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Asymptotic Properties for a Class of Partially Identified Models

一类部分识别模型的渐近性质

We propose inference procedures for partially identified population features for which the population identification region can be written as a transformation of the Aumann expectation of a properly defined set valued random variable (SVRV). An SVRV is a mapping that associates a set (rather than a real number) with each element of the sample space. Examples of population features in this class include interval-identified scalar parameters, best linear predictors with…

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Formal and Informal Risk Sharing in LDCs: Theory and Empirical Evidence

欠发达国家的正式与非正式风险分担:理论与经验证据

We develop and estimate a model of dynamic interactions in which commitment is limited and contracts are incomplete to explain the patterns of income and consumption growth in village economies of less developed countries. Households can insure each other through both formal contracts and informal agreements, that is, self-enforcing agreements specifying voluntary transfers. This theoretical setting nests the case of complete markets and the case where only informal…

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Asymptotic Least Squares Estimators for Dynamic Games

This paper considers the estimation problem in dynamic games with finite actions. we derive the equation system that characterizes the markovian equilibria. the equilibrium equation system enables us to characterize conditions for identification. we consider a class of asymptotic least squares estimators defined by the equilibrium conditions. this class provides a unified framework for a number of well-known estimators including those by Hotz and Miller (1993) and by…

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Partial Identification in Monotone Binary Models: Discrete Regressors and Interval Data

单调二元模型的部分识别:离散回归量与区间数据

We investigate identification in semi-parametric binary regression models, y = 1(xβ+υ+ε > 0) when υ is either discrete or measured within intervals. The error term ε is assumed to be uncorrelated with a set of instruments z, ε is independent of υ conditionally on x and z, and the support of −(xβ + ε) is finite. We provide a sharp characterization of the set of observationally equivalent parameters β. When there are as many instruments z as variables x, the bounds of the…

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The Identification Power of Equilibrium in Simple Games

简单博弈中均衡假设的识别能力

We examine the identification power that (Nash) equilibrium assumptions play in conducting inference about parameters in some simple games. We focus on three static games in which we drop the Nash equilibrium assumption and instead use rationalizability as the basis for strategic play. The first example examines a bivariate discrete game with complete information of the kind studied in entry models. The second example considers the incomplete-information version of the…

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The Sensitivity of Productivity Estimates

生产率估计对方法选择的敏感性

Researchers interested in estimating productivity can choose from an array of methodologies, each with its strengths and weaknesses. This study compares productivity estimates and evaluates the extent to which the conclusions of three important productivity debates in the economic development literature are sensitive to the choice of estimation method. Five widely used techniques are considered, two nonparametric and three parametric: index numbers, data envelopment…

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Current Methods for Recurrent Events Data With Dependent Termination

存在依赖性终止时复发事件数据的现有分析方法

There has been a recent surge of interest in modeling and methods for analyzing recurrent events data with risk of termination dependent on the history of the recurrent events. To aid the future users in understanding the implications of modeling assumptions and modeling properties, we review the state of the art statistical methods and present novel theoretical properties, identifiability results and practical consequences of key modeling assumptions of several fully…

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Robust and Efficient Adaptive Estimation of Binary-Choice Regression Models

二元选择回归模型的稳健高效自适应估计

The binary-choice regression models, such as probit and logit, are used to describe the effect of explanatory variables on a binary response variable. Typically estimated by the maximum likelihood method, estimates are very sensitive to deviations from a model, such as heteroscedasticity and data contamination. At the same time, the traditional robust (high-breakdown point) methods, such as the maximum trimmed likelihood, are not applicable because, by trimming observations,…

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Bayesian Hidden Markov Modeling of Array CGH Data

阵列比较基因组杂交数据的贝叶斯隐马尔可夫建模

Genomic alterations have been linked to the development and progression of cancer. The technique of comparative genomic hybridization (CGH) yields data consisting of fluorescence intensity ratios of test and reference DNA samples. The intensity ratios provide information about the number of copies in DNA. Practical issues such as the contamination of tumor cells in tissue specimens and normalization errors necessitate the use of statistics for learning about the genomic…

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Analysis of treatment response data from eligibility designs

资格随机设计中的处理反应数据分析

In this paper, we develop and compare two alternative approaches for calculating the effect of the actual intake when treatments are randomized, but compliance with the assignment in the treatment arm is less than perfect for reasons that are correlated with the outcome. The approaches are based on different identification assumptions about these unobserved confounders. In the first approach, which stems from [Sommer, A., Zeger, S., 1991. On estimating efficacy in clinical…

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Semiparametric estimation of a binary response model with a change-point due to a covariate threshold

协变量门限引致变点的二元响应模型半参数估计

This paper is concerned with semiparametric estimation of a threshold binary response model. The estimation method considered in the paper is semiparametric since the parameters for a regression function are finite-dimensional, while allowing for heteroskedasticity of unknown form. In particular, the paper considers Manski's [Manski, Charles F., 1975. Maximum score estimation of the stochastic utility model of choice. Journal of Econometrics 3 (3), 205-228; Manski, Charles…

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Inference in panel data models under attrition caused by unobservables

不可观测因素引致样本流失时的面板模型推断

This paper concerns identification and estimation of a finite-dimensional parameter in a panel data-model under nonignorable sample attrition. Attrition can depend on second period variables which are unobserved for the attritors but an independent refreshment sample from the marginal distribution of the second period values is available. This paper shows that under a quasi-separability assumption, the model implies a set of conditional moment restrictions where the moments…

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The effect of college curriculum on earnings: An affinity identifier for non-ignorable non-response bias

