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非经典测量误差下参数估计的界限AI 解读

The bias introduced by errors in the measurement of independent variables has increasingly been a topic of interest among researchers estimating economic parameters. However, studies typically use the assumption of classical measurement error; that is, the variable of interest and its measurement error are uncorrelated, and the expected value of the mismeasured variable is equal to the expected value of the true measure. These assumptions often arise from convenience rather…

弱识别下的广义矩估计AI 解读

This paper develops asymptotic distribution theory for GMM estimators and test statistics when some or all of the parameters are weakly identified. General results are obtained and are specialized to two important cases: linear instrumental variables regression and Euler equations estimation of the CCAPM. Numerical results for the CCAPM demonstrate that weak-identification asymptotics explains the breakdown of conventional GMM procedures documented in previous Monte Carlo…

存在误分类的二元选择模型识别AI 解读

Misclassification in binary choice (binomial response) models occurs when the dependent variable is measured with error, that is, when an actual “one” response is sometimes recorded as a zero and vice versa. This paper shows that binary response models with misclassification are semiparametrically identified, even when the probabilities of misclassification depend in unknown ways on model covariates and the distribution of the errors is unknown.

加性非线性 ARX 时间序列的非参数估计：局部线性拟合与投影AI 解读

We consider the estimation and identification of the components (endogenous and exogenous) of additive nonlinear ARX time series models. We employ a local polynomial fitting scheme coupled with projections. We establish the weak consistency (with rates) and the asymptotic normality of the projection estimates of the additive components. Expressions for the asymptotic bias and variance are given.

EM估计的标准误AI 解读

Summary The EM algorithm is a popular method for computing maximum likelihood estimates. One of its drawbacks is that it does not produce standard errors as a by-product. We consider obtaining standard errors by numerical differentiation. Two approaches are considered. The first differentiates the Fisher score vector to yield the Hessian of the log-likelihood. The second differentiates the EM operator and uses an identity that relates its derivative to the Hessian of the…

摘要暂缺

含滞后因变量的面板离散选择模型AI 解读

In this paper, we consider identification and estimation in panel data discrete choice models when the explanatory variable set includes strictly exogenous variables, lags of the endogenous dependent variable as well as unobservable individual-specific effects. For the binary logit model with the dependent variable lagged only once, Chamberlain (1993) gave conditions under which the model is not identified. We present a stronger set of conditions under which the parameters…

单调工具变量：教育回报的应用AI 解读

Econometric analyses of treatment response commonly use instrumental variable (IV) assumptions to identify treatment effects.Yet the credibility of IV assumptions is often a matter of considerable disagreement.There is therefore good reason to consider weaker but more credible assumptions.To this end, we introduce monotone instrumental variable (MIV) assumptions and the important special case of monotone treatment selection (MTS).We study the identifying power of MIV…

联立方程模型中工具变量估计量的解释：鱼类需求的应用AI 解读

In markets where prices are determined by the intersection of supply and demand curves, standard identification results require the presence of instruments that shift one curve but not the other. These results are typically presented in the context of linear models with fixed coefficients and additive residuals. The first contribution of this paper is an investigation of the consequences of relaxing both the linearity and the additivity assumption for the interpretation of…

基于拟似然的多变点拟合及其 DNA 序列分段应用AI 解读

We consider situations where a step function with a variable number of steps provides an adequate model for a regression relationship, while the variance of the observations depends on their mean. This model provides for discontinuous jumps at changepoints and for constant means and error variances in between changepoints. The basic statistical problem consists of identification of the number of changepoints, their locations and the levels the function assumes in between. We…

摘要暂缺

结合倾向得分匹配与预后协变量的额外调整AI 解读

Propensity score matching refers to a class of multivariate methods used in comparative studies to construct treated and matched control samples that have similar distributions on many covariates. This matching is the observational study analog of randomization in ideal experiments, but is far less complete as it can only balance the distribution of observed covariates, whereas randomization balances the distribution of all covariates, both observed and unobserved. An…

第一价格拍卖中的最优非参数估计AI 解读

This paper proposes a general approach and a computationally convenient estimation procedure for the structural analysis of auction data. Considering first-price sealed-bid auction models within the independent private value paradigm, we show that the underlying distribution of bidders' private values is identified from observed bids and the number of actual bidders without any parametric assumptions. Using the theory of minimax, we establish the best rate of uniform…

