Regional economic forecast using Elman neural networks with wavelet function.

Recently, the economy in Guangdong province has ranked first in the country, maintaining a good growth momentum. The prediction of Gross Domestic Product (GDP) for Guangdong province is an important issue. Through predicting the GDP, it is possible to analyze whether the economy in Guangdong province can maintain high-quality growth. Hence, to accurately forecast the economy in Guangdong, this paper proposed an Elman neural network combining with wavelet function. The wavelet function not only stimulates the forecast ability of Elman neural network, but also improves the convergence speed of Elman neural network. Experimental results indicate that our model has good forecast ability of regional economy, and the forecast accuracy reach 0.971. In terms of forecast precision and errors, our model defeats the competitors. Moreover, our model gains advanced forecast results to both individual economic indicator and multiple economic indicators. This means that our model is independently of specific scenarios in regional economic forecast. We also find that the investment in education has a major positive impact on regional economic development in Guangdong province, and the both surges positive correlation. Experimental results also show that our model does not exhibit exponential training time with the augmenting of data volume. Consequently, we propose that our model is suitable for the prediction of large-scale datasets. Additionally, we demonstrate that using wavelet function gains more profits than using complex network architectures in forecast accuracy and training cost. Moreover, using wavelet function can simplify the designs of complexity network architectures, reducing the training parameter of neural networks.

Managing government debt.

To construct a stochastic version of [R. J. Barro, J. Polit. Econ. 87, 940-971 (1979)] normative model of tax rates and debt/GDP dynamics, we add risks and markets for trading them along lines suggested by [K. J. Arrow, Rev. Econ. Stud. 31, 91-96 (1964)] and [R. J. Shiller, Creating Institutions for Managing Society's Largest Economic Risks (OUP, Oxford, 1994)]. These modifications preserve Barro's prescriptions that a government should keep its debt-gross domestic product (GDP) ratio and tax rate constant over time and also prescribe that the government insure its primary surplus risk by selling or buying the same number of shares of a Shiller macro security each period.

Estimation of the lost productivity to the GDP and the national cost of correcting visual impairment from refractive error in Kenya.

BACKGROUND: In developing countries such as Kenya, minimal attention has been directed towards population based studies on uncorrected refractive error (URE). However, the absence of population based studies, warrants utilization of other avenues to showcase to the stakeholders in eye health the worth of addressing URE. Hence this study estimated the lost productivity to the Gross Domestic Product (GDP) as a result of URE and the national cost required to address visual impairment from URE in Kenya. METHODS: The lost productivity to the GDP for the population aged 16-60 years was calculated. Thereafter the productivity loss of the caregivers of severe visual impaired individuals was computed as a product of the average annual productivity for each caregiver and a 5% productivity loss due to visual impairment. The productivity benefit of correcting refractive error was estimated based on the minimum wage for individuals aged between 16-60 years with URE. Estimation of the national cost of addressing URE was based on spectacle provision cost, cost of training functional clinical refractionists and the cost of establishing vision centres. A cost benefit analysis was undertaken based on the national cost estimates and a factor of 3.5 times. RESULTS: The estimated lost productivity to the GDP due to URE in in Kenya is approximately US$ 671,455,575 -US$ 1,044,486,450 annually for population aged between 16-60 years. The productivity loss of caregivers for the severe visually impaired is approximately US$ 13,882,899 annually. Approximately US$ 246,750,000 is required to provide corrective devices, US$ 413,280- US$ 108,262,300 to train clinical refractionists and US$ 39,800,000 to establish vision centres. The productivity benefit of correcting visual impairment is approximately US$ 41,126,400 annually. Finally, a cost benefit analysis showed a return of US$ 378,918,050 for human resources, US$ 863,625,000 for corrective devices and US$ 139,300,000 for establishment of vision centres. CONCLUSION: The magnitude of productivity loss due to URE in Kenya is significant warranting prioritization of refractive error services by the government and all stakeholders since any investment directed towards addressing URE has the potential to contribute a positive return.

Towards a greener future: examining carbon emission dynamics in Asia amid gross domestic product, energy consumption, and trade openness.

