Domestic Product Data Research Articles

Türkiye’nin Enerji İhtiyacını Tahmin Etmek için Jaya Algoritmasına Dayalı Yeni Hibrit Bir Yaklaşım

The main objective of this study is to develop a highly predictive model to forecast Turkey’s energy consumption. The model has developed based on regression functions and Jaya algorithm which is a new and powerful optimization algorithm. Linear, exponential, hyperbolic and quadratic functions were used as regression functions. Gross domestic product, population, import and export data have been used as independent variables in the model. The accuracy of Jaya method was investigated using error criteria such as average relative error, root mean square error, and mean absolute error. As a result of the analysis, it was concluded that the quadratic function developed with Jaya algorithm performed better than the others. After the optimal configurations have been defined, a scenario has been developed to estimate Turkey's future energy consumption values. The obtained results are compared with the previous studies. According to the obtained results, primary energy consumption of Turkey can be modeled using the proposed model and Jaya can be used to predict Turkey's future energy need.

ECONOMIC GROWTH, AIR POLLUTION, AND GOVERNMENT ENVIRONMENTAL REGULATION: EVIDENCE FROM 287 PREFECTURE-LEVEL CITIES IN CHINA

Air pollution control is crucial for promoting the modernization of governance systems and efficiency. To address the subjective contrived factors and errors in the gross domestic product (GDP) data in traditional statistical almanacs, our study aims to construct a panel data model of 287 prefecture-level cities for the period from 1998–2016 (using objective nighttime light data). We also used government work report words related to environmental regulation to characterize the constraints of government environmental regulations. For this purpose, we used instrumental variables (to explore the relationship and interaction between air pollution and economic growth) and a model setting, with which we carried out regression analysis and robustness tests; the findings were validated using a transmission mechanism hypothesis. We found that that economic growth and air pollution positively influence each other and government environmental regulations significantly reduce air pollution. We also found that to achieve high economic development, environmental pollution must be controlled to avoid further damage to human and material capital. Furthermore, government environmental regulations can help improve the environmental comfort level and economic development quality.

PND40 Price Analysis of Antiepileptic Drugs Marketed in the USA

To assess the characteristics and trends in 30-day wholesale acquisition costs (WAC) at the market entry of antiepileptic drugs (AEDs) approved by the US Food and Drug Administration (FDA) in the period of 1984-2020. Regulatory information was derived from the FDA website. WACs at market entry were retrieved from the IBM Micromedex Red Book from the date of FDA approval FDA to December 31, 2020. The defined daily dose (DDD) for adult patients was obtained from the FDA approved labels. Consumer price index (CPI) and gross domestic product (GDP) data were collected from US government databases. The AWP/DDD per month of therapy was calculated for each formulation. Trends of median prices of 30-day WAC/DDD each year were plotted with the CPI and the GDP, and trends were analyzed. The FDA approved 79 AEDs from 1984 to 2020, with 11 AEDs approved in the 1980s, 23 in the 1990s, 16 in the 2000s, 26 in the 2010s, and 3 in 2020. There were 33(41.8%) AEDs sponsored by US companies. The FDA used priority review to approve 19(24.1%) AEDs, and 16(20.3%) were designated as orphan drugs. The median market entry 30-day WAC/DDD was $22.50 in the 1980s (interquartile range [IQR]=$32.49), $92.66 (IQR=$90.33) in the 1990s, $174.69 (IQR=$224.47) in the 2000s, $1,097.85 (IQR=$2036.73) in the 2010s, and $8,217.00 (IQR=$8,604.75) for the 3 AEDs approved in 2020. WAC median prices determinately surpassed CPI in 1993 at $68.82 and GDP in 2000 at $130.74. AEDs prices at market entry increased significantly during the period 1984-2020. The increase in AED prices exceeded the CPI and the GDP during the same period. Newer formulations of AEDs seem to offer novel and effective ways of treating seizures but at the cost of higher prices.

