Annual GDP Research Articles

The Impact of Asset-Liability Management on the Profitability of Listed Commercial Banks in Vietnam

This paper investigates the effect of asset-liability management on the profitability of listed commercial banks in Vietnam, analyzing annual data from 2013 to 2023. The study uses VIF tests, Heteroskedasticity tests, Model Specification tests, and the Generalized Least Squares (GLS) model with the Modified Wald test to examine the data. The results reveal a positive correlation between bank asset management and annual GDP growth with profitability. Conversely, liability management and the year-on-year growth rate of total assets negatively impact profitability. Specifically, factors such as loans and advances, investments in securities on the asset side, and deposits and borrowings from other credit institutions, along with customer deposits on the liability side, are significant. Lending activities, in particular, are identified as key drivers of financial performance in the Vietnamese banking sector. However, the minimal impact of investment securities on profitability raises questions, given their traditionally significant role in banking profitability strategies globally. The study also highlights the negative effects of certain liabilities on bank profitability, stressing the need for careful liability management for banks in Vietnam. While GDP growth is generally linked with economic prosperity and financial sector growth, its impact on bank profitability in Vietnam appears limited, suggesting that other factors might play a more significant role.

BRICS and G7: Global Competition

The goals and policies of the BRICS contradict the policy of the unipolar world, which perpetuates the dependence of developing countries on highly developed countries. This fact makes the BRICS and G7 international associations direct competitors with mutually opposite goals and interests. In such a formulation of the issue, strengthening and increasing the competitiveness of one integration association should lead to weakening and reducing the competitiveness of another integration association. Recently, the size of countries and the size of their populations have not been considered key factors in their competitiveness. However, if we talk about the BRICS member countries, they use these two advantages as a basis for economic growth. The area of the territory of the BRICS countries was 1.85 times the area of the G7, and the population was more than 4 times as of the end of 2022. The current trend towards the entry of new member countries into the BRICS should lead to an even greater advantage in these indicators. The economic growth of the BRICS countries is based on the use of resources and investments, while the economic growth of the G7 countries is based on accumulated wealth, military and political influence in the world. A comparison of the two integration associations in terms of real GDP growth PPP shows that the annual GDP growth of the BRICS countries exceeds the GDP growth of the G7 countries. In addition, the real GDP growth of the BRICS countries is outpacing the growth of global GDP. Key indicators characterizing the size and pace of economic growth indicate the potential for further development of the BRICS and strengthening its competition with the G7 integration bloc. The BRICS countries have shown good economic growth rates even despite the external and internal challenges associated with the crisis in the global economy and numerous economic sanctions. At the same time, the economic development of the BRICS countries is not only quantitative, but also qualitative. Unlike the G7, it is based on the formation and expansion of a free trade system within the integration bloc and the formation of economic institutions that allow overcoming trade barriers between the countries of the association, as well as increasing investment through the New Development Bank created within the BRICS. The success of development and interaction of countries within BRICS attracts new member countries. In 2024, four more countries joined the BRICS bloc, such as Iran, the United Arab Emirates, Egypt and Ethiopia, and currently many more countries are taking the initiative and wish to become members of the integration association. However, competition in the Challenger-Leader format, in addition to incentives for economic growth on the basis of fair competition, simultaneously creates incentives for mutual economic, political and military blocking of the development of countries of the competing bloc, which creates great risks of slowing down global economic development in the future.

Disaggregation and Nowcasting of Regional GDP Series with a Simple Smoothing Algorithm

We propose a simple smoothing method for the spatiotemporal disaggregation of economic time series. Contrary to the existing methods, our approach does not require exogenous regressors and can therefore be used for countries lacking long and reliable series of regional economic indicators. The proposed method can also be applied sequentially, implying that one needs to revise only the estimates for the last low-frequency period when new data are disaggregated. This is a convenient feature when historical estimates are of interest. We apply this method to disaggregate annual real GDP data for Polish regions into quarterly series and compare the results with the series obtained from a multivariate linear regression-based procedure, considering the differences between the estimates and the consequences for regional recession dating. We also examine the nowcasting performance of the smoothing algorithm and find that it is superior to the regression-based alternative for most of the studied sample lengths and horizons up to a year.

