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Income Variance Dynamics and Heterogeneity

收入方差动态与异质性

Recent theoretical work has shown the importance of measuring microeconomic uncertainty for models of both general and partial equilibrium under imperfect insurance. In this paper the assumption of i.i.d. income innovations used in previous empirical studies is removed and the focus of the analysis is placed on models for the conditional variance of income shocks, which is related to the measure of risk emphasized by the theory. We first discriminate amongst various models…

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An Empirical Bayes Procedure for Improving Individual-Level Estimates and Predictions From Finite Mixtures of Multinomial Logit Models

改善多项Logit有限混合模型个体估计与预测的经验贝叶斯方法

with by specifying either a multinomial or a normal distribution of the coefficients, leading to finite mixture logit and mixed logit models. Focusing on the former, we show that individual-level estimates and predictions of finite mixtures estimated by maximizing the likelihood function can be improved through integration over the estimation error of the hyperparameters, using an empirical Bayes approach. We investigate the conjecture that this approach is more robust…

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How Do Behavioral Assumptions Affect Structural Inference? Evidence From a Laboratory Experiment

行为假设如何影响结构推断?来自实验室实验的证据

rational expectations has on structural inference in a dynamic discrete decision problem. Our design induces preferences up to the subjective rate of time preference, leaving unrestricted both this parameter and subjects' decision rules. We estimate subjects' discount rates under the assumption that all subjects use the rational expectations decision rule, and under weaker behavioral assumptions that allow decision rule heterogeneity. We find that certain sophisticated…

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Financial Constraints and Farm Investment

融资约束与农场投资

This study contributes to the q-based empirical investment literature by using a Bayesian approach to analyze the impact of internal financial variables on a q-based investment model, accounting specifically for variable selection and incorporating outliers explicitly within the advocated modeling framework. For the balanced panel analyzed, a farm's liquidity situation is found to affect its investment significantly. Incorporation of an outlier detection component changes…

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Nonparametric estimation of large covariance matrices of longitudinal data

纵向数据大规模协方差矩阵的非参数估计

Estimation of an unstructured covariance matrix is difficult because of its positive‐definiteness constraint. This obstacle is removed by regressing each variable on its predecessors, so that estimation of a covariance matrix is shown to be equivalent to that of estimating a sequence of varying‐coefficient and varying‐order regression models. Our framework is similar to the use of increasing‐order autoregressive models in approximating the covariance matrix or the spectrum…

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Matching conditional and marginal shapes in binary random intercept models using a bridge distribution function

用桥接分布匹配二元随机截距模型的条件与边际函数形式

SUMMARY Random effects logistic regression models are often used to model clustered binary response data. Regression parameters in these models have a conditional, subject-specific interpretation in that they quantify regression effects for each cluster. Very often, the logistic functional shape conditional on the random effects does not carry over to the marginal scale. Thus, parameters in these models usually do not have an explicit marginal, population-averaged…

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Standard error correction in two‐stage estimation with nested samples

嵌套样本两阶段估计的标准误修正

Data at different levels of aggregation are often used in two-stage estimation, with estimates obtained at the higher level of aggregation entering the estimation at the lower level of aggregation. An example is customers within markets: first-stage estimates on market data provide variables that enter the second-stage model on customers. We derive the asymptotic covariance matrix of the second-stage estimates for situations such as these. We implement the formulae in the…

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Censored Regression Quantiles

删失回归分位数

Using quantile regression to analyze survival times offers an valuable complement to traditional Cox proportional hazards modelling. Unfortunately, this approach has been hampered by the lack of a conditional quantile estimator for censored data that is directly analogous to the Kaplan–Meier estimator and applies under standard assumptions for censored regression models. Here a recursively reweighted estimator of the regression quantile process is developed as a direct…

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Statistical Models and Bioterrorism

统计模型与生物恐怖袭击

In the fall of 2001 an outbreak of inhalational anthrax occurred in the United States that was the result of bioterrorism. Letters contaminated with anthrax spores were sent through the postal system. In response to the outbreak, public health officials treated over 10,000 persons with antibiotic prophylaxis in the hopes of preventing further morbidity and mortality. No persons receiving the antibiotics subsequently developed disease. The question arises as to how many cases…

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Accommodating Stochastic Departures from Percentile Invariance in Causal Models

因果模型中对百分位不变性随机偏离的处理

Summary Consider a clinical trial in which participants are randomized to a single-dose treatment or a placebo control and assume that the adherence level is accurately recorded. If the treatment is effective, then good adherers in the treatment group should do better than poor adherers because they received more drug; the treatment group data follow a dose–response curve. But, good adherers to the placebo often do better than poor adherers, so the observed…

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Causal Inference with Generalized Structural Mean Models

使用广义结构均值模型进行因果推断

Summary We estimate cause–effect relationships in empirical research where exposures are not completely controlled, as in observational studies or with patient non-compliance and self-selected treatment switches in randomized clinical trials. Additive and multiplicative structural mean models have proved useful for this but suffer from the classical limitations of linear and log-linear models when accommodating binary data. We propose the generalized structural mean model to…

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Effects of Environmental Regulations on Manufacturing Plant Births: Evidence from a Propensity Score Matching Estimator

