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Asymptotic Distributions of Quasi-Maximum Likelihood Estimators for Spatial Autoregressive Models

空间自回归模型准最大似然估计量的渐近分布

This paper investigates asymptotic properties of the maximum likelihood estimator and the quasi-maximum likelihood estimator for the spatial autoregressive model. The rates of convergence of those estimators may depend on some general features of the spatial weights matrix of the model. It is important to make the distinction with different spatial scenarios. Under the scenario that each unit will be influenced by only a few neighboring units, the estimators may have -rate…

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Polarization: Concepts, Measurement, Estimation

极化:概念、测量与估计

We develop the measurement theory of polarization for the case in which income distributions can be described using density functions. The main theorem uniquely characterizes a class of polarization measures that fits into what we call the “identity-alienation” framework, and simultanously satisfies a set of axioms. Second, we provide sample estimators of population polarization indices that can be used to compare polarization across time or entities. Distribution-free…

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Dynamics of the federal funds target rate: a nonstationary discrete choice approach

联邦基金目标利率动态:非平稳离散选择方法

Abstract We apply a discrete choice approach to model the empirical behaviour of the Federal Reserve in changing the federal funds target rate, the benchmark of short‐term market interest rates in the US. Our methods allow the explanatory variables to be nonstationary as well as stationary. This feature is particularly useful in the present application as many economic fundamentals that are monitored by the Fed and are believed to affect decisions to adjust interest rate…

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Robust nonparametric inference for the median

中位数的稳健非参数推断

We consider the problem of constructing robust nonparametric confidence intervals and tests of hypothesis for the median when the data distribution is unknown and the data may contain a small fraction of contamination. We propose a modification of the sign test (and its associated confidence interval) which attains the nominal significance level (probability coverage) for any distribution in the contamination neighborhood of a continuous distribution. We also define some…

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Dynamics and Seasonality in Quarterly Panel Data

季度面板数据中的动态与季节性

This article presents an empirical analysis of the dynamics of individual earnings using Spanish quarterly earnings. I propose a new econometric methodology to control for the seasonality in my dataset. Moreover, I apply this methodology to the study of earnings mobility in Spain, using transition probabilities among earnings quintiles for the period 1985–1996. I find substantial mobility from one year to the next; however, earnings changes are basically among adjacent…

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NONPARAMETRIC IDENTIFICATION OF LATENT COMPETING RISKS MODELS

潜在竞争风险模型的非参数识别

This paper shows that nonparametric identification of latent competing risks models is possible without the usual conditional independence and exclusion restrictions.The authors thank Jinyong Hahn, James Heckman, and Shinichi Sakata for useful discussions on the subject matter of this paper. Any errors are the fault of the authors. Research funding for Rilstone was provided by the Social Sciences and Humanities Research Council of Canada.

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Nonlinear and Nonparametric Regression and Instrumental Variables

We consider regression when the predictor is measured with error and an instrumental variable (IV) is available. The regression function can be modeled linearly, nonlinearly, or nonparametrically. Our major new result shows that the regression function and all parameters in the measurement error model are identified under relatively weak conditions, much weaker than previously known to imply identifiability. In addition, we exploit a characterization of the IV estimator as a…

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New Estimation and Model Selection Procedures for Semiparametric Modeling in Longitudinal Data Analysis

纵向数据半参数建模的新估计与模型选择程序

Semiparametric regression models are very useful for longitudinal data analysis. The complexity of semiparametric models and the structure of longitudinal data pose new challenges to parametric inferences and model selection that frequently arise from longitudinal data analysis. In this article, two new approaches are proposed for estimating the regression coefficients in a semiparametric model. The asymptotic normality of the resulting estimators is established. An…

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Exact and Approximate Inferences for Nonlinear Mixed-Effects Models With Missing Covariates

协变量缺失的非线性混合效应模型:精确与近似推断

Nonlinear mixed-effects (NLME) models are popular in many longitudinal studies, including human immunodeficiency virus (HIV) viral dynamics, pharmacokinetic analyses, and studies of growth and decay. In practice, covariates in these studies often contain missing data, and so standard complete-data methods are not directly applicable. In this article we propose Monte Carlo parameter-expanded (PX)-EM algorithms for exact and approximate likelihood inferences for NLME models…

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Causal Inference With General Treatment Regimes

一般处理机制下的因果推断

In this article we develop the theoretical properties of the propensity function, which is a generalization of the propensity score of Rosenbaum and Rubin. Methods based on the propensity score have long been used for causal inference in observational studies; they are easy to use and can effectively reduce the bias caused by nonrandom treatment assignment. Although treatment regimes need not be binary in practice, the propensity score methods are generally confined to…

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Unbiased Estimating Equations From Working Correlation Models for Irregularly Timed Repeated Measures

不规则时点重复测量中由工作相关模型构造无偏估计方程

The method of generalized estimating equations (GEEs) has been criticized recently for a failure to protect against misspecification of working correlation models, which in some cases leads to loss of efficiency or infeasibility of solutions. However, the feasibility and efficiency of GEE methods can be enhanced considerably by using flexible families of working correlation models. We propose two ways of constructing unbiased estimating equations from general correlation…