Relationship between Public Expenditure and Inflation

Effective management of inflation remains one of the arduous tasks for managers of global economies. Inflation remains a macroeconomic indicator whose management outcomes have the potential to decide the electoral fortunes of elected governments and determine the purchasing power of household incomes. The purpose of this research was to assess how a steady increase in public expenditure could impact inflationary levels. The quantitative approach to scientific inquiry was adapted and used in the research. Specifically, the cross-sectional design formed the basis of the research. Data required for the research were obtained mainly from secondary sources. These included textbooks, peer-reviewed articles published in journals and grey literature. Other sources were Google Search Engine, including Netcials, MacroTrends, and databases of the World Bank and Bank of Ghana, among other significant sources. Respective data on Ghana’s annual GDP values from 1960 through 2020, annual inflation data from 1965 through 2020, changes in annual inflation rates from 1965 through 2020, and annual public expenditure values from 1983 through 2020 were collected and used in the research. Descriptive statistics and regression models were used to describe the research variables and to evaluate their behaviour over the stated time frame on inflation. The study revealed lax monetary policy as the root cause of consistently high inflationary rates over considerable periods and remained a strong contributor to the weak purchasing power of national fiat currencies. Further, relative price distortions away from their economic equilibrium are not healthy for the economy, while disinflationary policies adapted for implementation should be contingent on the causes of inflation. The single largest cost of inflation to consumers is the erosion of income, whereas higher tax rates are not the panacea for the challenges of mounting public expenditure and public debts. Respective inflation rates recorded in Ghana during 2012 (7.13%) and 1995 (59.46%) remained the lowest and highest from 1993 through 2020. Fiscal periods 2017 through 2020, 2009 through 2012, and 2005 through 2008 recorded the respective best (9.33%), second-best (11.46%) and third-best (13.32%) annual average inflation rates. With the exception of 2013 through 2016, the performance of the Ghanaian economy in relation to annual average inflationary control witnessed improvements during the second political and administrative terms compared to the first terms. However, the best annual average inflation rate over an eight-year period during the Fourth Republic was recorded from 2009 through 2016 (13.45%). Findings from the research revealed a positive and significant relationship between public expenditure and inflation (coefficient value = 1.2004653; p = 0.004, p < 0.05). Public expenditure accounted for 21.30% of the variation in inflation rate from 1983 through 2020. Results from the statistical output validated the significant influence of public expenditure on inflationary hikes, the need for monetary and fiscal policies related to inflation control to be strategically reviewed and strengthened to improve implementation outcomes, and the potential of rising public expenditure to undermine the rigidity and robustness of economic fundamentals through an unexpected surge in inflationary levels. The findings underscored the need for managers of various global economies to be keen on “economic” public expenditure to the neglect of profligate public expenditure, so the socio-economic derivatives from investments in public infrastructure would strongly add to, rather than subtract from, national development and growth efforts. The fundamental objective of MPC should be pivoted around three cardinal functions: the creation of maximum employment, moderation of long-term interest rates and ensuring price stability. Excessive public expenditure requires careful consideration by economies that whet their national development appetite with increased public infrastructure projects.

