论文检索

从不可比调查计算可比统计量：以印度贫困为例AI 解读

Applied economists are often interested in studying trends in economic indicators such as inequality or poverty; however, comparisons over time can be made impossible by changes in data collection methodology. We describe an easily implemented procedure, based on inverse probability weighting, that allows recovery of comparability of estimated parameters identified implicitly by a moment condition. The validity of the procedure requires the existence of a set of auxiliary…

通过变换回归构造分位数置信区间的修正代入法AI 解读

We propose a corrected plug-in method for constructing confidence intervals of the conditional quantiles of an original response variable through a transformed regression with heteroscedastic errors. The interval is easy to compute. Factors affecting the magnitude of the correction are examined analytically through the special case of Box–Cox regression. Monte Carlo simulations show that the new method works well in general and is superior over the commonly used delta method…

利用劳动者流动测量企业动态AI 解读

Information on firm dynamics is critical to understanding economic activity, yet is fundamentally difficult to measure. In this article we introduce a new way of capturing dynamics: following clusters of workers as they move across administrative entities. We show that a worker flow approach improves linkages across firms in longitudinal business databases. The approach also provides conceptual insights into the changing structure of businesses and employer–employee…

存在不依从且结局为二元变量的随机试验中治疗效应的估计AI 解读

Summary We propose a class of estimators of the treatment effect on a dichotomous outcome among the treated subjects within covariate and treatment arm strata in randomized trials with non-compliance. Recent papers by Vansteelandt and Goetghebeur, and Robins and Rotnitzky have presented consistent and asymptotically linear estimators of a causal odds ratio, which rely, beyond correct specification of a model for the causal odds ratio, on a correctly specified model for a…

纵向数据变系数模型的经验似然推断AI 解读

In this article local empirical likelihood-based inference for a varying coefficient model with longitudinal data is investigated. First, we show that the naive empirical likelihood ratio is asymptotically standard chi-squared when undersmoothing is employed. The ratio is self-scale invariant and the plug-in estimate of the limiting variance is not needed. Second, to enhance the performance of the ratio, mean-corrected and residual-adjusted empirical likelihood ratios are…

随机化后所选子群中生存结局比较的敏感性分析AI 解读

In some randomized studies, researchers are interested in determining the effect of treatment assignment on outcomes that may exist only in a subset chosen after randomization. For example, in preventative human immunodeficiency virus (HIV) vaccine efficacy trials, it is of interest to determine whether randomization to vaccine affects postinfection outcomes that may be right-censored. Such outcomes in these trials include time from infection diagnosis to initiation of…

协方差函数半参数估计下的纵向数据分析AI 解读

Improving efficiency for regression coefficients and predicting trajectories of individuals are two important aspects in analysis of longitudinal data. Both involve estimation of the covariance function. Yet, challenges arise in estimating the covariance function of longitudinal data collected at irregular time points. A class of semiparametric models for the covariance function is proposed by imposing a parametric correlation structure while allowing a nonparametric…

残疾与就业AI 解读

Measurement error in health and disability status has been widely accepted as a central problem in social science research. Long-standing debates about the prevalence of disability, the role of health in labor market outcomes, and the influence of federal disability policy on declining employment rates have all emphasized issues regarding the reliability of self-reported disability. In addition to random error, inaccuracy in survey datasets may be produced by a host of…

协方差平稳与单位根面板 AR(1) 模型的有效线性 GMM 估计AI 解读

This paper considers generalized method of moments (GMM) estimation of the inclusive panel AR(1) model that contains the covariance stationary panel AR(1) model and the panel AR(1) model with a unit root as special cases. The paper presents a two-step optimal linear GMM (OLGMM) estimator for the inclusive model that is asymptotically equivalent to the optimal nonlinear GMM estimator of Ahn and Schmidt (1997, Journal of Econometrics 76, 309–321) when the data are covariance…

股票持有者比非持有者更有效地分担风险吗？AI 解读

This paper analyzes the extent of risk-sharing among stockholders and nonstockholders. To evaluate the empirical importance of market incompleteness, it is essential to determine whether idiosyncratic shocks are important for the wealthy who have access to better insurance opportunities, but also face different risks, than the average household. We study a model where each period households decide whether to participate in the stock market by paying a fixed cost. Due to this…

