Value Of Gross Domestic Product Research Articles

The Measurement of the Gross Domestic Product affected by the shadow economy

The article presents a method for balancing Gross Domestic Product (GDP) when the measurements of its components are distorted by the existence of the shadow economy. Our proposal to measure GDP is based on a multiple ultrastructural model (MUM), where the explanatory variables are subject to error. We show that the expected value of GDP can be divided into two parts: the first part concerns data related to registered activities and the second part concerns unobserved data which may be partly related to the shadow economy. The empirical analysis is based on the annual data for individual voivodeships in Poland for the years 2000–2019. The data are obtained from the Local Data Bank of Statistics Poland. Two approaches to measuring GDP are considered: from the expenditure side and from the production side. The results show that the unobservable part of the variables necessary to balance GDP on the production side does not exceed 1% of GDP, and on the expenditure side, it mostly reaches about 3% of GDP.

Article Review: Relationship between Toxoplasmosis and other Diseases

Water provision is sensitive to climate change, and agricultural production and food supply are sensitive to water availability. Water scarcity affects food security and agricultural economic development through changes in agricultural production and changes in the composition of produced goods. Recent droughts also led to a decrease in the volume of water allocated to agriculture, which led to a decrease in total agricultural production and exports, and this has subsequent impacts on food security and economic development. The research aimed to measure the impact of water scarcity on agricultural economic development for the period 1990-2022. The research included three behavioral equations with three endogenous variables: the cultivated area, the value of agricultural output, and the value of gross domestic product, and four exogenous variables: the amount of available water, agricultural labor, and the value of agricultural investments and the income of other sectors, the studied model is called the sequential model, which was estimated using the Recursive method, using the ordinary least squares (OLS) method. The results indicated that increasing the amount of available water will lead to an increase in the cultivated areas by 141,129.2 dunums, and that increasing one thousand dunums of the cultivated area will increase agricultural output by 0.00821, and that agricultural labor is inversely proportional to agricultural output. It became clear that if the income of the rest of the sectors increased by one unit, the domestic product would increase by 0.1873. Water scarcity will reduce cultivated areas, which in turn will decrease agricultural output, causing the value of agricultural output to decrease and its contribution to the gross domestic product to decrease. In turn, it will have serious repercussions on agricultural economic development. Therefore, the research recommends the necessity of integrated water management and improving the efficiency of its use, as well as the application of modern technologies in agriculture, such as sprinkler irrigation, hydroponics, and redrawing crop compositions to ensure maximizing the net return per unit of water.

Specific Effect of Innovation Factors on Socioeconomic Development of Countries in View of the Global Crisis

Although the coronavirus pandemic has now faded into the background, the global crisis caused by COVID-19 has had the most devastating impacts worldwide. Given the potential relapse of such unexpected and uncertain events, it is vital to specify the patterns thereof and develop proactive measures for the countries to acquire an advanced readiness to deal with the related incidents. The most infected countries faced an increase in business bankruptcies, unemployment and inflation rates, low production volumes, and a decline in Gross Domestic Product (GDP). To withstand such socioeconomic consequences, the countries had to employ a number of measures, with innovation development acceleration being one. This paper aims to assess the dependency of an increase in GDP and a decrease in inflation and unemployment rates on the country-level growth of innovation development according to such Global Innovation Index (GII) pillars as institutions, human capital and research, infrastructure, market sophistication, business sophistication, knowledge and technology outputs, and creative outputs. The conducted research analysis covered the period from 2019 to 2022 based on the data for the GII pillar development level and economic performance indicators for 20 countries from five socioeconomic models. Descriptive and comparative statistics as well as correlation and regression analysis were used to prove the innovation development to be a key driver in increasing GDP and reducing inflation. To increase the GDP value, special attention should be paid to such GII pillars as institutions and human capital and research, while infrastructure and human capital and research are the pillars to reduce the inflation rates.

