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一个工具变量：恰好识别 IV 的偏差与覆盖率AI 解读

We revisit the finite-sample behavior of single-variable just-identified instrumental variables (just-ID IV) estimators, arguing that in most microeconometric applications, the usual inference strategies are likely reliable. Three widely-cited applications are used to explain why this is so. We then consider pretesting strategies of the form t1>c, where t1 is the first-stage t-statistic, and the first-stage sign is given. Although pervasive in empirical practice, pretesting…

模型误设下的分位数回归及其在美国工资结构中的应用AI 解读

Quantile regression (QR) fits a linear model for conditional quantiles just as ordinary least squares (OLS) fits a linear model for conditional means. An attractive feature of OLS is that it gives the minimum mean-squared error linear approximation to the conditional expectation function even when the linear model is misspecified. Empirical research using quantile regression with discrete covariates suggests that QR may have a similar property, but the exact nature of the…

何时应控制协变量？处理效应估计的面板式渐近分析AI 解读

The problem of when to control for continuous or high-dimensional discrete covariate vectors arises in both experimental and observational studies. Large-cell asymptotic arguments suggest that full control for covariates or stratification variables is always efficient, even if treatment is assigned independently of covariates or strata. Here, we approximate the behavior of different estimators using a panel-data-type asymptotic sequence with fixed cell sizes and the number…

补贴培训对受训者收入分位数影响的工具变量估计AI 解读

The effect of government programs on the distribution of participants' earnings is important for program evaluation and welfare comparisons.This paper reports es- timates of the effects of JTPA training programs on the distribution of earnings.The estimation uses a new instrumental variable (IV) method that measures program impacts on the quantiles of outcome variables.This quantile treatment effects (QTE) estimator accommodates exogenous covariates and reduces to quantile…