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Inference on an extended Roy model, with an application to schooling decisions in France

扩展 Roy 模型的推断及其在法国教育选择中的应用

This paper considers the identification and estimation of an extension of Roy’s model (1951) of sectoral choice, which includes a non-pecuniary component in the selection equation and allows for uncertainty on potential earnings. We focus on the identification of the non-pecuniary component, which is key to disentangling the relative importance of monetary incentives versus preferences in the context of sorting across sectors. By making the most of the structure of the…

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Effectively Selecting a Target Population for a Future Comparative Study

为未来比较研究有效选择目标人群

When comparing a new treatment with a control in a randomized clinical study, the treatment effect is generally assessed by evaluating a summary measure over a specific study population. The success of the trial heavily depends on the choice of such a population. In this paper, we show a systematic, effective way to identify a promising population, for which the new treatment is expected to have a desired benefit, utilizing the data from a current study involving similar…

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Bayesian Hierarchical Poisson Regression Models: An Application to a Driving Study With Kinematic Events

贝叶斯层次泊松回归:青少年驾驶运动学事件研究

Although there is evidence that teenagers are at a high risk of crashes in the early months after licensure, the driving behavior of these teenagers is not well understood. The Naturalistic Teenage Driving Study (NTDS) is the first U.S. study to document continuous driving performance of newly-licensed teenagers during their first 18 months of licensure. Counts of kinematic events such as the number of rapid accelerations are available for each trip, and their incidence…

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A SMOOTH NONPARAMETRIC CONDITIONAL DENSITY TEST FOR CATEGORICAL RESPONSES

分类响应条件密度的平滑非参数检验

We propose a consistent kernel-based specification test for conditional density models when the dependent variable is categorical/discrete. The method is applicable to popular parametric binary choice models such as the logit and probit specification and their multinomial and ordered counterparts, along with parametric count models, among others. The test is valid when the conditional density function contains both categorical and real-valued covariates. Theoretical support…

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ENTRY INTO PHARMACEUTICAL SUBMARKETS: A BAYESIAN PANEL PROBIT ANALYSIS

进入医药子市场:贝叶斯面板Probit分析

SUMMARY We study entry into pharmaceutical submarkets by using a dynamic panel probit model. We develop a Bayesian version of Wooldridge's approach to dealing with unobserved heterogeneity. We distinguish between greenfield entry (entry with first product) and undifferentiated entry, which may take the form of introducing further products. We extend the standard reduced form model to consider company size in the submarket and across all submarkets. We find that greenfield…

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BENEFIT DURATION, UNEMPLOYMENT DURATION AND JOB MATCH QUALITY: A REGRESSION‐DISCONTINUITY APPROACH

失业救济期限、失业持续时间与工作匹配质量:断点回归方法

SUMMARY We use a sharp discontinuity in the maximum duration of benefit entitlement to identify the effect of extended benefit duration on unemployment duration and post‐unemployment outcomes (employment stability and re‐employment wages). We address dynamic selection, which may arise even under an initially random assignment to treatment, estimating a bivariate discrete‐time hazard model jointly with a wage equation and correlated unobservables. Owing to the…

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EUCLIDEAN REVEALED PREFERENCES: TESTING THE SPATIAL VOTING MODEL

欧氏显示偏好:空间投票模型的检验

SUMMARY In the spatial model of voting, voters choose the candidate closest to them in the ideological space. Recent work by Degan and Merlo in 2009 shows that it is falsifiable on the basis of individual voting data in multiple elections. We show how to tackle the fact that the model only partially identifies the distribution of voting profiles and we give a formal revealed preference test of the spatial voting model in three national elections in the USA, and strongly…

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THE RESPONSES OF YOUTH TO A CASH TRANSFER CONDITIONAL ON SCHOOLING: A QUASI‐EXPERIMENTAL STUDY

青少年对附带就学条件的现金转移的反应:准实验研究

SUMMARY We estimate the effect of cash transfers given to youth conditional on high school attendance on the labor supply decisions and academic performance of youth. We exploit differences in the size of the total transfer received based on timing of birth to identify the causal effects of interest. Specifically, individuals born late in a quarter receive a larger total transfer than comparable individuals born early in the following quarter. We find that the transfer…