Implications of Gold Trading for the Global Economy

One of the precious metals found in the earth’s crust, whose economic value dates back several centuries and remains relevant in our contemporary socio-economic settings, is gold. Society’s veneration for the precious metal surges from one generation to the other. However, most developing economies endowed with large quantities of gold are plagued with unbridled activities of warlords, foreign-backed militias, rebels, and illegal artisanal miners, some of whom operate on behalf of political stalwarts who mask their true identity. The purpose of this research was to examine how trading activities related to gold tend to affect gross domestic product (GDP) values at the national and global levels. The quantitative approach to scientific inquiry was adapted and used in the study. Specifically, the cross-sectional design formed the basis of the research. Data required for the conduct of the research were obtained mainly from secondary sources. These included textbooks, peer-reviewed articles published in journals and grey literature. Other sources were the Google Search Engine, including databases of Macrotrends and World Bank, databases and archives of the United States Geological Survey, among other significant sources. Respective data on Ghana’s annual gold production volumes, gold revenues and GDP values from 1980 through 2020 and respective data on annual average closing prices per ounce of gold, global gold production volumes, global gold revenues and global GDP values from 1969 through 2020 were 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 national and global GDP values. The study revealed gold as a viable source of alternative investment and an effective portfolio diversifier in periods of volatility in the global equity markets. The average closing price per ounce of gold in 2020 was the highest since 1969. More than a third of the world’s total gold reserves (34.26%) were held by Australia, Russia and South Africa, and China remained the world’s largest producer of gold in 2019. For most developing economies with large production volumes, the percentage and monetary contribution of gold revenue to GDP was determined to be significant. However, for most advanced economies, percentage contribution was insignificant, albeit monetary contribution was found to be quite colossal and capable of impacting positively on national expenditures. Findings from the research revealed a positive and significant relationship between Ghana’s gold revenue and GDP (coefficient value = 9.574151593; p = 0.000, p < 0.05); and a positive but non-significant relationship between global gold revenue and global GDP (coefficient value = 527.3364872; p = 8.111, p > 0.05). Gold revenue accounted for nearly 97.64% of the variation in Ghana’s GDP from 1980 through 2020, while global gold revenue accounted for about 88.16% of the variation in global GDP from 1969 through 2020. During 2019, Ghana was the leading producer and highest-earner from gold sales in Africa; and the economy with the fifth-highest percentage contribution of gold revenue to GDP (9.52%); after Burkina Faso (17.37%), Mali (15.87%), Sudan (11.25%) and Guinea (10.02%) respectively. The statistical analysis confirmed and validated, to a large extent, the valuable contribution of gold revenue to national GDP, a clarion call for regulation and control of the activities of illegal artisanal miners to improve and actualise annual national estimates for total gold production volumes and revenues; the need for minerals and mining policy reforms and expeditious implementation of same to control environmental pollution and hazards. Dramatic transformation and an increase in recycling technologies are required to curb the accelerated depletion rate of gold reserves. It is imperative for the major gold-producing economies to take proactive steps towards the creation of economic parsimony in supply to positively affect the price per ounce of gold in the global market.

Natural gas, trade openness and economic growth in Peru: 1965–2022

Natural gas is a major fuel in Peru, accounting for nearly 45 % of all energy sources used to generate electricity. This research aims to analyze the dynamic association between economic growth and natural gas consumption (NGC), considering Peru's trade openness (Tr) from 1965 to 2022. The augmented Dickey–Fuller unit root test is utilized to test the stationary properties of the log series of real gross domestic product (GDP), NGC, and real Tr. We used the autoregressive distributed lag (ARDL) cointegration approach to determine the long-run (LR) equilibrium association between the variables. As the second cointegration method, we used the Engle-Granger test. The results of the ARDL test support the cointegration of all variables, we find the opposite case with Engle-Granger method. The Granger causality results support the neutrality hypothesis between GDP and NGC, a two-way causality association between Tr and GDP, and the neutrality hypothesis between NGC and Tr. Nevertheless, in the LR, cointegration confirms the growth hypothesis between GDP and NGC. Similarly, we find that in the LR, the first lag of Tr positively impacts the current GDP value. Meanwhile, in the short run, Tr has a positive effect on Peru's GDP. Then, using the findings of cointegration among all variables, we can conclude that NGC and Tr are the drivers of economic growth in Peru in the LR. Finally, we discuss the policy implications of our results.

