Provincial GDP Research Articles

Assessing Sustainable Development in Community Welfare and Economic Resilience to Extreme Weather in Indonesia

In recent decades, Indonesia has experienced a surge in natural disasters, resulting in increased casualties and disruptions to economic growth and welfare. This study investigates the impact of various types of natural disasters, focusing on how economic growth (measured by provincial GDP) and welfare levels (measured by the Human Development Index, HDI) influence the number of victims affected by extreme weather. Data on gross regional domestic product and the Human Development Index for each province in Indonesia were obtained from Statistics Indonesia. We employed multivariable negative binomial regression to analyze the relationships between the number of victims affected by extreme weather, provincial HDI, and provincial GDP. The results indicate significant correlations between provincial GDP, HDI, and the number of victims. Higher HDI correlates with fewer victims, whereas higher GDP is associated with an increase in victims. Additionally, we used the Self-Organizing Map (SOM) method, identifying two clusters as the optimal model. Cluster 1 comprises 31 provinces, while Cluster 2 comprises 3 provinces, with the latter highlighting the provinces with the highest disaster risk. Consequently, provinces such as West Java, Central Java, and East Java require heightened attention from various stakeholders involved in disaster management efforts. By examining these relationships, our study contributes to the understanding of sustainable development and resilience against natural disasters. It underscores the importance of improving welfare and economic policies to mitigate the impacts of extreme weather events.

Trends in violent offending among people with schizophrenia: A 10-year ecological study

Violent offending committed by people with schizophrenia has been a public concern. The present study aims to examine the incidence of violent offending among people with schizophrenia and its correlations with mental health resources and economic factors. In this study, an examination of violent offending by people with schizophrenia and those identified as not criminally responsible on account of mental disorder (NCRMD) between 2010 and 2019 in China's Hunan province was undertaken. Principal component analysis (PCA) and regression analyses were used to explore the association of violent offending in people with schizophrenia and those identified as NCRMD with violent offending in the general population, mental health medical resources, and provincial GDP. Between 2010 and 2019, a total of 2,093 people with schizophrenia committed violent offending in Hunan province, including 1,374 (65.6%) cases identified as NCRMD. Over the period, the incidence of violent offending in people with schizophrenia and those identified as NCRMD has been decreasing. The incidences were positively correlated with the incidence of violent offending in the general population and negatively associated with mental health resources and provincial GDP. These findings may be valuable in helping to develop strategies for violence prevention and risk management for people with schizophrenia.

Development of calcium-modified biochar for enhanced phytoremediation of human-induced salt pollutants (HISPs)

Soil salinization is a major environmental hazard that limits land availability. Human-induced salt pollutants (HISPs) are regularly presented in large quantities on the contaminated site (such as brine leakages and salt-water spills), causing a devastating shock with high salt stress to the ecosystem. For instance, Saskatchewan resulted in a 48% drop in wheat production and a 0.3% decline in provincial GDP. As the calcium-modified biochar can potentially ameliorate the negative effects of HISPs on plants and improve the plant, phytoremediation with calcium-modified biochar can have increased detoxification of hazardous pollutants from sites. Therefore, the objective of our study was to develop a biochar-assisted phytoremediation employing diverse approaches to calcium modification for the sustainable removal of HISPs. The co-pyrolyzed calcium biochar achieved a remarkable removal rate of 18.06%, reducing salinity from 9.44 to 7.81 dS/m. During a 90-day long-term phytoremediation, the overall reduction rate of calcium-modified biochar stimulated the germination and growth of Thinopyrum ponticum. The result of post-treatment further indicated that co-pyrolyzed biochar with Ca transferred salt into the plant compared to Ca-coated biochar, which only immobilized HISPs on its surface. These results offer two different treatment approaches for diverse situations involving HISPs contamination, addressing current in-situ spills and providing a calcium-related biochar technology for further research in desalination.

