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求职理论所隐含风险率形状不等式约束下的半参数持续期模型推断AI 解读

Using a four-month panel of revised Current Population Survey data from September-December 1993, we extend the class of semiparametric hazard models of the type first studied by Prentice and Gloeckler (1978), and brought to the attention of economists by Meyer (1988, 1990), to incorporate inequality restrictions on the shape of the hazard. This extension enables us to test hypotheses regarding the shape of the hazard implied by search theory using duration data alone. These…

购买力平价中对称性与比例性的面板检验AI 解读

Purchasing power parity (PPP) is a proposition equating the nominal exchange rate to the ratio of the domestic to foreign price levels. This article employs Bayesian panel-data methods to test for PPP, in particular, the implied symmetry and proportionality conditions. Using a dataset of all the Organization for Economic Cooperation and Development member countries in the post-Bretton Woods era, I do not find support for symmetry and proportionality in PPP over time 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…

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…

参数函数的拟合检验AI 解读

General methods for testing the fit of a parametric function are proposed. The idea underlying each method is to “accept” the prescribed parametric model if and only if it is chosen by a model selection criterion. Several different selection criteria are considered, including one based on a modified version of the Akaike information criterion and others based on various score statistics. The tests have a connection with nonparametric smoothing because they use orthogonal…

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…

依赖删失下基于重复测量的治疗差异秩估计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…

非平稳面板数据的线性回归极限理论AI 解读

This paper develops a regression limit theory for nonstationary panel data with large numbers of cross section and time series observations. The limit theory allows for both sequential limits and joins limits, and the relationship between these multidimensional limits is explored. The panel structures considered allow for no time series cointegration, heterogeneous cointegration, homogeneous cointegration, and near-homogeneous cointegration. The paper explores the existence…

摘要暂缺

离散选择数据的广义可加模型AI 解读

The usual assumption of a linear-in-parameters utility function in a multinomial logit model is relaxed by a sum of one-dimensional nonparametric functions of the explanatory variables. The model generalizes the logistic regression of the generalized additive model for a binary response to a qualitative variable that can assume more than two values. Simulation studies show that the proposed method can recover underlying nonlinearity in utility of various shapes. The model is…

随机面板前沿的半参数方法及其银行业应用AI 解读

This article introduces new modeling and estimation methods designed to help mitigate problems of endogeneity and misspecification. The authors use an output distance function to model the technology of a multioutput firm. They also use results from B. U. Park and L. Simar (1995) and B. U. Park, R. C. Sickles, and L. Simar (1998) on semiparametric efficient estimation of panel models to estimate multioutput stochastic distance frontiers for which the distribution of the…

纵向数据广义线性模型中回归估计量的效率AI 解读

Liang & Zeger (1986) introduced a generalised estimating equations approach based on a 'working' correlation matrix to obtain consistent and efficient estimators of regression parameters in the class of generalised linear models for repeated measures data. As demonstrated by Crowder (1995), because of the uncertainty of definition of the working correlation matrix, the Lian-Zeger approach may in some cases lead to a complete breakdown of the estimation of the regression…

采用 CAR(1) 分布的层级模型后验分布AI 解读

We examine properties of the conditional autoregressive model, or CAR(1) model, which is commonly used to represent regional effects in Bayesian analyses of mortality rates. We consider a Bayesian hierarchical linear mixed model where the fixed effects have a vague prior such as a constant prior and the random effect follows a class of CAR(1) models including those whose joint prior distribution of the regional effects is improper. We give sufficient conditions for the…

方差分量模型中的正交性与变换AI 解读

We consider variance components and other models for repeated measures in which a general transformation is applied to the response variable. Using Cox & Reid's (1987) concept of parameter orthogonality and some approximations to the information matrix we show that the intraclass correlation coefficient in the one-way model is robust to the choice of transformation. This robustness result generalises to a vector of parameters determining the correlation structure, to more…

动态异质面板的混合均值组估计AI 解读

It is now quite common to have panels in which both T, the number of time series observations, and N, the number of groups, are quite large and of the same order of magnitude. The usual practice is either to estimate N separate regressions and calculate the coefficient means, which we call the mean group (MG) estimator, or to pool the data and assume that the slope coefficients and error variances are identical. In this article we propose an intermediate procedure, the…

含删失内生变量与选择偏差的面板模型两步估计AI 解读

This paper presents some two-step estimators for a wide range of parametric panel data models with censored endogenous variables and sample selection bias. Our approach is to derive estimates of the unobserved heterogeneity responsible for the endogeneity/selection bias to include as additional explanatory variables in the primary equation. These are obtained through a decomposition of the reduced form residuals. The panel nature of the data allows adjustment, and testing,…

摘要暂缺

面板数据中的伪回归与残差型协整检验AI 解读

In the first half of the paper I study spurious regressions in panel data. Asymptotic properties of the least-squares dummy variable (LSDV) estimator and other conventional statistics are examined. The asymptotics of LSDV estimator are different from those of the spurious regression in the pure time-series. This has an important consequence for residual-based cointegration tests in panel data, because the null distribution of residual-based cointegration tests depends on the…

事件发生不规则且存在序列相关时的时间序列截面特征价格模型误差结构AI 解读

When estimating hedonic models of housing prices, the use of time series cross‐section repeat sales data can provide improvements in estimator efficiency and correct for unobserved characteristics. However, in cases where serial correlation is present, the irregular timing of sales should also be considered. In this paper we develop a model that uses information on the timing of events to account for the sporadic occurrence of events. The model presumes that the serial…

We present an econometrically tractable life cycle labor supply model for panel data including intertemporally progressive taxes on uncertai wage and nonwge incomes. Our two‐stage fixedeffects generalized method‐of‐moments approach first extimates intretemporal and then intertemporal preferences. Specification testing domonstrates the value of incorporating joint progressive taxation of labor and nonlabor incomes, Results for prime‐age men emphasize the roles played by…