环境规制对制造业工厂新设的影响:倾向得分匹配估计的证据

This study examines the effects of air quality regulation on economic activity. Anecdotal evidence and some recent empirical studies suggest that an inverse relationship exists between the stringency of environmental regulations and new plant formations. Using a unique county-level data set for New York State from 1980 to 1990, we revisit this conjecture using a seminonparametric method based on propensity score matching. Our empirical estimates suggest that…

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Bayesian inference for the mover–stayer model in continuous time with an application to labour market transition data

连续时间流动者—留驻者模型的贝叶斯推断及劳动市场转移应用

Abstract This paper presents Bayesian inference procedures for the continuous time mover–stayer model applied to labour market transition data collected in discrete time. These methods allow us to derive the probability of embeddability of the discrete‐time modelling with the continuous‐time one. A special emphasis is put on two alternative procedures, namely the importance sampling algorithm and a new Gibbs sampling algorithm. Transition intensities, proportions of stayers…

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Iterative and Recursive Estimation in Structural Nonadaptive Models

结构非自适应模型的迭代与递归估计

appears well suited for econometric models where the structural relationships of interest define the observed endogenous variables as a known function of unobserved state variables and unknown parameters. This nonlinear state-space specification paves the way for iterative or recursive EM-like strategies. In the E steps, the state variables are forecasted given the observations and a value of the parameters. In the M steps, these forecasts are used to deduce estimators of…

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Estimating subject-specific survival functions under the accelerated failure time model

加速失效时间模型下的个体生存函数估计

We use the semiparametric accelerated failure time model to predict the survival function and its related quantities for future subjects with a given set of covariates. We derive the large‐sample distribution for the subject‐specific cumulative hazard function estimate. We then propose a simple resampling technique for constructing pointwise confidence intervals and simultaneous bands for the corresponding survival function and its quantile function over a properly selected…

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Uniform consistency in causal inference

因果推断中的一致一致性

There is a long tradition of representing causal relationships by directed acyclic graphs (Wright, 1934). Spirtes (1994), Spirtes et al. (1993) and Pearl & Verma (1991) describe procedures for inferring the presence or absence of causal arrows in the graph even if there might be unobserved confounding variables, and/or an unknown time order, and that under weak conditions, for certain combinations of directed acyclic graphs and probability distributions, are asymptotically,…

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Rank-based regression with repeated measurements data

重复测量数据的秩回归

A rank‐based regression method is proposed for repeated measurements data. It is a generalisation of the classical Wilcoxon–Mann–Whitney rank statistic for independent observations. The method is valid under a weak condition on the error terms that can accommodate certain heteroscedasticity and within‐subject dependency. The asymptotic normality of the proposed estimator is proved using empirical process theory. A variance estimator, shown to be consistent, is also…

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Order-Preserving Nonparametric Regression, With Applications to Conditional Distribution and Quantile Function Estimation

保序非参数回归及其条件分布与分位数函数估计应用

In some regression problems we observe a “response” Yti to level t of a “treatment” applied to an individual with level Xi of a given characteristic, where it has been established that response is monotone increasing in the level of the treatment. A related problem arises when estimating conditional distributions, where the raw data are typically independent and identically distributed pairs (Xi, Zi), and Yti denotes the proportion of Zi's that do not exceed t. We expect the…

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Dynamic Latent Trait Models for Multidimensional Longitudinal Data

多维纵向数据的动态潜在特质模型

This article presents a new approach for analysis of multidimensional longitudinal data, motivated by studies using an item response battery to measure traits of an individual repeatedly over time. A general modeling framework is proposed that allows mixtures of count, categorical, and continuous response variables. Each response is related to age-specific latent traits through a generalized linear model that accommodates item-specific measurement errors. A transition model…

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How Much Does the Far Future Matter? A Hierarchical Bayesian Analysis of the Public's Willingness to Mitigate Ecological Impacts of Climate Change

遥远未来有多重要?公众减缓气候生态影响意愿的层级贝叶斯分析

How much does the far future matter? This question lies at the heart of many important environmental policy issues, such as global climate change, biodiversity loss, and the disposal of radioactive waste. Although philosophers, experts, and others offer their viewpoints on this deep question, the solution to many environmental problems lies in the willingness of the public to bear significant costs now to make the far future a better place. Short of national plebiscites, the…

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The Nonparametric Identification of Treatment Effects in Duration Models

持续期模型中处理效应的非参数识别

This paper analyzes the specification and identification of causal multivariate duration models. We focus on the case in which one duration concerns the point in time a treatment is initiated and we are interested in the effect of this treatment on some outcome duration. We define “no anticipation of treatment” and relate it to a common assumption in biostatistics. We show that (i) no anticipation and (ii) randomized treatment assignment can be imposed without restricting…

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Estimation of a Dynamic Auction Game

动态拍卖博弈的估计

This paper proposes an estimation method for a repeated auction game under the presence of capacity contraints.The estimation strategy is computationally simple as it does not require solving for the equilibrium of the game.It uses a two stage approach.In the first stage the distribution of bids conditional on state variables is estimated using data on bids, bidder characteristics and contract characteristics.In the second stage, an expression of the expected sum of future…

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