Forecasting Zhejiang Province's GDP Using a CNN-LSTM Model

Zhejiang province has experienced notable economic growth in recent years. Despite this, achieving sustainable high-quality economic development presents complex challenges and uncertainties. This study employs advanced neural network methodologies, including Convolutional Neural Networks (CNN), Long Short-Term Memory networks (LSTM), and an integrated CNN-LSTM model, to predict Zhejiang's economic trajectory. Our empirical analysis demonstrates the proficiency of neural networks in delivering reasonably precise economic forecasts, despite inherent prediction residuals. A comparative assessment indicates that the composite CNN-LSTM model surpasses the individual CNN and LSTM models in accuracy, providing a more reliable forecasting instrument for Zhejiang's high-quality economic progression.

Examine the Correlation Between the Number of Higher Education Institutions And the Provincial GDP In China

Economic inequality is a challenging affair influenced by various factors. Education has long been the topic usually raised when discussing economic inequality. This research investigates how secondary education impacts social status, mobility, and, most importantly, economic inequality nationally. This research has developed a unique methodology to investigate the relationship between the number of schools and economic inequality in China. By applying the indicator of the Gini coefficient, the distribution inequality of the number of schools in thirty-one provinces in China. This research combined studies by Liu. Y, Xu.M, and Gustafsson apply those theories to a more local context in different provinces. The results show that the number of higher education institutions positively correlates with the GDP per capita in each province, with some expectations caused by the flaw of the methodology.

Electricity generation and China's GDP growth under dual control policy

To achieve the carbon neutralization plan by 2060, China implemented the “Dual Control” ( Neng Hao Shuang Kong in Chinese) policy in 2015 by limiting the energy intensity and consumption, leading to forced slowdown of energy-related production and consumptions, which in turn hampered China's economic growth. The economic impact of energy shortage has been discussed in such studies as Cheng et al., the economic consequences of the new policy remain unanswered. In this article, we select China's provincial GDP and electricity generation data from 2001 to 2021 to perform causality tests and a double log model which delineates the nexus between GDP growth and electricity generation. We find that (a) electricity generation growth Granger causes GDP growth but not vice versa, and (b) a 1% increase in electricity generation growth will lead to 0.17% increase in GDP growth. The significance of the finding is: as coal still primarily fuels electricity generation, dual control will further hinder China's economic development sans significant enhancement of electric system or expansion of renewable energy, our findings thus support an upgrade of current grid network by China Power International Development; an expansion of renewable capacity such as a proposal of 400 GW new energy project; and construction of energy storage devices such as the CGD Group thermal storage System and Yingcheng Compressed Air Energy Storage System.

The allometric growth relationship between electricity consumption and economics in China.

Electric power is the basic industry of a modern country. The rapid development of the power industry has promoted economic development and social progress. With the establishment of the carbon neutrality target of carbon peak, China's power industry is also facing new situations and new challenges. This paper innovatively introduces the concept of allometric growth in biology, and uses the data of provincial electricity consumption and economic development from 1972 to 2017, to study the allometric growth relationship between electricity consumption and economics in China at multiple scales. Combined with the spatial autocorrelation analysis method, the temporal and spatial characteristics of allometric growth between electricity consumption and economic development were researched based on the analysis of spatial correlation of GDP electricity consumption intensity. The results show that: (1) The provincial GDP electricity consumption intensity shows an aggregate distribution, and the local aggregate pattern changed significantly from 1972 to 2017. (2) The High-High Cluster gradually disappeared, and the Low-Low Cluster moved southward, appearing in the middle and lower reaches of the Yangtze River. (3) The differential growth coefficient of electricity consumption and economic development increased initially and decreased from 1972 to 2017. (4) GDP would increase by 7.4%, 20.1%, and 15.6% in the simulation of electricity consumption, increasing 10% at the three stages of China's economic development. (5) The allometric growth coefficients of electricity consumption and economic development are very different in the three economic belts, eight economic zones, and provinces with different characteristics at the different stages of economic development. Formulating differentiated regulation policies for regional economic development and electricity consumption will be conducive to the coordinated development of electric power production and the national economy.

