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平滑非参数条件分位数前沿估计AI 解读

Traditional estimators for nonparametric frontier models (DEA, FDH) are very sensitive to extreme values/outliers. Recently, Aragon et al. [2005. Nonparametric frontier estimation: a conditional quantile-based approach. Econometric Theory 21, 358-389] proposed a nonparametric [alpha]-frontier model and estimator based on a suitably defined conditional quantile which is more robust to extreme values/outliers. Their estimator is based on a nonsmooth empirical conditional…

误设下线性理性预期模型估计量的偏差AI 解读

Most rational expectations models involve equations in which the dependent variable is a function of its lags and its expected future value. We investigate the asymptotic bias of generalized method of moment (GMM) and maximum likelihood (ML) estimators in such models under misspecification. We consider several misspecifications, and focus more specifically on the case of omitted dynamics in the dependent variable. In a stylized DGP, we derive analytically the asymptotic…

长期风险与收益的权衡AI 解读

Excess market returns are correlated with past market variance. This dependence is statistically mild at short horizons (thereby leading to a hard-to-detect risk-return trade-off, as in the existing literature) but increases with the horizon and is strong in the long run (i.e., between 6 and 10 years). From an econometric standpoint, we find that the long-run predictive power of past market variance is robust to the statistical properties of long-horizon stock-return…

高维加性模型中半参数函数的贝叶斯识别、选择与估计AI 解读

In this paper we propose an approach to both estimate and select unknown smooth functions in an additive model with potentially many functions. Each function is written as a linear combination of basis terms, with coefficients regularized by a proper linearly constrained Gaussian prior. Given any potentially rank deficient prior precision matrix, we show how to derive linear constraints so that the corresponding effect is identified in the additive model. This allows for the…

具有内生状态转换的马尔可夫状态转换回归模型估计AI 解读

Following Hamilton [1989. A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica 57, 357-384], estimation of Markov regime-switching regressions typically relies on the assumption that the latent state variable controlling regime change is exogenous. We relax this assumption and develop a parsimonious model of endogenous Markov regime-switching. Inference via maximum likelihood estimation is possible with relatively minor…

条件异方差波动下利用小波平滑检测收益变化AI 解读

In this paper, we propose two estimators, an integral estimator and a discretized estimator, for the wavelet coefficient of regression functions in nonparametric regression models with heteroscedastic variance. These estimators can be used to test the jumps of the regression function. The model allows for lagged-dependent variables and other mixing regressors. The asymptotic distributions of the statistics are established, and the asymptotic critical values are analytically…

与最优总体的边际比较及效率测度问题AI 解读

Consider a set of N populations ranked by an unknown scalar parameter, where a larger parameter value is better. An existing procedure, multiple comparisons with the best, constructs a set of upper and lower bounds for the N – 1 differences between the parameter value of the best population and the other populations, where these bounds hold jointly with a given probability. This article constructs the corresponding upper and lower bounds that hold marginally (for a single…

克伦威尔法则与经济意义度量中的先验作用AI 解读

We show that using Bayesian decision theory to draw inference about the economic significance of a model requires careful specification of model uncertainty in the prior density. As an example, we use the Bayesian investor's portfolio allocation problem to show that failure to include probability point mass on the null hypothesis that returns are not predictable will overstate the economic significance of the predictive model. The dissonance between the statistical and…

基于模拟的扩散过程模型设定检验AI 解读

This article makes two contributions. First, we outline a simple simulation-based framework for constructing conditional distributions for multifactor and multidimensional diffusion processes, for the case where the functional form of the conditional density is unknown. The distributions can be used, for example, to form predictive confidence intervals for time period t + τ, given information up to period t. Second, we use the simulation-based approach to construct a test…

真实还是伪长记忆？一种新检验AI 解读

It is well known that long memory characteristics observed in data can be generated by nonstationary structural-break or slow regime switching models. We propose a statistical test to distinguish between true long memory and spurious long memory based on invariance of the long memory parameter for temporal aggregates of the process under the null of true long memory. Geweke Porter-Hudak estimates of the long memory parameter obtained from different temporal aggregates of the…

利用宏观数据改善微观预测AI 解读

We consider the problem of combining forecasts from two different levels (called “macro” and “micro”), where we have access to the forecasts and their precisions but not to the full data set. We develop a theoretical framework and provide Monte Carlo evidence in the cases of both perfect and imperfect aggregation. Our proposed procedure is simple and robust. We also extend the procedure to time series and propose a forecast model for the European zero rates, combining…

均值矩阵的自适应估计：总体最小二乘与总体收缩AI 解读

An unknown constant matrix M is observed with additive random error. The basic problem considered is to devise an estimator of M that trades off bias against variance so as to achieve relatively low quadratic risk. This paper develops an adaptive total least squares estimator and an adaptive total shrinkage estimator of M that minimize estimated risk over certain large classes of linear estimators. It is shown that the asymptotic risk of the adaptive total least squares…