The purpose of this study is to examine the impact of gross domestic product, energy consumption, and trade openness on carbon emission in Asia. Among the 48 countries in Asia, 42 were included in the analysis, spanning a period of 20 years. Given that Asia is the predominant contributor, accounting for 53% of global emissions as of 2019, a comprehensive examination at both continental and individual country levels becomes imperative. Such an approach aligns with local, regional, and global development agendas, contributing directly and indirectly to climate change mitigation. The analytical techniques employed in this study encompassed panel regression and multiple linear regression, illuminating the specific contributions of each country to the study variables and their impact on carbon emissions. The findings suggest that gross domestic product (13 out of 42 countries), energy consumption (21 out of 42 countries), and trade openness (eight out of 42 countries) have a highly significant impact (p < 0.01) on carbon emissions in Asia. Energy consumption plays a vital role in increasing carbon emissions in Asia, driven by rising populations, urbanisation, and oil and gas production. Policymakers can take several actions such as adopting a carbon pricing system, using sustainable transportation, renewable energy development, and international cooperation within Asia to reach the goal of being carbon neutral by 2050.

Dynamic nonlinear CO2 emission effects of urbanization routes in the eight most populous countries.

A dynamic STIRPAT model used in the current study is based on panel data from the eight most populous countries from 1975 to 2020, revealing the nonlinear effects of urbanization routes (percentage of total urbanization, percentage of small cities and percentage of large cities) on carbon dioxide (CO2) emissions. Using "Dynamic Display Unrelated Regression (DSUR)" and "Fully Modified Ordinary Least Squares (FMOLS)" regressions, the outcomes reflect that percentage of total urbanization and percentage of small cities have an incremental influence on carbon dioxide emissions. However, square percentage of small cities and square percentage of total urbanization have significant adverse effects on carbon dioxide (CO2) emissions. The positive relationship between the percentage of small cities, percentage of total urbanization and CO2 emissions and the negative relationship between the square percentage of small cities, square percentage of total urbanization and CO2 emissions legitimize the inverted U-shaped EKC hypothesis. The impact of the percentage of large cities on carbon dioxide emissions is significantly negative, while the impact of the square percentage of large cities on carbon dioxide emissions is significantly positive, validating a U-shaped EKC hypothesis. The incremental effect of percentage of small cities and percentage of total urbanization on long-term environmental degradation can provide support for ecological modernization theory. Energy intensity, Gross Domestic Product (GDP), industrial growth and transport infrastructure stimulate long-term CO2 emissions. Country-level findings from the AMG estimator support a U-shaped link between the percentage of small cities and CO2 emissions for each country in the entire panel except the United States. In addition, the Dumitrescu and Hulin causality tests yield a two-way causality between emission of carbon dioxide and squared percentage of total urbanization, between the percentage of the large cities and emission of carbon dioxide, and between energy intensity and emission of carbon dioxide. This study proposes renewable energy options and green city-friendly technologies to improve the environmental quality of urban areas.

The spatiotemporal trend of human brucellosis in China and driving factors using interpretability analysis.

Human brucellosis has reemerged in China, with a distinct change in its geographical distribution. The incidence of human brucellosis has significantly risen in inland regions of China. To gain insights into epidemic characteristics and identify factors influencing the geographic spread of human brucellosis, our study utilized the Extreme Gradient Boosting (XGBoost) algorithm and interpretable machine learning techniques. The results showed a consistent upward trend in the incidence of human brucellosis, with a significant increase of 8.20% from 2004 to 2021 (95% CI: 1.70, 15.10). The northern region continued to face a serious human situation, with a gradual upward trend. Meanwhile, the western and southern regions have experienced a gradual spread of human brucellosis, encompassing all regions of China over the past decade. Further analysis using Shapley Additive Explanations (SHAP) demonstrated that higher Gross Domestic Product (GDP) per capita and increased funding for education have the potential to reduce the spread. Conversely, the expansion of human brucellosis showed a positive correlation with bed availability per 1000 individuals, humidity, railway mileage, and GDP. These findings strongly suggest that socioeconomic factors play a more significant role in the spread of human brucellosis than other factors.

Successive national agricultural policies/programmes, growth of gross domestic product (GDP) and expansion of agribusinesses in Nigeria.