ИНДЕКС ФОНДООТДАЧИ: СОВРЕМЕННОЕ СОСТОЯНИЕ И ФАКТОРЫ РОСТА

The scientific article contains an analysis of scientific literature on ensuring the efficient use of fixed assets in enterprises, research on capital productivity and capital intensity, and the development of main directions for the efficient use of fixed capital. The dynamics of the coefficients of renewal and disposal of fixed assets in the economy are presented in graphical form. The information base for the study was data from the official website of the Federal State Statistics Service. The maximum values of the renewal coefficient were observed in 2018, 2019 and 2022, and the minimum in 2015, 2020 and 2021. The maximum values of the retirement rate are presented in 2014, 2015 and 2016, and the minimum in 2019, 2020 and 2021. An econometric study of the capital productivity index showed an inverse and very weak relationship with the value of gross domestic product and the cost of fixed assets (the value of the correlation coefficient (index) (-0.1)): with an increase in the value of gross domestic product and the value of fixed assets in the period under study, no growth was observed capital productivity index. The value of the gross domestic product and the cost of fixed assets have a direct and close relationship (the value of the correlation coefficient (index) is 0.9): the annual growth of the gross domestic product is accompanied by an increase in the cost of fixed assets. A matrix of correlation coefficients (indices) was constructed to calculate the total correlation coefficient (index). The result of calculating the total correlation coefficient (index) (its value is 0.4) showed that there is a direct and weak connection between the capital productivity index, the value of the gross domestic product and the cost of fixed assets: the growth of the capital productivity index is weakly related to the growth of the gross domestic product and the cost of fixed assets funds.

Review of Research on the Impact of Changes Resulting from the Hard Coal Mining Sector in Poland on the GDP Value

Energy transition is one of the main objectives of the European Union. Significant changes will mainly affect countries in which significant modifications will have to be made to their energy sources. The process will involve high investment in infrastructure and additional costs of the transformation, such as reduced production (which may affect the GDP value) in the economic sectors involved in the process. The aim of this article is to provide the energy transition community, namely the national economy in general and those involved in planning for structural change in particular, with the key lessons and challenges in researching the impact of production changes in the mining sector. This article also shows the relevance of the mining sector in the economy. Within this area, particular attention is given to the following issues: the impact of economic sectors on the country’s GDP (gross domestic product); the identification of key sectors of the economy using the input–output method; the contribution of coal mining and the mining industry to Poland’s GDP; an analysis of changes in the structure of Poland’s economy using the input–output method; and the use of the input–output method in the context of changing/reducing the supply of economic sectors.

The analysis of main causes of increasing of cost of social aftermath of drug addiction in the region according to results of repeated evaluation

The social cost of drug consumption in the Samara Oblast was re-assessed in 2017-2020 (first assessment was implemented in 2007-2010). The main causes of increasing of social cost of drug consumption were analyzed on the basis of the study results. In Samara Oblast, due to financial and structural changes in state and non-state spheres, occurred increasing of social cost of drug consumption from 18.0 billion to 25.4 billion rubles per year. At that, percentage of social cost of drug consumption in the gross domestic product decreased from 2.9% to 1.6%. In general structure of expenses greatest changes affected percentage of social aftermath of drug addiction (increase from 17.8% to 26.1%) and expenses of drug consumers (decrease from 69.7% to 62.3%). The increase of absolute values of financial expenditures of the Oblast related to drug consumption conditioned by financial and structural changes in society, is accompanied by decreasing of percentage of ocial cost of drug consumption in value of gross domestic product. The main cause of its dynamics is significant increasing of gross regional product.

Comparison Methods of Machine Learning and Deep Learning to Forecast The GDP of Indonesia

The success of an economy can bring significant benefits to a country and its society. One way to measure economic growth is by looking at the value of gross domestic product (GDP). The value of a country's GDP is influenced by many factors, including inflation, exports, and imports. Therefore, predicting future economic growth requires forecasting the value of GDP. GDP forecasts are crucial as they provide information about the economic development of a country over a specific period of time. By forecasting GDP, governments and investors can make informed decisions to optimize profits or minimize risks when investing or doing business in a country. This research aims to forecast Indonesia's GDP for the second, third, and fourth quarters of 2023 using the best models from machine learning or deep learning methods. Forecasts are made for each method with and without additional variables. The results indicate that the SimpleRNN algorithm from deep learning without additional variables is the method with the smallest RMSE and MAPE for GDP forecasting. Therefore, the best method used to forecast GDP is the SimpleRNN algorithm, and the forecasted GDP values for Indonesia's second, third, and fourth quarters are 5.350.840,00, 5.483.895,00, and 5.610.077,50 billion rupiah.