Estimates of greenhouse gas emission in Turkey with grey wolf optimizer algorithm-optimized artificial neural networks

The main purpose of this study was to predict Turkey’s future greenhouse gas (GHG) emissions using an artificial neural network (ANN) model trained by a grey wolf optimizer (GWO) algorithm. Gross domestic product, energy consumption, population, urbanization rate, and renewable energy production data were used as predictor variables. To probe the accuracy of the proposed model, the new ANN-GWO model’s performance was compared with the performance of ANN-BP (back propagation), ANN-ABC (artificial bee colony), and ANN-TLBO (teaching–learning-based optimization) models using multiple error criteria. According to calculated error values, the ANN-GWO models predicted GHG emissions more accurately than classical ANN-BP, ANN-ABC, and ANN-TLBO models. According to the average relative error values calculated for the test set, ANN-GWO performs 32.23% better than ANN-BP, 35.29% better than ANN-ABC, and 19.33% better than ANN-TLBO. Using the ANN-GWO model, GHG emissions were forecasted out to 2030 under three different scenarios. The predictions obtained, consistent with a prior forecasting study in the literature, indicated that GHG emissions are expected to outpace official predictions (model prediction range for 2030, 956.97–1170.54 Mt CO2 equivalent). The present study demonstrated that GHG emissions can be predicted accurately with an ANN-GWO model, and that the GWO optimization method is advantageous for predicting future GHG emissions.

Assessment of the sustainable development of rural minority settlements based on multidimensional data and geographical detector method: A case study in Dehong, China

In a developing country, paying attention to the sustainable development of rural areas is conducive to the development of the entire country. Ethnic minority areas are an important part of China's economic and social development. Owing to a lack of relevant statistical data, most previous studies in this area have focused on the sustainable development of rural areas or the development of ethnic minorities, but have not studied the sustainable development of rural ethnic minorities. The development of rural ethnic minorities is worthy of attention. In this study, we took Dehong as the study area. First used toponyms to accurately identify the rural minority areas and then calculated a grid of settlement density. Second, we considered the digital number (DN) value of the visible infrared imaging radiometer suite (VIIRS) as a measure of the development of the region and digital elevation model (DEM), net primary productivity (NPP), normalized difference vegetation index (NDVI), and gross domestic product (GDP) data as the indicators of terrain, climate, ecological, and economic factors, respectively. Finally, linear regression and the geographical detector method were used to determine the weight of the factors for constructing a sustainable development index (SDI) to quantitatively analyze the sustainable development and influencing factors of each minority nationality. The factors evaluated using linear regression and the geographical detector method were ranked as follows: NDVI > elevation > GDP > slope > NPP > settlement density. The results demonstrate that of the five main ethnic minorities in Dehong, Dai and Jingpo have higher SDI, followed by Achang, Lisu and De'ang. In addition, we provide some suggestions for ethnic minorities in Dehong.

Analysis of Data Management in Sigi District Statistics Center

This study aims to determine data management on the gross regional domestic product at the Central Bureau of Statistics of Sigi Regency. Management of Sigi Regency Gross Regional Domestic Product data shows several uses of the final product manifested in the form of "final demand." The final demand referred to consists of components of household final consumption expenditure (PK-RT), final consumption expenditure of non-profit institutions serving households (PK-LNPRT), government final consumption expenditure (PK-P), gross fixed capital formation ( PMTB), Changes in Inventory (PI), as well as components of exports of goods and services.

