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IDENTIFICATION OF COVARIANCE STRUCTURES

协方差结构的识别

The issue of identification of covariance structures, which arises in a number of different contexts, has been so far linked to conditions on the true parameters to be estimated. In this paper, this limitation is removed.As done by Johansen (1995, Journal of Econometrics 69, 112–132) in the context of linear models, the present paper provides necessary and sufficient conditions for the identification of a covariance structure that depends only on the constraints and can…

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Causal Vaccine Effects on Binary Postinfection Outcomes

疫苗对感染后二元结局的因果效应

The effects of vaccine on postinfection outcomes, such as disease, death, and secondary transmission to others, are important scientific and public health aspects of prophylactic vaccination. As a result, evaluation of many vaccine effects condition on being infected. Conditioning on an event that occurs posttreatment (in our case, infection subsequent to assignment to vaccine or control) can result in selection bias. Moreover, because the set of individuals who would become…

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Likelihood-Based Inference on Haplotype Effects in Genetic Association Studies

遗传关联研究中单倍型效应的似然推断

A haplotype is a specific sequence of nucleotides on a single chromosome. The population associations between haplotypes and disease phenotypes provide critical information about the genetic basis of complex human diseases. Standard genotyping techniques cannot distinguish the two homologous chromosomes of an individual, so only the unphased genotype (i.e., the combination of the two homologous haplotypes) is directly observable. Statistical inference about…

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Clustering Categorical Data Based on Distance Vectors

基于距离向量的分类数据聚类

We introduce a novel statistical procedure for clustering categorical data based on Hamming distance (HD) vectors. The proposed method is conceptually simple and computationally straightforward, because it does not require any specific statistical models or any convergence criteria. Moreover, unlike most currently existing algorithms that compute the class membership or membership probability for every data point at each iteration, our algorithm sequentially extracts…

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Testing a Parametric Model Against a Nonparametric Alternative with Identification Through Instrumental Variables

工具变量识别下参数模型相对于非参数备择的检验

This paper is concerned with inference about a function g that is identified by a conditional moment restriction involving instrumental variables. The paper presents a test of the hypothesis that g belongs to a finite-dimensional parametric family against a nonparametric alternative. The test does not require nonparametric estimation of g and is not subject to the ill-posed inverse problem of nonparametric instrumental variables estimation. Under mild conditions, the test is…

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Identification and Inference in Nonlinear Difference-in-Differences Models

非线性双重差分模型的识别与推断

This paper develops a generalization of the widely used difference-in-differences method for evaluating the effects of policy changes. We propose a model that allows the control and treatment groups to have different average benefits from the treatment. The assumptions of the proposed model are invariant to the scaling of the outcome. We provide conditions under which the model is nonparametrically identified and propose an estimator that can be applied using either repeated…

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GENERALIZATION OF A RESULT ON “REGRESSIONS, SHORT AND LONG”

“短回归与长回归”结果的推广

This paper is concerned with the problem of combining a data set that identifies the conditional distribution P(y|x) with one that identifies the conditional distribution P(z|x) to identify the regressions E(y|x,·) ≡ [E(y|x,z = j),j ∈ Z] when the conditional distribution P(y|x,z) is unknown. Cross and Manski (2002, Econometrica 70, 357–368) studied this problem and showed that the identification region of E(y|x,·) can be precisely calculated when y has finite support. Here…

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NONPARAMETRIC STUDY OF SOLUTIONS OF DIFFERENTIAL EQUATIONS

微分方程解的非参数研究

The solution of differential equations lies at the heart of many problems in structural economics. In econometrics the general nonparametric analysis of consumer welfare is historically the most obvious application, but there are also many applications in finance and other fields. This work considers the general nonparametric form for these problems and identification conditions. It derives a kernel-based estimator and shows consistency and asymptotic normality.In…

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GMM with Many Moment Conditions

多矩条件下的广义矩估计

This paper provides a first order asymptotic theory for generalized method of moments (GMM) estimators when the number of moment conditions is allowed to increase with the sample size and the moment conditions may be weak. Examples in which these asymptotics are relevant include instrumental variable (IV) estimation with many (possibly weak or uninformed) instruments and some panel data models covering moderate time spans and with correspondingly large numbers of…

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Multivariate GARCH models: a survey

多变量 GARCH 模型综述

Abstract This paper surveys the most important developments in multivariate ARCH‐type modelling. It reviews the model specifications and inference methods, and identifies likely directions of future research. Copyright © 2006 John Wiley & Sons, Ltd.