Evaluating the Nexus between Macroeconomic Indicators and Stock Market Performance in Nigeria

This study examines the effect of macroeconomic indicators on stock market performance in Nigeria from 1986 to 2022 using time series data analysis. The analysis includes unit root tests, co-integration tests, and error correction model analysis to understand the long-term and short-term dynamics between macroeconomic variables and stock market performance. Various diagnostic tests, such as tests for autocorrelation, multicollinearity, and heteroscedasticity, were conducted to enhance the accuracy of the model. The results indicate a strong positive relationship between stock market performance and lagged values of Gross Domestic Product (GDP) and Inflation Rate (INF) in the long run. Economic growth, as indicated by GDP, and inflation rates play significant roles in driving stock market movements in Nigeria. Conversely, there is a negative relationship between stock market performance and lagged values of equity (EQUI) and interest rate (INTR), suggesting that changes in equity and interest rates may not have a long-term influence on stock market performance. The short-run analysis reveals short-term momentum in stock market performance, with past stock market returns and inflation rates positively affecting current stock market performance. However, variables like GDP, equities, exchange rates, and interest rates do not show significant short-term effects on stock market performance, indicating their impact may be more pronounced in the long run. These findings provide valuable insights for policymakers and investors seeking to understand the relationship between macroeconomic conditions and stock market movements in Nigeria.

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.

ВАЛОВИЙ ВНУТРІШНІЙ ПРОДУКТ ЯК ІНДИКАТОР РІВНЯ ЕКОНОМІЧНОГО РОЗВИТКУ КРАЇНИ (НА ПРИКЛАДІ ЧЕСЬКОЇ РЕСПУБЛІКИ)

The article addresses the current issue of researching and analyzing Gross Domestic Product (GDP) as an indicator of national economic competitiveness on a global scale and its impact on the macroeconomic stability of the Czech Republic. The authors emphasize the importance of GDP analysis for effective economic management, planning, forecasting, and ensuring macroeconomic stability. The study is based on a review of previous research and publications by both Ukrainian and foreign scholars. As a result, the concept of Gross Domestic Product (GDP) is thoroughly analyzed, with three main aspects of the concept elucidated: "gross," "domestic," and "product." Furthermore, the article provides crucial explanations to enhance comprehension of the GDP concept. Moreover, the article extensively analyzes the dynamics of nominal and real Gross Domestic Product (GDP) of the Czech Republic from 2016 to 2022. Special attention is given to the impact of the COVID-19 pandemic on the Czech economy and its adverse effects in 2020. The causes of GDP decline are highlighted, along with data on economic recovery at the end of 2020 and an assessment of GDP dynamics in 2021 and 2022. The significance of evaluating GDP growth rates and their potential implications for the Czech economy are underscored, as well as the importance of GDP per capita as an indicator of Czech economic competitiveness and the country's position in the GDP per capita ranking. Additionally, the article examines the impact of declining household consumption on Czech GDP due to inflation and low investments. The methodology of correlation-regression analysis is employed to identify trends in GDP dynamics, along with projected GDP values for 2024 and 2025. It is noted that the main drivers of Czech economic growth should be the export activities of companies and the recovery of household demand. However, further research is needed to explore the analysis of GDP dynamics as an indicator of macroeconomic stability, its impact on forming global competitiveness rankings, and positioning the Czech Republic in the global economic community.

Новые вызовы и запросы для национальной системы здравоохранения в цифровую эру

The authors emphasize that the quality of life of the population is a priority in the development of any state. Life expectancy at birth (LEB) is one of the important indicators. The paper reveals the statistical dependence of (LEB) on the value of gross domestic product in the country as a whole. Using statistical data, the authors demonstrate the strong fluctuations of the LEB indicator by regions and the lack of correlation between LEB and gross regional product per capita for the constituent entities of the Russian Federation. This problem re-quires a special approach when working with the life expectancy indicator in the healthcare system. The article considers the relevance of changing business processes and transition to a management model based on the patient’s medical profile in the healthcare system in order to achieve the national development goals of the state and improve the quality of population's life. The positive role of a patient-oriented approach in the devel-opment of the healthcare system is substantiated. The possibility of using medical marketing tools as part of social marketing is revealed in order to create communications, increase trust in the healthcare system, satis-faction with medical care, and increase the proportion of citizens leading a healthy lifestyle.

SOYBEAN PRODUCTION IN THE STATE OF MARANHÃO AND ITS RELATIONSHIP WITH THE GROSS DOMESTIC PRODUCTODUCT

Maranhão (MA) State is among the ten largest soybean producers in Brazil and is the second largest producer in the northeastern region, with an average yield of 2,915 kg ha-1, and the evolution of this production has positively influenced the Municipal Gross Domestic Product (GDP). Thus, this study aimed to characterize soybean production in MA, analyzing data from the main producing municipalities from 2010 to 2019 and relating the value of soybean production to GDP in the period. Municipal Agricultural Production and Municipal GDP data from the Brazilian Institute of Geography and Statistics were used to carry out exploratory and descriptive analyses, simple linear regression, and Pearson's correlation. To characterize the factors that influence crop yield, monthly graphs of temperature and pluviometric index were elaborated for the period of the soybean cycle in MA. The results indicated that the MA planted area evolved significantly and plantations were concentrated in the municipalities of Balsas and Tasso Fragoso, which also had the highest yields in the period, with 619,997 and 616,672 Megagram in 2018, respectively. The highest yield was observed in Buriticupu (3,900 kg ha-1) in 2019. The survey showed a strong and significant relationship between the value of production and GDPs.