回归模型中平均风险的最小化AI 解读

Most model selection mechanisms work in an “overall” modus, providing models without specific concern for how the selected model is going to be used afterward. The focused information criterion (FIC), on the other hand, is geared toward optimum model selection when inference is required for a given estimand. In this paper the FIC method is extended to weighted versions. This allows one to rank and select candidate models for the purpose of handling a range of similar tasks…

基于广义错误率的形式化数据窥探处理AI 解读

It is common in econometric applications that several hypothesis tests are carried out simultaneously. The problem then becomes how to decide which hypotheses to reject, accounting for the multitude of tests. The classical approach is to control the familywise error rate (FWE), which is the probability of one or more false rejections. But when the number of hypotheses under consideration is large, control of the FWE can become too demanding. As a result, the number of false…

近奇异设计下的收缩估计AI 解读

Shrinkage estimation procedures such as ridge regression and the lasso have been proposed for stabilizing estimation in linear models when high collinearity exists in the design. In this paper, we consider asymptotic properties of shrinkage estimators in the case of “nearly singular” designs.I thank Hannes Leeb and Benedikt Pötscher and also the referees for their valuable comments. This research was supported by a grant from the Natural Sciences and Engineering Research…

能否估计模型选择后估计量的无条件分布？AI 解读

We consider the problem of estimating the unconditional distribution of a post-model-selection estimator. The notion of a post-model-selection estimator here refers to the combined procedure resulting from first selecting a model (e.g., by a model-selection criterion such as the Akaike information criterion [AIC] or by a hypothesis testing procedure) and then estimating the parameters in the selected model (e.g., by least squares or maximum likelihood), all based on the same…

从临时派遣工作到永久就业：匹配估计及其敏感性AI 解读

Abstract The diffusion of temporary work agency (TWA) jobs has led to a harsh policy debate and ambiguous empirical evidence. Results for the USA, based on quasi‐experimental evidence, suggest that a TWA assignment decreases the probability of finding a stable job, while results for Europe, based on the conditional independence assumption (CIA), typically reach opposite conclusions. Using data for two Italian regions, we rely on a matching estimator to show that TWA…

从受污染数据中推断残障状态AI 解读

Abstract In light of widespread concerns about the reliability of self‐reported disability, we investigate what can be learned about the prevalence of work disability under various assumptions on the reporting error process. Developing a nonparametric bounding framework, we provide tight inferences under our strongest assumptions but then find that identification deteriorates rapidly as the assumptions are relaxed. For example, we find that inferences are highly sensitive to…

统计推断要义AI 解读

(2008). Essentials of Statistical Inference. Journal of the American Statistical Association: Vol. 103, No. 481, pp. 425-426.

相关与协方差矩阵的惩罚正态似然和岭正则化AI 解读

High dimensionality causes problems in various areas of statistics. A particular situation that rarely has been considered is the testing of hypotheses about multivariate regression models in which the dimension of the multivariate response is large. In this article a ridge regularization approach is proposed in which either the covariance or the correlation matrix is regularized to ensure nonsingularity irrespective of the dimensionality of the data. It is shown that the…

通过序贯检验一致改进 Bonferroni 类检验AI 解读

We propose a new method to uniformly improve cutoff tests (as, e.g., the Bonferroni test) by replacing them with a sequential testing procedure. The proposed procedure provides a uniform improvement—that is, it rejects the null hypothesis at least in all cases where the original procedure does, has level α, and never requires a sample size larger than that of the original procedure. Information on the often-unknown joint distribution of the test statistics across the…

生存结局下预后生物标志物的时间依赖预测值AI 解读

In a prospective cohort study, information on clinical parameters, tests and molecular markers is often collected. Such information is useful to predict patient prognosis and to select patients for targeted therapy. We propose a new graphical approach, the positive predictive value (PPV) curve, to quantify the predictive accuracy of prognostic markers measured on a continuous scale with censored failure time outcome. The proposed method highlights the need to consider both…

配对病例对照研究中条件似然与随机效应似然的等价性AI 解读

Two approaches dominate the analysis of highly stratified data sets: use of conditional likelihood and random-effects models. Conditioning is more traditional and has attractive robustness properties. Contemporary random-effects approaches rely more on accurate assumptions but can be applied to a larger class of problems. For pair-matched studies with arbitrary numbers of categorical covariates, we reconcile these two approaches, showing that the conditional approach has an…

热带非洲罗阿丝虫患病率的二元二项空间建模AI 解读

We present a state-of-the-art application of smoothing for dependent bivariate binomial spatial data to Loa loa prevalence mapping in West Africa. This application starts with the nonspatial calibration of survey instruments, continues with the spatial model building and assessment, and ends with robust, tested software intended for use by field workers for online prevalence map updating. From a statistical perspective, we address several important methodological issues:…