{"title":"非线性Tobit分解","authors":"Zhang Yi, Wang Yi, Nadarajah Saralees","doi":"10.1515/EQC.2006.271","DOIUrl":null,"url":null,"abstract":"This paper extends the decomposition of marginal effects suggested by McDonald and Moffitt [The Review of Economics and Statistics 62: 318-321, 1980] to a nonlinear tobit model, considering the increasing use of tobit analysis and substantive economic implications of the decomposition. The decomposition provides more information than is commonly realized based on the coefficients obtained from fitting a tobit model. In this paper the generalized decomposition of marginal effects is derived and the effects in the decomposition are expressed in explicit and closed form. A simulation study illustrates the application of the nonlinear decomposition using a simple nonlinear consumption function, along with maximum likelihood estimation on the parameters of the nonlinear tobit regression model.","PeriodicalId":360039,"journal":{"name":"Economic Quality Control","volume":"86 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Nonlinear Tobit Decomposition\",\"authors\":\"Zhang Yi, Wang Yi, Nadarajah Saralees\",\"doi\":\"10.1515/EQC.2006.271\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper extends the decomposition of marginal effects suggested by McDonald and Moffitt [The Review of Economics and Statistics 62: 318-321, 1980] to a nonlinear tobit model, considering the increasing use of tobit analysis and substantive economic implications of the decomposition. The decomposition provides more information than is commonly realized based on the coefficients obtained from fitting a tobit model. In this paper the generalized decomposition of marginal effects is derived and the effects in the decomposition are expressed in explicit and closed form. A simulation study illustrates the application of the nonlinear decomposition using a simple nonlinear consumption function, along with maximum likelihood estimation on the parameters of the nonlinear tobit regression model.\",\"PeriodicalId\":360039,\"journal\":{\"name\":\"Economic Quality Control\",\"volume\":\"86 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Economic Quality Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1515/EQC.2006.271\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Economic Quality Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/EQC.2006.271","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
本文将McDonald和Moffitt [the Review of Economics and Statistics 62: 318-321, 1980]提出的边际效应分解扩展到非线性tobit模型,考虑到tobit分析的日益使用和分解的实质性经济含义。该分解提供了比通常基于拟合tobit模型获得的系数实现的更多的信息。本文导出了边际效应的广义分解,并将分解中的效应用显式和封闭形式表示出来。仿真研究说明了非线性分解的应用,使用一个简单的非线性消耗函数,以及对非线性tobit回归模型参数的极大似然估计。
This paper extends the decomposition of marginal effects suggested by McDonald and Moffitt [The Review of Economics and Statistics 62: 318-321, 1980] to a nonlinear tobit model, considering the increasing use of tobit analysis and substantive economic implications of the decomposition. The decomposition provides more information than is commonly realized based on the coefficients obtained from fitting a tobit model. In this paper the generalized decomposition of marginal effects is derived and the effects in the decomposition are expressed in explicit and closed form. A simulation study illustrates the application of the nonlinear decomposition using a simple nonlinear consumption function, along with maximum likelihood estimation on the parameters of the nonlinear tobit regression model.