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A discontinuity test for identification in triangular nonseparable models

机译:用于三角形不可分模型的识别的不连续性检验

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摘要

This paper presents a test for the validity of control variable approaches to identification in triangular non separable models. Assumptions commonly imposed to justify such methods include full independence of instruments and disturbances and existence of a reduced form that is strictly monotonic in a scalar disturbance. We show that if the data has a particular structure, namely that the distribution of the endogenous variable has a mass point at the lower (or upper) boundary of its support, validity of the control variable approach implies a continuity condition on an identified function, which can be tested empirically. (C) 2016 Elsevier B.V. All rights reserved.
机译:本文提出了一种控制变量方法在三角形不可分模型中进行辨识的有效性的测试。通常证明这些方法合理的假设包括仪器和干扰的完全独立性以及在标量干扰中严格单调的简化形式的存在。我们表明,如果数据具有特定的结构,即内生变量的分布在其支持的下(或上)边界处有一个质点,那么控制变量方法的有效性就意味着所识别函数的连续性条件,可以凭经验进行测试。 (C)2016 Elsevier B.V.保留所有权利。

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