In Sub Saharan Africa, agriculture's contribution to employment and Gross Domestic Product (GDP) is estimated to be higher than other sectors. Policies designed and implemented for the agricultural sector could be an influencing factor to the variations in the contributions of agriculture to the annual national GDP. These policies are believed to have shaped and (some) still shaping the landscape of agriculture and national economy. The study analysed agriculture's GDP contribution during the implementation of various national agricultural policies, and the potential of the policies to foster agrobusiness development in Nigeria between 2000 and 2021. The study adopted mixed-method approach. Primary data were collected through a structured questionnaire administered on 29 purposively sampled state Agricultural Development Programme (ADP) directors across Nigeria. The questionnaire was face-validated by three experts. Reliability test was carryout using Cronbach Alpha approach, which yielded an index of 0.89. Copies of the questionnaire were administered on the respondents through direct contact. Secondary data were collected from the Nigeria's Federal Ministry of Agriculture and Rural Development, National Bureau of Statistics, and World Bank. Data was analysed with mean, standard deviation, percentages and ANOVA. Findings of the study revealed that the performance of implemented agricultural policies had influence on agricultural sector's percentage contribution to national GDP, and changes in agriculture's GDP contribution had significant impact on national GDP growth. The duration of active life of the policies did not influence their performance, like the Root and Tuber Expansion Programme which lasted longer yet performed less than the National Special Programme on Food Security in terms of improvement in agriculture's GDP contributions. All the policies implemented had several limitations in their ability to foster agribusinesses in Nigeria. The study recommends that future policies should focus on providing sustainable frameworks for developing the business in agriculture through value chain optimisation and the use of the teeming, young, and affordable labour force like China and India did to become global food producers.

Modelling the GDP of KSA using linear and non-linear NNAR and hybrid stochastic time series models.

BACKGROUND: Gross domestic product (GDP) serves as a crucial economic indicator for measuring a country's economic growth, exhibiting both linear and non-linear trends. This study aims to analyze and propose an efficient and accurate time series approach for modeling and forecasting the GDP annual growth rate (%) of Saudi Arabia, a key financial indicator of the country. METHODOLOGY: Stochastic linear and non-linear time series modeling, along with hybrid approaches, are employed and their results are compared. Initially, conventional linear and nonlinear methods such as ARIMA, Exponential smoothing, TBATS, and NNAR are applied. Subsequently, hybrid models combining these individual time series approaches are utilized. Model diagnostics, including mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE), are employed as criteria for model selection to identify the best-performing model. RESULTS: The findings demonstrated that the neural network autoregressive (NNAR) model, as a non-linear approach, outperformed all other models, exhibiting the lowest values of MAE, RMSE and MAPE. The NNAR(5,3) projected the GDP of 1.3% which is close to the projection of IMF benchmark (1.9) for the year 2023. CONCLUSION: The selected model can be employed by economists and policymakers to formulate appropriate policies and plans. This quantitative study provides policymakers with a basis for monitoring fluctuations in GDP growth from 2022 to 2029 and ensuring the sustained progression of GDP beyond 2029. Additionally, this study serves as a guide for researchers to test these approaches in different economic dynamics.

A global analysis of how human infrastructure squeezes sandy coasts.

Coastal ecosystems provide vital services, but human disturbance causes massive losses. Remaining ecosystems are squeezed between rising seas and human infrastructure development. While shoreline retreat is intensively studied, coastal congestion through infrastructure remains unquantified. Here we analyse 235,469 transects worldwide to show that infrastructure occurs at a median distance of 392 meter from sandy shorelines. Moreover, we find that 33% of sandy shores harbour less than 100 m of infrastructure-free space, and that 23-30% of this space may be lost by 2100 due to rising sea levels. Further analyses show that population density and gross domestic product explain 35-39% of observed squeeze variation, emphasizing the intensifying pressure imposed as countries develop and populations grow. Encouragingly, we find that nature reserves relieve squeezing by 4-7 times. Yet, at present only 16% of world's sandy shores have a protected status. We therefore advocate the incorporation of nature protection into spatial planning policies.

The economic burden associated with unmet surgical needs in Liberia: a retrospective macroeconomic analysis based on a nationwide enumeration of surgical procedures.