The global macroeconomic burden of Alzheimer's disease and other dementias: estimates and projections for 152 countries or territories

Alzheimer's disease and other dementias (ADODs) severely threaten the wellbeing of older people, their families, and communities, especially with projected exponential growth. Understanding the macroeconomic implications of ADODs for policy making is essential but under-researched. We used a health-augmented macroeconomic model to calculate the macroeconomic burden of ADODs for 152 countries or territories, accounting for: the effect on labour supply of reduced working hours of informal caregivers; the effect on labour supply of ADODs-related mortality and morbidity; age-sex-specific differences in education, work experience, labour market participations, and informal caregivers; and treatment and formal care costs diverting from savings and investments. ADODs will cost the world economy 14 513 billion international dollars (INT$, measured in the base year 2020; 95% uncertainty interval [UI] 12 106-17 778) from 2020 to 2050, equivalent to 0·421% (95% UI 0·351-0·515) of annual global GDP. Japan incurs the largest annual GDP loss at 1·463% (1·225-1·790). China (INT$2961 billion [2507-3564]), the USA (INT$2331 billion [1989-2829]), and Japan (INT$1758 billion [1471-2150]) face the largest absolute economic burdens. The economic burden of informal care ranges from 60·97% in high-income countries to 85·45% in lower-middle-income countries, and treatment and formal care costs range from 10·50% in lower-middle-income countries to 30·80% in high-income countries. The macroeconomic burden of ADODs is substantial and unequally distributed across countries and regions. Global efforts to reduce the burden, especially with regard to informal care, are urgently needed. National Institute on Aging, National Institutes of Health; Chinese Academy of Engineering; Chinese Academy of Medical Sciences; Bill & Melinda Gates Foundation; Davos Alzheimer's Collaborative through Data for Decisions.

The global cost of international commitments on land restoration

AbstractLand restoration and sustainable land management projects have now been proposed for up to a billion hectares globally, responding to continuous land degradation processes. But, a lack of reliable cost estimates hinders implementation, which results in a high perceived risk of restoration investments. This study addresses this gap, using cost data from 243 restoration projects from multiple sources to estimate the cost ranges for different types of restoration more precisely. The analysis shows median restoration costs vary from 185 $US/ha to 3012 $US/ha depending on the restoration measure, implying current global land restoration commitment cost 0.04%–0.27% of annual global GDP to implement. Since the majority of these commitments are made by developing countries, international cost‐sharing mechanisms, through climate or private finance, are required to move from goal setting to implementation.

Exploring the impact of auditor industry specialization on income smoothing

Since the late 1970s’ reform and opening-up, China’s economy has achieved remarkable success, maintaining an average annual GDP growth of 9.7% from 1978 to 2006. In 2007, China achieved a GDP of 3.38 trillion USD, surpassing Germany to become the world’s third-largest economy, and by the second quarter of 2010, it had become the second-largest economy globally. These developments have attracted international investors’ attention to Chinese equities. However, China’s poor reputation for corporate governance may deter investors, despite their positive outlook on China’s economy. Corporate managers in China are known to engage in income smoothing, taking actions to dampen fluctuations in their firms’ publicly reported net income. In 2004, the OECD proposed that a strong disclosure regime promoting real transparency can help attract capital and maintain confidence in the capital market, with income smoothing being a key concern for both institutional and individual investors. This study investigates how auditor industry specialization (AIS) affects income smoothing behavior in Chinese listed companies. Using a sample of 27,208 firm-year observations from 2006 to 2018 collected from the Taiwan Economic Journal Database, the results indicate that AIS is negatively related to managers’ income smoothing behavior, underscoring the importance of industry expertise in mitigating such practices. Additionally, an independent t-test highlights the difference between Big Four and non-Big Four auditors in influencing client companies’ income smoothing behaviors. The study further demonstrates the significant moderating effect of Big Four auditors on the relationship between accounting firms with top industry expertise and client companies’ income smoothing, reflecting the unique characteristics of the Chinese market. This study verifies the suppressive effect of AIS on firms’ income smoothing and indirectly suggests that governments (or the Chinese Institute of Certified Public Accountants, CICPA) should regularly disclose accounting firms/auditors with industry expertise publicly. This regime can help global investors make informed investment decisions.

