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Subgroup Consistent Poverty Indices

具有子群一致性的贫困指数

It seems desirable that the overall level of poverty should fall whenever poverty decreases within some subgroup of the population and is unchanged outside that group. Yet this simple and attractive property, which we call "subgroup consistency," is violated by many of the poverty indices suggested in recent years. This paper characterizes the class of subgroup consistent poverty indices, and identifies the special features associated with this property. Copyright 1991 by…

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Empirical models of discrete games

离散博弈的实证模型

This paper develops econometric models for discrete games. Specifically, we model the payoffs of games where a researcher observes qualitative or censored information about agents' decisions and payoffs. These models extend single-person qualitative choice models introduced by McFadden (1974) and others to multiple-person choice problems. The equations describing players' equilibrium strategies depend on the game's structure and the equilibrium solution concept. We show that…

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Describing the separability properties of empirical demand systems

描述经验需求系统的可分性性质

Abstract In empirical demand analysis separability restrictions are usually imposed as maintained hypotheses. The separability inflexibility of most functional forms makes parametric tests of these restrictions appear problematic. We follow Pudney (1981) in stressing the usefulness of a description of the separable structure of preferences underlying an estimated model, and propose a non‐iterative method for the production of such a description. An illustration with…

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Some Asymptotic Results for Jackknifing the Sample Quantile

样本分位数删 d 刀切法的若干渐近结果

This note studies the asymptotic behavior of the delete-$d$ jackknife in the irregular case of a sample $p$-quantile, calculated from a sample of $n$ iid r.v.'s. Two results are obtained: (a) an almost sure rate of convergence of the delete-$d$ jackknife histogram to the normal distribution; (b) almost sure convergence of the delete-$d$ jackknife variance estimate to the asymptotic variance of the sample $p$-quantile.

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Coverage Probabilities of Bootstrap-Confidence Intervals for Quantiles

分位数自助置信区间的覆盖概率

An asymptotic expansion of length 2 is established for the coverage probabilities of confidence intervals for the underlying $q$-quantile which are derived by bootstrapping the sample $q$-quantile. The corresponding level error turns out to be of order $O(n^{-1/2})$ which is unexpectedly low. A confidence interval of even more practical use is derived by using backward critical points. The resulting confidence interval is of the same length as the one derived by ordinary…

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Quantile Estimation with a Complex Survey Design

复杂调查设计下的分位数估计

Estimation of the finite population distribution function and related statistics, such as the median and interquartile range, is considered. Large-sample properties of estimators constructed from stratified cluster samples, and properties of large-sample confidence intervals, are established. The results are obtained within the context of a sequence of finite populations generated from a superpopulation.

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Generalized Linear Models with Random Effects; a Gibbs Sampling Approach

含随机效应的广义线性模型:Gibbs 抽样方法

Generalized linear models have unified the approach to regression for a wide variety of discrete, continuous, and censored response variables that can be assumed to be independent across experimental units. In applications such as longitudinal studies, genetic studies of families, and survey sampling, observations may be obtained in clusters. Responses from the same cluster cannot be assumed to be independent. With linear models, correlation has been effectively modeled by…

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An Approximate Bartlett Adjustment for Testing the Goodness of Fit of Multinomial Regression Models

多项回归模型拟合优度检验的近似 Bartlett 调整

SUMMARY For up to four categories and given sufficient replications per design point (eight or more seem to be enough), an adjusted likelihood ratio statistic for testing the goodness of fit of multinomial regression models is proposed. This adjustment does not depend on the multinomial model used and therefore will have a wide range of applications. It is certainly useful for the proportional odds model, introduced by McCullagh. This proportional odds model is used in some…

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Segmented or Competitive Labor Markets

分割还是竞争性劳动力市场

A normal Roy model with four sectors is developed. It allows to derive tests of several assumptions on the working of the labor market: strongly or weakly competitive or segmented. It shows that more important a feature of labor markets than segmentation is the presence of comparative advantages for individuals between the various economic sectors. The model is applied to data on women's labor-force participation in the main towns of Colombia in 1980. It uses multivariate…

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Identification and Panel Data Models with Endogenous Regressors

含内生解释变量的面板数据模型识别

This paper provides sufficient conditions for the identification of both static and dynamic models containing endogenous regressors from panel data by utilizing the restrictions across time periods on the parameters. It is shown that identification is achieved under quite weak conditions even in the presence of a general pattern of correlation between the errors and the time-varying variables. Efficient estimation procedures for the models considered and some specification…

