摘要翻译：
我们提出了一种灵活的方法，在非参数、不可分离的模型中使用“代理控制”进行估计和推理：协变量不满足标准的“不可混淆性”假设，但是满足标准的“不可混淆性”假设的变量的信息代理。我们的分析适用于横截面设置，但特别适合面板模型。我们的辨识结果激发了一个简单且“适定”的非参数估计量。我们推导了估计量的收敛速度，并构造了具有渐近正确大小的一致置信带。在面板环境中，我们的方法为识别不可分离的、一般的异质性和固定的T提供了一种新的方法。在面板中，不同时期的观测作为未观察到的异质性的代理，我们的关键识别假设来自对序列依赖结构的限制。我们将我们的方法应用于两个经验设置。我们使用横截面变异来估计等级保留对认知绩效的因果影响，我们使用面板数据来估计消费者需求反事实。
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英文标题：
《Proxy Controls and Panel Data》
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作者：
Ben Deaner
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最新提交年份：
2021
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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。
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英文摘要：
  We present a flexible approach to estimation, and inference in nonparametric, non-separable models using `proxy controls': covariates that do not satisfy a standard `unconfoundedness' assumption but are informative proxies for variables that do. Our analysis applies to cross-sectional settings but is particularly well-suited to panel models. Our identification results motivate a simple and `well-posed' nonparametric estimator. We derive convergence rates for the estimator and construct uniform confidence bands with asymptotically correct size. In panel settings, our methods provide a novel approach to the difficult problem of identification with non-separable, general heterogeneity and fixed T. In panels, observations from different periods serve as proxies for unobserved heterogeneity and our key identifying assumptions follow from restrictions on the serial dependence structure. We apply our methodology to two empirical settings. We estimate causal effects of grade retention on cognitive performance using cross-sectional variation and we estimate consumer demand counterfactuals using panel data.
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PDF链接：
https://arxiv.org/pdf/1810.00283