Analyzing the Threshold Impact of Public Debt on Economic Growth: an Investigation of the New Member States within the European Union

This paper aims to analyze the impact of public debt on economic growth in eleven EU new member states (NMS) from Central and South-Eastern Europe for the period 2000-2019. More specifically, we investigate if there is evidence of a non-linear (quadratic) relationship in this group of countries. Having in mind different economic and financial development, historical connections, and geographical proximity, we split them into three more homogenous groups: Balkan countries (BAL-4), Baltic countries (B-3), and Visegrad countries (VIS-4). The results of our study in all models indicate a statistically significant non-linear impact of public debt ratios on annual GDP per capita growth rates. The results across all models show a significant non-linear impact of public debt ratios on annual GDP per capita growth rates. Further, the calculated debt-to-GDP turning point, where the positive effect of accumulated public debt inverts into a negative effect, is roughly between 42.7%-58% of GDP, dependent on which sub-group we have analyzed. In general, the research may contribute to a better understanding of the problem of high public debt and its effect on economic activity in the new EU.

Compound hazard mapping for tropical cyclone-induced concurrent wind and rainfall extremes over India

India is the worst affected region in the world by tropical cyclones (TCs), causing an average 2% annual GDP loss. TCs instigate many other natural hazards that have a compounding effect on the adversely affected population and present significant challenges to the resilience of emergency response systems and infrastructure. Hence, any risk assessment on TC is inherently multivariate/compound in nature. This study investigates co-occurring wind and rainfall extremes during TCs across India (1979–2020) using a novel quasi-Lagrangian approach, focusing on location-specific hazards. Eastern coastal states and adjacent inland areas experience the highest frequency (≥10 cyclones in 40 years) of concurrent extremes (wind gusts ≥ 16 m/s and rainfall ≥ 18 mm/h). Whereas duration-wise, the eastern coastal states and Gujarat state experience frequent concurrent extremes lasting more than a day annually, with the Krishna–Godavari delta region particularly vulnerable to highly severe events (duration of concurrent extremes ≥ 24 h). This study provides a high-resolution cartographic product of compound hazard from TC-induced extremes for the first time over the entire India, highlighting regional heterogeneity and aiding targeted national-level risk mitigation and adaptation planning.

Analysis of Landscape Pattern Evolution and Impact Factors in the Mainstream Basin of the Tarim River from 1980 to 2020

The mainstream basin of the Tarim River serves as a vital ecological security barrier that prevents the merging and expansion of deserts and an important strategic corridor directly linking Qinghai and Xinjiang. With society’s development and climate change, ecological issues such as river interruption, vegetation degradation, and land desertification in the basin have notably intensified, and the ecological security is facing a critical test. Exploring the characteristics of landscape changes and their driving factors within the basin is crucial in improving the ecological environment system’s management. Based on land use data from 1980 to 2020, this study analyzed the characteristics of the spatiotemporal changes and pattern evolution of the landscape through a landscape transfer matrix and landscape pattern indices. It further revealed the impact factors of the landscape pattern through canonical correspondence analysis. The results showed that (1) in 1980–2020, the areas of desert, forest, farmland, and settlement landscapes increased, while the area of grassland landscape decreased, and the water landscape showed an “increasing–decreasing–recovery” pattern. The landscape transition types mainly included the transition from grassland to desert; mutual transitions among farmland, grassland, and forests; mutual transitions between water and grassland; and the transition from farmland to settlements. (2) The overall landscape pattern demonstrated increased fragmentation, shape complexity, and evenness with decreased aggregation. Furthermore, different landscapes exhibited distinct characteristics of landscape pattern changes; for instance, grassland landscape showed severe fragmentation, while desert landscape displayed the strongest dominance. (3) The landscape pattern was a result of the combined impact of natural and human factors, with the soil thickness (SOT), road density (ROD), annual actual evapotranspiration (AAE), population density (POD), and mean annual temperature (MAT) exhibiting significant influences. Specifically, the settlement and farmland landscapes were mainly influenced by the mean annual relative humidity (MAH), POD, GDP density (GDP), and distance to artificial water (DAW); the forest, grassland, and water landscapes were mainly influenced by the SOT, soil organic matter content (SOM), AAE, ROD, elevation (ELE), MAT, slope (SLP), and distance to natural water (DNW); and the desert landscape was mainly influenced by the DAW, DNW, SLP, AAE, SOT, SOM, and ROD. These findings can provide a scientific reference for landscape management and restoration, as well as sustainable social and economic development, in the mainstream basin of the Tarim River.