OBJECTIVES: The economic consequences of untreated surgical disease are potentially large. The aim of this study was to estimate the economic burden associated with unmet surgical needs in Liberia. DESIGN: A nationwide enumeration of surgical procedures and providers was conducted in Liberia in 2018. We estimated the number of disability-adjusted life years (DALYs) saved by operative activities and converted these into economic losses averted using gross national income per capita and value of a statistical life (VSL) approaches. The total, the met and the unmet needs for surgery were determined, and economic losses caused by unmet surgical needs were estimated. Finally, we valued the economic losses avoided by various surgical provider groups. RESULTS: A total of 55 890 DALYs were averted by surgical activities in 2018; these activities prevented an economic loss of between US$35 and US$141 million. About half of these values were generated by the non-specialist physician workforce. Furthermore, a non-specialist physician working a full-time position for 1 year prevented an economic loss of US$717 069 using the VSL approach, while a specialist resident and a certified specialist saved US$726 606 and US$698 877, respectively. The burden of unmet surgical need was associated with productivity losses of between US$388 million and US$1.6 billion; these losses equate to 11% and 46% of the annual gross domestic product for Liberia. CONCLUSION: The economic burden of untreated surgical disease is large in Liberia. There is a need to strengthen the surgical system to reduce ongoing economic losses; a framework where specialist and non-specialist physicians collaborate may result in better economic return than a narrower focus on training specialists alone.

Dynamic spillover effects of renewable energy efficiency in the European countries.

Renewable energy has gained significant attention due to the growing concern for environmental sustainability and the high reliance on energy imports in European countries. In this study, we use a two- stage approach to assess renewable energy efficiency (REEF) of European countries. Initially, we employ the data envelopment analysis (DEA) method to quantify the efficiency of renewable energy. Subsequently, we investigate the factors influencing REEF between 2005 and 2020. Our findings reveal a generally high level of REEF across European countries, but some countries have become worse in this regard (e.g., France, Ukraine, Russia, Belgium, Germany, Norway, and Serbia). In order to find the causes of these changes, we considered the explanatory variables of gross domestic product (GDP), energy price, renewable energy consumption, information and communications technology (ICT), and industrial value added in a spatial system generalized method of moments (spatial SYS-GMM) model. The findings provide confirmation of the spatial spillover effects of REEF within European countries. The strongest positive effect is related to energy prices. In simpler terms, as energy prices rise, the efficiency of renewable energy has increased in European countries. Additionally, ICT and renewable energy consumption have positive impacts, too. But GDP and industrial value added, have decreasing effects. Based on these findings, we put forth several policy suggestions aimed at enhancing the efficiency of renewable energy in European countries.

Prospects of natural gas consumption in Pakistan: based on the LMDI-STIRPAT PLSR framework.

The natural gas (NG) forms the sizeable portion of the primary energy consumption in Pakistan. However, its depleting domestic reserves and increasing demand is challenging to balance the supply-demand in the country. This paper investigates the relationship between NG consumption and driving factors using LMDI-STIRPAT PLSR framework. It is learned that fossil energy structure and per capita gross domestic product (GDP) are most influencing factors on NG consumption, followed by non-clean energy structure, energy intensity, and population. The factors were further modelled to forecast the future values of NG consumption for various scenarios. It is found that NG consumption would be 42.107 MTOE under the high development scenario which would be twice the baseline scenario. It is projected that indigenous NG production will fall from 4 to 2 billion cubic feet/day and demand will increase by 1.5 billion cubic feet/day. Therefore, an optimized strategy is required for a long-term solution to cater this increasing supply-demand.

Corporate social responsibility-an antidote for sustainable business performance: interconnecting role of digital technologies, employee eco-behavior, and tax avoidance.

Small- and medium-sized enterprises (SMEs) have consistently contributed significantly to the economy's gross domestic product (GDP). Organizations are motivated to achieve sustainable performance by mitigating the adverse impacts of company operations by improving productivity and optimizing resource utilization. In order to achieve this objective, the businesses are making all their efforts and developing the systems to ensure sustainable performance. Based on the prevailing research gaps, the current study examines the role of a portfolio of responsible digital technologies (DT), which provides a competitive advantage and helps achieve sustainable firm performance (SFP). Using a simple random sampling technique, data from 294 textile manufacturing SMEs is collected and analyzed using the structural equation model (SEM) in AMOS v.24. The results indicated that digital technologies, tax avoidance, green employee behavior, and corporate social responsibility facilitated improving the SFP of SMEs. Furthermore, it is worth noting that the link connecting TA and SFP is unaffected by CSR activities aimed at the environment. This finding, however, should not lessen the importance of TA, which deserves significant attention and thought from management.