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Panel data models with multiple time-varying individual effects

具有多个时变个体效应的面板数据模型

This paper considers a panel data model with time-varying individual effects. The data are assumed to contain a large number of cross-sectional units repeatedly observed over a fixed number of time periods. The model has a feature of the fixed-effects model in that the effects are assumed to be correlated with the regressors. The unobservable individual effects are assumed to have a factor structure. For consistent estimation of the model, it is important to estimate the…

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Consistency under sampling of exponential random graph models

指数随机图模型的抽样一致性

The growing availability of network data and of scientific interest in distributed systems has led to the rapid development of statistical models of network structure. Typically, however, these are models for the entire network, while the data consists only of a sampled sub-network. Parameters for the whole network, which is what is of interest, are estimated by applying the model to the sub-network. This assumes that the model is consistent under sampling, or, in terms of…

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Geometry of the faithfulness assumption in causal inference

因果推断中忠实性假设的几何结构

Many algorithms for inferring causality rely heavily on the faithfulness assumption. The main justification for imposing this assumption is that the set of unfaithful distributions has Lebesgue measure zero, since it can be seen as a collection of hypersurfaces in a hypercube. However, due to sampling error the faithfulness condition alone is not sufficient for statistical estimation, and strong-faithfulness has been proposed and assumed to achieve uniform or…

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Evaluating treatment protocols using data combination

利用数据组合评估处理分配规则

In real life, individuals are often assigned to binary treatments according to existing treatment protocols. Such protocols, when designed with “taste-based” motives, would be productively inefficient in that the expected returns to treatment for a marginal treatment recipient would vary across covariates and be larger for discriminated groups. This cannot be directly tested if assignment is based on more covariates than the researcher observes, because then the marginal…

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Quasi ML estimation of the panel AR(1) model with arbitrary initial conditions

任意初始条件下面板 AR(1) 模型的准最大似然估计

In this paper we show that the Quasi ML estimation method yields consistent Random and Fixed Effects estimators for the autoregression parameter ρ in the panel AR(1) model with arbitrary initial conditions and possibly time-series heteroskedasticity even when the error components are drawn from heterogeneous distributions. We investigate both analytically and by means of Monte Carlo simulations the properties of the QML estimators for ρ. The RE(Q)MLE for ρ is asymptotically…

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How Effective Were the Federal Reserve Emergency Liquidity Facilities? Evidence from the Asset‐Backed Commercial Paper Money Market Mutual Fund Liquidity Facility

美联储紧急流动性工具有多有效?资产支持商业票据流动性工具的证据

ABSTRACT The events following Lehman's failure in 2008 and the current turmoil emanating from Europe highlight the structural vulnerabilities of short‐term credit markets and the role of central banks as back‐stop liquidity providers. The Federal Reserve's response to financial disruptions in the United States importantly included the creation of liquidity facilities. Using a differences‐in‐differences approach, we evaluate one of the most unusual of these interventions—the…

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Search With Dirichlet Priors: Estimation and Implications for Consumer Demand

Dirichlet 先验下的搜寻:估计与消费者需求含义

This article is an empirical application of the search model with an unknown distribution, as introduced by Rothschild in 1974. For searchers who hold Dirichlet priors, we develop a novel characterization of optimal search behavior. Our solution delivers easily computable formulas for the ex-ante purchase probabilities as outcomes of search, as required by discrete-choice-based estimation. Using our method, we investigate the consequences of consumer learning on the…

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Local Linear GMM Estimation of Functional Coefficient IV Models With an Application to Estimating the Rate of Return to Schooling

函数系数工具变量模型的局部线性 GMM 估计及教育回报应用

We consider the local linear generalized method of moment (GMM) estimation of functional coefficient models with a mix of discrete and continuous data and in the presence of endogenous regressors. We establish the asymptotic normality of the estimator and derive the optimal instrumental variable that minimizes the asymptotic variance-covariance matrix among the class of all local linear GMM estimators. Data-dependent bandwidth sequences are also allowed for. We propose a…