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A Functional-Form-Free Test of the Research and Development/Firm Size Relationship

Parametric testing of the relationship between research and development (R&D) and firm size is limited by the hypothesized functional form, predominantly assumed to be linear in the logarithms of both variables. With a transformation of variables, the null hypothesis of constant returns to scale can be tested employing the multiple-rank F-test procedure. The findings of this analytical approach suggest that R&D intensity varies with firm size in some industries but not in…

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There Is No Aggregation Bias: Why Macro Logit Models Work

不存在聚合偏误:聚合 Logit 模型为何有效

In this article, we examine the aggregation properties of (nested) logit models to understand their exceptional macro-level performance. The problem of aggregating micro logit models involves integrating nonlinear functions of model parameters over a distribution of consumer heterogeneity. The aggregation problem is analyzed using a mixture of analytic and simulation techniques, with the simulation experiments using actual panel data to calibrate the distribution of…

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Testing for Preference Change in Consumer Demand: An Indirectly Separable, Semiparametric Model

消费者需求中的偏好变化检验:间接可分的半参数模型

This article considers the hypothesis that preference changes may partly explain observed consumption patterns. A model is developed based on indirect weak separability. The kernel estimator of the regression function models the unknown shape of demad functions, and a parametric structure models seasonality, dynamics, and preference change. This semiparametric specification is applied to U.S. meat demand. The results support the notion that changes in consumer preferences,…

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A Monte Carlo Analysis of Alternative Estimators in Models Involving Selectivity

含选择性模型中替代估计量的蒙特卡洛分析

In a simultaneous-equation model involving selectivity, Monte Carlo and response-surface techniques are used to assess the performance of five estimators commonly applied to a behavioral equation conditioned on an endogenous binary selectivity decision. The estimators include least squares with an exogenous dummy variable for the selectivity decision, three two-stage estimators that employ the estimated probability of the selectivity decision, and full information maximum…

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A Note on Capacity Utilization and Measurement of Scale Economies

产能利用与规模经济测度札记

This article investigates the measurement of returns to scale (RTS) via a cost function in the presence of quasi-fixed inputs. Caves, Christensen, and Swanson (CCS) proposed estimation of a variable-cost function and derived a formula for computing RTS from it. This article extends the CCS results by (a) investigating the bias that would result from erroneously using a total-cost function for measuring RTS, (b) indicating that the CCS procedure for measuring scale economies…

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Modality of the restricted likelihood for spatial Gaussian random fields

Numerical simulations recently reported in the literature have shown that the profile likelihood associated with the estimation of covariance range parameters for a Gaussian field can be multimodal. Here we complement these recent results by considering covari-ances with unknown nugget, scale and range parameters. Estimation is performed in a restricted maximum likelihood framework. For unbounded sampling domains and known range parameter, conditions ensuring asymptotic…

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A general estimator of the treatment effect when the data are heavily censored

重度删失数据下处理效应的一般估计量

A generalized Hodges-Lehmann type estimator for the treatment effect in the two-sample problem with right censoring, is proposed based on an inverse-quantile-type idea using truncated versions of the Kaplan-Meier estimators over the subspace where they are consistent. Its strong consistency and asymptotic normality can be obtained, under no conditions on the uninformative censorings, and the resulting variance is easily estimable from the data. In simulation studies the…

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Relative efficiency of the log rank test within a multiplicative intensity model

乘法强度模型中对数秩检验的相对效率

SUMMARY For large-sample clinical trials with independent individuals randomly allocated to two treatment groups, in which survival times follow a log linear multiplicative intensity model with treatment group as one covariate, this paper calculates the asymptotic relative efficiency of the log rank test for treatment effect as compared with the optimal score test. The method is to exhibit the failure hazard intensity, not of proportional hazards form, obtained by ignoring…

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Maximum likelihood estimates of the fractal dimension for random spatial patterns

Two approximate maximum likelihood estimates of the fractal dimension are suggested for random point patterns and planar curves, based on the distributions of the Palm probability and the spectrum.

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Estimating a multiplicative treatment effect under biased allocation

有偏治疗分配下的乘法治疗效应估计

Suppose that, given θ, x is Poisson with mean θ, while, given θ, y is Poisson with mean αθ or βθ according as treatment 1 or treatment 2 is used. Moreover, suppose that treatment 1 is used if x < a, while treatment 2 is used if x≥ a. Under this biased allocation of treatments we give consistent estimators of the two treatment effects α and β. The method also applies when x is binomial and θ is the odds on success, and to other cases.

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