Pengujian Beta Konsumsi dan Implikasinya Terhadap Imbal Hasil Saham Syariah di Indonesia dengan Mempertimbangkan Variabel Makro Ekonomi

This study aims to determine the effect of consumption beta on Islamic stock returns. The research model used Breeden's (1979) CCAPM model by adding macroeconomic variables as control variables in the first regression test. The sample selection used a purposive sampling technique and obtained 27 active Islamic stocks listed on the JII index during 2019. The data and information collected are historical data, namely the monthly closing price of the JII Islamic stock index, Gross Domestic Product Data, Inflation data and SBI interest rates. . The use of macroeconomic variable data is an effort to obtain a Goodness of fit model so that it is able to produce estimates in accordance with the actual value. The beta coefficient value obtained in the first test then carried out the second stage regression. The results prove that there is a negative influence between consumption beta on the average yield of Islamic JII stocks of 21.56%, with a consumption variable value of -0.046894 and a significant T value of 0.0147 <0.05. Thus, this research briefly proves that the CCAPM Breeden model (1979) applies to the JII Islamic stock index on the Indonesia Stock Exchange for the period 2019.

The Determination of the Factors Affecting Air Transportation Passenger Numbers

So long as human beings are required to go between places, the civil aviation industry will always exist. In this study, a country-based examination has been applied to air passenger numbers. 50 countries are selected according to the highest rating of air transportation passenger numbers, gross domestic product (GDP), total population, and human development index (HDI) data. 28 of these countries are included in the analysis which is common in at least three of these rankings. The relationship between the four parameters is examined via correlation analysis. Thereafter, the related parameters were taken as independent variables in multiple linear regression analyses to determine the factors affecting passenger numbers. The results show that GDP and HDI plays a significant role in passenger numbers. Based on these significant relationships, dimension reduction is done by explanatory factor analysis mapping countries clearly. Exploring the similarities of countries, multidimensional scaling (MDS) is used. The best countries using passenger transportation are found as the United States, the United Kingdom, Brazil, and Turkey via MDS configuration. Except for the United States, the reason these countries are found as the best according to passenger transportation is related to their geographical location which is not stated with the numbers.

Country-scale trends in air pollution and fossil fuel CO2 emissions during 2001–2018: confronting the roles of national policies and economic growth

Fossil fuel (FF) burning, the main energy source of the modern world’s economy, remains the major source of anthropogenic carbon dioxide (CO2) and pollutants in the atmosphere. Based on 18 years (2001–2018) of aerosol optical depth (AOD) data from Moderate Resolution Imaging Spectroradiometer satellite, FFCO2 emissions from the Open-Data Inventory for Anthropogenic Carbon dioxide, and gross domestic product (GDP) data from the World Bank, we found that air quality, FF consumption, and economy are strongly bonded at the continental scale but decoupled at the national level under favorable policies. The comparison of AOD vs PM2.5 and NO2 over urbanized areas shows that the pollutants leading to the AOD load can vary significantly by country. A strong connection between GDP and FFCO2 emissions indicates that economic growth deeply replies on FF consumption in most countries. Meanwhile, air pollution is more associated with the growing trend than the level of development of a country. With more mature technologies and renewable energy, economies can keep growing without compromising their environment and population health.

Economic Growth : The Impact of Zakat Funds and Tax on Business Capital

This study aims to determine the effect of Zakat Funds and Tax on Business Capitales on Economic Growth. The population in this study is the data of the Province of West Java from 2010 to 2017 where the economic growth report, Tax on Business Capital report and zakat fund distribution report are used. The sample taken by the author in this study is the Zakat Fund Distribution Data, Tax on Business Capital Data and the Gross Regional Domestic Product (PDRB) data of West Java Province from 2010 to 2017. Researchers used multiple statistical analysis and correlation methods. To obtain more accurate results in multiple regression analysis, classic assumption testing is executed so that the results obtained are regression equations. The results of the study show that the Zakat Fund Distribution and Tax on Business Capital data have a significant effect on economic growth. Based on data processing, it shows that the distribution of zakat funds and local taxes simultaneously in providing an influence on economic growth variables of 76%. While the rest of 100% - 76% = another 24% is the influence of other variables not examined in this study.Keywords : Zakat Funds; Tax on Business Capital; Economic Growth

