论文检索

用广义断点回归设计评估加利福尼亚州囚犯分类系统AI 解读

Published studies using the regression discontinuity design have been limited to cases in which linear regression is applied to a categorical treatment indicator and an equal interval outcome. This is unnecessarily narrow. We show here how a generalization the usual regression discontinuity design can be applied in a wider range of situations. We focus on the use of categorical treatment and response variables, but we also consider the more general case of any regression…

用广义断点回归设计评估加州囚犯分类制度AI 解读

Published studies using the regression discontinuity design have been limited to cases in which linear regression is applied to a categorical treatment indicator and an equal interval outcome. This is unnecessarily narrow. We show here how a generalization the usual regression discontinuity design can be applied in a wider range of situations. We focus on the use of categorical treatment and response variables, but we also consider the more general case of any regression…

非动态面板中的门槛效应：估计、检验与推断AI 解读

Threshold regression methods are developed for non-dynamic panels with individual-specific fixed effects. Least squares estimation of the threshold and regression slopes is proposed using fixed-effects transformations. A non-standard asymptotic theory of inference is developed which allows construction of confidence intervals and testing of hypotheses. The methods are applied to a 15-year sample of 565 US firms to test whether financial constraints affect investment…

固定效应动态面板模型的初始条件有多大信息量？AI 解读

I consider estimation of the autoregressive panel model with fixed effects yit=ci+βyi,t−1+εit. I investigate the estimation method developed by Blundell and Bond (1998), which makes use of the stationarity of the initial levels. I do it by numerically comparing the semiparametric information bounds for the case that incorporates the stationarity of the initial condition and for the case that does not. It is found that the efficiency gain can be substantial.

具有 AR(1) 扰动的不等间隔面板数据回归AI 解读

This paper deals with the estimation of unequally spaced panel data regression models with AR(1) remainder disturbances. A feasible generalized least squares (GLS) procedure is proposed as a weighted least squares that can handle a wide range of unequally spaced panel data patterns. This procedure is simple to compute and provides natural estimates of the serial correlation and variance components parameters. The paper also provides a locally best invariant test for zero…

已婚女性跨期劳动参与中的状态依赖、序列相关与异质性AI 解读

The intertemporal labor force participation of married women is analyzed using a dynamic search framework. Maximum simulated likelihood (MSL) estimation is used to estimate dynamic Probit models, and the sensitivity to alternative assumptions examined using Linear Probability models. Participation decisions are characterized by significant positive state dependence, unobserved heterogeneity, and negatively correlated errors. The hypothesis that women's participation is…

对称最低价密封投标拍卖：共同价值与独立私人价值范式的后验赔率比较AI 解读

I attempt to decide, using the posterior odds ratio, whether the symmetric common-value paradigm or the symmetric independent-private-values paradigm is a more probable explanation of the low-price, sealed-bid auctions conducted by the Indian Oil Corporation to purchase crude-oil from the international market. The estimation approach is structural parametric. The auctions are modelled as static non-cooperative games of incomplete information with risk neutral bidders. I…

劳动供给实证模型中相互依赖行为的识别AI 解读

In this paper we test a particular form of interdependent behaviour, namely the hypothesis that individuals' choices of hours of work are influenced by the average hours of work in a social reference group. There are problems in empirically disentangling the effects of interdependent behaviour and preference variation across groups. We show that panel data or data from several points in time are needed. In the empirical analysis we combine cross-section data from 1973, 1980,…

删失回归模型中的尾部信息迁移AI 解读

Consider a heteroscedastic regression model $Y = m(X) + \sigma(X)\varepsilon$, where the functions $m$ and $\sigma$ are “smooth,” and $\varepsilon$ is independent of $X$. The response variable $Y$ is subject to random censoring, but it is assumed that there exists a region of the covariate $X$ where the censoring of $Y$ is “light.” Under this condition, it is shown that the assumed nonparametric regression model can be used to transfer tail information from regions of light…

摘要暂缺

允许零支付意愿的二元选择条件估值模型AI 解读

Dichotomous-choice contingent-valuation data are modeled using a mixture distribution. The standard parametric survival model is modified such that respondents in the lowest willingness-to-pay category may have either zero willingness to pay or a small positive willingness to pay. In comparison to the standard model, the mixture model leads to a dramatic reduction in estimates of mean willingness to pay. Covariates such as income are found to be more significant in…

内生处理效应模型的估计与解释AI 解读

This article examines the relationship between two alternative approaches, instrumental variables and control function procedures, for estimating the impact of endogenous treatment effects. Although it is well known that the two approaches generate comparable estimates, the relationship between the estimators and their accompanying endogeneity tests appears not to be well understood. We show that the two procedures are closely related. We also examine the implications of the…

