "proportion of non-agricultural population", with explanatory powers of 0.663, 0.319, and 0.225, respectively. Notably, there is a substantial interaction between the "regional farmland area" and factors such as the "proportion of family farms supported by loans" and the "grain yield per unit area", with explanatory powers reaching 0.957 and 0.901, respectively. These findings offer valuable insights for promoting farmland transfer in agriculturally rich regions. Factors affecting the farmland transfer rate include "grain yield per unit area", "GDP per capita", and the "proportion of non-agricultural population", each with an explanatory power above 0.500. Moreover, their interactive explanatory powers with other indicators exceed 0.600, indicating that provinces with high agricultural productivity or economic development levels are more likely to undergo farmland transfer. The paper concludes by proposing strategies and recommendations to promote farmland transfer in both "large agricultural areas" and "metropolitan suburbs."

Modeling Climate Change Issues in Indonesia Based on Media Headlines

Climate change has become a global issue affecting all countries in the last decades. This phenomenon poses a concern to Indonesia as it is one of the climate change’s epicenters. Various studies have shown that climate change can harm multiple community activities, such as unstable agricultural production, decreased people’s health, and global warming. This study tried to model and analyze climate change topics discussed in the media. Finding hidden topics from texts can provide clues and information regarding public conversation surrounding climate change, such as public thoughts, perceptions, and readiness to mitigate the possible adverse effects of climate change. In order to identify hidden subjects from the corpus, this work modeled climate change issues in Indonesia using the latent Dirichlet allocation (LDA) algorithm to analyze texts from Indonesian media headlines. As many as 7,000 headline data from five online media were collected from 2017 to 2021 using web scraping techniques. The proposed approach produced eight topics related to climate change, which were determined by the highest coherence value of 0.560. Those topics were renewable energy, carbon emissions, environmental management, development economics, international cooperation, policy/regulation, rehabilitation, and disaster. Based on the results, the model could sufficiently describe the theme of discussion in society and photograph public thoughts and the government’s readiness in the form of policies and regulations in dealing with the climate change phenomenon.

Akuntansi Mudharabah

In line with the development of sharia economics, sharia financial institutions in managing their activities are also required to be more optimal in managing and applying the mudharabah accounting concept as an opportunity or opportunity to develop business or investment with capital that they do not have so as to create a concept of mutual benefit between the parties involved. concerned. In order to obtain these benefits, it is necessary to understand in detail the procedures and criteria and mudharabah accounting that are in accordance with the rules that have been established. So, the purpose of the discussion of this article is to examine the concept of mudharabah accounting in Islamic economics. The importance of this discussion topic as a reference for humans, especially Muslims to be able to understand matters relating to mudharabah accounting.

Income inequality as a determinant of neonatal mortality in the Americas during 2000–2019: implications for the attainment of Sustainable Development Goal target 3.2

BackgroundThe work of the WHO Commission on the Social Determinants of Health has been fundamental to provide a conceptual framework of the social determinants of health. Based on this framework, this study assesses the relationship of income inequality as a determinant of neonatal mortality in the Americas and relates it to the achievement of the Sustainable Development Goal target 3.2 (reduce neonatal mortality to at least as low as 12 deaths per 1,000 live births). The rationale is to evaluate if income inequality may be considered a social factor that influences neonatal mortality in the Americas.MethodsYearly data from 35 countries in the Americas during 2000–2019 was collected. Data sources include the United Nations Inter-agency Group for Child Mortality Estimation for the neonatal mortality rate (measured as neonatal deaths per 1,000 live births) and the United Nations University World Institute for Development Economics Research for the Gini index (measured in a scale from 0 to 100). This is an ecological study that employs a linear regression model that relates the neonatal mortality rate (dependent variable) to the Gini index (independent variable), while controlling for other factors that influence neonatal mortality. Coefficient estimates and their robust standard errors were obtained using panel data techniques.ResultsA positive relationship between income inequality and neonatal mortality is found in countries in the Americas during the period studied. In particular, the analysis suggests that a unit increase in a country’s Gini index during 2000–2019 is associated with a 0.27 (95% CI [− 0.04, 0.57], P =.09) increase in the neonatal mortality rate.ConclusionThe analysis suggests that income inequality may be positively associated with the neonatal mortality rate in the Americas. Nonetheless, given the modest magnitude of the estimates and Gini values and trends during 2000–2019, the findings suggest a potential limited scope for redistributive policies to support reductions in neonatal mortality in the region. Thus, policies and interventions that address higher coverage and quality of services provided by national health systems and reductions in socio-economic inequalities in health are of utmost importance.