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Can the strengths of AIC and BIC be shared? A conflict between model indentification and regression estimation

能否兼得 AIC 与 BIC 的优势?模型识别与回归估计的冲突

A traditional approach to statistical inference is to identify the true or best model first with little or no consideration of the specific goal of inference in the model identification stage. Can the pursuit of the true model also lead to optimal regression estimation? In model selection, it is well known that BIC is consistent in selecting the true model, and AIC is minimax-rate optimal for estimating the regression function. A recent promising direction is adaptive model…

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Bivariate current status data with univariate monitoring times

单一监测时间下的双变量现时状态数据

For bivariate current status data with univariate monitoring times, the identifiable part of the joint distribution is three univariate cumulative distribution functions, namely the two marginal distributions and the bivariate cumulative distribution function evaluated on the diagonal. We show that smooth functionals of these univariate cumulative distribution functions can be efficiently estimated with easily computed nonparametric maximum likelihood estimators based on…

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Data tracking and the understanding of Bayesian consistency

数据追踪与贝叶斯一致性的理解

We deal with strong consistency for Bayesian density estimation. An awkward consequence of inconsistency is described. It is pointed out that consistency at some density f0 depends on the prior mass assigned to the ‘pathological’ set of those densities that are close to f0, in a weak sense, and far apart from f0, in a Hellinger sense. An analysis of these sets leads to the identification of the notion of ‘data tracking’. Specific examples in which this phenomenon cannot…

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Nonparametric maximum likelihood estimation of the structural mean of a sample of curves

曲线样本结构均值的非参数最大似然估计

A random sample of curves can be usually thought of as noisy realisations of a compound stochastic process X(t) = Z{W(t)}, where Z(t) produces random amplitude variation and W(t) produces random dynamic or phase variation. In most applications it is more important to estimate the so-called structural mean μ(t) = E{Z(t)} than the crosssectional mean E{X(t)}, but this estimation problem is difficult because the process Z(t) is not directly observable. In this paper we propose…

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Nonparametric methods for inference in the presence of instrumental variables

存在工具变量时的非参数推断方法

We suggest two nonparametric approaches, based on kernel methods and orthogonal series to estimating regression functions in the presence of instrumental variables. For the first time in this class of problems, we derive optimal convergence rates, and show that they are attained by particular estimators. In the presence of instrumental variables the relation that identifies the regression function also defines an ill-posed inverse problem, the “difficulty” of which depends…

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Identification of multitype branching processes

多类型分枝过程的识别

We solve the problem of constructing an asymptotic global confidence region for the means and the covariance matrices of the reproduction distributions involved in a supercritical multitype branching process. Our approach is based on a central limit theorem associated with a quadratic law of large numbers performed by the maximum likelihood or the multidimensional Lotka–Nagaev estimator of the reproduction law means. The extension of this approach to the least squares…

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Linear Unmixing of Multivariate Observations

多变量观测的线性解混

In many fields of science there are multivariate observations that may be assumed to be generated by a (physical) linear mixing process of contributions from different sources. If the compositions of the sources are constant for different observations, then these observations are, up to a random error term, nonnegative linear combinations of a fixed set of so-called “source profiles” that characterize the sources. The goal of linear unmixing is to recover both the source…

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Periodically expanding discounted debt: a threat to fiscal policy sustainability?

周期性扩张的贴现债务是否威胁财政政策可持续性?

Abstract This paper models the behaviour of discounted US debt using a Markov‐switching time series model. The significance of modelling fiscal policy within this framework derives from the implications it has for long‐term sustainability. The two‐regime framework used in this paper identifies periods where the present value of US Federal debt is expanding versus periods when it is collapsing. Using an updated data series from Hamilton and Flavin ( 1986 ), a test is…

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Behavioral Identification in Coalitional Bargaining: An Experimental Analysis of Demand Bargaining and Alternating Offers

联盟议价中的行为识别:要价议价与交替出价的实验分析

Alternating-offer and demand bargaining models of legislative bargaining make very different predictions in terms of both ex ante and ex post distribution of payoffs, as well as in the role of the order of play. The experiment shows that actual bargaining behavior is not as sensitive to the different bargaining rules as the theoretical point predictions, whereas the comparative statics are in line with both models. We compare our results to studies that attempt to…

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Unbundling Institutions

This paper evaluates the importance of "property rights institutions," which protect citizens against expropriation by the government and powerful elites, and "contracting institutions," which enable private contracts between citizens. We exploit exogenous variation in both types of institutions driven by colonial history and document strong first‐stage relationships between property rights institutions and the determinants of European colonization strategy (settler…

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Estimation and Testing of Forecast Rationality under Flexible Loss

灵活损失函数下预测理性的估计与检验

In situations where a sequence of forecasts is observed, a common strategy is to examine "rationality" conditional on a given loss function. We examine this from a different perspective—supposing that we have a family of loss functions indexed by unknown shape parameters, then given the forecasts can we back out the loss function parameters consistent with the forecasts being rational even when we do not observe the underlying forecasting model? We establish identification…

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The Hedonic Regression Time-Dummy Method and the Monotonicity Axioms

特征价格回归时间虚拟变量法与单调性公理

This article demonstrates that the well-known and much applied hedonic regression time-dummy method, used to construct quality-adjusted price indexes, fails the monotonicity axioms from index theory. The article outlines the hedonic time-dummy method and defines the monotonicity axioms in this context. A simple numerical example is used to illustrate the failure of monotonicity. The reasons for this failure are identified and discussed. The frequency of the violation of…

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Likelihood ratio tests in curved exponential families with nuisance parameters present only under the alternative

存在仅在备择下可识别的干扰参数时,曲指数族中的似然比检验

For submodels of an exponential family, we consider likelihood ratio tests for hypotheses that render some parameters nonidentifiable. First, we establish the asymptotic equivalence between the likelihood ratio test and the score test. Secondly, the score-test representation is used to derive the asymptotic distribution of the likelihood ratio test. These results are derived for general submodels of an exponential family without assuming compactness of the parameter space.…

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