大学专业与收入:利用关联程度识别非可忽略无应答偏差

We link information on graduates from many cohorts to their high-school and college records and demographics to infer the impact of college major on earnings. We develop an estimator to handle potential non-response bias and identify non-response using an affinity measure--the potential respondent's link to the survey organization. This technique is generally applicable for adjusting for unit non-response. In the earnings model estimated using the identified (for…

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The Effect of Low‐Skilled Immigration on U.S. Prices: Evidence from CPI Data

低技能移民对美国物价的影响:来自CPI数据的证据

I exploit the large variation across U.S. cities and through time in the relative size of the low-skilled immigrant population to estimate the causal effect of immigration on prices of nontraded goods and services. Using an instrumental variables strategy, I find that, at current immigration levels, a 10 percent increase in the share of low-skilled immigrants in the labor force decreases the price of immigrant-intensive services, such as housekeeping and gardening, by 2…

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SEMI-NONPARAMETRIC INTERVAL-CENSORED MIXED PROPORTIONAL HAZARD MODELS: IDENTIFICATION AND CONSISTENCY RESULTS

半非参数区间删失混合比例风险模型:识别与一致性结果

In this paper I propose estimating distributions on the unit interval semi-nonparametrically using orthonormal Legendre polynomials. This approach will be applied to the interval-censored mixed proportional hazard (ICMPH) model, where the distribution of the unobserved heterogeneity is modeled semi-nonparametrically. Various conditions for the nonparametric identification of the ICMPH model are derived. I will prove general consistency results for M -estimators of (partly)…

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Comparing smooth transition and Markov switching autoregressive models of US unemployment

美国失业率的平滑转换与马尔可夫转换自回归模型比较

Abstract Logistic smooth transition and Markov switching autoregressive models of a logistic transform of the monthly US unemployment rate are estimated by Markov chain Monte Carlo methods. The Markov switching model is identified by constraining the first autoregression coefficient to differ across regimes. The transition variable in the LSTAR model is the lagged seasonal difference of the unemployment rate. Out‐of‐sample forecasts are obtained from Bayesian predictive…

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Partial identification of probability distributions with misclassified data

误分类数据下概率分布的部分识别

This paper addresses the problem of data errors in discrete variables. When data errors occur, the observed variable is a misclassified version of the variable of interest, whose distribution is not identified. Inferential problems caused by data errors have been conceptualized through convolution and mixture models. This paper introduces the direct misclassification approach. The approach is based on the observation that in the presence of classification errors, the…

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A semi-parametric Bayesian approach to the instrumental variable problem

工具变量问题的半参数贝叶斯方法

We develop a Bayesian semi-parametric approach to the instrumental variable problem. We assume linear structural and reduced form equations, but model the error distributions non-parametrically. A Dirichlet process prior is used for the joint distribution of structural and instrumental variable equations errors. Our implementation of the Dirichlet process prior uses a normal distribution as a base model. It can therefore be interpreted as modeling the unknown joint…

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Local polynomial estimation of nonparametric simultaneous equations models

非参数联立方程模型的局部多项式估计

We define a new procedure for consistent estimation of nonparametric simultaneous equations models under the conditional mean independence restriction of Newey et al. [1999. Nonparametric estimation of triangular simultaneous equation models. Econometrica 67, 565-603]. It is based upon local polynomial regression and marginal integration techniques. We establish the asymptotic distribution of our estimator under weak data dependence conditions. Simulation evidence suggests…

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Weak identification robust tests in an instrumental quantile model

工具变量分位数模型中的弱识别稳健检验

We develop a testing procedure that is robust to identification quality in an instrumental quantile model. In order to reduce the computational burden, a multi-step approach is taken, and a two-step Anderson-Rubin (AR) statistic is considered. We then propose an orthogonal decomposition of the AR statistic, where the null distribution of each component does not depend on the assumption of a full rank of the Jacobian. Power experiments are conducted, and inferences on returns…

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Identification and estimation of nonlinear models with misclassification error using instrumental variables: A general solution

利用工具变量识别和估计含误分类误差的非线性模型:一般解法

This paper provides a general solution to the problem of identification and estimation of nonlinear models with misclassification error in a general discrete explanatory variable using instrumental variables. The misclassification error is allowed to be correlated with all the explanatory variables in the model. It is not enough to identify the model by simply generalizing the identification in the binary case with a claim that the number of restrictions is no less than that…

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Analyst coverage and earnings management

分析师覆盖与盈余管理

What is the role of information intermediaries in corporate governance? This paper examines equity analysts' influence on managers' earnings management decisions. Do analysts serve as external monitors to managers, or do they put excessive pressure on managers? Using multiple measures of earnings management, I find that firms followed by more analysts manage their earnings less. To address the potential endogeneity problem of analyst coverage, I use two instrumental…

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Estimating deformations of isotropic Gaussian random fields on the plane

平面各向同性高斯随机场的形变估计

This paper presents a new approach to the estimation of the deformation of an isotropic Gaussian random field on ℝ2 based on dense observations of a single realization of the deformed random field. Under this framework we investigate the identification and estimation of deformations. We then present a complete methodological package—from model assumptions to algorithmic recovery of the deformation—for the class of nonstationary processes obtained by deforming isotropic…

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Bounds for Bayesian order identification with application to mixtures

贝叶斯阶数识别的误差界及其混合模型应用

The efficiency of two Bayesian order estimators is studied. By using nonparametric techniques, we prove new underestimation and overestimation bounds. The results apply to various models, including mixture models. In this case, the errors are shown to be O(e−an) and $O((\log n)^{b}/\sqrt{n})$ (a, b>0), respectively.

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