Cost-effectiveness of seasonal influenza vaccination of children in China: a modeling analysis

BackgroundChina has a high burden of influenza-associated illness among children. We aimed to evaluate the cost-effectiveness of introducing government-funded influenza vaccination to children in China (fully-funded policy) compared with the status quo (self-paid policy).MethodsA decision tree model was developed to calculate the economic and health outcomes, from a societal perspective, using national- and provincial-level data. The incremental cost-effectiveness ratio (ICER) [incremental costs per quality-adjusted life year (QALY) gained] was used to compare the fully-funded policy with the self-paid policy under the willingness-to-pay threshold equivalent to national and provincial GDP per capita. Sensitivity analyses were performed and various scenarios were explored based on real-world conditions, including incorporating indirect effect into the analysis.ResultsCompared to the self-paid policy, implementation of a fully-funded policy could prevent 1,444,768 [95% uncertainty range (UR): 1,203,446–1,719,761] symptomatic cases, 92,110 (95% UR: 66,953–122,226) influenza-related hospitalizations, and 6494 (95% UR: 4590–8962) influenza-related death per season. The fully-funded policy was cost-effective nationally (7964 USD per QALY gained) and provincially for 13 of 31 provincial-level administrative divisions (PLADs). The probability of a funded vaccination policy being cost-effective was 56.5% nationally, and the probability in 9 of 31 PLADs was above 75%. The result was most sensitive to the symptomatic influenza rate among children under 5 years [ICER ranging from − 25,612 (cost-saving) to 14,532 USD per QALY gained]. The ICER of the fully-funded policy was substantially lower (becoming cost-saving) if the indirect effects of vaccination were considered.ConclusionsIntroducing a government-funded influenza policy for children is cost-effective in China nationally and in many PLADs. PLADs with high symptomatic influenza rate and influenza-associated mortality would benefit the most from a government-funded influenza vaccination program.

The Initial Impacts of the COVID-19 Pandemic on Regional Economies in Indonesia: Structural Changes and Regional Income Inequality

The COVID-19 pandemic has exerted an enormous impact on the Indonesian economy. In 2020, the country’s economy contracted by 2.7%. However, the impact has been spatially heterogeneous. Based on provincial GDP across industrial sectors, this study examines how structural changes caused by the pandemic have affected the determinants of inter-provincial inequality in Indonesia by conducting a bi-dimensional inequality decomposition analysis. According to the bi-dimensional decomposition analysis, after the outbreak of COVID-19, the tourism sector reduced its contribution to inter-provincial inequality. On the other hand, the IC and financial services sectors were not affected by the pandemic and raised their contributions. When Indonesia recovers from the pandemic, it is likely that the tourism sector will regain its position as an important determinant of inter-provincial inequality. However, the most important sectors in determining inter-provincial inequality will be the IC, financial, and business services sectors, particularly in the Java–Bali region. With the rapid advancement of IC, financial, and e-business technologies, the roles of these high-inequality sectors are likely to increase unless policies that could facilitate spatial dispersion of these services and activities are implemented.

Does green investment reduce carbon emissions? New evidence from partially linear functional-coefficient models

Green investment (GI) has great potential to reach China's 'double carbon' target. However, it is still unknown what factors will govern the impact of GI on carbon emissions. This research relaxes the homogeneity and linearity assumed in traditional empirical models and adopts a newly developed partially linear functional-coefficient model to estimate the specific response function of GI on carbon emissions under regional heterogeneity. The results indicate that the role of GI plays a relatively greater role in the western and central regions than in the eastern regions. This highlights the latecomer advantage of the central and western regions under the 'double carbon' target. The beneficial effect of GI on carbon emission intensity is only apparent once the province's economic development level exceeds a certain threshold. For provinces with low GDP per capita, it is recommended to prioritize economic development. When the logarithm of the province's GDP per capita is higher than 9.70, we encourage strong GI. As the industrial structure continues to upgrade, the marginal effect of GI on carbon emissions will continue to increase after a key inflection point.

