{"title":"通过贸易进行的经济复杂性转移及其对索洛残差(全要素生产率)的影响:空间方法","authors":"Fadi Fawaz, Anis Mnif, Yaseen S. Alhaj - Yaseen","doi":"10.25115/sae.v42i1.9312","DOIUrl":null,"url":null,"abstract":"Previous literature suggests that trade contributes to knowledge and technology spillovers among trading partners. Using panel data and country-specific fixed effects, we show that the technology spillovers of a country is explained by the Economic Complexity from its major trading partners. We build an endogenous growth model for all OECD countries for the 1966–2016 period; we draw the residuals to measure the Total Factor Productivity of each country. Then, using spatial econometrics, we regress the Total Factor Productivity of each country on the Economic Complexity Index of its major trading partners. In addition, we run a Random Coefficient Model, to let this relationship vary randomly by country. We show that for 30 of the 36 countries, the TFP of a country positively depends on the ECI of its trading partners Finally, we run the endogenous growth model again, but now it includes the spatial lag term as an explanatory variable.","PeriodicalId":210068,"journal":{"name":"Studies of Applied Economics","volume":"42 8","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Economic Complexity Transfer through Trade and its Impact on the Solow Residual (Total Factor of Productivity): A Spatial Approach\",\"authors\":\"Fadi Fawaz, Anis Mnif, Yaseen S. Alhaj - Yaseen\",\"doi\":\"10.25115/sae.v42i1.9312\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Previous literature suggests that trade contributes to knowledge and technology spillovers among trading partners. Using panel data and country-specific fixed effects, we show that the technology spillovers of a country is explained by the Economic Complexity from its major trading partners. We build an endogenous growth model for all OECD countries for the 1966–2016 period; we draw the residuals to measure the Total Factor Productivity of each country. Then, using spatial econometrics, we regress the Total Factor Productivity of each country on the Economic Complexity Index of its major trading partners. In addition, we run a Random Coefficient Model, to let this relationship vary randomly by country. We show that for 30 of the 36 countries, the TFP of a country positively depends on the ECI of its trading partners Finally, we run the endogenous growth model again, but now it includes the spatial lag term as an explanatory variable.\",\"PeriodicalId\":210068,\"journal\":{\"name\":\"Studies of Applied Economics\",\"volume\":\"42 8\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Studies of Applied Economics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.25115/sae.v42i1.9312\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Studies of Applied Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25115/sae.v42i1.9312","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Economic Complexity Transfer through Trade and its Impact on the Solow Residual (Total Factor of Productivity): A Spatial Approach
Previous literature suggests that trade contributes to knowledge and technology spillovers among trading partners. Using panel data and country-specific fixed effects, we show that the technology spillovers of a country is explained by the Economic Complexity from its major trading partners. We build an endogenous growth model for all OECD countries for the 1966–2016 period; we draw the residuals to measure the Total Factor Productivity of each country. Then, using spatial econometrics, we regress the Total Factor Productivity of each country on the Economic Complexity Index of its major trading partners. In addition, we run a Random Coefficient Model, to let this relationship vary randomly by country. We show that for 30 of the 36 countries, the TFP of a country positively depends on the ECI of its trading partners Finally, we run the endogenous growth model again, but now it includes the spatial lag term as an explanatory variable.