论文检索

多元混合模型中的非参数推断AI 解读

We consider mixture models in which the components of data vectors from any given subpopulation are statistically independent, or independent in blocks. We argue that if, under this condition of independence, we take a nonparametric view of the problem and allow the number of subpopulations to be quite general, the distributions and mixing proportions can often be estimated root-n consistently. Indeed, we show that, if the data are k-variate and there are p subpopulations,…

利用泊松方差结构分析亡故供者肾移植数据的脆弱性生存模型AI 解读

In a recent study of transplant outcomes, donor age, cerebrovascular accident as the cause of death (CVA), renal insufficiency (serum creatinine >1.5 mg/dL), and history of hypertension have been identified as donor factors associated with elevated risk of kidney transplant failure. It is of great interest to know whether there remain other unmeasured donor factors associated with elevated risk of graft failure. In this article we study a sample of 6,024 deceased donor…

层级图模型AI 解读

There is continued debate regarding the exact relation between lower cholesterol levels and increased respiratory disease mortality. One of the goals of this study is to reveal the relationship between subcomponents of cholesterol and pulmonary function. We consider the subcomponents of total cholesterol, namely high-density lipoprotein cholesterol and low-density lipoprotein cholesterol, to investigate the relationship of cholesterol levels with pulmonary function in a…

多组微阵列数据的尖峰与厚尾基因选择AI 解读

DNA microarrays can provide insight into genetic changes that characterize different stages of a disease process. Accurate identification of these changes has significant therapeutic and diagnostic implications. Statistical analysis for multistage (multigroup) data is challenging, however. ANOVA-based extensions of two-sample Z-tests, a popular method for detecting differentially expressed genes in two groups, do not work well in multigroup settings. False detection rates…

离散变化下的非参数识别AI 解读

This paper provides weak conditions under which there is nonparametric interval identification of local features of a structural function that depends on a discrete endogenous variable and is nonseparable in latent variates. The function delivers values of a discrete or continuous outcome and instruments may be discrete valued. Application of the analog principle leads to quantile regression based interval estimators of values and partial differences of structural functions.…

大量弱工具变量下的一致估计AI 解读

This paper analyzes the conditions under which consistent estimation can be achieved in instrumental variables (IV) regression when the available instruments are weak and the number of instruments, Kn, goes to infinity with the sample size. We show that consistent estimation depends importantly on the strength of the instruments as measured by rn, the rate of growth of the so-called concentration parameter, and also on Kn. In particular, when Kn→∞, the concentration…

语言技能回报的非参数界限AI 解读

Abstract This paper applies the theoretical literature on nonparametric bounds on treatment effects to the estimation of how limited English proficiency (LEP) affects wages and employment opportunities for Hispanic workers in the United States. I analyse the identifying power of several weak assumptions on treatment response and selection, and stress the interactions between LEP and education, occupation and immigration status. I show that the combination of two weak but…

方向与射影形状AI 解读

This paper deals with projective shape analysis, which is a study of finite configurations of points modulo projective transformations. The topic has various applications in machine vision. We introduce a convenient projective shape space, as well as an appropriate coordinate system for this shape space. For generic configurations of k points in m dimensions, the resulting projective shape space is identified as a product of k−m−2 copies of axial spaces ℝPm. This…

面板数据的工具变量估计AI 解读

The system two stage least squares estimator for the linear panel data model is shown to have different characterizations depending on the choice of instrument matrix. The more general estimator, where, in effect, separate reduced form linear projections are estimated for each time period, also has the advantage of being applicable when the number of instruments changes across time periods. The issue of efficient estimation is also treated.

部分、弱与强识别下的广义经验似然估计与检验AI 解读

The purpose of this paper is to describe the performance of generalized empirical likelihood (GEL) methods for time series instrumental variable models specified by nonlinear moment restrictions as in Stock and Wright (2000, Econometrica 68, 1055–1096) when identification may be weak. The paper makes two main contributions. First, we show that all GEL estimators are first-order equivalent under weak identification. The GEL estimator under weak identification is inconsistent…

