Estimation of Semiparametric Limited Dependent

半参数有限相关估计

• 批准号: 9321024
• 负责人: Bo Honore
• 金额: $ 4.98万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-07-01 至 1995-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9321024&HistoricalAwards=false
• 关键词: Estimation; Semiparametric; Limited; Dependent

9321024 Honore This project contributes to our understanding of the properties of statistical models that are widely used in economic research. The research will provide whole new classes of econometric estimators that are not subject to some of the limitations of existing methods. The results from this project will be especially useful for a more thorough analysis of economic panel data such as the survey data from the Panel Study of Income Dynamics and for the econometric analysis of the duration of unemployment. More specifically, the project continues research on the estimation of semiparametric models in three areas. The first part of the project shows that it is possible to modify the large battery of estimators for the censored regression model in the econometrics literature in such a way that they can be applied when the censoring points are random and not known for all individuals. The advantage of this approach is that the resulting estimators will make weaker assumptions than the proposed in the literature. For example, the investigator will be able to construct estimators that require only conditional symmetry or quantile independence of the errors rather than independence between the errors and the regressors. The second part of the project concerns the estimation of discrete choice panel data models. It is known that a conditional logit approach can be used to estimate panel data logit models when all the explanatory variables are exogenous or when the only explanatory variables are lagged variables. Thus far, it is not known how to estimate such models when the explanatory variables consist of lagged dependent variables as well as exogenous variables. The approach taken in this project will be used in a logit as well as a semiparametric setting. The third part continues work on econometric duration models. The investigator demonstrated that it is possible to modify his estimators of the parameters of a mixed Weibull distribution i n such a way that rates of convergence arbitrarily close to root-n.

小行星9321024 该项目有助于我们理解在经济研究中广泛使用的统计模型的属性。 这项研究将提供全新的计量经济学估计，不受现有方法的一些限制。 该项目的结果将特别有助于更全面地分析经济面板数据，如收入动态面板研究的调查数据，以及对失业持续时间的计量经济学分析。 更具体地说，该项目继续研究三个领域的半参数模型的估计。 该项目的第一部分表明，它是可能的，以这样一种方式，他们可以应用于当截尾点是随机的，并不知道所有的个人修改的估计量的大电池的经济计量学文献中的截尾回归模型。 这种方法的优点是，由此产生的估计将比文献中提出的假设更弱。 例如，研究者将能够构造仅要求误差的条件对称性或分位数独立性而不是误差与回归量之间的独立性的估计量。 本项目的第二部分涉及离散选择面板数据模型的估计。 当所有的解释变量都是外生变量或仅有的解释变量是滞后变量时，条件logit方法可以用来估计面板数据logit模型。 到目前为止，它是不知道如何估计这样的模型时，解释变量包括滞后因变量以及外生变量。 本项目中采用的方法将用于logit和半参数设置。 第三部分继续研究计量经济持续期模型。 研究者证明，可以修改混合威布尔分布参数的估计量，使收敛速度任意接近根n。