论文检索

分析纵向数据的广义经验似然方法AI 解读

Abstract Efficient estimation of parameters is a major objective in analyzing longitudinal data. We propose two generalized empirical likelihood-based methods that take into consideration within-subject correlations. A nonparametric version of the Wilks theorem for the limiting distributions of the empirical likelihood ratios is derived. It is shown that one of the proposed methods is locally efficient among a class of within-subject variance-covariance matrices. A…

病例对照与队列研究中因果效应的锐界AI 解读

Evaluating the causal effect of an exposure on a response from case-control and cohort studies is a major concern in epidemiological and medical research. Since causal effects are in general nonidentifiable from such studies, this paper derives bounds on two causal measures: the causal risk difference and the causal risk ratio. We use the potential response approach and a linear programming method to derive sharp bounds on the causal risk difference, and a novel fractional…

医疗费用研究中反变换条件均值的估计AI 解读

We propose a new approach for analyzing skewed and heteroscedastic health care cost data through regression of the conditional quantiles of the transformed cost. Using the appealing equivariance property of quantiles to monotone transformations, we propose a distribution-free estimator of the conditional mean cost on the original scale. The proposed method is extended to a two-part heteroscedastic model to account for zero costs commonly seen in health care cost studies.…

观测模式具有信息性时的纵向数据边际分析AI 解读

We consider solutions to generalized estimating equations with singular working correlation matrices, of which the estimator of Diggle et al. (2007) is a special case. We give explicit conditions for consistent estimation when the pattern of observations may be informative. In such cases, simulations reveal reduced bias and reduced mean squared error compared with existing alternatives. A study of peritoneal dialysis is used to illustrate the methodology.

广义删失分位数回归模型的积分最大得分估计AI 解读

Quantile regression techniques have been widely used in empirical economics. In this paper, we consider the estimation of a generalized quantile regression model when data are subject to fixed or random censoring. Through a discretization technique, we transform the censored regression model into a sequence of binary choice models and further propose an integrated smoothed maximum score estimator by combining individual binary choice models, following the insights ofÂ…

分布性政策效应的非参数估计AI 解读

This paper proposes a fully nonparametric procedure to evaluate the effect of a counterfactual change in the distribution of some covariates on the unconditional distribution of an outcome variable of interest. In contrast to other methods, we do not restrict attention to the effect on the mean. In particular, our method can be used to conduct inference on the change of the distribution function as a whole, its moments and quantiles, inequality measures such as the Lorenz…

企业内部工资差异的锦标赛模型估计AI 解读

We consider the estimation of a tournament model with moral hazard (based on Rosen (1986), AER)) when only aggregate data on intra-firm employment levels and salaries are available. Equilibrium restrictions of the model allow us to recover parameters of interest, including equilibrium effort levels in each hierarchical stage of the firm. We illustrate our estimation procedures using data from major retail chains in the US. We find that only a fraction of the wage…

贝叶斯分位数回归方法AI 解读

Abstract This paper is a study of the application of Bayesian exponentially tilted empirical likelihood to inference about quantile regressions. In the case of simple quantiles we show the exact form for the likelihood implied by this method and compare it with the Bayesian bootstrap and with Jeffreys' method. For regression quantiles we derive the asymptotic form of the posterior density. We also examine Markov chain Monte Carlo simulations with a proposal density formed…

矩不等式模型的贝叶斯分析AI 解读

This paper presents a study of the large-sample behavior of the posterior distribution of a structural parameter which is partially identified by moment inequalities. The posterior density is derived based on the limited information likelihood. The posterior distribution converges to zero exponentially fast on any δ-contraction outside the identified region. Inside, it is bounded below by a positive constant if the identified region is assumed to have a nonempty interior.…

动态离散选择模型中的异质性AI 解读

We consider dynamic discrete choice models with heterogeneity in both the levels parameter and the state dependence parameter. We first present an empirical analysis that motivates the theoretical analysis which follows. The theoretical analysis considers a simple two-state, first-order Markov chain model without covariates in which both transition probabilities are heterogeneous. Using such a model we are able to derive exact small sample results for bias and mean squared…

Abrevaya (1999b) considered estimation of a transformation model in the presence of left truncation. This paper observes that a cross‐sectional version of the statistical model considered in Frederiksen et al. (2007) is a generalization of the model considered by Abrevaya (1999b) and the generalized model can be estimated by a pairwise comparison version of one of the estimators in Frederiksen et al. (2007). Specifically, our generalization will allow for discretized…

动态面板模型中系统GMM估计量的弱工具变量问题AI 解读

The system GMM estimator for dynamic panel data models combines moment conditions for the model in first differences with moment conditions for the model in levels. It has been shown to improve on the GMM estimator in the first differenced model in terms of bias and root mean squared error. However, we show in this paper that in the covariance stationary panel data AR(1) model the expected values of the concentration parameters in the differenced and levels equations for the…