Women's Development Training To Encourage Women's Participation In The Aspect Of Development (Economic, Political, And Social) In The Implementation Of Sustainable Development Goals (SDGs) In Kampung Nelayan Seberang Belawan

Women's Development Training To Encourage Women's Participation In The Aspect Of Development (Economic, Political, And Social) In The Implementation Of Sustainable Development Goals (SDGs) In Kampung Nelayan Seberang Belawan

Can the development of the rural digital economy reduce agricultural carbon emissions? A spatiotemporal empirical study based on China's provinces

Rapid advancement of the rural digital economy has intensified the demand for leveraging digital tools to foster low-carbon and sustainable agricultural practices, garnering widespread academic and bureaucratic attention. Understanding how the rural digital economy influences agricultural carbon emissions is crucial for unlocking emission reduction potential, facilitating a transition towards sustainable energy usage in rural areas, and nurturing green agricultural development. In this study, we employ the entropy method, a spatial Durbin model, and a panel threshold model to assess the impact of the rural digital economy on agricultural carbon emissions across each province in China from 2010 to 2022. Additionally, we delve into the mechanism through which the rural digital economy facilitates agricultural carbon reduction, particularly in terms of “agricultural socialized services”.Our findings reveal several key insights. Firstly, the rural digital economy contributes significantly to reducing agricultural carbon emission intensity. Secondly, there is a non-linear relationship between the rural digital economy and agricultural carbon emissions. With the development of rural digital economy showing a marginal decreasing trend, there is an obvious threshold effect. Thirdly, enhancing agricultural socialized services through the rural digital economy can curb agricultural carbon emissions. Lastly, the carbon reduction effect of the rural digital economy is more significant in more economically developed areas, areas with moderate levels of economic development, and areas with low technological investment; implementation of a “zero growth” policy for fertilizers strengthens this carbon reduction effect. This study sheds light on the mechanisms and effects of agricultural carbon emissions, offering quantitative evidence and theoretical support for the transition towards low-carbon and sustainable agricultural development.

Shadow of Technology: Robotics Development and Regional Economic Inequality

Shadow of Technology: Robotics Development and Regional Economic Inequality

Advances in behavioral economics: paradigm shift towards a humanistic economics

The objective of the study is to offer a critical review, of scope and limits of content, on the development of behavioral economics, with attention to the Ibero-American contributions to overcome the biases of the Neoclassical Synthesis and thus rehumanize the study of economics, so a bibliometric study was developed in the Scopus database, comprising more than a thousand articles related to behavioral economics. With the metadata obtained a descriptive analysis has been made, plus bibliometric maps using VosViewer software, to present the thematic connections. Thus, it can be seen that there is a growing trend in scientific production in this field, and that the United States, Germany and the United Kingdom are the leading countries with a greater number of researches and of greater impact, influencing theoretical and applied developments. The most cited research is focused on the generation of scientific knowledge that contributes to achieving objectives of social interest, which is precisely where behavioral economics must go in order to achieve a more humane economy. There is an incipient participation of researchers from Latin American countries, especially in Scopus Q1-rated journals, which could represent an advance in innovation that could translate into a paradigmatic change, if governments and public policy designers seek an economy less focused on production and GDP growth, and rather focused on human satisfaction.

Research on the Decoupling Relationship and Driving Factors of Carbon Emissions in the Construction Industry of the East China Core Economic Zone

This study focuses on the core economic zone of East China, utilizing the decoupling model to investigate the relationship between carbon emissions and economic development in the construction industry. Furthermore, it analyzes the driving factors through the application of the logarithmic mean index method. The findings reveal that, firstly, Zhejiang and Jiangsu provinces exhibit higher total carbon emissions in the construction industry. Except for Fujian Province, the other regions exhibit a downward trend after 2019. Secondly, there is considerable spatial variability in carbon emissions in the construction industry within the core economic zone of East China, and it gradually decreases over the study period. While economically developed regions like Zhejiang and Jiangsu provinces tend to concentrate and consume more resources and energy, their impact on surrounding neighboring provinces or cities is relatively limited. Thirdly, carbon emissions from the construction industry in the core economic zone of East China show a development trend shifting from weak decoupling to strong decoupling, indicating a healthy growth in the construction industry. Specifically, different regions show different trends. Lastly, regarding influencing factors, the impact direction of carbon intensity on total carbon emissions shows instability. Energy intensity consistently exhibits inhibitory effects, and the economy and the population scale act as driving forces.

The Belt and Road Initiative and Dynamics of Structural Transformation

Structural transformation is among the core questions in development economics, but in recent decades, the discipline has shifted its focus away from production and transformation in favour of analyses on exchange, growth and productivity. Yet, the structural transformation question remains central, and needs to be confronted with the main changes in the global economic and political landscape, such as the emergence of the Belt and Road Initiative (BRI). With its emphasis on an infrastructure-based connectivity agenda, the BRI opens the space for a paradigm shift in development, and for a renewed emphasis on structural transformation. This article introduces a special issue that explores the role of the BRI in promoting structural transformation in low- and middle-income countries, to understand if and under which conditions the BRI creates pathways that can change the structure of the economies. Through an explicit focus on the role of BRI on transformation in low- and middle-income countries, this special issue examines how domestic institutions regulate and coordinate production diversification, national and international sectoral specificities, and drivers and barriers to technological innovation and trade. In this sense, the special issue sheds light on new conceptualisations and empirical examples of industrial policies.