Revisiting the resource curse: Does volatility matter?

AbstractCountries with abundant natural resources often possess greater wealth, yet the impact of these resources on economic growth remains unclear. This paper examines how natural‐resource abundance and its volatility impact economic growth. It questions whether natural resources themselves are a curse or if the negative growth effects are due to the volatility of natural‐resource revenues. The study also investigates how volatility of natural resources affects key economic growth channels, such as investment, human capital, and institutional quality. Using the standard panel model and panel smooth transition regression (PSTR), the paper analyzes data from 125 countries (1988–2020). Results show that natural‐resource abundance boosts economic growth, contradicting the resource‐curse theory. However, the growth impact is non‐linear and varies with natural‐resource volatility. Countries with high volatility face up to a 22 percentage point annual GDP growth loss compared with those with low volatility, suggesting that volatility and poor government responses drive the resource‐curse paradox, not the abundance of resources per se.

Study on the Constraints and Practical Knowledge for Intensive Dairy Cattle Farming in Mongolia

The given text highlights the importance of managing the intensive farming of Mongolian dairy cattle effectively to improve the quality of dairy products and promote the livestock industry's comprehensive development. The livestock industry is a crucial pillar of Mongolia's economy, contributing about 12% to the annual GDP. However, Mongolia's dairy industry has not been fully developed, and there has been a significant increase in the quality and demand for dairy products in recent years due to urbanization. The text also discusses the challenges faced by Mongolian livestock farming, such as the extensive farming practices, harsh winters, and lack of management and planning. The author suggests standardizing the standards for large-scale ranch management operations and practical operations of modern ranch management systems to enhance the livestock industry's intensification, scaling, organization, socialization, and industrialization. The text also highlights the need to improve the management level of breeders, plan the construction of breeding farms rationally, strengthen the inspection efforts of relevant departments, and enhance technical research to address the problems existing in intensive management. Overall, the text provides a comprehensive study on developing the livestock industry and promoting the healthy and sustainable development of the livestock economy.

Analysis and Forecasting of Energy Data and GDP Based on Pearson Correlation Analysis-Random Forest Algorithm

The relationship between energy data and GDP is an important economic issue because energy is the foundation that supports modern economic development. This paper examines the relationship between energy data and GDP and uses Pearson correlation analysis to calculate the relationship between each variable in energy data and annual GDP for 52 regions. The results show that total electricity consumption is the factor with the highest degree of influence on GDP, followed by natural gas consumption, biomass consumption, hydroelectricity consumption, LPG consumption and geothermal energy consumption. This indicates that there is an extremely strong correlation between local energy data and GDP. To further explore this correlation, this paper attempts to predict the GDP of the locality based on the local energy data using a machine learning approach.The Random Forest algorithm is chosen as the machine learning model, and the training, validation and test sets are divided according to the ratio of 6:2:2. By using MSE, RMSE, MAE, MAPE and R to evaluate the model, it is found that the random forest machine learning algorithm can predict the local GDP well.The predicted value of GDP and the actual value of GDP are very close to each other, meanwhile, the value of MSE is 62.779.These findings show that the local energy data are closely related to economic development. The impact of energy factors on the economy should be taken into account when formulating economic policies. In addition, machine learning algorithms can provide strong support for economic forecasting and provide more accurate information for decision makers.

Can the military be a better manager of the economy?