定性响应时间序列的条件异方差：银行最优惠贷款利率的吉布斯抽样分析AI 解读

Previous time series applications of qualitative response models have ignored features of the data, such as conditional heteroscedasticity, that are routinely addressed in time series econometrics of financial data. This article addresses this issue by adding Markov-switching heteroscedasticity to a dynamic ordered probit model of discrete changes in the bank prime lending rate and estimating via the Gibbs sampler. The dynamic ordered probit model of Eichengreen, Watson, and…

杂论：纵向数据的随机系数自回归模型AI 解读

Stable autoregressive models with exogenous covariates can be used to mimic nonstationary, stabilising growth profiles in longitudinal data. If different individuals have very different trajectories, the autoregressive parameters can be interpreted as random variables varying from one individual to the next. If all random effects are assumed Gaussian, the model with be quite easy to estimate although the marginal distributions of the observations will no longer be Gaussian.…

纵向数据的半参数加性回归模型AI 解读

In previous work we have studied a nonparametric additive time-varying regression model for longitudinal data recorded at irregular intervals. The model allows the influence of each covariate to vary separately with time. For small datasets, however, only a limited number of covariates may be handled in this way. In this paper, we introduced a semiparametric regression model for longitudinal data. The influence of some of the covariates varies nonparametrically with time…

纵向数据的均值—协方差联合模型：无约束参数化AI 解读

We provide unconstrained parameterisation for and model a covariance using covariates. The Cholesky decomposition of the inverse of a covariance matrix is used to associate a unique unit lower triangular and a unique diagonal matrix with each covariance matrix. The entries of the lower triangular and the log of the diagonal matrix are unconstrained and have meaning as regression coefficients and prediction variances when regressing a measurement on its predecessors. An…

相互相关的自回归时间序列面板建模AI 解读

We propose a method of modelling panel time series data with both inter- and intra-individual correlation, and of fitting an autoregressive model to such data. Estimators are obtained by a conditional likelihood argument. If there are few observations in each series, the estimators can be dramatically improved by Burg-type estimators taking edge effects into account. The consequences of ignoring the intercorrelation term are analysed. Partial lack of consistency is…

分位数比较函数的半参数推断及其在受试者工作特征曲线中的应用AI 解读

In studies to compare two samples, more information may be available on one treatment than the other. When one population is modelled parametrically and the other nonparmetrically, we study large sample properties of a semiparametric sample quantile comparison function and show that it can have substantially smaller asymptotic variance than its nonparametric counterpart, especially near the boundaries. We describe applications to both two-sample tests and receiver operating…

次序统计量之差与学生化样本分位数的鞍点近似AI 解读

Summary For a sample from a given distribution the difference of two order statistics and the Studentized quantile are statistics whose distribution is needed to obtain tests and confidence intervals for quantiles and quantile differences. This paper gives saddlepoint approximations for densities and saddlepoint approximations of the Lugannani–Rice form for tail probabilities of these statistics. The relative errors of the approximations are n −1 uniformly in a neighbourhood…

依赖删失重复测量下治疗差异的秩估计AI 解读

In comparing the effectiveness of two treatments, suppose that for each patient repeated measurements of an outcome variable are taken at prespecified time points, but some observations may be missing due to the patient's dependent right censoring. In this article, a simple rank estimation procedure, constructed based on an artificial censoring technique, is proposed for the treatment differences over time without imposing a parametric structure on the dependence between the…

利用数据驱动先验进行加性非参数回归的变量选择与函数估计AI 解读

A hierarchical Bayesian approach is proposed for variable selection and function estimation in additive nonparametric Gaussian regression models and additive nonparametric binary regression models. The prior for each component function is an integrated Wiener process resulting in a posterior mean estimate that is a cubic smoothing spline. Each of the explanatory variables is allowed to be in or out of the model, and the regression functions are estimated by model averaging.…

用自回归负多项回归模型分析多种情绪的时间变化AI 解读

This article presents an autoregressive random coefficient model with overdispersed negative multinomial marginal distributions for the analysis of heterogeneity and serial dependencies in multivariate longitudinal count data. The model structure consists of four components that take into account (a) individual difference effects, (b) random time effects, (c) multiple event categories, and (d) autodependencies. The last component is based on a stochastic integer-valued…

时变暴露对重复二元结局边际均值的因果效应估计AI 解读

We provide sufficient conditions for estimating from longitudinal data the causal effect of a time-dependent exposure or treatment on the marginal probability of response for a dichotomous outcome. We then show how one can estimate this effect under these conditions using the g-computation algorithm of Robins. We also derive the conditions under which some current approaches to the analysis of longitudinal data, such as the generalized estimating equations (GEE) approach of…

摘要暂缺