摘要翻译:
Kotlarski恒等式在应用经济学研究中得到了广泛的应用。然而,如何在这种流行的识别方法的基础上进行推理一直是一个悬而未决的问题。本文通过构造重复测量误差模型中潜变量密度函数的一个新的置信带来解决这一公开问题。置信区间建立在我们的发现之上,我们可以将Kotlarski的恒等式改写为一个线性矩限制系统。置信区间一致控制一类数据生成过程的渐近大小,并且对所有固定方案都是一致的。仿真研究支持了我们的理论结果。
---
英文标题:
《Inference based on Kotlarski's Identity》
---
作者:
Kengo Kato, Yuya Sasaki, Takuya Ura
---
最新提交年份:
2019
---
分类信息:
一级分类:Economics 经济学
二级分类:Econometrics 计量经济学
分类描述:Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论,微观计量经济学,宏观计量经济学,通过新方法发现的经济关系的实证内容,统计推论应用于经济数据的方法论方面。
--
---
英文摘要:
Kotlarski's identity has been widely used in applied economic research. However, how to conduct inference based on this popular identification approach has been an open question for two decades. This paper addresses this open problem by constructing a novel confidence band for the density function of a latent variable in repeated measurement error model. The confidence band builds on our finding that we can rewrite Kotlarski's identity as a system of linear moment restrictions. The confidence band controls the asymptotic size uniformly over a class of data generating processes, and it is consistent against all fixed alternatives. Simulation studies support our theoretical results.
---
PDF链接:
https://arxiv.org/pdf/1808.09375