Provincial waste generation prediction using evolutionary-based neuro-fuzzy model: A South Africa case study

The accurate prediction of waste generation at the provincial level is essential for effective waste management planning in South Africa. However, the complex and uncertain nature of waste generation patterns poses significant challenges for policymakers and waste management authorities. Existing prediction models often overlook the intricate relationships between various factors influencing waste generation. Therefore, there is a need to develop an advanced predictive model that integrates evolutionary algorithms and neuro-fuzzy systems to provide reliable and comprehensive waste generation predictions. In this study, adaptive neuro-fuzzy inference system (ANFIS) model with two evolutionary algorithms namely particle swarm optimization (PSO) and genetic algorithm (GA) were developed to predict the provincial waste quantities generated using South Africa as a case study. Relevant demographic and economic variables of nine provinces in South Africa namely population, provincial GDP, household number and employment data were set of input variables while the waste quantity generated was set as output variable. The fuzzy c-means (FCM) clustering technique developed the fuzzy inference system based on its speed boost capability. Hyper-parameters setting of the FCM-clustered neuro-fuzzy model in a range of 2–7 clusters was tested. The models’ accuracy was evaluated using known statistical metrics like root mean square error (RMSE), Average Absolute Percentage Relative Error (AAPRE), mean absolute deviation (MAD), and co-efficient of determination (R2). The most accurate model is the FCM-ANFIS-GA with 5-clusters giving RMSE, AAPRE, MAD and R2-values of 0.7335, 0.3656, 7.3359 and 0.9986 at the training phase and 0.8041, 0.3291, 8.1467 and 0.9962 at the testing phase. The developed model would assist in sustainable waste management and would be beneficial to South African Waste Information Center (SAWIC) and other countries.

Temporal and Spatial Analysis of the Changes in the Supply of Ecological Products in State-Owned Forest Farms after the Reform

To reveal the changes in the supply efficiency of forest farm ecological products after the reform of state-owned forest farms, this study uses the ecological product accounting method to calculate the physical quantity and value of state-owned forest farm ecological products using data from 2015 and 2020. Through exploratory spatial data analysis, the spatial distribution of the supply efficiency of ecological products of state-owned forest farms and its primary index are studied to explore the temporal and spatial evolution of ecological products from state-owned forest farms in China. The results show the following: (1) Through the reform of state-owned forest farms, the supply capacity of forest farms’ ecological products has been greatly improved, and the physical quantity and value quantity of ecological products have shown an increasing trend, with growth rates of 31.7% and 24.2%, respectively. (2) There is strong spatial heterogeneity in the supply efficiency of ecological products from state-owned forest farms in various provinces, and the overall distribution pattern is gradually decreasing from the northwest to the southeast coastal provinces. (3) There is a negative correlation between the supply capacity of ecological products and provincial GDP. The supply capacity of ecological products in provinces with high per capita GDP is relatively low. (4) The comprehensive index of the supply efficiency of ecological products and its first-level index of state-owned forest farms are characterized by different degrees of agglomeration in space, which are mainly represented by three distribution modes: “H–H”, “L–L”, and “L–H”. Therefore, it is necessary to clarify the ecological function orientation of state-owned forest farms, improve the endogenous power of ecological product supply, actively explore and connect social ecological needs, and achieve coordinated progress in terms of ecological environmental protection and economic development.

The influence of institutional pressure on target setting

We examine whether the desire to maintain sociopolitical legitimacy with critical stakeholders affects sales targets set by Chinese firms. Drawing from institutional theory, we argue that enterprises owned by local government (local-SOEs) feel greater pressure to maintain their legitimacy with the local government relative to private firms (non-SOEs), leading to a stronger association between the provincial GDP target (a legitimate benchmark) and firm-level targets. Results from manually collected data support this conjecture and are robust to alternate measures and samples. Increases in the demand for legitimacy -- measured using exogenous shocks and sample characteristics -- strengthen the association. Finally, changes in the coverage in the official press and changes in target achievement rates document the real effects of this strategy. Our findings demonstrate the effects of institutional pressures on corporate decisions and enrich our understanding on the socially constructed as well as instrumental rationality role of management accounting.