摘要暂缺

可能存在弱工具变量的线性结构模型中的投影统计推断AI 解读

It is well known that standard asymptotic theory is not applicable or is very unreliable in models with identification problems or weak instruments. One possible way out consists of using a variant of the Anderson–Rubin ((1949), AR) procedure. The latter allows one to build exact tests and confidence sets only for the full vector of the coefficients of the endogenous explanatory variables in a structural equation, but not for individual coefficients. This problem may in…

不假定参数已识别的 GMM 参数检验AI 解读

We propose a generalized method of moments (GMM) Lagrange multiplier statistic, i.e., the K statistic, that uses a Jacobian estimator based on the continuous updating estimator that is asymptotically uncorrelated with the sample average of the moments. Its asymptotic χ-super-2 distribution therefore holds under a wider set of circumstances, like weak instruments, than the standard full rank case for the expected Jacobian under which the asymptotic χ-super-2 distributions of…

含一个隐藏变量的路径分析模型的识别AI 解读

We study criteria for identifiability of path analysis models with one hidden variable. We first derive sufficient criteria for identification of models in which marginalisation is carried out over the hidden variable. The sufficient criteria are based on the structure of the directed acyclic graph associated with the path analysis model and can be derived from the graph. We treat further the identification of models when the hidden variable is conditioned on and establish…

摘要暂缺

摘要暂缺

企业杠杆是否不足？杠杆对违约概率的影响AI 解读

ABSTRACT A commonly held view in corporate finance is that firms are less leveraged than they should be, given the potentially large tax benefits of debt. In this paper, I study the effect of firms' leverage on default probabilities as represented by the firms' ratings. Using an instrumental variable approach, I find that the leverage's effect on ratings is three times stronger than it is if the endogeneity of leverage is ignored. This stronger effect results in a higher…

结构方程、处理效应与计量经济政策评估AI 解读

This paper uses the marginal treatment effect (MTE) to unify the nonparametric literature on treatment effects with the econometric literature on structural estimation using a nonparametric analog of a policy invariant parameter; to generate a variety of treatment effects from a common semiparametric functional form; to organize the literature on alternative estimators; and to explore what policy questions commonly used estimators in the treatment effect literature answer. A…

利用分位数回归反事实分解工资分布变化AI 解读

Abstract We propose a method to decompose the changes in the wage distribution over a period of time in several factors contributing to those changes. The method is based on the estimation of marginal wage distributions consistent with a conditional distribution estimated by quantile regression as well as with any hypothesized distribution for the covariates. Comparing the marginal distributions implied by different distributions for the covariates, one is then able to…

带辅助数据的测量误差模型AI 解读

We study the problem of parameter inference in (possibly non-linear and non-smooth) econometric models when the data are measured with error. We allow for arbitrary correlation between the true variables and the measurement errors. To solve the identification problem, we require the existence of an auxiliary data-set that contains information about the conditional distribution of the true variables given the mismeasured variables. Our main assumption requires that the…

利用企业家努力与财富检验代理理论AI 解读

ABSTRACT We develop a principal‐agent model in an entrepreneurial setting and test the model's predictions using unique data on entrepreneurial effort and wealth in privately held firms. Accounting for unobserved firm heterogeneity using instrumental‐variables techniques, we find that entrepreneurial ownership shares increase with outside wealth and decrease with firm risk; effort increases with ownership; and effort increases firm performance. The magnitude of the effects…

动态面板数据模型中的偏误修正估计AI 解读

This study develops a new bias-corrected estimator for the fixed-effects dynamic panel data model and derives its limiting distribution for finite number of time periods, T, and large number of cross-section units, N. The bias-corrected estimator is derived as a bias correction of the least squares dummy variable (within) estimator. It does not share some of the drawbacks of recently developed instrumental variables and generalized method-of-moments estimators and is…

食品消费截面与时间序列弹性的面板及伪面板估计AI 解读

This article addresses the problem of the bias of income and expenditure elasticities estimated on pseudopanel data caused by measurement error and unobserved heterogeneity. We gauge these biases empirically by comparing cross-sectional, pseudo-panel, and true panel data from both Polish and U.S. expenditure surveys. Our results suggest that unobserved heterogeneity imparts a downward bias to cross-section estimates of income elasticities of at-home food expenditures and an…

(a) Let , where Q is the fixed effects (FE) transformation given by Q = I NT − P with P = I N [otimes ] ι T ι T ′/ T .