{"title":"具有不可观测异质性的二元面板数据的动态模型承认根n一致条件估计","authors":"F. Bartolucci, V. Nigro","doi":"10.2139/ssrn.967389","DOIUrl":null,"url":null,"abstract":"A model for binary panel data is introduced which allows for state dependence and unobserved heterogeneity beyond the effect of available covariates. The model is of quadratic exponential type and its structure closely resembles that of the dynamic logit model. However, it has the advantage of being easily estimable via conditional likelihood with at least two observations (further to an initial observation) and even in the presence of time dummies among the regressors. Copyright 2010 The Econometric Society.","PeriodicalId":416571,"journal":{"name":"CEIS: Centre for Economic & International Studies Working Paper Series","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"49","resultStr":"{\"title\":\"A Dynamic Model for Binary Panel Data With Unobserved Heterogeneity Admitting a Root-N Consistent Conditional Estimator\",\"authors\":\"F. Bartolucci, V. Nigro\",\"doi\":\"10.2139/ssrn.967389\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A model for binary panel data is introduced which allows for state dependence and unobserved heterogeneity beyond the effect of available covariates. The model is of quadratic exponential type and its structure closely resembles that of the dynamic logit model. However, it has the advantage of being easily estimable via conditional likelihood with at least two observations (further to an initial observation) and even in the presence of time dummies among the regressors. Copyright 2010 The Econometric Society.\",\"PeriodicalId\":416571,\"journal\":{\"name\":\"CEIS: Centre for Economic & International Studies Working Paper Series\",\"volume\":\"75 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"49\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CEIS: Centre for Economic & International Studies Working Paper Series\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.967389\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"CEIS: Centre for Economic & International Studies Working Paper Series","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.967389","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Dynamic Model for Binary Panel Data With Unobserved Heterogeneity Admitting a Root-N Consistent Conditional Estimator
A model for binary panel data is introduced which allows for state dependence and unobserved heterogeneity beyond the effect of available covariates. The model is of quadratic exponential type and its structure closely resembles that of the dynamic logit model. However, it has the advantage of being easily estimable via conditional likelihood with at least two observations (further to an initial observation) and even in the presence of time dummies among the regressors. Copyright 2010 The Econometric Society.
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