PENGARUH JUMLAH INDUSTRI, TENAGA KERJA, DAN PENGELUARAN PEMERINTAH TERHADAP PERTUMBUHAN EKONOMI DI KAWASAN GERBANGKERTASUSILA TAHUN 2014-2018

GERBANGKERTASUSILA in East Java Province is the highest contributor to GRDP in East Java Province. The purpose of the research itself is to determine the influence of the number of industries, labor, and government spending with economic growth in the GERBANGKERTASUSILA region in 2014-2018. In this study, the Gross Regional Domestic Product (GRDP) data on the number of industries, labor in the industrial sector, and government expenditure in the industrial sector over a period of five years is 2014-2018. The method in this study uses Panel Data which is a combination of time series data (2014-2018) and cross data (seven regencies / cities) in East Java Province as well as the Random Effect approach model. The data analysis of this study used multiple linear regression with the source of the data obtained from BPS (Statistics Indonesia) which then processed the data using Eviews-9. The results of this study indicate that each variable of the number of industries, labor, and government spending has a significant and positive influence on economic growth in the GERBANGKERTASUSILA region in 2014-2018.

Contribution of Iranian scholars to medical sciences: A holistic overview of 140-years publication.

Background: This study investigated the trends in the scientific output of Iran published in PubMed indexed journals. To the best of our knowledge, there was no previous study to examine the Iranian scientific output in all fields of health and biomedical sciences. Methods: Using a bibliometric approach, we tracked 140 years (between 1877 and 2016) of Iranian scientific productions in PubMed. The journals which papers widely published over them were analyzed. The metadata of journals was extracted from Web of Science (WoS), Scopus, and Scimago Journal & Country Rank. The Gross Domestic Product (GDP) data was elaborated from the World Bank to evaluate the relationship with research output. We used Pearson’s correlation coefficient at p<0.01 significance level and reported the data in a scatterplot. Results: We identified 106 226 documents produced by Iranian authors in journals indexed in PubMed since 1877. The number of papers climbed dramatically in 2000 and afterward, and this was consistent with the country’s GDP. Although the scientific contribution of Iranian researchers is remarkable, 67% of papers (26 978 out of 106 226) were published in local Journals categorized into quartile 3 and 4 of WoS and Scopus. The study shows that GDP growth has had a positive influence on publication output (r=0.738, p<0.001). Conclusion: This is the first study with a panorama view of Iran’s contribution to biomedical literature. Based on the results of our survey, although the number of Iranian publications rose over time but they are mostly published in low ranked journals. Health policy-makers advise reconsidering the criteria for measuring research activities. Improving policies will help researchers to publish in higher ranked journals.

Escola do pobre: a renda per capita familiar dos alunos e as políticas de cota e de permanência como fator de inserção social no Instituto Federal do Mato Grosso (IFMT)

As instituições da Rede Federal de Educação Profissional, Científica e Tecnológica (RFEPCT) desde 1909, tem assumido, prioritariamente, o compromisso transformador na sociedade ao formar os cidadãos humildes em trabalhadores qualificados por meio da educação profissional. Considerando a manutenção de tal preceito na RFEPCT, questiona-se, então, se o Instituto Federal de Mato Grosso (IFMT) acolhe, de fato, os jovens pertencentes às famílias de baixa renda e centra a oferta do ensino profissional e o desenvolvimento de suas atividades nesse público-alvo. Este artigo tem como objetivo analisar a renda per capita familiar dos alunos do IFMT comparando-os aos dados de Índice de Desenvolvimento Humano (IDH) e do Produto Interno Bruto (PIB) per capita dos municípios sedes dos 14 campi e 05 campi avançados. Os procedimentos metodológicos adotados para o alcance deste intento foram a pesquisa bibliográfica e documental, por meio de levantamento de fontes institucionais oficiais e banco de dados do IBGE. Os resultados apontaram que, no ano de 2016, a instituição atendeu 64,5% de alunos pertencentes a família de baixa renda, com uma renda per capita familiar inferior a 1,5 salário-mínimo. A partir desse período, adotou as políticas de inclusão/acesso/permanência, por meio da institucionalização do sistema de cotas, destinando 60% de suas vagas para alunos advindos de escolas públicas e, dentre essas, para pessoas com deficiência e autodeclarados pardos, pretos e índios. Assim, tem buscado promover a inserção social de jovens de baixa renda e contribuir para o crescimento e desenvolvimento de regiões do estado de Mato Grosso.