时间维度固定的面板单位根推断：不同检验的比较AI 解读

The objective of the paper is to investigate and compare the performance of some of the unit root tests in micropanels, which have been suggested in the literature. The framework is a first-order autoregressive panel data model allowing for heterogeneity in the intercept but not in the autoregressive parameter. The tests are all based on usual t-statistics corresponding to least squares estimators of the autoregressive parameter resulting from different transformations of…

改进的随机占优自助法检验AI 解读

We propose a new method of testing stochastic dominance that improves on existing tests based on the standard bootstrap or subsampling. The method admits prospects involving infinite as well as finite dimensional unknown parameters, so that the variables are allowed to be residuals from nonparametric and semiparametric models. The proposed bootstrap tests have asymptotic sizes that are less than or equal to the nominal level uniformly over probabilities in the null…

含固定效应的空间自回归面板模型估计AI 解读

This paper establishes asymptotic properties of quasi-maximum likelihood estimators for SAR panel data models with fixed effects and SAR disturbances. A direct approach is to estimate all the parameters including the fixed effects. Because of the incidental parameter problem, some parameter estimators may be inconsistent or their distributions are not properly centered. We propose an alternative estimation method based on transformation which yields consistent estimators…

无排除限制的一类三角联立方程模型估计AI 解读

This paper provides a control function estimator to adjust for endogeneity in the triangular simultaneous equations model where there are no available exclusion restrictions to generate suitable instruments. Our approach is to exploit the dependence of the errors on exogenous variables (e.g. heteroscedasticity) to adjust the conventional control function estimator. The form of the error dependence on the exogenous variables is subject to restrictions, but is not…

随机效应面板模型中的异方差与序列相关检验AI 解读

This paper considers a panel data regression model with heteroskedastic as well as serially correlated disturbances, and derives a joint LMÂ test for homoskedasticity and no first order serial correlation. The restricted model is the standard random individual error component model. It also derives a conditional LM test for homoskedasticity given serial correlation, as well as, a conditional LM test for no first order serial correlation given heteroskedasticity, all in the…

受污染多期教育实验的处理效应估计：缩小班级规模的动态影响AI 解读

This paper introduces an empirical strategy to estimate dynamic treatment effects in randomized trials that provide treatment in multiple stages and in which various noncompliance problems arise, such as attrition and selective transitions between treatment and control groups. Our approach is applied to the highly influential four-year randomized class size study, Project STAR. We find benefits from attending small classes in all cognitive subject areas in kindergarten and…

普通教育与职业培训：转型经济体的证据AI 解读

This paper examines the relative benefits of general education and vocational training during Romania's transition to a market economy. We examine a 1973 educational reform that shifted a large proportion of students from vocational training to general education. Using census and household survey data, we analyze the effect of this policy with a regression discontinuity design. We find that men affected by the policy are significantly less likely to work in manual or…

IPS 面板单位根检验的局部渐近功效与初始观测影响AI 解读

In this note we derive the local asymptotic power function of the standardized averaged Dickey–Fuller panel unit root statistic of Im, Pesaran, and Shin (2003, Journal of Econometrics , 115, 53–74), allowing for heterogeneous deterministic intercept terms. We consider the situation where the deviation of the initial observation from the underlying intercept term in each individual time series may not be asymptotically negligible. We find that power decreases monotonically as…

不同收敛速度估计量的合并：侧重社会互动模型的最小 χ² 方法AI 解读

This paper considers the extension of the classical minimum distance approach for the pooling of estimates with various rates of convergence. Under a setting where relatively high rates of convergence can be attained, the minimum distance estimators are shown to be consistent and asymptotically normally distributed. The constrained estimates can be efficient relative to the unconstrained ones. The minimized distance function is shown to be asymptotically χ 2 -distributed,…

面板数据模型的方差矩阵设定AI 解读

Many regression models have two dimensions, say time ( t = 1,…, T ) and households ( i = 1,…, N ), as in panel data, error components, or spatial econometrics. In estimating such models we need to specify the structure of the error variance matrix Ω , which is of dimension T N × T N . If T N is large, then direct computation of the determinant and inverse of Ω is not practical. In this note we define structures of Ω that allow the computation of its determinant and inverse,…

固定效应动态面板中在单位根处保持强工具的 GMM 估计AI 解读

This paper develops new estimation and inference procedures for dynamic panel data models with fixed effects and incidental trends. A simple consistent GMM estimation method is proposed that avoids the weak moment condition problem that is known to affect conventional GMM estimation when the autoregressive coefficient ( ρ ) is near unity. In both panel and time series cases, the estimator has standard Gaussian asymptotics for all values of ρ ∈ (−1, 1] irrespective of how the…

用于因果推断的带符号有向无环图AI 解读

Summary Formal rules governing signed edges on causal directed acyclic graphs are described and it is shown how these rules can be useful in reasoning about causality. Specifically, the notions of a monotonic effect, a weak monotonic effect and a signed edge are introduced. Results are developed relating these monotonic effects and signed edges to the sign of the causal effect of an intervention in the presence of intermediate variables. The incorporation of signed edges in…