中文摘要
一类重要的结构模型研究技能形成的决定因素以及干预的最优时机。本文为这些模型提供新的识别结果，并考察看似无害的尺度和位置限制对感兴趣参数的影响。为此，我首先在不施加这些附加限制的情况下刻画所有参数的识别集，并表明在弱于文献中常用假设的条件下，重要的政策相关参数是点识别的。施加标准尺度和位置限制的含义取决于模型的具体设定方式，但它们通常会影响参数的解释，并可能影响反事实分析。重要的是，对于流行的常数替代弹性（CES）生产函数，常用的尺度限制会固定已识别参数并导致设定偏误。因此，仅仅改变观测变量的计量单位就可能导致无效的投资策略和误导性的政策建议。我展示了如何简便地调整现有估计量以解决这些问题。作为副产品，本文还提出了关于限制何时才真正属于标准化的一般性正式定义。
Abstract
Abstract An important class of structural models studies the determinants of skill formation and the optimal timing of interventions. In this article, I provide new identification results for these models and investigate the effects of seemingly innocuous scale and location restrictions on parameters of interest. To do so, I first characterize the identified set of all parameters without these additional restrictions and show that important policy-relevant parameters are point identified under weaker assumptions than commonly used in the literature. The implications of imposing standard scale and location restrictions depend on how the model is specified, but they generally impact the interpretation of parameters and may affect counterfactuals. Importantly, with the popular constant elasticity of substitution (CES) production function, commonly used scale restrictions fix identified parameters and lead to misspecification. Consequently, simply changing the units of measurements of observed variables might yield ineffective investment strategies and misleading policy recommendations. I show how existing estimators can easily be adapted to solve these issues. As a byproduct, this article also presents a general and formal definition of when restrictions are truly normalizations.