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离散选择的实证福利分析：若干一般结果AI 解读

This paper develops nonparametric methods for welfare‐analysis of economic changes in the common setting of multinomial choice. The results cover (a) simultaneous price‐change of multiple alternatives, (b) introduction/elimination of an option, (c) changes in choice‐characteristics, and (d) choice among nonexclusive alternatives. In these cases, Marshallian consumer surplus becomes path‐dependent, but Hicksian welfare remains well‐defined. We demonstrate that under…

流动性的测度AI 解读

Our new approach to mobility measurement involves separating out the valuation of positions in terms of individual status (using income, social rank, or other criteria) from the issue of movement between positions. The quantification of movement is addressed using a general concept of distance between positions and a parsimonious set of axioms that characterize the distance concept and yield a class of aggregative indices. This class of indices induces a superclass of…

一致随机序的非参数拟合优度检验AI 解读

We propose $L^{p}$ distance-based goodness-of-fit (GOF) tests for uniform stochastic ordering with two continuous distributions $F$ and $G$, both of which are unknown. Our tests are motivated by the fact that when $F$ and $G$ are uniformly stochastically ordered, the ordinal dominance curve $R=FG^{-1}$ is star-shaped. We derive asymptotic distributions and prove that our testing procedure has a unique least favorable configuration of $F$ and $G$ for $p\in [1,\infty]$. We use…

瑞士顶端收入份额波动吗？重新评估1981—2010年的演变AI 解读

In the past twenty years, the share of top incomes in Switzerland has risen, while exhibiting large variations. Switzerland is similar to European countries for the top 1% but closer to the United States for higher top income groups. With the synthetic control method, we close a time gap in the tax data, exploiting the fact that Swiss cantons changed their tax system at different points in time. Using social security data, which cover all top labor incomes, we document the…

积分得分估计AI 解读

We study the properties of the integrated score estimator (ISE), which is the Laplace version of Manski’s maximum score estimator (MMSE). The ISE belongs to a class of estimators whose basic asymptotic properties were studied in Jun, Pinkse, and Wan (2015, Journal of Econometrics 187(1), 201–216). Here, we establish that the MMSE, or more precisely $$\root 3 \of n |\hat \theta _M - \theta _0 |$$ , (locally first order) stochastically dominates the ISE under the conditions…

局部平稳时间序列的分位数谱分析AI 解读

Summary Classical spectral methods are subject to two fundamental limitations: they can account only for covariance-related serial dependences, and they require second-order stationarity. Much attention has been devoted lately to quantile-based spectral methods that go beyond covariance-based serial dependence features. At the same time, covariance-based methods relaxing stationarity into much weaker local stationarity conditions have been developed for a variety of time…

因子设计中的秩方法：关于非参数处理效应的假设检验AI 解读

Summary Existing tests for factorial designs in the non-parametric case are based on hypotheses formulated in terms of distribution functions. Typical null hypotheses, however, are formulated in terms of some parameters or effect measures, particularly in heteroscedastic settings. Here this idea is extended to non-parametric models by introducing a novel non-parametric analysis-of-variance type of statistic based on ranks or pseudoranks which is suitable for testing…

非参数条件分位数估计：局部加权分位数核方法AI 解读

Nonparametric conditional cumulative distribution function (CDF) estimation has emerged as a powerful tool having widespread potential application, which has led to a literature on estimators of conditional quantile functions that are obtained via inversion of the nonparametrically estimated conditional CDF. Other nonparametric estimators of conditional quantiles that are based on an alternative characterization of the quantile (i.e., as the function that minimizes the…

动态幂律分布的非参数方法与基于局部时间的估计AI 解读

Summary This paper introduces nonparametric econometric methods that characterize general power law distributions under basic stability conditions. These methods extend the literature on power laws in the social sciences in several directions. First, we show that any stationary distribution in a random growth setting is shaped entirely by two factors: the idiosyncratic volatilities and reversion rates (a measure of cross‐sectional mean reversion) for different ranks in the…

美国信用合作社行业的多元化经济AI 解读

Summary Significant scale economies have been recently cited to rationalize a dramatic growth in the US retail credit union sector over the past few decades. In this paper, we explore another plausible supply‐side explanation for the growth of the industry, namely economies of diversification. We focus on the fact that credit unions differ among themselves in the range of financial services they offer to their members. Since larger credit unions tend to offer a more…

偏倚抽样下生存数据分位数回归的估计与推断AI 解读

Biased sampling occurs frequently in economics, epidemiology, and medical studies either by design or due to data collecting mechanism. Failing to take into account the sampling bias usually leads to incorrect inference. We propose a unified estimation procedure and a computationally fast resampling method to make statistical inference for quantile regression with survival data under general biased sampling schemes, including but not limited to the length-biased sampling,…

理解测量误差对分位数回归的影响AI 解读

The impact of measurement error in explanatory variables on quantile regression functions is investigated using a small variance approximation. The approximation shows how the error contaminated and error free quantile regression functions are related. A key factor is the distribution of the error free explanatory variable. Exact calculations probe the accuracy of the approximation. The order of the approximation error is unchanged if the density of the error free…

