论文检索

Medigap 保险市场的激励与选择效应：Dirichlet 过程混合模型应用AI 解读

This paper presents an empirical study of endogenous treatment effects in the presence of heterogeneous responses. We estimate the incentive and selection effects of having prescription drug coverage on total drug expenditures using a sample from the Medicare Current Beneficiary Survey (MCBS). A Dirichlet process mixture (DPM) model is used to model the heterogeneity in treatment effects. Rather than estimating a finite mixture model with a fixed number of components, we…

具有内生选择的有序 Probit 模型的贝叶斯分析AI 解读

This paper presents a Bayesian analysis of an ordered probit model with endogenous selection. The model can be applied when analyzing ordered outcomes that depend on endogenous covariates that are discrete choice indicators modeled by a multinomial probit model. The model is illustrated by analyzing the effects of different types of medical insurance plans on the level of hospital utilization, allowing for potential endogeneity of insurance status. The estimation is…

含内生性的两部模型贝叶斯分析：医疗支出应用AI 解读

Abstract This paper studies the effect of managed care on medical expenditure using a model in which the insurance status is assumed to be endogenous. Insurance plan choice is modeled through the multinomial probit model. The medical expenditure variable, the outcome of interest, has a significant proportion of zeros that are handled using the two‐part model, extended to handle endogenous insurance. The estimation approach is Bayesian, based on the Gibbs Sampler. The model…

存在选择的非正态处理—结果模型：设定、模拟似然估计与医疗利用应用AI 解读

We develop a specification and estimation framework for a class of nonlinear, non-normal microeconometric models of treatment and outcome with selection. A latent factor structure is used to accommodate selection into treatment and a simulated likelihood method is used for estimation. The methodology is applied to examine the causal effect of managed care, a multinomial discrete choice process, on the utilization of health care services, measured as binary indicators and…

摘要暂缺

摘要暂缺

多元混合泊松回归的模拟最大似然估计及应用AI 解读

This paper proposes and implements simulated maximum likelihood estimation of bivariate count models with unrestricted correlation pattern of unobserved heterogeneity. The implementation incorporates both antithetic acceleration and adjustment for first-order simulation bias. Both the Monte Carlo simulation evidence and an application to health utilization data confirm that the method is reliable and feasible in data analysis.

摘要暂缺

休闲出游次数模型中的过多零值AI 解读

This article develops a modeling approach for a count data set for recreational boating trips that shows a frequency of zero counts significantly higher than that expected for Poisson distributed data. As alternatives to the Poisson regression, the authors consider several parametric and semiparametric mixed and modified Poisson models. The analysis suggests that the negative binomial hurdles model, which allows for overdispersion and also accommodates the presence of…

摘要暂缺

参数模型中的独立性检验：应用与示例AI 解读

Tests of independence between variables in discrete and continuous bivariate and multivariate regression equations are derived using series expansions of joint distributions in terms of marginal distributions and their related orthonormal polynomials. Th e tests are conditional moment tests based on covariances between pair s of orthonormal polynomials. Examples include tests of serial independence against bilinear and/or autoregressive conditional heteroskedasticity…

指数族中的变量增广设定检验AI 解读

This paper motivates, exposits, and develops the variable augmentation specification test (VAST) approach from the perspective of generalized linear exponential family, which includes several parametric families widely used in applied econometrics and statistics. The approach is equivalent to score tests and link tests and serves to both unify and simplify the computation of score tests in such models using the Engle-Davidson-MacKinnon technique of artificial regression.…

摘要暂缺

摘要暂缺

摘要暂缺

计数数据计量模型：若干估计量与检验的比较及应用AI 解读

Abstract This paper deals with specification, estimation and tests of single equation reduced form type equations in which the dependent variable takes only non‐negative integer values. Beginning with Poisson and compound Poisson models, which involve strong assumptions, a variety of possible stochastic models and their implications are discussed. A number of estimators and their properties are considered in the light of uncertainty about the data generation process. The…