AbstractPakistan has struggled for a political system suitable for its postindependence development; however, repeated struggles between democracy and dictatorship have slowed Pakistan's economic growth. I quantified the impact of military dictatorship on Pakistan's economy from 1999 to 2008 using synthetic control methods. I found that while the average annual GDP per capita growth grew during the military dictatorship, it was four times lower than synthetic Pakistan's. I conclude that the military did not help Pakistan with its economic malaise. The increase in military expenditure and the prevalence of terrorism due to the military dictatorship may have hindered Pakistan's economic growth.

Analysis of Interprovincial Trade Relationships Based on Improved Gravity Modeling

This paper analyzes the inter-provincial trade flows estimated by the improved gravity model using the complex network method. The article collects the distance and annual GDP value of each province from Baidu map and China Statistical Yearbook, and uses the gravity model to estimate the inter-provincial trade flow. Considering that the inter-provincial trade in the current year may be related to the GDP value of the previous year, the original model is improved by introducing the Gi-1 index and the results are normalized by multiplying them by 100 as the weights of the network constructed, and a fully connected network is established with the name of each province as a node connected network, and do the analysis of the network's node strength, weighted tight centrality, weight entropy of the three indicators, while using spectral clustering to further explore the trade relationship between the provinces.

The change of renewable energy and zero-carbon economy in an anthropogenically warming climate

Anthropogenetic global warming has led to increasingly significant environmental issues, biodiversity losses, and socioeconomic impacts. There is a rising demand for transition from fossil fuels to renewable energy (RE), reducing carbon emissions, and thus realizing zero-carbon economy. Nevertheless, it remains a challenge to achieve the carbon-free economy and mitigate global warming, without fully understanding the ongoing RE development. The major objectives of this research are to (1) investigate the changes of different RE types compared with fossil fuels in the U.S., U.K., Mexico, Canada, and China; (2) examine the relationships between RE, temperature anomalies, and GDP; and (3) propose potential strategies for zero-carbon economy and climate change. The annual mean energy, temperature, and GDP data in these five selected countries during 1980 to 2021 are collected for analysis, and their relation-ships are addressed through Pearson's correlation analysis, along with significance test. The results suggest an increasing trend of RE and rising RE-fossil fuels ratio during the past four decades. All five countries either showed exponential or linear increasing trends in GDP and RE. The correlation analysis suggests a significantly positive correlation between RE and GDP in both countries. For example, different from the U.S., the synchronized growth in RE and fossil fuels in China leads to a significantly positive correlation between these two. All five countries provide their unique data of renewable development, which can stimulate the research and enable further study. This study will shed light over possible strategic plans for an optimized use of renewable energy, ensuring below 1.5C temperature rise, and reaching carbon neutrality by 2050.

A study of the attenuation stage of a global infectious disease.

Differences in control measures and response speeds between regions may be responsible for the differences in the number of infections of global infectious diseases. Therefore, this article aims to examine the decay stage of global infectious diseases. We demonstrate our method by considering the first wave of the COVID-19 epidemic in 2020. We introduce the concept of the attenuation rate into the varying coefficient SEIR model to measure the effect of different cities on epidemic control, and make inferences through the integrated adjusted Kalman filter algorithm. We applied the varying coefficient SEIR model to 136 cities in China where the total number of confirmed cases exceeded 20 after the implementation of control measures and analyzed the relationship between the estimated attenuation rate and local factors. Subsequent analysis and inference results show that the attenuation rate is significantly related to the local annual GDP and the longitude and latitude of a city or a region. We also apply the varying coefficient SEIR model to other regions outside China. We find that the fitting curve of the average daily number of new confirmed cases simulated by the variable coefficient SEIR model is consistent with the real data. The results show that the cities with better economic development are able to control the epidemic more effectively to a certain extent. On the other hand, geographical location also affected the effectiveness of regional epidemic control. In addition, through the results of attenuation rate analysis, we conclude that China and South Korea have achieved good results in controlling the epidemic in 2020.

