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决策理论在工具变量模型中的应用AI 解读

This paper applies some general concepts in decision theory to a simple instrumental variables model. There are two endogenous variables linked by a single structural equation; k of the exogenous variables are excluded from this structural equation and provide the instrumental variables (IV). The reduced-form distribution of the endogenous variables conditional on the exogenous variables corresponds to independent draws from a bivariate normal distribution with linear…

弱可分模型中的内生虚拟变量AI 解读

In this paper, we consider the nonparametric identification and estimation of the average effect of a dummy endogenous regressor in models where the regressors are weakly but not additively separable from the error term. The model is not required to be strictly increasing in the error term, and the class of models considered includes limited dependent variable models such as discrete choice models. Conditions are established conditions under which it is possible to identify…

按出现顺序标记的隐马尔可夫模型：推断与模型选择AI 解读

Summary The system equation of a hidden Markov model is rewritten to label the components by order of appearance, and to make explicit the random behaviour of the number of components, mt. We argue that this reformulation is often a good way to achieve identifiability, as it facilitates the interpretation of the posterior density, and the estimation of the number of components that have appeared in a given sample. We develop a sequential Monte Carlo algorithm for estimating…

非负Garrotte估计量研究AI 解读

Summary We study the non-negative garrotte estimator from three different aspects: consistency, computation and flexibility. We argue that the non-negative garrotte is a general procedure that can be used in combination with estimators other than the original least squares estimator as in its original form. In particular, we consider using the lasso, the elastic net and ridge regression along with ordinary least squares as the initial estimate in the non-negative garrotte.…

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滞后解释变量冗余性的再考察AI 解读

In a recent Econometric Theory problem, it was demonstrated that in a conditionally heteroskedastic time series regression with martingale difference errors the use of lagged values of regressors as instruments may not increase the efficiency of estimation relative to ordinary least squares. We provide an example of an analogous phenomenon in a model with serially correlated errors, where the optimal instrumental variables estimator is asymptotically as efficient as the…

含时变协变量的混合风险率模型的非参数识别AI 解读

Most nonparametric identification results for the mixed proportional hazards model for single spell duration data depend crucially on the proportional hazards assumption. Here, it is shown that variation in covariates over time, combined with variation across observations, is sufficient to ensure identification without the proportional hazards assumption. The required variation over time is minimal, and the mixed hazards model is identified without the proportional hazards…

半参数截断回归模型的加权与两阶段最小二乘估计AI 解读

This paper provides a root-n consistent, asymptotically normal weighted least squares estimator of the coefficients in a truncated regression model. The distribution of the errors is unknown and permits general forms of unknown heteroskedasticity. Also provided is an instrumental variables based two-stage least squares estimator for this model, which can be used when some regressors are endogenous, mismeasured, or otherwise correlated with the errors. A simulation study…

弱工具变量下 IV 估计量的有限样本证据AI 解读

Abstract We present finite sample evidence on different IV estimators available for linear models under weak instruments; explore the application of the bootstrap as a bias reduction technique to attenuate their finite sample bias; and employ three empirical applications to illustrate and provide insights into the relative performance of the estimators in practice. Our evidence indicates that the random‐effects quasi‐maximum likelihood estimator outperforms alternative…

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相关性与大规模同时显著性检验AI 解读

Large-scale hypothesis testing problems, with hundreds or thousands of test statistics zi to consider at once, have become familiar in current practice. Applications of popular analysis methods, such as false discovery rate techniques, do not require independence of the zi's, but their accuracy can be compromised in high-correlation situations. This article presents computational and theoretical methods for assessing the size and effect of correlation in large-scale testing.…

存在误分类时平均处理效应的估计AI 解读

This paper considers identification and estimation of the effect of a mismeasured binary regressor in a nonparametric or semiparametric regression, or the conditional average effect of a binary treatment or policy on some outcome where treatment may be misclassified. Failure to account for misclassification is shown to result in attenuation bias in the estimated treatment effect. An identifying assumption that overcomes this bias is the existence of an instrument for the…

单指标模型与加性指标模型的可识别性AI 解读

We provide a proof for the identifiability for both single-index models and partially linear single-index models assuming only the continuity of the regression function, a condition much weaker than the differentiability conditions assumed in the existing literature. Our discussion is then extended to the identifiability of the additive-index models.

处理或响应变量不可观测时因果效应的图形可识别性判据AI 解读

We consider the problem of using data in studies with an unobserved treatment/response variable in order to evaluate average causal effects, when cause-effect relationships between variables can be described by a directed acyclic graph and the corresponding recursive factorization of a joint distribution. The paper proposes graphical criteria to test whether average causal effects are identifiable even if a treatment/response variable is unobserved. If the answer is…

区间删失：可识别性与常和性质AI 解读

The constant-sum property given in Oller et al. (2004) for censoring models justifies the use of a simplified likelihood to obtain the nonparametric maximum likelihood estimator of the lifetime distribution. In this paper we study the relevance of the constant-sum property in the identifiability of the lifetime distribution. We show that the lifetime distribution is not identifiable outside the class of constant-sum models. We also show that the lifetime probabilities…

对称分布混合模型的推断AI 解读

This article discusses the problem of estimation of parameters in finite mixtures when the mixture components are assumed to be symmetric and to come from the same location family. We refer to these mixtures as semi-parametric because no additional assumptions other than symmetry are made regarding the parametric form of the component distributions. Because the class of symmetric distributions is so broad, identifiability of parameters is a major issue in these mixtures. We…

高出生率会阻碍经济增长吗？AI 解读

This paper examines the impact of the birth rate on economic growth by using a panel data set of 28 provinces in China over twenty years. Because China's one-child policy applied only to the Han Chinese but not to minorities, this unique affirmative policy allows us to use the proportion of minorities in a province as an instrumental variable to identify the causal effect of the birth rate on economic growth. We find that the birth rate has a negative impact on economic…

抗击疟疾：等待“神奇”疫苗时应预防战争AI 解读

The World Health Organization estimates that 300 million clinical cases of malaria occur annually and observed that during the 80s and part of the 90s its incidence increased. In this paper, we explore the influence of refugees from civil wars on the incidence of malaria in the refugee-receiving countries. Using civil wars as an instrumental variable, we show that for each 1,000 refugees there are between 2,000 and 2,700 cases of malaria in the refugee-receiving country. On…

分位数处理效应的有效半参数估计AI 解读

This paper develops estimators for quantile treatment effects under the identifying restriction that selection to treatment is based on observable characteristics. Identification is achieved without requiring computation of the conditional quantiles of the potential outcomes. Instead, the identification results for the marginal quantiles lead to an estimation procedure for the quantile treatment effect parameters that has two steps: nonparametric estimation of the propensity…

非线性测量误差模型的工具变量估计AI 解读

This paper establishes that instruments enable the identification of nonparametric regression models in the presence of measurement error by providing a closed form solution for the regression function in terms of Fourier transforms of conditional expectations of observable variables. For parametrically specified regression functions, we propose a root n consistent and asymptotically normal estimator that takes the familiar form of a generalized method of moments estimator…

多元广义正交因子 GARCH 模型AI 解读

We propose a factor generalized autoregressive conditional heteroscedasticity (GARCH) model and develop test procedures for checking the correctness of the number of factors. Maximum likelihood estimation of the model is straightforward once computationally simple preliminary estimates are obtained. Motivated by the empirical application of the article, a mixture of Gaussian distributions is considered in addition to the conventional Gaussian likelihood. Interestingly, some…