The Role of Renewable Energy Generation in Sustainable Economic Growth: The Case of Turkey

Energy is a crucial factor in both the production and consumption process. It is a critical component not only for economic growth but also for social, technological, and environmental issues. With the events and facts in these areas in the last fifty years, the importance of the energy factor has more increased, and the search for alternative energy sources has accelerated. Thus, renewable energy sources have started more preferred by considering sustainable growth goals. This study aims to investigate the role of renewable energy generation on economic growth for the period of 1990-2017. In the study conducted using the Autoregressive Distributed Lag (ARDL) method, gross domestic product, capital stock, employment, and renewable energy generation data of Turkey were employed. According to the findings, increases in capital stock, employment, and renewable energy production affect economic growth positively.

Future global socioeconomic risk to droughts based on estimates of hazard, exposure, and vulnerability in a changing climate

A consistent and equitable global drought risk assessment for multiple regions, populations, and economic sectors at the gridded scale under future diverse climate change scenarios has been the subject of scarce research. Climate change is projected to increase the future hazard of drought and cause consequential damages to socioeconomic systems. The risk assessment of drought caused by climate change can be a bridge between impacts and adaptation. To assess the socioeconomic risk to droughts in a base period and two future periods (2016 to 2035 and 2046 to 2065), the projections of five general circulation models and population and gross domestic product (GDP), land cover, and water resources data were used to analyze the socioeconomic risk under three scenarios combining representative concentration pathways (RCPs) and shared socioeconomic pathways (SSPs). The socioeconomic risk was calculated as the product of three determinants: hazard, exposure, and vulnerability. The risk of the global population to drought was projected to be highest in 2046 to 2065 under scenario RCP8.5–SSP3, with up to 1.45 × 109 persons affected, a 63% increase compared with the base period. The highest risk to GDP (4.29 × 1013 purchasing power parity $) was possibly in 2046 to 2065 under scenario RCP2.6–SSP1, with the risk increasing 5.64 times compared to the base period. Regions with high socioeconomic risk were primarily concentrated in the East and South Asia, Midwestern Europe, eastern US, and the coastal areas of South America. With climate change, the inequality in future socioeconomic risk to drought among countries is predicted to increase. The ten countries with the highest risks to population and GDP accounted for nearly 70% of the global risk.

The Development of Critical Care Medicine in China: From SARS to COVID-19 Pandemic.

Background Critical care medicine is a branch of medical science that deals with the characteristics and regularity of life-threatening processes initiated by any injury or disease and, accordingly, relevant treatment for patients with critical illness. Conceptions of critical care medicine in China stemmed in the early 1970s. Ever since the establishment of the first intensive care unit (ICU) along with the increasingly incomparable role of ICU in medical practices, critical care medicine has become an indispensable part of the Chinese medical and health system. Currently, critical care medicine as a secondary clinical discipline and a well-constructed science is in sustainable development on the way towards systematization and standardization. Methods The gross domestic product (GDP) and population data were obtained from the National Bureau of Statistics. The number of ICUs, ICU beds, and hospital beds and other data regarding ICU staffing and facility resources were obtained from the Yearbook of Health in the People's Republic of China and National Bureau of Statistics. The mortality rates of SARS and COVID-19 and the number of health workers aiding Hubei amid COVID-19 pandemic were obtained from the National Health Commission. Findings. Critical care medicine in mainland China has made significant strides: both quantity and quality are progressing at a fast pace after SARS in 2003. Although there exist some disparities in healthcare personnel and medical resources, they have not hindered the country from mobilizing its healthcare workers and resources against a public health emergency.