Unequal climate impacts on global values of natural capital.

Ecosystems generate a wide range of benefits for humans, including some market goods as well as other benefits that are not directly reflected in market activity1. Climate change will alter the distribution of ecosystems around the world and change the flow of these benefits2,3. However, the specific implications of ecosystem changes for human welfare remain unclear, as they depend on the nature of these changes, the value of the affected benefits and the extent to which communities rely on natural systems for their well-being4. Here we estimate country-level changes in economic production and the value of non-market ecosystem benefits resulting from climate-change-induced shifts in terrestrial vegetation cover, as projected by dynamic global vegetation models (DGVMs) driven by general circulation climate models. Our results show that the annual population-weighted mean global flow of non-market ecosystem benefits valued in the wealth accounts of the World Bank will be reduced by 9.2% in 2100 under the Shared Socioeconomic Pathway SSP2-6.0 with respect to the baseline no climate change scenario and that the global population-weighted average change in gross domestic product (GDP) by 2100 is -1.3% of the baseline GDP. Because lower-income countries are more reliant on natural capital, these GDP effects are regressive. Approximately 90% of these damages are borne by the poorest 50% of countries and regions, whereas the wealthiest 10% experience only 2% of these losses.

Analysis of economic and educational spillover effects in PEPFAR countries.

The United States President's Emergency Plan for AIDS Relief (PEPFAR) has been credited with saving millions lives and helping to change the trajectory of the global human immunodeficiency virus (HIV) epidemic. This study assesses whether PEPFAR has had impacts beyond health by examining changes in five economic and educational outcomes in PEPFAR countries: the gross domestic product (GDP) per capita growth rate; the share of girls and share of boys, respectively, who are out of school; and female and male employment rates. We constructed a panel data set for 157 low- and middle-income countries between 1990 and 2018 to estimate the macroeconomic impacts of PEPFAR. Our PEPFAR group included 90 countries that had received PEPFAR support over the period. Our comparison group included 67 low- and middle-income countries that had not received any PEPFAR support or had received minimal PEPFAR support (<$1M or <$.05 per capita) between 2004 and 2018. We used differences in differences (DID) methods to estimate the program impacts on the five economic and educational outcome measures. This study finds that PEPFAR is associated with increases in the GDP per capita growth rate and educational outcomes. In some models, we find that PEPFAR is associated with reductions in male and female employment. However, these effects appear to be due to trends in the comparison group countries rather than programmatic impacts of PEPFAR. We show that these impacts are most pronounced in COP countries receiving the highest levels of PEPFAR investment.

Spatiotemporal characteristics and influencing factors of carbon emissions from land-use change in Shaanxi Province, China.

Due to global warming, there evolves a global consensus and urgent need on carbon emission mitigations, especially in developing countries. We investigated the spatiotemporal characteristics of carbon emissions induced by land use change in Shaanxi at the city level, from 2000 to 2020, by combining direct and indirect emission calculation methods with correction coefficients. In addition, we evaluated the impact of 10 different factors through the geodetector model and their spatial heterogeneity with the geographic weighted regression (GWR) model. Our results showed that the carbon emissions and carbon intensity of Shaanxi had increased overall in the study period but with a decreased growth rate during each 5-year period: 2000-2005, 2005-2010, 2010-2015, and 2015-2020. In terms of carbon emissions, the conversion of croplands into built-up land contributed the most. The spatial distribution of carbon emissions in Shaanxi was ranked as follows: Central Shaanxi > Northern Shaanxi > Southern Shaanxi. Local spatial agglomeration was reflected in the cold spots around Xi'an, and hot spots around Yulin. With respect to the principal driving factors, the gross domestic product (GDP) was the dominant factor affecting most of the carbon emissions induced by land cover and land use change in Shaanxi, and socioeconomic factors generally had a greater influence than natural factors. Socioeconomic variables also showed evident spatial heterogeneity in carbon emissions. The results of this study may aid in the formulation of land use policy that is based on reducing carbon emissions in developing areas of China, as well as contribute to transitioning into a "low-carbon" economy.