Singme Music Entertainment Services Marketing Information System with Content-Based Filtering Method and TAM Testing

With the times, the website used as marketing and sales media, which developed into E-Commerce. In 2019, there was 16,277 businesses used the E-Commerce concept, and also the value of Gross Domestic Product (GDP) was about 5.07%. Furthermore, because of the Coronavirus Disease (COVID) pandemic, the GDP decreased to -2.07% In 2020 and even impacted 10 out of 17 business sectors. Music entertainment business was also impacted by the pandemic, because during the pandemic, the government restricted certain public activities. Therefore, this system named Singme will help singers or music groups to market their services and provide related information for the public. Searching the services in Singme will be assisted by using Content-Based Filtering (CBF) method, it will give the recommendations of the services which have correlations with the keywords. Using Technology Acceptance Model (TAM) to test 122 feedback data about Singme with SmartPLS application v3.2.9. As the results, all hypotheses are acceptable because each t-statistic value > t-table value (1.981), and also each p-value < 0.05. Which PEOU influences PU by 34.3%, PU and POEU influence ATU by 50.7%, PU and ATU influence BITU by 56.1%, and BITU influences ASU by 52.3%.

The Impact of Macroeconomics Variables and Bank Internal Factors on Islamic Banking Performance During Covid-19 in Indonesia


 
 
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 Previous studies focused on Bank internal factors in analysing the financial performance of Islamic banks. In this paper, we examine the performance of Islamic Banks in Indonesia by using key macroeconomics and bank internal variables as well as including covid-19 as a dummy variable from 2010 to 2021. The study used secondary data collected from World Bank database and Islamic banks annual financial reports. An Econometrics models such as VAR, unit root test and Johansen cointegration test were employed in the estimation process in which ROA was used as a proxy to measure the performance of Islamic Bank whereas Eight variables such as GDP, BOPO, CAR, FDR, NPF, Trade, Inflation, and Covid-19 were used in determining the performance of Islamic Banks in Indonesia. The findings indicate that, the lagged values of Gross Domestic Product (GDP), BOPO, CAR, FDR trade and Covid-19 all have a positive relationship with ROA. In the other hand, the lagged variable of Non-performing Financing (NPF) shows a negative and statistically insignificant relationship with ROA. Consequently, the study recommends that government should introduce expansionary fiscal policy to stimulate economic growth thereby enhancing Islamic banks performance. From this results, management of Islamic banks and those in academia can use it in understanding the macroeconomic and bank internal factors that impact the financial performance of Islamic banking. However, this paper could not examine other variables like digital index, taxation and banks governance structure in determining the financial performance of Islamic banks in Indonesia.
 
 

The industrialization of medicinal plants in Indonesia

This article reviews the use of medicinal plants in Indonesia, the development of the medicinal plant industry, and its role in the process of industrializing medicinal plants. The review was carried out using the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) method by including the criteria for original articles and reports. Searches were done on Google Scholar, Proquest, Pubmed, Science Direct, and Springer websites. The key words employed for the search included economic development, industrialization, leading sectors, medicinal plants, and modernization. The inclusion and exclusion criteria was based on duplication, redundancy, method and quality of the article. In the search results of the selected article database, 71 out of 300 articles and reports were included in the criteria. According to the findings of this systematic review, the industrialization of medicinal plants represents an opportunity to alter regional and national economic structures. Industrialization of medicinal plants is a process of modernizing medicinal plant commodities which aims to increase the added value of all economic sectors with the manufacturing sector which are interrelated. The industrialization of medicinal plants is marked by the development and improvement of superior medicinal plant commodities as the leading sector of the regional and national economy. Industrialization of superior medicinal plant commodities can change the economic structure by increasing the contribution of the industrial sector to consumer demand, increasing Gross Domestic Product (GDP), increasing export value and availability of employment opportunities as well as increasing long-term economic development and increasing income per capita, to ensure equal distribution of welfare for farmers and the community. Industrialization of medicinal plants can increase the added value of medicinal plant commodities, increase consumer demand, increase the value of GDP, increase the value of exports and employment, increase the potential for domestic and foreign demand, encourage the development of the domestic and foreign industrial sectors, expand employment opportunities, reduce dependence on imports, and increase the country’s foreign exchange. Economic development oriented toward the medicinal plant industry is the right industrialization strategy for Indonesia. Key words: Economic Development, Industrialization, Leading Sectors, Medicinal Plants, Modernization