Does Financial Statements Information Contribute to Macroeconomic Indicators

This paper aims to analyze the impact of financial statement information on macroeconomic indicators, including the labor market and domestic product data growth. We attempt to examine the effect of variables by applying Classical and Bayesian analyses. We applied quarterly GDP (Growth Domestic Product) data from the real-time data set for macroeconomists maintained by the Statistical Center of Iran (SCI). Additionally, financial statement information is collected from the Tehran Exchange Market database. The results suggest that earnings growth dispersion provides related data about final GDP growth. The results suggest that after considering the effect of other influential factors, specifically real initial GDP, earnings growth dispersion is useful in forecasting future GDP changes. However, the results indicate that there is no link between earnings growth dispersion and GDP restatements. The findings are important for economists and policymakers to have more accurate economic estimation and prediction by applying for accounting numbers.

Solving multicollinearity problem of gross domestic product using ridge regression method

This study is dedicated to solving multicollinearity problem for the general linear model by using Ridge regression method. The basic formulation of this method and suggested forms for Ridge parameter is applied to the Gross Domestic Product data in Iraq. This data has normal distribution. The best linear regression model is obtained after solving multicollinearity problem with the suggesting of value.

Methodological Features of GDP Formation Within the Framework of the System of National Accounts

Purpose of the study. The aim of this work is to examine methodological approaches to the formation of gross domestic product on an annual and quarterly basis within the framework of the System of National Accounts, using the example of 189 countries. The work is based on a dynamic and structural analysis of statistical information of gross domestic product published on the official websites of statistical agencies and the International Monetary Fund.Materials and methods. The information base of the study is the official statistical data of countries published on the website of the International Monetary Fund, as well as methodological provisions for the formation of gross domestic product. The research methodological base is represented by statistical methods of information analysis and empirical research.Results. The analysis of data and methodological approaches to gross domestic product formation in different countries has been carried out, as a result of which the main problems of a number of countries regarding the accuracy and relevance of gross domestic product data have been identified. These problems are grouped into six key criteria based on practical macroeconomic approaches, in particular gross domestic product: updating of the base year, annual and quarterly gross domestic product data, timeliness of reporting gross domestic product data, method of compiling gross domestic product (production, expenditure, income), use of the international standard “System of national accounts, 2008”.Conclusion. Despite a rather large volume of macroeconomic indicators, one of the main indicators is gross domestic product, the dynamics of which reflects the development of the economy. Therefore, reliable data on gross domestic product play a key role in the analysis of macroeconomic and financial policies, as well as in the analysis and accuracy of forecasting the development of the country’s economy. The study revealed that 50% of the countries surveyed had acceptable base years, meaning that the transition to the new base year did not exceed 10 years. Virtually all countries generate annual gross domestic product data, while quarterly estimates of gross domestic product form about 65% of countries. The timeliness of data dissemination also varies from country to country, and many do not publish date information. 72% surveyed countries provide annual gross domestic product data in a timely manner, while 55% surveyed countries provide quarterly gross domestic product data in a timely manner. The production method is the most common of the three methods of calculating gross domestic product (the production method, the method of using income and the generation of gross domestic product by source of income). Gross domestic product formation in accordance with the current version of the international standard “System of National Accounts, 2008” is applied in 52% of countries, and in most other countries the previous version of the international standard “System of National Accounts, 1993” is used.

Trends in affordability of tobacco products before and after the transition to GST in India

ObjectiveTo estimate the trends in affordability of bidis, cigarettes and smokeless tobacco (SLT) in India and examine the impact of transition from the earlier indirect taxation system to the new...