摘要暂缺

不完整面板下的联立方程估计AI 解读

This paper compares the performance of several single and system estimators of a two equation simultaneous model with unbalanced panel data. The Monte Carlo design varies the degree of unbalancedness in the data and the variance components ratio due to the individual effects. One useful result for applied researchers is that the feasible error components 2SLS and 3SLS procedures based on simple ANOVA type estimators of the variance components perform well with incomplete…

现状数据的不可识别性与非信息性删失AI 解读

The event times and examination times that produce current status data are typically assumed to be independent. Here, an increasing sequence of nested models is considered for current status data, namely independence models, 'constant sum' models and models for which the conditional probability of the occurrence of the event prior to the examination time, given the examination time, is nondecreasing in the examination time. In the class of constant sum models, the…

相关残差下单因子模型的识别AI 解读

A necessary and sufficient condition for the identification of a single-factor model with correlated residuals is derived by studying the zero elements of their concentration matrix. In particular the new condition is expressed in terms of the complementary graph of the residuals. This graphical condition can be simply checked by means of an efficient algorithm. An example is also given showing that sometimes the single-factor model with correlated residuals can be sued to…

稀有事件生存数据的一类加权对数秩检验AI 解读

In many epidemiological and medical follow-up studies, a majority of study subjects do not experience the event of interest during the follow-up period. An important example is the ongoing prostate, lung, colorectal, and ovarian cancer Screening trial of the National Cancer Institute. In such a situation, the widely used Gp family of weighted log-rank statistics essentially reduces to the special case of the (unweighted) log-rank statistics. We propose a simple modification…

协变量和结局缺失的随机实验非参数分析AI 解读

Analysis of randomized experiments with missing covariate and outcome data is problematic, because the population parameters of interest are not identified unless one makes untestable assumptions about the distribution of the missing data. This article shows how population parameters can be bounded without making untestable distributional assumptions. Bounds are also derived under the assumption that covariate data are missing completely at random. In each case the bounds…

稀有事件生存数据的一类加权对数秩检验AI 解读

In many epidemiological and medical follow-up studies, a majority of study subjects do not experience the event of interest during the follow-up period. An important example is the ongoing prostate, lung, colorectal, and ovarian cancer Screening trial of the National Cancer Institute. In such a situation, the widely used Gp family of weighted log-rank statistics essentially reduces to the special case of the (unweighted) log-rank statistics. We propose a simple modification…

《基于模拟的计量经济学方法》书评AI 解读

The accessibility of high-performance computing power has always influenced theoretical and applied econometrics. Gouriéroux and Monfort begin their recent offering, Simulation-Based Econometric Methods , with a stylized three-stage classification of the history of statistical econometrics. In the first stage, lasting through the 1960's, models and estimation methods were designed to produce closed-form expressions for the estimators. This spurred thorough investigation of…

二元失效时间数据的一类加权依赖度量AI 解读

Summary This paper considers a class of summary measures of the dependence between a pair of failure time variables over a finite follow-up region. The class consists of measures that are weighted averages of local dependence measures, and includes the cross-ratio-measure and finite region version of Kendall's τ; recently proposed by the authors. Two new special cases are identified that can avoid the need to estimate the bivariate survivor function and that admit explicit…

潜在可分性：不依赖弱可分性的商品分组AI 解读

This paper develops a new concept of separability with overlapping groups. This is shown to provide a useful empirical and theoretical framework for investigating the grouping of goods and prices. It is a generalisation of weak separability in which goods are allowed to enter more than one group and where the composition of groups is identified by the choice of group specific exclusive goods. For the Almost Ideal and Translog demand models and their generalisations, we…

识别股票收益中的牛市与熊市AI 解读

This article uses a Markov-switching model that incorporates duration dependence to capture non-linear structure in both the conditional mean and the conditional variance of stock returns. The model sorts returns into a high-return stable state and a low-return volatile state. We label these as bull and bear markets, respectively. The filter identifies all major stock-market downturns in over 160 years of monthly data. Bull markets have a declining hazard function although…