{"title":"面板数据的建模创新和增长","authors":"B. Mu, Yue Li","doi":"10.56502/ijie1010003","DOIUrl":null,"url":null,"abstract":"This paper comprehensively reviews how innovation and growth are modelled in theoretical and empirical literature. We distinguish between economic modelling (microfounded) and econometric modelling (ad hoc). The two modelling approaches are complementary to each other for their comparative advantages in causality identification and forecasting performance. Popular models of the two approaches are illustrated and compared. We also propose an eclectic approach to combine the two approaches in one analysis framework.","PeriodicalId":46622,"journal":{"name":"International Journal of Entrepreneurship and Innovation","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Modelling Innovation and Growth in Panel Data\",\"authors\":\"B. Mu, Yue Li\",\"doi\":\"10.56502/ijie1010003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper comprehensively reviews how innovation and growth are modelled in theoretical and empirical literature. We distinguish between economic modelling (microfounded) and econometric modelling (ad hoc). The two modelling approaches are complementary to each other for their comparative advantages in causality identification and forecasting performance. Popular models of the two approaches are illustrated and compared. We also propose an eclectic approach to combine the two approaches in one analysis framework.\",\"PeriodicalId\":46622,\"journal\":{\"name\":\"International Journal of Entrepreneurship and Innovation\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2022-12-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Entrepreneurship and Innovation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.56502/ijie1010003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Entrepreneurship and Innovation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.56502/ijie1010003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BUSINESS","Score":null,"Total":0}
This paper comprehensively reviews how innovation and growth are modelled in theoretical and empirical literature. We distinguish between economic modelling (microfounded) and econometric modelling (ad hoc). The two modelling approaches are complementary to each other for their comparative advantages in causality identification and forecasting performance. Popular models of the two approaches are illustrated and compared. We also propose an eclectic approach to combine the two approaches in one analysis framework.
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