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Arriving in Time: Estimation of English Auctions With a Stochastic Number of Bidders

利用竞标者到达时间估计人数随机的英式拍卖

We develop a new econometric approach for the estimation of second-price ascending-bid auctions with a stochastic number of bidders. Our empirical framework considers the arrival process of new bidders as well as the distribution of bidders’ valuations of objects being auctioned. By observing the timing of bidder arrival, the model is identified even when the number of potential bidders is stochastic and unknown. The relevance of our approach is illustrated with an empirical…

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ESTIMATION OF BINARY CHOICE MODELS WITH LINEAR INDEX AND DUMMY ENDOGENOUS VARIABLES

含二元内生变量的线性指数二元选择模型估计

This paper presents computationally simple estimators for the index coefficients in a binary choice model with a binary endogenous regressor without relying on distributional assumptions or on large support conditions and yields root- n consistent and asymptotically normal estimators. We develop a multistep method for estimating the parameters in a triangular, linear index, threshold-crossing model with two equations. Such an econometric model might be used in testing for…

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SEMIPARAMETRIC STRUCTURAL MODELS OF BINARY RESPONSE: SHAPE RESTRICTIONS AND PARTIAL IDENTIFICATION

二元响应半参数结构模型:形状限制与部分识别

I study the partial identifying power of structural single-equation threshold-crossing models for binary responses when explanatory variables may be endogenous. The sharp identified set of threshold functions is derived for the case in which explanatory variables are discrete, and I provide a constructive proof of sharpness. There is special attention to a widely employed semiparametric shape restriction, which requires the threshold-crossing function to be a monotone…

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A SMOOTH TEST FOR THE EQUALITY OF DISTRIBUTIONS

分布相等性的平滑检验

The two-sample version of the celebrated Pearson goodness-of-fit problem has been a topic of extensive research, and several tests like the Kolmogorov-Smirnov and Cramér-von Mises have been suggested. Although these tests perform fairly well as omnibus tests for comparing two probability density functions (PDFs), they may have poor power against specific departures such as in location, scale, skewness, and kurtosis. We propose a new test for the equality of two PDFs based on…

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A nonparametric prior for simultaneous covariance estimation

用于同时协方差估计的非参数先验

In the modeling of longitudinal data from several groups, appropriate handling of the dependence structure is of central importance. Standard methods include specifying a single covariance matrix for all groups or independently estimating the covariance matrix for each group without regard to the others, but when these model assumptions are incorrect, these techniques can lead to biased mean effects or loss of efficiency, respectively. Thus, it is desirable to develop…

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Bias attenuation results for nondifferentially mismeasured ordinal and coarsened confounders

非差异性误测的有序及粗化混杂变量的偏差衰减结果

Suppose we are interested in the effect of a binary treatment on an outcome where that relationship is confounded by an ordinal confounder. We assume that the true confounder is not observed, rather we observe a nondifferentially mismeasured version of it. We show that under certain monotonicity assumptions about its effect on the treatment and on the outcome, an effect measure controlling for the mismeasured confounder will fall between its corresponding crude and the true…

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Unified inference for sparse and dense longitudinal models

稀疏与密集纵向模型的统一推断

In longitudinal data analysis, statistical inference for sparse data and dense data could be substantially different. For kernel smoothing estimate of the mean function, the convergence rates and limiting variance functions are different under the two scenarios. The latter phenomenon poses challenges for statistical inference as a subjective choice between the sparse and dense cases may lead to wrong conclusions. We develop self-normalization based methods that can adapt to…

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Adjusting Treatment Effect Estimates by Post-Stratification in Randomized Experiments

随机实验中通过后分层调整处理效应估计

Summary Experimenters often use post-stratification to adjust estimates. Post-stratification is akin to blocking, except that the number of treated units in each stratum is a random variable because stratification occurs after treatment assignment. We analyse both post-stratification and blocking under the Neyman–Rubin model and compare the efficiency of these designs. We derive the variances for a post-stratified estimator and a simple difference-in-means estimator under…

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