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离散响应的混合多项 Logit 模型AI 解读

This paper considers mixed, or random coefficients, multinomial logit (MMNL) models for discrete response, and establishes the following results. Under mild regularity conditions, any discrete choice model derived from random utility maximization has choice probabilities that can be approximated as closely as one pleases by a MMNL model. Practical estimation of a parametric mixing family can be carried out by Maximum Simulated Likelihood Estimation or Method of Simulated…

纵向数据的非参数动态加性回归模型AI 解读

In this work we study additive dynamic regression models for longitudinal data. These models provide a flexible and nonparametric method for investigating the time-dynamics of longitudinal data. The methodology is aimed at data where measurements are recorded at random time points. We model the conditional mean of responses given the full internal history and possibly time-varying covariates. We derive the asymptotic distribution for a new nonparametric least squares…

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面板 Probit 中的异方差误设：GMM 与模拟最大似然的小样本比较AI 解读

This paper compares generalized method of moments (GMM) and simulated maximum likelihood (SML) approaches to the estimation of the panel probit model. Both techniques circumvent multiple integration of joint density functions without the need to restrict the error term variance-covariance matrix of the latent normal regression model. Particular attention is paid to a three-stage GMM estimator based on nonparametric estimation of the optimal instruments for given conditional…

存在误分类的二元选择模型识别AI 解读

Misclassification in binary choice (binomial response) models occurs when the dependent variable is measured with error, that is, when an actual “one” response is sometimes recorded as a zero and vice versa. This paper shows that binary response models with misclassification are semiparametrically identified, even when the probabilities of misclassification depend in unknown ways on model covariates and the distribution of the errors is unknown.

多方程模型的半参数估计AI 解读

This paper proposes a semiparametric estimator for multiple equations multiple index (MEMI) models. Examples of MEMI models include several sample selection models and the multinomial choice model. The proposed estimator minimizes the average distance between the dependent variable unconditional and conditional on an index. The estimator is √N-consistent and asymptotically normally distributed. The paper also provides a Monte Carlo experiment to evaluate the finite-sample…

观测与删失时间依赖协变量的面板计数数据回归分析AI 解读

Summary Panel count data often occur in a long-term study where the primary end point is the time to a specific event and each subject may experience multiple recurrences of this event. Furthermore, suppose that it is not feasible to keep subjects under observation continuously and the numbers of recurrences for each subject are only recorded at several distinct time points over the study period. Moreover, the set of observation times may vary from subject to subject. In…

函数线性模型的两步估计及其纵向数据应用AI 解读

Summary Functional linear models are useful in longitudinal data analysis. They include many classical and recently proposed statistical models for longitudinal data and other functional data. Recently, smoothing spline and kernel methods have been proposed for estimating their coefficient functions nonparametrically but these methods are either intensive in computation or inefficient in performance. To overcome these drawbacks, in this paper, a simple and powerful two-step…

含滞后因变量的面板离散选择模型AI 解读

In this paper, we consider identification and estimation in panel data discrete choice models when the explanatory variable set includes strictly exogenous variables, lags of the endogenous dependent variable as well as unobservable individual-specific effects. For the binary logit model with the dependent variable lagged only once, Chamberlain (1993) gave conditions under which the model is not identified. We present a stronger set of conditions under which the parameters…

单调工具变量：教育回报的应用AI 解读

Econometric analyses of treatment response commonly use instrumental variable (IV) assumptions to identify treatment effects.Yet the credibility of IV assumptions is often a matter of considerable disagreement.There is therefore good reason to consider weaker but more credible assumptions.To this end, we introduce monotone instrumental variable (MIV) assumptions and the important special case of monotone treatment selection (MTS).We study the identifying power of MIV…

联立方程模型中工具变量估计量的解释：鱼类需求的应用AI 解读

In markets where prices are determined by the intersection of supply and demand curves, standard identification results require the presence of instruments that shift one curve but not the other. These results are typically presented in the context of linear models with fixed coefficients and additive residuals. The first contribution of this paper is an investigation of the consequences of relaxing both the linearity and the additivity assumption for the interpretation of…