Rural banking spatial competition and stability

This study empirically examined the spatial competition and stability of rural banks. Using detailed quarter-balanced panel bank-level data on rural banks in Indonesia, this study investigated spatial competition and bank stability using a spatial autoregressive model (SAR) constructed by weight matrices based on the inverse distance between a bank and its neighboring banks to measure market power using the adjusted-Lerner index. The significant characteristics of rural banks were discussed, and a unique dataset was used, such as provincial GDP, inflation, and forex. The results showed that banks exerted some pricing power with an existing inverted U-shaped relationship, which was consistent with the monopolistically competitive structure of the industry. This supported the competition-fragility hypothesis. In addition, the evidence showed that bank stability increased with a decrease in the stability of neighboring banks.

The Determinants of Profitability in the City Commercial Banks: Case of China

This study uses a panel data regression model to investigate how internal and external factors affect the profitability of city commercial banks in China. The research sample consists of 16 listed city commercial banks with an unbalanced dataset covering the time period within the period of 2008–2020. A panel data regression method is utilized to investigate the factors that influence the profitability of city commercial banks in China. There are several estimation methods in panel data, and the most commonly employed models are the fixed effects and random effects models. The pooled OLS model is often used for comparison for panel data regression, and the appropriate model will be determined by statistical hypothesis testing. The results show that internal explanatory variables such as bank size, capital adequacy, credit quality, and operating efficiency and external explanatory variables such as province GDP and inflation have a significant impact on the profitability of city commercial banks, while liquidity has no significant effect on the bank’s profitability. The paper contributes to the relevant literature by identifying the determinants of city commercial banks’ profitability considering the latest situation of the banking sector in China and provides practical implications from the perspective of improving bank profitability, which are important for both banking management and regulators and for the municipal and state.

Accounting for ecosystem services and asset value: pilot accounts for KwaZulu-Natal, South Africa

Pilot monetary ecosystem accounts were compiled for KwaZulu-Natal Province, South Africa, in order to highlight any data, methodological or process issues in their compilation and to contribute towards charting a strategy for ecosystem accounting. The Province is highly diverse, with eight biomes, large proportions under communal, private and state tenure, globally important biodiversity, variable landscape condition and encompassing catchment areas of nine river systems. We accounted for the supply and use of wild biomass, reared animal production, cultivation (including silviculture), nature-based tourism, property value, carbon storage and sequestration, pollination, flow regulation (maintenance of base flows), sediment retention, water quality amelioration and flood attenuation. For each ecosystem service, we devised conceptually valid methods that were suitable for the existing data to produce values consistent with the System of National Accounts. These were then summed to estimate total annual flows from each 100 x 100 m spatial unit and its asset value. Challenges encountered included lack of data on small-scale and subsistence production, mismatches in the classification of landcover and government production statistics, unreliable measures of ecosystem condition, the large scale of hydrological modelling and lack of centralised data organisation relating to hydrological services. There was heavy reliance on past empirical research and on global datasets. The combined value of the annual flow of the ecosystem services valued was R52.5 billion in 2011, equivalent to 12% of the provincial GDP. However, the values of many of the services have decreased over the accounting period, due to a combination of changes in demand and ecosystem condition. Asset value was undermined to some extent by unsustainable use of provisioning services. Some areas will require careful messaging, particularly in regard to the contentious issue of valuing carbon retention and the use of exchange values rather than welfare values that are used in economic analysis.

An overview study on management and implementation of WEEE in China.