Socio-Economic Development of Tibet in the 11th Five-Year Plan (2006–2010). Part 9

The 11th Five-year Plan of the People's Republic of China was an important stage in the socio-economic development of both the whole of China and the TAR in its composition. The plan set an annual GDP growth rate of 7.5 %, which actually exceeded 10 %. Tibet, on the other hand, was developing at a rate of more than 12 % per year. During the five-year plan, Tibet experienced many serious trials: a series of powerful earthquakes that claimed thousands of lives. In 2008, when China was preparing to host the Olympic Games in Beijing in August, Western intelligence agencies provoked an uprising in Lhasa on March 18. The leaders of France (in 2008) and the United States (in 2010) distinguished themselves by provocations against China, meeting with the Dalai Lama, despite the vigorous objections of the Chinese authorities. Nevertheless, Britain officially recognized Tibet for the first time as an autonomous region within the PRC. Significant achievements have been made in the development of transport in the region and especially aviation. Tibet remained one of the twelve least developed western regions of the People's Republic of China, but its economy continued to develop dynamically. The authority of Tibet in the world community has significantly increased, one of the manifestations of this was the great success of Tibet at the world Exhibition in Shanghai in 2010.

Mathematical Models of Migration Balance and Migration Attitudes in Armenia

The purpose of the study is to provide a quantitative explanation of the migration balance and migration attitudes in Armenian society. A linear regression model has been constructed to explain the dependence of the migration balance on variables at the macro level, including annual GDP growth, the internal and external political state of Armenia. Data from the Armenian Statistical Service on statistics of border movements and annual GDP growth were used. The foreign policy state is represented by a variable taking the values “Truce”, “War”, and “Intense War”. The internal political state is represented by a variable taking the values “Open conflict”, “Latent conflict”, “Balanced”, “Positive expectations”, and “High expectations”. Based on the model, an estimate of the migration balance for 2023 was calculated. According to a sociological survey conducted in November 2022 using the structural modeling method (Structural Equation Modeling), two models were built that explain migration attitudes in society through the socio-economic characteristics of the respondent and characteristics of his political culture, including: the presence of a labor migrant in the family, the age of the respondent, approval of the 2018 revolution in Armenia, the realization of expectations from the revolution, a sense of political competence, political subjectivity and patriotism. The results of the study can be used to forecast the migration balance and migration attitudes in the society, as well as strategic planning and management of migration processes in Armenia.

Modelling the socio-economic impacts of coal-fired electricity phaseout under carbon neutrality target: A dynamic CGE-based study of China

Given its significant carbon emissions, the phaseout of coal-fired electricity emerges as a crucial strategy in achieving the goal of carbon neutrality, which will fundamentally reshape China's social-economic landscape. In this study, a dynamic computable general equilibrium (CGE) model was constructed to evaluate the economic and social ramifications of phasing out coal-fired electricity, encompassing diverse pathway scenarios. The results suggest that the phaseout of coal-fired electricity will significantly influence the socio-economic system compared to the Business as Usual (BAU) scenario. Different phaseout scenarios are projected to yield a cumulative decrease in carbon dioxide emissions ranging from 36.38 to 60.15 Gt between 2020 and 2060. Consequently, there will be a cumulative GDP ranging from 22.22 to 36.29 trillion yuan, accompanied by a cumulative decline in employment affecting 23.68 to 29.92 million individuals. The anticipated trends in annual GDP and job losses are expected to exhibit a U-shaped curve, initially increasing, and then decreasing from 2020 to 2060 compared to the BAU scenario. A distinct trade-off is anticipated to arise between the potential for carbon reduction and the resultant losses in jobs and economic output. The more optimistic scenario, characterized by a lower peak value, an earlier peak time, and a later phaseout time, is projected to result in a relatively lower socioeconomic impact per unit of CO2 emissions reduction. These findings provide policymakers with vital insights, informing the development of strategies for a gradual transition away from coal-fired electricity while minimizing socio-economic repercussions.