{"title":"A Universal Model for General Gross Domestic Product Across Global Economies","authors":"Billy Gao","doi":"10.11648/j.ijefm.20241203.11","DOIUrl":null,"url":null,"abstract":"In addressing the need for a robust economic measure, this paper presents a mathematical model to forecast Gross Domestic Product (GDP) across diverse global economies. Our model, constructed from a dataset spanning 39 years from 16 varied economies, deciphers GDP by dissecting its fundamental components of population and productivity. Through meticulous literature review and data analysis, the research develops four predictive models, using linear and exponential trends, to represent the immediate and projected rates of change in both population and productivity. The research reveals a nuanced dynamic between these elements, identifying productivity, especially in infrastructure, healthcare, telecommunications, and innovation, as a pivotal force in driving economic growth. The study not only underlines the significant influence of these sectors but also the critical role of developed economies in aiding less developed ones to counteract the widening poverty gap. A comprehensive sensitivity analysis within the paper evaluates the impact of these factors on GDP, equipping policymakers with essential insights into enhancing economic progress. By combining immediate and long-term growth metrics derived from twenty-four influential variables into a cohesive predictive model, this research illuminates the complex interplay of forces shaping GDP trajectories. It suggests that while boosting population can yield short-term economic gains, enduring prosperity hinges on amplifying productivity. Moreover, the study points to the potential socio-economic divides that necessitate proactive measures for equitable development. Although challenges such as data dependency and growth discrepancies are acknowledged, the model proposes more frequent data analyses for capturing economic fluctuations accurately. Conclusively, the paper bridges a critical gap in economic modeling literature and provides a pragmatic framework for crafting inclusive economic policies and development strategies, thus making a significant contribution to both theoretical and applied economic fields.\n","PeriodicalId":258703,"journal":{"name":"International Journal of Economics, Finance and Management Sciences","volume":"104 24","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Economics, Finance and Management Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11648/j.ijefm.20241203.11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In addressing the need for a robust economic measure, this paper presents a mathematical model to forecast Gross Domestic Product (GDP) across diverse global economies. Our model, constructed from a dataset spanning 39 years from 16 varied economies, deciphers GDP by dissecting its fundamental components of population and productivity. Through meticulous literature review and data analysis, the research develops four predictive models, using linear and exponential trends, to represent the immediate and projected rates of change in both population and productivity. The research reveals a nuanced dynamic between these elements, identifying productivity, especially in infrastructure, healthcare, telecommunications, and innovation, as a pivotal force in driving economic growth. The study not only underlines the significant influence of these sectors but also the critical role of developed economies in aiding less developed ones to counteract the widening poverty gap. A comprehensive sensitivity analysis within the paper evaluates the impact of these factors on GDP, equipping policymakers with essential insights into enhancing economic progress. By combining immediate and long-term growth metrics derived from twenty-four influential variables into a cohesive predictive model, this research illuminates the complex interplay of forces shaping GDP trajectories. It suggests that while boosting population can yield short-term economic gains, enduring prosperity hinges on amplifying productivity. Moreover, the study points to the potential socio-economic divides that necessitate proactive measures for equitable development. Although challenges such as data dependency and growth discrepancies are acknowledged, the model proposes more frequent data analyses for capturing economic fluctuations accurately. Conclusively, the paper bridges a critical gap in economic modeling literature and provides a pragmatic framework for crafting inclusive economic policies and development strategies, thus making a significant contribution to both theoretical and applied economic fields.