We examine inference in panel data when the number of groups is small, as is typically the case for difference-in-differences estimation and when some variables are fixed within groups. In this case, standard asymptotics based on the number of groups going to infinity provide a poor approximation to the finite sample distribution. We show that in some cases the t-statistic is distributed as t and propose simple two-step estimators for these cases. We apply our analysis to…

市场进入成本、生产者异质性与出口动态AI 解读

As the exchange rate, foreign demand, production costs and export promotion policies evolve, manufacturing firms are continually faced with two issues: whether to be an exporter, and if so, how much to export. we develop a dynamic structural model of export supply that characterizes these two decisions and estimate the model using plant-level panel data on Colombian chemical producers. The model embodies uncertainty, plant-level heterogeneity in export profits, and sunk…

弱可分模型中的内生虚拟变量AI 解读

In this paper, we consider the nonparametric identification and estimation of the average effect of a dummy endogenous regressor in models where the regressors are weakly but not additively separable from the error term. The model is not required to be strictly increasing in the error term, and the class of models considered includes limited dependent variable models such as discrete choice models. Conditions are established conditions under which it is possible to identify…

贝叶斯密度回归AI 解读

Summary The paper considers Bayesian methods for density regression, allowing a random probability distribution to change flexibly with multiple predictors. The conditional response distribution is expressed as a non-parametric mixture of regression models, with the mixture distribution changing with predictors. A class of weighted mixture of Dirichlet process priors is proposed for the uncountable collection of mixture distributions. It is shown that this specification…

摘要暂缺

摘要暂缺

摘要暂缺

动态效率估计AI 解读

The shadow cost approach is developed in the context of the dynamic duality model of intertemporal decision making to formulate theoretical and econometric models of dynamic efficiency. The dynamic efficiency model is applied to a panel of 72 U.S. major investor-owned electric utilities using fossil fuel–fired steam electric power generation over the period 1986–1999. The major results show that most electric utilities underutilized fuel relative to the aggregated labor and…

失业与流动性约束AI 解读

Abstract We present a dynamic framework for the interaction between borrowing (liquidity) constraints and deviations of actual hours from desired hours, both measured by discrete‐valued indicators, and estimate it as a system of dynamic binary and ordered probit models with panel data from the Panel Study of Income Dynamics. We analyze a household's propensity to be liquidity constrained by means of a dynamic binary probit model. We analyze qualitative aspects of the…

失业与低工资就业的相互关联动态AI 解读

Abstract This paper examines the extent of state dependence in unemployment and the role played in this by intervening low‐wage employment. A range of dynamic random and fixed‐effects estimators are compared. Low‐wage employment is found to have almost as large an adverse effect as unemployment on future prospects and the difference in their effects is found to be insignificant. Evidence is presented that low‐wage jobs act as the main conduit for repeat unemployment and…

外包与贸易变化下的就业部门调整：动态固定效应多项 Logit 证据AI 解读

Abstract This paper analyzes the effects of trade and outsourcing on the transition probabilities of employment between sectors, using a dynamic multinomial logit framework with fixed effects. The data cover a sample of individual Austrian male workers over the period 1988–2001. Our results strongly support the view that international economic forces are important determinants of labor market turnover. In particular, an increase in the outsourcing intensity negatively…

强处理选择下匹配算法的表现评估AI 解读

Abstract This paper investigates the method of matching regarding two crucial implementation choices: the distance measure and the type of algorithm. We implement optimal full matching—a fully efficient algorithm—and present a framework for statistical inference. The implementation uses data from the NLSY79 to study the effect of college education on earnings. We find that decisions regarding the matching algorithm depend on the structure of the data: In the case of strong…

通过幂变换构建线性分位数回归AI 解读

In this article we consider the linear quantile regression model with a power transformation on the dependent variable. Like the classical Box–Cox transformation approach, it extends the applicability of linear models without resorting to nonparametric smoothing, but transformations on the quantile models are more natural due to the equivariance property of the quantiles under monotone transformations. We propose an estimation procedure and establish its consistency and…

卵巢癌治疗观察性研究中的精细平衡最小距离匹配AI 解读

In observational studies of treatment effects, matched samples have traditionally been constructed using two tools, namely close matches on one or two key covariates and close matches on the propensity score to stochastically balance large numbers of covariates. Here we propose a third tool, fine balance, obtained using the assignment algorithm in a new way. We use all three tools to construct a matched sample for an ongoing study of provider specialty in the treatment of…