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Unit Root Quantile Autoregression Inference

单位根分位数自回归推断

We study statistical inference in quantile autoregression models when the largest autoregressive coefficient may be unity. The limiting distribution of a quantile autoregression estimator and its t-statistic is derived. The asymptotic distribution is not the conventional Dickey–Fuller distribution, but rather a linear combination of the Dickey–Fuller distribution and the standard normal, with the weight determined by the correlation coefficient of related time series.…

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Wavelet-Based Testing for Serial Correlation of Unknown Form in Panel Models

面板模型中未知形式序列相关的小波检验

Wavelet analysis is a new mathematical method developed as a unified field of science over the last decade or so. As a spatially adaptive analytic tool, wavelets are useful for capturing serial correlation where the spectrum has peaks or kinks, as can arise from persistent dependence, seasonality, and other kinds of periodicity. This paper proposes a new class of generally applicable wavelet-based tests for serial correlation of unknown form in the estimated residuals of a…

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Likelihood Estimation and Inference in a Class of Nonregular Econometric Models

一类非正规计量经济模型中的似然估计与推断

We study inference in structural models with a jump in the conditional density, where location and size of the jump are described by regression curves. Two prominent examples are auction models, where the bid density jumps from zero to a positive value at the lowest cost, and equilibrium job-search models, where the wage density jumps from one positive level to another at the reservation wage. General inference in such models remained a long-standing, unresolved problem,…

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Making inferences about the polarization, welfare and poverty of nations: a study of 101 countries 1970–1995

国家间极化、福利与贫困的推断:101 国研究

Abstract Stochastic Dominance techniques are adapted and employed to study the extent and progress of Polarization, Welfare and Poverty of 101 nations over the period 1970–1995. The adaptations provide methods of comparing mass relocation by evaluating various degrees of right and left separation between distributions. The results reveal that, whilst welfare increased and then diminished and poverty diminished and then increased, polarization between rich and poor countries…

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Analysis of Longitudinal Data with Irregular, Outcome-Dependent Follow-Up

随访时间不规则且依赖结局的纵向数据分析

Summary A frequent problem in longitudinal studies is that subjects may miss scheduled visits or be assessed at self-selected points in time. As a result, observed outcome data may be highly unbalanced and the availability of the data may be directly related to the outcome measure and/or some auxiliary factors that are associated with the outcome. If the follow-up visit and outcome processes are correlated, then marginal regression analyses will produce biased estimates.…

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The Effects of 401(K) Participation on the Wealth Distribution: An Instrumental Quantile Regression Analysis

401(k)参与对财富分布的影响:工具变量分位数回归分析

We use instrumental quantile regression approach to examine the effects of 401(k) plans on wealth using data from the Survey of Income and Program Participation. Using 401(k) eligibility as an instrument for 401(k) participation, we estimate the quantile treatment effects of participation in a 401(k) plan on several measures of wealth. The results show the effects of 401(k) participation on net financial assets are positive and significant over the entire range of the asset…

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Estimating the Elasticity of Intertemporal Substitution When Instruments Are Weak

弱工具变量下跨期替代弹性的估计

In the instrumental variables (IV) regression model, weak instruments can lead to bias in estimators and size distortion in hypothesis tests. This paper examines how weak instruments affect the identification of the elasticity of intertemporal substitution (EIS) through the linearized Euler equation. Conventional IV methods result in an empirical puzzle that the EIS is significantly less than 1 but its reciprocal is not different from 1. This paper shows that weak…

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Estimating the social return to higher education: evidence from longitudinal and repeated cross-sectional data

估计高等教育的社会回报:来自纵向与重复横截面数据的证据

Economists have speculated for at least a century that the social return to education may exceed the private return. In this paper, I estimate spillovers from college education by comparing wages for otherwise similar individuals who work in cities with different shares of college graduates in the labor force. OLS estimates show a large positive relationship between the share of college graduates in a city and individual wages, over and above the private return to education.…

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Efficient Semiparametric Estimation of Censored and Truncated Regressions via a Smoothed Self-Consistency Equation

An asymptotically efficient likelihood-based semiparametric estimator is derived for the censored regression (tobit) model, based on a new approach for estimating the density function of the residuals in a partially observed regression. Smoothing the self-consistency equation for the nonparametric maximum likelihood estimator of the distribution of the residuals yields an integral equation, which in some cases can be solved explicitly. The resulting estimated density is…

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Statistical Treatment Rules for Heterogeneous Populations

An important objective of empirical research on treatment response is to provide decision makers with information useful in choosing treatments. Manski (2000, 2002, 2003) showed how identification problems generate ambiguity about the identity of optimal treatment choices. This paper studies treatment choice using sample data. I consider a planner who must choose among alternative statistical treatment rules, these being functions that map observed covariates of population…

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