Peran Pasar Modal Syariah Dalam Meningkatkan Perekonomian Di Indonesia

The Islamic capital market is an alternative source of funding as well as an investment vehicle for a company whose operational activities are based on sharia principles. In this case the Islamic capital market affects the level of economic growth of a country. where when the level of investment is high, the country's economic growth will increase and vice versa. The purpose of this study is to determine the role of the Islamic capital market in increasing economic growth in Indonesia. This research uses the literature study method with sources from articles, books and data analysis using descriptive analysis regarding the role of the Islamic capital market in increasing economic growth in Indonesia. The results of the study show that Indonesia's economic growth is inseparable from the role of Islamic stock investment. Economic growth can be measured with the value of Gross Domestic Product (GDP). GDP continues to increase over the past few years, as well as the sharia stock market capitalization which is quite stable. Where is the relationship between capitalization Islamic stock market with a positive Gross Domestic Product (GDP).

Greenhouse gas emission, GDP, tertiary education, and rule of law: A comparative study between high-income and lower-middle income countries

Global climate change is a pressing concern, particularly in underdeveloped countries. Because greenhouse gases are a key cause of climate change and economic growth is tied to emissions. The study aimed to determine how the Gross Domestic Product (GDP), Tertiary Education, and Rule of Law could be utilized more effectively to reduce greenhouse gas emissions.The study used data from 30 Lower-Middle Income Countries (LMICs) and 10 High-Income Countries (HICs), as grouped by the World Bank, for the period between 2000 and 2014. In this study, sum of greenhouse gas emission is the response variable and GDP value, Gross enrollment in tertiary education, Rule of law index are the key explanatory variables. Independent sample t-test and multiple linear regression models were applied to analyze the data.The study found a significant impact of GDP on greenhouse gas emissions [0.722, (0.653, 0.790), p < 0.01] for LMICs and [-0.605, (−0.728, −0.482), p < 0.01] for HICs. For Tertiary Education, the regression model coefficient is [-0.187, (−0.274, −0.100), p < 0.01], and [0.480, (0.356, 0.603), p < 0.01], respectively for the LMICs and HICs. And the Rule of Law index [-0.046, (−0.112, 0.020), p = 0.170], and [0.099, (−0.028, −0.227), p = 0.125] for LMICs and HICs respectively came out as statistically not significant although from the mean test, the difference between the mean of the variable Rule of Law of LMCs and HICs is statistically significant [p < 0.01] thus, it has some impact on the efficient use of economic growth.This study concludes that in the LMICs, greenhouse gas emissions are highly positively associated with GDP and the negative coefficient for tertiary education indicates it holds down the emissions. For the HICs, it is evident that GDP is not a major driver and positive significance for tertiary education indicates that the greenhouse gas emissions may result from extravagant operations that might be linked with higher tertiary education, which requires further analysis.

Using nighttime light data to estimate water evaporation inside buildings in China's urban areas

AbstractUrbanization has a great impact on urban evapotranspiration. Water evaporation inside buildings is an important part of urban water vapor resources and a crucial core of urban hydrological processes. The systematic studies on building water evaporation (BWE) are mostly the method of experimental monitoring. This study proposed a new method to simulate and estimate water evaporation flux inside buildings in urban areas. Based on the nighttime light data and urban per capita gross domestic product (GDP), a new modeling system was built to simulate the total BWE. Building area was calculated using the nighttime light data. And the BWE coefficient Df was estimated according to the important indicator of economic development per capita GDP value. Then the water evaporation inside urban buildings and the spatial distribution of water evaporation inside buildings in typical cities could be obtained. The results showed that the total amount of water evaporation inside buildings in China's urban areas was 24.5 billion m3. Among the 31 provincial capitals in China, Shanghai had the largest BWE of 1.08 billion m3. The minimum water evaporation of buildings in Lhasa was 20.0 million m3. Studies of BWE can assess urban water budgets, support on‐demand allocation of water resources, and provide a fundamental understanding of the relationship between water resources and energy heat island effects in urban areas.