The moderating role of national economic development on the relationship between ESG and firm performance in the global hospitality industry

This study examines the effect of national economic development (NED) on the relationship between Environmental, Social, and Governance (ESG) and firm performance. While ESG principles are embraced collectively by firms and nations, the influence and benefits of implementing ESG practices may vary across countries and firms operating within them. Drawing on the market-orientated perspective and Maslow’s hierarchy of needs model, we attempt to fill the gap within the global hospitality context by examining NED as a country-level boundary condition. With a sample of 1383 observations of global hospitality firms from 2002 to 2022, the findings suggest that the more economically developed a country is, the more firms can generate firm performance by engaging in sustainability performances. Moreover, it suggests the varying effects of individual ESG factors on firm performance regarding their short- and long-term effects. The study findings have important implications, providing valuable insights for researchers, policymakers, and practitioners.

Editorial

The Journal Scientific Research World Economy EconConnections - Professionals On Line, plays an essential role as the main platform for the dissemination of theoretical and empirical research in a wide range of disciplines within the field of economics and related areas. Enveloping a wide range of topics, it stands as the primary channel for the exploration of general economic theory, political economy, business economics, industrial economics, labor economics, urban and rural economics, development economics, technological economics, tourism economics, transportation economics, macroeconomics, microeconomics, quantitative economics, resources and environmental economics, economic history and demography, as well as international trade, exchange rates, finance , accounting and insurance.

The Influence Of Village Funds And Allocation Of Village Funds And Financial Assistance On Poverty Alleviation In East Kalimantan Province

The aim of this research is to determine and prove the effect of providing village funds, allocation of village funds and provincial financial assistance on the level of welfare of village communities in districts throughout East Kalimantan as viewed from a development economics perspective. The analytical method used in this research is a panel data regression model. Data processing techniques were carried out using the Eviews 7.0 computer program. The research results show that Village Funds have a positive and significant effect on poverty alleviation. This means that the greater the distribution of village funds, the more poverty alleviation programs in the village will increase; Allocation of village funds has a significant positive effect on poverty alleviation. This means that the greater the distribution of village fund allocations, the more poverty alleviation programs in the village will increase; Provincial financial assistance has a significant positive effect on poverty alleviation. This means that the greater the distribution of provincial financial assistance, the more poverty alleviation programs will increase; Village funds, village fund allocation and provincial financial assistance simultaneously have a significant effect on poverty alleviation. This means that the distribution of village funds, allocation of village funds and provincial financial assistance have a significant impact on poverty alleviation in villages.

How does technological progress affect low carbon economic growth? Evidence from regional heterogeneity in China.

The rapid economic development leads to excessive consumption of fossil energy, resulting in a large number of carbon emissions, which makes the sustainable development of China's economy and society face great challenges. Under the background of global warming and environmental deterioration, developing low-carbon economy has become an inevitable choice for China to change its development model and improve its international competitiveness. Technological progress is the first driving force to promote economic growth. However, the influence degree and mechanism of technological progress on the development of low-carbon economy are still unclear. Based on this, the paper proposes the concept of low-carbon GDP, which is used to measure the low-carbon economic development of 30 Chinese provinces. Then, the panel fixed effect model is used to study the effect degree and mechanism of technological progress on low-carbon GDP and the moderating effect of other factors on the relationship between them. The results show that, first, economically developed provinces and regions have higher per capita low-carbon GDP and low-carbon GDP index, but the speed and quality of low-carbon economic development are not necessarily higher. Second, technological progress can promote the growth of low-carbon GDP and make greater contributions to resources-poor regions. Third, improving local education can make technological progress more effective in low-carbon economic development. China needs to upgrade technological development by developing new and high-tech technologies, promoting new urbanization and strengthening education in order to promote low-carbon economic development.

Analisis Faktor-Faktor Yang Mempengaruhi Lama Mencari Kerja Perempuan Lulusan S1 Prodi Ekonomi Pembangunan FEB Universitas Riau

There are various factors that cause women to experience difficulties in getting work, even though they already have a bachelor's degree. Some of them are influenced by age, salary, work experience and GPA. Therefore, researchers conducted an analysis of the factors that influence the length of time looking for work for women graduates of the Development Economics Study Program, FEB, Riau University, which aims to determine the influence of age, wages and work experience on the length of looking for work for educated female workers who graduated from the FEB Development Economics Study Program. Riau University. The analytical model used in this research is multiple linear regression data. The sample used was 78 students from a total population of 781 female students who graduated from the S1 Development Economics Study Program, Riau University from 2013 to 2018. The results of this research show that the most influential thing is the length of time looking for work for women who graduated from the Development Economics Study Program, FEB Riau University. is choosing too many jobs with the desired wage standard. Meanwhile, the factors of age, work experience and GPA have a significant influence.