Comparative assessment of the environmental pollution and marine economic growth of Guangxi and China by using the environmental Kuznets curve fitting model.

This study examined the nexus between per capita gross ocean product (GOP) growth and total nitrogen (TN), total phosphorus (TP), and chemical oxygen demand (COD) discharged from land-based sources in Guangxi and China. Multiple pollution indicators, such as red tide area (RTA), seawater quality area (SWQA), and eutrophication area (EA), were used as marine environmental quality indicators, and annual time series data during the period 2010-2019 were employed. The data were analyzed using the environment Kuznets curve fitting model. Results showed that the average annual growth rates of the GOP and gross domestic product (GDP) of China were 9.88% and 10.79%, respectively, and those of Guangxi were 13.62% and 10.02%, respectively. The average annual GOP ratio in GDP for Guangxi and China was 6.59 and 9.47, respectively. The marine tertiary industry was the most dominant marine industry; it accounted for 41.12-50.01% (mean: 46.12%) of Guangxi's GDP and 47-60% (mean: 52.47%) of China's GDP. The TP, COD, SWQA, and EA of Guangxi and the TP, TN, COD, SWQA, and EA of China displayed inverted U-shaped GOP growth. These findings indicate that the marine economic growth and marine environmental quality of Guangxi and China are harmonious. However, TN increased synchronously with marine economic growth in Guangxi. Therefore, the industrial structure must be further optimized, pollutant discharge management must be strengthened, and the harmonious development of Guangxi's marine economy and marine environment needs to be promoted.

The dynamic effect of macroeconomic factors on housing prices: Evidence from South Africa.

This study examines the dynamic short- and long-run causal relationship between South African real house prices and key macroeconomic fundamentals (gross domestic product(GDP), mortgage rate, exchange rate-USDZAR, affordability, household debt to disposable income, unemployment rate, share prices (JSE ALL share index), foreign direct investment, and producer price index) over the period 2000Q1-2019Q4. The study uses a vector error correction model (VECM) to estimate the relationships while accounting for endogeneity and reverse causality. Although, there seems to be a significant association(both short and long-run) between house prices and all macroeconomic fundamental variables, GDP and producer price index appear to have the greatest impact. Further, our results suggest that any short-term disequilibrium in house prices always self-corrects in the long-run.

Estimation of non-health gross domestic product (NHGDP) loss due to COVID-19 deaths in West Bengal, India.

OBJECTIVES: The state of West Bengal witnessed a significant surge of COVID-19 in all three waves. However, there is a gap in understanding the economic loss associated with COVID-19. This study estimates future non-health gross domestic product (NHGDP) losses associated with COVID-19 deaths in West Bengal, India. SETTING: Various open domains were used to gather data on COVID-19 deaths in West Bengal and the aforementioned estimates. PRIMARY AND SECONDARY OUTCOME MEASURES: The NHGDP losses were evaluated using the cost-of-illness approach. Future NHGDP losses were discounted at 3%. Excess death estimates by the WHO and Global Burden of Disease (GBD) were used. Sensitivity analysis was carried out by varying discount rates and average age of death (AAD). RESULTS: 21 532 deaths in West Bengal from 17 March 2020 to 31 December 2022 decreased the future NHGDP by $0.92 billion. Nearly 90% of loss was due to deaths occurring in the age group of 30 years and above. Majority of the NHGDP loss was borne by the 46-60 years age group. NHGDP loss/death was $55,171; however, the average loss/death declined with rise in age. Based on the GBD and WHO excess death estimates, the NHGDP loss increased to $9.38 billion and $9.42 billion, respectively. When the lower age interval is considered as AAD, the NHGDP loss increased to $1.3 billion. At 5% and 10% discount rates, the losses reduced to $0.767 billion and $0.549 billion, respectively. CONCLUSIONS: Results from the study suggest that COVID-19 contributed to a major economic loss in West Bengal. The mortality and morbidity caused by COVID-19, the substantial economic costs at individual and population levels in West Bengal, and probably across India and other countries, is another economic argument for better infection control strategies across the globe to minimise the impact of COVID-19.