{"title":"明古鲁省经济增长率的面板数据回归分析","authors":"Filo Supianti","doi":"10.33369/jsds.v2i1.27258","DOIUrl":null,"url":null,"abstract":"Panel data is a combination of time series data and cross section data. The analytical method used for panel data is panel data regression. One of the advantages of analysis using panel data regress One of the indicators to measure the development of the production of goods and services in an economic area in a given year against the value of the previous year which is calculated based on GDP/GRDP at constant prices is Economic Growth. The dependent variable in this study is the growth rate of GRDP. The independent variable in this study is IPM, TPAK, TPT. This study uses panel data regression analysis with the Common Effect Model (CEM), Fixed Effect Model (FEM) and Random Effect Model (REM). The data processing in this study uses the R Studio application.","PeriodicalId":29911,"journal":{"name":"Japanese Journal of Statistics and Data Science","volume":"26 1","pages":"0"},"PeriodicalIF":1.1000,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Panel Data Regression Analysis for Economic Growth Rate In Bengkulu Province\",\"authors\":\"Filo Supianti\",\"doi\":\"10.33369/jsds.v2i1.27258\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Panel data is a combination of time series data and cross section data. The analytical method used for panel data is panel data regression. One of the advantages of analysis using panel data regress One of the indicators to measure the development of the production of goods and services in an economic area in a given year against the value of the previous year which is calculated based on GDP/GRDP at constant prices is Economic Growth. The dependent variable in this study is the growth rate of GRDP. The independent variable in this study is IPM, TPAK, TPT. This study uses panel data regression analysis with the Common Effect Model (CEM), Fixed Effect Model (FEM) and Random Effect Model (REM). The data processing in this study uses the R Studio application.\",\"PeriodicalId\":29911,\"journal\":{\"name\":\"Japanese Journal of Statistics and Data Science\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2023-06-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Japanese Journal of Statistics and Data Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.33369/jsds.v2i1.27258\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Japanese Journal of Statistics and Data Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33369/jsds.v2i1.27258","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
Panel Data Regression Analysis for Economic Growth Rate In Bengkulu Province
Panel data is a combination of time series data and cross section data. The analytical method used for panel data is panel data regression. One of the advantages of analysis using panel data regress One of the indicators to measure the development of the production of goods and services in an economic area in a given year against the value of the previous year which is calculated based on GDP/GRDP at constant prices is Economic Growth. The dependent variable in this study is the growth rate of GRDP. The independent variable in this study is IPM, TPAK, TPT. This study uses panel data regression analysis with the Common Effect Model (CEM), Fixed Effect Model (FEM) and Random Effect Model (REM). The data processing in this study uses the R Studio application.