子组平均处理效应的差异能解释处理效应异质性吗？社会实验证据AI 解读

We assess whether welfare reform affects earnings only through mean impacts that are constant within but vary across subgroups. This is important because researchers interested in treatment effect heterogeneity typically focus on estimating mean impacts that only vary across subgroups. Using a novel approach to simulating treatment group earnings under the constant mean impacts within subgroup model, we find this model does a poor job of capturing treatment effect…

竞争风险模型中协变量效应符号的可识别性AI 解读

We present a new framework for the identification of competing risks models, which also include Roy models. We show that by establishing a Hicksian-type decomposition, the direction of covariate effects on the marginal distributions of the competing risks model can be identified under weak restrictions. Our approach leaves the marginal distributions and their joint distribution completely unspecified, except that the associated copula is invariant in the covariates. Results…

区间删失变量下加权平均导数的渐近有效估计AI 解读

This paper studies the identification and estimation of weighted average derivatives of conditional location functionals including conditional mean and conditional quantiles in settings where either the outcome variable or a regressor is interval-valued. Building on Manski and Tamer (2002, Econometrica 70(2), 519–546) who study nonparametric bounds for mean regression with interval data, we characterize the identified set of weighted average derivatives of regression…

互补性与识别AI 解读

This paper examines the identification power of assumptions that formalize the notion of complementarity in the context of a nonparametric bounds analysis of treatment response. I extend the literature on partial identification via shape restrictions by exploiting cross-dimensional restrictions on treatment response when treatments are multidimensional; the assumption of supermodularity can strengthen bounds on average treatment effects in studies of policy complementarity.…

局部分块分位数回归AI 解读

In this paper, we consider the nonparametric estimation of a broad class of quantile regression models, in which the partially linear, additive, and varying coefficient models are nested. We propose for the model a two-stage kernel-weighted least squares estimator by generalizing the idea of local partitioned mean regression (Christopeit and Hoderlein, 2006, Econometrica 74, 787–817) to a quantile regression framework. The proposed estimator is shown to have desirable…

简单、可扩展且准确的后验区间估计AI 解读

Summary Standard posterior sampling algorithms, such as Markov chain Monte Carlo procedures, face major challenges in scaling up to massive datasets. We propose a simple and general posterior interval estimation algorithm to rapidly and accurately estimate quantiles of the posterior distributions for one-dimensional functionals. Our algorithm runs Markov chain Monte Carlo in parallel for subsets of the data, and then averages quantiles estimated from each subset. We provide…

随机缺失数据下的条件矩模型AI 解读

We consider a general statistical model defined by moment restrictions when data are missing at random. Using inverse probability weighting, we show that such a model is equivalent to a model for the observed variables only, augmented by a moment condition defined by the missingness mechanism. Our framework covers parametric and semiparametric mean regressions and quantile regressions. We allow for missing responses, missing covariates and any combination of them. The…

存在样本选择时，我们能了解多少种族工资差距？AI 解读

We examine the distance and relations between the distributions of wages for two exogenously identified groups (black and white women here). The literature commonly employs decomposition methods for the conditional means, to propose explanations for observed wage differentials, as “structural” components, attributable to difference in market structures, and the “composition” components, attributable to difference in characteristics and skills. Estimation of these components…

基于Basmann加权几何均值度量的收入分布最大熵估计AI 解读

This paper introduces a new Maximum Entropy based inequality measure that is related to Basmann’s class of weighted geometric mean (WGM) measures, but with the added feature that the new measure is flexible enough to describe other characteristics of an observed income distribution function (IDF), a feature that other well-known measures do not possess. As an application, using Current Population Survey (CPS) data, we apply the new measure to Blinder and Esaki’s (1978)…

分布尾部性质的固定 k 渐近推断AI 解读

We consider inference about tail properties of a distribution from an iid sample, based on extreme value theory. All of the numerous previous suggestions rely on asymptotics where eventually, an infinite number of observations from the tail behave as predicted by extreme value theory, enabling the consistent estimation of the key tail index, and the construction of confidence intervals using the delta method or other classic approaches. In small samples, however, extreme…

遗传混合模型中的半参数推断AI 解读

In genetic backcross studies, data are often collected from complex mixtures of distributions with known mixing proportions. Previous approaches to the inference of these genetic mixture models involve parameterizing the component distributions. However, model misspecification of any form is expected to have detrimental effects. We propose a semiparametric likelihood method for genetic mixture models: the empirical likelihood under the exponential tilting model assumption,…

任意预测变量空间上的分位数平面联合估计AI 解读

In spite of the recent surge of interest in quantile regression, joint estimation of linear quantile planes remains a great challenge in statistics and econometrics. We propose a novel parameterization that characterizes any collection of noncrossing quantile planes over arbitrarily shaped convex predictor domains in any dimension by means of unconstrained scalar, vector and function valued parameters. Statistical models based on this parameterization inherit a fast…