全球铝冶炼厂的成本与技术结构AI 解读

A cost model is developed for the estimation of several technological parameters describing the production process of aluminium smelters worldwide. The model is similar to Baltagi and Griffin's (1988), but, instead of estimating technological change using a panel data set of firms, we estimate, among other things, the vintage effect, using a cross-section of aluminium smelters in operation throughout 1994. The vintage effect is defined as the variable cost differential that…

全球铝冶炼厂的成本与技术结构AI 解读

A cost model is developed for the estimation of several technological parameters describing the production process of aluminium smelters worldwide. The model is similar to Baltagi and Griffin's (1988), but, instead of estimating technological change using a panel data set of firms, we estimate, among other things, the vintage effect, using a cross-section of aluminium smelters in operation throughout 1994. The vintage effect is defined as the variable cost differential that…

使用 GMM 自助法考察地方政府的动态行为AI 解读

Even though recent Monte Carlo evidence has shown that the use of bootstrap critical values, instead of asymptotic ones, improves the size of the tests substantially, empirical applications using GMM bootstrap techniques are largely missing. In this paper, the dynamic relationship between local government revenues and expenditures is re-investigated using GMM bootstrapping techniques on a panel of 265 Swedish municipalities over the period 1979-1987. A lag of one year is…

英国护理职业中的性别、族群、薪酬与晋升：广义有序 Probit 模型AI 解读

We analyse job grading within the UK National Health Service nursing profession, using 1994 survey data. We start from the ordered probit model, for which we develop and apply appropriate specification tests. Threshold constancy and covariate exogeneity are rejected, with important consequences for estimates of the influence of gender, ethnicity, training and career interruptions. We find little evidence of disadvantage for females relative to males, but significant…

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不依赖反事实的因果推断AI 解读

A popular approach to the framing and answering of causal questions relies on the idea of counterfactuals: Outcomes that would have been observed had the world developed differently; for example, if the patient had received a different treatment. By definition, one can never observe such quantities, nor assess empirically the validity of any modeling assumptions made about them, even though one's conclusions may be sensitive to these assumptions. Here I argue that for making…

多维纵向数据：从连续、离散或事件时间响应估计治疗效应AI 解读

Multidimensional data arise when a number of different response variables are required to measure the outcome of interest. Examples of such outcomes include quality of life, cognitive ability, and health status. The goal of this article is to develop a methodology to estimate a treatment effect from multidimensional data that have been collected longitudinally using continuous, discrete, or time-to-event responses or a mixture of these types of responses. A transformation of…

设计性缺失下的功效计算：铅暴露与注意力随访研究AI 解读

Longitudinal designs often change at critical times based on available funding, staffing, scientific opportunities, and subjects. This article presents three levels of investigation into missingness by design in a partially completed longitudinal study: Missingness that is completely at random (MCAR), at random (MAR), and nonignorable (MN). We first derive new expressions for the asymptotic variance and power based on multivariate normal data that are either MCAR or missing…

结合倾向得分匹配与预后协变量的额外调整AI 解读

Propensity score matching refers to a class of multivariate methods used in comparative studies to construct treated and matched control samples that have similar distributions on many covariates. This matching is the observational study analog of randomization in ideal experiments, but is far less complete as it can only balance the distribution of observed covariates, whereas randomization balances the distribution of all covariates, both observed and unobserved. An…

自变量无测量误差或有测量误差时的聚类数据非参数函数估计AI 解读

We consider local polynomial kernel regression with a single covariate for clustered data using estimating equations. We assume that at most m < ∞ observations are available on each cluster. In the case of random regressors, with no measurement error in the predictor, we show that it is generally the best strategy to ignore entirely the correlation structure within each cluster and instead pretend that all observations are independent. In the further special case of…

计量经济学实践：方法与应用论文集AI 解读

Part 1 Specification analysis and aggregation. Part 2 Distributed lags. Part 3 Errors in variables and panel data. Part 4 Applications. Part 5 Data issues.

长程依赖下随机加权经验过程的线性化及非线性回归分位数应用AI 解读

This paper discusses some asymptotic uniform linearity results of randomly weighted empirical processes based on long range dependent random variables. These results are subsequently used to linearize nonlinear regression quantiles in a nonlinear regression model with long range dependent errors, where the design variables can be either random or nonrandom. These, in turn, yield the limiting behavior of the nonlinear regression quantiles. As a corollary, we obtain the…