Waste electrical and electronic equipment (WEEE) which contains various valuable and harmful materials is an inevitable waste in modern society. In order to resolve the pollution problems associated with WEEE treatment, a WEEE management system has been established in China. The main role of importers and manufacturers of electrical and electronic equipment (EEE) is to pay the treatment fees to facilitate the WEEE recycling in China. The announced treatment and subsidy fee is given by set, not by the weight of WEEE. There is no lesser green treatment fee for the producers which can produce environmentally friendly EEE in China. Also, the recovery of refrigerants from the foaming agent of refrigerators is not required in China. In total, 45 million sets of recycled WEEE were certified in 2020, a year that contains the most updated data. Among them, 48%, 14%, 20%, 10% and 8% are for TV, refrigerator, washing machine, computer and air conditioners, respectively. The spatial analysis indicates that the WEEE recycling activities are mainly concentrated on the mid-east and east regions of China. It also can be concluded that the certified amount of each province has higher positive correlation with provincial population than provincial GDP per capita and green recovery rate. It also clearly notes that the amount of recycled air conditioner is the lowest for each province. Thus, more effort should be conducted to increase the recycling of scrapped air conditioner in China.

China's unconventional carbon emissions trading market: The impact of a rate-based cap in the power generation sector

China has launched a national level carbon emissions trading market with a rate-based cap and benchmarks in the power generation sector. This emissions trading system (ETS) differs from a mass-based one, which lacks an absolute carbon cap. This study assesses the impact of such an unconventional ETS on economic development, carbon emission mitigation, and power system transition by applying a multi-regional dynamic computable general equilibrium model. The results show that ETS can facilitate the decarbonisation of the power sector and reduce carbon intensities of coal and gas power, the two technologies covered at the first stage of China's ETS. Furthermore, power generation of these technologies will be decreased significantly, and a noticeable fallback of electrification will occur. National GDP loss under a rate-based cap is slightly higher than the one under a mass-based cap, while provincial GDP losses have close relations with coal phaseout and permit scarcity.

Performance-Based Authoritarianism Revisited: GDP Growth and the Political Fortunes of China’s Provincial Leaders

An influential performance-based authoritarianism thesis attributes China’s reform-era economic success to merit-based political selection whereby the ruling Chinese Communist Party (CCP) has persistently rewarded with career advancement local leaders overseeing fast GDP growth. Yet voluminous empirical research on whether boosting local economic growth has bestowed career advantages on provincial leaders remains inconclusive due to the assumption of static preferences of the national leadership for unbridled GDP growth and inconsistency in data measurement in studies with disparate time coverage. Employing annual individual-level data consistently coded with a general measure of career mobility and a rigorous measure of relative economic performance, I reexamine how provincial GDP growth affected the career outcomes of the governors and provincial party secretaries under different CCP national chiefs spanning the entire reform era. My findings challenge the sweeping, one-sided conventional wisdom and call for greater attention to shifting political and economic contexts in theoretical and empirical research on contemporary China.

The Economic Loss Prediction of Flooding Based on Machine Learning and the Input-Output Model

As climate change becomes increasingly widespread, rapid, and intense, the frequency of heavy rainfall and floods continues to increase. This article establishes a prediction system using feature sets with multiple data dimensions, including meteorological data and socio-economic data. Based on data of historical floods in 31 provinces and municipalities in China from 2006 to 2018, five machine learning methods are compared to predict the direct economic losses. Among them, GBR performs the best with a goodness-of-fit of 90%. Combined with the input-output (IO) model, the indirect economic losses of agriculture to other sectors are calculated, and the total economic losses caused by floods can be predicted effectively by using the GBR-IO model. The model has a strong generalization ability with a minimum requirement of 80 pieces of data. The results of the data show that in China, provinces heavily reliant on agriculture suffered the most with the proportion of direct economic losses to provincial GDP exceeding 1‰. Therefore, some policy implications are provided to assist the government to take timely pre-disaster preventive measures and conduct post-disaster risk management, thereby reducing the economic losses caused by floods.